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Assessing extinction-risk of endangered plants using species distribution models: a case study of habitat depletion caused by the spread of greenhouses

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Abstract

The species distribution models (SDMs) are useful tools for investigating rare and endangered species as well as the environmental variables affecting them. In this paper, we propose the application of SDMs to assess the extinction-risk of plant species in relation to the spread of greenhouses in a Mediterranean landscape, where habitat depletion is one of the main causes of biodiversity loss. For this purpose, presence records of the model species (Linaria nigricans, a endemic and threatened species) and the greenhouses, a dataset of environmental variables, and different only presence-based modelling algorithms (Bioclim, Domain, GARP, MaxEnt and ENFA) were used to build SDMs for L. nigricans as well as for greenhouses. To evaluate the models a modified approach of the area-under-curve ROC was applied. Combining the most accurate models, we generated an extinction-risk model of L. nigricans populations, which enabled us to assess the sustainability of the most threatened populations. Our results show that is possible to model greenhouses spreading as a “biological invasion”. The procedure explained and used in this work is quite novel, and offers an objective spatial criterion intended for the management of natural resources and for the conservation of the biodiversity in areas threatened by habitat depletion processes as particular as greenhouses expansion.

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References

  • Anon (1992) Directive 92/43 of the council of the European community on the conservation of habitats and wild fauna and flora. European Community, Brussels

    Google Scholar 

  • Anon (2003) Ley de la Comunidad Autónoma de Andalucía 8/2003, de 28 de octubre. de la Flora y la Fauna Silvestres, Junta de Andalucía, Sevilla

    Google Scholar 

  • Araújo MB, Williams PH (2000) Selecting areas for species persistence using occurrence data. Biol Conserv 96:331–345. doi:10.1016/S0006-3207(00)00074-4

    Article  Google Scholar 

  • Araújo MB, Williams PH, Fuller RJ (2002) Dynamics of extinction and the selection of nature reserves. Proc R Soc Lond 269:1971–1980. doi:10.1098/rspb.2002.2121

    Article  Google Scholar 

  • Artnzen JW (2006) From descriptive to predictive distribution models: a working example with Iberian amphibians and reptiles. Front Zool 3:8. doi:10.1186/1742-9994-3-8

    Article  Google Scholar 

  • Barry S, Elith J (2006) Error and uncertainty in habitat models. J Appl Ecol 43:413–423. doi:10.1111/j.1365-2664.2006.01136.x

    Article  Google Scholar 

  • Buckland ST, Elston DA (1993) Empirical models for the spatial distribution of wildlife. J Appl Ecol 30:478–495. doi:10.2307/2404188

    Article  Google Scholar 

  • Cabezudo B, Talavera S, Blanca G, Salazar C, Cueto M, Valdés B, Hernández J, Herrera CM, Rodríguez C, Navas D (2005) Lista Roja de la Flora Vascular de Andalucía. Consejería de Medio Ambiente de la Junta de Andalucía, Sevilla

    Google Scholar 

  • Carpenter G, Gillson AN, Winter J (1993) DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animals. Biodivers Conserv 2:667–680. doi:10.1007/BF00051966

    Article  Google Scholar 

  • Costa GC, Wolfe C, Shepard DB, Caldwell JP, Vitt LJ (2007) Detecting the influence of climatic variables on species distributions: a test using GIS niche-based models along a steep longitudinal environmental gradient. J Biogeography (online early articles). doi:10.1111/j.1365-2699.2007.01809.x

  • Eastman JR (2006) Idrisi Andes. Guide to GIS and image processing. Clark University, Worcester

    Google Scholar 

  • Elith J, Graham CH, Anderson RP, Dudík M, Ferrier S, Guisan A, Hijmans RJ, Huettmann F, Leathwick JR, Lehmann A, Li J, Lohmann LG, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JM, Peterson AT, Phillips SJ, Richardson KS, Scachetti-Pereira R, Schapire RE, Soberón J, Williams S, Wisz MS, Zimmermann NE (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151. doi:10.1111/j.2006.0906-7590.04596.x

    Article  Google Scholar 

  • Farber O, Kadmon R (2003) Assessment of alternative approaches for bioclimatic modelling with special emphasis on the Mahalanobis distance. Ecol Modell 160:115–130. doi:10.1016/S0304-3800(02)00327-7

    Article  CAS  Google Scholar 

  • Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv 24:38–49. doi:10.1017/S0376892997000088

    Article  Google Scholar 

  • Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Modell 135:147–186. doi:10.1016/S0304-3800(00)00354-9

    Article  Google Scholar 

  • Guisan A, Broennimann O, Engler R, Vust M, Yoccoz NG, Lehmann A, Zimmermann NE (2006) Using niche-based models to improve the sampling of rare species. Conserv Biol 20(2):501–511. doi:10.1111/j.1523-1739.2006.00354.x

    Article  PubMed  Google Scholar 

  • Hirzel AH, Hausser J, Chesser D, Perrin N (2002) Ecological-Niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology 83(7):2027–2036

    Article  Google Scholar 

  • Hirzel AH, Hausser J, Perrin N (2004) Biomapper 3.0. Laboratory for Conservation Biology, University of Bern

