
@article{
Aguilar2002,
   Author = {Aguilar, A. and Borrell, A. and Reijnders, P. J. H. },
   Title = {Geographical and temporal variation in levels of organochlorine contaminants in marine mammals},
   Journal = {Marine Environmental Research},
   Volume = {53},
   Pages = {425-452},
      Year = {2002} }




@article{
Akcakayaetal2003,
   Author = {Akcakaya, H. R. and Halley, J. M. and Inchausti, P.},
   Title = {Population-level mechanisms for reddened spectra in ecological time series},
   Journal = {Journal of Animal Ecology},
   Volume = {72},
   Number = {4},
   Pages = {698-702},
   Abstract = {1. The temporal variability of many animal populations increases with the length of census period. This pattern is associated with the reddened spectral colour, quantified by the spectral exponent, which is typically around + 1. 2. We used simulation models to explore the effects of various population-level processes on the spectral colour of the simulated time series of abundances. 3. Our results showed that the observed spectral exponents could be explained as the effect of a combination of measurement error and natural variability (in the form of white environmental noise). 4. Thus, it may not be necessary to invoke complex varieties of environmental noise to explain the observed spectral exponents.},
      Year = {2003} }




@article{
Alilietal2005,
   Author = {Alili, L. and Patie, P. and Pedersen, J. L.},
   Title = {Representations of the first hitting time density of an Ornstein-Uhlenbeck process},
   Journal = {Stochastic Models},
   Volume = {21},
   Pages = {967-980},
      Year = {2005} }




@article{
Allen2003,
   Author = {Allen, Linda J. S.},
   Title = {Risk of population extinction due to demographic stochasticity in population models},
   Journal = {Comments on Theoretical Biology },
   Volume = {8},
   Pages = {433 - 454},
   Abstract = {The risk of population extinction in stochastic models due to demographic variation is reviewed in some basic population models. Theoretical results pertaining to the probability of population extinction and expected time to extinction in discrete and continuous-time Markov chain models are presented along with some numerical examples illustrating these results. We begin with the simplest type of stochastic population model, the exponential growth model, then discuss the logistic growth model, a model with an Allee effect, and a spatially implicit metapopulation model. All of these stochastic models are continuous in time, but the state space is discrete. It is shown that similar methods of analysis apply to all of these models. In addition, some nonlinear structured models are considered. These models are formulated as branching processes, discrete-time Markov chain models. The extinction dynamics for all of these models are compared. 
},
      Year = {2003} }




@article{
Alverson1992,
   Author = {Alverson, D. L.},
   Title = {A review of commercial fisheries and the Steller sea lion (Eumetopias jubatus): the conflict arena},
   Journal = {Reviews in Aquatic Science},
   Volume = {6},
   Pages = {203-256},
      Year = {1992} }




@article{
AndersenDeacon2001,
   Author = {Andersen, M. E. and Deacon, J. E.},
   Title = {Population size of Devils Hole pupfish (Cyprinodon diabolis) correlates with water level},
   Journal = {Copeia},
   Volume = {2001},
   Pages = {224–228},
      Year = {2001} }




@article{
AndersonPiatt1999,
   Author = {Anderson, P. J. and Piatt, J. F.},
   Title = {Community reorganization in the Gulf of Alaska following ocean climate regime shift},
   Journal = {Marine Ecology Progress Series},
   Volume = {189},
   Pages = {117-123},
   Abstract = {A shift in ocean climate during the late 1970s triggered a reorganization of community structure in the Gulf of Alaska ecosystem, as evidenced in changing catch composition on long-term (1953 to 1997) small-mesh trawl surveys. Forage species such as pandalid shrimp and capelin declined because of recruitment failure and predation, and populations have not yet recovered. Total trawl catch biomass declined >50\% and remained low through the 1980s. In contrast, recruitment of high trophic-level groundfish improved during the 1980s, yielding a >250\% increase in catch biomass during the 1990s. This trophic reorganization apparently had negative effects on piscivorous sea birds and marine mammals. },
      Year = {1999} }




@book{
Andrewartha54,
   Author = {Andrewartha, H.G. and Birch, L.C.},
   Title = {The Distribution and Abundance of Animals},
   Publisher = {The University of Chicago Press},
   Address = {Chicago},
      Year = {1954} }




@techreport{
AnglissOutlaw2005,
   Author = {Angliss, R.P. and Outlaw, R. B.},
   Title = {Alaska marine mammal stock assessments, 2005},
   Institution = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-161},
   Number = {NMFS-AFSC-161},
      Year = {2005} }




@book{
Aoki1987,
   Author = {Aoki, M.},
   Title = {State space modeling of time series},
   Publisher = {Springer},
   Address = {New York},
      Year = {1987} }




@article{
ArinoPimm1995,
   Author = {Ari\~{n}o, A. and Pimm, S.},
   Title = {On the nature of population extremes},
   Journal = {Evolutionary Ecology},
   Volume = {9},
   Pages = {423-443},
      Year = {1995} }




@article{
Baconetal1999,
   Author = {Bacon, Corinne E. and Jarman, Walter M. and Estes, James A. and Simon, Mary and Norstrom, Ross J.},
   Title = {Comparison of organochlorine contaminants among sea otter (Enhydra lutris) populations in California and Alaska},
   Journal = {Environmental Toxicology and Chemistry},
   Volume = {18},
   Pages = {452–458},
      Year = {1999} }




@incollection{
Bairlein1991,
   Author = {Bairlein, F.},
   Title = {Population studies of white storks (Ciconia ciconia) in Europe},
   BookTitle = {Bird population studies: relevance to conservation and management},
   Editor = {Perrins, C. M. and Lebreton, J. D. and Hirons, G. J. M.},
   Publisher = {Oxford University Press},
   Address = {Oxford},
   Pages = {207–229},
      Year = {1991} }




@inproceedings{
Baker1983,
   Author = {Baker, W. W. },
   Title = {The decline and extirpation of a population of red-cockaded woodpeckers in northwest Florida},
   BookTitle = {Red-cockaded Woodpecker Symposium II},
   Editor = {Wood, D. A.},
   Address= {Tallahassee, Florida},
   Publisher = {Florida State Game and Fresh Water Fish Comm.},
   Pages = {44-45},
      Year = {1983} }




@article{
Barronetal2003,
   Author = {Barron, M. G. and Heintz, R. and Krahn, M. M.},
   Title = {Contaminant exposure and effects in pinnipeds: implications for Steller sea lion declines in Alaska},
   Journal = {The Science of the Total Environment},
   Volume = {311},
   Pages = {111-133},
      Year = {2003} }




@incollection{
Becker1991,
   Author = {Becker, P. H.},
   Title = {Population and contamination studies in coastal birds: The common tern Sterna hirundo},
   BookTitle = {Bird population studies: Relevance to conservation and management},
   Editor = {Perrins, C. M. and Lebreton, J. D. and Hirons, G. J. M.},
   Publisher = {Oxford University Press},
   Address = {Oxford},
   Pages = {433–460},
      Year = {1991} }




@book{
BeissingerMcCullough2002,
   Author = {Beissinger, S. R. and McCullough, D. R.},
   Title = {Population viability analysis},
   Publisher = {University of Chicago Press},
   Address = {Chicago},
      Year = {2002} }




@article{
BeissingerWestphal1998,
   Author = {Beissinger, S. R. and Westphal, M. I.},
   Title = {On the use of demographic models of population viability in endangered species management},
   Journal = {Journal of Wildlife Management},
   Volume = {62},
   Number = {3},
   Pages = {821-841},
      Year = {1998} }




@article{
BengtsonSiniff1981,
   Author = {Bengtson, J. L. and Siniff, D. B.},
   Title = {Reproductive aspects of female crabeater seals (Lobodon carcinophagus) along the Antarctic Peninsula},
   Journal = {Canadian Journal of Zoology},
   Volume = {59},
   Pages = {92-102},
      Year = {1981} }




@article{
BengtssonCavanaugh2006,
   Author = {Bengtsson, Thomas and Cavanaugh, Joseph E.},
   Title = {An improved {A}kaike information criterion for state-space model selection},
   Journal = {Computational Statistics and Data Analysis},
   Volume = {50},
   Number = {10},
   Pages = {2635-2654},
   Note = {0167-9473
doi: DOI: 10.1016/j.csda.2005.05.003},
   Keywords = {AIC
Kullback-Leibler information
Kullback's directed divergence
State-space model
Time series analysis},
   Year = {2006} }




@article{
Bennettsetal1999,
   Author = {Bennetts, R. E. and Link, W. A. and Sauer, J. R. and P. W. Sykes, Jr.},
   Title = {Factors influencing counts in an annual survey of snail kites in Florida},
   Journal = {Auk},
   Volume = {116},
   Pages = {316–323},
      Year = {1999} }




@article{
BensonTrites2002,
   Author = {Benson, A. J. and Trites, A. W.},
   Title = {Ecological effects of regime shifts in the Bering Sea and eastern North Pacific Ocean},
   Journal = {Fish and Fisheries},
   Volume = {3},
   Pages = {95-113},
      Year = {2002} }




@article{
Besbeasetal2002,
   Author = {Besbeas, P. and Freeman, S. N. and Morgan, B. J. T. and Catchpole, E. A.},
   Title = {Integrating mark-recapture recovery and census data to estimate animal abundance and demographic parameters},
   Journal = {Biometrics},
   Volume = {58},
   Pages = {540–547},
      Year = {2002} }




@article{
Bickhametal1996,
   Author = {Bickham, J. W. and Patton, J. C. and Loughlin, T. R.},
   Title = {High variability for control-region sequences in a marine mammal: implications for conservation and biogeography of Steller sea lions (Eumetopias jubatus)},
   Journal = {Journal of Mammalogy},
   Volume = {77},
   Pages = {95-108},
      Year = {1996} }




@article{
Biernackietal2003,
   Author = {Biernacki, Christophe and Celeux, Gilles and Govaert, Gérard},
   Title = {Choosing starting values for the {EM} algorithm for getting the highest likelihood in multivariate Gaussian mixture models},
   Journal = {Computational Statistics and Data Analysis},
   Volume = {41},
   Number = {3-4},
   Pages = {561-575},
   Keywords = {Classification EM
EM algorithm
Initialization strategies
Multivariate Gaussian mixture
Optimization
Stochastic EM},
   Year = {2003} }




@book{
Bolker2008,
   Author = {Bolker, Benjamin M.},
   Title = {Ecological models and data in R},
   Publisher = {Princeton University Press},
   Address = {Princeton, NJ},
      Year = {2008} }




@Manual{
Borman2009,
   Author = {Borman, Sean},
   Title = {The Expectation Maximization Algorithm - A short tutorial},
   Url = {http://www.seanborman.com/publications/EM_algorithm.pdf},
   Year = {2009} }



@article{
BorrellReijnders1999,
   Author = {Borrell, A. and Reijnders, P. J. H.},
   Title = {Summary of temporal trends in pollutant levels observed in marine mammals},
   Journal = {Journal of Cetacean Research and Management},
   Volume = {1},
   Pages = {149-157},
      Year = {1999} }




@article{
Bowenetal1981,
   Author = {Bowen, W. D. and Capstick, C. K. and Sergeant, D. E.},
   Title = {Temporal changes in the reproductive potential of female harp seals (Pagophilus groenlandicus)},
   Journal = {Canadian Journal of Fisheries and Aquatic Sciences},
   Volume = {38},
   Pages = {495-503},
      Year = {1981} }




@article{
Bowenetal2006,
   Author = {Bowen, W. D. and Iverson, S. J. and McMillan, J. I. and Boness, D. J.},
   Title = {Reproductive performance in grey seals: age-related improvement and senescence in a capital breeder },
   Journal = {Journal of Animal Ecology},
   Volume = {75},
   Number = {6},
   Pages = {1340-1351},
      Year = {2006} }




@article{
Boyce1992,
   Author = {Boyce, M. S.},
   Title = {Population viability analysis},
   Journal = {Annual Review of Ecology and Systematics},
   Volume = {23},
   Pages = {481-506},
      Year = {1992} }




@article{
Boyd1985,
   Author = {Boyd, I. L.},
   Title = {Pregnancy and ovulation rates in grey seals (Halichoerus gryus) in the British coast},
   Journal = {Journal of Zoology. Series A},
   Volume = {205},
   Pages = {265-272},
      Year = {1985} }




@article{
Boyd2000,
   Author = {Boyd, I. L.},
   Title = {State-dependent fertility in pinnipeds: contrasting capital and income breeders},
   Journal = {Functional Ecology},
   Volume = {14},
   Pages = {623–630},
      Year = {2000} }




@article{
Boydetal1995,
   Author = {Boyd, I. L. and Croxall, J. P. and Lunn, N. J. and Reid, K.},
   Title = {Population demography of Antarctic fur seals: the costs of reproduction and implications for life-histories},
   Journal = {Journal of Animal Ecology},
   Volume = {65},
   Pages = {505-518},
      Year = {1995} }




@article{
Brahametal1980,
   Author = {Braham, H. W. and Everitt, R. D. and Rugh, D. J.},
   Title = {Northern sea lion population decline in the eastern Aleutian Islands},
   Journal = {Journal of Wildlife Management},
   Volume = {44},
   Number = {1},
   Pages = {25-33},
      Year = {1980} }




@phdthesis{
Brandon2000,
   Author = {Brandon, E.A.A.},
   Title = {Maternal investment in Steller sea lions in Alaska},
   School = {Texas AM University},
   Type = {Ph.D. thesis},
      Year = {2000} }




@book{
BrockwellDavis1991,
   Author = {Brockwell, Peter J. and Davis, Richard A.},
   Title = {Time series: theory and methods},
   Publisher = {Springer-Verlag},
   Address = {New York, NY},
      Year = {1991} }




@article{
BrookKikkawa1998,
   Author = {Brook, B. W. and Kikkawa, J.},
   Title = {Examining threats faced by island birds: a population viability analysis on the Capricorn silvereye using long-term data},
   Journal = {Journal of Applied Ecology},
   Volume = {35},
   Pages = {491–503},
      Year = {1998} }




@article{
Brooketal2000,
   Author = {Brook, Barry W. and O'Grady, Julian J. and Chapman, Andrew P. and Burgman, Mark A. and Ak\c{c}akaya, H. Resit and Frankham, Richard},
   Title = {Predictive accuracy of population viability analysis in conservation biology},
   Journal = {Nature},
   Volume = {404},
   Pages = {385-387},
      Year = {2000} }




@article{
Brownetal2005,
   Author = {Brown, R. F. and Wright, B. E.  and Riemer, S. D. and Laake, J.},
   Title = {Trends in abundance and current status of harbor seals in Oregon:1977-2003},
   Journal = {Marine Mammal Science},
   Volume = {21},
   Pages = {657-670},
      Year = {2005} }




@phdthesis{
Bryant1998,
   Author = {Bryant, A. A.},
   Title = {Metapopulation ecology of Vancouver Island marmots (Marmota vancouverensis)},
   School = {University of Victoria},
   Type = {Ph.D.},
      Year = {1998} }




@article{
Bucklandetal2007,
   Author = {Buckland, Stephen T. and Newman, Ken B. and Fern´andez, Carmen and Thomas, Len and Harwood, John},
   Title = {Embedding population dynamics models in inference},
   Journal = {Statistical Science},
   Volume = {22},
   Pages = {44–58},
      Year = {2007} }




@article{
Bucklandetal2004,
   Author = {Buckland, S. T. and Newman, K. B. and Thomas, L. and Koesters, N. B.},
   Title = {State-space models for the dynamics of wild animal populations},
   Journal = {Ecological Modelling},
   Volume = {171},
   Pages = {157-175},
      Year = {2004} }




@techreport{
BurbidgeKuchling2004,
   Author = {Burbidge, Andrew A and Kuchling, Gerald},
   Title = {Western swamp tortoise recovery plan},
   Institution = {Department of Conservation and Land Management, Perth, Australia},
      Year = {2004} }




@techreport{
BWDC2003,
   Author = {Bureau of Wildlife Diversity Conservation},
   Title = {Bald eagle population monitoring (project 92912501000)},
   Institution = {Bureau of Wildlife Diversity Conservation, Gainesville, FL},
   Type = {Annual study progress report},
      Year = {2003} }




@article{
Bureketal2005,
   Author = {Burek, K. A. and Gulland, F. M.D. and Sheffield, G. and Beckmen, K. B. and Keyes, E. and Spraker, T. R. and Smith, A. W. and Skilling, D. E. and Evermann, J. F. and Stott, J. L. and Saliki, J. T. and Trites, A. W.},
   Title = {Infectious disease and the decline of Steller sea lions (Eumetopias jubatus) in Alaska, USA: Insights from serological data},
   Journal = {Journal of Wildlife Diseases},
   Volume = {41},
   Pages = {512-524},
      Year = {2005} }




@article{
Burn2004,
   Author = {Burn, D. M.},
   Title = {Endangered and threatened wildlife and plants; listing the southwest Alaska distinct population segment of the northern sea otter (Enhydra lutris kenyoni) as threatened},
   Journal = {Federal Register},
   Volume = {69},
   Number = {28},
   Pages = {6600-6621},
      Year = {2004} }




@book{
BurnhamAnderson2002,
   Author = {Burnham, K. P. and Anderson, D. R.},
   Title = {Model selection and multimodel inference},
   Publisher = {Springer Science+Business Media, Inc.},
   Address = {New York, New York},
   Edition = {2nd},
      Year = {2002} }




@book{
BurnhamAnderson2002,
   Author = {Burnham, K. P. and Anderson, D. R.},
   Title = {Model selection and multi-model inference},
   Publisher = {Springer Publishing},
   Address = {New York, NY},
      Year = {2002} }




@techreport{
Byrd2005,
   Author = {Byrd, Vernon},
   Title = {Is the pelagic distribution of seabirds in the Bering Sea driven by climate change? A retrospective analysis},
      Year = {2005} }




@article{
Cabot1996,
   Author = {Cabot, D.},
   Title = {Performance of the roseate tern population breeding in North-West Europe — Ireland, Britain and France, 1960–94},
   Journal = {Biology and Environment: Proceedings of the Royal Irish Academy},
   Volume = {96B},
   Number = {2},
   Pages = {55–68},
      Year = {1996} }




@article{
Calderetal2003,
   Author = {Calder, C. and Lavine, M. and Muller, P. and Clark, J. S.},
   Title = {Incorporating multiple sources of stochasticity into dynamic population models},
   Journal = {Ecology},
   Volume = {84},
   Number = {6},
   Pages = {1395–1402},
      Year = {2003} }




@techreport{
CalkinsPitcher1982,
   Author = {Calkins, D. G. and Pitcher, K. W.},
   Title = {Population assessment, ecology and trophic relationships of Steller sea lions in the Gulf of Alaska},
   Institution = {U.S. Department of Commerce},
   Number = {Final Report 17},
      Year = {1982} }




@article{
Calletal2007,
   Author = {Call, Katherine A. and Fadely, Brian S. and Greig, Angie and Rehberg, Michael J.},
   Title = {At-sea and on-shore cycles of juvenile Steller sea lions (Eumetopias jubatus) derived from satellite dive recorders: A comparison between declining and increasing populations},
   Journal = { Deep-Sea Research},
   Volume = {54},
   Pages = {298-310},
      Year = {2007} }




@phdthesis{
Cameron2001,
   Author = {Cameron, M. },
   Title = {Dynamics of a Weddell seal (Leptonychotes weddellii) population in McMurdo Sound, Antarctica},
   School = {University of Minnesota},
   Type = {Ph.D.},
      Year = {2001} }




@article{
CameronSiniff2004,
   Author = {Cameron, M. F. and Siniff, D. B.},
   Title = {Age-specific survival, abundance, and immigration rates of a Weddell seal (Leptonychotes weddellii) population in McMurdo Sound, Antarctica},
   Journal = {Canadian Journal of Zoology},
   Volume = {82},
   Pages = {601–615},
      Year = {2004} }




@article{
Carlinetal1992,
   Author = {Carlin, B. P. and Polson, N. G. and Stoffer, D. S.},
   Title = {A Monte Carlo approach to nonnormal and nonlinear state-space modeling},
   Journal = {Journal of the American Statistical Association},
   Volume = {87},
   Pages = {493-500},
      Year = {1992} }




@techreport{
Carrettaetal2006,
   Author = {Carretta, J.V. and Forney, K.A. and Muto, M.M. and Barlow, J. and Baker, J. and Hanson, Brad and Lowry, M.},
   Title = {U.S. Pacific Marine Mammal Stock Assessments: 2005},
   Institution = {U.S. Department of Commerce, NOAA Technical Memorandum NMFS-SWFSC-388},
      Year = {2006} }




@incollection{
Carrettaetal2006,
   Author = {Carretta, James V. and Forney, Karin A. and Muto, Marcia M. and Barlow, Jay and Baker, Jason and Hanson, Brad and Lowry, Mark S.},
   Title = {Stock assessment for the harbor seal (Phoca vitulina richardsi): California stock},
   BookTitle = {U.S. Pacific marine mammal stock assessments: 2005},
   Publisher = {U.S. Department of Commerce, NOAA-TM-NMFS-SWFSC-388},
   Address = {Washington, DC},
   Pages = {8-14},
      Year = {2006} }




@book{
Caswell2001,
   Author = {Caswell, H.},
   Title = {Matrix population models: construction, analysis, and interpretation},
   Publisher = {Sinauer},
   Address = {Sunderland, MA, USA},
      Year = {2001} }




@article{
CavanaughShumway1997,
   Author = {Cavanaugh, J.E. and Shumway, R.H.},
   Title = {A bootstrap variant of {AIC} for state-space model selection},
   Journal = {Statistica Sinica},
   Volume = {7},
   Pages = {473-496},
      Year = {1997} }




@techreport{
Chumbleyetal1997,
   Author = {Chumbley, K. and Sease, J. and Strick, M. and Towell, R.},
   Title = {Field studies of Steller sea lions (Eumetopias jubatus) at Marmot Island, Alaska 1979 through 1994},
   Institution = {NOAA Tech. Memo. NMFS-AFSC-77,  U.S. Department of Commerce},
      Year = {1997} }




@article{
Cohen1977,
   Author = {Cohen, J.},
   Title = {Ergodicity of age structure in populations with Markovian vital rates, III: finite-state moments and growth rate; an illustration},
   Journal = {Advances in Applied Probability},
   Volume = {9},
   Number = {462-475},
      Year = {1977} }




@article{
CoulsonThomas1985,
   Author = {Coulson, J. C. and Thomas, C. S.},
   Title = {Changes in the biology of the kittiwake Rissa tridactyla: A 31-year study of a breeding colony},
   Journal = {Journal of Animal Ecology},
   Volume = {54},
   Pages = {9–26},
      Year = {1985} }




@article{
Coulsonetal2001,
   Author = {Coulson, T. and Mace, G. M. and Hudson, E. and Possingham, H.},
   Title = {The use and abuse of population viability analysis},
   Journal = {Trends in Ecology and Evolution},
   Volume = {16},
   Number = {5},
   Pages = {219-221},
   Abstract = {A recent study by Brook ef al. empirically tested the performance of population viability analysis (PVA) using data from 21 populations across a wide range of species. The study concluded that PVAs are good at predicting the future dynamics of populations. We suggest that this conclusion is a result of a bias in the studies that Brook et al, included in their analyses, We present arguments that PVAs can only be accurate at predicting extinction probabilities if data are extensive and reliable, and if the distribution of vital rates between individuals and years can be assumed stationary in the future, or if any changes can be accurately predicted. In particular, we note th at although catastrophes are likely to have precipitated many extinctions, estimates of the probability of catastrophes are unreliable.},
      Year = {2001} }




