Insights on the role of forest cover and on the changes in forest cover on thirty-five endangered mammal species distributions

Abstract

The changes in forest cover can determine the survival of terrestrial endangered mammal species in the wild. This study assessed the impacts of forest cover changes on endangered mammal species distribution at global scale aiming to understand how the changes in forest cover may have impacted the distributions of 35 endangered small and large-body terrestrial mammals. There were used forest data obtained from time-series analyses of Landsat images between 2000 and 2014, species occurrence records collected by observations between 2000 and 2015 of Global Biodiversity Information Facility and species range data of International Union for Nature Conservation (IUCN) of the year 2015, to test the ‘natural and resource conditions’ hypothesis. Hypothesis on ‘natural and resource conditions’ produced models with high prediction accuracy of above 70 percent for 88 percent of 35 species models. The changes in forest cover explained species occurrences in 10 percent of all species models. In average, 59 percent of species occurrence records overlapped with species range data. The 51 percent of all species had no occurrence records between 2000 and 2015. Species and forest data collection as well as transnational cooperation for conservation of species roaming in the wild in upland forested areas and in cross-border areas may be critical for endangered mammal species conservation.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • Allouche, O., Tsoar, A. & Kadmon, R., 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43(6), pp.1223–1232. Available at: https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2664.2006.01214.x.

  • Anselin, L., 1988. Spatial Econometrics: Methods and Models, Dordrecht: Kluwer Academic Publishers.

  • Anselin, L., Syabri, I. & Kho, Y., 2006. GeoDa: An Introduction to Spatial Data Analysis. Geographical Analysis 38 (1), 5–22.

  • Baker, A.D. & Leberg, P.L., 2018. Impacts of human recreation on carnivores in protected areas. PLOS ONE, 13(4), pp. 1–21. Available at: https://doi.org/10.1371/journal.pone.0195436.

  • Barnosky, A.D. et al., 2016. Variable impact of late-Quaternary megafaunal extinction in causing ecological state shifts in North and South America. Proceedings of the National Academy of Sciences of the United States of America, 113(4), pp. 856–861. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739530/.

  • Baselga, A. et al., 2012. Global patterns in the shape of species geographical ranges reveal range determinants. Journal of Bio-geography, 39(4), pp. 760–771. Available at: http://dx.doi.org/10.1111/j.1365-2699.2011.02612.x.

  • Buxton, R.T. et al., 2017. Noise pollution is pervasive in U.S. protected areas. Science, 356(6337), pp. 531–533. Available at: http://science.sciencemag.org/content/356/6337/531.

  • Carroll, C. & Miquelle, D.G., 2006. Spatial viability analysis of Amur tiger Panthera tigris altaica in the Russian Far East: the role of protected areas and landscape matrix in population persistence. Journal of Applied Ecology, 43(6), pp. 1056–1068. Available at: http://dx.doi.org/10.1111/j.1365-2664.2006.01237.x.

  • Ceballos, G. & Ehrlich, P.R., 2006. Global mammal distributions, biodiversity hotspots, and conservation. Proceedings of the National Academy of Sciences, 103(51), pp. 19374–19379. Available at: http://www.pnas.org/content/103/51/19374.abstract.

  • Chefaoui, R.M. & Lobo, J.M., 2008. Assessing the effects of pseudo-absences on predictive distribution model performance. Ecological modelling, 210(4), pp. 478–486.

  • Conrad, O. et al., 2015. System for Automated Geoscientific Analyses (SAGA) v. 2.1.4. Geoscientific Model Development, 8(7), pp. 1991–2007.

  • DeFries, R. et al., 2007. Land use change around protected areas: Management to balance human needs and ecological function. Ecological Applications, 17(4), pp. 1031–1038. Available at: http://dx.doi.org/10.1890/05-1111.

  • Distler, T. et al., 2009. Determinants and prediction of broad-scale plant richness across the western neotropics. Annals of the Missouri Botanical Garden, 96(3), pp. 470–491. Available at: http://dx.doi.org/10.3417/2008034.

