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Applying species distribution modelling to improving conservation based decisions: a gap analysis of Trinidad and Tobago’s endemic vascular plants

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Abstract

For the successful conservation of a species, habitat loss and fragmentation must be controlled through a protected area network that adequately covers its habitat. Here the suitable habitats of all of Trinidad and Tobago’s endemic plant species are determined and used to perform a gap analysis of a proposed protected area network. Data from a recently completed botanical survey, the WorldClim 2 environmental parameters, and a range of other sources were used to determine the habitat of each species using the species distribution model MaxEnt. Modelled habitat suitability for each species was combined and used to create maps showing endemic richness, weighted endemism and corrected weighted endemism, and to rank areas by conservation value using Zonation. The coverage of the proposed protected area network and a land use map were overlaid on these modelled distributions. We identified data limitations which meant that more than half of the 66 endemic species could not be modelled with confidence. For the remaining species, we found that the proposed protected area network contains just 13 ± 7% of the total modelled habitat of the endemic species. For eight endemic species > 25% of the suitable habitat is degraded. Model analysis indicated that elevation and temperature seasonality are the most important drivers of endemism. Based on a gap analysis the inclusion of high elevation areas of Trinidad’s Northern Range in the proposed protected area network would expand the coverage to include > 25% of the total modelled habitat of the endemic species, thus greatly increasing the long-term sustainability of the endemic species populations.

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References

  • Anon (2013) Improving forest and protected area management in Trinidad and Tobago. GEF Project ID 4769. Global Environment Facility (GEF), Trinidad and Tobago. https://www.thegef.org/sites/default/files/project_documents/IFPAM-_TT-_FAO_Project_Document_1.pdf. Accessed 10 Sept 2017

  • Baksh-Comeau YS, Maharaj SS, Adams CD, Harris SA, Filer DL, Hawthorne WD (2016) An annotated checklist of the vascular plants of Trinidad and Tobago with analysis of vegetation types and botanical ‘hotspots’. Phytotaxa 250(1):1. https://doi.org/10.11646/phytotaxa.250.1.1

    Article  Google Scholar 

  • Beard JS (1946) The natural vegetation of Trinidad. Clarendon Press, Oxford

    Google Scholar 

  • Beharry SL, Clarke RM, Kumarsingh K (2014) Variations in extreme temperature and precipitation for a Caribbean island: Trinidad. Theoret Appl Climatol 122(3–4):783–797. https://doi.org/10.1007/s00704-014-1330-9

    Article  Google Scholar 

  • Briner S, Elkin C, Huber R (2013) Evaluating the relative impact of climate and economic changes on forest and agricultural ecosystem services in mountain regions. J Environ Manag 129:414–422

    Article  Google Scholar 

  • Brooks TM, Mittermeier RA, Mittermeier CG, Fonseca GABD, Rylands AB, Konstant WR, Flick P, Pilgram J, Oldfield S, Magin G, Hilton-Taylor C (2002) Habitat loss and extinction in the hotspots of biodiversity. Conserv Biol 16(4):909–923

    Article  Google Scholar 

  • Brown JL, Anderson B (2014) SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods Ecol Evol 5(7):694–700. https://doi.org/10.1111/2041-210x.12200

    Article  Google Scholar 

  • Brown C, Hansell J, Bally G, Hardy F (1965) Land capability survey of Trinidad and Tobago, 1st edn. Trinidad Government Printery, Port of Spain

    Google Scholar 

  • Deka K, Sharma Baruah P, Sarma B, Borthakur SK, Tanti B (2017) Preventing extinction and improving conservation status of Vanilla borneensis Rolfe, A rare, endemic and threatened orchid of Assam, India. J Nat Conserv 37:39–46. https://doi.org/10.1016/j.jnc.2017.03.001

    Article  Google Scholar 

  • Di Virgilio G, Laffan SW, Ebach MC, Chapple DG (2014) Spatial variation in the climatic predictors of species compositional turnover and endemism. Ecol Evol 4(16):3264–3278