@article{
Coulsonetal2004,
   Author = {Coulson, T. and Rohani, P. and Pascual, M.},
   Title = {Skeletons, noise and population growth: the end of an old debate?},
   Journal = {Trends in Ecology and Evolution},
   Volume = {19},
   Number = {7},
   Pages = {359-364},
   Abstract = {Population dynamics models remain largely deterministic, although the presence of random fluctuations in nature is well recognized. This deterministic approach is based on the implicit assumption that systems can be separated into a deterministic part that captures the essential features of the system and a random part that can be neglected. But is it possible, in general, to understand population dynamics without the explicit consideration of random fluctuations? Here, we suggest perhaps not, and argue that the dynamics of many systems are a result of interactions between the deterministic nonlinear skeleton and noise.},
      Year = {2004} }




@article{
Cramp1972,
   Author = {Cramp, Stanley},
   Title = {One hundred and fifty years of mute swans on the Thames},
   Journal = {Wildfowl},
   Volume = {23},
   Pages = {119-124},
      Year = {1972} }




@article{
Cressieetal2009,
   Author = {Cressie, Noel and Calder, Catherine A. and Clark, James S. and Ver Hoef, Jay M. and Wikle, Christopher K.},
   Title = {Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling},
   Journal = {Ecological Applications},
   Volume = {10},
   Number = {3},
   Pages = {553-570},
      Year = {2009} }




@article{
Crouseetal1987,
   Author = {Crouse, D. T. and Crowder, L. B. and Caswell, H.},
   Title = {A stage-based population-model for Loggerhead sea-turtles and implications for conservation},
   Journal = {Ecology},
   Volume = {68},
   Pages = {1412-1423},
      Year = {1987} }




@incollection{
Croxalletal1998,
   Author = {Croxall, J. P. and Prince, P. A. and Rothery, P. and Wood, A. G.},
   Title = {Population changes in albatrosses in South Georgia},
   BookTitle = {Albatross biology and conservation},
   Editor = {Robertson, G. and Gales, R.},
   Publisher = {Surrey Beatty and Sons},
   Address = {Chipping Norton, NSW},
   Pages = {69-83},
      Year = {1998} }




@article{
Croxalletal1990,
   Author = {Croxall, J. P. and Rothery, P. and Pickering, S. P. C. and Prince, P. A. },
   Title = {Reproductive performance, recruitment and survival of wandering albatrosses Diomedea exulans at Bird Island, South Georgia},
   Journal = {Journal of Animal Ecology},
   Volume = {59},
   Number = {2},
   Pages = {775-796},
      Year = {1990} }




@article{
Cuthbertetal2003,
   Author = {Cuthbert, Richard and Ryan, Peter G. and Cooper, John and Hilton, Geoff},
   Title = {Demography and population trends of the Atlantic yellow-nosed albatross},
   Journal = {Condor},
   Volume = {105},
   Number = {3},
   Pages = {439–452},
      Year = {2003} }




@article{
Daleetal2000,
   Author = {Dale, V. H. and Brown, S. and Haeuber, R. A. and Hobbs, N. T. and Huntly, N. and Naiman, R. J. and Riebsame, W. E. and Turner, M. G. and Valone, T. J.},
   Title = {Ecological principles and guidelines for managing the use of land},
   Journal = {Ecological Applications},
   Volume = {10},
   Number = {3},
   Pages = {639-670},
      Year = {2000} }




@article{
Dalton2005,
   Author = {Dalton, R.},
   Title = {Conservation biology: Is this any way to save a species?},
   Journal = {Nature},
   Volume = {436},
   Pages = {14-16},
      Year = {2005} }




@techreport{
Danksetal1996,
   Author = {Danks, Alan and Burbidge, Andrew A. and Burbidge, Allan H. and Smith, Graeme T.},
   Title = {Noisy scrub-bird (Atrichornis clamosus) recovery plan},
   Institution = {Department of Conservation and Land Management, Como, Australia},
      Year = {1996} }




@techreport{
DauMallek2003,
   Author = {Dau, Christian P. and Mallek, Edward J.},
   Title = {Aerial survey of emperor geese and other waterbirds in Southwestern Alaska, Spring 2003},
   Type = {Report. U. S. Fish and Wildlife Service, Migratory Bird Management, 1011 E. Tudor Road, Anchorage, Alaska 99503},
      Year = {2003} }




@article{
Davis1994,
   Author = {Davis, Alison},
   Title = {Status, distribution, and population trends of the New Zealand shore plover Thinornis novaeseelandiae},
   Journal = {Notornis},
   Volume = {S41},
   Pages = {179-194},
      Year = {1994} }




@article{
DavisNewton1981,
   Author = {Davis, P. E. and Newton, I.},
   Title = {Population and breeding of red kites in Wales Over a 30-year period},
   Journal = {Journal of Animal Ecology},
   Volume = {50},
   Number = {3},
   Pages = {759-772},
      Year = {1981} }




@article{
deJong1988,
   Author = {de Jong, Piet},
   Title = {The likelihood for a state space model},
   Journal = {Biometrika},
   Volume = {75},
   Number = {1},
   Pages = {165-169},
      Year = {1988} }




@article{
deJong1989,
   Author = {de Jong, Piet},
   Title = {Smoothing and interpolation with the state space model},
   Journal = {Journal of the American Statistical Association},
   Volume = {84},
      Year = {1989} }




@article{
deJongPenzer1998,
   Author = {de Jong, Piet and Penzer, Jeremy},
   Title = {Diagnosing shocks in time series},
   Journal = {Journal of the American Statistical Association},
   Volume = {93},
   Number = {442},
   Pages = {796-806},
      Year = {1998} }




@techreport{
deJongPenzer2004,
   Author = {de Jong, P. and Penzer, Jeremy},
   Title = {The ARMA model in state space form},
      Year = {2004} }




@article{
deValpine2002,
   Author = {de Valpine, Perry},
   Title = {Review of methods for fitting time-series models with process and observation error and likelihood calculations for nonlinear, non-Gaussian state-space models},
   Journal = {Bulletin of Marine Science},
   Volume = {70},
   Number = {2},
   Pages = {455-471},
      Year = {2002} }




@article{
deValpine2003,
   Author = {de Valpine, Perry},
   Title = {Better inferences from population-dynamics experiments using Monte Carlo state-space likelihood methods},
   Journal = {Ecology},
   Volume = {84},
   Pages = {3064–3077},
      Year = {2003} }




@article{
deValpine2004,
   Author = {de Valpine, P.},
   Title = {Monte Carlo state-space likelihoods by weighted posterior kernel density estimation},
   Journal = {Journal of the American Statistical Association},
   Volume = {99},
   Pages = {523–536},
      Year = {2004} }




@article{
deValpineHastings2002,
   Author = {de Valpine, Perry and Hastings, Alan},
   Title = {Fitting population models incorporating process noise and observation error},
   Journal = {Ecological Monographs},
   Volume = {72},
   Number = {1},
   Pages = {57-76},
   Abstract = {We evaluate a method for fitting models to time series of population abundances
that incorporates both process noise and observation error in a likelihood framework.
The method follows the probability logic of the Kalman filter, but whereas the Kalman
filter applies to linear, Gaussian systems, we implement the full probability calculations
numerically so that any nonlinear, non-Gaussian model can be used. We refer to the method
as the ‘‘numerically integrated state-space (NISS) method’’ and compare it to two common
methods used to analyze nonlinear time series in ecology: least squares with only process
noise (LSPN) and least squares with only observation error (LSOE). We compare all three
methods by fitting Beverton-Holt and Ricker models to many replicate model-generated
time series of length 20 with several parameter choices. For the Ricker model we chose
parameters for which the deterministic part of the model produces a stable equilibrium, a
two-cycle, or a four-cycle. For each set of parameters we used three process-noise and
observation-error scenarios: large standard deviation (0.2) for both, and large for one but
small (0.05) for the other. The NISS method had lower estimator bias and variance than
the other methods in nearly all cases. The only exceptions were for the Ricker model with
stable-equilibrium parameters, in which case the LSPN and LSOE methods has lower bias
when noise variances most closely met their assumptions. For the Beverton-Holt model,
the NISS method was much less biased and more precise than the other methods.
We also evaluated the utility of each method for model selection by fitting simulated
data to both models and using information criteria for selection. The NISS and LSOE
methods showed a strong bias toward selecting the Ricker over the Beverton-Holt, even
when data were generated with the Beverton-Holt. It remains unclear whether the LSPN
method is generally superior for model selection or has fortuitously better biases in this
particular case. These results suggest that information criteria are best used with caution
for nonlinear population models with short time series. Finally we evaluated the convergence of likelihood ratios to theoretical asymptotic
distributions. Agreement with asymptotic distributions was very good for stable-point Ricker
parameters, less accurate for two-cycle and four-cycle Ricker parameters, and least
accurate for the Beverton-Holt model. The numerically integrated state-space method has
a number of advantages over least squares methods and offers a useful tool for connecting
models and data and ecology.},
      Year = {2002} }




@article{
deValpineHilborn2005,
   Author = {de Valpine, P. and Hilborn, Ray},
   Title = {State-space likelihoods for nonlinear fisheries time series},
   Journal = {Canadian Journal of Fisheries and Aquatic Sciences},
   Volume = {62},
   Pages = {1937-1952},
      Year = {2005} }




@techreport{
DeMasteretal2004,
   Author = {DeMaster, D. and Angliss, R. and Cochrane, J. and Mace, P. and Merrick, R. and Miller, M. and Rumsey, S. and Taylor, B. and Thompson, G. and Waples, R.},
   Title = {Recommendations to NOAA Fisheries: ESA listing criteria by the Quantitative Working Group 10 June 2004},
   Institution = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-F/SPO-67},
      Year = {2004} }




@article{
DeMasteretal2006,
   Author = {DeMaster, Douglas P. and Trites, Andrew W. and Clapham, Phillip and Mizroch, Sally and Wade, Paul and Small, Robert J. and Ver Hoef, Jay},
   Title = {The sequential megafaunal collapse hypothesis: Testing with existing data},
   Journal = {Progress in Oceanography},
   Volume = {68},
   Pages = {329–342},
      Year = {2006} }




@article{
Dempsteretal1977,
   Author = {Dempster, Arthur and Laird, Nan and Rubin, Donald},
   Title = {Likelihood from incomplete data via the {EM} algorithm},
   Journal = {Journal of the Royal Statistical Society, Series B},
   Volume = {39},
   Number = {1},
   Pages = {1-38},
      Year = {1977} }




@article{
denBoer1991,
   Author = {den Boer, P. J.},
   Title = {Seeing the trees for the wood: random walks or bounded fluctuations of population size?},
   Journal = {Oecologia},
   Volume = {86},
   Pages = {484-491},
      Year = {1991} }




@article{
denBoerReddingius1989,
   Author = {den Boer, P. J. and Reddingius, J.},
   Title = {On the stabilization of animal numbers.  Problems of testing. 2. Confontation with data from the field},
   Journal = {Oecologia},
   Volume = {79},
   Pages = {484-491},
      Year = {1989} }




@article{
DennisCostantino1988,
   Author = {Dennis, Brian and Costantino, R. F.},
   Title = {Analysis of steady-state populations with the gamma abundance model: application to Tribolium},
   Journal = {Ecology},
   Volume = {69},
   Pages = {1200-1213},
      Year = {1988} }




@article{
Dennis2001,
   Author = {Dennis, B. and Desharnais, R. A. and Cushing, J. M. and Henson, S. M. and Costantino, R. F.},
   Title = {Estimating chaos and complex dynamics in an insect population},
   Journal = {Ecological Monographs},
   Volume = {71},
   Number = {2},
   Pages = {277-303},
   Abstract = {A defining hypothesis of theoretical ecology during the past century has been that population fluctuations might largely be explained by relatively low-dimensional, nonlinear ecological interactions, provided such interactions could be correctly identified and modeled. The realization in recent decades that such nonlinear interactions might result in chaos and other exotic dynamic behaviors has been exciting but tantalizing, in that attributing the fluctuations of a particular real population to the complex dynamics of a particular mathematical model has proved to be an elusive goal. We experimentally tested a model-predicted sequence of transitions (bifurcations) in the dynamic behavior of a population from stable equilibria to quasiperiodic and periodic cycles to chaos to three-cycles using cultures of the flour beetle Tribolium. The predictions arose from a system of difference equations (the LPA model) describing the nonlinear life-stage interactions, predominantly cannibalism. We built a stochastic version of the model incorporating demographic variability and obtained conditional least-squares estimates for the model parameters. We generated 2000 "bootstrapped data sets" with a time-series bootstrap technique, and for each set we reestimated the model parameters. The resulting 2000 bootstrapped parameter vectors were used to obtain confidence intervals for the model parameters and estimated distributions of the Liapunov exponents for the deterministic portion (the skeleton) of the model as well as fur the full stochastic model. Frequency distributions of estimated dynamic behaviors of the skeleton at each experimental treatment were produced. For one treatment, over 83% of the bootstrapped parameter estimates corresponded to chaotic attractors, and the remainder of the estimates yielded high-period cycles. The low-dimensional skeleton accounted for at least 90% of the variability in the population abundances and accurately described the responses of populations to experimental demographic manipulations, including treatments for which the predicted dynamic behavior was chaos. Demographic stochasticity described the remaining noise quite well. We conclude that the fluctuations of experimental hour battle populations are explained largely by known nonlinear forces involving cannibalistic-stage interactions. Claims of dynamic behavior such as periodic cycles or chaos must be accompanied by a consideration of the reliability of the estimated parameters and a realization that the population fluctuations are a blend of deterministic forces and stochastic events.},
      Year = {2001} }




@article{
Dennisetal1998,
   Author = {Dennis, B. and Kemp, W. P. and Taper, M. L.},
   Title = {Joint density dependence},
   Journal = {Ecology},
   Volume = {79},
   Number = {2},
   Pages = {426-441},
      Year = {1998} }




@article{
Dennisetal1991,
   Author = {Dennis, B. and Munholland, P. L. and Scott, J. M.},
   Title = {Estimation of growth and extinction parameters for endangered species},
   Journal = {Ecological Monographs},
   Volume = {61},
   Pages = {115-143},
      Year = {1991} }




@article{
DennisOtten2000,
   Author = {Dennis, Brian and Otten, Mark R. M.},
   Title = {Joint effects of density dependence and rainfall on abundance of San Joaquin Kit Fox},
   Journal = {Journal of Wildlife Management},
   Volume = {64},
   Number = {2},
   Pages = {388-400},
      Year = {2000} }




@article{
Dennisetal2006,
   Author = {Dennis, B. and Ponciano, J. M. and Lele, S. R. and Taper, M. L. and Staples, D. F.},
   Title = {Estimating density dependence, process noise, and observation error},
   Journal = {Ecological Monographs},
   Volume = {76},
   Number = {3},
   Pages = {323-341},
      Year = {2006} }




@article{
DennisTaper1994,
   Author = {Dennis, Brian and Taper, Mark L.},
   Title = {Density dependence in time series observations of natural populations: estimation and testing },
   Journal = {Ecological Monographs},
   Volume = {64},
   Number = {2},
   Pages = {205-224},
      Year = {1994} }




@techreport{
DOC2001,
   Author = {Department of Conservation},
   Title = {New Zealand shore plover recovery plan 2001-2011},
   Institution = {New Zealand Department of Conservation, PO Box 10-420, Wellington, NZ},
   Type = {Threatened Species Recovery Plan 44},
      Year = {2001} }




@article{
DiserudEngen2000,
   Author = {Diserud, O. H. and Engen, S.},
   Title = {A general and dynamic species abundance model, embracing the lognormal and the gamma models},
   Journal = {American Naturalist},
   Volume = {155},
   Number = {4},
   Pages = {498-511},
      Year = {2000} }




@techreport{
DOAWR,
   Author = {Division of Aquatic and Wildlife Resources},
   Title = {Job progress reports: current status, distribution, and natural history of Mariana fruit bats},
   Institution = {Federal Aid to Fish and Wildlife Restoration, Guam, Guam Department of Agriculture, Mangilao, Guam.},
      Year = {1981-2001} }




@book{
DixitPindyck1994,
   Author = {Dixit, Vinash K. and Pindyck, Robert S.},
   Title = {Investment under uncertainty},
   Publisher = {Princeton University Press},
   Address = {Princeton, NJ},
      Year = {1994} }




@article{
Doaketal1994,
   Author = {Doak, D. and Kareiva, P. and Klepetka, B.},
   Title = {Modeling population viability for the desert tortoise in the Western Mojave desert},
   Journal = {Ecological Applications},
   Volume = {4},
   Pages = {446-460},
      Year = {1994} }




@article{
DorazioJohnson2003,
   Author = {Dorazio, Robert M. and Johnson, Fred A.},
   Title = {Bayesian inference and decision theory--a framework for decision making in natural resource management},
   Journal = {Ecological Applications},
   Volume = {13},
   Number = {2},
   Pages = {556-563},
      Year = {2003} }




@article{
Doroffetal2003,
   Author = {Doroff, A. M. and Estes, J. A. and Tinker, M. T. and Burns, D. M. and Evans, T. J.},
   Title = {Sea otter population declines in the Aleutian archipelago},
   Journal = {Journal of Mammalogy},
   Volume = {84},
   Pages = {55-64},
      Year = {2003} }




@article{
DoucetTadic2003,
   Author = {Doucet, A. and Tadic, V. B.},
   Title = {Parameter estimation in general state-space models using particle methods},
   Journal = {Annals of the Institute of Statistical Mathematics},
   Volume = {55},
   Number = {2},
   Pages = {409-422},
      Year = {2003} }




@article{
Drechsleretal2004,
   Author = {Drechsler, Martin and Burgman, Mark A.},
   Title = {Combining population viability analysis with decision analysis},
   Journal = {Biodiversity and Conservation},
   Volume = {13},
   Number = {1},
   Pages = {115-139},
      Year = {2004} }




@article{
Driscoll2007,
   Author = {Driscoll, D. A.},
   Title = {How to find a metapopulation},
   Journal = {Canadian Journal of Zoology},
   Volume = {85},
   Number = {10},
   Pages = {1031-1048},
      Year = {2007} }




@article{
Duffy2003,
   Author = {Duffy, J. Emmett},
   Title = {Biodiversity loss, trophic skew, and ecosystem functioning},
   Journal = {Ecology Letters},
   Volume = {3},
   Pages = {680-687},
      Year = {2003} }




@article{
Dunnetal1978,
   Author = {Dunnet, G. M. and Ollason, J. C. and Anderson, A.},
   Title = {A 28-year study of breeding fulmars Fulmarus glacialis in Orkney},
   Journal = {Ibis},
   Volume = {121},
   Pages = {293-300},
      Year = {1978} }




@book{
DurbinKoopman2001,
   Author = {Durbin, J. and Koopman, S. J.},
   Title = {Time series analysis by state space methods},
   Publisher = {Oxford University Press},
   Address = {Oxford},
      Year = {2001} }




@article{
Eberhardt2002,
   Author = {Eberhardt, L. L.},
   Title = {A paradigm for population analysis of long-lived vertebrates},
   Journal = {Ecology},
   Volume = {83},
   Number = {10},
   Pages = {2841-2854},
      Year = {2002} }




@article{
Eberhardtetal1986,
   Author = {Eberhardt, L. L. and Knight, R. R. and Blanchard, B.},
   Title = {Monitoring grizzly bear population trends},
   Journal = {Journal of Wildlife Management},
   Volume = {50},
   Pages = {613-618},
      Year = {1986} }




@article{
Ellison2004,
   Author = {Ellison, A. M.},
   Title = {Bayesian inference in ecology},
   Journal = {Ecology Letters},
   Volume = {7},
   Pages = {509-520},
      Year = {2004} }




@article{
Ellner2003,
   Author = {Ellner, S. P.},
   Title = {When does parameter drift decrease the uncertainty in extinction risk estimates?},
   Journal = {Ecology Letters},
   Volume = {6},
   Number = {12},
   Pages = {1039-1045},
   Abstract = {Halley (2003) proposed that parameter drift decreases the uncertainty in long-range extinction risk estimates, because drift mitigates the extreme sensitivity of estimated risk to estimated mean growth rate. However, parameter drift has a second, opposing effect: it increases the uncertainty in parameter estimates from a given data set. When both effects are taken into account, parameter drift can increase, sometimes substantially, the uncertainty in risk estimates. The net effect depends sensitively on the type of drift and on which model parameters must be estimated from observational data on the population at risk. In general, unless many parameters are estimated from independent data, parameter drift increases the uncertainty in extinction risk. These findings suggest that more mechanistic PVA models, using long-term data on key environmental variables and experiments to quantify their demographic impacts, offer the best prospects for escaping the high data requirements when extinction risk is estimated from observational data.},
      Year = {2003} }




@article{
Ellneretal2002,
   Author = {Ellner, S. P. and Fieberg, J. and Ludwig, D. and Wilcox, C.},
   Title = {Precision of population viability analysis},
   Journal = {Conservation Biology},
   Volume = {16},
   Number = {1},
   Pages = {258-261},
      Year = {2002} }




@article{
EllnerHolmes2008,
   Author = {Ellner, S. P. and Holmes, E. E.},
   Title = {Resolving the debate on when extinction risk is predictable},
   Journal = {Ecology Letters},
   Volume = {11},
   Pages = {E1-E5},
      Year = {2008} }




@article{
Engenetal2003,
   Author = {Engen, S. and Lande, R. and Sæther, B.-E.},
   Title = {Demographic stochasticity and allee effects in populations' with two sexes},
   Journal = {Ecology},
   Volume = {84},
   Number = {9},
   Pages = {2378-2386},
      Year = {2003} }




@article{
Engenetal2007,
   Author = {Engen, S. and Lande, R. and Sæther, B-E},
   Title = {Using reproductive value to estimate key parameters in density-independent age-structured populations},
   Journal = {Journal of Theoretical Biology},
   Volume = {244},
   Pages = {308-317},
   Abstract = {The dynamics of reproductive value are used to provide a simple derivation of Tuljapurkar’s approximation for the long-run growth
rate and environmental variance of lnN, in a density-independent age-structured population in a random environment. With no
environmental autocorrelation, the dynamics of total population size, N, generally shows time lags and autocorrelation caused by life
history, which may strongly bias estimates of environmental variance obtained by ignoring age structure. In contrast, the total
reproductive value, V, is Markovian and obeys a first-order autoregressive process. This suggests a simple method for estimating the
environmental variance, and avoiding potentially large bias due to age-structure fluctuations, by converting a multivariate time series of
age structure to a univariate time series of lnV. We illustrate the method by estimating the long-run growth rate and the environmental
variance in an exponentially growing population of Bighorn Sheep.
r 2006 Elsevier Ltd. All rights reserved.},
      Year = {2007} }




