Abstract
The global network of protected areas (PAs) is systematically biased towards remote and unproductive places. Consequently, the processes threatening biodiversity are not halted and conservation impact—defined as the beneficial environmental outcomes arising from protection relative to the counterfactual of no intervention—is smaller than previously thought. Yet, many conservation plans still target species’ representation, which can fail to lead to impact by not considering the threats they face, such as land conversion and climate change. Here we aimed to identify spatial conservation priorities that minimize the risk of land conversion, while retaining sites with high value for threatened plants at risk from climate change in the Brazilian Cerrado. We compared a method of sequential implementation of conservation actions to a static strategy applied at one time-step. For both schedules of conservation actions, we applied two methods for setting priorities: (i) minimizing expected habitat conversion and prioritizing valuable sites for threatened plants (therefore maximizing conservation impact), and (ii) prioritizing sites based only on their value for threatened plants, regardless of their vulnerability to land conversion (therefore maximizing representation). We found that scenarios aimed at maximizing conservation impact reduced total vegetation loss, while still covering large proportions of species’ ranges inside PAs and priority sites. Given that planning to avoid vegetation loss provided these benefits, vegetation information could represent a reliable surrogate for overall biodiversity. Besides allowing for the achievement of two distinct goals (representation and impact), the impact strategies also present great potential for implementation, especially under current conservation policies.
Similar content being viewed by others
References
Andam KS, Ferraro PJ, Pfaff A et al (2008) Measuring the effectiveness of protected area networks in reducing deforestation. Proc Natl Acad Sci USA 105:16089–16094. https://doi.org/10.1073/pnas.0800437105
Araújo MB, New M (2007) Ensemble forecasting of species distributions. Trends Ecol Evol 22:42–47. https://doi.org/10.1016/j.tree.2006.09.010
Arponen A, Heikkinen RK, Thomas CD, Moilanen A (2005) The value of biodiversity in reserve selection: representation, species weighting, and benefit functions. Conserv Biol 19:2009–2014. https://doi.org/10.1111/j.1523-1739.2005.00218.x
Ascough JC, Maier HR, Ravalico JK, Strudley MW (2008) Future research challenges for incorporation of uncertainty in environmental and ecological decision-making. Ecol Modell 219:383–399. https://doi.org/10.1016/j.ecolmodel.2008.07.015
Bernard E, Penna LAO, Araújo E (2014) Downgrading, downsizing, degazettement, and reclassification of protected areas in Brazil. Conserv Biol 28:939–950. https://doi.org/10.1111/cobi.12298
Breiman L (2001) Random forests. Mach Learn 45(1):5–32. https://doi.org/10.1017/CBO9781107415324.004
Broennimann O, Treier UA, Müller-Schärer H et al (2007) Evidence of climatic niche shift during biological invasion. Ecol Lett 10:701–709
Brook BW, Sodhi NS, Bradshaw CJA (2008) Synergies among extinction drivers under global change. Trends Ecol Evol 23:453–460. https://doi.org/10.1016/j.tree.2008.03.011
Busby JR (1991) BIOCLIM: a bioclimate analysis and prediction system. In: Margules CR, Austin MP (eds) Nature conservation: cost effective biological surveys and data analysis. CSIRO, Canberra, pp 64–68
Carpenter G, Gillison AN, Winter J (1993) Domain—a flexible modeling procedure for mapping potential distributions of plants and animals. Biodivers Conserv 2:667–680. https://doi.org/10.1007/BF00051966
Carranza T, Balmford A, Kapos V, Manica A (2014) Protected area effectiveness in reducing conversion in a rapidly vanishing ecosystem: the Brazilian Cerrado. Conserv Lett 7:216–223. https://doi.org/10.1111/conl.12049
