Allen, C. D. et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manag. 259, 660–684 (2010).
Google Scholar
Chen, I.-C., Hill, J. K., Ohlemuller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).
Google Scholar
Wiens, J. J. Climate-related local extinctions are already widespread among plant and animal species. PLOS Biol. 14, e2001104 (2016).
Google Scholar
Anadón, J. D., Sala, O. E. & Maestre, F. T. Climate change will increase savannas at the expense of forests and treeless vegetation in tropical and subtropical Americas. J. Ecol. 102, 1363–1373 (2014).
Google Scholar
ECLAC et al. Climate Change in Central America: Potential Impacts and Public Policy Options (United Nations, 2015).
Khatun, K., Imbach, P. & Zamora, J. An assessment of climate change impacts on the tropical forests of Central America using the Holdridge Life Zone (HLZ) land classification system. iForest—Biogeosciences Forestry 6, 183 (2013).
Google Scholar
TEEB. The Economics of Ecosystems and Biodiversity: Mainstreaming the Economics of Nature: A synthesis of the approach, conclusions and recommendations of TEEB (Progress Press, 2010).
Diffenbaugh, N. S. & Giorgi, F. Climate change hotspots in the CMIP5 global climate model ensemble. Climatic Change 114, 813–822 (2012).
Google Scholar
Myers, N. Biodiversity hotspots revisited. BioScience 53, 916–917 (2003).
Google Scholar
Corrales, L., Bouroncle, C. & Zamora, J. C. In Climate Change Impacts on Tropical Forests in Central America (ed. Chiabai, A.) 17–38 (Routledge, 2015).
Gunter, U., Ceddia, M. G. & Tröster, B. International ecotourism and economic development in Central America and the Caribbean. J. Sustain. Tour. 25, 43–60 (2017).
Google Scholar
Hernández-Blanco, M., Costanza, R., Anderson, S., Kubiszewski, I. & Sutton, P. Future scenarios for the value of ecosystem services in Latin America and the Caribbean to 2050. Curr. Res. Environ. Sustainability 2, 100008 (2020).
Google Scholar
Hecht, S. B. Forests lost and found in tropical Latin America: the woodland ‘green revolution’. J. Peasant Stud. 41, 877–909 (2014).
Google Scholar
Colwell, R. K., Brehm, G., Cardelús, C. L., Gilman, A. C. & Longino, J. T. Global warming, elevational range shifts, and lowland biotic attrition in the wet tropics. Science 322, 258–261 (2008).
Google Scholar
Imbach, P. et al. Modeling potential equilibrium states of vegetation and terrestrial water cycle of Mesoamerica under climate change scenarios. J. Hydrometeor 13, 665–680 (2012).
Google Scholar
Newbold, T., Oppenheimer, P., Etard, A. & Williams, J. J. Tropical and Mediterranean biodiversity is disproportionately sensitive to land-use and climate change. Nat. Ecol. Evol. 1–9. https://doi.org/10.1038/s41559-020-01303-0 (2020).
Freeman, B. G., Lee-Yaw, J. A., Sunday, J. M. & Hargreaves, A. L. Expanding, shifting and shrinking: the impact of global warming on species’ elevational distributions. Glob. Ecol. Biogeogr. 27, 1268–1276 (2018).
Google Scholar
Booth, T. H. Species distribution modelling tools and databases to assist managing forests under climate change. For. Ecol. Manag. 430, 196–203 (2018).
Google Scholar
Urbina-Cardona, N. et al. Species distribution modeling in Latin America: a 25-year retrospective review. Trop. Conserv. Sci. 12, 1940082919854058 (2019).
Google Scholar
Araújo, M. B. et al. Standards for distribution models in biodiversity assessments. Sci. Adv. 5, eaat4858 (2019).
Google Scholar
BIOMARCC-SINAC-GIZ. Estimación de los posibles cambios en la distribución de especies de flora arbórea en el Pacífico Norte y Sur de Costa Rica en respuesta a los efectos del Cambio Climático (2013).
de Sousa, K. et al. Suitability of Key Central American Agroforestry Species Under Future Climates: an Atlas (World Agroforestry Centre, 2017).
Calabrese, J. M., Certain, G., Kraan, C. & Dormann, C. F. Stacking species distribution models and adjusting bias by linking them to macroecological models. Glob. Ecol. Biogeogr. 23, 99–112 (2014).
Google Scholar
Biber, M. F., Voskamp, A., Niamir, A., Hickler, T. & Hof, C. A comparison of macroecological and stacked species distribution models to predict future global terrestrial vertebrate richness. J. Biogeogr. 47, 114–129 (2020).
