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Improving biodiversity monitoring by modeling relative abundance from "presence only" data

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  • Jingwa A, Brian

Abstract

One of the greatest concerns of this age is finding definitive ways to curb the loss of biodiversity. Although there have been growing calls on biodiversity protection and conservation by governments and institutions, the challenge lies on fitting models that best explain the trends of target species over space and time. The objective of this project was to determine the probability of detection of four species and how it changes with time during the season. Also, the occupancy of each species and its relationship with abundance was obtained. Siteoccupancy models were fitted to the data, with each model having four components; occupancy, colonization, extinction and detection probability. Model selection was done on the basis of the AIC criterion. The results show different trends for each species over time. The occupancies of each species do reflect the abundances in the various stages of their life cycles. The colonization, extinction and detection probability estimates were also obtained at each time point.

Suggested Citation

  • Jingwa A, Brian, 2011. "Improving biodiversity monitoring by modeling relative abundance from "presence only" data," MPRA Paper 35232, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:35232
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    File URL: https://mpra.ub.uni-muenchen.de/35232/1/MPRA_paper_35232.pdf
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    More about this item

    Keywords

    Presence-only data; data modelling; site occupancy; colonization; extinction; detection probability; species abundance;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Y40 - Miscellaneous Categories - - Dissertations - - - Dissertations
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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