Carroll C, Noss RF, Paquet PC (2001) Carnivores as focal species for conservation planning in the rocky mountain region. Ecol Appl 11:961–980
Carvalho SB, Brito JC, Crespo EG et al (2011) Conservation planning under climate change: toward accounting for uncertainty in predicted species distributions to increase confidence in conservation investments in space and time. Biol Conserv 144:2020–2030. https://doi.org/10.1016/j.biocon.2011.04.024
Child D (1990) The essentials of factor analysis, 2nd edn. Cassel Educational Limited, London
Costello C, Polasky S (2004) Dynamic reserve site selection. Resour Energy Econ 26:157–174. https://doi.org/10.1016/j.reseneeco.2003.11.005
Crouzeilles R, Beyer HL, Mills M et al (2015) Incorporating habitat availability into systematic planning for restoration: a species-specific approach for Atlantic Forest mammals. Divers Distrib. https://doi.org/10.1111/ddi.12349
Dessai S, Hulme M (2004) Does climate adaptation policy need probabilities? Clim Policy 4:107–128. https://doi.org/10.1080/14693062.2004.9685515
Devillers R, Pressey RL, Grech A et al (2014) Reinventing residual reserves in the sea: are we favouring ease of establishment over need for protection? Aquat Conserv Mar Freshw Ecosyst 25:480–504. https://doi.org/10.1002/aqc.2445
Drechsler M (2005) Probabilistic approaches to scheduling reserve selection. Biol Conserv 122:253–262. https://doi.org/10.1016/j.biocon.2004.07.015
Engler R, Guisan A, Rechsteiner L (2004) An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. J Appl Ecol 41:263–274. https://doi.org/10.1111/j.0021-8901.2004.00881.x
Faleiro FV, Machado RB, Loyola RD (2013) Defining spatial conservation priorities in the face of land-use and climate change. Biol Conserv 158:248–257. https://doi.org/10.1016/j.biocon.2012.09.020
Ferraro PJ (2009) Counterfactual thinking and impact evaluation in environmental policy. In: Birnbaum M, Mickwitz P (eds) Environmental program and policy evaluation: new directions for evaluation. Jossey-Bass, San Francisco, pp 75–84
Forzza RC, Leitman PM, Costa A et al (2010) Catálogo de plantas e fungos do Brasil, vol 2. Andrea Jakobsson Estúdio: Instituto de Pesquisas Jardim Botânico, Rio de Janeiro
Friedman JH (1991) Multivariate adaptive regression splines. Ann Stat 19:1–141
Hansen AJ, Neilson RP, Dale VH et al (2001) Global change in forests: responses of species, communities, and biomes. Bioscience 51:765. https://doi.org/10.1641/0006-3568(2001)051%5b0765:GCIFRO%5d2.0.CO;2
Hijmans ARJ, Phillips S, Leathwick J, Elith J (2012) Package “dismo”. Species distribution modeling
Hijmans RJ, van Etten J, Cheng J et al (2016) Package “raster”. Geographic data analysis and modeling
Hoekstra JM, Boucher TM, Ricketts TH, Roberts C (2005) Confronting a biome crisis: global disparities of habitat loss and protection. Ecol Lett 8:23–29. https://doi.org/10.1111/j.1461-0248.2004.00686.x
IPCC (2014) Climate change 2014: Synthesis report. Contribution of working groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on climate change. Core Writing Team, Geneva
IUCN (2014) Guidelines for using the IUCN Red List Categories and Criteria
Jones KR, Watson JEM, Possingham HP, Klein CJ (2016) Incorporating climate change into spatial conservation prioritisation: a review. Biol Conserv 194:121–130. https://doi.org/10.1016/j.biocon.2015.12.008
Joppa LN, Pfaff A (2009) High and far: biases in the location of protected areas. PLoS ONE 4:1–6. https://doi.org/10.1371/journal.pone.0008273
Kadmon R, Farber O, Danin A (2004) Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models. Ecol Appl 14:401–413. https://doi.org/10.1890/02-5364
Klink CA, Moreira AG (2002) Past and current human occupation, and land use. In: Oliveira PS, Marquis RJ (eds) The cerrados of Brazil: ecology and natural history of a neotropical savanna. Columbia University Press, New York, pp 69–88
Knight AT, Cowling RM, Rouget M et al (2008) Knowing but not doing: selecting priority conservation areas and the research-implementation gap. Conserv Biol 22:610–617. https://doi.org/10.1111/j.1523-1739.2008.00914.x
