Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias
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A Purvis, 2000, Predicting extinction risk in declining species, Proc R Soc B Biol Sci, 267, 1947, 10.1098/rspb.2000.1234
GM Mace, 2008, Quantification of extinction risk: IUCN's system for classifying threatened species, Conserv Biol, 22, 1424, 10.1111/j.1523-1739.2008.01044.x
IUCN (2001) IUCN Red List Categories and Criteria, Version 3.1. Gland, Switzerland: IUCN – The World Conservation Union.
G Harris, 2008, Range size and extinction risk in forest birds, Conserv Biol, 22, 163, 10.1111/j.1523-1739.2007.00798.x
ASL Rodrigues, 2006, The value of the IUCN Red List for conservation, Trends Ecol Evol, 21, 71, 10.1016/j.tree.2005.10.010
N Myers, 2000, Biodiversity hotspots for conservation priorities, Nature, 403, 853, 10.1038/35002501
R Mittermeier, 1998, Biodiversity hotspots and major tropical wilderness areas: approaches to setting conservation priorities, Conserv Biol, 12, 516, 10.1046/j.1523-1739.1998.012003516.x
A Moilanen, 2005, Prioritizing multiple-use landscapes for conservation: methods for large multi-species planning problems, Proc R Soc B Biol Sci, 272, 1885, 10.1098/rspb.2005.3164
Peterson A (2006) Uses and requirements of ecological niche models and related distributional models. Biodivers Informatics: 59–72.
Ferrier S (1984) The status of the Rufous Scrub-bird Atrichornis rufescens: habitat, geographical variation and abundance. PhD thesis. Armidale, Australia: University of New England.
M Austin, 2006, Evaluation of statistical models used for predicting plant species distributions: Role of artificial data and theory, Ecol Modell, 199, 197, 10.1016/j.ecolmodel.2006.05.023
J Elith, 2009, Species Distribution Models: Ecological Explanation and Prediction Across Space and Time, Annu Rev Ecol Evol Syst, 40, 677, 10.1146/annurev.ecolsys.110308.120159
J Soberón, 2005, Interpretation of models of fundamental ecological niches and species' distributional areas, Biodivers Informatics, 2, 1, 10.17161/bi.v2i0.4
J Elith, 2011, A statistical explanation of MaxEnt for ecologists, Divers Distrib, 17, 43, 10.1111/j.1472-4642.2010.00725.x
Elith J, Burgman M (2002) Predictions and their validation: Rare plants in the Central Highlands, Victoria, Australia. Predicting Species Occurrences: Issues of Accuracy and Scale. Washington, USA: Island Press. pp. 303–313.
A Jimenez-Valverde, 2011, Use of niche models in invasive species risk assessments, Biol Invasions, 13, 2785, 10.1007/s10530-011-9963-4
J Jeschke, 2008, Usefulness of bioclimatic models for studying climate change and invasive species, Ann N Y Acad Sci, 1134, 1, 10.1196/annals.1439.002
S Sinclair, 2010, How useful are species distribution models for managing biodiversity under future climates, Ecol Soc, 15, 8, 10.5751/ES-03089-150108
JS Thorn, 2009, Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus), Divers Distrib, 15, 289, 10.1111/j.1472-4642.2008.00535.x
Franklin J (2009) Mapping Species Distributions: Spatial Inference and Prediction. Cambridge, UK: Cambridge University Press.
M Boyce, 1999, Relating populations to habitats using resource selection functions, Trends Ecol Evol, 14, 268, 10.1016/S0169-5347(99)01593-1
Manly BFJ, McDonald LL, Thomas D (1993) Resource Selection by Animals: Statistical Design and Analysis for Field Studies. Chapman & Hall.
Ripley BD (1996) Pattern Recognition and Neural Networks. Cambridge, UK: Cambridge University Press.
Phillips SJ, Dudík M, Schapire RE (2004) A maximum entropy approach to species distribution modeling. Proceedings of the twenty-first international conference on Machine learning. New York, New York, USA: ACM. p. 83.
Breiman L, Friedman J, Stone CJ, Olshen RA (1984) Classification and Regression Trees. Chapman & Hall.
J Elith, 2006, Novel methods improve prediction of species' distributions from occurrence data, Ecography, 29, 129, 10.1111/j.2006.0906-7590.04596.x
MS Wisz, 2008, Effects of sample size on the performance of species distribution models, Divers Distrib, 14, 763, 10.1111/j.1472-4642.2008.00482.x
SJ Phillips, 2006, Maximum entropy modeling of species geographic distributions, Ecol Modell, 190, 231, 10.1016/j.ecolmodel.2005.03.026
Elith J, Leathwick JR (2006) Conservation prioritisation using species distribution modelling. In: Moilanen A, Wilson KA, Possingham HP, editors. Spatial conservation prioritization: quantitative methods and computational tools. Oxford, UK: Oxford University Press.
