ArticlePlants (Basel, Switzerland)2026
Climatic Suitability from MaxEnt Models Reflects Growth Performance in European Forest Trees.
Article in Plants (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Landscape Characteristics and Distribution of Suitable Habitats for the Black-Tailed Godwit During the Non-Breeding Season: A Case Study of the Middle and Lower Yangtze River Region.Animals : an open access journal from MDPI · 2026Article
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Authors and funding
2 authors.
Funding
Abstract
Species distribution models (SDMs) are widely used to define climatic constraints on species ranges, yet their ability to reflect demographic processes remains poorly understood. We integrated annually calibrated SDMs (1981-2005) with tree-ring width data from 15 European forest species in the Iberian Peninsula to evaluate if climatic suitability mirrors tree growth, particularly for populations at their climatic tolerance limits. Our results show that higher suitability consistently relates to reduced growth decline, acting as a reliable proxy for forest vigor. Notably, interannual variability in climatic suitability was positively associated with growth, suggesting that climatic fluctuations may enhance physiological resilience. We also found that Mediterranean species exhibit higher growth sensitivity to climatic suitability changes than Eurosiberian species. These findings demonstrate that SDMs can capture functional constraints beyond mere presence, positioning annual climatic suitability as a key predictor of radial growth and offering valuable insights for forest management under climate change.
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Registered trials
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