Nondetection sampling bias in marked presence-only data
Article first published online: 2 DEC 2013
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Ecology and Evolution
Volume 3, Issue 16, pages 5225–5236, December 2013
How to Cite
Ecology and Evolution 2013; 3(16): 5225–5236
- Issue published online: 22 DEC 2013
- Article first published online: 2 DEC 2013
- Manuscript Accepted: 23 OCT 2013
- Manuscript Revised: 21 OCT 2013
- Manuscript Received: 20 AUG 2013
- Platte River Recovery Implementation Program
- National Science Foundation Integrative Graduate Education and Research Traineeship. Grant Number: NSF-DGE-0903469
- 2012. Comparative interpretation of count, presence-absence and point methods for species distribution models. Methods Ecol. Evol. 3:177–187. , , and .
- 2006. Five (or so) challenges for species distribution modelling. J. Biogeogr. 33:1677–1688. , and .
- 2001. A comprehensive review of observational and site evaluation data of migrant whooping cranes in the United States, 1943–99. Available at http://www.npwrc.usgs.gov/resource/birds/wcdata/pdf/wcdata.pdf. (accessed 17 July 2013). , and .
- 1993. Empirical models for the spatial distribution of wildlife. J. Appl. Ecol. 30:478–495. , and .
- 1993. Statistics for spatial data. Wiley, New York.
- 2003. Statistical analysis of spatial point patterns. Hodder Education, London, U.K.
- 2012. Predicting the Geographic Distribution of a Species from Presence-Only Data Subject to Detection Errors. Biometrics 68:1–25.
- 1994. An introduction to the bootstrap. Chapman and Hall/CRC, Boca Raton, FL. , and .
- 2007. Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines. Divers. Distrib. 13:265–275. , and .
- 2006. Novel methods improve prediction of species' distributions from occurrence data. Ecography, 29, 129–151. , , , , , , et al.
- 2008. A working guide to boosted regression trees. J. Anim. Ecol. 77:802–813. , , and .
- 2007. Bayesian weight trimming for generalized linear regression models. Surv. Methodol. 33:23–34.
- 2013. Finite-sample equivalence in statistical models for presence only data. Ann. Appl. Stat. in press. and .
- 2004. Removing GPS collar bias in habitat selection studies. J. Appl. Ecol. 41:201–212. , , , , , , et al.
- 2000. Predictive habitat distribution models in ecology. Ecol. Model. 135:147–186. , and .
- 2002. Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecol. Model. 157:89–100. , , and .
- 2013. Inference from presence-only data; the ongoing controversy. Ecography 36:864–867. , and .
- 2009. The elements of statistical learning: data mining, inference, and prediction. 2nd ed. Springer, New York, NY. , , and .
- 2010. How much can we learn about missing data?: an exploration of a clinical trial in psychiatry. J. Royal Statist. Soc.: Series A 173:593–612. , , and .
- 2008. Sensitivity of species-distribution models to error, bias, and model design: An application to resource selection functions for woodland caribou. Ecol. Model. 213:143–155. , and .
- 2011. Towards the modelling of true species distributions. J. Biogeogr. 38:617–618.
- 2013. The importance of correcting for sampling bias in MaxEnt species distribution models (M. Robertson, Ed.). Divers. Distrib. 19:1366–1379. , , , , , , et al.
- 2002. Statistical analysis with missing data. Wiley, New York, NY. , and .
- 2002. Resource selection by animals: statistical design and analysis for field studies. Kluwer Academic Publishers, Dordrecht. , , , , and .
- 2012. Eliciting expert knowledge in conservation science. Cons. Biol., 26, 29–38. , , , , , , and .
- 2012. Strategy for modelling nonrandom missing data mechanisms in observational studies using Bayesian methods. J. Offic. Stat. 28:279–302. , , , and .
- 2013. How long should we ignore imperfect detection of species in the marine environment when modelling their distribution. Fish Fisheries. (in press). .
- 2006. Modelling distribution and abundance with presence-only data. J. Appl. Ecol. 43:405–412. and .
- 2012. Expert knowledge and its application in landscape ecology. Springer, New York, NY. , , and .
- 2006. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190:231–259. , , and .
- 2009. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol. Appl. 19:181–197. , , , , , , et al.
- 2013. Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology. Biometrics 69:274–281. , and .
- 2011. Does accounting for imperfect detection improve species distribution models? Ecography 34:659–670. , , , and .
- 1976. Inference and missing data. Biometrika 63:581–592.
- 2000. Recent applications of point process methods in forestry statistics. Stat. Sci. 15:61–78. , and .
- 2013. Opportunistic citizen science data of animal species produce reliable estimates of distribution trends if analysed with occupancy models. J. Appl. Ecol. 50:1450–1458 , , and .
- 2013. Advancing our thinking in presence-only and used-available analysis. J. Anim. Ecol. 82:1125–1134 , and .
- 2010. Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology. Ann. Appl. Stat. 4:1383–1402. , and .
- 2013. Fitting and interpreting occupancy models. PLoS ONE 8:e52015. , , and .
- 2007. Eliciting and using expert opinions about dropout bias in randomized controlled trials. Clinical Trials 4:125–139. , , , and .
- 2013. Presence-only modelling using MAXENT: when can we trust the inferences? Methods Ecol. Evol. 4:236–243. , , , , , , et al.
- 2012. Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation. Statist. Methodol. in press. , , , , and .
- 2009. Mixed effects models and extensions in ecology with R. Springer, New York, NY. , , , , and .