ArticleEcology and evolution2025
Occurrence Data Sources Matter for Species Distribution Modeling: A Case Study of
Article in Ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Conservation and Targeted Wild Tending ofBiology · 2026Article
- Modeling Human Impact on the Distribution of the Only Existing Species ofEcology and evolution · 2026Article
- Habitat Suitability Assessment of Milu (Animals : an open access journal from MDPI · 2026Article
- A Multi-Factor Habitat Suitability Model for Asian Elephants in the Greater Mekong Subregion: Effects of Vegetation and Climate.Ecology and evolution · 2026Article
- Multi-Source Remote Sensing and Ensemble Learning for Habitat Suitability Mapping of the Common Leopard (Sensors (Basel, Switzerland) · 2026Article
- Large Variability in Response to Future Climate and Land-Use Changes of François' Langur in China.Biology · 2026Article
- The Response ofEcology and evolution · 2026Article
- Climate-Driven Futures of Olive (Plants (Basel, Switzerland) · 2025Article
- Predicting Ecological Risks ofBiology · 2025Article
- Spatiotemporal Distribution Shifts ofBiology · 2025Article
- Unveiling the Impact of Climatic Factors on the Distribution Patterns ofPlants (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Climate change is anticipated to escalate the frequency and severity of global natural disasters over the next few decades, thereby significantly reshaping species distributions and populations. Species distribution models (SDMs), as essential tools in biogeography and biodiversity conservation, are pivotal for evaluating the impacts of climate change on species and forecasting their distribution ranges under different climate change scenarios over various periods. However, the absence of necessary background knowledge for model construction significantly affects the accuracy of these models, with the selection of different occurrence data sources being a key factor that constrains the accuracy of model predictions. In this study, using
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.