Biodiversity and Conservation

, Volume 16, Issue 9, pp 2649–2675 | Cite as

Identification of Biodiversity Conservation Priorities using Predictive Modeling: An Application for the Equatorial Pacific Region of South America

  • Manuel Peralvo
  • Rodrigo Sierra
  • Kenneth R. Young
  • Carmen Ulloa- Ulloa
Original paper


We used predictive modeling of species distributions to identify conservation priority areas in the equatorial Pacific region of western Ecuador and northwestern Peru. Museum and herbarium data and predictive models of species distributions are increasingly being used to assess the conservation status of individual species. In this study, we assembled occurrence data for 28 species of vascular plants, birds, and mammals to assess the conservation priorities of the set of natural communities that they represent. Environmental variables were used to predict the species’ distributions using correlative modeling as an alternative to point data, which has been the traditional approach to identify critical areas. Specific priority sites for conservation were identified using an area-selection algorithm based on simulated annealing. Four scenarios of prioritization were created using different criteria for the spatial compactness of the selected sites and fragmentation of remnant habitat. The results provide a preliminary assessment of conservation priorities for the dry ecosystems of the Equatorial Pacific region, and will serve as guidelines to focus future fieldwork.


Area-selection algorithms Ecuador Peru Species distribution modeling Systematic conservation planning Tropical dry forest 