    Google Scholar 

  • Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecol Modell 199:142–152. doi:10.1016/j.ecolmodel.2006.05.017

    Article  Google Scholar 

  • Loiselle BA, Howell CA, Graham CH, Goerck JM, Brooks T, Smith KG, Williams PH (2003) Avoiding pitfalls of using species distributon models in conservation planning. Conserv Biol 17:1591–1600. doi:10.1111/j.1523-1739.2003.00233.x

    Article  Google Scholar 

  • Martínez-Fernández J, Esteve MA (2004) Assessing the sustainability of Mediterranean intensive agricultural systems through the combined use of dynamic system models, environmental modelling and geographical information systems. In: Quaddus MA, Siddique MAB (eds) Handbook of sustainable development planning. Studies in modelling and decision support. Cheltenham, Edward Elgar, pp 215–248

    Google Scholar 

  • Mota JF, Peñas J, Castro H, Cabello J, Guirado J (1996) Agricultural development versus biodiversity conservation: the Mediterranean semiarid vegetation in El Ejido (Almería, southeastern Spain). Biodivers Conserv 5:1597–1617. doi:10.1007/BF00052118

    Article  Google Scholar 

  • Mota JF, Pérez-García FJ, Peñas J, Cabello J, Cueto M (2003) La flora amenazada de Almería en tablas y fichas. Especies en peligro: casos estudiados. In: Mota, JF, Cueto, M, Merlo, ME (eds), Flora Amenazada de la provincia de Almería. Universidad de Almería-IEA, Almería, pp 227–245

  • Mota J, Cabello J, Cerrillo MI, Rodríguez-Tamayo ML (2004) Los subdesiertos de Almería: naturaleza de cine. Consejería de Medio Ambiente, Junta de Andalucía

    Google Scholar 

  • Ninyerola M, Pons X, Roure JM (2000) A methodological approach of climatological modelling of air temperature and precipitation through GIS techniques. Int J Clim 20:1823–1841. doi:10.1002/1097-0088(20001130)20:14<1823::AID-JOC566>3.0.CO;2-B

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modelling of species geographic distributions. Ecol Modell 190:231–259. doi:10.1016/j.ecolmodel.2005.03.026

    Article  Google Scholar 

  • Sala OE, Chapin FS, Armesto JJ, Berlow E, Bloomfield J, Dirzo R et al (2000) Global biodiversity scenarios for the year 2100. Science 287:1770–1774. doi:10.1126/science.287.5459.1770

    Article  PubMed  CAS  Google Scholar 

  • Segurado P, Araújo MB (2004) An evaluation of methods for modelling species distributions. J Biogeography 31:1555–1568. doi:10.1111/j.1365-2699.2004.01076.x

    Article  Google Scholar 

  • Soulé ME (1991) Conservation: tactics for a constant crisis. Science 253:744–750. doi:10.1126/science.253.5021.744

    Article  PubMed  Google Scholar 

  • Stockwell D, Peters D (1999) The GARP modelling system: problems and solutions to automated spatial prediction. Int J GIS 13:143–158

    Google Scholar 

  • Takakura T, Fang W (2002) Climate under cover, 2nd edn. Springer, Germany. doi:204ISBN:978-1-4020-0845-0

    Google Scholar 

  • Thuiller W (2003) BIOMOD—optimizing predictions of species distributions and projecting potential future shifts under global change. Glob Change Biol 9:1353–1362. doi:10.1046/j.1365-2486.2003.00666.x

    Article  Google Scholar 

  • Thuiller W, Lavorel S, Araújo MB (2005a) Niche properties and geographical extent as predictors of species sensitivity to climate change. Glob Ecol Biogeogr 14:347–357. doi:10.1111/j.1466-822X.2005.00162.x

    Article  Google Scholar 

  • Thuiller W, Richardson DM, Pysek P, Midgley GF, Hughes GO, Rouget M (2005b) Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Glob Change Biol 11:2234–2250. doi:10.1111/j.1365-2486.2005.001018.x

    Article  Google Scholar 

  • Ward DF (2007) Modelling the potential geographic distribution of invasive ant species in New Zealand. Biol Invasions 9:723–735. doi:10.1007/s10530-006-9072-y

    Article  Google Scholar 

  • Zaniewski AE, Lehmann A, Overton JM (2002) Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecol Modell 157:261–280. doi:10.1016/S0304-3800(02)00199-0

    Article  Google Scholar 

Download references

Acknowledgments

This research has been financed by the Spanish Ministerio de Education y Ciencia (REN2003-09427-C02 project), and the Andalusian Consejería de Innovación, Ciencia y Tecnología de la Junta de Andalucía (RNM 1067 project). The authors are very grateful to N. Donadio, J. Cabello, C. Oyonarte, M. Piquer, D. Alcaraz, H. Schwarzeger, V. Vargas and J. L. Caparrós for their technical support and help during field work. We are also indebted to David Nesbitt for the English translation.

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Correspondence to Blas M. Benito.

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Benito, B.M., Martínez-Ortega, M.M., Muñoz, L.M. et al. Assessing extinction-risk of endangered plants using species distribution models: a case study of habitat depletion caused by the spread of greenhouses. Biodivers Conserv 18, 2509–2520 (2009). https://doi.org/10.1007/s10531-009-9604-8

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