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AMBIO

, Volume 43, Issue 2, pp 149–161 | Cite as

Smallholder Farms as Stepping Stone Corridors for Crop-Raiding Elephant in Northern Tanzania: Integration of Bayesian Expert System and Network Simulator

  • Claudia Pittiglio
  • Andrew K. Skidmore
  • Hein A. M. J. van Gils
  • Michael K. McCall
  • Herbert H. T. Prins
Report

Abstract

Crop-raiding elephants affect local livelihoods, undermining conservation efforts. Yet, crop-raiding patterns are poorly understood, making prediction and protection difficult. We hypothesized that raiding elephants use corridors between daytime refuges and farmland. Elephant counts, crop-raiding records, household surveys, Bayesian expert system, and least-cost path simulation were used to predict four alternative categories of daily corridors: (1) footpaths, (2) dry river beds, (3) stepping stones along scattered small farms, and (4) trajectories of shortest distance to refuges. The corridor alignments were compared in terms of their minimum cumulative resistance to elephant movement and related to crop-raiding zones quantified by a kernel density function. The “stepping stone” corridors predicted the crop-raiding patterns. Elephant presence was confirmed along these corridors, demonstrating that small farms located between refuges and contiguous farmland increase habitat connectivity for elephant. Our analysis successfully predicted elephant occurrence in farmland where daytime counts failed to detect nocturnal presence. These results have conservation management implications.

Keywords

Ecological corridors Bayesian expert system Human–elephant conflict Crop damage control Farms Movement behavior 

Notes

Acknowledgments

This research was funded by the University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), The Netherlands, and the Global Environment Facility Project GCP/URT/124/WBG. The authors would like to thank the Food and Agriculture Organization of the United Nations (FAO), the Livestock, Environment and Development Initiative (LEAD), the African Wildlife Foundation (AWF), and the canvassers for their support to the crop-raiding data collection. The authors also thank the GEF project for providing the GIS layers used in this analysis and Istituto Oikos for providing the validation dataset.

Supplementary material

13280_2013_437_MOESM1_ESM.pdf (399 kb)
Supplementary material 1 (PDF 399 kb)

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Copyright information

© Royal Swedish Academy of Sciences 2013

Authors and Affiliations

  • Claudia Pittiglio
    • 1
  • Andrew K. Skidmore
    • 1
  • Hein A. M. J. van Gils
    • 1
  • Michael K. McCall
    • 2
    • 3
  • Herbert H. T. Prins
    • 4
  1. 1.Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation (ITC)University of TwenteEnschedeThe Netherlands
  2. 2.Department of Urban and Regional Planning and Geo-Information Management, Faculty of Geo-Information Science and Earth Observation (ITC)University of TwenteEnschedeThe Netherlands
  3. 3.Centro de Investigaciones en Geografía Ambiental (CIGA)Universidad Nacional Autónoma de México (UNAM)MoreliaMexico
  4. 4.Resource Ecology GroupWageningen UniversityWageningenThe Netherlands

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