Boundary length modifier


Conservation Data Center

CRU CL 2.0

Climatic Research Unit’s Climatologic database


Digital Elevation Model


National Directorate of Natural Resources of Ecuador


El Niño/Southern Oscillation


Genetic Algorithm for Rule Set Prediction


Geographic Information Science


National Institute of Natural Resources of Peru


International Union for the Conservation of Nature and Natural Resources


Land Use/Land Cover


Missouri Botanical Garden


Potential evapotranspiration


Provisional South-American Datum


Spatial Portfolio Optimization Tool


Shuttle Radar Topographic Mission


The Nature Conservancy


Universal Transversal Mercator


Missouri Botanical Garden’s VAScular Tropicos database


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anderson RP, Gómez-Laverde M, Peterson AT (2002a) Geographical distributions of spiny pocket mice in South America: insights from predictive models. Glob Ecol Biogeogr 11:131–141Google Scholar
  2. Anderson RP, Peterson AT, Gómez-Laverde M (2002b) Using niche-based GIS modeling to test geographic predictions of competitive exclusion and competitive release in South American pocket mice. Oikos 98:3–16Google Scholar
  3. Anderson RP, Lew D, Peterson AT (2003) Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecol Model 162:211–232Google Scholar
  4. Anderson RP, Martínez-Meyer E (2004) Modeling Species’ distributions for preliminary conservation assessments: an implementation with the spiny pocket mice (Heteromys) of Ecuador. Biol Conserv 116:167–179Google Scholar
  5. Araújo MB, Williams PH (2000) Selecting areas for species persistence using occurrence data. Biol Conserv 96:331–345Google Scholar
  6. Armenteras D, Gast F, Villareal H (2003) Andean forest fragmentation and the representativeness of protected natural areas in the eastern Andes, Colombia. Biol Conserv 113:245–256Google Scholar
  7. Bernex N, Revesz B (1988) Atlas regional de Piura. Centro de Investigación y Promoción del Campesinado, Pontificia Universidad Católica del Perú, LimaGoogle Scholar
  8. BirdLife International (2003) BirdLife’s online World Bird Database: the site for bird conservation. Version 2.0. BirdLife International, Cambridge. Available from (accessed February 2004)
  9. Bonn A, Gaston KJ (2005) Capturing biodiversity: selecting priority areas for conservation using different criteria. Biodivers Conserv 14:1083–1100Google Scholar
  10. Brown JH, Kodric-Brown A (1977) Turnover rates in insular biogeography: effect of immigration on extinction. Ecology 58:445–449Google Scholar
  11. Cabeza M, Moilanen A (2001) Design of reserve networks and the persistence of biodiversity. Trends Ecol Evol 16:242–248PubMedGoogle Scholar
  12. Cain ML, Damman H, Muir A (1998) Seed dispersal and the Holocene migration of woodland herbs. Ecol Monogr 68:325–347Google Scholar
  13. Caviedes CN (2001) El Niño in history: storming through the ages. University Press of Florida, Gainesville, FloridaGoogle Scholar
  14. Ceballos G (1995) Vertebrate diversity, ecology, and conservation in Neotropical dry forests. In: Bullock SH, Mooney HA, Medina E (eds) Seasonally dry tropical forests. Cambridge University Press, New York, pp 195–200Google Scholar
  15. Cerón C, Palacios W, Valencia R, Sierra R (1999) Las formaciones naturales de la costa del Ecuador. In: Sierra R (ed) Propuesta preliminar de un sistema de clasificación de vegetación para el Ecuador Continental. Proyecto INEFAN/GEF-BIRF y EcoCiencia, Quito, Ecuador, pp 55–78Google Scholar
  16. Church RL, Stoms DM, Davis FW (1996) Reserve selection as a maximal covering location problem. Biol Conserv 76:105–112Google Scholar
  17. Cowell CM, Parker AJ (2004) Biogeography in the Annals. Ann Assoc Am Geogr 94:256–268Google Scholar
  18. Crews-Meyer KA (2002) Characterizing landscape dynamism using paneled-pattern metrics. Photogram Eng Remote Sens 68:1031–1040Google Scholar
  19. Davis S, Heywood VH, Hamilton AC (eds) (1997) Centres of plant diversity, volume 3: the Americas. IUCN, Gland, SwitzerlandGoogle Scholar
  20. Dirección Nacional de Recursos Naturales (DINAREN). Undated a. Mapa Geológico del Ecuador. Escala 1:250,000. DINAREN, Quito, EcuadorGoogle Scholar
