Fire, vital rates, and population viability: A hierarchical Bayesian analysis of the endangered Florida scrub mint

Ecological Monographs

Volumn 80, Issue 4, 2010, Pages 627-649

  Evans, Margaret E K ^a,b   Holsinger, Kent E ^c   Menges, Eric S ^d  

^a ECOLE NORMALE SUPÉRIEURE   (France)

^b YALE UNIVERSITY   (United States)

^c UNIVERSITY OF CONNECTICUT   (United States)

^d ARCHBOLD BIOLOGICAL STATION   (United States)

Author keywords

Dicerandra frutescens; Element selection; Environmental stochasticity; Extinction risk; Florida scrub mint; Generalized linear mixed models (GLMM); Log pseudomarginal likelihood; Matrix selection; Population viability analysis

Indexed keywords

ANALYTICAL FRAMEWORK; BAYESIAN ANALYSIS; DEMOGRAPHY; DICOTYLEDON; ENDANGERED SPECIES; EXTINCTION RISK; FECUNDITY; FIRE BEHAVIOR; GROWTH RATE; LINEARITY; POPULATION GROWTH; POPULATION VIABILITY ANALYSIS; SPECIES CONSERVATION; STOCHASTICITY; SURVIVAL;

DICERANDRA FRUTESCENS; LAMIACEAE; MAGNOLIOPHYTA;

EID: 78649300257     PISSN: 00129615     EISSN: 15577015     Source Type: Journal    
DOI: 10.1890/09-1758.1     Document Type: Article

References (125)

