Integrated species distribution models: combining presence‐background data and site‐occupancy data with imperfect detection
暂无分享,去创建一个
Yang Wang | Matt White | Robert M. Dorazio | Ascelin Gordon | Lewi Stone | M. White | L. Stone | R. Dorazio | A. Gordon | Vira Koshkina | V. Koshkina | Yang Wang
[1] Brett J Furnas,et al. Detecting diversity: emerging methods to estimate species diversity. , 2014, Trends in ecology & evolution.
[2] Mark S. Boyce,et al. Modelling distribution and abundance with presence‐only data , 2006 .
[3] Steven J. Phillips,et al. Point process models for presence‐only analysis , 2015 .
[4] W. Jetz,et al. Uncertainty, priors, autocorrelation and disparate data in downscaling of species distributions , 2014 .
[5] J. Andrew Royle,et al. ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.
[6] J. Elith,et al. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .
[7] T. Hastie,et al. Bias correction in species distribution models: pooling survey and collection data for multiple species , 2014, Methods in ecology and evolution.
[8] D. Warton,et al. Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology , 2013, Biometrics.
[9] T. Hastie,et al. Finite-Sample Equivalence in Statistical Models for Presence-Only Data. , 2012, The annals of applied statistics.
[10] Robert M Dorazio,et al. Predicting the Geographic Distribution of a Species from Presence‐Only Data Subject to Detection Errors , 2012, Biometrics.
[11] R. Fletcher,et al. Integrated models that unite local and regional data reveal larger-scale environmental relationships and improve predictions of species distributions , 2016, Landscape Ecology.
[12] Alastair Scott,et al. Fitting binary regression models with case-augmented samples , 2006 .
[13] Trevor Hastie,et al. Inference from presence-only data; the ongoing controversy. , 2013, Ecography.
[14] D. Warton,et al. Correction note: Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology , 2010, 1011.3319.
[15] Robert P. Anderson,et al. Maximum entropy modeling of species geographic distributions , 2006 .
[16] M. Kéry,et al. Predicting species distributions from checklist data using site‐occupancy models , 2010 .
[17] Avishek Chakraborty,et al. Point pattern modelling for degraded presence‐only data over large regions , 2011 .
[18] M. Hooten,et al. Hierarchical Species Distribution Models , 2016 .
[19] Tom Fawcett,et al. An introduction to ROC analysis , 2006, Pattern Recognit. Lett..
[20] Damaris Zurell,et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance , 2013 .
[21] Brendan A. Wintle,et al. Is my species distribution model fit for purpose? Matching data and models to applications , 2015 .
[22] H. Possingham,et al. IMPROVING PRECISION AND REDUCING BIAS IN BIOLOGICAL SURVEYS: ESTIMATING FALSE‐NEGATIVE ERROR RATES , 2003 .
[23] Robert M. Dorazio,et al. Accounting for imperfect detection and survey bias in statistical analysis of presence‐only data , 2014 .
[24] José J. Lahoz-Monfort,et al. Ignoring Imperfect Detection in Biological Surveys Is Dangerous: A Response to ‘Fitting and Interpreting Occupancy Models' , 2014, PloS one.