Knight AT, Cowling RM, Boshoff AF et al (2011) Walking in STEP: lessons for linking spatial prioritisations to implementation strategies. Biol Conserv 144:202–211. https://doi.org/10.1016/j.biocon.2010.08.017
Kujala H, Moilanen A, Araújo MB, Cabeza M (2013) Conservation planning with uncertain climate change projections. PLoS ONE. https://doi.org/10.1371/journal.pone.0053315
Ladle RJ, Whittaker RJ (2011) Social values and conservation biogeography. In: Conservation biogeography, 1st edn. Blackwell, Chichester, p 297
Lehtomäki J, Moilanen A (2013) Environmental modelling and software methods and work flow for spatial conservation prioritization using Zonation. Environ Model Softw 47:128–137. https://doi.org/10.1016/j.envsoft.2013.05.001
Lemes P, Loyola RD (2013) Accommodating species climate-forced dispersal and uncertainties in spatial conservation planning. PLoS ONE 8:e54323. https://doi.org/10.1371/journal.pone.0054323
Lemes P, Melo AS, Loyola RD (2013) Climate change threatens protected areas of the Atlantic Forest. Biodivers Conserv 23:357–368. https://doi.org/10.1007/s10531-013-0605-2
Lima-Ribeiro MS, Varela S, González-Hernández J et al (2015) Ecoclimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers. Biodivers Inform 10:1–21. https://doi.org/10.17161/bi.v10i0.4955
Lourival R, Drechsler M, Watts ME et al (2011) Planning for reserve adequacy in dynamic landscapes; maximizing future representation of vegetation communities under flood disturbance in the Pantanal wetland. Divers Distrib 17:297–310. https://doi.org/10.1111/j.1472-4642.2010.00722.x
Martinelli G, Moraes MA (2013) Livro Vermelho da flora do Brasil. Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro
Mascia MB (2014) Protected area downgrading, downsizing, and degazettement (PADDD) in Africa, Asia, and Latin America and the Caribbean, 1900–2010. Biol Conserv 169:355–361. https://doi.org/10.1016/j.biocon.2013.11.021
Mascia MB, Pailler S (2011) Protected area downgrading, downsizing, and degazettement (PADDD) and its conservation implications. Conserv Lett 4:9–20. https://doi.org/10.1111/j.1755-263X.2010.00147.x
Meir E, Andelman S, Possingham HP (2004) Does conservation planning matter in a dynamic and uncertain world? Ecol Lett 7:615–622. https://doi.org/10.1111/j.1461-0248.2004.00624.x
Meller L, Cabeza M, Pironon S et al (2014) Ensemble distribution models in conservation prioritization: from consensus predictions to consensus reserve networks. Divers Distrib 20:309–321. https://doi.org/10.1111/ddi.12162
Millennium Ecosystem Assessment (2005) Ecosystems and Human well-being: synthesis. Island Press, Washington, DC
Ministério da Agricultura Pecuária e Abastecimento (2014) Projeções do Agronegócio: Brasil 2013/2014 a 2023/2024—Projeções de Longo Prazo, 5nd edn. Ministério da Agricultura, Pecuária e Abastecimento. Assessoria de Gestão Estratégica, Brasília
Ministério do Meio Ambiente (2007) Cerrado e Pantanal: áreas e ações prioritárias para conservação da biodiversidade. MMA, Brasília
Mittermeier RA, Gil PR, Hoffman M et al (2004) Hotspots revisited: earth’s biologically richest and most endangered terrestrial ecoregions. Cemex, Conservation International, Agrupación Sierra Madre, Mexico City
Moilanen A, Franco AMA, Early RI et al (2005) Prioritizing multiple-use landscapes for conservation: methods for large multi-species planning problems. Proc R Soc B Biol Sci 272:1885–1891. https://doi.org/10.1098/rspb.2005.3164
Moilanen A, Runge MC, Elith J et al (2006a) Planning for robust reserve networks using uncertainty analysis. Ecol Modell 199:115–124. https://doi.org/10.1016/j.ecolmodel.2006.07.004
Moilanen A, Wintle BA, Elith J, Burgman M (2006b) Uncertainty analysis for regional-scale reserve selection. Conserv Biol 20:1688–1697. https://doi.org/10.1111/j.1523-1739.2006.00560.x
Moilanen A, Pouzols FM, Meller L et al (2014) Spatial conservation planning methods and software Zonation