@article{
Engenetal2005,
   Author = {Engen, S. and Lande, R. and Sæther, B.-E. and Weimerskirch, H.},
   Title = {Extinction in relation to demographic and environmental stochasticity in age-structured models},
   Journal = {Mathematical Biosciences},
   Volume = {195},
   Number = {2},
   Pages = {210-227},
      Year = {2005} }




@article{
EngenSaether2000,
   Author = {Engen, S. and Sæther, B.-E.},
   Title = {Predicting the time to quasi-extinction for populations far below their carrying capacity},
   Journal = {Journal of Theoretical Biology},
   Volume = {205},
   Pages = {649-658},
      Year = {2000} }




@article{
Engenetal2001,
   Author = {Engen, S. and Sæther, B. -E. and Møller, A. P.},
   Title = {Stochastic population dynamics and time to extinction of a declining population of barn swallows},
   Journal = {Journal of Animal Ecology},
   Volume = {70},
   Pages = {789-797},
      Year = {2001} }




@article{
Erzini2005,
   Author = {Erzini, Karim},
   Title = {Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables},
   Journal = {Fisheries Oceanography},
   Volume = {14},
   Pages = {195-209},
      Year = {2005} }




@article{
Erzinietal2005,
   Author = {Erzini, K. and Inejih, C. A. O. and Stobberup, K. A.},
   Title = {An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data},
   Journal = {ICES Journal of Marine Science},
   Volume = {62},
   Pages = {353-359},
      Year = {2005} }




@incollection{
Etienneetal2004,
   Author = {Etienne, R. S. and Ter Braak, C.J.F. and Vos, C.C.},
   Title = {Application of stochastic patch occupancy models to real metapoulations},
   BookTitle = {Ecology, genetics, and evolution of metapopulations},
   Editor = {Hanski, I.A. and Gaggiotti, O. E.},
   Publisher = {Elsevier Academic Press},
   Address = {Burlington, MA},
   Pages = {105-132},
      Year = {2004} }




@article{
FaganHolmes2006,
   Author = {Fagan, W. F and Holmes, E. E.},
   Title = {Quantifying the extinction vortex},
   Journal = {Ecology Letters},
   Volume = {9},
   Pages = {51-60},
      Year = {2006} }




@article{
Faganetal2001,
   Author = {Fagan, W. F. and Meir, E. and Prendergast, J. and Folarin, A. and Karieva, P.},
   Title = {Characterizing population vulnerability for 758 species},
   Journal = {Ecology Letters},
   Volume = {4},
   Number = {2},
   Pages = {132-138},
   Abstract = {We investigate relationships between life history traits and the character of population dynamics as revealed by time series data. Our classification of time series is according to 'extinction category,' where we identify three classes of populations: (i) weakly varying populations with such high growth rates that long-term persistence is likely (unless some extreme catastrophe occurs); (ii) populations with such low growth rates that average population size must be large to buffer them against extinction in a variable environment; and (iii) highly variable populations that fluctuate so dramatically that dispersal or some other refuge mechanism is likely to be key to their avoidance of extinction. Using 1941 time series representing 758 species from the Global Population Dynamics Database, we find that, depending on the form of density dependence one assumes, between 46 and 90% of species exhibit dynamics that are so variable that even large carrying capacities could not buffer them against extinction on a 100-year time horizon. The fact that such a large proportion of population dynamics are so locally variable vindicates the growing realization that dispersal, habitat connectedness, and large-scale processes are key to local persistence. Furthermore, for mammals, simply by knowing body size, age at first reproduction, and average number of offspring we could correctly predict extinction categories for 83% of species (60 of 72).},
      Year = {2001} }




@book{
Feller1968,
   Author = {Feller, W.},
   Title = {An introduction to probability theory and its applications},
   Publisher = {Wiley},
   Address = {New York, NY, USA},
      Year = {1968} }




@book{
Ferguson1996,
   Author = {Ferguson, Thomas S.},
   Title = {A course in large sample theory},
   Publisher = {Chapman and Hall},
      Year = {1996} }




@techreport{
FerreroFritz1994,
   Author = {Ferrero, R. and Fritz, L. W.},
   Title = {Comparisons of walleye pollock, Theragra chalcogramma, harvest to Steller sea lion, Eumetopias jubatus, abundance in the Bering Sea and Gulf of Alaska},
   Institution = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-43},
      Year = {1994} }




@book{
FerroroFritz2002,
   Author = {Ferrero, R. C. and Fritz, L. W.},
   Title = {Steller sea lion research coordination: a brief history and summary of recent progress},
   Publisher = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-129, 34p.},
      Year = {2002} }




@article{
FestaBianchet2003,
   Author = {Festa-Bianchet, M. and Gaillard, J. and Côté, S. D.},
   Title = {Variable age structure and apparent density dependence in survival of adult ungulates},
   Journal = {Journal of Animal Ecology},
   Volume = {72},
   Pages = {640–649},
      Year = {2003} }




@article{
FiebergEllner2000,
   Author = {Fieberg, J. and Ellner, S. P.},
   Title = {When is it meaningful to estimate an extinction probability?},
   Journal = {Ecology},
   Volume = {81},
   Number = {7},
   Pages = {2040-2047},
   Abstract = {Recently Don Ludwig has shown that calculations of extinction probabilities based on currently available data are often meaningless due to the large uncertainty accompanying the estimates. Here we address two questions posed by his findings. Can one ever calculate extinction probabilities accurately? If so, how much data would be necessary? Our analysis indicates that reliable predictions of long-term extinction probabilities are likely to require unattainable amounts of data. Analytic calculations based on diffusion approximations indicate that reliable predictions of extinction probabilities can be made only for short-term time horizons (10% to 20% as long as the period over which the population has been monitored). Simulation results for unstructured and structured populations (three stage classes) agree with these calculations.},
      Year = {2000} }




@article{
FiebergEllner2001,
   Author = {Fieberg, J. and Ellner, S. P.},
   Title = {Stochastic matrix models for conservation and management: a comparative review of methods},
   Journal = {Ecology Letters},
   Volume = {4},
   Number = {3},
   Pages = {244-266},
   Abstract = {Stochastic matrix models are frequently used by conservation biologists to measure the viability of species and to explore various management actions. Models are typically parameterized using two or more sets of estimated transition rates between age/size/stage classes. While standard methods exist for analyzing a single set of transition rates, a variety of methods have been employed to analyze multiple sets of transition rates. We review applications of stochastic matrix models to problems in conservation and use simulation studies to compare the performance of different analytic methods currently in use. We find that model conclusions are likely to be robust to the choice of parametric distribution used to model vital rate fluctuations over time. However, conclusions can be highly sensitive to the within-year correlation structure among vital rates, and therefore we suggest using analytical methods that provide a means of conducting a sensitivity analysis with respect to correlation parameters. Our simulation results also suggest that the precision of population viability estimates can be improved by using matrix models that incorporate environmental covariates in conjunction with experiments to estimate transition rates under a range of environmental conditions.},
      Year = {2001} }




@article{
FisherTippett1928,
   Author = {Fisher, R. A. and Tippett, L. H. C.},
   Title = {Limiting forms of the frequency distributions of the largest and smallest member of a sample},
   Journal = {Biometrika},
   Volume = {17},
   Pages = {364-387},
      Year = {1928} }




@article{
Foley1994,
   Author = {Foley, P.},
   Title = {Predicting extinction times from environmental stochasticity and carrying capacity},
   Journal = {Conservation Biology},
   Volume = {8},
   Number = {1},
   Pages = {124-137},
      Year = {1994} }




@article{
Foley2000,
   Author = {Foley, P.},
   Title = {Problems in Extinction Model Selection and Parameter Estimation},
   Journal = {Environmental Management},
   Volume = {26},
   Pages = {55-73},
   Abstract = {It is a vexing problem to achieve a consensus about the proper scientific way to assess population viability for habitat conservation plans. Rather than a hypothesis-testing approach, here it is proposed to select population models, estimate extinction parameters, and assess prediction uncertainty using a pragmatic, empirical Bayesian approach. The simplest usable models include the effects of population growth, r; carrying capacity, K; Allee threshold, NA; and environmental stochasticity, vr. Analytic predictions of expected extinction times are available for such models. Models that are more complex can be elaborated from this basis. Selection from a hierarchy of nesting population models can often be done through the evaluation of parameters. The estimation of the most important extinction parameters can be undertaken in a variety of ways. Time series can be analyzed to estimate rd, vr, A, and K. Habitat models and individualistic population models may help estimate NA and K and demographic stochasticity. Fine-scale biogeography and climatological data may be useful in the estimation of a variety of parameters. Because it takes many years to estimate extinction parameters accurately for a given population of interest, the most efficient estimation procedures are desirable. I propose the use of prior information from an (as yet nonexistent) population biology database. The accumulation of local information through monitoring will improve our estimates allowing adaptive management. Uncertainty in the estimates will always remain, but it may be quantified by the posterior distributions. A crude example is discussed using treefrog population data. Although the motivations, beliefs, and biases of competing stakeholders will differ, a habitat conservation plan could accommodate this variation in the prior distributions. Field experience from monitoring will increasingly clear up any discrepancies between the opposing beliefs and the real ecosystem. As the world is an uncertain place and because there is no universal scientific method, there will always be controversy and surprises. The best we can do is (1) agree about our prior information, (2) agree about the strategy of model selection and parameter estimation, and (3) agree about our strategy for adaptive management. Perhaps the greatest impediment to such prior agreements for HCPs is the likely paranoia inspired by the use of unfamiliar statistical methodology. We need to train students of ecology in a more flexible and deeper understanding of statistics and philosophy of science.},
      Year = {2000} }




@article{
Forster1981,
   Author = {Forster, Charles W.},
   Title = {Density dependence as related to life history strategy},
   Journal = {Ecology},
   Volume = {62},
   Number = {3},
   Pages = {602-610},
      Year = {1981} }




@article{
Forster2002,
   Author = {Forster, Malcolm R.},
   Title = {Predictive accuracy as an achievable goal of science},
   Journal = {Philosophy of Science},
   Volume = {69},
   Pages = {S124-S134},
      Year = {2002} }




@article{
FoxKendall2002,
   Author = {Fox, Gordon A. and Kendall, Bruce E.},
   Title = {Demographic stochasticity and the variance reduction effect},
   Journal = {Ecology},
   Volume = {83},
   Number = {7},
   Pages = {1928-1934},
      Year = {2002} }




@article{
FritzBrown2005,
   Author = {Fritz, L. W. and Brown, E.},
   Title = {Survey- and fishery-derived estimates of Pacific cod (Gadus macrocephalus) biomass: implications for strategies to reduce interactions between groundfish fisheries and Steller sea lions (Eumetopias jubatus)},
   Journal = {Fishery Bulletin},
   Volume = {103},
   Pages = {501-515},
      Year = {2005} }




@article{
Fritzetal1995,
   Author = {Fritz, L. W. and Ferrero, R. C. and Berg, R. J. },
   Title = {The threatened status of Steller sea lions, Eumetopias jubatus, under the Endangered Species Act: effects on Alaska groundfish fisheries management},
   Journal = {Marine Fisheries Review},
   Volume = {57},
   Pages = {14-27},
      Year = {1995} }




@article{
FritzHinckley2005,
   Author = {Fritz, L. W. and Hinckley, S.},
   Title = {A critical review of the regime shift-“junk food”-nutritional stress hypothesis for the decline of the western stock of Steller sea lion},
   Journal = {Marine Mammal Science},
   Volume = {21},
   Pages = {476-518},
      Year = {2005} }




@techreport{
FritzStinchcomb2005,
   Author = {Fritz, L. W. and Stinchcomb, C. },
   Title = {Aerial, ship, and land-based surveys of Steller sea lions (Eumetopias jubatus) in the western stock in Alaska, June and July 2003 and 2004},
   Institution = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-153},
      Year = {2005} }




@article{
Fulleretal2002,
   Author = {Fuller, R.J. and Ward, E. and Hird, D. and Brown, A.F.},
   Title = {Declines of ground-nesting birds in two areas of upland farmland in the south Pennines of England},
   Journal = {Bird Study},
   Volume = {49},
   Number = {2},
   Pages = {146-152},
      Year = {2002} }




@article{
FurstenbergKesten1960,
   Author = {Furstenberg, H. and Kesten, H.},
   Title = {Products of random matrices},
   Journal = {Annals of Mathematical Statistics},
   Volume = {31},
   Pages = {457-469},
      Year = {1960} }




@article{
GarberBurger1995,
   Author = {Garber, S. D. and Burger, J.},
   Title = {A 20-year study documenting the relationship between turtle decline and human recreation},
   Journal = {Ecological Applications},
   Volume = {5},
   Pages = {1151-1162},
      Year = {1995} }




@article{
Gerberetal1999,
   Author = {Gerber, L. R. and Master, D. P. De and Kareiva, P. M.},
   Title = {Grey whales and the value of monitoring data in implementing the U.S. Endangered Species Act},
   Journal = {Conservation Biology},
   Volume = {13},
   Pages = {1215-1219},
      Year = {1999} }




@article{
Gerberetal2005,
   Author = {Gerber, L. R. and McCallum, H. and Lafferty, K. D. and Sabo, J. L. and Dobson, A.},
   Title = {Exposing extinction risk analysis to pathogens: Is disease just another form of density dependence?},
   Journal = {Ecological Applications},
   Volume = {15},
   Number = {4},
   Pages = {1402-1414},
   Abstract = {In the United States and several other countries., the development of population viability analyses (PVA) is a legal requirement of any species survival plan developed for threatened and endangered species. Despite the importance of pathogens in natural populations, little attention has been given to host-pathogen dynamics in PVA. To study the effect of infectious pathogens on extinction risk estimates generated from PVA, we review and synthesize the relevance of host-pathogen dynamics in analyses of extinction risk. We then develop a stochastic, density-dependent host-parasite model to investigate the effects of disease on the persistence of endangered populations. We show that this model converges on a Ricker model of density dependence under a suite of limiting assumptions, including. a high probability that epidemics will arrive and occur. Using this modeling framework, we then quantify: (1) dynamic differences between time series generated by disease and Ricker processes with the same parameters; (2) observed probabilities of quasi-extinction for populations exposed to disease or self-limitation; and (3) bias in probabilities of quasi-extinction estimated by density-independent PVAs when populations experience either form of density dependence. Our results suggest two generalities about the relationships among disease, PVA, and the management of endangered species. First, disease more strongly increases variability in host abundance and, thus, the probability of quasi-extinction, than does self-limitation. This result stems from the fact that the effects and the probability of occurrence of disease are both density dependent. Second, estimates of quasi-extinction are more often overly optimistic for populations experiencing disease than for those subject to self-limitation. Thus, although the results of density-independent PVAs may be relatively robust to some particular assumptions about density dependence, they are less robust when endangered populations are known to be susceptible to disease. If potential management actions involve manipulating pathogens, then it may be useful to. model disease explicitly.},
      Year = {2005} }




@techreport{
GhahramaniHinton1996,
   Author = {Ghahramani, Z. and Hinton, G. E.},
   Title = {Parameter estimation for linear dynamical systems},
   Institution = {University of Totronto, Dept. of Computer Science},
   Number = {CRG-TR-96-2},
      Year = {1996} }




@article{
GilmartinEberhardt1995,
   Author = {Gilmartin, W. G. and Eberhardt, L. L.},
   Title = {Status of the Hawaiian monk seal (Monachus schauinslandi) population},
   Journal = {Canadian Journal of Zoology},
   Volume = {73},
   Pages = {1185-1190},
      Year = {1995} }




@incollection{
Gilpin1990,
   Author = {Gilpin, M.E.},
   Title = {Extinction in finite metapopulations living in correlated environments},
   BookTitle = {Living in a patchy environment},
   Editor = {Shorrocks, B.  and Swingland, I. R.},
   Publisher = {Oxford University Press},
   Address = {New York},
   Pages = {177-186},
      Year = {1990} }




@article{
GilpinAyala1973,
   Author = {Gilpin, M. E. and Ayala, F. J.},
   Title = {Global models of growth and competition},
   Journal = {Proceedings of the National Academy of Science USA},
   Volume = {70},
   Pages = {3590-3593},
      Year = {1973} }




@incollection{
GilpinSoule1986,
   Author = {Gilpin, M.E. and Soule, M.E.},
   Title = {Minimum viable populations: Processes of species extinction.},
   BookTitle = {Conservation Biology: The Science of Scarcity and Diversity},
   Editor = {Soule, M.E.},
   Publisher = {Sinauer},
   Address = {Sunderland, Massachusetts},
   Pages = {19-34},
      Year = {1986} }




@article{
Ginsbergetal1995,
   Author = {Ginsberg, J. R. and Mace, G. M. and Albon, S.},
   Title = {Local extinction in a small and declining population: wild dogs in the Serengeti},
   Journal = {Proceedings of the Royal Society of London Series B Biological Sciences},
   Volume = {262},
   Pages = {221-228},
      Year = {1995} }




@article{
Ginzburgetal1982,
   Author = {Ginzburg, L. and Slobodkin, L. B. and Johnson, K. and Bindman, A. G.},
   Title = {Quasi-extinction probabilities as a measure of impact on population growth. },
   Journal = {Risk Analysis},
   Volume = {21},
   Pages = {171-181},
      Year = {1982} }




@article{
Giordanietal2007,
   Author = {Giordani, Paolo and Kohn, Robert and Dijk, Dick van},
   Title = {A unified approach to nonlinearity, structural change, and outliers},
   Journal = {Journal of Econometrics},
   Volume = {137},
   Pages = {112–133},
      Year = {2007} }




@incollection{
Goodman1987,
   Author = {Goodman, D.},
   Title = {The demography of chance extinction},
   BookTitle = {Viable Populations for Conservation},
   Editor = {Soule, Michael},
   Publisher = {Cambridge University Press},
   Address = {Cambridge, UK},
   Pages = {11-34},
      Year = {1987} }




@incollection{
Goodman2002,
   Author = {Goodman, Daniel},
   Title = {Predictive Bayesian population viability analysis: a logic for listing criteria, delisting criteria, and recovery plans},
   BookTitle = {Population viability analysis},
   Editor = {Beissinger, Steven R. and McCullough, Dale R.},
   Publisher = {University of Chicago Press},
   Address = {Chicago, IL},
      Year = {2002} }




@article{
Green1984,
   Author = {Green, P.},
   Title = {Iteratively reweighted least squares for maximum likelihood estimation, and some robust and resistant alternatives (with discussion)},
   Journal = {Journal of the Royal Statistical Society B},
   Volume = {46},
   Pages = {149-192},
      Year = {1984} }




@article{
Gudmundsson1994,
   Author = {Gudmundsson, G.},
   Title = {Time series analysis of catch-at-age observations},
   Journal = {Applied Statistics},
   Volume = {43},
   Pages = {117-126},
      Year = {1994} }




@article{
HakoyamaIwasa2000,
   Author = {Hakoyama, H. and Iwasa, Y.},
   Title = {Extinction risk of a density-dependent population estimated from a time series of population size},
   Journal = {Journal of Theoretical Biology},
   Volume = {204},
   Pages = {337-359},
   Abstract = {Environmental threats, such as habitat size reduction or environmental pollution, may not cause immediate extinction of a population but shorten the expected time to extinction. We develop a method to estimate the mean time to extinction for a density-dependent population with environmental fluctuation. We first derive a formula for a stochastic differential equation model (canonical model) of a population with logistic growth with environmental and demographic stochasticities. We then study an approximate maximum likelihood (AML) estimate of three parameters (intrinsic growth rater, carrying capacity K, and environmental stochasticity 2e) from a time series of population size. The AML estimate of r has a significant bias, but by adopting the Monte Carlo method, we can remove the bias very effectively (bias-corrected estimate). We can also determine the confidence interval of the parameter based on the Monte Carlo method. If the length of the time series is moderately long (with 40–50 data points), parameter estimation with the Monte Carlo sampling bias correction has a relatively small variance. However, if the time series is short (less than or equal to 10 data points), the estimate has a large variance and is not reliable. If we know the intrinsic growth rater, however, the estimate of K and 2eand the mean extinction timeT are reliable even if only a short time series is available. We illustrate the method using data for a freshwater fish, Japanese crucian carp (Carassius auratus subsp.) in Lake Biwa, in which the growth rate and environmental noise of crucian carp are estimated using fishery records.},
      Year = {2000} }




@article{
HalleyKunin1999,
   Author = {Halley, J. and Kunin, W.},
   Title = {Extinction risk and the 1/f family of noise models},
   Journal = {Theoretical Population Biology},
   Volume = {56},
   Pages = {215-239},
      Year = {1999} }




@article{
Halley1996,
   Author = {Halley, J. M.},
   Title = {Ecology, evolution and 1/f-noise},
   Journal = {Trends in Ecology and Evolution},
   Volume = {11},
   Number = {1},
   Pages = {33-37},
   Abstract = {Among ecologists, there has been a growing recognition of the importance of long-term correlations in environmental time series, The family of 1/f-noises-fluctuations defined in terms of the different timescales present - is a useful approach to this problem, White noise and the random walk, the two currently favoured descriptions of environmental fluctuations, lie at extreme ends of this family of processes, Recent analyses of data, results of models, and examination of basic 1/f-noise properties, suggest that pink 1/f-noise, which lies midway between white noise and the random walk, might be the best null model of environmental variation, If true, this would have important consequences for the interpretation of ecological time series and for ecological and evolutionary modelling.},
      Year = {1996} }




@article{
Halley2003,
   Author = {Halley, J. M.},
   Title = {Parameter drift stabilizes long-range extinction forecasts},
   Journal = {Ecology Letters},
   Volume = {6},
   Number = {5},
   Pages = {392-397},
   Abstract = {Estimates of the reliability of population viability analysis (PVA), accounting for uncertainties in model parameters, often arrive at confidence intervals for extinction probability so wide as to be almost meaningless. This lack of precision is a consequence of extreme sensitivity to average linear growth rate, when predicting to a distant time horizon. Longer-term trends or drift in parameter values (a form of 'reddened' environmental variability) will also affect the accuracy of such forecasts. This letter reports how, contrary to intuition, introducing such a component of variability may improve the precision of extinction forecasts. The paradoxical result arises because the dependence of extinction probability on growth rate is weakened, and shifted onto other parameters (e.g. diffusion strength) where dependence is less sensitive. This offers hope that, with reasonable knowledge of environmental stochasticity, it may still be meaningful to carry out longer range PVAs.},
      Year = {2003} }




@article{
HalleyInchausti2004,
   Author = {Halley, J. M. and Inchausti, P.},
   Title = {The increasing importance of 1/f-noises as models of ecological variability},
   Journal = {Fluctuation and Noise Letters},
   Volume = {4},
   Number = {2},
   Pages = {R1-R26},
   Abstract = {The features of 1/f-noise processes offer important new insights into the field of population biology, greatly helping our quest for understanding and for prediction of ecological processes. 1/f-noises account quite satisfactorily for the observed nature of ecological fluctuations. This article reviews the application of 1/f-noise processes to ecology. After a discussion of the basic problems of population ecology that makes such an innovation necessary, we review the features of 1/f-noises concentrating especially on those aspects that make these processes attractive as a solution. We also present a discussion of the analysis of real ecological data, which confirms that there are good empirical as well as good theoretical reasons to establish a leading role for pink 1/f noise. We then discuss the consequences of such a model for our understanding of ecology. The article finishes with a number of observations about some aspects of ecological data and applications that are likely to drive research in a different direction from that associated with engineering and the physical sciences.},
      Year = {2004} }