    Article  PubMed  PubMed Central  Google Scholar 

  • Dirnböck T, Essl F, Rabitsch W (2011) Disproportional risk for habitat loss of high-altitude endemic species under climate change. Glob Change Biol 17(2):990–996

    Article  Google Scholar 

  • Dudley N (ed) (2008) Guidelines for applying protected area management categories. IUCN, Gland

    Google Scholar 

  • Eitzinger A, Farrell A, Rhiney K, Carmona S, van Loosen I, Taylor M (2015) Trinidad and Tobago: assessing the impact of climate change on cocoa and tomato. CIAT Policy Brief No. 27. Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia

  • Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40(1):677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159

    Article  Google Scholar 

  • Elith J, Graham CH, Anderson RP, Dudı´k M, Ferrier S, Guisan A, Guisan RJ, Huettmann F, Leathwick JR, Lehmann A, Li J (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151

    Article  Google Scholar 

  • Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17(1):43–57. https://doi.org/10.1111/j.1472-4642.2010.00725.x

    Article  Google Scholar 

  • Fick SE, Hijmans RJ (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol. https://doi.org/10.1002/joc.5086

    Article  Google Scholar 

  • Fourcade Y, Engler JO, Rodder D, Secondi J (2014) Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS ONE 9(5):e97122. https://doi.org/10.1371/journal.pone.0097122

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Franklin J (2010) Moving beyond static species distribution models in support of conservation biogeography. Divers Distrib 16(3):321–330. https://doi.org/10.1111/j.1472-4642.2010.00641.x

    Article  Google Scholar 

  • Gaucherel C, Vezy R, Gontrand F, Bouchet D, Ramesh BR (2016) Spatial analysis of endemism to redefine conservation areas in Western Ghats (India). J Nat Conserv 34:33–41

    Article  Google Scholar 

  • Gordon A, Simondson D, White M, Moilanen A, Bekessy SA (2009) Integrating conservation planning and landuse planning in urban landscapes. Landsc Urban Plann 91(4):183–194

    Article  Google Scholar 

  • Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8(9):993–1009. https://doi.org/10.1111/j.1461-0248.2005.00792.x

    Article  Google Scholar 

  • Guisan A, Tingley R, Baumgartner JB, Naujokaitis-Lewis I, Sutcliffe PR, Tulloch AI, Regan TJ, Brotons L, McDonald-Madden E, Mantyka-Pringle C, Martin TG (2013) Predicting species distributions for conservation decisions. Ecol Lett 16(12):1424–1435. https://doi.org/10.1111/ele.12189

    Article  PubMed  PubMed Central  Google Scholar 

  • Hayes TM (2006) Parks, people, and forest protection: an institutional assessment of the effectiveness of protected areas. World Dev 34(12):2064–2075. https://doi.org/10.1016/j.worlddev.2006.03.002

    Article  Google Scholar 

  • Helmer EH, Ruzycki TS, Benner J, Voggesser SM, Scobie BP, Park C, Fanning DW, Ramnarine S (2012) Detailed maps of tropical forest types are within reach: forest tree communities for Trinidad and Tobago mapped with multiseason Landsat and multiseason fine-resolution imagery. For Ecol Manag 279:147–166. https://doi.org/10.1016/j.foreco.2012.05.016

    Article  Google Scholar 

  • Hernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29:773–785. https://doi.org/10.1111/j.2006.0906-7590.04700.x

    Article  Google Scholar 

  • Hoover JD, Kumar S, James SA, Leisz SJ, Laituri M (2017) Modeling hotspots of plant diversity in New Guinea. Trop Ecol 58(3):623–640

    Google Scholar 

  • Hutchinson GE (1957) Cold spring harbor symposium on quantitative biology. Concluding Remarks 22:415–427

    Google Scholar 

  • Irl SDH, Harter DEV, Steinbauer MJ, Gallego Puyol D, Fernández-Palacios JM, Jentsch A, Beierkuhnlein C (2015) Climate vs. topography—spatial patterns of plant species diversity and endemism on a high-elevation island. J Ecol 103(6):1621–1633. https://doi.org/10.1111/1365-2745.12463

