Abstract
Modeling climate change effects on species and communities is critical especially in isolated islands. We analyzed the potential effects of climate change on 200 plant species in Puerto Rico under two emission scenarios and in four periods over the twenty-first century. Our approach was based on ensemble bioclimatic modeling using eight modeling algorithms and community richness analysis. Our findings showed that the probabilities of environmental suitability decline for wet climate species and increase for drier and warm climate species in the future periods under both emission scenarios, with stronger effects under the higher emission scenario. Expansion of dry climate species to higher elevations appears to be a prominent response of species to climatic change in the island based on changes in environmental suitability but the actual species redistribution will be influenced by their life histories, potential adaptation, dispersal abilities, species introductions, and species interactions. This potential movement leads to a spatial pattern of species richness at site level that shows a positive relationship with elevation, which becomes stronger in the later periods of the century. The spatial pattern of species richness, if combined with single species projections, can provide critical information for conservation management in the island. Conservation management can support island-wide biological diversity by protecting the wet climate species on the uplands.
Similar content being viewed by others
References
Acevedo-Rodrıguez P, Strong MT (2011) Flora of the West Indies: catalogue of the seed plants of the West Indies. Smithsonian Institution, National Museum of Natural History, Washington, DC
Bawiec, W J (1998) Geology, geochemistry, geophysics, mineral occurrences, and mineral resource assessment for the Commonwealth of Puerto Rico. U S Geological Survey, Open File Report CD–ROM 98–38
Berg MP, KIERS E, Driessen G, Van Der Heijden M, Kooi BW, Kuenen F, Ellers J (2010) Adapt or disperse: understanding species persistence in a changing world. Glob Chang Biol 16(2):587–598
Boyce MS, Vernier PR, Nielsen SE, Schmiegelow FKA (2002) Evaluating resource selection functions. Ecol Model 157:281–300
Brandeis TJ, Helmer EH, Marcano-Vega H, Lugo AE (2009) Climate shapes the novel plant communities that form after deforestation in Puerto Rico and the US Virgin Islands. For Ecol Manag 258(7):1704–1718
Chase JM, Myers JA (2011) Disentangling the importance of ecological niches from stochastic processes across scales. Philos Trans R Soc Lond Ser B Biol Sci 366:2351–2363
D’Amen M, Bombi P, Pearman PB, Schmatz DR, Zimmermann NE, Bologna MA (2011) Will climate change reduce the efficacy of protected areas for amphibian conservation in Italy? Biol Conserv 144(3):989–997
Daly C, Helmer EH, Quiñones M (2003) Mapping the climate of Puerto Rico, Vieques and Culebra. Int J Climatol 23(11):1359–1381
D'Amen M, Dubuis A, Fernandes RF, Pottier J, Pellissier L, Guisan A (2015) Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models. J Biogeogr 42(7):1255–1266
D'Amen M, Rahbek C, Zimmermann NE, Guisan A (2017) Spatial predictions at the community level: from current approaches to future frameworks. Biol Rev 92(1):169–187
del Mar Lopez T, Aide TM, Thomlinson JR (2001) Urban expansion and the loss of prime agricultural lands in Puerto Rico. AMBIO 30(1):49–54
Di Cola V, Broennimann O, Petitpierre B, Breiner FT, D'Amen M, Randin C, Pellissier L (2017) ecospat: an R package to support spatial analyses and modeling of species niches and distributions. Ecography 40(6):774–787
Dubuis A, Pottier J, Rion V, Pellissier L, Theurillat JP, Guisan A (2011) Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches. Divers Distrib 17(6):1122–1131
Duque A, Stevenson PR, Feeley KJ (2015) Thermophilization of adult and juvenile tree communities in the northern tropical Andes. PNAS 112(34):10744–10749
Elith J, Kearney M, Phillips S (2010) The art of modelling range–shifting species. Methods Ecol Evol 1:330–342
Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D, Shaffer S, Shimada J, Umland J, Werner M, Oskin M, Burbank D, Alsdorf D (2007) The shuttle radar topography mission, Rev Geophys 45(2), RG2004. https://doi.org/10.1029/2005RG000183
Feeley KJ, Silman MR (2010a) Modelling the responses of Andean and Amazonian plant species to climate change: the effects of georeferencing errors and the importance of data filtering. J Biogeogr 37(4):733–740
Feeley KJ, Silman MR (2010b) Biotic attrition from tropical forests correcting for truncated temperature niches. Glob Chang Biol 16(6):1830–1836
Feeley K, Rehm EM, Machovina B (2012) Perspective: The responses of tropical forest species to global climate change: acclimate, adapt, migrate, or go extinct? Front Biogeogr 4(2):69–84
Fei S, Desprez JM, Potter KM, Jo I, Knott JA, Oswalt CM (2017) Divergence of species responses to climate change. Sci Adv 3(5):e1603055
Gilman SE, Urban MC, Tewksbury J, Gilchrist GW, Holt RD (2010) A framework for community interactions under climate change. Trends Ecol Evol 25(6):325–331
