Predictive Modeling and Mapping of Malayan Sun Bear (Helarctos malayanus) Distribution Using Maximum Entropy

PLoS ONE

Volumn 7, Issue 10, 2012, Pages

  Nazeri, Mona ^a   Jusoff, Kamaruzaman ^a   Madani, Nima ^a   Mahmud, Ahmad Rodzi ^a   Bahman, Abdul Rani ^a   Kumar, Lalit ^b  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^b UNIVERSITY OF NEW ENGLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BEAR; ENTROPY; EVERGREEN RAIN FOREST; GEOGRAPHIC DISTRIBUTION; GEOGRAPHIC INFORMATION SYSTEM; HABITAT; MALAYAN SUN BEAR; NONHUMAN; PREDICTION; SPECIES DISTRIBUTION; STATISTICAL MODEL; TROPICAL RAIN FOREST;

ANIMALS; BIODIVERSITY; CLIMATE CHANGE; ECOLOGY; ENTROPY; FORECASTING; GEOGRAPHY; MALAYSIA; MODELS, BIOLOGICAL; POPULATION DENSITY; POPULATION DYNAMICS; TREES; TROPICAL CLIMATE; URSIDAE;

HELARCTOS MALAYANUS;

EID: 84868153017     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0048104     Document Type: Article

References (49)