1. Adler, P. B., and J. HilleRisLambers. 2008. The influence of climate and species composition on the population dynamics of ten prairie forbs. Ecology 89:3049-3060.
2. Anderson, D. R., G. C. White, and K. P. Burnham. 1995. Some specialized risk assessment methodologies for vertebrate populations. Environmental and Ecological Statistics 2:91-115.
3. Bakker, V. J., and D. F. Doak. 2009. Population viability management: ecological standards to guide adaptive management for rare species. Frontiers in Ecology and the Environment. [doi: 10.1890/070220]
4. Bakker, V. J., D. F. Doak, G. W. Roemer, D. K. Garcelon, T. J. Coonan, S. A. Morrison, C. Lynch, K. Rallis, and R. Shaw. 2009. Incorporating ecological drivers and uncertainty into a demographic population viability analysis for the island fox. Ecological Monographs 79:77-108.
5. Bates, D., M. Maechler, and B. Dai. 2008. lme4: linear mixedeffects models using S4 classes. R package version 0.999375-28.
6. Beissinger, S. R., and D. R. McCullough, editors. 2002. Population viability analysis. University of Chicago Press, Chicago, Illinois, USA.
7. Beissinger, S. R., J. M. Wunderle, Jr., J. M. Meyers, B.-E. Sæther, and S. Engen. 2008. Anatomy of a bottleneck: diagnosing factors limiting population growth in the Puerto Rican parrot. Ecological Monographs 78:185-203.
8. Bierzychudek, P. 1982. The demography of jack-in-the-pulpit, a forest perennial that changes sex. Ecological Monographs 52: 335-351.
9. Bolker, B. 2009. Learning hierarchical models: advice for the rest of us. Ecological Applications 19:588-592.
10. Bolker, B. M., M. E. Brooks, C. J. Clark, S. W. Geange, J. R. Poulsen, M. H. H. Stevens, and J.-S. S. White. 2008. Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology and Evolution 24:127-135.
11. Bouchard, M., and D. Pothier. 2008. Simulations of the effects of changes in mean fire return intervals on balsam fir abundance, and implications for spruce budworm outbreaks. Ecological Modelling 218:207-218.
12. Boyce, M. S. 1992. Population viability analysis. Annual Review of Ecology and Systematics 23:481-506.
13. Calder, C., M. Lavine, P. Muller, and J. S. Clark. 2003. Incorporating multiple sources of stochasticity into dynamic population models. Ecology 84:1395-1402.
14. Calvert, A. M., S. J. Bonner, I. D. Jonsen, J. M. Flemming, S. J. Walde, and P. D. Taylor. 2009. A hierarchical Bayesian approach to multi-state mark-recapture: simulations and applications. Journal of Applied Ecology 46:610-620.
15. Carlin, B. P., J. S. Clark, and A. E. Gelfand. 2006. Elements of hierarchical Bayesian inference. Pages 3-24 in J. S. Clark and A. E. Gelfand, editors. Hierarchical modelling for the environmental sciences. Oxford University Press, Oxford, UK.
16. Caswell, H. 2001. Matrix population models. Second edition. Sinauer Associates, Sunderland, Massachusetts, USA.
17. Caswell, H., and T. Kaye. 2001. Stochastic demography and conservation of an endangered perennial plant (Lomatium bradshawii) in a dynamic fire regime. Advances in Ecological Research 32:1-51. (Pubitemid 33804390)
18. Childs, D. Z., M. Rees, K. E. Rose, P. J. Grubb, and S. P. Ellner. 2004. Evolution of size-dependent flowering in a variable environment: construction and analysis of a stochastic integral projection model. Proceedings of the Royal Society B 271:425-434.
19. Clark, J. S. 2003. Uncertainty and variability in demography and population growth: a hierarchical approach. Ecology 84: 1370-1381.
20. Clark, J. S. 2005. Why environmental scientists are becoming Bayesians. Ecology Letters 8:2-14.
21. Clark, J. S. 2007. Models for ecological data, an introduction. Princeton University Press. Princeton, New Jersey, USA.
22. Clark, J. S., et al. 2001. Ecological forecasts: an emerging imperative. Science 293:657-660.
23. Cohen, J. E. 1979. Comparative statics and stochastic dynamics of age-structure populations. Theoretical Population Biology 16:159-171.
24. Coulson, T., E. A. Catchpole, S. D. Albon, B. J. T. Morgan, J. M. Pemberton, T. H. Clutton-Brock, M. J. Crawley, and B. T. Grenfell. 2001. Age, sex, density, winter weather, and population crashes in Soay Sheep. Science 292:1528-1531.
25. Dey, D. K., M.-H. Chen, and H. Chang. 1997. Bayesian approach for nonlinear random effects models. Biometrics 53:1239-1252.
26. Diez, J. M. 2007. Hierarchical patterns of symbiotic orchid germination linked to adult proximity and environmental gradients. Journal of Ecology 95:159-170.