RJ Hijmans, 2005, Very high resolution interpolated climate surfaces for global land areas, Int J Climatol, 25, 1965, 10.1002/joc.1276
KH Kozak, 2008, Integrating GIS-based environmental data into evolutionary biology, Trends Ecol Evol, 23, 141, 10.1016/j.tree.2008.02.001
R Dennis, 2000, Bias in butterfly distribution maps: the influence of hot spots and recorder's home range, J Insect Conserv, 4, 73, 10.1023/A:1009690919835
R Kadmon, 2004, Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models, Ecol Appl, 14, 401, 10.1890/02-5364
PJ Leitão, 2011, Effects of geographical data sampling bias on habitat models of species distributions: a case study with steppe birds in southern Portugal, Int J Geogr Inf Sci, 25, 439, 10.1080/13658816.2010.531020
N Bystriakova, 2012, Sampling bias in geographic and environmental space and its effect on the predictive power of species distribution models, Syst Biodivers, 10, 1, 10.1080/14772000.2012.705357
TC Edwards, 2006, Effects of sample survey design on the accuracy of classification tree models in species distribution models, Ecol Modell, 199, 132, 10.1016/j.ecolmodel.2006.05.016
B Loiselle, 2008, Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes?, J Biogeogr, 35, 105, 10.1111/j.1365-2699.2007.01779.x
S Reddy, 2003, Geographical sampling bias and its implications for conservation priorities in Africa, J Biogeogr, 30, 1719, 10.1046/j.1365-2699.2003.00946.x
MM Syfert, 2013, The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models, PLoS One, 8, e55158, 10.1371/journal.pone.0055158
GC Costa, 2009, Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot, Biodivers Conserv, 19, 883, 10.1007/s10531-009-9746-8
J Beck, 2013, Spatial bias in the GBIF database and its effect on modelling species' geographic distributions, Ecol Inform, 19, 10, 10.1016/j.ecoinf.2013.11.002
Y Fourcade, 2013, Confronting expert-based and modelled distributions for species with uncertain conservation status: a case study from the Corncrake (Crex crex), Biol Conserv, 167, 161, 10.1016/j.biocon.2013.08.009
MB Araújo, 2006, Five (or so) challenges for species distribution modelling, J Biogeogr, 33, 1677, 10.1111/j.1365-2699.2006.01584.x
Hijmans RJ, Elith J (2012) Species distribution modeling with R. <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://cran.r-project.org/web/packages/dismo/vignettes/dm.pdf" xlink:type="simple">http://cran.r-project.org/web/packages/dismo/vignettes/dm.pdf</ext-link>.
SJ Phillips, 2008, Transferability, sample selection bias and background data in presence-only modelling: a response to Peterson, et al. (2007), Ecography, 31, 272, 10.1111/j.0906-7590.2008.5378.x
SJ Phillips, 2009, Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data, Ecol Appl, 19, 181, 10.1890/07-2153.1
Dudík M, Schapire RE, Phillips SJ (2005) Correcting sample selection bias in maximum entropy density estimation. Appearing in Advances in Neural Information Processing Systems. <volume>Vol</volume>: . 18.
D Rödder, 2009, Niche shift versus niche conservatism? Climatic characteristics of the native and invasive ranges of the Mediterranean house gecko (Hemidactylus turcicus), Glob Ecol Biogeogr, 18, 674, 10.1111/j.1466-8238.2009.00477.x
PE Osborne, 2002, Should data be partitioned spatially before building large-scale distribution models?, Ecol Modell, 157, 249, 10.1016/S0304-3800(02)00198-9
S Kramer-Schadt, 2013, The importance of correcting for sampling bias in MaxEnt species distribution models, Divers Distrib, 19, 1366, 10.1111/ddi.12096
S Varela, 2014, Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models, Ecography
RA Boria, 2014, Spatial filtering to reduce sampling bias can improve the performance of ecological niche models, Ecol Modell, 275, 73, 10.1016/j.ecolmodel.2013.12.012
SD Veloz, 2009, Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models, J Biogeogr, 36, 2290, 10.1111/j.1365-2699.2009.02174.x
O Arino, 2008, GLOBCOVER The most detailed portrait of Earth, ESA Bull - Eur Sp Agency, 136, 24
P Maisongrande, 2004, VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products, Int J Remote Sens, 25, 9, 10.1080/0143116031000115265
RK Heikkinen, 2006, Methods and uncertainties in bioclimatic envelope modelling under climate change, Prog Phys Geogr, 6, 751, 10.1177/0309133306071957
RD Sagarin, 2002, The “abundant centre” distribution: to what extent is it a biogeographical rule?, Ecol Lett, 5, 137, 10.1046/j.1461-0248.2002.00297.x
Nelson A (2008) Travel time to major cities: A global map of Accessibility. Luxembourg: Office for Official Publications of the European Communities.