@article{
HalleyKunin1999,
   Author = {Halley, J. M. and Kunin, V. E.},
   Title = {Extinction risk and the 1/f family of noise models},
   Journal = {Theoretical Population Biology},
   Volume = {56},
   Number = {3},
   Pages = {215-230},
   Abstract = {In order to predict extinction risk in the presence of reddened, or correlated, environmental variability, fluctuating parameters may be represented by the family of 1/f noises, a series of stochastic models with different levels of variation acting on different timescales. We compare the process of parameter estimation for three 1/f models (white, pink and brown noise) with each other, and with autoregressive noise models (which are not 1/f noises), using data from a model time-series (length, T) of population. We then calculate the expected increase in variance and the expected extinction risk for each model, and we use these to explore the implication of assuming an incorrect noise model. When parameterising these models, it is necessary to do so in terms of the measured ("sample") parameters rather than fundamental ("population") parameters. This is because these models are non-stationary: their parameters need not stabilize on measurement over long periods of time and are uniquely defined only over a specified "window" of timescales defined by a measurement process. We find that extinction forecasts can differ greatly between models, depending on the length, T, and the coefficient of variability, CV, of the time series used to parameterise the models, and on the length of time into the future which is to be projected. For the simplest possible models, ones with population itself the 1/f noise process, it is possible to predict the extinction risk based on CV of the observed time series. Our predictions, based on explicit formulae and on simulations, indicate that (a) for very short projection times relative to T, brown and pink noise models are usually optimistic relative to equivalent white noise model; (b) for projection timescales equal to and substantially greater than T, an equivalent brown or pink noise model usually predicts a greater extinction risk, unless CV is very large; and (c) except for very small values of CV, for timescales very much greater than T, the brown and pink models present a more optimistic picture than the white noise model. In most cases, a pink noise is intermediate between white and brown models. Thus, while reddening of environmental noise may increase the long-term extinction probability for stationary processes, this is not generally true for non-stationary processes, such as pink or brown noises. (C) 1999 Academic Press.},
      Year = {1999} }




@article{
Hamptonetal2008,
   Author = {Hampton, Stephanie E. and Izmest'Eva, Lyubov R. and Moore, Marianne V. and Katz, Stephen L. and Dennis, Brian and Silow, Eugene A.},
   Title = {Sixty years of environmental change in the world's largest freshwater lake -- Lake Baikal, Siberia},
   Journal = {Global Change Biology},
   Volume = {14},
   Pages = {1947-1958},
   Note = {: Global Change Biology
: 14
: © 2008 The Authors. Journal compilation © 2008 Blackwell Publishing Ltd},
      Year = {2008} }




@article{
Hamptonetal2006,
   Author = {Hampton, Stephanie E. and Scheuerell, Mark D. and Schindler, Daniel E.},
   Title = {Coalescence in the Lake Washington story: Interaction strengths in a planktonic food web},
   Journal = {Limnology and Oceanography},
   Volume = {51},
   Number = {5},
   Pages = {2042-2051},
      Year = {2006} }




@article{
HamptonSchindler2006,
   Author = {Hampton, Stephanie E. and Schindler, Daniel E.},
   Title = {Empirical evaluation of observation scale effects in community time series},
   Journal = {Oikos},
   Volume = {113},
   Number = {3},
   Pages = {424-439},
      Year = {2006} }




@book{
Hanski1999,
   Author = {Hanski, I.},
   Title = {Metapopulation ecology},
   Publisher = {Oxford University Press, USA},
      Year = {1999} }




@incollection{
HanskiSimberloff1997,
   Author = {Hanski, Ilkka and Simberloff, Daniel},
   Title = {The metapopulation approach, its history, conceptual domain, and application to conservation},
   BookTitle = {Metapopulation biology},
   Editor = {Hanski, Ilkka and Gilpin, Michael E.},
   Publisher = {Academic Press},
   Address = {San Diego, CA},
   Pages = {5-26},
      Year = {1997} }




@book{
HanskiGilpin1997,
   Editor = {Hanski, I.A. and Gilpin, M.E.},
   Title = {Metapopulation Biology: Ecology, Genetics, and Evolution},
   Publisher = {Academic Press},
   Address = {San Diego},
      Year = {1997} }




@article{
HareMantua2000,
   Author = {Hare, S. R. and Mantua, N. J. },
   Title = {Empirical evidence for North Pacific regime shifts in 1977 and 1989},
   Journal = {Progress in Oceanography},
   Volume = {47},
   Pages = {103-145},
      Year = {2000} }




@article{
HarkonenHeideJorgensen1990,
   Author = {Härkönen, T. and Heide-Jørgensen},
   Title = {Comparative life histories of East Atlantic and other harbour seal populations},
   Journal = {Ophelia},
   Volume = {32},
   Number = {3},
   Pages = {211-235},
      Year = {1990} }




@incollection{
Haroldson2004,
   Author = {Haroldson, M.},
   Title = {Unduplicated females},
   BookTitle = {Yellowstone grizzly bear investigations: annual report of the Interagency Grizzly Bear Study Team, 2003},
   Editor = {Schwartz, C.C. and Haroldson, M.A.},
   Publisher = {U.S. Geological Survey, Bozeman, Montana.},
   Pages = {10-15},
      Year = {2004} }




@article{
Harrisonetal2006,
   Author = {Harrison, Philip J. and Buckland, Stephen T. and Thomas, Len and Harris, Rob and Pomeroy, Paddy P. and Harwood, John},
   Title = {Incorporating movement into models of grey seal population dynamics},
   Journal = {Journal of Animal Ecology},
   Volume = {75},
   Pages = {634-645},
      Year = {2006} }




@article{
Harveyetal1998,
   Author = {Harvey, Andrew and Koopman, Siem Jan and Penzer, Jeremy},
   Title = {Messy time series: a unified approach},
   Journal = {Advances in Econometrics},
   Volume = {13},
   Pages = {103-143},
      Year = {1998} }




@book{
Harvey1989,
   Author = {Harvey, Andrew C.},
   Title = {Forecasting, structural time series models and the Kalman filter},
   Publisher = {Cambridge University Press},
   Address = {Cambridge, UK},
      Year = {1989} }




@book{
Harvey1993,
   Author = {Harvey, Andrew C.},
   Title = { Time Series Models},
   Publisher = {Harvester Wheatsheaf},
   Address = {London},
   Edition = {2nd},
      Year = {1993} }




@article{
HarveyKoopman1992,
   Author = {Harvey, Andrew C. and Koopman, Siem Jan},
   Title = {Diagnostic checking of unobserved components time series models},
   Journal = {Journal of Business and Economic Statistics},
   Volume = {10},
   Number = {4},
   Pages = {377-389},
      Year = {1992} }




@article{
HarveyPhillips1979,
   Author = {Harvey, Andrew C. and Phillips, G. D. A.},
   Title = {Maximum likelihood estimation of regression models with autoregressive-moving average disturbances},
   Journal = {Biometrika},
   Volume = {66},
   Number = {1},
   Pages = {49-58},
      Year = {1979} }




@incollection{
HarveyShephard1993,
   Author = {Harvey, Andrew C and Shephard, Neil},
   Title = {Structural time series models},
   BookTitle = {Handbook of Statistics, Volume 11},
   Editor = {Maddala, G S and Rao, C R and Vinod, H D},
   Publisher = {Elsevier Science Publishers B V},
   Address = {Amsterdam},
      Year = {1993} }




@article{
HastingsPowell1991,
   Author = {Hastings, A. and Powell, T.},
   Title = {Chaos in a 3-species food-chain},
   Journal = {Ecology},
   Volume = {72},
   Number = {3},
   Pages = {896-903},
      Year = {1991} }




@techreport{
HayesBuchanan2002,
   Author = {Hayes, G. E. and Buchanan, J. B.},
   Title = {Washington state status report for the peregrine falcon},
   Institution = {Washington Department of Fish and Wildlife, Olympia, WA},
      Year = {2002} }




@techreport{
Hayesetal1998,
   Author = {Hays, D. W. and Tirhi, M. J. and Stinson, D. W.},
   Title = {Washington state status report for the sharptailed grouse},
   Institution = {Washington Department Fish and Wildlife, Olympia, WA. 57 pp.},
      Year = {1998} }




@article{
Heiseetal2003,
   Author = {Heise, Kathy and Barrett-Lennard, Lance G. and Saulitis, Eva and Matkin, Craig and Bain, David},
   Title = {Examining the evidence for killer whale predation on Steller sea lions in British Columbia and Alaska},
   Journal = {Aquatic Mammals },
   Volume = {29},
   Number = {3},
   Pages = {325-334},
      Year = {2003} }




@article{
HendersonSearle1979,
   Author = {Henderson, Harold V. and Searle, S. R.},
   Title = {Vec and Vech Operators for Matrices, with Some Uses in Jacobians and Multivariate Statistics },
   Journal = {The Canadian Journal of Statistics},
   Volume = {7},
   Number = {1},
   Pages = {65-81},
      Year = {1979} }




@article{
Hennen2006,
   Author = {Hennen, Daniel},
   Title = {Associations between the Alaska Steller sea lion decline and commercial fisheries},
   Journal = {Ecological Applications},
   Volume = {16},
   Pages = {704-717},
      Year = {2006} }




@article{
Heppelletal1996,
   Author = {Heppell, S. S. and Crowder, L. B. and Crouse, D. T.},
   Title = {Models to evaluate headstarting as a management tool for long-lived turtles},
   Journal = {Ecological Applications},
   Volume = {6},
   Pages = {556-565},
      Year = {1996} }




@article{
Hermanetal2005,
   Author = {Herman, D. P. and Burrows, D. G. and Wade, P. R. and Durban, J. W. and Matkin, C. O. and LeDuc, R. G. and Barrett-Lennard, L. G. and Krahn, M. M.},
   Title = {Feeding ecology of eastern North Pacific killer whales Orcinus orca from fatty acid, stable isotope, and organochlorine analyses of blubber biopsies},
   Journal = {Marine Ecology Progress Series},
   Volume = {302},
   Pages = {275-291},
   Abstract = {Blubber biopsy samples from eastern North Pacific killer whales Orcinus orca were analyzed
for fatty acids, carbon and nitrogen stable isotopes and organochlorine contaminants. Fatty acid
profiles were sufficiently distinct among the 3 reported ecotypes (‘resident,’ ‘transient’ or ‘offshore’)
to enable individual animals to be correctly classified by ecotype and also by mitochondrial DNA
(mtDNA) haplotype. Profiles of PCBs also enabled unambiguous classification of all 3 killer whale
ecotypes, but stable isotope values lacked sufficient resolution. Fatty acid, stable isotope and PCB
profiles of the resident and transient ecotypes were consistent with those expected for these whales
based on their reported dietary preferences (fish for resident whales, marine mammals for transients).
In addition, these ecotype profiles exhibited broad similarity across geographical regions, suggesting
that the dietary specialization reported for resident and transient whales in the well-studied eastern
North Pacific populations also extends to the less-studied killer whales in the western Gulf of Alaska
and Aleutian Islands. Killer whales of the same ecotype were also grouped by region of sample collection.
The mean stable isotope ratios of various regional groups differed considerably, suggesting
that the prey preferences of these North Pacific killer whales may be both region and ecotype specific.
Furthermore, 3 specific ecotypes of killer whales were found to have measured stable isotope
values that were consistent with dietary preferences reported in the literature. Finally, although the
offshore population had blubber fatty acid profiles implicating fish as its primary prey, contaminant
and stable isotope results were equally congruent with predation on marine mammals.},
      Year = {2005} }




@article{
Higginsetal1988,
   Author = {Higgins, Lesley V. and Costa, Daniel P. and Huntley, Anthony C. and LeBoeuf, Burney J.},
   Title = {Behavioral and physiological measurements of maternal investment in the Steller sea lion, Eumetopias jubatus},
   Journal = {Marine Mammal Science},
   Volume = {4},
   Pages = {44-58},
      Year = {1988} }




@book{
HilbornMangel1997,
   Author = {Hilborn, Ray and Mangel, Marc},
   Title = {The ecological detective: confronting models with data},
   Publisher = {Princeton University Press},
   Address = {Princeton, NJ},
      Year = {1997} }




@article{
Hinrichsen2002,
   Author = {Hinrichsen, Rich},
   Title = {The accuracy of alternative stochastic growth rate estimates for salmon populations},
   Journal = {Canadian Journal of Fisheries and Aquatic Sciences},
   Volume = {59},
   Pages = {1014-1023},
      Year = {2002} }




@article{
Hinrichsen2009,
   Author = {Hinrichsen, R.},
   Title = {Population viability analysis for several populations using multivariate state-space models },
   Journal = {Ecological Modelling},
   Volume = {220},
   Number = {9-10},
   Pages = {1197-1202},
      Year = {2009} }




@incollection{
HinrichsenHolmes2009,
   Author = {Hinrichsen, R. and Holmes, E. E.},
   Title = {Using multivariate state-space models to study spatial structure and dynamics},
   BookTitle = {Spatial Ecology},
   Editor = {Cantrell, Robert Stephen and Cosner, Chris and Ruan, Shigui},
   Publisher = {CRC/Chapman Hall},
      Year = {2009} }




@article{
Hogarth2005,
   Author = {Hogarth, W. },
   Title = {Complex research on sea lions is worth the expense},
   Journal = {Nature},
   Volume = {436},
   Pages = {1088},
      Year = {2005} }




@article{
Holmes2001,
   Author = {Holmes, E. E.},
   Title = {Estimating risks in declining populations with poor data},
   Journal = {Proceedings of the National Academy of Sciences of the United States of America},
   Volume = {98},
   Number = {9},
   Pages = {5072-5077},
   Abstract = {Census data on endangered species are often sparse, error-ridden, and confined to only a segment of the population. Estimating trends and extinction risks using this type of data presents numerous difficulties. In particular, the estimate of the variation in year-to-year transitions in population size (the "process error" caused by stochasticity in survivorship and fecundities) is confounded by the addition of high sampling error variation. In addition, the year-to-year variability in the segment of the population that is sampled may be quite different from the population variability that one is trying to estimate. The combined effect of severe sampling error and age- or stage-specific counts leads to severe biases in estimates of population-level parameters. I present an estimation method that circumvents the problem of age- or stage-specific counts and is markedly robust to severe sampling error. This method allows the estimation of environmental variation and population trends for extinction-risk analyses using corrupted census counts-a common type of data for endangered species that has hitherto been relatively unusable for these analyses.},
      Year = {2001} }




@article{
Holmes2004,
   Author = {Holmes, E. E.},
   Title = {Beyond theory to application and evaluation: diffusion approximations for population viability analysis},
   Journal = {Ecological Applications},
   Volume = {14},
   Number = {4},
   Pages = {1272-1293},
   Abstract = {Census data on endangered species are often plagued by problems that make quantitative population viability analysis (PVA) a challenge. This paper addresses four such problems: sampling error, density dependence, nonstable age structure, and population supplementation that masks the true population status. Estimating trends and extinction risks using such corrupted data presents serious parameter estimation difficulties. Here I review diffusion approximation (DA) methods for estimating population status and risks from time series data. A variety of parameterization methods are available for DA models; some correct for data corruption and others do not. I illustrate how stochastic Leslie matrix models can be used to evaluate the performance of a proposed DA model and to select among different DA parameterization methods for a given application. Presenting the uncertainty in estimated risks is critical, especially when the data are highly corrupted and estimated parameters are more uncertain. Using a Bayesian approach, I demonstrate how the level of data support for different risk levels can be calculated using DA parameter likelihood functions.},
      Year = {2004} }




@techreport{
Holmes2010,
   Author = {Holmes, E. E.},
   Title = {Derivation of the {EM} algorithm for constrained and unconstrained MARSS models},
   Institution = {Northwest Fisheries Science Center, Mathematical Biology Program},
   Type = {Technical report},
      Year = {2010} }




@article{
HolmesFagan2002,
   Author = {Holmes, E. E. and Fagan, W. E.},
   Title = {Validating population viability analysis for corrupted data sets},
   Journal = {Ecology},
   Volume = {83},
   Number = {9},
   Pages = {2379-2386},
   Abstract = {Diffusion approximation (DA) methods provide a powerful tool for population viability analysis (PVA) using simple time series of population counts. The e methods have a strong theoretical foundation based on stochastic age-structured models, but their application to data with high sampling error or age-structure cycles has been problematic. Recently, a new method was developed for estimating DA parameters from highly corrupted time series. We conducted an extensive cross-validation of this new method using 189 long-term time series of salmon counts with very high sampling error and nonstable age-structure fluctuations. Parameters were estimated from one segment of a time series, and a subsequent segment was used to evaluate the predictions regarding the risk of crossing population thresholds. We also tested the theoretical distributions of the estimated parameters. The distribution of parameter estimates is an essential aspect of a PVA because it-allows one to calculate confidence levels for risk metrics. This study is the first data-based cross-validation of these theoretical distributions. Our cross-validation analyses found that, when parameterization methods designed for corrupted data sets are used, DA predictions are very robust even for problematic data. Estimates of the probability of crossing population thresholds were unbiased, and the estimated parameters closely followed the expected theoretical distributions.},
      Year = {2002} }




@techreport{
Holmesetal2005,
   Author = {Holmes, E.E. and Fagan, W.F. and Rango, J.J. and Folarin, A. and J.A., Sorensen and Lippe, J.E. and McIntyre, N.E.},
   Title = {Cross validation of quasi-extinction risks from real time series: An examination of diffusion approximation methods},
   Institution = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-NWFSC-67},
      Year = {2005} }




@article{
Holmesetal1994,
   Author = {Holmes, E. E. and Lewis, M.A. and Banks, J. and Veit, R.},
   Title = {Partial differential equation models in ecology},
   Journal = {Ecology},
   Volume = {75},
   Pages = {17-29},
      Year = {1994} }




@article{
Holmesetal2007,
   Author = {Holmes, E. E. and Sabo, J. L. and Viscido, S. V. and Fagan, W. F.},
   Title = {A statistical approach to quasi-extinction forecasting},
   Journal = {Ecology Letters},
   Volume = {10},
   Number = {12},
   Pages = {1182-1198},
      Year = {2007} }




@incollection{
HolmesSemmens2004,
   Author = {Holmes, E. E. and Semmens, B.},
   Title = {Population viability analysis for metapopulations: a diffusion approximation approach},
   BookTitle = {Ecology, Genetics, and Evolution of Metapopulations},
   Editor = {Hanski, Illka and Gaggiotti, Oscar E.},
   Publisher = {Elsevier Press},
   Pages = {565-598},
      Year = {2004} }




@Manual{
MARSSpkg,
   Author = {Holmes, E. E. and Ward, E. J.},
   Title = {MARSS: Multivariate Autoregressive State Space modeling,},
   Url = {http://www.fishbox.iugo-cafe.org/user/e2holmes/MARSS},
   Year = {2010} }
   Note = {R package version 1.0} }



@techreport{
HolmesWard2010,
   Author = {Holmes, E. E. and Ward, E. W.},
   Title = {Analyzing noisy, gappy, and multivariate population abundance data: modeling, estimation, and model selection in a maximum-likelihood framework},
   Institution = {Northwest Fisheries Science Center, Mathematical Biology Program},
      Year = {2010} }




@article{
HolmesYork2003,
   Author = {Holmes, Elizabeth E. and York, Anne E.},
   Title = {Using age structure to detect impacts on threatened populations: a case study using Steller sea lions},
   Journal = {Conservation Biology},
   Volume = {17},
   Pages = {1794-1806},
      Year = {2003} }




@article{
HorneFielding2002,
   Author = {Horne, G. and Fielding, A. H.},
   Title = {Recovery of the peregrine falcon Falco peregrinus in Cumbria, UK, 1966-99},
   Journal = {Bird Study},
   Volume = {49},
   Pages = {229-236},
      Year = {2002} }




@incollection{
Huberetal1991,
   Author = {Huber, H. R. and Beckham, C. and Nisbet, J. S},
   Title = {Effects of the 1982-83 El Niño on elephant seals at the South Farallon Islands},
   BookTitle = {Pinnipeds and El Niño: responses to environmental stress},
   Editor = {Trillmich, F. and Ono, K.},
   Publisher = {Springer-Verlag},
   Address = {Berlin},
   Pages = {219-233},
      Year = {1991} }




@article{
Huberetal1991b,
   Author = {Huber, Harriet R. and Rovetta, Ane C. and Fry, Laurie A. and Johnston, Stuart},
   Title = {Age-specific natality of Northern elephant seals at the South Farallon Islands, California},
   Journal = {Journal of Mammalogy},
   Volume = {72},
   Number = {3},
   Pages = {525-534},
      Year = {1991} }




@article{
Humbertetal2009,
   Author = {Humbert, Jean-Yves and Mills, L. Scott and Horne, Jon S. and Dennis, Brian},
   Title = {A better way to estimate population trends},
   Journal = {Oikos},
   Volume = {118},
   Number = {12},
   Pages = {1940-1946},
      Year = {2009} }




@article{
Hurvichetal1990,
   Author = {Hurvich, C. M. and Shumway, R. H. and Tsai, C. L.},
   Title = {Improved estimators of Kullback-Leibler information for autoregressive model selection in small samples},
   Journal = {Biometrika},
   Volume = {77},
   Pages = {709-719},
      Year = {1990} }




@article{
HurvichTsai1989,
   Author = {Hurvich, C. M. and Tsai, C.-L.},
   Title = {Regression and time series model selection in small samples},
   Journal = {Biometrika},
   Volume = {76},
   Pages = {297-307},
      Year = {1989} }




@article{
InchaustiHalley2001,
   Author = {Inchausti, Pablo and Halley, John},
   Title = {Investigating long-term ecological variability using the Global Population Dynamics Database},
   Journal = {Science},
   Volume = {293},
   Number = {5530},
   Pages = {655-657},
      Year = {2001} }




@article{
InchaustiHalley2002,
   Author = {Inchausti, P. and Halley, J.},
   Title = {The long-term temporal variability and spectral colour of animal populations},
   Journal = {Evolutionary Ecology Research},
   Volume = {4},
   Number = {7},
   Pages = {1033-1048},
   Abstract = {We analysed the temporal variability and the spectral colour of 544 natural populations of 123 species that have been censused for more than 30 years. We compared the tendency for variability to increase with time (equivalent to spectral reddening) using three basic measures: an exponent of increasing variance, the 30 year temporal variability and the spectral exponent. For each, we considered the main ecological correlates: taxon, trophic level, latitude, and habitat type and body size. Our results confirm previous findings that population variability increases over time, and those ecological populations have reddened spectra. This effect is universally prevalent, being similar for populations of different taxa, having different body sizes, belonging to different trophic levels, living at different latitudes and exhibiting different types of population dynamics. Generally, the amount of reddening appears to be greater than that expected from environmental forcing alone. Also, there is no evidence that ecological variability tends towards a finite limit, although the increase of variability does decelerate. Our results suggest that widely used measures of population variability, such as the coefficient of variation or standard deviation of the logarithm of abundance, should be supplemented by measures of either spectral reddening or the rate of increase of the population variance.},
      Year = {2002} }