  21. Dirección Nacional de Recursos Naturales (DINAREN). Undated b. Mapa Geomorfológico del Ecuador. Escala 1:250,000. DINAREN, Quito, EcuadorGoogle Scholar
  22. Dinerstein E, Olson DM, Graham DJ, Webster AL, Primm SA, Bookbinder MP, Ledec G (1995) A conservation assessment of the terrestrial ecosystems of Latin America and the Caribbean. World Wildlife Fund and World Bank, Washington, DCGoogle Scholar
  23. Eamus D (1999) Ecophysiological traits of deciduous and evergreen woody species in the seasonally dry tropics. Trends Ecol Evol 14:11–16PubMedGoogle Scholar
  24. Faith DP, Walker PA (2002) The role of trade-offs in biodiversity conservation planning: linking local management, regional planning and global conservation efforts. J Biosci 27:393–407PubMedGoogle Scholar
  25. Ferrier S (2002) Mapping spatial pattern in biodiversity for regional conservation planning: where to from here? Syst Biol 51:331–363PubMedGoogle Scholar
  26. Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence–absence models. Environ Conserv 24:38–49Google Scholar
  27. Gibson LA, Wilson BA, Cahill DM, Hill J (2004) Modeling habitat suitability of the swamp antechinus (Antechinus minimus maritimus) in the coastal heathlands of southern Victoria, Australia. Biol Conserv 117:143–150Google Scholar
  28. Gillespie TW (1999) Life history characteristics and rarity of woody plants in tropical dry forest fragments of Central America. J Trop Ecol 15:637–649Google Scholar
  29. Gillespie TW (2000) Rarity and conservation of forest birds in the tropical dry forest region of Central America. Biol Conserv 96:161–168Google Scholar
  30. Gillespie TW, Grijalva A, Farris CN (2000) Diversity, composition and structure of tropical dry forests in Central America. Plant Ecol 147:37–47Google Scholar
  31. Gómez EN (1999) Nuevo Atlas del Ecuador. Ministry of Education, Quito, EcuadorGoogle Scholar
  32. Goodchild MF (2003) Geographic Information Science and systems for environmental management. Ann Rev Environ Resour 28:493–519Google Scholar
  33. Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186Google Scholar
  34. Hanski I (1998) Metapopulation dynamics. Nature 396:41–49Google Scholar
  35. Harris AT, Asner GP, Miller ME (2003) Changes in vegetation structure after long-term grazing in pinyon-juniper ecosystems: Integrating imaging spectroscopy and field studies. Ecosystems 6:368–383Google Scholar
  36. Hoekstra JM, Boucher TM, Ricketts TH, Roberts C (2005) Confronting a biome crisis: global disparities of habitat loss and protection. Ecol Lett 8:23–29Google Scholar
  37. Holbrook NM, Whitbeck JL, Mooney HA (1995) Drought responses of Neotropical dry forest trees. In: Bullock SH, Mooney HA, Medina E (eds) Seasonally dry tropical forests. Cambridge University Press, New York, pp 243–276Google Scholar
  38. Hutchinson GE (1957) Concluding remarks. Cold Spring Harb Symp Quant Biol 22:415–427Google Scholar
  39. Instituto Nacional de Recursos Naturales (INRENA) (1995) Mapa Forestal del Perú. Escala 1:1’000,000. INRENA, Lima PeruGoogle Scholar
  40. Instituto Nacional de Recursos Naturales (INRENA) Undated. Mapa Geológico y de Fallas Geológicas. Escala 1:250,000. INRENA, Lima, PeruGoogle Scholar
  41. International Union for the Conservation of Nature and Natural Resources (IUCN) (2003) 2003 IUCN Red List of Threatened Species. Available from (accessed February 2004)
  42. Jaksic FM (2001) Ecological effects of El Niño in terrestrial ecosystems of western South America. Ecography 24:241–250Google Scholar
  43. Janzen DH (1986) Tropical dry forests, the most endangered major tropical ecosystem. In: Wilson EO (ed) Biodiversity. National Academy Press, Washington, DC, pp 130–137Google Scholar
  44. Josse C, Navarro G, Comer P, Evans R, Faber-Langendoen D, Fellows M, Kittel G, Menard S, Pyne M, Reid M, Schulz K, Snow K, Teague J (2003) Ecological Systems of Latin America and the Caribbean: a working classification of terrestrial systems. NatureServe, Arlington, VA. Available from: (accessed January 2004)