Google Scholar
Zakharova, L., Meyer, K. M. & Seifan, M. Trait-based modelling in ecology: a review of two decades of research. Ecol. Model. 407, 108703 (2019).
Google Scholar
Lyra, A. et al. Projections of climate change impacts on central America tropical rainforest. Climatic Change 141, 93–105 (2017).
Google Scholar
Boukili, V. K. & Chazdon, R. L. Environmental filtering, local site factors and landscape context drive changes in functional trait composition during tropical forest succession. Perspect. Plant Ecol. Evol. Syst. 24, 37–47 (2017).
Google Scholar
Imbach, P. A., Locatelli, B., Molina, L. G., Ciais, P. & Leadley, P. W. Climate change and plant dispersal along corridors in fragmented landscapes of Mesoamerica. Ecol. Evol. 3, 2917–2932 (2013).
Google Scholar
Meyer, N. F. V., Moreno, R., Reyna-Hurtado, R., Signer, J. & Balkenhol, N. Towards the restoration of the Mesoamerican Biological Corridor for large mammals in Panama: comparing multi-species occupancy to movement models. Mov. Ecol. 8, 3 (2020).
Google Scholar
Cabrera-Guzmán, E. & Reynoso, V. H. Amphibian and reptile communities of rainforest fragments: minimum patch size to support high richness and abundance. Biodivers. Conserv 21, 3243–3265 (2012).
Google Scholar
Crespin, S. J. & García-Villalta, J. E. Integration of land-sharing and land-sparing conservation strategies through regional networking: The Mesoamerican Biological Corridor as a Lifeline for Carnivores in El Salvador. AMBIO 43, 820–824 (2014).
Google Scholar
Rehm, E. & Feeley, K. J. Many species risk mountain top extinction long before they reach the top. Front. Biogeogr. 8, (2016).
Fung, E. et al. Mapping conservation priorities and connectivity pathways under climate change for tropical ecosystems. Climatic Change 141, 77–92 (2017).
Google Scholar
Ojea, E., Zamora, J. C., Martin-Ortega, J. & Imbach, P. In Climate Change Impacts on Tropical Forests in Central America: an Ecosystem Service Perspective (ed. Chiabai, A.) 113–151 (Routledge, 2015).
Bernal, B., Murray, L. T. & Pearson, T. R. H. Global carbon dioxide removal rates from forest landscape restoration activities. Carbon Balance Manag. 13, 22 (2018).
Google Scholar
Toledo, M. et al. Climate is a stronger driver of tree and forest growth rates than soil and disturbance. J. Ecol. 99, 254–264 (2011).
Google Scholar
Rojas, M. R., Locatelli, B. & Billings, R. Climate change and outbreaks of Southern Pine Beetle in Honduras. For. Syst. 19, 70–76 (2010).
Estrada‐Villegas, S., Hall, J. S., Breugel, Mvan & Schnitzer, S. A. Lianas reduce biomass accumulation in early successional tropical forests. Ecology 101, e02989 (2020).
Google Scholar
Balslev, H. et al. Species diversity and growth forms in Tropical American Palm Communities. Bot. Rev. 77, 381–425 (2011).
Google Scholar
Ratajczak, Z., D’Odorico, P. & Yu, K. The Enemy of My Enemy Hypothesis: Why Coexisting with Grasses May Be an Adaptive Strategy for Savanna Trees. Ecosystems 20, 1278–1295 (2017).
Google Scholar
Heijden, G. M. F., van der, Powers, J. S. & Schnitzer, S. A. Lianas reduce carbon accumulation and storage in tropical forests. PNAS 112, 13267–13271 (2015).
Google Scholar
da Cunha Vargas, B., Grombone-Guaratini, M. T. & Morellato, L. P. C. Lianas research in the Neotropics: overview, interaction with trees, and future perspectives. Trees https://doi.org/10.1007/s00468-020-02056-w. (2020).
Nanni, A. S. et al. The neotropical reforestation hotspots: a biophysical and socioeconomic typology of contemporary forest expansion. Glob. Environ. Change 54, 148–159 (2019).
Google Scholar
Stan, K. et al. Climate change scenarios and projected impacts for forest productivity in Guanacaste Province (Costa Rica): lessons for tropical forest regions. Reg. Environ. Change 20, 14 (2020).
Google Scholar
Olson, D. M. et al. Terrestrial ecoregions of the World: a New Map of Life on Earth: a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 51, 933–938 (2001).
Google Scholar
Poorter, L. et al. Wet and dry tropical forests show opposite successional pathways in wood density but converge over time. Nat. Ecol. Evol. 3, 928–934 (2019).
