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J. Sauer, W. Link (2002)
HIERARCHICAL MODELING OF POPULATION STABILITY AND SPECIES GROUP ATTRIBUTES FROM SURVEY DATAEcology, 83
(1991)
Regression with frailty in survival
Regional inference for wildlife survival
Fitch Fitch (1940)
A biogeographical study of the ordinoides artenkreis of garter snakes (genus Thamnophis )Univ. Calif. Publ. Zool., 44
W. Link, J. Sauer (1996)
Extremes in Ecology: Avoiding the Misleading Effects of Sampling Variation in Summary AnalysesEcology, 77
(1993)
Determination of threatened status for the giant garter snake
G. Wylie, M. Casazza, B. Halstead, C. Gregory (2009)
Sex, season, and time of day interact to affect body temperatures of the Giant GartersnakeJournal of Thermal Biology, 34
(2011)
Comparing
(1980)
Status of the giant garter snake Thamnophis couchii gigas (Fitch). California Department of Fish and Game, Inland Fisheries Endangered Species
E. Papadatou, C. Ibáñez, R. Pradel, J. Juste, O. Gimenez (2011)
Assessing survival in a multi-population system: a case study on bat populationsOecologia, 165
M. Casazza, G. Wylie, C. Gregory (2000)
A funnel trap modification for surface collection of aquatic amphibians and reptilesHerpetological review, 31
(2009)
A primer of wildlife event time analysis using WinBUGS
C. Mcgilchrist, C. Aisbett (1991)
Regression with frailty in survival analysis.Biometrics, 47 2
J. Kruschke (2010)
Bayesian data analysis.Wiley interdisciplinary reviews. Cognitive science, 1 5
(1996)
Extremes in
(1989)
Wetlands of the California Central Valley: status and trends: 1939mid-1980’s
H. Fitch (1941)
A Biogeographical study of the ordinoides artenkreis of garter snakes, genus Thamnophis, by Henry S. Fitch.
H. Reinert, D. Cundall (1982)
An Improved Surgical Implantation Method for Radio-Tracking SnakesCopeia, 1982
D. Murray (2006)
On Improving Telemetry-Based Survival Estimation, 70
S. Winterstein, K. Pollock, C. Bunck (2001)
Analysis of Survival Data from Radiotelemetry Studies
(1971)
Animals of California declared to be endangered or threatened
J. Royle, R. Dorazio (2008)
Hierarchical Modeling and Inference in Ecology: The Analysis of Data from Populations, Metapopulations and Communities
S. Beaupre, D. Rossman, N. Ford, R. Seigel (1996)
The Garter Snakes: Evolution and Ecology
R. Team (2014)
R: A language and environment for statistical computing.MSOR connections, 1
(1980)
Status of the giant garter snake Thamnophis couchii gigas (Fitch). California Department of Fish and Game, Inland Fisheries Endangered
The Authors. Animal Conservation © 2011 The Zoological Society of London survival among species with imperfect detection using multilevel analysis of mark-recapture data: a case study on bats
J. Grand, B. Williams, J. Nichols, M. Conroy (2002)
Analysis and Management of Animal Populations
S. Sturtz, U. Ligges, A. Gelman (2005)
R2WinBUGS: A Package for Running WinBUGS from RJournal of Statistical Software, 12
(2003)
WinBUGS User Manual
Papadatou Papadatou, Pradel Pradel, Schaub Schaub, Dolch Dolch, Geiger Geiger, Ibañez Ibañez, Kerth Kerth, Popa‐Lisseanu Popa‐Lisseanu, Schorcht Schorcht, Teubner Teubner, Gimenez Gimenez (2011b)
Comparing survival among species with imperfect detection using multilevel analysis of mark‐recapture data: a case study on batsEcography
(1989)
Wetlands of the California Central Valley: status and trends: 1939-mid-1980's. Portland: U. S. Fish and Wildlife Service
G. Wylie, M. Casazza, C. Gregory, B. Halstead (2010)
Abundance and Sexual Size Dimorphism of the Giant Gartersnake (Thamnophis gigas) in the Sacramento Valley of California, 44
Elise Zipkin, Amielle DeWan, J. Royle (2009)
Impacts of forest fragmentation on species richness: a hierarchical approach to community modellingJournal of Applied Ecology, 46
(1980)
Status of the giant garter snake Thamnophis couchii gigas ( Fitch )
Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but information is borrowed across sites to tell us about survival in each site’: random effects models as means of borrowing strength in survival studies of wild vertebrates Response from the authors: ‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology
Animal Conservation – Wiley
Published: Apr 1, 2012
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