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

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Abstract

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.

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Abbreviations

BLM:

Boundary length modifier

CDC:

Conservation Data Center

CRU CL 2.0:

Climatic Research Unit’s Climatologic database

DEM:

Digital Elevation Model

DINAREN:

National Directorate of Natural Resources of Ecuador

ENSO:

El Niño/Southern Oscillation

GARP:

Genetic Algorithm for Rule Set Prediction

GIScience:

Geographic Information Science

INRENA:

National Institute of Natural Resources of Peru

IUCN:

International Union for the Conservation of Nature and Natural Resources

LULC:

Land Use/Land Cover

MBG:

Missouri Botanical Garden

PET:

Potential evapotranspiration

PSAD:

Provisional South-American Datum

SPOT:

Spatial Portfolio Optimization Tool

SRTM:

Shuttle Radar Topographic Mission

TNC:

The Nature Conservancy

UTM:

Universal Transversal Mercator

VAST:

Missouri Botanical Garden’s VAScular Tropicos database

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Acknowledgements

We would like to thank The Nature Conservancy for providing funds for the travel of the first author to Ecuador. The staff of TNC’s Equatorial Pacific Project and the Jatun Sacha/CDC Alliance provided their kind advice and access to data without which this study would not have been possible. Many thanks are due to Blanca León and Diego Tirira for their feedback in the process of selection of plant and vertebrate species, and to one anonymous reviewer who provided constructive comments. All the arguments made in this article remain the responsibility of the authors.

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  1. Department of Geography and the Environment, University of Texas at Austin, 210 W. 24th, Austin, TX, 78712, USA

    Manuel Peralvo, Rodrigo Sierra & Kenneth R. Young

  2. Missouri Botanical Garden, 299, St. Louis, MO, 63166-0299, USA

    Carmen Ulloa- Ulloa

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  1. Manuel Peralvo
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  2. Rodrigo Sierra
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  4. Carmen Ulloa- Ulloa
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Correspondence to Manuel Peralvo.

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Peralvo, M., Sierra, R., Young, K.R. et al. Identification of Biodiversity Conservation Priorities using Predictive Modeling: An Application for the Equatorial Pacific Region of South America. Biodivers Conserv 16, 2649–2675 (2007). https://doi.org/10.1007/s10531-006-9077-y

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