K McCarthy, 2012, Predicting Species Distributions from Samples Collected along Roadsides, Conserv Biol, 26, 68, 10.1111/j.1523-1739.2011.01754.x
F Ihlow, 2012, On the brink of extinction? How climate change may affect global chelonian species richness and distribution, Glob Chang Biol, 18, 1520, 10.1111/j.1365-2486.2011.02623.x
J Elith, 2010, The art of modelling range-shifting species, Methods Ecol Evol, 1, 330, 10.1111/j.2041-210X.2010.00036.x
RM Chefaoui, 2008, Assessing the effects of pseudo-absences on predictive distribution model performance, Ecol Modell, 210, 478, 10.1016/j.ecolmodel.2007.08.010
N Barve, 2011, The crucial role of the accessible area in ecological niche modeling and species distribution modeling, Ecol Modell, 222, 1810, 10.1016/j.ecolmodel.2011.02.011
P Acevedo, 2012, Delimiting the geographical background in species distribution modelling, J Biogeogr, 39, 1383, 10.1111/j.1365-2699.2012.02713.x
CF Dormann, 2007, Methods to account for spatial autocorrelation in the analysis of species distributional data: a review, Ecography, 30, 609, 10.1111/j.2007.0906-7590.05171.x
D Rödder, 2009, Global Amphibian Extinction Risk Assessment for the Panzootic Chytrid Fungus, Diversity, 1, 52, 10.3390/d1010052
Stiels D, Schidelko K, Engler JO, Elzen R, Rödder D (2011) Predicting the potential distribution of the invasive Common Waxbill Estrilda astrild (Passeriformes: Estrildidae). J Ornithol: 769–780.
S Dray, 2007, The ade4 package: implementing the duality diagram for ecologists, J Stat Softw, 22, 1, 10.18637/jss.v022.i04
S Gonzalez, 2011, Population distribution models: species distributions are better modeled using biologically relevant data partitions, BMC Ecol, 11, 20, 10.1186/1472-6785-11-20
JM Lobo, 2008, AUC: a misleading measure of the performance of predictive distribution models, Glob Ecol Biogeogr, 17, 145, 10.1111/j.1466-8238.2007.00358.x
A Jimenez-Valverde, 2012, Discrimination capacity in species distribution models depends on the representativeness of the environmental domain, Glob Ecol Biogeogr, 22, 508, 10.1111/geb.12007
EA Freeman, 2008, {PresenceAbsence}: An R Package for Presence Absence Analysis, J Stat Softw, 23, 1, 10.18637/jss.v023.i11
T Schoener, 1968, The Anolis lizards of Bimini: resource partitioning in a complex fauna, Ecology, 49, 704, 10.2307/1935534
DL Warren, 2008, Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution, Evolution, 62, 2868, 10.1111/j.1558-5646.2008.00482.x
J Bray, 1957, An ordination of the upland forest communities of southern Wisconsin, Ecol Monogr, 7, 325, 10.2307/1942268
D Rödder, 2011, Quantitative metrics of overlaps in Grinnellian niches: advances and possible drawbacks, Glob Ecol Biogeogr, 20, 915, 10.1111/j.1466-8238.2011.00659.x
O Broennimann, 2012, Measuring ecological niche overlap from occurrence and spatial environmental data, Glob Ecol Biogeogr, 21, 481, 10.1111/j.1466-8238.2011.00698.x
C Liu, 2005, Selecting thresholds of occurrence in the prediction of species distributions, Ecography, 28, 385, 10.1111/j.0906-7590.2005.03957.x
MB Araújo, 2005, Validation of species–climate impact models under climate change, Glob Chang Biol, 11, 1504, 10.1111/j.1365-2486.2005.01000.x
JA Swets, 1988, Measuring the accuracy of diagnostic systems, Science, 240, 1285, 10.1126/science.3287615
A Jimenez-Valverde, 2014, Threshold-dependence as a desirable attribute for discrimination assessment: implications for the evaluation of species distribution models, Biodivers Conserv, 23, 369, 10.1007/s10531-013-0606-1
W Thuiller, 2004, Effects of restricting environmental range of data to project current and future species distributions, Ecography, 27, 165, 10.1111/j.0906-7590.2004.03673.x
JJ VanDerWal, 2009, Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?, Ecol Modell, 220, 589, 10.1016/j.ecolmodel.2008.11.010
WM Adams, 2004, Biodiversity conservation and the eradication of poverty, Science, 306, 1146, 10.1126/science.1097920