  45. Kelley C, Garson J, Aggarwal A, Sarkar S (2002) Place prioritization for biodiversity reserve network design: a comparison of the SITES and ResNet software packages for coverage and efficiency. Divers Distrib 8:297–306Google Scholar
  46. Khurana E, Singh JS (2001) Ecology of seed and seedling growth for conservation and restoration of tropical dry forest: a review. Environ Conserv 28:39–52Google Scholar
  47. Kirkpatrick JB (1983) An iterative method for establishing priorities for the selection of nature reserves: an example from Tasmania. Biol Conserv 25:127–134Google Scholar
  48. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680PubMedGoogle Scholar
  49. Levins R (1969) Some demographic and genetic consequences of environmental heterogeneity for biological control. Bull Entomol Soc Am 15:237–240Google Scholar
  50. Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405:243–253PubMedGoogle Scholar
  51. Margules CR, Pressey RL, Williams PH (2002) Representing biodiversity: data and procedures for identifying priority areas for conservation. J Biosci 27:309–326PubMedGoogle Scholar
  52. McDonnell M, Possingham HP, Ball IR, Cousins EA (2002) Mathematical methods for spatially cohesive reserve design. Environ Model Assess 7:107–114Google Scholar
  53. Meir E, Andelman S, Possingham HP (2004) Does conservation planning matter in a dynamic and uncertain world? Ecol Lett 7:615–622Google Scholar
  54. Mertens B, Lambin EF (2000) Land-cover-change trajectories in southern Cameroon. Ann Assoc Am Geogr 90:467–494Google Scholar
  55. Missouri Botanical Garden (MBG) (2003) TROPICOS database. MBG, Saint Louis. Available from (accessed June 2004)
  56. Munday M, Munday G (1992) The climate of south-west Ecuador. In: Best B (ed) The threatened forests of south-west Ecuador. Biosphere Publications, Leeds, pp 7–59Google Scholar
  57. Murphy PG, Lugo AE (1986) Ecology of tropical dry forest. Ann Rev Ecol Syst 17:67–88Google Scholar
  58. Murphy PG, Lugo AE (1995) Dry forest of Central America and the Caribbean islands. In: Bullock SH, Mooney HA, Medina E (eds) Seasonally dry tropical forests. Cambridge University Press, New York, pp 9–34Google Scholar
  59. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858PubMedGoogle Scholar
  60. New M, Lister D, Hulme M, Makin I (2002) A high-resolution data set of surface climate over global land areas. Clim Res 21:1–25Google Scholar
  61. Nix HA (1986) A biogeographic analysis of Australian elapid snakes. In: Longmore R (ed) Atlas of elapid snakes of Australia. Bureau of Flora and Fauna, Canberra, pp 4–15Google Scholar
  62. Norton-Griffiths M, Southey C (1995) The opportunity costs of biodiversity conservation in Kenya. Ecol Econ 12:125–139Google Scholar
  63. O’Connor RJ (2002) The conceptual basis of species distribution modeling: time for a paradigm shift? In: Scott JM, Heglund PJ, Morrison ML et al (eds) Predicting species occurrences: issues of scale and accuracy. Island Press, Washington, DC, pp 25–33Google Scholar
  64. Olson DM, Dinerstein E (2002) The global 200: priority ecoregions for global conservation. Ann Mo Bot Gard 89:199–294Google Scholar
  65. Olson DM, Dinerstein E, Wikramanayake ED, Burgess ND, Powell GVN, Underwood EC, D‘amico JA, Itoua I, Strand H, Morrison J, Loucks CJ, Allnut TF, Ricketts TH, Kira Y, Lamoreux JF, Wettengel WW, Hedao P, Kassem KR (2001) Terrestrial Ecoregions of the world: a new map of life on earth. Bioscience 51:933–938Google Scholar
  66. Peterson AT (2001) Predicting species’ geographic distributions based on ecological niche modeling. Condor 103:599–605Google Scholar
  67. Peterson AT, Ball LG, Cohoon KC (2002a) Predicting distributions of Mexican birds using ecological niche modeling methods. Ibis 144:E27–E32Google Scholar
  68. Peterson AT, Egbert SL, Sánchez-Cordero V, Price KP (2000) Geographic analysis of conservation priority: endemic birds and mammals in Veracruz, Mexico. Biol Conserv 93:85–94Google Scholar
  69. Peterson AT, Ortega-Huerta MA, Bartley J, Sanchez-Cordero V, Soberón J, Buddemeier RH, Stockwell DRB (2002b) Future projections for Mexican faunas under global climate change scenarios. Nature 416:626–629Google Scholar
