The importance of correcting for sampling bias in MaxEnt species distribution models

Diversity and Distributions - Tập 19 Số 11 - Trang 1366-1379 - 2013
Stephanie Kramer‐Schadt1, Jürgen Niedballa1, John D. Pilgrim2, Boris Schröder3,4, Jana Lindenborn1, Vanessa Reinfelder1, Milena Stillfried1, Ilja Heckmann1, Anne K. Scharf1, Dave M. Augeri5,6, Susan M. Cheyne7,8, Andrew J. Hearn8, Joanna Ross8, David W. Macdonald8, John Mathai9, James A. Eaton10, Andrew J. Marshall11, Gono Semiadi12, Rustam Rustam13, Henry Bernard14, Raymond Alfred15, Hiromitsu Samejima16, J. W. Duckworth17, Christine Breitenmoser‐Würsten18, Jerrold L. Belant19, Heribert Hofer1, Andreas Wilting1
1Leibniz Institute for Zoo and Wildlife Research, Alfred–Kowalke–Straße 17, 10315 Berlin, Germany
2The Biodiversity Consultancy, 3E King’s Parade, Cambridge, CB2 1SJ, UK
3Environmental Modelling Group, Institute of Earth and Environmental Science, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany
4Landscape Ecology Department of Ecology and Ecosystem Management Technische Universität München Emil‐Ramann‐Str. 6 85354 Freising‐Weihenstephan Germany
5College of Natural Resources, Colorado State University, Fort Collins, CO, USA
6Craighead Institute, Bozeman, MT, USA
7Orangutan Tropical Peatland Project, Jalan Semeru No. 91, Bukit Hindu, Palangka Raya, Indonesia
8Wildlife Conservation Research Unit, Department of Zoology, Oxford University, The Recanati-Kaplan Centre, Tubney House, Abingdon Road, Tubney, Abingdon, Oxfordshire, OX13 5QB UK
9Wildlife Conservation Society Malaysia Program, 7 Jalan Ridgeway, 93200 Kuching, Malaysia
10A-3A-5, Casa Indah I, Persiaran Surian, Petaling Jaya, 47410 Malaysia
11Department of Anthropology, University of California, One Shields Avenue, Davis, CA, 95616-8522 USA
12Puslit Biologi LIPI, Jl. Raya Jakarta-Bogor Km. 46, Cibinong, 16911 Indonesia
13Faculty of Forestry, Mulawarman University, Samarinda 75123, East Kalimantan, Indonesia
14Institute for Tropical Biology & Conservation, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
15Borneo Conservation Trust, 5th Floor, Block B, Wisma MUIS, 88100 Kota Kinabalu, Sabah, Malaysia
16Center for Southeast Asian Studies, Kyoto University, Kyoto, Japan
176 Stratton Road, Saltford, Bristol, BS31 3BS UK
18IUCN/SSC Cat Specialist Group c/o KORA, Muri b. Bern, Switzerland
19Carnivore Ecology Laboratory, Forest and Wildlife Research Center, Mississippi State University, Box 9690 MS, Mississippi, 39762 USA

Tóm tắt

AbstractAimAdvancement 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 Viverra tangalunga in Borneo.LocationBorneo, Southeast Asia.MethodsWe 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 versus background manipulation to reduce overprediction or underprediction in specific areas.ResultsSpatial 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.Main ConclusionsWe 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.

Từ khóa


Tài liệu tham khảo

10.1111/j.1365-2699.2006.01584.x

Augeri D.M., 2005, On the biogeographic ecology of the Malayan sun bear, 330

10.1016/j.ecolmodel.2009.10.033

10.1111/j.1600-0587.2011.06871.x

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

10.1111/j.1749-4877.2012.00314.x

10.1017/S0952836902001073

10.1111/j.1541-0420.2012.01779.x

10.1111/j.2007.0906-7590.05171.x

Dormann C.F., 2012, Collinearity: a review of methods to deal with it and a simulation study evaluating their performance, Ecography, 35, 1

10.1111/j.1600-0587.2009.05901.x

10.1146/annurev.ecolsys.110308.120159

10.1111/j.2006.0906-7590.04596.x

10.1111/j.1472-4642.2010.00725.x

10.1017/S0376892997000088

Franklin J., 2009, Mapping species distributions. spatial inference and prediction

10.1111/j.1365-2664.2007.01408.x

10.1016/j.biocon.2011.03.010

10.1111/j.0906-7590.2006.04700.x

10.1002/joc.1276

Hoekman D., 2009, PALSAR land cover mapping methodology validation study Borneo, 1

Hosmer D.W., 1989, Applied logistic regression

10.1371/journal.pone.0022873

10.1644/10-MAMM-A-155.1

10.1016/j.mambio.2009.10.002

10.1016/j.actao.2007.02.001

10.1890/1051-0761(2003)013[0853:ASAOFA]2.0.CO;2

10.1890/02-5364

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

10.1126/science.1155193

10.1111/j.1472-4642.2006.00293.x

10.1016/j.biocon.2009.12.038

10.1111/j.1600-0587.2011.06888.x

10.1111/j.0906-7590.2005.03957.x

10.1111/j.1466-8238.2007.00358.x

10.2193/0022-541X(2005)069[0849:WATIWP]2.0.CO;2

10.1371/journal.pone.0010360

10.1111/j.1365-2699.2006.01594.x

10.1139/z06-197

10.1111/j.0906-7590.2008.5378.x

10.1016/j.ecolmodel.2005.03.026

10.1890/07-2153.1

10.1111/j.2007.0906-7590.05041.x

10.1046/j.1365-2699.2003.00946.x

10.1890/03-5374

10.1016/j.ecolmodel.2005.10.003

10.1111/j.1541-0420.2012.01824.x

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

10.1111/j.2041-210X.2011.00182.x

10.1890/ES10-00207.1

10.1016/j.biocon.2008.11.002

10.1371/journal.pone.0055158

10.1111/j.1365-2699.2009.02174.x

10.1890/10-1171.1

10.1214/10-AOAS331

10.1371/journal.pone.0009612

Wilting A., 2010, Diversity of Bornean viverrids and other small carnivores in Deramakot Forests Reserve, Sabah, Malaysia, Small Carnivore Conservation, 42, 10

10.1111/j.1472-4642.2008.00482.x

10.1111/2041-210x.12004

Thông tin
Thông tin xuất bản

Diversity and Distributions

Tập 19 Số 11

1366-1379

Thông tin tác giả