27. Diez, J. M., and H. R. Pulliam. 2007. Hierarchical analysis of species distributions and abundance across environmental gradients. Ecology 88:3144-3152.
28. Doak, D., P. Karieva, and B. Klepetka. 1994. Modeling population viability for the desert tortoise in the western Mojave Desert. Ecological Applications 4:446-460.
29. Doak, D. F., and W. Morris. 1999. Detecting population-level consequences of ongoing environmental change without long-term monitoring. Ecology 80:1537-1551.
30. Dobson, A. P., J. P. Rodriguez, W. M. Roberts, and D. S. Wilcove. 1997. Geographic distribution of endangered species in the United States. Science 275:550-553
31. Drechsler, M., and M. A. Burgman. 2004. Combining population viability analysis with decision analysis. Biodiversity and Conservation 13:115-139.
32. Drechsler, M., K. Frank, I. Hanski, R. B. O'Hara, and C. Wissel. 2003. Ranking metapopulation extinction risk: from patterns in data to conservation management decisions. Ecological Applications 13:990-998.
33. Ellner, S. P. 2003. When does parameter drift decrease the uncertainty in extinction risk estimates? Ecology Letters 6: 1039-1045
34. Ellner, S. P., and J. Fieberg. 2003. Using PVA for management despite uncertainty: effects of habitat, hatcheries, and harvest on salmon. Ecology 84:1359-1369.
35. Ellner, S. P., and M. Rees. 2006. Integral projection models for species with complex demography. American Naturalist 167: 410-428.
36. Estill, J. C., and M. B. Cruzan. 2001. Phytogeography of rare plant species endemic to the southeastern United States. Castanea 66:3-23.
37. Evans, M. E. K., R. Ferriere, M. J. Kane, and D. L. Venable. 2007. Bet hedging via seed banking in desert evening primroses (Oenothera, Onagraceae): demographic evidence from natural populations. American Naturalist 169:184-194.
38. Evans, M. E. K., K. E. Holsinger, and E. S. Menges. 2008. Modeling the effect of fire on demography of Dicerandra frutescens ssp. frutescens, an endangered plant endemic to Florida scrub. Population Ecology 50:53-62.
39. Evans, M. E. K., E. S. Menges, and D. R. Gordon. 2004. Mating systems and limits to seed production in two Dicerandra mints endemic to Florida scrub. Biodiversity and Conservation 13:1819-1832.
40. Ferson, S., and M. A. Burgman. 1995. Correlations, dependency bounds and extinction risks. Biological Conservation 73:101-105.
41. Fieberg, J., and S. P. Ellner. 2001. Stochastic matrix models for conservation and management: a comparative review of methods. Ecology Letters 4:244-266.
42. Foley, P. 2000. Problems in extinction model selection and parameter estimation. Environmental Management 26:S55-S73.
43. Gelfand, A. E., and D. K. Dey. 1994. Bayesian model choice: asymptotics and exact calculations. Journal of the Royal Statistical Society Series B (Methodological) 56:501-514.
44. Gelfand, A. E., D. K. Dey, and H. Chang. 1992. Model determination using predictive distributions with implementation via sampling-based methods. Pages 147-167 in J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, editors. Bayesian statistics 4. Oxford University Press, Oxford, UK.
45. Gelman, A., J. B. Carlin, H. S. Stern, and D. B. Rubin. 2003. Bayesian data analysis. Second edition. Chapman and Hall, London, UK.
46. Gelman, A., and D. B. Rubin. 1992. Inference from iterative simulation using multiple sequences. Statistical Science 7: 457-511.
47. Gillespie, C. S., and A. Golightly. 2010. Bayesian inference for generalized stochastic population growth models with application to aphids. Journal of the Royal Statistical Society Series C Applied Statistics 59:341-357.
48. Gotelli, N. J. 1998. A primer of ecology. Second edition. Sinauer Associates, Sunderland, Massachusetts, USA.
49. Gotelli, N. J., and A. M. Ellison. 2006. Forecasting extinction risk with nonstationary matrix models. Ecological Applications 16:51-61.
50. Harwood, J., and K. Stokes. 2003. Coping with uncertainty in ecological advice: lessons from fisheries. Trends in Ecology and Evolution 18:617-622.
51. Hobbs, N. T. 2009. New tools for insight from ecological models and data. Ecological Applications 19:551-552.
52. Hooten, M. B., and C. K. Wikle. 2007. Shifts in the spatiotemporal growth dynamics of shortleaf pine. Environmental and Ecological Statistics 14:207-227.
53. Hooten, M. B., and C. K. Wikle. 2008. A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove. Environmental and Ecological Statistics 15:59-70.
