Could Protected Areas in Brazil’s Semi-Arid Conserve Endangered Birds Facing Climatic and Land Cover Changes?


  • Tiago Castro Silva Instituto Chico Mendes de Conservação da Biodiversidade
  • Lara Gomes Côrtes Instituto Chico Mendes de Conservação da Biodiversidade
  • Marinez Ferreira de Siqueira Instituto de Pesquisa do Jardim Botânico do Rio de Janeiro



Protected areas act as pillars on which conservation strategies are built. Besides human activities, global climate changes are an additional concern to species’ conservation. In northeastern Brazil, climate change should lead to a replacement of the current native vegetation by semi-desert vegetation. This study evaluates whether the protected areas of the Caatinga can contribute to the maintenance of suitable climatic conditions for endangered birds over time in the face of global climate changes and land cover change. We used ecological niche models as input layers in a spatial prioritization program, in which stability indices were used to weight the targets. Results predicted that most taxa (18) will have their suitability lowered in the future, and all taxa (23) will have their ecological niche geographically displaced. However, our results showed that the Caatinga’s protected areas system integrated with a set of priority areas can maintain suitable climatic conditions for endangered birds in the face of climate change and land cover change. On average, Caatinga’s protected areas system could protect climatic stability areas at least 1.7 times greater than the scenarios without it. This reinforces the importance of protected areas as a biodiversity conservation strategy. 


Araújo, M. B. 2009. Climate change and spatial conservation planning, p. 172–184. In A. Moilanen, K. E. Wilson, & H. P. Possingham (Eds.), Climate Change and Spatial Conservations Planning. Oxford University Press.

Araújo, M. B., Alagador, D., Cabeza, M., Nogués-Bravo, D., & Thuiller, W. 2011. Climate change threatens European conservation areas. Ecology Letters, 14(5), 484–492.

Araújo, M. B., & New, M. 2007. Ensemble forecasting of species distributions. Trends in Ecology & Evolution, 22(1), 42–47.

Baselga, A., & Araújo, M. B. 2009. Individualistic vs community modelling of species distributions under climate change. Ecography, 32(1), 55–65.

Booth, T. H., Nix, H. A., Busby, J. R., & Hutchinson, M. F. 2014. Bioclim : the first species distribution modelling package, its early applications and relevance to most current MaxEnt studies. Diversity and Distributions, 20(1), 1–9.

Breiman, L. 2001. Random Forests. Machine Learning, 45(1), 5–32.

Carrol, C., Dunk, J. R., & Moilanen, A. 2010. Optimizing resiliency of reserve networks to climate change: multispecies conservation planning in the Pacific Northwest, USA. Global Change Biology, 16(3), 891–904.

Cavalcanti, I. F. A., & Shimizu, M. H. 2012. Climate Fields over South America and Variability of SACZ and PSA in HadGEM2-ES. American Journal of Climate Change, 01(03), 132–144.

Cortes, C., & Vapnik, V. 1995. Support-vector networks. Machine Learning, 20(3), 273–297.

Groves, C. R., Game, E. T., Anderson, M. G., Cross, M., Enquist, C., Ferdaña, Z., Shafer, S. L. 2012. Incorporating climate change into systematic conservation planning. Biodiversity and Conservation, 21(7), 1651–1671.

Hannah, L., Midgley, G., Andelman, S., Araújo, M., Hughes, G., Martinez-Meyer, E., Williams, P. 2007. Protected area needs in a changing climate. Frontiers in Ecology and the Environment, 5(3), 131–138.

Hijmans, R. J., Phillips, S., Leathwick, J., & Elith, J. 2013. Dismo: Species distribution modeling. Vienna, Austria: The R Foundation for Statistical Computing. <>. (Acesso em 2015)

ICMBio, (Instituto Chico Mendes de Conservação da Biodiversidade), 2014. Portaria no 92, de 2 de setembro de 2014.

Keppel, G., Van Niel, K. P., Wardell-Johnson, G. W., Yates, C. J., Byrne, M., Mucina, L., Franklin, S. E. 2012. Refugia: identifying and understanding safe havens for biodiversity under climate change. Global Ecology and Biogeography, 21(4), 393–404.

Kujala, H., Moilanen, A., Araújo, M. B., Cabeza, M., & Williams, P. 2013. Conservation Planning with Uncertain Climate Change Projections. PLoS ONE, 8(2), e53315.

Lemes, P., Loyola, R. D., Possinghma, H., Butchart, S., & Collingham, Y. 2013. Accommodating Species Climate-Forced Dispersal and Uncertainties in Spatial Conservation Planning. PLoS ONE, 8(1), e54323.

Liu, C., White, M., & Newell, G. 2013. Selecting thresholds for the prediction of species occurrence with presence-only data. Journal of Biogeography, 40, 778–789.

Madsen, H., & Thyregod, P. 2011. Introduction to general and generalized linear models. CRC Press. < to General and Generalized Linear Models&f=false> (Acesso em 2015)

Magrin, G. O., Marengo, J. A., Boulanger, J.-P., Buckeridge, M. S., Castellanos, E., Poveda, G., Vicuña, S. 2014. Central and South America. p. 1499–1566. In V. R. Barros, C. B. Field, D. J. Dokken, M. D. Mastrandrea, & K. J. Mach (Eds.), Climate Change 2014: Impacts, Adaptation and Vulnerability. Cambridge: Cambridge University Press.