Google Scholar
Condit, R., Pérez, R. & Daguerre, N. Trees of Panama and Costa Rica (Princeton University Press, 2010).
CATIE. Árboles de Centroamérica: un Manual Para Extensionistas (CATIE, 2003).
Flores-Vindas, E. & Obando-Vargas, G. Árboles del Trópico Húmedo: Importancia Socioeconómica (Editorial Tecnológica de Costa Rica, 2014).
Hammel, B. E., Grayum, M. H., Herrera, C. & Zamora Villalobos, N. Manual de plantas de Costa Rica vols 1–6 (Missouri Botanical Garden, 2003).
Boukili, V. Functional trait data for La Selva, database (2014).
Burns, R. M., Mosquera, M. S. & Whitmore, J. L. Useful Trees of the Tropical Region of North America (North American Forestry Commission, 1998).
CATIE. Rasgos funcionales, base de datos del Programa Producción y Conservación en Bosques del CATIE (colleción de resultados de tesis). (2019).
Delgado, D. et al. Análisis de la Vulnerabilidad al Cambio Climático de Bosques de Montaña en Latinoamérica (Centro Agronómico Tropical de Investigación y Enseñanza (CATIE), 2016).
FAO. Crop Ecological Requirements Database (ECOCROP). http://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1027491/ (2020).
Finegan, B., Camacho, M. & Zamora, N. Diameter increment patterns among 106 tree species in a logged and silviculturally treated Costa Rican rain forest. For. Ecol. Manag. 121, 159–176 (1999).
Google Scholar
Hall, J. S. & Ashton, M. S. Guide to Early Growth and Survival in Plantations of 64 Tree Species Native to Panama and the Neotropics. (Smithsonian Tropical Research Institute, 2016).
MARENA/INAFOR. Guía de Especies Forestales (Editora de Arte, S.A, 2002).
Runes Vargas, V. Base de rasgos funcionales y usos de las especies más abundantes en los sistemas agroforestales de Centroamérica (Agroforestry Tree Functional Traits). in Diversidad en sistemas agroforestales de Centroamérica una aproximación desde el enfoque functional. Master thesis, CATIE, Costa Rica (2016).
Vázquez-Yanes, C., Batis Muñoz, A. I., Alcocer Silva, M. I., Gual Díaz, M. & Sánchez Dirzo, C. Árboles y arbustos potencialmente valiosos para la restauración ecológica y la reforestación. Reporte técnico del proyecto J084. (1999).
Vozzo, J. A. Tropical Tree Seed Manual (U.S. Department of Agriculture, Forest Service, 2002).
Webb, D. B., Wood, P. J., Smith, J. P. & Sian Henman, G. A Guide to Species Selection for Tropical and Sub-tropical Plantations (Unit of Tropical Silviculture, Commonwealth Forestry Institute, University of Oxford, 1984).
Soultan, A. & Safi, K. The interplay of various sources of noise on reliability of species distribution models hinges on ecological specialisation. PLoS ONE 12, e0187906 (2017).
Google Scholar
GBIF. GBIF Occurrence Download. Accessed from R via rgbif 2020-05-18. Darwin Core Archive. https://doi.org/10.15468/dl.pstza2. (2020).
Anderson-Teixeira, K. J. et al. CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Glob. Change Biol. 21, 528–549 (2015).
Google Scholar
CRIA. SpeciesLink (CRIA, 2012).
Peet, R. K., Lee, M. T., Jennings, M. D. & Faber-Langendoen, D. VegBank: a permanent, open-access archive for vegetation plot data. Biodivers. Ecol. 4, 233–241 (2012).
Google Scholar
Šímová, I. et al. Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species. J. Biogeogr. 45, 895–916 (2018).
Google Scholar
US Forest Service. Forest Inventory and Analysis National Program (US Forest Service, 2013).
de Sousa, K., van Zonneveld, M., Holmgren, M., Kindt, R. & Ordoñez, J. C. Replication data for: ‘The future of coffee and cocoa agroforestry in a warmer Mesoamerica’. Harvard Dataverse https://doi.org/10.7910/DVN/0O1GW1. (2019).
Chamberlain, S. rgbif: Interface to the Global ‘Biodiversity’ Information Facility API. R package version 2.3. (2020).
Maitner, B. S. et al. The BIEN R package: A tool to access the botanical information and ecology network (BIEN) database. Methods Ecol. Evol. 9, 373–379 (2018).
Google Scholar
Morales, J. F. Sinopsis of the genus Weinmannia (Cunoniaceae) in Mexico and Central America. An. Jard.ín Bot.ánico Madr. 67, 137–155 (2010).
Google Scholar
Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 170122 (2017).
