The importance of correcting for sampling bias in MaxEnt species distribution models
Tóm tắt
Advancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better‐surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet
Borneo, Southeast Asia.
We collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range‐restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north‐eastern Borneo, we investigated the efficacy of spatial filtering
Spatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased.
We conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.
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Tài liệu tham khảo
Augeri D.M., 2005, On the biogeographic ecology of the Malayan sun bear, 330
Brodie J., 2011, Small carnivores of the Maliau Basin, Sabah, Borneo, including a new locality for Hose's Civet Diplogale hosei, Small Carnivore Conservation, 44, 1
Dormann C.F., 2012, Collinearity: a review of methods to deal with it and a simulation study evaluating their performance, Ecography, 35, 1
Franklin J., 2009, Mapping species distributions. spatial inference and prediction
Hoekman D., 2009, PALSAR land cover mapping methodology validation study Borneo, 1
Hosmer D.W., 1989, Applied logistic regression
Kalkvik H.M., 2011, Investigating niche and lineage diversification in widely distributed taxa: phylogeography and ecological niche modeling of the Peromyscus maniculatus species group, Ecography, 34, 1
Riley S.J., 1999, A terrain ruggedness that quantifies topographic heterogeneity, Intermountain Journal of Science, 5, 23
Rondinini C., 2006, Tradeoffs of different types of species occurrence data for use in systematic conservation planning, Ecology Letters, 9, 1145, 10.1111/j.1461-0248.2006.00970.x
Wilting A., 2010, Diversity of Bornean viverrids and other small carnivores in Deramakot Forests Reserve, Sabah, Malaysia, Small Carnivore Conservation, 42, 10