Müller KR, Mika S, Rätsch G et al (2001) An introduction to kernel-based learning algorithms. IEEE Trans Neural Netw 12:181–201. https://doi.org/10.1109/72.914517
Munang R, Thiaw I, Alverson K et al (2013) Climate change and ecosystem-based adaptation: a new pragmatic approach to buffering climate change impacts. Curr Opin Environ Sustain 5:67–71. https://doi.org/10.1016/j.cosust.2012.12.001
Nepstad DC, Stickler CM, Filho BS- et al (2008) Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point. Philos Trans R Soc Lond B Biol Sci 363:1737–1746. https://doi.org/10.1098/rstb.2007.0036
O’Hanley JR, Church RL, Keith Gilless J (2007) Locating and protecting critical reserve sites to minimize expected and worst-case losses. Biol Conserv 134:130–141. https://doi.org/10.1016/j.biocon.2006.08.009
Oliveira U, Paglia AP, Brescovit AD et al (2016) The strong influence of collection bias on biodiversity knowledge shortfalls of Brazilian terrestrial biodiversity. Divers Distrib 22:1232–1244. https://doi.org/10.1111/ddi.12489
Pachauri RK (2014) Climate Change 2014. Synthesis Report
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. J Biogeogr 34:102–117. https://doi.org/10.1111/j.1365-2699.2006.01594.x
Pereira HM, Leadley PW, Proença V et al (2010) Scenarios for global biodiversity in the 21st century. Science 330(6010):1496–1501
Pfaff A, Robalino J (2012) Protecting forests, biodiversity, and the climate: predicting policy impact to improve policy choice. Oxf Rev Econ Policy 28:164–179. https://doi.org/10.1093/oxrep/grs012
Pfaff A, Robalino J, Lima E et al (2014) Governance, location and avoided deforestation from protected areas: greater restrictions can have lower impact, due to differences in location. World Dev 55:7–20. https://doi.org/10.1016/j.worlddev.2013.01.011
Possingham H, Ball I, Andelman S (2000) Mathematical methods for identifying representative reserve netorks. In: Ferson S, Burgman M (eds) Quantitative methods for conservation biology. Springer, New York, pp 291–305
Pressey RL, Hager TC, Ryan KM et al (2000) Using abiotic data for conservation assessments over extensive regions: quantitative methods applied across New South Wales, Australia. Biol Conserv 96:55–82
Pressey RL, Whish GL, Barrett TW, Watts MEJ (2002) Effectiveness of protected areas in north-eastern New South Wales: recent trends in six measures. Biol Conserv 106:57–69. https://doi.org/10.1016/S0006-3207(01)00229-4
Pressey RL, Watts ME, Barrett TW (2004) Is maximizing protection the same as minimizing loss? Efficiency and retention as alternative measures of the effectiveness of proposed reserves. Ecol Lett 7:1035–1046. https://doi.org/10.1111/j.1461-0248.2004.00672.x
Pressey RL, Cabeza M, Watts ME et al (2007) Conservation planning in a changing world. Trends Ecol Evol 22:583–592. https://doi.org/10.1016/j.tree.2007.10.001
Pressey RL, Visconti P, Ferraro PJ (2015) Making parks make a difference: poor alignment of policy, planning and management with protected-area impact, and ways forward. Philos Trans R Soc Lond B Biol Sci 370:20140280. https://doi.org/10.1098/rstb.2014.0280
Pressey RL, Weeks R, Gurney GG (2017) From displacement activities to evidence-informed decisions in conservation. Biol Conserv 212:337–348. https://doi.org/10.1016/j.biocon.2017.06.009
Rangel TF, Loyola RD (2012) Labeling ecological niche models. Nat Conserv 10:119–126
Santika T, Mcalpine CA, Lunney D et al (2015) Assessing spatio-temporal priorities for species’ recovery in broad-scale dynamic landscapes. J Appl Ecol 52:832–840. https://doi.org/10.1111/1365-2664.12441
Segan DB, Hole DG, Donatti CI et al (2015) Considering the impact of climate change on human communities significantly alters the outcome of species and site-based vulnerability assessments. Divers Distrib 21:1101–1111. https://doi.org/10.1111/ddi.12355
Selig ER, Turner WR, Troëng S et al (2014) Global priorities for marine biodiversity conservation. PLoS ONE 9:1–11. https://doi.org/10.1371/journal.pone.0082898