  • Dormann, C.F., 2007. Effects of incorporating spatial autocorrelation into the analysis of species distribution data. Global Ecology and Biogeography, 16(2), pp. 129–138. Available at: http://dx.doi.org/10.1111/j.1466-8238.2006.00279.x.

  • Elith, J. & Leathwick, J.R., 2009. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics, 40(1), pp. 677–697. Available at: https://doi.org/10.1146/annurev.ecolsys.110308.120159.

  • Environmental Systems Research Institute, 2016. ArcGIS Release 10.3. Redlands, CA.

  • Estavillo, C., Pardini, R. & Rocha, P.L.B. da, 2013. Forest Loss and the Bio-diversity Threshold: An Evaluation Considering Species Habitat Requirements and the Use of Matrix Habitats. PLoS ONE, 8(12), p.e82369. Available at: http://dx.doi.org/10.1371%2Fjournal.pone.0082369.

  • Ester, P. et al., 2018. From tropical shelters to temperate defaunation: The relationship between agricultural transition stage and the distribution of threatened mammals. Global Ecology and Biogeography, 27(6), pp. 647–657. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.12725.

  • Faurby, S. & Svenning, J.C., 2015. Historic and prehistoric human-driven extinctions have reshaped global mammal diversity patterns. Diversity and Distributions, 21(10), pp. 1155–1166. Available at: http://dx.doi.org/10.1111/ddi.12369.

  • Feng, G. et al., 2017. Historical anthropogenic footprints in the distribution of threatened plants in China. Biological Conservation, 210, pp. 3–8.

  • Fernández, N. et al., 2003. Identifying breeding habitat for the Iberian lynx: Inferences from fine-scale spatial analysis. Ecological Applications, 13(5), pp. 1310–1324. Available at: http://dx.doi.org/10.1890/02-5081.

  • Fernandez, N., Delibes, M. & Palomares, F., 2006. Landscape evaluation in conservation: molecular sampling and habitat modeling for the Iberian lynx. Ecological applications : a publication of the Ecological Society of America, 16(3), pp. 1037–1049.

  • Fischer, G. et al., 2008. Global Agroecological Zones Assessment for Agriculture (GAEZ 2008), Laxenburg. Austria. Available at: www.fao.org.

  • Fischer, J. & Lindenmayer, D.B., 2007. Landscape modification and habitat fragmentation: a synthesis. Global Ecology and Bio-geography, 16(3), pp. 265–280. Available at: http://dx.doi.org/10.1111/j.1466-8238.2007.00287.x.

  • Foley, J.A. et al., 2005. Global Consequences of Land Use. Science, 309(5734), pp. 570–574. Available at: http://www.sciencemag.org/cgi/content/abstract/309/5734/570.

  • Gaillard, J.M. et al., 2010. Habitat-performance relationships: finding the right metric at a given spatial scale. Philos Trans R Soc Lond B Biol Sci, 365(1550), pp. 2255–2265.

  • GBIF.org, 2018a. GBIF Occurrence Download. Downloaded on 13 January 2018. https://doi.org/10.15468/dl.gfufyq.

  • GBIF.org, 2018b. GBIF Occurrence Download. Downloaded on 13 January 2018. https://doi.org/10.15468/dl.jgy1ug.

  • Hansen, A.J. & DeFries, R., 2007. Ecological mechanisms linking protected areas to surrounding lands. Ecological Applications, 17(4), pp. 974–988. Available at: http://dx.doi.org/10.1890/05-1098.

  • Hansen, M.C. et al., 2013. High-resolution global maps of 21st-century forest cover change. Science (New York, N.Y.), 342(6160), pp. 850–853.

  • Hesterberg, T.C., 2015. What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum. The American Statistician, 69(4), pp. 371–386. Available at: https://doi.org/10.1080/00031305.2015.1089789.

  • Hosmer, D.W. & Lemeshow, S., 2000. Applied Logistic Regression, John Wiley and Sons (ed.), New York, USA, 373pp. Available at: http://ecsocman.edu.ru/db/msg/2425.html.