54. Hooten, M. B., C. K. Wikle, R. M. Dorazio, and J. A. Royle. 2007. Hierarchical spatiotemporal matrix models for characterizing invasions. Biometrics 63:558-567.
55. Hui, D. F., Y. Q. Luo, D. Schimel, J. S. Clark, A. Hastings, K. Ogle, and M. Williams. 2008. Converting raw data into ecologically meaningful products. A meeting report on datamodel assimilation in ecology: techniques and applications. Norman, Oklahoma, 22-24 October 2007. EOS, Transactions, American Geophysical Union, 25 January, 2008.
56. Kalisz, S., and M. A. McPeek. 1993. Extinction dynamics, population growth and seed banks: an example using an agestructured annual. Oecologia 95:314-320.
57. King, R., S. P. Brooks, and T. Coulson. 2008. Analyzing complex mark-recapture data in the presence of individual and temporal covariates and model uncertainty. Biometrics 64:1187-1195.
58. Koch, P. L., K. A. Hoppe, and S. D. Webb. 1998. The isotopic ecology of late Pleistocene mammals in North America. Part 1. Florida. Chemical Ecology 152:119-138.
59. Koehler, E., E. Brown, and S. J.-P. A. Haneuse. 2009. On the assessment of Monte Carlo error in simulation-based statistical analyses. American Statistician 63:155-162.
60. LaDeau, S. L., A. M. Kilpatrick, and P. P. Marra. 2007. West Nile virus emergence and large-scale declines of North American bird populations. Nature 447:710-714.
61. Lande, R., and S. H. Orzack. 1988. Extinction dynamics of agestructured populations in a fluctuating environment. Proceedings of the National Academy of Sciences USA 85:7418-7421.
62. Leirs, H., N. C. Stenseth, J. D. Nichols, J. E. Hines, R. Verhagen, and W. Verheyen. 1997. Stochastic seasonality and nonlinear density-dependent factors regulate population size in an African rodent. Nature 389:176-180.
63. Lele, S. R., B. Dennis, and F. Lutscher. 2007. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods. Ecology Letters 10:551-563.
64. Lillegard, M., S. Engen, B.-E. Sæther, V. Grotan, and M. C. Drever. 2008. Estimation of population parameters from aerial counts of North American mallards: a cautionary tale. Ecological Applications 18:197-207.
65. Lima, M., R. Julliard, N. C. Stenseth, and F. M. Jaksic. 2001. Demographic dynamics of a neotropical small rodent (Phyllotis darwini): feedback structure, predation and climatic factors. Journal of Animal Ecology 70:761-775.
66. Lima, M., J. E. Keymer, and F. M. Jaksic. 1999. El Nino- Southern Oscillation-driven rainfall variability and delayed density dependence cause rodent outbreaks in Western South America: linking demography and population dynamics. American Naturalist 153:476-491.
67. Ludwig, D. 1996. Uncertainty and the assessment of extinction probabilities. Ecological Applications 6:1067-1076.
68. Ludwig, D., M. Mangel, and B. Haddad. 2001. Ecology, conservation, and public policy. Annual Review of Ecology and Systematics 32:481-517.
69. Marin, J. M., R. M. Diez, and D. R. Insua. 2003. Bayesian methods in plant conservation biology. Biological Conservation 113:379-387.
70. Maschinski, J., J. E. Baggs, P. Quintana-Ascencio, and E. S. Menges. 2006. Using population viability analysis to predict the effects of climate change on the extinction risk of anendangered limestone endemic shrub, Arizona cliffrose. Conservation Biology 20:218-228.
71. Maunder, M. N. 2004. Population viability analysis based on combining Bayesian, integrated, and hierarchical analyses. Acta Oecologia 26:85-94.
72. Maunder, M. N., S. J. Harley, and J. Hampton. 2006. Including parameter uncertainty in forward projections of computationally intensive statistical population dynamic models. ICES Journal of Marine Science 63:969-979.
73. McMahon, S., and J. Diez. 2007. Scales of association: hierarchical linear models and the measurement of ecological systems. Ecology Letters 10:1-16.
74. Melbourne, B. A., and A. Hastings. 2008. Extinction risk depends strongly on factors contributing to stochasticity. Nature 454:100-103.
75. Menges, E. S. 1999. Ecology and conservation of Florida scrub. Pages 7-22 in R. C. Anderson, J. S. Fralish, and J. Baskin, editors. The savanna, barren, and rock outcrop communities of North America. Cambridge University Press, Cambridge, UK.
76. Menges, E. S. 2000. Population viability analysis in plants: challenges and opportunities. Trends in Ecology and Evolution 15:51-56.
77. Menges, E. S. 2007. Integrating demography and fire management: an example from Florida scrub. Australian Journal of Botany 55:261-272.
