Predicting bird species distributions in reconstructed landscapes

J.R. Thomson, R. Mac Nally, Erica Fleishman, Gregory Horrocks

    Research output: Contribution to journalArticle

    55 Citations (Scopus)

    Abstract

    Landscape optimization for biodiversity requires prediction of species distributions under alternative revegetation scenarios. We used Bayesian model averaging with logistic regression to predict probabilities of occurrence for 61 species of birds within highly fragmented box–ironbark forests of central Victoria, Australia. We used topographic, edaphic, and climatic variables as predictors so that the models could be applied to areas where vegetation has been cleared but may be replanted. Models were evaluated with newly acquired, independent data collected in large blocks of remnant native vegetation. Successful predictions were obtained for 18 of 45 woodland species (40%). Model averaging produced more accurate predictions than “single best” models. Models were most successful for smaller-bodied species that probably depend on particular vegetation types. Predictions for larger, generalist species, and seasonal migrants were less successful, partly because of changes in species distributions between model building (1995–1997) and validation (2004–2005) surveys. We used validated models to project occurrence probabilities for individual species across a 12,000-km2 region, assuming native vegetation was present. These predictions are intended to be used as inputs, along with landscape context and temporal dynamics, into optimization algorithms to prioritize revegetation. Longer-term data sets to accommodate temporal dynamics are needed to improve the predictive accuracy of models.
    Original languageEnglish
    Pages (from-to)752-766
    Number of pages15
    JournalConservation Biology
    Volume21
    Issue number3
    DOIs
    Publication statusPublished - 2007

    Fingerprint

    biogeography
    birds
    prediction
    revegetation
    land restoration
    vegetation
    Victoria (Australia)
    bird species
    distribution
    generalist
    habitat fragmentation
    vegetation types
    vegetation type
    woodlands
    woodland
    logistics
    biodiversity
    bird

    Cite this

    Thomson, J.R. ; Mac Nally, R. ; Fleishman, Erica ; Horrocks, Gregory. / Predicting bird species distributions in reconstructed landscapes. In: Conservation Biology. 2007 ; Vol. 21, No. 3. pp. 752-766.
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    abstract = "Landscape optimization for biodiversity requires prediction of species distributions under alternative revegetation scenarios. We used Bayesian model averaging with logistic regression to predict probabilities of occurrence for 61 species of birds within highly fragmented box–ironbark forests of central Victoria, Australia. We used topographic, edaphic, and climatic variables as predictors so that the models could be applied to areas where vegetation has been cleared but may be replanted. Models were evaluated with newly acquired, independent data collected in large blocks of remnant native vegetation. Successful predictions were obtained for 18 of 45 woodland species (40{\%}). Model averaging produced more accurate predictions than “single best” models. Models were most successful for smaller-bodied species that probably depend on particular vegetation types. Predictions for larger, generalist species, and seasonal migrants were less successful, partly because of changes in species distributions between model building (1995–1997) and validation (2004–2005) surveys. We used validated models to project occurrence probabilities for individual species across a 12,000-km2 region, assuming native vegetation was present. These predictions are intended to be used as inputs, along with landscape context and temporal dynamics, into optimization algorithms to prioritize revegetation. Longer-term data sets to accommodate temporal dynamics are needed to improve the predictive accuracy of models.",
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    Predicting bird species distributions in reconstructed landscapes. / Thomson, J.R.; Mac Nally, R.; Fleishman, Erica; Horrocks, Gregory.

    In: Conservation Biology, Vol. 21, No. 3, 2007, p. 752-766.

    Research output: Contribution to journalArticle

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