  • Iojă C. I. et al., 2010. The efficacy of Romania’s protected areas network in conserving biodiversity. Biological conservation, 143:2468-2.

  • IUCN, 2012. IUCN Red List Categories and Criteria: Version 3.1. Second edition., Gland, Switzerland and Cambridge, UK: IUCN. iv + 32pp. Available at: http://s3.amazonaws.com/iucnredlist-newcms/staging/public/attachments/3097/redlist_cats_crit_en.pdf.

  • IUCN, 2017. IUCN Spatial Data Resources. Available at: http://www.iucnredlist.org/technical-documents/red-list-training/iucnspatialresources [Accessed October 18, 2016].

  • IUCN, 2016. The IUCN Red List of Threatened Species. Version 2016-2. Available at: http://www.iucnredlist.org/technical-documents/spatial-data [Accessed October 18, 2016].

  • IUCN and UNEP-WCMC, 2015. The World Database on Protected Areas (WDPA) [Online], [version July 2015], Cambridge, UK:UNEPWCMC. Available at: www.protectedplanet.net. [Accessed May 3, 2016].

  • Johnson, C.J., Seip, D.R. & Boyce, M.S., 2004. A quantitative approach to conservation planning: using resource selection functions to map the distribution of mountain caribou at multiple spatial scales. Journal of Applied Ecology, 41(2), pp. 238–251. Available at: http://dx.doi.org/10.1111/j.0021-8901.2004.00899.x.

  • Kanagaraj, R. et al., 2011. Assessing habitat suitability for tiger in the fragmented Terai Arc Landscape of India and Nepal. Ecography, 34(6), pp. 970–981. Available at: http://dx.doi.org/10.1111/j.1600-0587.2010.06482.x.

  • Kehoe, L. et al., 2016. Agriculture rivals biomes in predicting global species richness. Ecography, p.n/a-n/a. Available at: http://dx.doi.org/10.1111/ecog.02508.

  • Knorn, J. et al., 2012. Forest restitution and protected area effectiveness in post-socialist Romania. Biological Conservation, 146(1), pp. 204–212. Available at: http://www.sciencedirect.com/science/article/pii/S0006320711004836.

  • Liu, C. et al., 2005. Selecting thresholds of occurrence in the prediction of species distributions. Ecography, 28(3), pp. 385–393. Available at: http://dx.doi.org/10.1111/j.0906-7590.2005.03957.x.

  • Liu, J. et al., 2001. Ecological Degradation in Protected Areas: The Case of Wolong Nature Reserve for Giant Pandas. Science, 292(5514), pp. 98–101.

  • MacKinnon, J. & De Wulf, R., 1994. Designing protected areas for giant pandas in China. In R. I. Miller, ed. Mapping the Diversity of Nature. Dordrecht: Springer Netherlands, pp. 127–142. Available at: http://dx.doi.org/10.1007/978-94-011-0719-8_8.

  • Di Marco, M. et al., 2017. Limitations and trade-offs in the use of species distribution maps for protected area planning. Journal of Applied Ecology, 54(2), pp. 402–411. Available at: http://dx.doi.org/10.1111/1365-2664.12771.

  • McCullagh, P. & Nelder, J.A., 1989. Generalized Linear Models. Chapman and Hall, London, England, 511 pp.

  • Mohd-Azlan, J. & Sanderson, J., 2007. Geographic distribution and conservation status of the bay cat Catopuma badia, a Bornean endemic. Oryx, 41(3), pp. 394–397. Available at: https://www.cambridge.org/core/article/geographic-distribution-and-conservation-status-of-the-bay-cat-catopuma-badia-a-bornean-endemic/F80BFBE97BE28558BCAA3173F5A343E3.

  • Naves, J. et al., 2003. Endangered Species Constrained by Natural and Human Factors: The Case of Brown Bears in Northern Spain. Conservation Biology, 17(5), pp. 1276–1289. Available at: http://www.jstor.org/stable/3588953.