78. Menges, E. S., P. J. McIntyre, M. S. Finer, E. Gross, and R. Yahr. 1999. Microhabitat of the narrow Florida scrub endemic Dicerandra christmannii, with comparisons to its congener D. frutescens. Journal of the Torrey Botanical Society 126:24-31.
79. Menges, E. S., and P. F. Quintana-Ascencio. 2004. Population viability analysis with fire in Eryngium cuneifolium: deciphering a decade of demographic data. Ecological Monographs 74:79-99.
80. Menges, E. S., P. F. Quintana-Ascencio, C. W. Weekley, and O. G. Gaoue. 2006. Population viability analysis and fire return intervals for an endemic Florida scrub mint. Biological Conservation 127:115-127.
81. Menges, E. S., C. W. Weekley, S. I. Hamzé, and R. L. Pickert. 2007. Soil preferences for listed plants on the Lake Wales Ridge in Highlands County, Florida. Florida Scientist 70:24-39.
82. Meyer, S. E., D. Quinney, and J. Weaver. 2006. A stochastic population model for Lepidium papilliferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank. American Journal of Botany 93:891-902.
83. Mills, L. S., and M. S. Lindberg. 2002. Sensitivity analysis to evaluate the consequences of conservation actions. Pages 338-366 in S. R. Beissinger and D. R. McCullough, editors. Population viability analysis. University of Chicago Press, Chicago, Illinois, USA.
84. Moloney, K. A. 1986. A generalized algorithm for determining category size. Oecologia 69:176-180.
85. Morales, J. M., D. T. Haydon, J. Frair, K. E. Holsinger, and J. M. Fryxell. 2004. Extracting more out of relocation data: building movement models as mixtures of random walks. Ecology 85:2436-2445.
86. Moritz, M. A., T. J. Moody, L. J. Miles, M. M. Smith, and P. deValpine. 2009. The fire frequency analysis branch of the pyrostatistics tree: sampling decisions and censoring in fire interval data. Environmental and Ecological Statistics 16: 271-289.
87. Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: theory and practice of population viability analysis. Sinauer Associates, Sunderland, Massachusetts, USA.
88. Morris, W. F., S. Tuljapurkar, C. Haridas, E. S. Menges, C. Horvitz, and C. Pfister. 2006. Climate change effects on disturbance-prone populations: elasticities to within- vs. between-disturbance-stage variability. Ecology Letters 9: 1331-1341.
89. Newman, K. B., S. T. Buckland, S. T. Lindley, L. Thomas, and C. Fernandez. 2006. Hidden process models for animal population dynamics. Ecological Applications 16:74-86.
90. O'Hara, R. B., S. Lampila, and M. Orell. 2009. Estimation of rates of births, deaths, and immigration from mark-recapture data. Biometrics 65:275-281.
91. Peres, C. A., et al. 2003. Demographic threats to the sustainability of Brazil nut exploitation. Science 302:2112-2114.
92. Ponciano, J. M., M. L. Taper, B. Dennis, and S. R. Lele. 2009. Hierarchical models in ecology: confidence intervals, hypothesis testing, and model selection using data cloning. Ecology 90:356-362.
93. Punt, A. E., and R. Hilborn. 1997. Fisheries stock assessment and decision analysis: the Bayesian approach. Reviews in Fish Biology and Fisheries 7:35-63.
94. Purves, D. W., M. A. Zavala, and K. Ogle. 2007. Environmental heterogeneity, bird-mediated directed dispersal, and oak woodland dynamics in Mediterranean Spain. Ecological Monographs 77:77-97.
95. Quintana-Ascencio, P. F., E. S. Menges, and C. W. Weekley. 2003. A fire-explicit population viability analysis of Hypericum cumulicola in Florida rosemary scrub. Conservation Biology 17:433-449.
96. Reed, J. M., L. S. Mills, J. B. Dunning, Jr., E. S. Menges, K. S. McKelvey, R. Frye., S. R. Beissinger, M. C. Anstett, and P. Miller. 2002. Emerging issues in population viability analysis. Conservation Biology 16:7-19.
97. Restrepo, V. R., J. M. Hoenig, J. E. Powers, J. W. Baird, and S. C. Turner. 1992. A simple simulation approach to risk and cost analysis, with applications to swordfish and cod fisheries. Fisheries Bulletin U.S. 90:736-748.
98. Rivot, E., E. Prevost, E. Parent, and J. L. Bagliniere. 2004. A Bayesian state-space modeling framework for fitting a salmon stage-structured population dynamic model to multiple time series of field data. Ecological Modelling 179: 463-485.
99. Royle, J. A., M. Kery, R. Gauthier, and H. Schmid. 2007. Hierarchical spatial models of abundance and occurrence from imperfect survey data. Ecological Monographs 77:465-481.
100. Royle, J. A., and C. K. Wikle. 2005. Efficient statistical mapping of avian count data. Environmental and Ecological Statistics 12:225-243.