@article{
InchaustiHalley2003,
   Author = {Inchausti, P. and Halley, J.},
   Title = {On the relation between temporal variability and persistence time in animal populations},
   Journal = {Journal of Animal Ecology},
   Volume = {72},
   Number = {6},
   Pages = {899-908},
   Abstract = {1. The relationship between temporal variability, spectral redness and population persistence for a large number of long-term time series was investigated. Although both intuition and theory suggest that more variability in population abundance would mean greater probability of extinction, previous empirical support for this view has not been conclusive. Possible reasons are the shortage of long-term data and the difficulties of adequately characterizing temporal variability, two issues that are explicitly addressed in this paper. 2.We examined the relationship between population variability and quasi-extinction time (measured as the time required to observe a 90% decline of population abundance) for a large set of data comprising 554 populations for 123 species that were censused for more than 30 years. Two aspects of temporal variability were considered in relation with the quasi-extinction time: a baseline value (coefficient of variation over a fixed, 30-year, time scale), and a measure of the rate of increase of the population variability over time (spectral exponent). 3. The results show that the quasi-extinction time was shorter for populations having higher temporal variability and redder dynamics. The relation between persistence time and population variability was compared for different taxa, trophic levels, habitat type (aquatic and terrestrial) and body sizes and compared with theoretical expectations.},
      Year = {2003} }




@article{
InchaustiWeimerskirch2001,
   Author = {Inchausti, Pablo and Weimerskirch, Henri},
   Title = {Risks of decline and extinction of the endangered Amsterdam albatross and the projected impact of long-line fisheries},
   Journal = {Biological Conservation},
   Volume = {100},
   Pages = {377-386},
      Year = {2001} }




@book{
IUCNRedListCriteria,
   Author = {IUCN},
   Title = {IUCN Red List Categories and Criteria: Version 3.1},
   Publisher = { IUCN Species Survival Commission, IUCN},
   Address = {Gland, Switzerland and Cambridge, UK},
      Year = {2001} }




@article{
Ives1995ec,
   Author = {Ives, Anthony R.},
   Title = {Measuring resilience in stochastic systems},
   Journal = {Ecological Monographs},
   Volume = {65},
   Pages = {217–233},
      Year = {1995} }




@article{
Ivesetal1999,
   Author = {Ives, Anthony R. and Carpenter, S. R. and Dennis, Brian},
   Title = {Community interaction webs and zooplankton responses to planktivory manipulations},
   Journal = {Ecology},
   Volume = {80},
   Pages = {1405–1421},
      Year = {1999} }




@article{
Ivesetal2003,
   Author = {Ives, A. R.  and Dennis, B. and Cottingham, K. L. and Carpenter, S. R.},
   Title = {Estimating community stability and ecological interactions from time-series data},
   Journal = {Ecological Monographs},
   Volume = {73},
   Number = {2},
   Pages = {301-330},
   Abstract = {Natural ecological communities are continuously buffeted by a varying environment, often making it difficult to measure the stability of communities using concepts requiring the existence of an equilibrium point. Instead of an equilibrium point, the equilibrial state of communities subject to environmental stochasticity is a stationary distribution, which is characterized by means, variances, and other statistical moments. Here, we derive three properties of stochastic multispecies communities that measure different characteristics associated with community stability. These properties can be estimated from multispecies time-series data using first-order multivariate autoregressive (MAR( 1)) models. We demonstrate how to estimate the parameters of MAR(1) models and obtain confidence intervals for both parameters and the measures of stability. We also address the problem of estimation when there is observation (measurement) error. To illustrate these methods, we compare the stability of the planktonic communities in three lakes in which nutrient loading and planktivorous fish abundance were experimentally manipulated. MAR(1) models and the statistical methods we present can be used to identify dynamically important interactions between species and to test hypotheses about stability and other dynamical properties of naturally varying ecological communities. Thus, they can be used to integrate theoretical and empirical studies of community dynamics.},
      Year = {2003} }




@article{
Jacksonetal2001,
   Author = {Jackson, Jeremy B. and Kirby, Michael X. and Berger, Wolfgang H. and Bjorndal, Karen A. and Botsford, Louis W. and Bourque, Bruce J. and Bradbury, Roger H. and Cooke, Richard and Erlandson, Jon and Estes, James A. and Hughes, Terence P. and Kidwell, Susan and Lange, Carina B. and Lenihan, Hunter S. and Pandol, John M. and Peterson, Charles H. and Steneck, Robert S. and Tegner, Mia J. and Warner, Robert R.},
   Title = {Historical overfishing and the recent collapse of coastal ecosystems},
   Journal = {Science},
   Volume = {293},
   Pages = {629-638},
      Year = {2001} }




@article{
Jacobietal1996,
   Author = {Jacobi, J.D. and Fancy, S.G. and Giffin, J.G. and Scott, J.M.},
   Title = {Long-term population variability in the palila, an endangered Hawaiian honeycreeper},
   Journal = {Pacific Science},
   Volume = {50},
   Number = {4},
   Pages = {363-370},
      Year = {1996} }




@article{
Jacobsonetal2004,
   Author = {Jacobson, Andrew R. and Provenzale, Antonello and Hardenberg, Achaz von and Bassano, Bruno and Festa-Bianchet, Marco},
   Title = {Climate forcing and density dependence in a mountain ungulate population},
   Journal = {Ecology},
   Volume = {85},
   Pages = {1598-1610},
      Year = {2004} }




@techreport{
Janzetal2000,
   Author = {Janz, D. W. and Bryant, A. A. and Dawe, N. K. and Schwantje, H. and Harper, B. and Nagorsen, D. and Doyle, D. and deLaronde, M. and Fraser, D. and Lindsay, D. and Leigh-Spencer, S. and McLaughlin, R. and Simmons, R.},
   Title = {National recovery plan for the Vancouver Island marmot (Marmota vancouverensis)},
   Institution = {RENEW report no. 19.  34pp.},
      Year = {2000} }




@article{
Jeffriesetal2003,
   Author = {Jeffries, Steven and Huber, Harriet and Calambokidis, John and Laake, Jeffrey},
   Title = {Trends and status of harbor seals in Washington State 1978-1999},
   Journal = {Journal of Wildlife Management},
   Volume = {67},
   Number = {1},
   Pages = {208-219},
      Year = {2003} }




@article{
Jemisonetal2006,
   Author = {Jemison, L. A. and Pendleton, G. W. and Wilson, C. A. and Small, R. J.},
   Title = {Long-term trends in harbor seal numbers at Tugidak Island and Nanvak Bay, AK},
   Journal = {Marine Mammal Science},
   Volume = {22},
   Pages = {339-360},
   Keywords = {Bering sea, top-predators},
   Year = {2006} }




@article{
JohnsonOmland2004,
   Author = {Johnson, Jerald B. and Omland, Kristian S.},
   Title = {Model selection in ecology and evolution},
   Journal = {Trends in Ecology and Evolution},
   Volume = {19},
   Pages = {101-108},
      Year = {2004} }




@book{
JohnsonWichern2007,
   Author = {Johnson, R. A. and Wichern, D. W.},
   Title = {Applied multivariate statistical analysis},
   Publisher = {Prentice Hall},
   Address = {Upper Saddle River, NJ},
      Year = {2007} }




@article{
Jonsenetal2003,
   Author = {Jonsen, I. D. and Myers, R. A. and Flemming, J. M.},
   Title = {Meta-analysis of animal movement using state-space models},
   Journal = {Ecology},
   Volume = {84},
   Number = {11},
   Pages = {3055-3063},
      Year = {2003} }




@incollection{
JouventinWeimerskirch1991,
   Author = {Jouventin, P. and Weimerskirch, H.},
   Title = {Changes in the population size and demography of southern seabirds: Management implications},
   BookTitle = {Bird population studies},
   Editor = {Perrins, C. M. and Lebreton, J. D. and Hirons, G. J. M.},
   Publisher = {Oxford University Press},
   Address = {Oxford},
   Pages = {297–314},
      Year = {1991} }




@article{
Kalman1960,
   Author = {Kalman, R. E.},
   Title = {A new approach to linear filtering and prediction problems},
   Journal = {Journal of Basic Engineering},
   Volume = {82},
   Number = {1},
   Pages = {35-45},
      Year = {1960} }




@article{
Kareivaetal2000,
   Author = {Kareiva, P. and Marvier, M. and McClure, M.},
   Title = {Recovery and management options for spring/summer chinook salmon in the Columbia River Basin},
   Journal = {Science},
   Volume = {290},
   Pages = {977-979},
      Year = {2000} }




@book{
KarlinTaylor1981,
   Author = {Karlin, Samuel and Taylor, Howard M.},
   Title = {A second course in stochastic processes},
   Publisher = {Academic Press},
   Address = {San Diego},
      Year = {1981} }




@techreport{
Keating2002,
   Author = {Keating, K. A.},
   Title = {History of pronghorn population monitoring, research, and management in Yellowstone National Park},
   Institution = {U.S. Geological Service, Northern Rocky Mountain Science Center, Bozeman, Montana. 72pp},
      Year = {2002} }




@book{
KedemFokianos2002,
   Author = {Kedem, Benjamin and Fokianos, Konstantinos},
   Title = {Regression models for time series analysis},
   Publisher = {Wiley and Sons},
   Address = {Hoboken, NJ},
   Series = {Wiley Series in Probability and Statistics},
      Year = {2002} }




@book{
Keilson1979,
   Author = {Keilson, Julien},
   Title = {Markov chain models -- rarity and exponentiality},
   Publisher = {Springer-Verlag},
   Address = {New York},
      Year = {1979} }




@article{
Keithetal2004,
   Author = {Keith, D. A. and McCarthy, M. A. and Regan, H. and Regan, T. and Bowles, C. and Drill, C. and Craig, C. and Pellow, B. and Burgman, M. A. and Master, L. L. and Ruckelshaus, M. and Mackenzie, B. and Andelman, S. J. and Wade, P. R.},
   Title = {Protocols for listing threatened species can forecast extinction},
   Journal = {Ecology Letters},
   Volume = {7},
   Number = {11},
   Pages = {1101-1108},
   Abstract = {Risk-ranking protocols are used widely to classify the conservation status of the world's species. Here we report on the first empirical assessment of their reliability by using a retrospective study of 18 pairs of bird and mammal species (one species extinct and the other extant) with eight different assessors. The performance of individual assessors varied substantially, but performance was improved by incorporating uncertainty in parameter estimates and consensus among the assessors. When this was done, the ranks from the protocols were consistent with the extinction outcome in 70-80% of pairs and there were mismatches in only 10-20% of cases. This performance was similar to the subjective judgements of the assessors after they had estimated the range and population parameters required by the protocols, and better than any single parameter. When used to inform subjective judgement, the protocols therefore offer a means of reducing unpredictable biases that may be associated with expert input and have the advantage of making the logic behind assessments explicit. We conclude that the protocols are useful for forecasting extinctions, although they are prone to some errors that have implications for conservation. Some level of error is to be expected, however, given the influence of chance on extinction. The performance of risk assessment protocols may be improved by providing training in the application of the protocols, incorporating uncertainty in parameter estimates and using consensus among multiple assessors, including some who are experts in the application of the protocols. Continued testing and refinement of the protocols may help to provide better absolute estimates of risk, particularly by re-evaluating how the protocols accommodate missing data.},
      Year = {2004} }




@techreport{
KelleyRau2006,
   Author = {Kelley, J.R., Jr. and Rau, R. D.},
   Title = {American woodcock population status, 2006},
   Institution = {U.S. Fish and Wildlife Service, Laurel, Maryland},
      Year = {2006} }




@article{
Kendall1959,
   Author = {Kendall, M.},
   Title = {Hiawatha designs an experiment},
   Journal = {The American Statistician},
   Volume = {13},
   Pages = {23-24},
      Year = {1959} }




@article{
KlugCottingham2001,
   Author = {Klug, J. L. and Cottingham, K. L.},
   Title = {Interactions among environmental drivers: Community responses to changing nutrients and dissolved organic carbon},
   Journal = {Ecology},
   Volume = {82},
   Number = {12},
   Pages = {3390-3403},
      Year = {2001} }




@article{
KohnAnsley1989,
   Author = {Kohn, Robert and Ansley, Craig F.},
   Title = {A fast algorithm for signal extraction, influence and cross-validation in state-space models},
   Journal = {Biometrika},
   Volume = {76},
   Number = {1},
   Pages = {65-79},
      Year = {1989} }




@article{
Komdeur1996,
   Author = {Komdeur, J.},
   Title = {Breeding of the Seychelles magpie robin (Copsychus sechellarum) and implications for its conservation},
   Journal = {Ibis},
   Volume = {138},
   Pages = {485–498},
      Year = {1996} }




@article{
Koopman1993,
   Author = {Koopman, Siem Jan},
   Title = {Distrubance smoother for state space models},
   Journal = {Biometrika},
   Volume = {80},
   Number = {1},
   Pages = {117-126},
      Year = {1993} }




@article{
Koopmanetal1998,
   Author = {Koopman, Siem Jan and Shephard, Neil and Doornik, Jurgen A.},
   Title = {Statistical algorithms for models in state space using SsfPack 2.2},
   Journal = {Econometrics Journal},
   Volume = {2},
   Pages = {113–166},
      Year = {1999} }




@techreport{
Krahn2006,
   Author = {Krahn, Peggy},
   Title = {Feeding ecology of eastern North Pacific killer whales (Orcinus orca) from fatty acid, stable isotope and organochlorine contaminant profiles of biopsy samples},
      Year = {2006} }




@article{
Lande1993,
   Author = {Lande, R.},
   Title = {Risks of population extinction from demographic and environmental stochasticity and random catastrophes},
   Journal = {American Naturalist},
   Volume = {142},
   Pages = {911-927},
      Year = {1993} }




@book{
Landeetal2003,
   Author = {Lande, R. and Engen, S. and Saether, B.},
   Title = {Stochastic population dynamics in ecology and conservation},
   Publisher = {Oxford University Press},
   Address = {Oxford},
   Series = {Oxford Series in Ecology and Evolution},
      Year = {2003} }




@article{
Landeetal1999,
   Author = {Lande, Russell and Engen, Steinar and Sæther, Bernt-Erik},
   Title = {Spatial scale of population synchrony: environmental correlation versus dispersal and density regulation},
   Journal = {American Naturalist},
   Volume = {154},
   Number = {3},
   Pages = {271-281},
      Year = {1999} }




@article{
LandeOrzack1988,
   Author = {Lande, R. and Orzack, S. H.},
   Title = {Extinction dynamics of age-structured populations in a fluctuating environment},
   Journal = {Proceedings of the National Academy of Science USA},
   Volume = {85},
   Pages = {7418-7421},
      Year = {1988} }




@article{
Lander1981,
   Author = {Lander, R. H.},
   Title = {A life table and biomass estimate for Alaskan fur seals},
   Journal = {Fisheries Research},
   Volume = {1},
   Pages = {55-70},
      Year = {1981} }




@article{
Larralde2004,
   Author = {Larralde, Hernan},
   Title = {A first passage time distribution for a discrete version of the Ornstein-Uhlenbeck process},
   Journal = {Journal of Physics A: Mathematical and General},
   Volume = {37},
   Pages = {3759-3767},
      Year = {2004} }




@article{
Lele2006,
   Author = {Lele, Subhash R.},
   Title = {Sampling variability and estimates of density dependence: a composite likelihood approach},
   Journal = {Ecology},
   Volume = {87},
   Number = {1},
   Pages = {189-202},
      Year = {2006} }




@article{
Leleetal2007,
   Author = {Lele, S. R. and Dennis, B. and Lutscher, F.},
   Title = {Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods},
   Journal = {Ecology Letters},
   Volume = {10},
   Number = {7},
   Pages = {551-563},
   Abstract = {We introduce a new statistical computing method, called data cloning, to calculate maximum likelihood estimates and their standard errors for complex ecological models. Although the method uses the Bayesian framework and exploits the computational simplicity of the Markov chain Monte Carlo (MCMC) algorithms, it provides valid frequentist inferences such as the maximum likelihood estimates and their standard errors. The inferences are completely invariant to the choice of the prior distributions and therefore avoid the inherent subjectivity of the Bayesian approach. The data cloning method is easily implemented using standard MCMC software. Data cloning is particularly useful for analysing ecological situations in which hierarchical statistical models, such as state-space models and mixed effects models, are appropriate. We illustrate the method by fitting two nonlinear population dynamics models to data in the presence of process and observation noise.},
      Year = {2007} }




@incollection{
Levins1970,
   Author = {Levins, R.},
   Title = {Extinction},
   BookTitle = {Some mathematical problems in biology},
   Editor = {Gesternhaber, M. },
   Publisher = {American Mathematical Society},
   Address = {Providence},
   Pages = {77–107},
      Year = {1970} }




@article{
LewontinCohen1969,
   Author = {Lewontin, R. C. and Cohen, D.},
   Title = {On population growth in a randomly varying environment},
   Journal = {Proceedings of the National Academy of Science USA},
   Volume = {62},
   Pages = {1056–1060},
      Year = {1969} }




@article{
Lendenmayeretal1995,
   Author = {Lindenmayer, D. B. and Burgman, M. A. and Akcakaya, H. R. and Lacy, R. C. and Possingham, H. P.},
   Title = {A review of the generic computer-programs Alex, Ramas/Space and Vortex for modeling the viability of wildlife metapopulations},
   Journal = {Ecological Modelling},
   Volume = {82},
   Number = {2},
   Pages = {161-174},
   Abstract = {An assessment is presented of three computer packages, ALEX, RAMAS/space and VORTEX, that have been developed for analyses of metapopulation viability. Their usefulness was assessed in the context of the need to understand the assumptions and limitations of the programs. The study examined many attributes of these programs, ranging from availability and ''user-friendliness'' to the mathematical structure and procedures underpinning the sub-models. Key features and strengths of, and differences between, the various programs were highlighted. They are structured differently and vary in the way processes such as environmental and demographic variation are modelled. Many of these differences reflect what the architects of the programs consider to be the most important factors influencing the viability of metapopulations. These differences mean that the programs may produce different results even for investigations of the same populations. The selection of the most appropriate program should be based on a range of key criteria including: (1) the key question(s) and objectives of the study, and, (2) the strengths, limitations and assumptions that underpin the program and how these match the attributes, life history parameters and available data for the target species. The processes of data assembly, running the programs and reading the accompanying documentation give the user an improved understanding of population behaviour and dynamics. The wide variety of threatened taxa and diversity of conservation problems highlight the value of a broad range of sound, well-developed and relatively error-free packages for simulating metapopulation viability. However, in some cases it may be more appropriate to develop a new program that is tailored specifically to the requirements of a particular management problem.},
   Keywords = {management strategies, model comparison, population viability
simulation-model; population; survival; plant},
   Year = {1995} }




@article{
Lindley2003,
   Author = {Lindley, S. T.},
   Title = {Estimation of population growth and extinction parameters from noisy data},
   Journal = {Ecological Applications},
   Volume = {13},
   Number = {3},
   Pages = {806-813},
   Abstract = {The random-walk-with-drift model of population dynamics is an important tool in conservation biology, partly because its parameters are easily estimated from periodic observations of population size. Estimating the model with noisy data is problematic, however, because the commonly used estimators of process variation are biased if population abundance measurements are imprecise, and a recently developed method that attempts to remove this bias is not robust. In this paper, I show how the random-walk-with-drift model can be applied to noisy time series of population estimates by converting the random-walk-with-drift model to state-space form and applying the Kalman filter to yield the likelihood of the data. The likelihood function allows the variances of the process error and measurement error and the growth rate of the population to be estimated in a way that is robust and fully supported by statistical theory. Comparative analysis using simulated data indicates that the Kalman-filter method reduces the bias in estimates of process variance without yielding negative variance estimates. I apply the method to California sea otter and Yellowstone grizzly bear data to illustrate how the method (and simple extensions) can be used to assess the status of real populations. California sea otters appear to have little risk of extinction over the next 100 years although the population may not be secure over the long term if a recent apparent cessation of population growth persists. The grizzly bear population appears to have responded positively to the 1988 Yellowstone fires, and if the population continues to grow at the average rate observed over the study period, it is extremely unlikely to go extinct.},
   Keywords = {diffusion approximation, extinction model, grizzly bear, Yellowstone population, Kalman filter, measurement errors bids parameter estimates, parameter estimation, random walk, sea otter, California population, state-space model
yellowstone grizzly bears; observation error; probability; models},
   Year = {2003} }




@article{
LoeryNichols1985,
   Author = {Loery, G. and Nichols, J. D.},
   Title = {Dynamics of a black-capped chickadee population},
   Journal = {Ecology},
   Volume = {66},
   Pages = {1195–1203},
      Year = {1985} }




@incollection{
Loughlin1997,
   Author = {Loughlin, T. R. },
   Title = {Using the phylogeographic method to identify Steller sea lion stocks},
   BookTitle = {Molecular Genetics of Marine MammalsMolecular Genetics of Marine Mammals},
   Editor = {Dizon, A. E. and Chivers, S. J. and Perrin, W. F.},
   Publisher = {Society for Marine Mammalogy, Spec. Publ. 3.},
   Pages = {159-171},
      Year = {1997} }




@inproceedings{
LoughlinMerrick1988,
   Author = {Loughlin, T. R. and Merrick, R. L.},
   Title = {Comparison of commercial harvest of walleye pollock and northern sea lion abundance in the Bering Sea and Gulf of Alaska},
   BookTitle = {International Symposium on Biology and Management of Walleye Pollock},
   Address= {University of Alaska, Anchorage, Alaska},
   Publisher = {Alaska Sea Grant Report 89-1},
   Pages = {679-700},
      Year = {1988} }




@article{
Loughlinetal2003,
   Author = {Loughlin, T. R. and Sterling, J. T. and Merrick, R. L. and Sease, J. L. and York, A. E.},
   Title = {Diving behavior of immature Steller sea lions (Eumetopias jubatus)},
   Journal = {Fishery Bulletin},
   Volume = {101},
   Pages = {566-582},
      Year = {2003} }




@article{
LoughlinYork2000,
   Author = {Loughlin, T. R. and York, A. E.},
   Title = {An accounting of the sources of Steller sea lion, Eumetopias jubatus, mortality},
   Journal = {Marine Fisheries Review},
   Volume = {62},
   Number = {4},
   Pages = {40-45},
      Year = {2000} }




@article{
Ludwig1996,
   Author = {Ludwig, D.},
   Title = {Uncertainty and the assessment of extinction probabilities},
   Journal = {Ecological Applications},
   Volume = {6},
   Number = {4},
   Pages = {1067-1076},
   Abstract = {A proper assessment of the probability of early collapse or extinction of a population requires consideration of our uncertainty about crucial parameters and processes. Simple simulation approaches to assessment consider only a single set of parameter values, but what is required is consideration of all more or less plausible combinations of parameters. Bayesian decision theory is an appropriate tool for such assessment. I contrast standard (frequentist) and Bayesian approaches to a simple regression problem. I use these results to calculate the probability of early population collapse for three data sets relating to the Palila, Laysan Finch, and Snow Goose. The Bayesian results imply much higher risk of early collapse than maximum likelihood methods. This difference is due to large probabilities of early collapse for certain parameter values that are plausible in light of the data. Because of simplifying assumptions, these results are not directly applicable to assessment. Nevertheless they imply that maximum likelihood and similar methods based upon point parameter estimates will grossly underestimate the risk of early collapse.},
      Year = {1996} }