Gotelli NJ, Anderson MJ, Arita HT, Chao A, Colwell RK, Connolly SR, Grytnes JA (2009) Patterns and causes of species richness: a general simulation model for macroecology. Ecol Lett 12(9):873–886
Guisan A, Rahbek C (2011) SESAM–a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages. J Biogeogr 38(8):1433–1444
Harsch MA, Phillips A, Zhou Y, Leung MR, Rinnan DS, Kot M (2017) Moving forward: insights and applications of moving-habitat models for climate change ecology. J Ecol 105(5):1169–1181
Henareh Khalyani A, Gould WA, Harmsen E, Terando A, Quinones M, Collazo JA (2016) Climate change implications for tropical islands: interpolating and interpreting statistically downscaled GCM projections for management and planning. J Appl Meteorol Climatol 55(2):265–282
Hijmans RJ, van Etten J (2014) raster: Geographic data analysis and modeling. R package version 2, 15
Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecol Model 199:142–152
Loreau M (2000) Are communities saturated? On the relationship between α, β and γ diversity. Ecol Lett 3(2):73–76
Mateo RG, de la Estrella M, Felicísimo ÁM, Muñoz J, Guisan A (2013) A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador. Biol Conserv 160:150–161
Mateo RG, Mokany K, Guisan A (2017) Biodiversity models: what if unsaturation is the rule? Trends Ecol Evol 32(8):556–566
Moritz C, Patton JL, Conroy CJ, Parra JL, White GC, Beissinger SR (2008) Impact of a century of climate change on small–mammal communities in Yosemite National Park, USA. Science 322(5899):261–264
Muscarella R, Uriarte M (2016) Do community-weighted mean functional traits reflect optimal strategies? Proc R Soc B 283:20152434. https://doi.org/10.1098/rspb.2015.2434
Muscarella R, Uriarte M, Erickson DL, Swenson NG, Kress WJ, Zimmerman JK (2016) Variation of tropical forest assembly processes across regional environmental gradients. Perspect Plant Ecol Syst 23:52–62
Nogués-Bravo D, Rahbek C (2011) Communities under climate change. Science 334(6059):1070–1071
Ovaskainen O, Tikhonov G, Norberg A, Guillaume Blanchet F, Duan L, Dunson D, Abrego N (2017) How to make more out of community data? A conceptual framework and its implementation as models and software. Ecol Lett 20(5):561–576
Pecl GT, Araújo MB, Bell JD, Blanchard J, Bonebrake TC, Chen IC, Falconi L (2017) Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355(6332):eaai9214
Peterson AT (2011) Ecological niches and geographic distributions. Princeton University Press, Princeton
Pottier J, Dubuis A, Pellissier L, Maiorano L, Rossier L, Randin CF, Guisan A (2013) The accuracy of plant assemblage prediction from species distribution models varies along environmental gradients. Glob Ecol Biogeogr 22(1):52–63
R Development Core Team (2017) R version 330: a language and environment for statistical computing R foundation for statistical computing, Vienna, AustriaURL http://wwwR–projectorg/. Accessed March to December 2017.
Schindler DE, Armstrong JB, Reed TE (2015) The portfolio concept in ecology and evolution. Front Ecol Environ 13(5):257–263
Soberón J (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecol Lett 10(12):1115–1123
Thuiller W (2003) BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change. Glob Chang Biol 9:1353–1362
Thuiller W, Georges D, Engler R, Breiner F, Georges MD, Thuiller CW (2016) biomod2: ensemble platform for species distribution modeling. R package version 3.3–7
USDA (2017) Forest inventory and analysis database forest service available at: http://appsfsfedus/fiadbdownloads/datamarthtml. Accessed Feb 2017
USDA Soil Survey Staff (2014) Gridded Soil Survey Geographic (gSSURGO) Database for Puerto Rico United States Department of Agriculture, Natural Resources Conservation Service Available online at https://www.gdgscegovusdagov/. Accessed June 2016.
Webster MS, Madhavi AC, Darling ES, Armstrong J, Pinsky ML, Knowlton N, Schindler DE (2016) Who should pick the winners of climate change? Trends Ecol Evol 32:3
Wilson MFJ, O’Connell B, Brown C, Guinan JC, Grehan AJ (2007) Multiscale terrain analysis of multibeam bathymetry data for habitat mapping on the continental slope marine. Geodesy 30:3–35
Young BE, Franke I, Hernandez PA, Herzog SK, Paniagua L, Tovar C, Valqui T (2009) Using spatial models to predict areas of endemism and gaps in the protection of Andean slope birds. Auk 126(3):554–565
Acknowledgments
We thank Dr. Ariel Lugo for his cases of advice and Dr. Thomas Brandeis for sharing the Puerto Rico tree assemblages data in Brandeis et al. (2009).
Funding
This study was funded by the USDA Caribbean Climate Hub.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Appendix I
(DOCX 23 kb)
Appendix II
(DOCX 878 kb)
Rights and permissions
About this article
Cite this article
Henareh Khalyani, A., Gould, W.A., Falkowski, M.J. et al. Climate change increases potential plant species richness on Puerto Rican uplands. Climatic Change 156, 15–30 (2019). https://doi.org/10.1007/s10584-019-02491-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10584-019-02491-w