  70. Peterson AT, Sánchez-Cordero V, Soberón J, Bartley J, Buddemeier RH, Navarro-Siguenza AG (2001) Effects of global climate change on geographic distributions of Mexican Cracidae. Ecol Model 144:21–30Google Scholar
  71. Peterson AT, Shaw J (2003) Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects. Int J␣Parasitol 33:919–931PubMedGoogle Scholar
  72. Peterson AT, Soberón J, Sánchez-Cordero V (1999) Conservatism of ecological niches in evolutionary time. Science 285:1265–1267PubMedGoogle Scholar
  73. Peterson AT, Stockwell DRB, Kluza DA (2002c) Distributional prediction based on ecological niche modeling of primary occurrence data. In: Scott JM, Heglund PJ, Morrison ML et al (eds) Predicting species occurrences: issues of scale and accuracy. Island Press, Washington, DC, pp␣617–623Google Scholar
  74. Peterson AT, Vieglais DA (2001) Predicting species invasions using ecological niche modeling. BioScience 51:363–371Google Scholar
  75. Petit CC, Lambin EF (2002) Impact of data integration technique on historical land-use/land-cover change: comparing historical maps with remote sensing data in the Belgian Ardennes. Landsc Ecol 17:117–132Google Scholar
  76. Ponder WF, Carter GA, Flemons P, Chapman RR (2001) Evaluation of museum collection data for use in biodiversity assessment. Conserv Biol 15:648–657Google Scholar
  77. Possingham H, Ball I, Andelman S (2000) Mathematical methods for identifying representative reserve networks. In: Fersona S, Burgman M (eds) Quantitative methods for conservation biology. Springer-Verlag, New York, pp 291–305Google Scholar
  78. Prendergast JR, Quinn RM, Lawton JH (1999) The gaps between theory and practice in selecting nature reserves. Conserv Biol 13:484–492Google Scholar
  79. Pressey RL, Logan VS (1998) Size of selection units for future reserves and its influence on actual vs. targeted representation of features: a case study in western New South Wales. Biological Conservation 85:305–319Google Scholar
  80. Pressey RL, Nicholls AO (1989) Efficiency in conservation evaluation: scoring versus iterative approaches. Biol Conserv 50:199–218Google Scholar
  81. Pulliam HR (1988) Sources, sinks, and population regulation. Am Nat 132:652–661Google Scholar
  82. Pulliam HR (2000) On the relationship between niche and distribution. Ecol Lett 3:349–361Google Scholar
  83. Redford KH, Coppolillo P, Sanderson EW, da Fonseca G, Dinerstein E, Groves C, Mace G, Maginnis S, Mittermeier RA, Noss R, Olson D, Robinson JG, Vedder A, Wright M (2003) Mapping the conservation landscape. Conserv Biol 17:116–131Google Scholar
  84. Rempel RS, Carr AP (2003) Patch Analyst extension for ArcView: version 3. Available from∼rrempel/patch/index.htm (accessed May 2004)
  85. Rodrigues ASL, Gaston KJ (2001) How large do reserve networks need to be? Ecol Lett 4:602–609Google Scholar
  86. Rodríguez LO, Young KR (2000) Biological diversity of Peru: determining priority areas for conservation. Ambio 29:329–337Google Scholar
  87. Sánchez-Cordero V, Martínez-Meyer E (2000) Museum specimen data predict crop damage by tropical rodents. Proc Natl Acad Sci 97:7074–7077PubMedGoogle Scholar
  88. Sarkar S, Justus J, Fuller T, Kelley C, Garson J, Mayfield M (2005) Effectiveness of environmental surrogates for the selection of conservation area networks. Conserv Biol 19:815–825Google Scholar
  89. Scott JM, Davis F, Csuti B, Noss R, Butterfield B, Groves C, Anderson H, Caicco S, D’Erchia F, Edwards TC, Ulliman J, Wright G (1993) GAP analysis: a geographic approach to protection of biological diversity. Wildl Monogr 123:1–41Google Scholar
  90. Shoutis D (2003) SPOT: the spatial portfolio optimization tool. The Nature Conservancy, Washington, DCGoogle Scholar
  91. Sierra R, Campos F, Chamberlin J (2002) Assessing biodiversity conservation priorities: ecosystem risk and representativeness in continental Ecuador. Landsc Urban Plan 59:95–110Google Scholar
  92. Sierra R, Cerón C, Palacios W, Valencia R (1999) Mapa de Vegetación del Ecuador Continental, Escala 1:1’000,000. INEFAN/GEF-BIRF Project and EcoCiencia, Quito, EcuadorGoogle Scholar
  93. Soberón J, Peterson AT (2005) Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodivers Inform 2:1–10Google Scholar