@article{
Ludwig1999,
   Author = {Ludwig, D.},
   Title = {Is it meaningful to estimate a probability of extinction?},
   Journal = {Ecology},
   Volume = {80},
   Number = {1},
   Pages = {298-310},
   Abstract = {I calculate probabilities of quasi-extinction of natural populations from time series of census data or estimated abundance. The results depend sensitively upon estimated parameters. Short time series or poor fits of the model to data lead to wide confidence intervals for the probability of quasi-extinction. In many cases there are substantial errors in estimated abundance. These errors further increase the size of the confidence interval, to the point where the estimates may become meaningless. A further complication is that natural populations are subject to occasional catastrophes, and these increase the probability of extinction. Unfortunately, evidence concerning the frequency of occurrence of catastrophes and the distribution of their sizes is generally lacking. Assessments that fail to compute confidence intervals or that disregard observation errors or possible catastrophes may be unduly optimistic about the viability of natural populations.},
      Year = {1999} }




@article{
LunnBoyd1993,
   Author = {Lunn, N.J. and Boyd, I.L.},
   Title = {Influence of maternal characteristics and environmental variation on reproduction in Antarctic fur seals},
   Journal = {Symposium of the Zoological Society of London},
   Volume = {66},
   Pages = {115-129},
      Year = {1993} }




@article{
Lunnetal1994,
   Author = {Lunn, N. J. and Boyd, I. L. and Croxall, J. P.},
   Title = {Reproductive performance of female Antarctic fur seals: the influence of age, breeding experience, environmental variation and individual quality},
   Journal = {The Journal of Animal Ecology},
   Volume = {63},
   Number = {4},
   Pages = {827-840},
      Year = {1994} }




@book{
MacArthurWilson1967,
   Author = {MacArthur, Robert H. and Wilson, E.O.},
   Title = {The theory of island biogeography},
   Publisher = {Princeton University Press},
   Address = {Princeton},
      Year = {1967} }




@article{
MaceLande1991,
   Author = {Mace, Georgina M. and Lande, Russell},
   Title = {Assessing extinction threats: toward a reevaluation of IUCN threatened species categories},
   Journal = {Conservation Biology},
   Volume = {5},
   Number = {2},
   Pages = {148–157},
      Year = {1991} }




@article{
Maniscalcoetal2006,
   Author = {Maniscalco, John M. and Parker, Pamela and Atkinson, Shannon},
   Title = {Interseasonal and interannual measures of maternal care among individual Steller sea lions (Eumetopias jubatus)},
   Journal = {Journal of Mammalogy},
   Volume = {87},
   Number = {2},
   Pages = {304-311},
      Year = {2006} }




@inproceedings{
Masatomi1987,
   Author = {Masatomi, H.},
   Title = {Population dynamics of red-crowned cranes in Hokkaido since the 1950s},
   BookTitle = {Proceedings of the 1987 International Crane Workshop},
   Publisher = {International Crane Foundation, Baraboo, WI},
   Pages = {297–299},
      Year = {1987} }




@article{
McBeath2004,
   Author = {McBeath, J.},
   Title = {Greenpeace v. National Marine Fisheries Service: Steller sea lions and commercial fisheries in the North Pacific},
   Journal = {Alaska Law Review},
   Volume = {21},
   Pages = {1-42},
      Year = {2004} }




@article{
McCarthyetal2003,
   Author = {McCarthy, M. A. and Andelman, S. J. and Possingham, H. P.},
   Title = {Reliability of relative predictions in population viability analysis},
   Journal = {Conservation Biology},
   Volume = {17},
   Number = {4},
   Pages = {982-989},
   Abstract = {Despite numerous claims that population viability analysis (PYA) makes reliable predictions of the relative risks of extinction, there is little evidence to support this assertion. To assess the veracity of the claim, we investigated uncertainty in the relative predictions of a PVA model with simulation experiments. We used a stochastic Ricker model to investigate the reliability of predicted changes in risks of decline in response to changes in parameters, the reliability of ranking species in terms of their relative threat, and the reliability of choosing the better of two management decisions. The predicted changes in risks of decline within 100 years were more reliable than absolute predictions. We made useful predictions of relative risks using only 10 years of data. Across 160 different parameter combinations, the rank correlation between the true risks of extinction within 100 years and predicted risks was 0.59 with 10 years of data, increasing to 0.89 with 100 years of data. We identified the better of two management strategies 67-74% of the time using 10 years of data, increasing to 92-93% of the time with 100 years of data. Our results demonstrate that, despite considerable uncertainty in the predicted risks of decline, PVA may reliably contribute to the management of threatened species.},
      Year = {2003} }




@book{
McCullaghNelder1989,
   Author = {McCullagh, P. and Nelder, J. A.},
   Title = {Generalized linear models},
   Publisher = {Chapman and Hall},
   Address = {London},
      Year = {1989} }




@article{
McFarlaneetal2000,
   Author = {McFarlane, Gordon A. and King, Jacquelynne R. and Beamish, Richard J.},
   Title = {Have there been recent changes in climate? Ask the fish},
   Journal = {Progress in Oceanography},
   Volume = {47},
   Pages = {147-169},
      Year = {2000} }




@book{
McLachlanKrishnan2008,
   Author = {McLachlan, Geoffrey J. and Krishnan, Thriyambakam},
   Title = {The {EM} algorithm and extensions},
   Publisher = {John Wiley and Sons, Inc.},
   Address = {Hoboken, NJ},
   Edition = {2nd},
      Year = {2008} }




@article{
McLaughlinetal2002,
   Author = {McLaughlin, John F. and Hellmann, Jessica J. and Boggs, Carol L. and Ehrlich, Paul R.},
   Title = {The route to extinction: population dynamics of a threatened butterfly},
   Journal = {Oecologia},
   Volume = {132},
   Pages = {538–548},
      Year = {2002} }




@article{
MeirFagan2000,
   Author = {Meir, E. and Fagan, W. F.},
   Title = {Will observation error and biases ruin the use of simple extinction models?},
   Journal = {Conservation Biology},
   Volume = {14},
   Number = {1},
   Pages = {148-154},
      Year = {2000} }




@article{
Merrick1997,
   Author = {Merrick, R. L.},
   Title = {Current and Historical Roles of Apex Predators in the Bering Sea Ecosystem},
   Journal = {Journal of Northwest Atlantic Fishery Science},
   Volume = {22},
   Pages = {343–355},
   Abstract = {Large population declines (>50%) since the early-1970s of some eastern Bering Sea
and Aleutian Island apex predator populations (Steller sea lions, murres, and kittiwakes)
suggest that major changes have occurred in the structure of the Bering Sea ecosystem.
One cause of the decline in mammalian and avian predator populations may be a decrease
in availability or abundance of preferred prey (e.g. capelin, juvenile walleye pollock).
However, adult groundfish biomass has generally been at high levels, and periods of high
adult groundfish biomass coincide with periods of decline of sea lion and seabird
populations. Adult groundfish may, therefore, be out-competing other predators for their
common prey (i.e. small schooling fish). Three factors may have led to increases in adult
groundfish biomass in the southeastern Bering Sea, changes in environmental conditions,
present commercial fishing practices, and predator release resulting from overharvesting
of marine mammals and some fishes during 1955–75. If the decline in whale and fur seal
populations during 1955–75 contributed to the current high biomass of groundfish, then
marine mammals once (but no longer) exerted a structuring effect on the Bering Sea ecosystem.
The current high abundance of piscivorous adult groundfish in the eastern Bering
Sea may, therefore, impede the recovery of marine mammal and bird populations to historical
levels.
Key words: Bering Sea, ecosystem, groundfish, predators,},
      Year = {1997} }




@article{
MerrickLoughlin1997,
   Author = {Merrick, R. L. and Loughlin, T.},
   Title = {Foraging behavior of adult female and young-of-year Steller sea lions in Alaskan waters},
   Journal = {Canadian Journal of Zoology},
   Volume = {75},
   Pages = {776-786},
      Year = {1997} }




@article{
Merricketal1987,
   Author = {Merrick, R. L. and Loughlin, T. R. and Calkins, D. G.},
   Title = {Decline in abundance of the northern sea lion, Eumetopias jubatus, in Alaska, 1956-86},
   Journal = {Fishery Bulletin},
   Volume = {85},
   Pages = {351-365},
      Year = {1987} }




@book{
Merricketal1996,
   Author = {Merrick, R. L. and Loughlin, T. R. and Calkins, D.G.},
   Title = {Hot branding: A technique for long-term marking of pinnipeds},
   Publisher = {U.S Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-68, 21p.},
      Year = {1996} }




@article{
Meyeretal1998,
   Author = {Meyer, A. H. and Schmidt, B. R. and Grossenbacher, K.},
   Title = {Analysis of three amphibian populations with quarter-century long time-series},
   Journal = {Proceedings of the Royal Society of London Ser. B},
   Volume = {265},
   Pages = {523-528},
      Year = {1998} }




@article{
MicolJouventin2001,
   Author = {Micol, T. and Jouventin, P.},
   Title = {Long-term population trends in seven Antarctic seabirds at Pointe Géologie (Terre Adélie): human impact compared with environmental change},
   Journal = {Polar Biology},
   Volume = {24},
   Pages = {175-185},
      Year = {2001} }




@article{
MiddletonNisbet1997,
   Author = {Middleton, D. A. J. and Nisbet, R. M.},
   Title = {Population persistence time: estimates, models, and mechanisms},
   Journal = {Ecological Applications},
   Volume = {7},
   Pages = {107–117},
      Year = {1997} }




@phdthesis{
Milette1999,
   Author = {Milette, Linda Leontine},
   Title = {Behaviour of lactating Steller sea lions (Eumetopias jubatus) during the breeding season: a comparison between a declining and stable population in Alaska},
   School = {University of British Columbia},
   Type = {M.S. thesis},
      Year = {1999} }




@article{
MiletteTrites2003,
   Author = {Milette, Linda L. and Trites, Andrew W.},
   Title = {Maternal attendance patterns of Steller sea lions (Eumetopias jubatus) from stable and declining populations in Alaska},
   Journal = {Canadian Journal of Zoology},
   Volume = {81},
   Pages = {340–348},
   Abstract = {Maternal attendance patterns of Alaskan Steller sea lions (Eumetopias jubatus) were compared during the
summer breeding seasons in 1994 and 1995 at Sugarloaf Island (a declining population) and Lowrie Island (a stable
population). Our goal was to determine whether there were differences in maternal attendance between the two populations
that were consistent with the hypothesis that lactating Steller sea lions in the area of decline were food-limited
during summer. Our a priori expectations were based on well-documented behavioural responses of otariids to reduced
prey availability. We found that foraging trips were significantly shorter in the area of population decline, counter to
initial predictions. The mean length of foraging trips in the declining area was 19.5 h compared with 24.9 h in the stable
area. In contrast, the mean perinatal period (time between parturition and first feeding trip) was significantly longer
in the area of decline (9.9 versus 7.9 days), again countering initial predictions. The mean length of shore visits for the
declining population was also significantly longer (27.0 h compared with 22.6 h where the population was stable). For
both populations, the mean time that mothers foraged increased as pups grew older, whereas the time that they spent
on shore with their pups became shorter. Behavioural observations of maternal attendance patterns are inconsistent with
the hypothesis that lactating Steller sea lions from the declining population had difficulty obtaining prey during summer.},
      Year = {2003} }




@article{
MillarMeyer2000,
   Author = {Millar, R. B. and Meyer, R.},
   Title = {Bayesian state-space modeling of age structured data: fitting a model is just the beginning},
   Journal = {Canadian Journal of Fisheries and Aquatic Sciences},
   Volume = {57},
   Pages = {43–50},
      Year = {2000} }




@article{
Miller2001,
   Author = {Miller, Craig},
   Title = {Long-term monitoring of a breeding colony of white herons (Egretta alba) on the Waitangiroto River, South Westland, New Zealand},
   Journal = {Notornis},
   Volume = {48},
   Pages = {157-163},
      Year = {2001} }




@article{
MilnerGullandeetal2000,
   Author = {Milner-Gulland, E. J. and Coulson, T. N. and Clutton-Brock, T. H.},
   Title = {On harvesting a structured ungulate population},
   Journal = {Oikos},
   Volume = {88},
   Pages = {592–602},
      Year = {2000} }




@article{
MizrochRice2006,
   Author = {Mizroch, Sally A. and Rice, Dale W.},
   Title = {Have North Pacific killer whales switched prey species in response to depletion of the great whale populations?},
   Journal = {Marine Ecology Progress Series},
   Volume = {310},
   Pages = {235–246},
      Year = {2006} }




@article{
Moore1991,
   Author = {Moore, N. W.},
   Title = {The development of dragonfly communities and the consequences of territorial behaviour: A 27-year study on small ponds at Woodwalton Fen, Cambridgeshire, United Kingdom},
   Journal = {Odontologica},
   Volume = {20},
   Pages = {203–231},
      Year = {1991} }




@article{
Morales1999,
   Author = {Morales, L. M.},
   Title = {Viability in a pink environment: why "white noise models can be dangerous},
   Journal = {Ecology Letters},
   Volume = {2},
   Number = {4},
   Pages = {228-232},
   Abstract = {Analysis of long time series suggests that environmental fluctuations may be accurately represented by 1/f noise (pink noise), where temporal correlation is found at several scales, and the range of fluctuations increases over time. Previous studies on the effects of coloured noise on population dynamics used first or second order autoregressive noise. I examined the importance of coloured noise for extinction risk using true 1/f noise. I also considered the problem of estimating extinction risk with a Limited sample of environmental variation. Pink noise environments increased extinction risk in random walk models where environmental variation affected the growth rate. However, pink noise environments decreased extinction risk in the Ricker model where environmental variation modified the carrying capacity. Underestimation of environmental variance almost always yielded underestimation of extinction risk. For either population viability analysis or management, we should carefully consider the long-term behaviour of the environment as well as how we include environmental noise in population models.},
      Year = {1999} }




@article{
Morrisetal2002,
   Author = {Morris, W. F. and Bloch, P. L. and Hudgens, B. R. and Moyle, L. C. and Stinchcombe, J. R.},
   Title = {The use of population viability analysis in endangered species recovery planning: past trends and recommendations for future improvement},
   Journal = {Ecological Applications},
   Volume = {12},
   Pages = {708-712},
      Year = {2002} }




@book{
MorrisDoak2003,
   Author = {Morris, W. F. and Doak, D.F.},
   Title = {Quantitative conservation biology: theory and practice of population viability analysis},
   Publisher = {Sinauer Associates},
   Address = {Sunderland, MA USA},
      Year = {2003} }




@article{
MyersWorm2003,
   Author = {Myers, R. A. and Worm., B.},
   Title = {Rapid worldwide depletion of predatory fish communities},
   Journal = {Nature},
   Volume = {423},
   Pages = {280-283},
      Year = {2003} }




@article{
NappHunt2001,
   Author = {Napp, Jeffrey M. and Hunt, George L.},
   Title = {Anomalous conditions in the south-eastern Bering Sea 1997: linkages among climate, weather, ocean, and Biology},
   Journal = {Fisheries Oceanography},
   Volume = {10},
   Number = {1},
   Pages = {61-68},
      Year = {2001} }




@book{
NRC1996,
   Author = {National Research Council},
   Title = {The Bering Sea ecosystem},
   Publisher = {The National Academies Press},
   Address = {Washington, DC},
      Year = {1996} }




@book{
NRC2003,
   Author = {National Research Council},
   Title = {Decline of the Steller sea lion in Alaskan waters: Untangling food webs and fishing nets},
   Publisher = {The National Academies Press},
   Address = {Washington, DC},
      Year = {2003} }




@article{
Newby1973,
   Author = {Newby, T.C.},
   Title = {Changes in Washington State harbor seal population, 1942-1972},
   Journal = {Murrelet},
   Volume = {54},
   Pages = {5-6},
      Year = {1973} }




@article{
Newman1998,
   Author = {Newman, K. B. },
   Title = {State-space modeling of animal movement and mortality with application to salmon},
   Journal = {Biometrics},
   Volume = {54},
   Pages = {1290–1314},
      Year = {1998} }




@article{
Newmanetal2006,
   Author = {Newman, K. B. and Buckland, S. T. and Lindley, S. T. and Thomas, L. and Fern´andez, C. .  },
   Title = {Hidden process models for animal population dynamics},
   Journal = {Ecological Applications},
   Volume = {16},
   Pages = {74–86},
      Year = {2006} }




@article{
Newmanetal2008,
   Author = {Newman, Ken B. and Fernández, Carmen and Thomas, Len and Buckland, Stephen T.},
   Title = {Monte carlo inference for state space models of wild animal populations},
   Journal = {Biometrics},
   Volume = {in press},
      Year = {2008} }




@book{
Newton1998,
   Author = {Newton, I.},
   Title = {Population limitation in birds},
   Publisher = {Academic Press},
   Address = {San Diego, CA.},
   Note = {p. 1–27 and 449–480},
      Year = {1998} }




@article{
NicholsonPossingham2007,
   Author = {Nicholson, Emily and Possingham, Hugh P.},
   Title = {Making conservation decisions under uncertainty for the persistence of multiple species},
   Journal = {Ecological Applications},
   Volume = {17},
   Number = {1},
   Pages = {251–265},
      Year = {2007} }




@techreport{
NMFS1992,
   Author = {NMFS},
   Title = {Final recovery plan for the Steller sea lion (Eumetopias jubatus)},
   Institution = {National Marine Fisheries Service},
      Year = {1992} }




@article{
NMFS1997,
   Author = {NMFS},
   Title = {Threatened fish and Wildlife; change in listing status of Steller sea lions under the Endangered Species Act},
   Journal = {Federal Register},
   Volume = {62},
   Number = {86},
   Pages = {24345-24355},
      Year = {1997} }




@article{
NMML,
   Author = {NMML},
      Year = {Unpublished data} }




@article{
Nobileetal1985,
   Author = {Nobile, A. G. and Ricciardi, L. M. and Sacerdote, L.},
   Title = {Exponential trends of Ornstein-Uhlenbeck first-passage-time densities},
   Journal = {Journal of Applied Probability},
   Volume = {22},
   Pages = {360–369},
      Year = {1985} }




@article{
NorstromMuir1994,
   Author = {Norstrom, R. J. and Muir, D. C.},
   Title = {Chlorinated hydrocarbon contaminants in Arctic marine mammals},
   Journal = {Science of the Total Environment},
   Volume = {154},
   Pages = {107-128},
      Year = {1994} }




@book{
Okubo1980,
   Author = {Okubo, A.},
   Title = {Diffusion and ecological problems: mathematical models},
   Publisher = {Springer-Verlag},
   Address = {New York},
   Volume = {10},
   Series = {Biomathematics},
      Year = {1980} }




@book{
OkuboLevin2001,
   Author = {Okubo, A. and Levin, S.},
   Title = {Diffusion and ecological problems: modern perspectives},
   Publisher = {Springer-Verlag},
   Address = {New York},
      Year = {2001} }




@article{
Olssonetal2007,
   Author = {Olsson, R. K. and Petersen, K. B. and Lehn-Schioler, T.},
   Title = {State-space models: from the EM algorithm to a gradient approach},
   Journal = {Neural Computation},
   Volume = {19},
   Number = {4},
   Pages = {1097-1111},
      Year = {2007} }




@Manual{
OSNZ,
   Author = {Ornithological Society of New Zealand},
   Title = {, Beach Patrol Data Base, PO Box 12397, Wellington, New Zealand},
   Year = {} }



@techreport{
O'SheaBogan2003,
   Author = {O'Shea, T.J. and Bogan, M.A.},
   Title = {Monitoring trends in bat populations of the United States and territories: problems and prospects},
   Institution = {U.S. Geological Survey, Biological Resources Discipline, Information and Technology Report, USGS/BRD/ITR-2003-0003},
      Year = {2003} }




@article{
Ottichiloetal2000,
   Author = {Ottichilo, W. K. and Leeuw, J. De and Skidmore, A. K. and Prins, H. H. T. and Said, M. Y.},
   Title = {Population trends of large non-migratory wild herbivores and livestock in the Masai Mara ecosystem, Kenya, between 1977 and 1997},
   Journal = {African Journal of Ecology},
   Volume = {38},
   Pages = {202-216},
      Year = {2000} }




@techreport{
PFC2002,
   Author = {Pacific Flyway Council},
   Title = {Pacific Flyway Management Plan for Pacific Brant},
   Institution = {U. S. Fish and Wildlife Service},
      Year = {2002} }




@article{
Packeretal1999,
   Author = {Packer, C. and Altizer, S. and Appel, M. and Brown, E. and Martenson, J. and O’Brien, S. J. and Roelke-Parker, M. and Hofmann-Lehman, R. and Lutz, H.},
   Title = {Viruses of the Serengeti: patterns of infection and mortality in African lions},
   Journal = {Journal of Animal Ecology},
   Volume = {68},
   Pages = {1161–1178},
      Year = {1999} }




@article{
Parr1992,
   Author = {Parr, R. },
   Title = {The decline to extinction of a population of golden plover in North-East Scotland},
   Journal = {Ornis Scand.},
   Volume = {23},
   Pages = {152–158},
      Year = {1992} }




@article{
PascualAdkison1994,
   Author = {Pascual, M. A. and Adkison, M. D.},
   Title = {The decline of northern sea lion populations: demography, harvest, or environment?},
   Journal = {Ecological Applications},
   Volume = {4},
   Pages = {393-403},
      Year = {1994} }




@article{
Paulyetal1998,
   Author = {Pauly, D. and Christensen, V. and Dalsgaard, J. and Froese, R. and F. Torres, Jr. },
   Title = {Fishing down marine food webs},
   Journal = {Science},
   Volume = {279},
   Pages = {860-863},
      Year = {1998} }




@article{
Pearlman1980,
   Author = {Pearlman, J. G.},
   Title = {An algorithm for the exact likelihood of a high-order autoregressivemoving average process},
   Journal = {Biometrika},
   Volume = {67},
   Number = {1},
   Pages = {232–233},
      Year = {1980} }




@article{
Pendletonetal2006,
   Author = {Pendleton, Grey W. and Pitcher, Kenneth W. and Fritz, Lowell W. and York, Anne E. and Raum-Suryan, Kimberly L. and Loughlin, Thomas R. and Calkins, Donald G. and Hastings, Kelly K. and Gelatt., Thomas S.},
   Title = {Survival of Steller sea lions in Alaska: a comparison of increasing and decreasing populations},
   Journal = {Canadian Journal of Zoology},
   Volume = {84},
   Pages = {1163-1172},
      Year = {2006} }




@techreport{
Penzer2001,
   Author = {Penzer, Jeremy},
   Title = {Critical values for time series diagnostics},
   Institution = {Department of Statistics, London School of Economics},
      Year = {2001} }