    Article  Google Scholar 

  • IUCN (2017) The IUCN Red List of Threatened Species. Version 2017-3. http://www.iucnredlist.org. Downloaded on 08 May 2018

  • Jarvis A, Reuter HI, Nelson A, Guevara E (2008) Hole-filled SRTM for the globe, Version 4. CGIAR-CSI SRTM 90 m Database. International Center for Tropical Agriculture, Cali, Columbia. http://srtm.csi.cgiar.org

  • Jiang Z, Huete AR, Didan K, Miura T (2008) Development of a two-band enhanced vegetation index without a blue band. Remote Sens Environ 112(10):3833–3845

    Article  Google Scholar 

  • Lehtomäki J, Moilanen A (2013) Methods and workflow for spatial conservation prioritization using Zonation. Environ Modell Softw 47:128–137

    Article  Google Scholar 

  • Maharaj S, New M (2013) Modelling individual and collective species responses to climate change within Small Island States. Biol Conserv 167:283–291. https://doi.org/10.1016/j.biocon.2013.08.027

    Article  Google Scholar 

  • Marini MÂ, Barbet-Massin M, Lopes LE, Jiguet F (2010) Predicting the occurrence of rare Brazilian birds with species distribution models. J Ornithol 151(4):857–866. https://doi.org/10.1007/s10336-010-0523-y

    Article  Google Scholar 

  • Merow C, Smith MJ, Silander JA (2013) A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36(10):1058–1069. https://doi.org/10.1111/j.1600-0587.2013.07872.x

    Article  Google Scholar 

  • Moilanen A, FM. P, Meller L, Veach V, Atponen A, Leppanen J, et al (2014) Zonation: spatial conservation planning and methods software ± User Manual, Version 4. University of Helsinki, Finland: C-BIG Conservation Biology Informatics Group, Department of Bioscience

  • Parolo G, Rossi G, Ferrarini A (2008) Toward improved species niche modelling: Arnica montanain the Alps as a case study. J Appl Ecol 45(5):1410–1418. https://doi.org/10.1111/j.1365-2664.2008.01516.x

    Article  Google Scholar 

  • Pearson RG, Raxworthy CJ, Nakamura M, Peterson AT (2006) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34(1):102–117. https://doi.org/10.1111/j.1365-2699.2006.01594.x

    Article  Google Scholar 

  • Peterman WE, Crawford JA, Kuhns AR (2013) Using species distribution and occupancy modeling to guide survey efforts and assess species status. J Nat Conserv 21(2):114–121. https://doi.org/10.1016/j.jnc.2012.11.005

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190(3–4):231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026

    Article  Google Scholar 

  • Phillips S, Dudi´K KM, Elith J, Graham C, Lehmann A, Leathwick J, Ferrier S (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl 19(1):181–197

    Article  PubMed  Google Scholar 

  • Phillips SJ, Anderson RP, Dudík M, Schapire RE, Blair ME (2017) Opening the black box: an open-source release of Maxent. Ecography 40(7):887–893

    Article  Google Scholar 

  • Raes N, Roos MC, Slik JW, Van Loon EE, Steege HT (2009) Botanical richness and endemicity patterns of Borneo derived from species distribution models. Ecography 32(1):180–192

    Article  Google Scholar 

  • Rezende VL, de Oliveira-Filho AT, Eisenlohr PV, Kamino LHY, Vibrans AC (2015) Restricted geographic distribution of tree species calls for urgent conservation efforts in the Subtropical Atlantic Forest. Biodivers Conserv 24(5):1057–1071

    Article  Google Scholar 

  • Sörensen R, Zinko U, Seibert J (2006) On the calculation of the topographic wetness index: evaluation of different methods based on field observations. Hydrol Earth Syst Sci Discuss 10(1):101–112

    Article  Google Scholar 

  • Starr CK (2009) Trinidad & Tobago. The Encyclopedia of Islands. University California Press, Berkeley, pp 926–929