Soares-Filho B, Rajâo R, Merry F et al (2016) Brazil’s market for trading forest certificates. PLoS ONE 11:1–17. https://doi.org/10.1371/journal.pone.0152311
Strange N, Thorsen BJ, Bladt J (2006) Optimal reserve selection in a dynamic world. Biol Conserv 131:33–41. https://doi.org/10.1016/j.biocon.2006.02.002
Strassburg BBN, Brooks T, Feltran-Barbieri R et al (2017) Moment of truth for the Cerrado hotspot. Nat Ecol Evol 1:13–15. https://doi.org/10.1038/s41559-017-0099
Summers DM, Bryan BA, Crossman ND, Meyer WS (2012) Species vulnerability to climate change: impacts on spatial conservation priorities and species representation. Glob Chang Biol 18:2335–2348. https://doi.org/10.1111/j.1365-2486.2012.02700.x
Tamme R, Götzenberger L, Zobel M et al (2014) Predicting species’ maximum disperal distances from simple plant traits. Ecology 95:505–513. https://doi.org/10.1890/13-1000.1
Tessarolo G, Rangel TF, Araújo MB, Hortal J (2014) Uncertainty associated with survey design in species distribution models. Divers Distrib 20:1258–1269. https://doi.org/10.1111/ddi.12236
Thomas CD, Cameron A, Green RE et al (2004) Extinction risk from climate change. Nature 427:145–148. https://doi.org/10.1038/nature02121
Thomson JR, Moilanen AJ, Vesk PA et al (2009) Where and when to revegetate: a quantitative method for scheduling landscape reconstruction. Ecol Appl 19:817–828. https://doi.org/10.1890/08-0915.1
Thuiller W, Lavorel S, Araújo MB et al (2005) Climate change threats to plant diversity in Europe. PNAS 102:8245–8250
Varela S, Anderson RP, García-Valdés R, Fernández-González F (2014) Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models. Ecography (Cop) 37:1084–1091. https://doi.org/10.1111/j.1600-0587.2013.00441.x
Visconti P, Joppa L (2015) Building robust conservation plans. Conserv Biol 29:503–512. https://doi.org/10.1111/cobi.12416
Visconti P, Pressey RL, Segan DB, Wintle BA (2010) Conservation planning with dynamic threats: the role of spatial design and priority setting for species’ persistence. Biol Conserv 143:756–767. https://doi.org/10.1016/j.biocon.2009.12.018
Wisz MS, Hijmans RJ, Li J et al (2008) Effects of sample size on the performance of species distribution models. Divers Distrib 14:763–773. https://doi.org/10.1111/j.1472-4642.2008.00482.x
Zweig MH, Campbell G (1993) Receiver-operating characteristics (ROC) plots—a fundamental evaluation tool in clinical medicine. Clin Chem 39:561–577
Acknowledgements
Lara M. Monteiro received a master scholarship from CAPES. Robert L. Pressey’s research is funded by CNPq (Grant 308532/2014-7), O Boticário Group Foundation for Nature Protection (Grant PROG_0008_2013), and CNCFlora (Grant 065/2016). Fernanda Thiesen Brum received a postdoctoral scholarship from CNPq (Grant 152172/2016-5) and currently holds an industrial and technological development scholarship (DTI-A) by CNPq (Grant 381106/2017-9). Robert L. Pressey acknowledges the support of the Australian Research Council. Leonor Patricia C. Morellato is funded by FAPESP, the São Paulo Research Foundation (Grants #2010/52113-5 and #2013/50155-0 FAPESP-Microsoft Research Virtual Institute) and receives a Research Productivity Fellowship from CNPq. This paper is a contribution of the Brazilian Network on Global Climate Change Research funded by CNPq (Grant 437167/2016-0) and FINEP (Grant 01.13.0353.00) and of the INCT in Ecology, Evolution and Biodiversity Conservation founded by MCTIC/CNPq/FAPEG (Grant 465610/2014-5).
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Guarino Rinaldi Colli.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Monteiro, L.M., Brum, F.T., Pressey, R.L. et al. Evaluating the impact of future actions in minimizing vegetation loss from land conversion in the Brazilian Cerrado under climate change. Biodivers Conserv 29, 1701–1722 (2020). https://doi.org/10.1007/s10531-018-1627-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10531-018-1627-6