@book{
Perez2003,
   Author = {Perez, M. A.},
   Title = {Compilation of incidental marine mammal take data from the domestic and joint venture groundfish fisheries in the U. S. EEZ of the North Pacific, 1989-2001.},
   Publisher = {U.S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-138, 145p.},
      Year = {2003} }




@techreport{
PerezLoughlin1991,
   Author = {Perez, M. A. and Loughlin, T. R.},
   Title = {Incidental catch of marine mammals by foreign and joint venture trawl vessels in the U. S. EEZ of the North Pacific, 1973-88},
   Institution = {U.S. Department of Commerce, NOAA Tech. Rep. 104},
   Number = {104},
      Year = {1991} }




@article{
PetersonSilvy1996,
   Author = {Peterson, M. J and Silvy, N. J.},
   Title = {Reproductive stages limiting productivity of the endangered Attwater’s prairie chicken},
   Journal = {Conservation Biology},
   Volume = {10},
   Pages = {1264–1276},
      Year = {1996} }




@article{
Petersonetal1998,
   Author = {Peterson, R. O. and Thomas, N. J. and Thurber, J. M. and Vucetich, J. A. and Waite, T. A.},
   Title = {Population limitation and the wolves of Isle Royale},
   Journal = {Journal of Mammalogy},
   Volume = {79},
   Pages = {828–841},
      Year = {1998} }




@article{
Pettersson1985,
   Author = {Pettersson, B.},
   Title = {Extinction of an isolated population of the middle spotted woodpecker Dendrocopos medius (L.) in Sweden and its relation to general theories on extinction},
   Journal = {Biological Conservation},
   Volume = {32},
   Pages = {335–353},
      Year = {1985} }




@book{
Pimm1991,
   Author = {Pimm, S.},
   Title = {The balance of nature? ecological issues in the conservation of species and communities},
   Publisher = {Chicago University Press},
   Address = {Chicago, IL},
      Year = {1991} }




@article{
PimmRedfearn1988,
   Author = {Pimm, S. and Redfearn, A.},
   Title = {The variability of natural populations},
   Journal = {Nature},
   Volume = {334},
   Pages = {613-614},
      Year = {1988} }




@article{
Pimmetal1988,
   Author = {Pimm, S. L. and Jones, H. L. and Diamond, J.},
   Title = {On the risk of extinction},
   Journal = {American Naturalist},
   Volume = {132},
   Pages = {757-785},
      Year = {1988} }




@article{
Pistoriusetal2001,
   Author = {Pistorius, P. A. and Bester, M. N. and Kirkman, S. P. and Taylor, F. E.},
   Title = {Temporal changes in fecundity and age at sexual matruity of southern elephant seals at Marion Island},
   Journal = {Polar Biology},
   Volume = {24},
   Pages = {343-348},
      Year = {2001} }




@article{
Pitcher1990,
   Author = {Pitcher, K. W.},
   Title = {Major decline in number of harbor seals, Phoca vitulina richardsi, on Tugidak Island, Gulf of Alaska},
   Journal = {Marine Mammal Science},
   Volume = {6},
   Pages = {121–134},
      Year = {1990} }




@article{
PitcherCalkins1981,
   Author = {Pitcher, Kenneth W. and Calkins, Donald G.},
   Title = {Reproductive biology of Steller sea lions in the Gulf of Alaska},
   Journal = {Journal of Mammalogy},
   Volume = {62},
   Number = {3},
   Pages = {599-605},
      Year = {1981} }




@article{
Pitcheretal1998,
   Author = {Pitcher, K. W. and Calkins, D. G. and Pendleton, G. W.},
   Title = {Reproductive performance of female Steller sea lions: an energetic-based reproductive strategy?},
   Journal = {Canadian Journal of Zoology},
   Volume = {76},
   Pages = {2075-2083},
      Year = {1998} }




@article{
PitcherMcAllister1981,
   Author = {Pitcher, K.W and McAllister, D.C.},
   Title = {Movements and haul out behavior of radio-tagged harbor seals, /textit{Phoca vitulina}},
   Journal = {Canadian Field Naturalist},
   Volume = {95},
   Pages = {292-297},
      Year = {1981} }




@article{
Pitcheretal,
   Author = {Pitcher, K.W. and Olesiuk, P. F and Brown, R. F. and Lowry, M. S. and Jeffries, S. J. and Sease, J. L. and Perryman, W. L. and Stinchcomb, C. E. and Lowry, L. F.},
   Title = { Status and trends in abundance and distribution of the eastern Steller sea lion (Eumetopias jubatus) population},
   Journal = {Fishery Bulletin},
      Year = {In press} }




@techreport{
Plotkin1995,
   Author = {Plotkin, P.T.},
   Title = {National Marine Fisheries Service and U. S. Fish and Wildlife Service status reviews for sea turtles listed under the Endangered Species Act of 1973},
   Institution = {National Marine Fisheries Service, Silver Spring, Maryland},
      Year = {1995} }




@book{
Polya1968,
   Author = {Polya, George},
   Title = {Mathematics and Plausible Reasoning, Vol II},
   Publisher = {Princeton University Press},
   Address = {Princeton, NJ},
      Year = {1968} }




@article{
Poncetetal2006,
   Author = {Poncet, Sally and Robertson, Graham and Phillips, Richard A. and Lawton, Kieran and Phalan, Ben and Trathan, Philip N. and Croxall, John P.},
   Title = {Status and distribution of wandering, black-browed and grey-headed albatrosses breeding at South Georgia},
   Journal = {Polar Biology},
   Volume = {29},
   Pages = {772–781},
      Year = {2006} }




@article{
Princeetal1994,
   Author = {Prince, P. A. and Rothery, P. and Croxall, J. P. and Wood, A. G. },
   Title = {Population dynamics of black-browed and grey-headed albatrosses Diomedea melanophris and D. chrysostoma at Bird Island, South Georgia},
   Journal = {Ibis},
   Volume = {136},
   Number = {1},
   Pages = {50-71},
   Abstract = {Population dynamics of Black-browed and Grey-headed Albatrosses Diomedea melanophris and D. chrysostoma were studied at Bird Island, South Georgia, for 17 consecutive years (1975-1991). Over this period, almost all the Grey-headed Albatross colonies decreased at an average rate of 1.8% per annum. Although the total Black-browed Albatross population increased (at 0.8% p.a.), 14 of the 23 colonies (including both study colonies) decreased. Black-browed Albatrosses follow an annual breeding cycle: over 80% of birds successful in rearing a chick and 75% of those failing to do so returned to breed the next year, 5-10% of both categories delayed one further year (even when still paired). Grey-headed Albatrosses are essentially biennial: <1% of successful birds bred the next year, 68% returned to breed 2 years later, 11% the next and 5% not until the fourth year. In contrast, over 50% of birds that failed to rear a chick bred the next year, 23% delayed for one further year. Birds which failed after March did not return the next year, whereas 80% of birds which failed during incubation did breed the following year. Grey-headed Albatrosses showed higher (39%) and more consistent breeding success than Black-browed Albatrosses (29%, including 4 years of almost complete breeding failure); hatching success was similar in both species, and fledging success was the main source of variation in Black-browed Albatross productivity. We link this to the dependence of this species on Antarctic krill, a variable resource largely absent in 3 of the 4 years of widespread failure.},
      Year = {1994} }




@misc{
RCran,
   Author = {R Development Core Team},
   Title = {R: A language and environment for statistical computing},
   Publisher = {R Foundation for Statistical Computing, Vienna, Austria},
   Year = {2009} }




@incollection{
RagenLavigne1999,
   Author = {Ragen, T. J. and Lavigne, D. M.},
   Title = {The Hawaiian monk seal: Biology of an endangered species},
   BookTitle = {Conservation and management of marine mammals},
   Editor = {Twiss, J. and Reeves, R.},
   Publisher = {Smithsonian Institution Press},
   Address = {Washington, DC},
   Pages = {224-245},
      Year = {1999} }




@article{
Rauch1963,
   Author = {Rauch, H. E.},
   Title = {Solutions to the linear smoothing problem},
   Journal = {IEEE Transactions on Automatic Control},
   Volume = {8},
   Pages = {371–372},
      Year = {1963} }




@article{
Rauchetal1965,
   Author = {Rauch, H. E. and Tung, F. and Striebel, C. T.},
   Title = {Maximum likelihood estimation of linear dynamical systems},
   Journal = {Journal of AIAA},
   Volume = {3},
   Pages = {1445-1450},
      Year = {1965} }




@article{
RaumSuryanetal2002,
   Author = {Raum-Suryan, Kimberly L. and Pitcher, Kenneth W. and Calkins, Donald G. and Sease, John L. and Loughlin, Thomas R.},
   Title = {Dispersal, rookery fidelity, and metapopulation structure of Steller Sea Lions (Eumetopias jubatus) in an increasing and a decreading population in Alaska},
   Journal = {Marine Mammal Science},
   Volume = {18},
   Pages = {746-764},
      Year = {2002} }




@book{
Redner2001,
   Author = {Redner, S. },
   Title = {A guide to first-passage processes},
   Publisher = {Cambridge University Press},
   Address = {Cambridge, UK},
      Year = {2001} }




@incollection{
Reedetal1998,
   Author = {Reed, A. and Giroux, J.-F. and Gauthier, G.},
   Title = {Population size, productivity, harvest and distribution},
   BookTitle = {The greater snow goose: report of the Arctic Goose Habitat Working Group. Arctic Goose Joint Venture Special Publication},
   Editor = {Batt, B. D. J.},
   Publisher = {U.S. Fish and Wildlife Service, Washington, D.C and Canadian Wildlife Service, Ottawa, Ontario. 88pp.},
   Pages = {5–31},
      Year = {1998} }




@article{
ReedOring1993,
   Author = {Reed, J. M. and Oring, L. W.},
   Title = {Long-term population trends of the endangered Ae’o (Hawaiian stilt, Himantopus mexicanus knudseni )},
   Journal = {Transactions of the Western Section of the Wildlife Society},
   Volume = {29},
   Pages = {54–60},
      Year = {1993} }




@article{
Reijnders1984,
   Author = {Reijnders, P. J. H.},
   Title = {Man-induced environmental factors in relation to fertility changes in pinnipeds},
   Journal = {Environmental Conservation},
   Volume = {11},
   Pages = {61-65},
      Year = {1984} }




@article{
Reijnders1986,
   Author = {Reijnders, P. J. H.},
   Title = {Reproductive failure in common seals feeding on fish from polluted coastal waters},
   Journal = {Nature},
   Volume = {324},
   Pages = {456 - 457},
      Year = {1986} }




@article{
Reynolds1974,
   Author = {Reynolds, C. M.},
   Title = {The census of heronries, 1969-73},
   Journal = {Bird Study},
   Volume = {21},
   Pages = {129-134},
      Year = {1974} }




@article{
Reynolds1979,
   Author = {Reynolds, C. M.},
   Title = {The heronries census: 1972-1977 population changes and a review},
   Journal = {Bird Study},
   Volume = {26},
   Pages = {7-12},
      Year = {1979} }




@book{
Ricciardi1977,
   Author = {Ricciardi, Luigi M.},
   Title = {Diffusion processes and related topics in biology},
   Publisher = {Springer-Verlag},
   Address = {New York},
   Volume = {14},
   Series = {Lecture Notes in Biomathematics},
      Year = {1977} }




@techreport{
RichardsonAllen2000,
   Author = {Richardson, S. and Allen, H.},
   Title = {Draft Washington state recovery plan for the sea otter},
   Institution = {Washington Department of Fish and Wildlife, Olympia, Washington},
      Year = {2000} }




@article{
Rohanietal2004,
   Author = {Rohani, Pejman and Miramontes, Octavio and Keeling, Matt J.},
   Title = {The colour of noise in short ecological time series data},
   Journal = {Mathematical Medicine and Biology},
   Volume = {21},
   Pages = {63-72},
   Abstract = {The statistical properties of ecological time series data and general trends therein have
historically been of great interest to ecologists. In recent years, there has been a focus
on establishing the relative importance of ‘memory’ in these data. The classic study
by Pimm and Redfearn (1988 Nature, 334, 613–614) has been extremely important in
establishing within the ecological community the idea that population time series are
generally ‘red-shifted’ (dominated by long-term trends). This conclusion was reached by
exploring the relationship between observed variability and census length in ecological
data and comparing them with those for artificially generated data. Here, we highlight some
subtle problems with this approach and suggest possible alternative methods of analysis,
especially when the time series of interest are short.},
      Year = {2004} }




@article{
Rosenblatt1956,
   Author = {Rosenblatt, M.},
   Title = {A central limit theorem and a strong mixing condition},
   Journal = {PNAS},
   Volume = {42},
   Pages = {43-47},
      Year = {1956} }




@article{
RoweisGhahramani1999,
   Author = {Roweis, S. and Ghahramani, Z.},
   Title = {A unifying review of linear gaussian models},
   Journal = {Neural Computation},
   Volume = {11},
   Pages = {305-345},
      Year = {1999} }




@incollection{
Runyoroetal1995,
   Author = {Runyoro, V. R. and Hofer, H. and Chausi, H. E. B. and Moehlman, P. D.},
   Title = {Long term trends in the herbivore populations of the Ngorongoro Crater, Tanzania},
   BookTitle = {Serengeti II: Dynamics, management, and conservation of an ecosystem},
   Editor = {Sinclair, A. R. E. and Arcese, P.},
   Publisher = {University of Chicago Press},
   Address = {Chicago},
   Pages = {146–168},
      Year = {1995} }




@incollection{
Saboetal2005,
   Author = {Sabo, J. L. and Beisner, B.E. and Berlow, E.L. and Cuddington, K. and Hastings, A. and Koen-Alonso, M. and Kokkoris, G.D. and McCann, K. and Melian, C. and Moore, J.},
   Title = {Population dynamics and food web structure--predicting measurable food web properties with minimal detail and resolution},
   BookTitle = {Dynamic food webs},
   Editor = {de Ruiter, P.C. and Wolters, V. and Moore, J.C.},
   Publisher = {Academic Press},
   Address = {San Diego},
   Pages = {437-451},
      Year = {2005} }




@article{
SaboGerber2007,
   Author = {Sabo, J. L. and Gerber, L.R.},
   Title = {Predicting extinction risk in spite of predator-prey oscillations},
   Journal = {Ecological Applications},
   Volume = {17},
   Number = {5},
   Pages = {1543-1554},
      Year = {2007} }




@article{
Saboetal2004,
   Author = {Sabo, J. L. and Holmes, E. E. and Kareiva, P.},
   Title = {Efficacy of simple viability models in ecological risk assessment: does density dependence matter?},
   Journal = {Ecology},
   Volume = {85},
   Number = {2},
   Pages = {328-341},
   Abstract = {One commonly used PVA (population viability analysis) approach applies a diffusion approximation (DA) of population growth to time series of abundance data to estimate population parameters and various metrics of extinction risk. The simplest versions of this PVA assume density-independent population growth, an assumption that is commonly called into question for populations experiencing self-limitation. Using time series data generated from simulations of populations limited by three commonly used forms of density dependence (ceiling, Beverton-Holt, and Ricker) we asked the question: "When do simple density-independent PVA models provide useful guidelines for prioritizing extinction risk despite density-dependence inherent in the underlying real populations?" Simple DA methods severely underestimated maximum growth rates (mu(max)) used to generate time series data for all three forms of density dependence. These methods also underestimated the intrinsic environmental variability in growth rates, or process error (sigma(2)), for the ceiling model, but overestimated this parameter for the Beverton-Holt and Ricker models. Despite misestimation of the intrinsic parameters, the estimated probabilities of 50% and 75% declines were highly correlated with the observed probabilities for populations growing with a ceiling (coefficients of correlation, or R-2 = 0.87-0.93). DA methods were less accurate for populations exhibiting more complex forms of density dependence (R-2 = 0.61-0.79). Although correlations between observed and estimated risks were high, bias (e.g., over and underestimation) was extensive. Estimated probabilities of 50% declines were typically much lower (overly optimistic) than observed probabilities of the same decline. By contrast, accuracy increased substantially for predictions of 75% decline, and the "optimistic" bias was replaced by conservative bias (overestimates of risk). Regardless of the form of density dependence, estimates of risk were least accurate when populations were recovering rapidly but were much more accurate when most needed by conservation practitioners: when the population fluctuated near its carrying capacity, recovered slowly to this abundance level, or declined toward extinction. Finally, when we classified risk in broad categories (e.g., extremely low, low, moderate, high, and extremely high), DA methods correctly or conservatively estimated the risk of a 75% decline for >85% of the parameter combinations, regardless of the form of density dependence followed by the real population.},
      Year = {2004} }




@incollection{
SaetherEngen2002,
   Author = {Sæther, B. -E. and Engen, S.},
   Title = {Including uncertainty in population viability analysis using population prediciton intervals},
   BookTitle = {Population Viability Analysis},
   Editor = {Beissinger, S. R. and McCullough, D. R.},
   Publisher = {University of Chicago Press},
   Address = {Chicago, IL},
   Pages = {191-212},
      Year = {2002} }




@article{
Saetheretal1998,
   Author = {Sæther, B.-E. and Engen, S. and Islam, A. and McCleery, R. and Perrins, C.},
   Title = {Environmental stochasticity and extinction risk in a population of a small songbird, the great tit},
   Journal = {American Naturalist},
   Volume = {151},
   Pages = {441–450},
      Year = {1998} }




@article{
Saetheretal2000,
   Author = {Sæther, B.-E. and Tufto, J. and Engen, S and Jerstad, K. and Røstad, O. W. and Skätan, J. E.},
   Title = {Population dynamical consequences of climate change for a small temperate songbird},
   Journal = {Science},
   Volume = {287},
   Pages = {854-856},
      Year = {2000} }




@article{
Schweppe1965,
   Author = {Schweppe, F. C.},
   Title = {Evaluation of likelihood functions for {G}aussian signals},
   Journal = {IEEE Transactions on Information Theory},
   Volume = {IT-r},
   Pages = {294-305},
      Year = {1965} }




@article{
ScofieldDerek2002,
   Author = {Scofield, R. Paul and Christie, Derek},
   Title = {Beach patrol records indicate a substantial decline in sooty shearwater (Puffinus griseus) numbers},
   Journal = {Notornis},
   Volume = {49},
   Pages = {158-165},
      Year = {2002} }




@techreport{
SeaseGudmundson2002,
   Author = {Sease, J. L. and Gudmundson, C. J.},
   Title = {Aerial and ship-based surveys of Steller sea lions (Eumetopias jubatus) from the western stock in Alaska, June and July 2001 and 2002},
   Institution = {U. S. Deparment of Commerce, NOAA Tech. Memo. NMFS-AFSC-131},
      Year = {2002} }




@techreport{
Seaseetal1993,
   Author = {Sease, J. L. and Lewis, J. P. and McAllister, D. C. and Merrick, R. L. and Mello, S. M.},
   Title = {Aerial and ship-based surveys of Steller sea lions (Eumetopias jubatus) from the Southeast Alaska, the Gulf of Alaska, and Aleutian Islands during June and July 1992},
   Institution = {U. S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-17},
      Year = {1993} }




@techreport{
SeaseLoughlin1999,
   Author = {Sease, J. L. and Loughlin, T. R.},
   Title = {Aerial and ship-based surveys of Steller sea lions (Eumetopias jubatus) in Alaska, June and July 1997 and 1998},
   Institution = {U. S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-100},
      Year = {1999} }




@article{
Shnute1994,
   Author = {Shnute, Jon T.},
   Title = {A general framework for developing sequential fisheries models},
   Journal = {Canadian Journal of Fisheries and Aquatic Sciences},
   Volume = {51},
   Pages = {1676-1688},
      Year = {1994} }




@article{
ShumwayStoffer1982,
   Author = {Shumway, R. H. and Stoffer, D. S.},
   Title = {An approach to time series smoothing and forecasting using the {EM} algorithm},
   Journal = {Journal of Time Series Analysis},
   Volume = {3},
   Number = {4},
   Pages = {253-264},
      Year = {1982} }




@book{
ShumwayStoffer2000,
   Author = {Shumway, R. H. and Stoffer, D. S.},
   Title = {Time series analysis and its applications},
   Publisher = {Springer-Verlag},
   Address = {New York, New York, USA},
      Year = {2000} }




@book{
ShumwayStoffer2006,
   Author = {Shumway, R.H. and Stoffer, D.S.},
   Title = {Time series analysis and its applications},
   Publisher = {Springer-Science+Business Media, LLC},
   Address = {New York, New York},
   Edition = {2nd},
      Year = {2006} }




@article{
Siblyetal2005,
   Author = {Sibly, R. M. and Barker, D. and Denham, M. C. and Hone, J. and Pagel, M.},
   Title = {On the regulation of populations of mammals, birds, fish, and insects},
   Journal = {Science},
   Volume = {309},
   Pages = {607-610},
      Year = {2005} }




@article{
Smalletal2003,
   Author = {Small, R. J. and Pendleton, G. W. and Pitcher, K. W.},
   Title = {Trends in abundance of Alaska harbor seals, 1983–2001},
   Journal = {Marine Mammal Science},
   Volume = {19},
   Pages = {344-362},
      Year = {2003} }




@incollection{
SmirnovMiquelle1999,
   Author = {Smirnov, E. N. and Miquelle, D. G.},
   Title = {Population dynamics of the Amur tiger in Sikhote-Alin State Biosphere Reserve},
   BookTitle = {Riding the tiger; Meeting the needs of people and wildlife in Asia},
   Editor = {Seidensticker, J. and Christie, S. and Jackson, P.},
   Publisher = {Cambridge University Press},
   Address = {Cambridge},
   Pages = {61-70},
      Year = {1999} }




@book{
SmitalovaSujan1992,
   Author = {Smitalova, K. and Sujan, Stefan},
   Title = {A mathematical treatment of dynamical models in biological science},
   Publisher = {Ellis Horwood Ltd},
   Address = {New York, NY, USA},
      Year = {1992} }




@book{
Snyderetal1987,
   Author = {Snyder, N. F. R. and Wiley, J. W. and Kepler, C. B.},
   Title = {The parrots of Luquillo: Natural history and conservation of the Puerto Rican parrot},
   Publisher = {Western Foundation of Vertebrate Zoology},
   Address = {Los Angeles, CA},
      Year = {1987} }




@article{
Solomon1998,
   Author = {Solomon, Barry D.},
   Title = {Impending recovery of Kirtland’s warbler: case study in the effectiveness of the Endangered Species Act},
   Journal = {Environmental Management},
   Volume = {22},
   Number = {1},
   Pages = {9-17},
      Year = {1998} }




@article{
SpencerLensink1970,
   Author = {Spencer, D. L. and Lensink, C. J.},
   Title = {The muskox of Nunivak Island},
   Journal = {Journal of Wildlife Management},
   Volume = {34},
   Pages = {1-15},
      Year = {1970} }




@article{
Spiegelhalteret2002,
   Author = {Spiegelhalter, D. J. and Best, N. G. and Carlin, B. R. and van der Linde, A.},
   Title = {Bayesian measures of model complexity and fit},
   Journal = {Journal of the Royal Statistical Society Series B-Statistical Methodology},
   Volume = {64},
   Pages = {583-616},
      Year = {2002} }




