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Biodiversity and Conservation

, Volume 17, Issue 13, pp 3079–3095 | Cite as

LIVES: a new habitat modelling technique for predicting the distribution of species’ occurrences using presence-only data based on limiting factor theory

  • Jin LiEmail author
  • David W. Hilbert
Original Paper

Abstract

Predictive modelling techniques using presence-only data have attracted increasing attention because they can provide information on species distributions and their potential habitat for conservation and ecosystem management. However, the existing predictive modelling techniques have several limitations. Here, we propose a novel predictive modelling technique, Limiting Variable and Environmental Suitability (LIVES), for predicting the distributions and potential habitats of species using presence-only data. It is based on limiting factor theory, which postulates that the occurrence of a species is only determined by the factor that most limits its distribution. LIVES predicts the suitability of a candidate grid cell for a species in terms of limiting environmental factor. It also predicts the most limiting factor or the potential limiting factor at the grid cell. The environmental factors can be climatic, geological, biological and any other relevant environmental factors, whether quantitative or qualitative. The predicted habitats consist of the current distribution of the species and the potentially suitable areas for the species where there is currently no record of occurrence. We also compare several properties of LIVES and other predictive modelling techniques. On the basis of 1,000 simulations, the average predictions of LIVES are more accurate than the two other commonly used modelling techniques (BIOCLIM and DOMAIN) for presence-only data.

Keywords

Climate change Habitat suitability Predictive model Spatial distribution Species distribution 

Notes

Acknowledgment

Assistance in GIS from Trevor Parker is gratefully acknowledged. We would like to thank John Ludwig, Guy Carpenter and Xiufu Zhang for critical and valuable comments on this manuscript. We also thank Alexandre H. Hirzel and Robert Hijmans for their helpful comments and information.

Glossary

BIOCLIM

A bioclimate analysis and prediction system

DOMAIN

A flexible modelling procedure for mapping potential distributions of plants and animals based on the Gower similarity metric

EDGM

Environmental-Distance Geometric Mean

EMTs

Existing modelling techniques, i.e. BIOCLIM, DOMAIN, EDGM, ENFA and MDM

ENFA

Ecological-Niche Factor Analysis

LIVES

Limiting Variable and Environmental Suitability

MDM

Mahalanobis distance model

SRs

Specimens and recordings

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.CSIRO Sustainable Ecosystems & CRC for Tropical Rainforest Ecology & ManagementTropical Forest Research CentreAthertonAustralia
  2. 2.Marine & Coastal Environment, PMD, Geoscience AustraliaCanberraAustralia

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