1. IUCN (1996) Red List of Threatened Animals. IUCN, Gland, Switzerland and Cambridge, UK.
2. Frederick C, Kyes R, Hunt K, Collins D, Durrant B, et al. (2010) Methods of estrus detection and correlates of the reproductive cycle in the sun bear (Helarctos malayanus). Theriogenology 74: 1121-1135.
3. Augeri DM (2005) On the biogeographic ecology of the Malayan sun bear. PhD Dissertation. University of Cambridge, Cambridge, UK.330 p.
4. Te Wong S, Servheen C, Ambu L, (2002) Food habits of malayan sun bears in lowland tropical forests of borneo. Ursus 13: 127-136.
5. Steinmetz R, Garshelis DL, Chutipong W, Seuaturien N, (2011) The Shared Preference Niche of Sympatric Asiatic Black Bears and Sun Bears in a Tropical Forest Mosaic. PLoS ONE 6: e14509.
6. Te Wong S, Servheen CW, Ambu L, (2004) Home range, movement and activity patterns, and bedding sites of Malayan sun bears Helarctos malayanus in the Rainforest of Borneo. Biological Conservation 119: 169-181.
7. Guisan A, Zimmermann NE, (2000) Predictive habitat distribution models in ecology. Ecological Modelling 135: 147-186.
8. Elith J, Graham CH, Anderson RP, Dudík M, Ferrier S, et al. (2006) Novel methods improve prediction of species' distributions from occurrence data. Ecography 29: 129-151.
9. Graham CH, Ferrier S, Huettman F, Moritz C, Peterson AT, (2004) New developments in museum-based informatics and applications in biodiversity analysis. Trends in Ecology & Evolution 19: 497-503.
10. Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, et al. (2004) Extinction risk from climate change. Nature 427: 145-148.
11. Graham CH, Mortiz C,Williams SE (2006) Habitat history improves prediction of biodivesity in a rainforest fauna. Proceeding of the Natural Academy of Science. 632-636.
12. Václavík T, Meentemeyer RK, (2009) Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions? Ecological Modelling 220: 3248-3258.
13. Jones CC, Acker SA, Halpern CB, (2010) Combining local- and large-scale models to predict the distributions of invasive plant species. Ecological Applications 20: 311-326.
14. Hirzel AH, Posse B, Oggier PA, Crettenand Y, Glenz C, et al. (2004) Ecological requirements of reintroduced species and the implications for release policy: the case of the bearded vulture. Oxford, ROYAUME-UNI: Blackwell. 14 p.
15. Imam E, Kushwaha SPS, Singh A, (2009) Evaluation of suitable tiger habitat in Chandoli National Park, India, using spatial modelling of environmental variables. Ecological Modelling 220: 3621-3629.
16. Zafra-Calvo N, Cerro R, Fuller T, Lobo JM, Rodríguez MÁ, et al. (2010) Prioritizing areas for conservation and vegetation restoration in post-agricultural landscapes: A Biosphere Reserve plan for Bioko, Equatorial Guinea. Biological Conservation 143: 787-794.
17. Guisan A, Broennimann O, Engler R, Vust M, Yoccoz NG, et al. (2006) Using niche-based models to improve the sampling of rare species. Conservation biology: the journal of the Society for Conservation Biology 20: 501-511.
18. Jackson CR, Robertson MP, (2011) Predicting the potential distribution of an endangered cryptic subterranean mammal from few occurrence records. Journal for Nature Conservation 19: 87-94.
19. Phillips SJ, Anderson RP, Schapire RE, (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231-259.
20. Stockwell D, (1999) The GARP modelling system: problems and solutions to automated spatial prediction. International Journal of Geographical Information Science 13: 143-158.
21. Hirzel AH, Hausser J, Chessel D, Perrin N, (2002) Ecological-Niche Factor Analysis: how to compute habitat suitability maps without absence data? Ecology 83: 2027-2036.
22. Calenge C, Darmon G, Basille M, Loison A, Jullien JM, (2008) The factorial decomposition of the Mahalanobis distances in habitat selection studies. Ecology 89: 555-566.
23. Anderson RP, Gómez-Laverde M, Peterson AT, (2002) Geographical distributions of spiny pocket mice in South America: Insights from predictive models. Global Ecology and Biogeography 11: 131-141.
24. Tsoar A, Allouche O, Steinitz O, Rotem D, Kadmon R, (2007) A comparative evaluation of presence-only methods for modelling species distribution. Diversity and Distributions 13: 397-405.
25. IUCN red list of threatened species website. Available: http://www.iucnredlist.org. Accessed 2012 April 22.
26. Meijaarad E, Sheil D, Nasi R, Augri D, Rosenbaum B, et al. (2005) Life After Logging: Reconciling wildlife conservation and production forestry in Indonesian Borneo. Bogor, Indonesia. 349.
27. Fredrikkson G, (2005) Human-sun bear conflicts in East Kalimantan, Indonesian Borneo. Ursus 16: 130-137.
28. Keith DA, Akcakaya HR, Thuiller W, Midgley GF, Pearson RG, et al. (2008) Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models. Biology Letters 4: 560-563.
29. Sodhi NS, Koh LP, Brook BW, Ng PKL, (2004) Southeast Asian biodiversity: an impending disaster. Trends in Ecology & Evolution 19: 654-660.
30. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J, (2000) Biodiversity hotspots for conservation priorities. Nature 403: 853-858.
31. Sodhi NS, Brook BW (2006) Southeast Asian Biodiversity in Crisis: Cambridge University, New York.
32. Peh KSH, de Jong J, Sodhi NS, Lim SLH, Yap CAM, (2005) Lowland rainforest avifauna and human disturbance: persistence of primary forest birds in selectively logged forests and mixed-rural habitats of southern Peninsular Malaysia. Biological Conservation 123: 489-505.
33. Servheen C, Herrero S, Peyton B (1999) Bears: status survey and conservation action plan. IUCN, Gland, Switzerland.
34. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.
35. MEDIAS-France (2008) GlobCover Land Cover v2 2008 database. European Space Agency, European Space Agency GlobCover Project.
36. Huete A, Didan K, Miura T, Rodriguez EP, Gao X, et al. (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 83: 195-213.
37. Phillips SJ, Anderson RP, Schapire RE, (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231-259.
38. Phillips SJ, Dudik M, (2008) Modeling of species distributions with MaxEnt: new extentions and a comprehensive evaluation. Ecography 31: 161-175.
39. Phillips S, (2008) Response to "Transferability and model evaluation in ecological niche modelling". Ecography 31: 272-278.
40. Phillips SJ, Dudik M, Schapire RE (2004) A maximum entropy approach to species distribution modeling. Proceeding of the 21st International Conference on Machine Learning New York,USA. ACM press.
41. Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, et al. (2010) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions: no-no.
42. Papeş M, Gaubert P, (2007) Modelling ecological niches from low numbers of occurrences: Assessment of the conservation status of poorly known viverrids (Mammalia, Carnivora) across two continents. Diversity and Distributions 13: 890-902.
43. Saatchi SB, Wolfgang TS, Hans M, Scott S, Thomas B, (2008) Modeling distribution of Amazonian tree species and diversity using remote sensing measurements. Remote Sensing of Environment 112: 2000-2017.
44. Mingyang L, Yunwei J, Kumar S, Stohlgren TJ, (2008) Modeling potential habitats for alien species Dreissena polymorpha in Continental USA. Acta Ecologica Sinica 28: 4253-4258.
45. Suárez-Seoane S, García de la Morena EL, Morales Prieto MB, Osborne PE, de Juana E, (2008) Maximum entropy niche-based modelling of seasonal changes in little bustard (Tetrax tetrax) distribution. Ecological Modelling 219: 17-29.
46. Carroll C, (2010) Role of climatic niche models in focal-species-based conservation planning: Assessing potential effects of climate change on Northern Spotted Owl in the Pacific Northwest, USA. Biological Conservation 143: 1432-1437.
47. Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson A, (2007) Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar. Journal of Biogeography 34: 102-117.
48. Lobo JM, Jiménez-Valverde A, Real R, (2008) AUC: a misleading measure of the performance of predictive distribution models. Global Ecology and Biogeography 17: 145-151.
49. Elith J (2000) Quantitative methods for modeling species habitat: comparative performance and an application to Australian plants. In: Ferson S, Burgman M, editors. Quantitative methods for conservation biology. Springer. 39-58.