101. Ruiz, J., R. Gonzales-Quiros, L. Prieto, and G. Navarro. 2009. A Bayesian model for anchovy (Engraulis encrasicolus): the combined forcing of man and environment. Fisheries Oceanography 18:62-76.
102. Runge, M. C., and A. N. Moen. 1998. A modified model for projecting age-structured populations in random environments. Mathematical Biosciences 150:21-41.
103. Rupp, T. S., M. Olson, L. G. Adams, B. W. Dale, K. Joly, J. Henkelman, W. B. Collins, and A. M. Starfield. 2006. Simulating the influences of various fire regimes on Caribou winter habitat. Ecological Applications 16:1730-1743.
104. Schick, R. S., S. R. Loarie, F. Colchero, B. D. Best, A. Boustany, D. A. Conde, P. N. Halpin, L. N. Joppa, C. M. McClellan, and J. S. Clark. 2008. Understanding movementdata and movement processes: current and emerging directions. Ecology Letters 11:1338-1350.
105. Schofield, M. R., R. J. Barker, and D. I. MacKenzie. 2009. Flexible hierarchical mark-recapture modeling for open populations using WinBUGS. Environmental and Ecological Statistics 16:369-387.
106. Shea, K., and the NCEAS Working Group on Population Management. 1998. Management of populations in conservation, harvesting and control. Trends in Ecology and Evolution 13:371-375.
107. Silva, J. F., J. Raventos, and H. Caswell. 1991. Population reponses to fire in a tropical savanna grass, Andropogon semiberbis: a matrix model approach. Journal of Ecology 79: 345-356.
108. Skaug, H. J., and D. A. Fournier. 2006. Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models. Computational Statistics and Data Analysis 51:699-709.
109. Smith, M., H. Caswell, and P. Mettler-Cherry. 2005. Stochastic flood and precipitation regimes and the population dynamics of a threatened floodplain plant. Ecological Applications 15: 1036-1052.
110. Snall, T., R. B. O'Hara, C. Ray, and S. K. Collinge. 2008. Climate-driven spatial dynamics of plague among prairie dog colonies. American Naturalist 171:238-248.
111. Spiegelhalter, D. J., N. G. Best, B. P. Carlin, and A. van der Linde. 2002. Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society 64:583-639.
112. Spiegelhalter, D. J., A. Thomas, N. G. Best, and D. Lunn. 2003. WinBUGS user manual. Version 1.4. Technical report. Medical Research Council Biostatistics Unit, Cambridge, UK.
113. Sullivan, P. 1992. A Kalman filter approach to catch-at-length analysis. Biometrics 48:237-257.
114. Tuljapurkar, S. 1989. An uncertain life: demography in random environments. Theoretical Population Biology 35:227-294.
115. Tuljapurkar, S. 1990. Population dynamics in variable environments. Lecture notes in biomathematics 185. Springer-Verlag, New York, New York, USA.
116. Turner, W. R., D. D. Wilcover, and H. M. Swain. 2006. State of the scrub: conservation progress, management responsibilities, and land acquisition priorities for imperiled species of Florida's Lake Wales Ridge.
117. Van Mantgem, P. J., N. L. Stephenson, M. Keifer, and J. Keeley. 2004. Effects of an introduced pathogen and fire exclusion on the demography of sugar pine. Ecological Applications 14:1590-1602.
118. Ver Hoef, J. M., and K. J. Frost. 2003. A Bayesian hierarchical model for monitoring harbor seal changes in Prince William Sound, Alaska. Environmental and Ecological Statistics 10: 201-219.
119. Wade, P. R. 2000. Bayesian methods in conservation biology. Conservation Biology 14:1308-1316.
120. Wade, P. R. 2002. Bayesian population viability analysis. Pages 213-238 in S. R. Beissinger and D. R. McCullough, editors. Population viability analysis. University of Chicago Press, Chicago, Illinois, USA.
121. Weekley, C. W., D. Gagnon, E. S. Menges, P. F. Quintana-Ascencio, and S. Saha. 2007. Variation in soil moisture in relation to rainfall, vegetation, gaps, and time-since-fire in Florida scrub. Ecoscience 14:377-386.
122. Weekley, C. W., E. S. Menges, and R. L. Pickert. 2008. An ecological map of Florida's Lake Wales Ridge: a new boundary delineation and an assessment of post-Columbian habitat loss. Florida Scientist 71:45-64.
123. Wikle, C. K. 2003. Hierarchical Bayesian models for predicting the spread of ecological processes. Ecology 84:1382-1394.
124. Winship, A. J., and A. W. Trites. 2006. Risk of extirpation of Stellar 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. Marine Mammal Science 22:124-155.
125. Zabel, R. W., M. D. Scheuerell, M. M. McClure, and J. G. Williams. 2006. The interplay between climate variability and density dependence in the population viability of Chinook salmon. Conservation Biology 20:190-200.