ArticleScientific reports2022
Distribution model transferability for a wide-ranging species, the Gray Wolf.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 16 citations in OpenAlex.
- The archaeology of climate change: a blueprint for integrating environmental and cultural systems.Nature communications · 2025Review
- Influence of Human Hunting Strategies and Large Carnivore Presence on Population Dynamics of European Facultative Scavengers.Ecology and evolution · 2024Article
- Testing spatial transferability of species distribution models reveals differing habitat preferences for an endangered delphinid (Ecology and evolution · 2024Article
- Key Factors behind the Dynamic Stability of Pairs of Egyptian Vultures in Continental Spain.Animals : an open access journal from MDPI · 2023Article
- Ecological niche model transferability of the white star apple (Chrysophyllum albidum G. Don) in the context of climate and global changes.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using existing data can be a reliable and cost-effective way to predict species distributions, and particularly useful for recovering or expanding species. We developed a current gray wolf (Canis lupus) distribution model for the western Great Lakes region, USA, and evaluated the spatial transferability of single-state models to the region. This study is the first assessment of transferability in a wide-ranging carnivore, as well as one of few developed for large spatial extents. We collected 3500 wolf locations from winter surveys in Minnesota (2017-2019), Wisconsin (2019-2020), and Michigan (2017-2020). We included 10 variables: proportion of natural cover, pastures, and crops; distance to natural cover, agriculture, developed land, and water; major and minor road density; and snowfall (1-km res.). We created a regional ensemble distribution by weight-averaging eight models based on their performance. We also developed single-state models, and estimated spatial transferability using two approaches: state cross-validation and extrapolation. We assessed performance by quantifying correlations, receiver operating characteristic curves (ROC), sensitivities, and two niche similarity indices. The regional area estimated to be most suitable for wolves during winter (threshold = maximum sensitivity/specificity) was 106,465 km
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