Biodiversity and Conservation

, Volume 19, Issue 5, pp 1443–1454 | Cite as

Linking local ecological knowledge and habitat modelling to predict absolute species abundance on large scales

  • José Daniel Anadón
  • Andrés Giménez
  • Rubén Ballestar
Original Paper


Assessing the spatial structure of abundance of a species is a basic requirement to carry out adequate conservation strategies. However, existing attempts to predict species abundance, particularly in absolute units and on large scales, are scarce and have led to weak results. In this work we present a scheme to obtain, in an affordable way, a predictive model of absolute animal abundance on large scales based on the modelling of data obtained from local ecological knowledge (LEK) and its calibration. To exemplify this scheme, we build and validate a predictive absolute abundance model of the endangered terrestrial tortoise Testudo graeca in Southeast Iberian Peninsula. For that purpose, we collected distribution and relative abundance data of T. graeca using a low cost methodology, such as LEK, by means of interviewing shepherds. The information from LEK was employed to build a predictive habitat-based model of relative abundance. The relative abundance model was transformed into an absolute abundance model by means of calibration with a classical absolute abundance sampling method such as distance sampling. The obtained absolute abundance model predicted the observed absolute abundances values well in independent locations when compared with other works (R 2 = 36%) and thus can offer a cost-effective predictive ability. Our results show that reliable habitat-based predictive maps of absolute species abundance on regional scales can be obtained starting from low cost sampling methods of relative abundance, such as LEK, and its calibration.


Model validation Predictive abundance modelling Local ecological knowledge Interviews Distance sampling Model calibration Absolute abundance Double sampling Terrestrial tortoise Testudo graeca 



The authors wish to thank the shepherds whose knowledge constitutes the basis of this work. I. Pérez collaborated in various steps of this work. R. Jovani made valuable suggestions on a previous draft. Finally, we are grateful to all the people who participated in the linear samplings. This project was partially funded by ACUSUR and the Spanish Council of Science and Technology (project CGL2004-01335). We also thank the interest in the project of the Junta of Andalucía.


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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • José Daniel Anadón
    • 1
    • 2
  • Andrés Giménez
    • 1
  • Rubén Ballestar
    • 1
  1. 1.Área de Ecología, Departamento Biología AplicadaUniversidad Miguel Hernández, Edificio TorreblancaAlicanteSpain
  2. 2.Department of Ecological ModellingHelmholtz Center for Environmental Research-UFZLeipzigGermany

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