    Google Scholar 

  • Steinbauer MJ, Otto R, Naranjo-Cigala A, Beierkuhnlein C, Fernández-Palacios J-M (2012) Increase of island endemism with altitude—speciation processes on oceanic islands. Ecography 35(1):23–32. https://doi.org/10.1111/j.1600-0587.2011.07064.x

    Article  Google Scholar 

  • Taylor C, Cadenhead N, Lindenmayer DB, Wintle BA (2017) Improving the design of a conservation reserve for a critically endangered species. PLoS ONE 12(1):e0169629. https://doi.org/10.1371/journal.pone.0169629

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Torresdal JD, Farrell AD, Goldberg CS (2017) Environmental DNA detection of the golden tree frog (Phytotriades auratus) in Bromeliads. PLoS ONE 12(1):e0168787

    Article  PubMed  PubMed Central  Google Scholar 

  • Turner IM (1996) Species loss in fragments of tropical rain forest: a review of the evidence. J Appl Ecol 33:200–209

    Article  Google Scholar 

  • Van den Eynden V, Oatham M, Alexander B, Naranjit A, Quashie J, Koonhow B, Bruce K, Barker M, Roberts R, O’Neil S, Thomas W (2007) Matura national park environmentally sensitive area participatory biological baseline survey. https://doi.org/10.6084/m9.figshare.5234815.v1. Accessed 10 Sept 2017

  • Van den Eynden V, Oatham MP, Johnson W (2008) How free access internet resources benefit biodiversity and conservation research: Trinidad and Tobago’s endemic plants and their conservation status. Oryx. https://doi.org/10.1017/s0030605308007321

    Article  Google Scholar 

  • Van Gils H, Conti F, Ciaschetti G, Westinga E (2012) Fine resolution distribution modelling of endemics in Majella National Park, Central Italy. Plant Biosyst—An Int J Dealing Aspects of Plant Biol 146(sup1):276–287. https://doi.org/10.1080/11263504.2012.685194

    Article  Google Scholar 

  • Wan J, Wang C, Han S, Yu J (2014) Planning the priority protected areas of endangered orchid species in northeastern China. Biodivers Conserv 23(6):1395–1409

    Article  Google Scholar 

  • Williams JN, Seo C, Thorne J, Nelson JK, Erwin S, O’Brien JM, Schwartz MW (2009) Using species distribution models to predict new occurrences for rare plants. Divers Distrib 15(4):565–576. https://doi.org/10.1111/j.1472-4642.2009.00567.x

    Article  Google Scholar 

  • Yackulic CB, Chandler R, Zipkin EF, Royle JA, Nichols JD, Campbell Grant EH, Veran S (2013) Presence-only modelling using MAXENT: when can we trust the inferences? Methods Ecol Evol 4(3):236–243. https://doi.org/10.1111/2041-210x.12004

    Article  Google Scholar 

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Acknowledgements

The authors thank Bheshem Ramlal and Suresh Sookbir for acquisition of GIS layers and Ariel Mohan for comments on the manuscript. This work was supported by the ‘The Improving Forest and protected area Management in Trinidad and Tobago Project’ (GCP/TRI/003/GFF).

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Authors and Affiliations

  1. Department of Life Sciences, University of the West Indies, St. Augustine Campus, St. Augustine, Trinidad and Tobago

    Joshua A. Spiers, Michael P. Oatham, Luke V. Rostant & Aidan D. Farrell

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  1. Joshua A. Spiers
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  2. Michael P. Oatham
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Correspondence to Aidan D. Farrell.

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Communicated by David Hawksworth.

This article belongs to the Topical Collection: Biodiversity protection and reserves.

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Spiers, J.A., Oatham, M.P., Rostant, L.V. et al. Applying species distribution modelling to improving conservation based decisions: a gap analysis of Trinidad and Tobago’s endemic vascular plants. Biodivers Conserv 27, 2931–2949 (2018). https://doi.org/10.1007/s10531-018-1578-y

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  • DOI: https://doi.org/10.1007/s10531-018-1578-y

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