@article{
Springeretal2003,
   Author = {Springer, A. M. and Estes, J. A. and van Vliet, G. B. and Williams, T. M. and Doak, D. F. and Danner, E. M. and Forney, K. A. and Pfister, B.},
   Title = {Sequential megafaunal collapse in the North Pacific Ocean: an ongoing legacy of industrial whaling?},
   Journal = {Proceedings of the National Academy of Sciences},
   Volume = {100},
   Number = {21},
   Pages = {12,223–8},
      Year = {2003} }




@article{
Stafford1971,
   Author = {Stafford, J.},
   Title = {The heron population of England and Wales, 1928-1970},
   Journal = {Bird Study},
   Volume = {18},
   Pages = {218-221},
      Year = {1971} }




@article{
Staplesetal2004,
   Author = {Staples, D. F. and Taper, M. L. and Dennis, B.},
   Title = {Estimating population trend and process variation for {PVA} in the presence of sampling error},
   Journal = {Ecology},
   Volume = {85},
   Number = {4},
   Pages = {923-929},
   Abstract = {Time series of population abundance estimates often are the only data available for evaluating the prospects for persistence of a species of concern. With such data, it is possible to perform a population viability analysis (PVA) with diffusion approximation methods using estimates of the mean population trend and the variance of the trend, the so-called process variation. Sampling error in the data, however, may bias estimators of process variation derived by simple methods. We develop a restricted maximum likelihood (REML)-based method for estimating trend, process variation, and sampling error from a single time series based on a discrete-time model of density-independent growth coupled with a model of the sampling process. Transformation of the data yields a conventional linear mixed model, in which the variance components are functions of the process variation and sampling error. Simulation results show essentially unbiased estimators of trend, process variation, and sampling error over a range of process variation/sampling error combinations. Example data analyses are provided for the Whooping Crane (Grus americana), grizzly bear (Ursus arctos horribilis), California Condor (Gymnogyps californianus), and Puerto Rican Parrot (Amazona vittata). This REML-based method is useful for PVA methods that depend on accurate estimation of process variation from time-series data.},
      Year = {2004} }




@article{
Staplesetal2005,
   Author = {Staples, David F. and Taper, Mark L. and Shepard, Bradley B.},
   Title = {Risk-based viable population monitoring},
   Journal = {Conservation Biology},
   Volume = {19},
   Number = {6},
   Pages = {1908-1916},
      Year = {2005} }




@techreport{
Stinsonetal2004,
   Author = {Stinson, D. W. and Hays, D. W. and Schroeder, M. A.},
   Title = {Washington state recovery plan for the greater sage-grouse},
   Institution = {Washington Department of Fish and Wildlife, Olympia, Washington},
      Year = {2004} }




@article{
StofferWall1991,
   Author = {Stoffer, David S. and Wall, Kent D.},
   Title = {Bootstrapping state-space models: {G}aussian maximum likelihood estimation and the {K}alman filter},
   Journal = {Journal of the American Statistical Association},
   Volume = {86},
   Number = {416},
   Pages = {1024-1033},
      Year = {1991} }




@article{
Storchetal2002,
   Author = {Storch, D. and Gaston, K. J. and Cepak, J.},
   Title = {Pink landscapes: 1/f spectra of spatial environmental variability and bird community composition},
   Journal = {Proceedings of the Royal Society of London Series B-Biological Sciences},
   Volume = {269},
   Number = {1502},
   Pages = {1791-1796},
   Abstract = {Temporal and spatial environmental variability are predicted to have reddened spectra that reveal increases in variance with the period or length sampled. However, spectral analyses have seldom been performed on ecological data to determine whether these predictions hold true in the case of spatial environmental variability. For a 50 km long continuous transect of 128 point samples across a heterogeneous cultural landscape in the Czech Republic, both habitat composition and bird species composition decomposed by standard ordination techniques did indeed exhibit reddened spectra. The values of main ordination axes have relationships between log spectral density and log frequency with slopes close to -1, indicating 1/f, or 'pink' noise type of variability that is characterized by scale invariance. However, when habitat composition was controlled for and only residuals for bird species composition were analysed, the spectra revealed a peak at intermediate frequencies, indicating that population processes that structure bird communities but are not directly related to the structure of the environment might have some typical correlation length. Spatial variability of abundances of individual species was mostly reddened as well, but the degree was positively correlated to their total abundance and niche position (strength of species-habitat association). If 'pink' noise type of variability is as generally typical for spatial environmental variability as for temporal variability, the consequences may be profound for patterns of species diversity on different spatial scales, the form of species-area relationships and the distribution of abundances within species ranges.},
      Year = {2002} }




@article{
Sullivan1992,
   Author = {Sullivan, P. J. },
   Title = {A Kalman Filter approach to catch-at-length analysis},
   Journal = {Biometrics},
   Volume = {48},
   Pages = {237-257},
      Year = {1992} }




@article{
TaperDennis1994,
   Author = {Taper, M. L. and Dennis, Brian},
   Title = {Density dependence in time series observations of natural populations: estimation and testing },
   Journal = {Ecological Monographs},
   Volume = {64},
   Number = {2},
   Pages = {205-224},
      Year = {1994} }




@article{
Taylor1995,
   Author = {Taylor, B. L.},
   Title = {The reliability of using population viability analysis for risk classification of species},
   Journal = {Conservation Biology},
   Volume = {9},
   Number = {3},
   Pages = {551-558},
   Abstract = {I examine whether or not it is appropriate to use extinction probabilities generated by population viability analyses, based on best estimates for model parameters, as criteria for listing species in Red Data Book categories as recently proposed by the World Conservation Union. Such extinction probabilities are influenced by how accurately model parameters are estimated and by how accurately the models depict actual population dynamics. I evaluate the effect of uncertainty in parameter estimation through simulations. Simulations based on Steller sea lions were used to evaluate bias and precision in estimates of probability of extinction and to consider the performance of two proposed classification schemes. Extinction time estimates were biased (because of violation of the assumption of stable age distribution) and underestimated the variability of probability of extinction for a given time (primarily because of uncertainty in parameter estimation). Bias and precision in extinction probabilities are important when these probabilities are used to compare the risk of extinction between species. Suggestions are given for population viability analysis techniques that incorporate parameter uncertainty. I conclude that testing classification schemes with simulations using quantitative performance objectives should precede adoption of quantitative listing criteria},
      Year = {1995} }




@incollection{
Tayloretal2002,
   Author = {Taylor, Barbara L. and Wade, Paul R. and Ramakrishnan, Uma and Gilpin, Michael and Akcakaya, H. Resit},
   Title = {Incorporating uncertainty in population viability analyses for the purpose of classifying species by risk},
   BookTitle = {Population viability analysis},
   Editor = {Beissinger, Steven R. and Mccullough, Dale R.},
   Publisher = {University of Chicago Press},
   Address = {Chicago, IL},
   Pages = {239-252},
      Year = {2002} }




@incollection{
Terborghetal1999,
   Author = {Terborgh, J. and Estes, J. A. and Paquet, P. and Ralls, K. and Boyd-Heger, D. and Miller, B. J. and Noss, R. F.},
   Title = {The role of top carnivores in regulating terrestrial ecosystems},
   BookTitle = {Continental Conservation},
   Editor = {Soule´, M. E. and Terborgh, J.},
   Publisher = {Island Press},
   Address = {Washington, DC},
   Pages = {39–64},
      Year = {1999} }




@article{
Towelletal2006,
   Author = {Towell, R. G. and Ream, R. R. and York, A. E.},
   Title = {Decline in northern fur seal (Callorhinus ursinus) pup production on the Pribilof Islands},
   Journal = {Marine Mammal Science},
   Volume = {22},
   Pages = {486-501},
      Year = {2006} }




@book{
TrillmichOno1991,
   Editor = {Trillmich, F. and Ono, K.},
   Title = {Pinnipeds and El Niño: responses to environmental stress},
   Publisher = {Springer-Verlag},
   Address = {Berlin},
      Year = {1991} }




@article{
Tritesetal2006,
   Author = {Trites, A. W. and Deecke, V. B. and Gregr, E. J. and Ford, J. K. B. and Olesiuk, P. F.},
   Title = {Killer whales, whaling and sequential megafaunal collapse in the North Pacific: a comparative analysis of the dynamics of marine mammals in Alaska and British Columbia following commercial whaling},
   Journal = {Marine Mammal Science},
   Volume = {in press},
      Year = {2006} }




@article{
TritesDonnelly2003,
   Author = {Trites, A. W. and Donnelly, C. P.},
   Title = {The decline of Steller sea lions in Alaska: a review of the nutritional stress hypothesis},
   Journal = {Mammal Review},
   Volume = {33},
   Pages = {3-28},
      Year = {2003} }




@techreport{
Tritesetal1999,
   Author = {Trites, A. W. and Livingston, P. A. and Mackinson, S. and Vasconcellos, M. C. and Springer, A. M. and Pauly, D.},
   Title = {Ecosystem change and the decline of marine mammals in the eastern Bering Sea: testing the ecosystem shift and commercial whaling hypotheses},
   Institution = {University of British Columbia},
   Number = {Fisheries Centre Research Reports 7},
      Year = {1999} }




@article{
Tritesetal2006,
   Author = {Trites, A. W. and Porter, B. P. and Deecke, V. B. and Coombs, A. P. and Marcotte, M. L. and Rosen, D. A. S.},
   Title = {Insights into the timing of weaning and the attendance patterns of lactating Steller sea lions (Eumetopias jubatus) in Alaska during winter, spring, and summer},
   Journal = {Aquatic Mammals},
   Volume = {32},
   Number = {1},
   Pages = {85-97},
      Year = {2006} }




@article{
TritesPorter2002,
   Author = {Trites, A. W. and Porter, B. T.},
   Title = {Attendance patterns of Steller sea lions (Eumetopias jubatus) and their young during winter},
   Journal = {Journal of Zoology},
   Volume = {256},
   Pages = {547-556},
      Year = {2002} }




@article{
Tuljapurkar1989,
   Author = {Tuljapurkar, S. D.},
   Title = {An uncertain life: demography in random environments},
   Journal = {Theoretical Population Biology},
   Volume = {35},
   Pages = {227-294},
      Year = {1989} }




@article{
Tuljapurkar1990,
   Author = {Tuljapurkar, S. D.},
   Title = {Population dynamics in variable environments},
   Journal = {Lecture Notes in Biomathematics},
   Volume = {85},
      Year = {1990} }




@article{
TuljapurkarOrzack1980,
   Author = {Tuljapurkar, S. D. and Orzack, S. H.},
   Title = {Population dynamics in variable environments. I. Long-run growth rates and extinction},
   Journal = {Theoretical Population Biology},
   Volume = {18},
   Pages = {314-342},
      Year = {1980} }




@book{
Turchin1998,
   Author = {Turchin, P.},
   Title = {Quantitative analysis of movement},
   Publisher = {Sinauer},
   Address = {Sunderland, MA},
      Year = {1998} }




@article{
Turelli1986,
   Author = {Turelli, Michael},
   Title = {Stochastic community theory: a partially guided tour},
   Journal = {Biomathematics},
   Volume = {17},
   Pages = {321-339},
      Year = {1986} }




@techreport{
USFWS1991,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Utah prairie dog recovery plan},
   Institution = {U.S. Fish and Wildlife Service, Denver, Colorado
},
      Year = {1991} }




@article{
USFWS1999b,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Proposed rule to remove the bald eagle in the lower 48 states from the list of endangered and threatened wildlife},
   Journal = {Federal Register},
   Volume = {64},
   Number = {128},
   Pages = {36454-36464},
      Year = {1999} }




@techreport{
USFWS1999a,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Technical/agency draft revised recovery plan for the Puerto Rican parrot (Amazona vittata)},
   Institution = {U.S. Department of the Interior, Southeast Region, Atlanta, Georgia},
      Year = {1999} }




@techreport{
USFWS2003a,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Draft revised recovery plan for the 'Alala (Corvus hawaiiensis)},
   Institution = {U.S. Department of the Interior, Region 1, Portland, Oregon},
      Year = {2003} }




@techreport{
USFWS2003c,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Final revised recovery plan for the Southern sea otter, (Enhydra lutris nereis)},
   Institution = {U.S. Department of the Interior, Portland, Oregon},
      Year = {2003} }




@article{
USFWS2003d,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Final rule to remove the Douglas County distinct population segment of Columbian white-tailed deer from the federal list of endangered and threatened wildlife},
   Journal = {Federal Register},
   Volume = {68},
   Number = {142},
   Pages = {43647-43659},
      Year = {2003} }




@techreport{
USFWS2003b,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Recovery plan for the Great Lakes piping plover (Charadrius melodus)},
   Institution = {U.S. Department of the Interior, Great Lakes-Big Rivers Region, Ft. Snelling, Minnesota},
      Year = {2003} }




@techreport{
USFWS2004,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Trumpeter swan survey of the Rocky Mountain population, winter 2004},
   Institution = {U.S. Department of Interior, Migratory Birds and State Programs, Mountain-Prairie Region, Lakewood, Colorado},
      Year = {2004} }




@techreport{
USFWS2004,
   Author = {U.S. Fish and Wildlife Service},
   Title = {Waterfowl population status, 2005},
   Institution = {U.S. Department of the Interior},
      Year = {2005} }




@techreport{
USFWS2006,
   Author = {U.S. Fish and Wildlife Service},
   Title = {2003-2005 post-delisting monitoring report for theDouglas County distinct population segment of the Columbian white-tailed deer (Odocoileus virginianus leucurus)},
   Institution = {U.S. Fish and Wildlife Service, Roseburg Field Office, Roseburg, Oregon, April 2006},
      Year = {2006} }




@techreport{
USFWS1992,
   Author = {U.S. Fish and Wildlife Service and National Marine Fisheries Service},
   Title = {Recovery plan for the Kemp's Ridley sea turtle (Lepidochelys kempii) .},
   Institution = {National Marine Fisheries Service, St. Petersburg, Florida},
      Year = {1992} }




@article{
Viljugreinetal2005,
   Author = {Viljugrein, H. and Stenseth, N. C. and Smith, G. W. and Steinbakk, G. H.},
   Title = {Density dependence in North American ducks},
   Journal = {Ecology},
   Volume = {86},
   Pages = {245–254},
      Year = {2005} }




@article{
Voyeretal2003,
   Author = {Voyer, A. G. and Smith, K. G. and Festa-Bianchet, M.},
   Title = {Dynamics of hunted and unhunted mountaing goat Oreamunos americuanus populations},
   Journal = {Wildlife Biology},
   Volume = {9},
   Pages = {213-218},
      Year = {2003} }




@incollection{
VucetichPeterson2004,
   Author = {Vucetich, J. A.  and Peterson, R. O.},
   Title = {Long-term population and predation dynamics of wolves on Isle Royale},
   BookTitle = {Biology and Conservation of Wild Canids},
   Editor = {Macdonald, D. and Sillero-Zubiri, C.},
   Publisher = {Oxford University Press},
   Address = {Oxford},
   Pages = {281-292},
      Year = {2004} }




@article{
Wade2000,
   Author = {Wade, Paul},
   Title = {Bayesian methods in conservation biology},
   Journal = {Conservation Biology},
   Volume = {14},
   Number = {5},
   Pages = {1308-1316},
      Year = {2000} }




@article{
Wadeetal2006,
   Author = {Wade, P. and Barrett-Lennard, L. and Black, N. and Brownell, R. L. Jr. and Burkanov, V. and Burdin, A. and Calambokidis, J. and Cerchio, S. and Dahlheim, M. and Ford, J. and Friday, N. and Fritz, L. and Jacobsen, J. and Loughlin, T. and Lowry, M. and Matkin, C. and Matkin, D. and Mehta, A. and Mizroch, S. and Muto, M. and Rice, D. and Siniff, D. and Small, R. and Steiger, G. and Straley, J. and Van Blaricom, G. and Clapham, P.},
   Title = {Marine mammal abundance, biomass, and trends in the eastern North Pacific – a reanalysis of evidence for sequential megafauna collapse},
   Journal = {Marine Mammal Science},
   Volume = {in press},
      Year = {2006} }




@article{
Wang2007,
   Author = {Wang, G.},
   Title = {On the latent state estimation of nonlinear population dynamics using Bayesian and non-Bayesian state-space models},
   Journal = {Ecological modelling},
   Volume = {200},
   Pages = {521-528},
      Year = {2007} }




@article{
Wangetal2006,
   Author = {Wang, G. M. and Hobbs, N. T. and Boone, R. B. and Illius, A. W. and Gordon, I. J. and Gross, J. E. and Hamlin, K. L.},
   Title = {Spatial and temporal variability modify density dependence in populations of large herbivores},
   Journal = {Ecology},
   Volume = {87},
   Pages = {95-102},
      Year = {2006} }




@article{
Wardetal2009c,
   Author = {Ward, E. J. and Chirakkal, H. and Gonz{\'{a}}lez-{S}u{\'{a}}rez, M. and Aurioles-{G}amboa, D. and Holmes, E. E. and Gerber, L.},
   Title = {Inferring spatial structure from time-series data: using multivariate state-space models to detect metapopulation structure of {C}alifornia sea lions in the {G}ulf of {C}alifornia, {M}exico},
   Journal = {Journal of Applied Ecology },
   Volume = {1},
   Number = {47},
   Pages = {47-56},
      Year = {2009} }




@article{
Weimerskirch2004,
   Author = {Weimerskirch, H.},
   Title = {Diseases threaten Southern Ocean albatrosses},
   Journal = {Polar Biology},
   Volume = {27},
   Pages = {374-379},
      Year = {2004} }




@book{
WestHarrison1997,
   Author = {West, M. and Harrison, J.},
   Title = {Bayesian Forecasting and Dynamic Models},
   Publisher = {Springer-Verlag},
   Address = {New York},
   Edition = {2nd},
      Year = {1997} }




@article{
WestlakeOCorryCrowe2002,
   Author = {Westlake, R. L. and O'Corry-Crowe, G. M.},
   Title = {Macrogeographic structure and patterns of genetic diversity in harbor seals (Phoca vitulina) from Alaska to Japan},
   Journal = {Journal of Mammalogy},
   Volume = {83},
   Number = {4},
   Pages = {1111-1126},
   Abstract = {We examined sequence variation in the control region of the mitochondrial genome from 778 seals sampled at 161 locations from northern Japan to southeastern Alaska to learn more about the evolutionary history and population structure of, and effects of recent declines on genetic diversity in, harbor seals (Phoca vitulina) in the northern Pacific Ocean. High haplotypic diversity (H = 0.975) and a poorly resolved mitochondrial genome (mtDNA) phylogeny suggest that harbor seals in the Pacific underwent a rapid expansion in population size in their recent evolutionary past, possibly after the retreat of Pleistocene ice sheets. Weak phylogeographic partitioning of lineages attests to a complex evolutionary and demographic history of contemporary Pacific populations. Extensive macrogeographic subdivision was evident among a subset of grouped localities that represent centers of abundance along the distributional continuum. Heterogeneity was influenced by population size and correlated with geographic distance, suggesting that dispersal occurs primarily among neighboring subpopulations. The 2 currently recognized subspecies of harbor seal in the Pacific, P. v. richardii of North America and P. v. stejnegeri of Asia, do not represent phylogenetically discrete mtDNA assemblages. The greatest differentiation detected was along the Commander-Aleutian Island chain, the region of the presumed subspecies boundary and a likely contact zone for expanding refugial populations of a number of marine mammal species after retreat of ice sheets. Differentiation between the Kodiak Archipelago and Prince William Sound, and between Bristol Bay and the Pribilof Islands, indicates that current management stocks are inappropriate and highlights the need for a detailed analysis of population and stock structure in Alaska. A decline in population size in Prince William Sound over the past few decades was accompanied by a discernible reduction in mtDNA diversity, manifested as a loss of rare haplotypes through random drift. A continued population decline will erode genetic diversity further, with potentially adverse effects on evolutionary potential and individual fitness.},
   Keywords = {genetic diversity; genetic drift; harbor seal; isolation-by-distance;
mitochondrial DNA
MICROSATELLITE DNA ANALYSES; ANIMAL MITOCHONDRIAL-DNA; INTRASPECIFIC
STRUCTURE; CONSERVATION BIOLOGY; POPULATION-STRUCTURE; ENHYDRA-LUTRIS;
PHYLOGEOGRAPHY; DISPERSAL; EVOLUTION; POLYMORPHISMS},
   Year = {2002} }




@article{
WhitehouseHallMartin2000,
   Author = {Whitehouse, A. M. and Hall-Martin, A. J.},
   Title = {Elephants in Addo National Park, South Africa: reconstruction of the population’s history},
   Journal = {Oryx},
   Volume = {34},
   Pages = {46–55},
      Year = {2000} }




@article{
WilcoxPossingham2002,
   Author = {Wilcox, C. and Possingham, H.},
   Title = {Do life history traits affect the accuracy of diffusion approximations for mean time to extinction?},
   Journal = {Ecological Applications},
   Volume = {12},
   Number = {4},
   Pages = {1163-1179},
   Abstract = {Estimating the risk of extinction is one of the central foci of conservation biology, but such estimates are often constrained by the available data. In the face of limited data. several authors have suggested using diffusion approximations to estimate the mean time to extinction as a means of quantifying the risk of extinction. However, the accuracy of the diffusion approximation for characterizing extinction processes has not been well tested. We develop a simulation model that includes life history parameters and incorporates both demographic and environmental stochasticity in population dynamics. We use the simulation model to study the effects of stochasticity on the accuracy of the diffusion approximation across different life history strategies. Our results show that predictions for mean time to extinction from the diffusion approximation may differ significantly from simulated ones, and that the amount and direction of the error in the approximation is not systematic. Given that this error is unpredictable and may be very sensitive to the exact demographic rates. we believe that the diffusion approximation should be used with caution as a basis for assessing extinction risk or making management decisions.},
      Year = {2002} }




@book{
Wilcox2004,
   Author = {Wilcox, Rand R.},
   Title = {Introduction to robust estimation and hypothesis testing},
   Publisher = {Academic Press},
   Address = {Burlington, MA},
   Edition = {2nd},
      Year = {2004} }




@techreport{
Wiles2004,
   Author = {Wiles, G. J.},
   Title = {Washington state status report for the killer whale},
   Institution = {Washington Department of Fish and Wildlife, Olympia, WA},
      Year = {2004} }




@article{
Williamsetal2004,
   Author = {Williams, T. M. and Estes, J. A. and Doak, D. F. and Springer, A. M.},
   Title = {Killer appetites: assessing the role of predators in ecological communities},
   Journal = {Ecology},
   Volume = {85},
   Pages = {3373-3384},
      Year = {2004} }




@article{
WinshipTrites2006,
   Author = {Winship, A. J. and Trites, A. W.},
   Title = {Risk of extripation of Steller sea lions in the Gulf of Alaska and Aleutian Islands: a population viability analysis based on alternative hypotheses for why sea lions declined in Western Alaska},
   Journal = {Marine Mammal Science},
   Volume = {23},
   Pages = {124-155},
      Year = {2006} }




@article{
Wisdometal2000,
   Author = {Wisdom, M. J. and Mills, L. S. and Doak, D. F.},
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