No species left behind: borrowing strength to map data-deficient species.
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PubMed
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| Auteurs principaux: | , , , , , , , , , , , , |
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| Format: | Artículo científico |
| Langue: | en |
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Trends in ecology & evolution
2025
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| author | Sharma, Shubhi Winner, Kevin Pollock, Laura J Thorson, James T Mäkinen, Jussi Merow, Cory Pedersen, Eric J Chefira, Kalkidan F Portmann, Julia M Iannarilli, Fabiola Beery, Sara de Lutio, Riccardo Jetz, Walter |
| author_facet | Sharma, Shubhi Winner, Kevin Pollock, Laura J Thorson, James T Mäkinen, Jussi Merow, Cory Pedersen, Eric J Chefira, Kalkidan F Portmann, Julia M Iannarilli, Fabiola Beery, Sara de Lutio, Riccardo Jetz, Walter Sharma, Shubhi Winner, Kevin Pollock, Laura J Thorson, James T Mäkinen, Jussi Merow, Cory Pedersen, Eric J Chefira, Kalkidan F Portmann, Julia M Iannarilli, Fabiola Beery, Sara de Lutio, Riccardo Jetz, Walter |
| collection | PubMed - marine biology |
| contents | No species left behind: borrowing strength to map data-deficient species. Sharma, Shubhi Winner, Kevin Pollock, Laura J Thorson, James T Mäkinen, Jussi Merow, Cory Pedersen, Eric J Chefira, Kalkidan F Portmann, Julia M Iannarilli, Fabiola Beery, Sara de Lutio, Riccardo Jetz, Walter Biodiversity Animals Conservation of Natural Resources Phylogeny Animal Distribution Models, Biological We lack the data needed to detect and understand biodiversity change for most species, despite some species having millions of observations. This unequal data coverage impedes conservation planning and our understanding of biodiversity patterns. The 'borrowing strength' approach leverages data-rich species to improve predictions for data-deficient species. We review multi- and joint-species distribution models that incorporate traits and phylogenies (termed 'ancillary information') and highlight how they could improve data-deficient spatial predictions. When ancillary information is informative of niche similarity, it has immense potential to improve estimates for data-deficient species distributions and address the Wallacean shortfall. While no statistical method can replace data-collection efforts, approaches discussed in this review offer an important contribution toward closing existing data gaps. |
| format | Artículo científico |
| id | pubmed_40571432 |
| institution | PubMed |
| language | en |
| publishDate | 2025 |
| publisher | Trends in ecology & evolution |
| record_format | pubmed |
| spellingShingle | No species left behind: borrowing strength to map data-deficient species. Sharma, Shubhi Winner, Kevin Pollock, Laura J Thorson, James T Mäkinen, Jussi Merow, Cory Pedersen, Eric J Chefira, Kalkidan F Portmann, Julia M Iannarilli, Fabiola Beery, Sara de Lutio, Riccardo Jetz, Walter Biodiversity Animals Conservation of Natural Resources Phylogeny Animal Distribution Models, Biological No species left behind: borrowing strength to map data-deficient species. Sharma, Shubhi Winner, Kevin Pollock, Laura J Thorson, James T Mäkinen, Jussi Merow, Cory Pedersen, Eric J Chefira, Kalkidan F Portmann, Julia M Iannarilli, Fabiola Beery, Sara de Lutio, Riccardo Jetz, Walter Biodiversity Animals Conservation of Natural Resources Phylogeny Animal Distribution Models, Biological We lack the data needed to detect and understand biodiversity change for most species, despite some species having millions of observations. This unequal data coverage impedes conservation planning and our understanding of biodiversity patterns. The 'borrowing strength' approach leverages data-rich species to improve predictions for data-deficient species. We review multi- and joint-species distribution models that incorporate traits and phylogenies (termed 'ancillary information') and highlight how they could improve data-deficient spatial predictions. When ancillary information is informative of niche similarity, it has immense potential to improve estimates for data-deficient species distributions and address the Wallacean shortfall. While no statistical method can replace data-collection efforts, approaches discussed in this review offer an important contribution toward closing existing data gaps. |
| title | No species left behind: borrowing strength to map data-deficient species. |
| topic | Biodiversity Animals Conservation of Natural Resources Phylogeny Animal Distribution Models, Biological |
| url | https://pubmed.ncbi.nlm.nih.gov/40571432/ |