Addressing risks to biodiversity arising from a changing climate: The need for ecosystem restoration in the Tana River Basin, Kenya
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80. Neumann R. Primitive ideas: protected area buffer zones and the politics of land in Africa. Development and change. 1997; 28: 559–582. 81. Barendse J, Roux D, Erfmann W, Baard J, Kraaij T, Nieuwoudt C. Viewshed and sense of place as con- servation features: A case study and research agenda for South Africa’s national parks. Koedoe. 2016; 58: 1–16. 82. WWF Kenya. State of the Forest in Kenya 2018. 2018. Available: https://www.wwfkenya.org/state_of__ forest_in_kenya.cfm 83. Hallegatte S. Strategies to adapt to an uncertain climate change. Global environmental change. 2009; 19: 240–247. 84. GoK. National Climate Change Response Strategy. Nairobi: Government of Kenya; 2010. 85. GoK. Kenya National Climate Change Action Plan. Nairobi: Government of Kenya; 2012. 86. KEFRI. A Guide to Tree Planting in Kenya. Nairobi: KEFRI; 1990. 87. Mappin B, Chauvenet AL, Adams VM, Di Marco M, Beyer HL, Venter O, et al. Restoration priorities to achieve the global protected area target. Conservation Letters. 2019; 12: e12646. 88. Gardner CJ, Bicknell JE, Baldwin-Cantello W, Struebig MJ, Davies ZG. Quantifying the impacts of defaunation on natural forest regeneration in a global meta-analysis. Nature Communications. 2019; 10: 4590. https://doi.org/10.1038/s41467-019-12539-1 PMID: 31611554 89. Arbieu U, Gru¨ newald C, Schleuning M, Bo¨ hning-Gaese K. The importance of vegetation density for tourists’ wildlife viewing experience and satisfaction in African savannah ecosystems. PloS one. 2017; 12. https://doi.org/10.1371/journal.pone.0185793 PMID: 28957420
90. Tylianakis JM, Didham RK, Bascompte J, Wardle DA. Global change and species interactions in terres- trial ecosystems. Ecology Letters. 2008; 11: 1351–1363. https://doi.org/10.1111/j.1461-0248.2008. 01250.x PMID: 19062363 91. McDermott Long O, Warren R, Price J, Brereton TM, Botham MS, Franco AMA. Sensitivity of UK butter- flies to local climatic extremes: which life stages are most at risk? Journal of Animal Ecology. 2017; 86: 108–116. https://doi.org/10.1111/1365-2656.12594 PMID: 27796048 92. Medek DE, Schwartz J, Myers SS. Estimated Effects of Future Atmospheric CO2 Concentrations on Protein Intake and the Risk of Protein Deficiency by Country and Region. Environmental Health Per- spectives. 2017; 125: 087002. https://doi.org/10.1289/EHP41 PMID: 28885977 93. Thomas CD. Habitat use and geographic ranges of butterflies from the wet lowlands of Costa Rica. Bio- logical Conservation. 1991; 55: 269–281. 94. Arau´jo MB, Anderson RP, Ma´rcia Barbosa A, Beale CM, Dormann CF, Early R, et al. Standards for dis- tribution models in biodiversity assessments. Sci Adv. 2019; 5: eaat4858. https://doi.org/10.1126/ sciadv.aat4858 PMID: 30746437 95. Stockwell DRB, Peterson AT. Effects of sample size on accuracy of species distribution models. Eco- logical Modelling. 2002; 148: 1–13. https://doi.org/10.1016/S0304-3800(01)00388-X 96. Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, et al. Effects of sample size on the per- formance of species distribution models. Diversity and Distributions. 2008; 14: 763–773. https://doi.org/ 10.1111/j.1472-4642.2008.00482.x
97. Fourcade Y, Engler JO, Ro¨ dder D, Secondi J. Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correct- ing Sampling Bias. PLOS ONE. 2014; 9: e97122. https://doi.org/10.1371/journal.pone.0097122 PMID: 24818607 PLOS ONE Risks to Kenya’s biodiversity from climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0254879 July 21, 2021 25 / 25