  • Nüchel, J. et al., 2018. Snub-nosed monkeys (Rhinopithecus): potential distribution and its implication for conservation. Biodiversity and Conservation, 27(6), pp. 1517–1538. Available at: https://doi.org/10.1007/s10531-018-1507-0.

  • Pekin, B.K. & Pijanowski, B.C., 2012. Global land use intensity and the endangerment status of mammal species. Diversity and Distributions, 18(9), pp. 909–918. Available at: http://dx.doi.org/10.1111/j.1472-4642.2012.00928.x.

  • Phillips, S.J., Anderson, R.P. & Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3–4), pp. 231–259.

  • Pimm, S.L. & Raven, P., 2000. Biodiversity: Extinction by numbers. Nature, 403(6772), pp.843–845. Available at: http://dx.doi.org/10.1038/35002708.

  • Pollock, L.J., Thuiller, W. & Jetz, W., 2017. Large conservation gains possible for global biodiversity facets. Nature, 546(7656), pp. 141–144.

  • R Development Core Team, 2018. Bootstrap Resampling for Mixed Effects and Plain Models. Available at: github.com/ColmanHumphrey/glmmboot.

  • R Development Core Team, R., 2011. R: A Language and Environment for Statistical Computing R. D. C. Team, ed. R Foundation for Statistical Computing, 1(2.11.1), p. 409. Available at: http://www.r-project.org.

  • Ramankutty, N. et al., 2010. Global Agricultural Lands: Pastures, 2000. Data distributed by the Socioeconomic Data and Applications Center (SEDAC). Available at: http://sedac.ciesin.columbia.edu/es/aglands.html [Accessed May 26, 2016].

  • Rogers, L.M. & Gorman, M.L., 1995. The population dynamics of small mammals living in set-aside and surrounding semi-natural and crop land. Journal of Zoology, 236(3), pp. 451–464. Available at: http://dx.doi.org/10.1111/j.1469-7998.1995.tb02724.x.

  • Rozendaal, D. M. A. et al., ‘Biodiversity recovery of Neotropical secondary forests,’ Sci. Adv., vol. 5, no. 3, p. eaau3114, Mar. 2019.

  • Soto, C. & Palomares, F., 2015. Coexistence of sympatric carnivores in relatively homogeneous Mediterranean landscapes: functional importance of habitat segregation at the fine-scale level. Oecologia, 179(1), pp. 223–235.

  • Strindberg, S. et al., 2018. Guns, germs, and trees determine density and distribution of gorillas and chimpanzees in Western Equatorial Africa. Science Advances, 4(4). Available at: http://advances.sciencemag.org/content/4/4/eaar2964.abstract.

  • Veach, V., Moilanen, A. & Di Minin, E., 2017. Threats from urban expansion, agricultural transformation and forest loss on global conservation priority areas. PLOS ONE, 12(11), p.e0188397. Available at: https://doi.org/10.1371/journal.pone.0188397.

  • Viña, A. and Liu, J. (2017) ‘Hidden roles of protected areas in the conservation of biodiversity and ecosystem services’, Ecosphere, 8(6), p. ecs2.1864. doi: 10.1002/ecs2.1864.

  • Wich, S.A. et al., 2014. Will Oil Palm’s Homecoming Spell Doom for Africa’s Great Apes? Current Biology, 24(14), pp. 1659–1663. Available at: http://dx.doi.org/10.1016/j.cub.2014.05.077.

  • Yu, G. et al., 2003. Feeding habitat of giant pandas (Ailuropoda melanoleuca): why do they prefer bamboo patch edges? Journal of Zoology, 261(3), pp. 307–312. Available at: https://www.cambridge.org/core/article/feeding-habitat-of-giant-pandas-ailuropoda-melanoleuca-why-do-they-prefer-bamboo-patch-edges/78CB23D3484FBB2EC43222CAEB126EDE.

OPEN ACCESS

Journal + Issues

Search