Using a species distribution model to guide <scp>NSW</scp> surveys of the long‐footed potoroo (<i>Potorous longipes</i>)

Wauchope-Drumm, Mareshell; Bentley, Joss; Beaumont, Linda J.; Baumgartner, John B.; Nipperess, David A.

doi:10.1111/aec.12804

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…Finally, a few studies have tested the ability of SDMs to predict occurrence using other methods. For example, Wauchope‐Drumm et al (2020) compared the average predicted suitability scores for independent presences versus absences for a rare marsupial, finding that mean suitability was significantly higher for independent presences than absences. Likewise, Pinto et al (2016) found that predicted suitability was higher for observed flapper skate tracks (based on geolocator data) than for random tracks.…”

Section: Resultsmentioning

confidence: 99%

Species distribution models rarely predict the biology of real populations

et al. 2021

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Species distribution models (SDMs) are widely used in ecology. In theory, SDMs capture (at least part of ) species' ecological niches and can be used to make inferences about the distribution of suitable habitat for species of interest. Because habitat suitability is expected to influence population demography, SDMs have been used to estimate a variety of population parameters, from occurrence to genetic diversity. However, a critical look at the ability of SDMs to predict independent data across different aspects of population biology is lacking. Here, we systematically reviewed the literature, retrieving 201 studies that tested predictions from SDMs against independent assessments of occurrence, abundance, population performance, and genetic diversity. Although there is some support for the ability of SDMs to predict occurrence (~53% of studies depending on how support was assessed), the predictive performance of these models declines progressively from occurrence to abundance, to population mean fitness, to genetic diversity. At the same time, we observed higher success among studies that evaluated performance for single versus multiple species, pointing to a possible publication bias. Thus, the limited accuracy of SDMs reported here may reflect the best-case scenario. We discuss the limitations of these models and provide specific recommendations for their use for different applications going forward. However, we emphasize that predictions from SDMs, especially when used to inform conservation decisions, should be treated as hypotheses to be tested with independent data rather than as stand-ins for the population parameters we seek to know.

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Section: Resultsmentioning

confidence: 99%

Species distribution models rarely predict the biology of real populations

et al. 2021

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“…This study is important in identifying the consequence of habitat change on the habitat suitability of the Timor friarbird. This information is the basic knowledge for effective decision-making for habitat conservation (Wauchope-drumm et al 2019;Chiatante et al 2019). This study aims to assess landscape factors that contribute to the habitat suitability of the Timor friarbird and to determine whether the western part of Timor Island is the optimum habitat for the species.…”

Section: Introductionmentioning

confidence: 99%

The habitat suitability of Timor friarbird (Philemon inornatus) in Western Timor Island, Indonesia

et al. 2022

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Abstract. Paga B, Pudyatmoko S, Wijayanti LR, Yuda P, Sulaksono N. 2021. The habitat suitability of Timor friarbird (Philemon inornatus) in Western Timor Island, Indonesia. Biodiversitas 23: 703-713. Timor friarbird is an endemic bird to Timor Island. The population of this bird has been declining due to land cover changes as a result of massive anthropogenic pressures. This study aimed to assess the suitability of Timor friarbird's habitat by using 12 ecogeographical variables. The sources of data included Sentinel 2A satellite imagery and remote sensing-based algorithms. The bird's presence was analyzed by using a combination of line transect with point count methods. Ecological Niche Factor Analysis (ENFA) model was applied to obtain habitat suitability value as well as coefficient of marginality (M) and specialization (S). These results showed that the Timor friarbird needs a habitat with a different value from the average of the entire habitat. High specialization value indicated that the species has a narrow ecological niche. Factors influencing habitat suitability included the distance from roads, the presence of mangroves, primary and secondary dryland forests, rivers, and low-density settlements. About 75% of the study area is classified as unsuitable habitat, and only 22% is suitable with range classes of suitability from marginal to optimal habitat. Areas with less anthropogenic pressure on the land cover will be preferred more by the bird. Improvement of unsuitable habitat and protection of suitable habitat, therefore, will be the most important strategy for Timor friarbird conservation.

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A gap analysis of reconnaissance surveys assessing the impact of the 2019–20 wildfires on vertebrates in Australia

Southwell

Wilkinson

Hao

et al. 2022

Biological Conservation

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Using a species distribution model to guide NSW surveys of the long‐footed potoroo (Potorous longipes)

Abstract: This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Cited by 4 publications

References 39 publications

Species distribution models rarely predict the biology of real populations

Species distribution models rarely predict the biology of real populations

The habitat suitability of Timor friarbird (Philemon inornatus) in Western Timor Island, Indonesia

A gap analysis of reconnaissance surveys assessing the impact of the 2019–20 wildfires on vertebrates in Australia

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