Google Scholar
Danielson, J. J. & Gesch, D. B. Global multi-resolution terrain elevation data 2010 (GMTED2010). http://pubs.er.usgs.gov/publication/ofr20111073 (2011).
Hengl, T. et al. SoilGrids1km—Global Soil Information Based on Automated Mapping. PLoS ONE 9, e105992 (2014).
Google Scholar
Schmitt, S., Pouteau, R., Justeau, D., de Boissieu, F. & Birnbaum, P. SSDM—an R package to predict distribution of species richness and composition based on stacked species distribution models. Methods. Ecol. Evol. 8, 1795–1803 (2017).
Beaumont, L. J. et al. Which species distribution models are more (or less) likely to project broad-scale, climate-induced shifts in species ranges? Ecol. Model. 342, 135–146 (2016).
Google Scholar
Lay, G. L., Engler, R., Franc, E. & Guisan, A. Prospective sampling based on model ensembles improves the detection of rare species. Ecography 33, 1015–1027 (2010).
Google Scholar
Guo, C. et al. Uncertainty in ensemble modelling of large-scale species distribution: effects from species characteristics and model techniques. Ecol. Model. 306, 67–75 (2015).
Google Scholar
Naimi, B. On uncertainty in species distribution modelling https://doi.org/10.3990/1.9789036538404 (University of Twente, 2015).
Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many?: How to use pseudo-absences in niche modelling? Methods Ecol. Evol. 3, 327–338 (2012).
Google Scholar
Hirzel, A. H., Le Lay, G., Helfer, V., Randin, C. & Guisan, A. Evaluating the ability of habitat suitability models to predict species presences. Ecol. Model. 199, 142–152 (2006).
Google Scholar
Naimi, B. & Araújo, M. B. sdm: a reproducible and extensible R platform for species distribution modelling. Ecography 39, 368–375 (2016).
Google Scholar
Diniz‐Filho, J. A. F. et al. Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change. Ecography 32, 897–906 (2009).
Google Scholar
Guillera‐Arroita, G. et al. Is my species distribution model fit for purpose? Matching data and models to applications. Glob. Ecol. Biogeogr. 24, 276–292 (2015).
Google Scholar
Phillips, S. J. & Elith, J. POC plots: calibrating species distribution models with presence-only data. Ecology 91, 2476–2484 (2010).
Google Scholar
Schwarz, J. & Heider, D. GUESS: projecting machine learning scores to well-calibrated probability estimates for clinical decision-making. Bioinformatics 35, 2458–2465 (2019).
Google Scholar
D’Amen, M., Rahbek, C., Zimmermann, N. E. & Guisan, A. Spatial predictions at the community level: from current approaches to future frameworks: Methods for community-level spatial predictions. Biol. Rev. 92, 169–187 (2017).
Google Scholar
Lobo, J. M., Jiménez‐Valverde, A. & Real, R. AUC: a misleading measure of the performance of predictive distribution models. Glob. Ecol. Biogeogr. 17, 145–151 (2008).
Google Scholar
Lewis, O. T. Climate change, species–area curves and the extinction crisis. Philos. Trans. R. Soc. B: Biol. Sci. 361, 163–171 (2006).
Google Scholar
Griscom, H. P. & Ashton, M. S. Restoration of dry tropical forests in Central America: a review of pattern and process. For. Ecol. Manag. 261, 1564–1579 (2011).
Google Scholar
Rahman, M., Islam, M., Gebrekirstos, A. & Bräuning, A. Trends in tree growth and intrinsic water-use efficiency in the tropics under elevated CO2 and climate change. Trees 33, 623–640 (2019).
Google Scholar
Riitters, K., Wickham, J., O’Neill, R., Jones, K. B. & Smith, E. Global-scale patterns of forest fragmentation. Conservation Ecol. 4, 3 (2000).
Morelli, T. L. et al. The fate of Madagascar’s rainforest habitat. Nat. Clim. Change 10, 89–96 (2020).
Google Scholar
Baumbach, L., Warren, D. L., Yousefpour, R. & Hanewinkel, M. Replication data for ‘Climate change may induce connectivity loss and mountaintop extinction in Central American forests’. https://doi.org/10.5281/zenodo.4835834 (2021).
Baumbach, L., Warren, D. L., Yousefpour, R. & Hanewinkel, M. Supplementary data for ‘Climate change may induce connectivity loss and mountaintop extinction in Central American forests’. https://doi.org/10.5281/zenodo.4836270. (2021).
Gu, Z., Gu, L., Eils, R., Schlesner, M. & Brors, B. circlize Implements and enhances circular visualization in R. Bioinformatics 30, 2811–2812 (2014).
Google Scholar
Source: Ecology - nature.com