  94. Soulé ME (1991) Conservation: tactics for a constant crisis. Science 253:744–750PubMedGoogle Scholar
  95. Soulé ME, Sanjayan MA (1998) Conservation targets: do they help? Science 279:2060–2061PubMedGoogle Scholar
  96. Stevens S (ed) (1997) Conservation through survival: indigenous peoples and protected areas. Island Press, Washington, DCGoogle Scholar
  97. Stockwell DRB, Noble IR (1992) Induction of sets of rules from animal distribution data: a robust and informative method of analysis. Math Comput Simul 33:385–390Google Scholar
  98. Stockwell DRB, Peters DP (1999) The GARP modeling system: Problems and solutions to automated spatial prediction. Int J Geogr Inform Syst 13:143–158Google Scholar
  99. Stockwell DRB, Peterson AT (2002a) Controlling bias in biodiversity data. In: Scott JM, Heglund PJ, Morrison ML et al (eds) Predicting species occurrences: issues of scale and accuracy. Island Press, Washington, DC, pp 537–545Google Scholar
  100. Stockwell DRB, Peterson AT (2002b) Effects of sample size on accuracy of species distribution models. Ecol Model 148:1–13Google Scholar
  101. Stockwell DRB, Peterson AT (2003) Comparison of resolution of methods used in mapping biodiversity patterns from point-occurrence data. Ecol Indic 3:213–221Google Scholar
  102. Stotz DF, Fitzpatrick JW, Parker TA III, Moskovits DK (1996) Neotropical birds: ecology and conservation. The University of Chicago Press, ChicagoGoogle Scholar
  103. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94Google Scholar
  104. Tilman D (1997) Community invasibility, recruitment limitation, and grassland biodiversity. Ecology 78:81–92CrossRefGoogle Scholar
  105. Tirira D (ed) (2001) Libro rojo de los mamíferos del Ecuador. Simbioe, EcoCiencia, Ministerio del Ambiente, y UICN, Quito, EcuadorGoogle Scholar
  106. Tirira D, Padilla D, Díaz M, Almeida P, Cortes K (2004) Portafolio de sitios prioritarios de conservación de la Ecorregión Pacífico Ecuatorial, capítulo terrestre. Alianza CDC-Jatun Sacha y TNC, Quito, EcuadorGoogle Scholar
  107. Turpie JK (1995) Prioritizing South African estuaries for conservation: a practical example using waterbirds. Biol Conserv 74:175–185Google Scholar
  108. Valencia R, Pitman N, León-Yánez S, Jørgensen PM (eds) (2000) Libro rojo de las plantas endémicas del Ecuador (2000). Herbario QCA, Pontificia Universidad Católica del Ecuador, Quito, EcuadorGoogle Scholar
  109. Valutis L, Mullen R (2000) The Nature Conservancy’s approach to prioritizing conservation action. Environ Sci Policy 3:341–346Google Scholar
  110. Vane-Wright RI, Humphries CJ, Williams PH (1991) What to protect? Systematics and the agony of choice. Biol Conserv 55:235–254Google Scholar
  111. Williams PH (1998) Key sites for conservation: area-selection methods for biodiversity. In: Mace GM, Balmford A, Ginsberg JR (eds) Conservation in a changing world. Cambridge University Press, Cambridge, pp 211–249Google Scholar
  112. Williams PH, Margules CR, Hilbert DW (2002) Data requirements and data sources for biodiversity priority area selection. J Biosci 27:327–338PubMedGoogle Scholar
  113. Wilson EO (1999) The diversity of life, 2nd edn. Norton & Company Inc., New YorkGoogle Scholar
  114. Young KR, Blumler MA, Daniels LD, Veblen TT, Ziegler SS (2003) Biogeography. In: Gaile GL, Willmott CJ (eds) Geography in America at the dawn of the 21st century. Oxford University Press, Oxford, pp 17–31Google Scholar
  115. Zaniewski AE, Lehmann A, Overton JM (2002) Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecol Model 157:261–280Google Scholar
  116. Zerner C (ed) (2000) People, plants, and justice: the politics of nature conservation. Columbia University Press, New YorkGoogle Scholar
  117. Zhang J, Goodchild MF (2002) Uncertainty in geographical information. Taylor and Francis, LondonGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • Manuel Peralvo
    • 1
  • Rodrigo Sierra
    • 1
  • Kenneth R. Young
    • 1
  • Carmen Ulloa- Ulloa
    • 2
  1. 1.Department of Geography and the EnvironmentUniversity of Texas at AustinAustinUSA
  2. 2.Missouri Botanical GardenSt. LouisUSA

Personalised recommendations