Mahalanobis, P.C. 1936. On the generalised distance in statistic. Proceedings National Institute of Science of India, 2(1), 49–55.

Manhães, A.P., Loyola, R., Mazzochini, G.G., Ganade, G., Oliveira-Filho, A.T., Carvalho, A.R. 2017. Low-cost strategies for protecting ecosystem services and biodiversity. Biological Conservation, 217, 187-194.

Marengo, J. A., & Bernasconi, M. 2015. Regional differences in aridity/drought conditions over Northeast Brazil: present state and future projections. Climatic Change, 129(1–2), 103–115.

Margules, C. R., & Pressey, R. L. 2000. Systematic conservation planning. Nature, 405(6783), 243–253.

MMA (Ministério do Meio Ambiente) 2002. Caatinga. In Avaliação e identificação de áreas e ações prioritárias para a conservação, utilização sustentável e repartição dos benefícios da biodiversidade nos biomas brasileiros. (p. 404). Brasília - DF: MMA/SBF. <> (Acesso em 2015)

MMA (Ministério do Meio Ambiente) 2011. Monitoramento do desmatamento nos biomas brasileiros por satélite. Brasília - DF. <> (Acesso em 2015)

MMA (Ministério do Meio Ambiente) 2014a. Portaria no 444 de 17 de dezembro de 2014. Diário Oficial da União. 17/12/2014

MMA (Ministério do Meio Ambiente) 2014b. Portaria no 445 de 17 de dezembro de 2014. Diário Oficial da União. 17/12/2014

Moilanen, A., Franco, A. M. ., Early, R. I., Fox, R., Wintle, B., & Thomas, C. D. 2005. Prioritizing multiple-use landscapes for conservation: methods for large multi-species planning problems. Proceedings of the Royal Society of London: Biological Sciences, 272(1575).

Moilanen, A., Pouzols, F. M., Laura, M., Victoria, V., Arponen, A., Leppanen, J., & Kujala, H. 2014. Spatial conservation planning methods and software - ZONATION - Version 4 User Manual. Helsinki: University of Helsinki, Finland. <> (Acesso em 2015).

Naidoo, R., Balmford, A., Ferraro, P. J., Polasky, S., Ricketts, T. H., & Rouget, M. 2006. Integrating economic costs into conservation planning. Trends in Ecology & Evolution, 21(12), 681–687.

Nenzén, H. K., & Araújo, M. B. 2011. Choice of threshold alters projections of species range shifts under climate change. Ecological Modelling, 222(18), 3346–3354.

Oyama, M. D., & Nobre, C. A. 2003. A new climate-vegetation equilibrium state for Tropical South America. Geophysical Research Letters, 30(23).

Parmesan, C., & Yohe, G. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature, 421(6918), 37–42.

Pearson, R. G., & Dawson, T. P. 2003). Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography, 12(5), 361–371.

Pfafstetter, O. (2012). Bacias Hidrográficas Ottocodificadas (Níveis Otto). Agência Nacional de Águas. <> (Acesso em 2015)

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

R Core Team. 2015. R: A language and environment for statistical computing. R Foundation for Statistical Computing. <> (Acesso em 2015).

Rao, C. R. 1973. Prasantha Chandra Mahalanobis. 1893-1972. Biographical Memoirs of Fellows of the Royal Society, 19, 454–492.

Rayfield, B., Moilanen, A., & Fortin, M.-J. 2009. Incorporating consumer–resource spatial interactions in reserve design. Ecological Modelling, 220(5), 725–733.

Root, T. L., Price, J. T., Hall, K. R., Schneider, S. H., Rosenzweig, C., & Pounds, J. A. 2003. Fingerprints of global warming on wild animals and plants. Nature, 421(6918), 57–60.

Silva, J. M. C., Souza, M. A., Bieber, A. G. D., & Carlos, C. J. 2003. Aves da Caatinga: Status, uso do habitat e sensitividade. In: I. R. Leal, M. Tabarelli, & J. M. C. Silva (Eds.), Ecologia e conservação da caatinga (p. 822). Recife: Universitária da UFPE.

Silveira, C. S., Filho, F. A. S., Costa, A. A., & Cabral, A. L. 2013. Avaliação de desempenho dos modelos do CMIP5 quanto à representação dos padrões de variação da precipitação no século XX sobre a região nordeste do Brasil, Amazônia e bacia do Prata e análise das projeções para o cenário RCP8.5. Revista Brasileira de Meteorologia, 28(3), 317–330.

Tabarelli, M., & Silva, J. M. C. 2003. Áreas e ações prioritárias para a conservação da biodiversidade da Caatinga. In: I. R. Leal, M. Tabarelli, & J. M. C. Silva (Eds.), Ecologia e conservação da caatinga (p. 822). Recife: Universitária da UFPE.

Virkkala, R., Heikkinen, R. K., Fronzek, S., Leikola, N., & Nelson, K. 2013. Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network. PLoS ONE, 8(5), e63376.

Wiens, J. J., & Graham, C. H. 2005. Niche Conservatism: Integrating Evolution, Ecology, and Conservation Biology. Annual Review of Ecology, Evolution, and Systematics, 36(1), 519–539.

Zhang, L., Liu, S., Sun, P., Wang, T., Wang, G., Zhang, X., & Wang, L. 2015. Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties. PLOS ONE, 10(3), e0120056.






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