ArticleFrontiers in plant science2025
Predicting potential suitable habitat of
Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Assessing Potential Habitat Suitability of the Endangered Endo-HoloparasiticPlants (Basel, Switzerland) · 2026Article
- Habitat suitability and driving factors of the endangered medicinal plantFrontiers in plant science · 2026Article
- Modeling the Habitat Suitability and Range Shift ofBiology · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Understanding the impacts of climate change and land use dynamics on parasitic plants is crucial for ecological restoration and sustainable resource management in arid regions. This study proposes a two-dimensional modeling framework that integrates parasitic constraints and land use dynamics to predict the potential suitable habitat of Methods: Using an optimized MaxEnt model, host suitability probability was incorporated as a continuous probabilistic constraint, and high-resolution land use data were coupled to enhance ecological realism. The framework was applied to assess habitat suitability under current (1970-2000) and future climate scenarios (2050s, 2070s, 2090s, SSP126, SSP370, SSP585). Results: The inclusion of parasitic constraints reduced the suitable habitat area by 4.5% (from 138.20 × 104 km² to 131.92 × 104 km²) and exacerbated habitat fragmentation, particularly in Northwest China. Future projections reveal a decrease in the total suitable habitat area but an increase in the area of highly suitable regions, with the centroid shifting towards the northwest. Land use analysis demonstrated that unused land (70.21%) and grassland (13.81%) constitute the primary habitats, highlighting their significance for sustainable cultivation. Key environmental drivers identified include July precipitation, soil pH, and temperature of the warmest quarter. The model exhibited high predictive accuracy (AUC: 0.947-0.949). Discussion: The framework provides a reliable tool for assessing host-parasite interactions and land use impacts. These findings offer valuable insights for adaptive management strategies that balance ecological restoration and the sustainability of medicinal resources in arid ecosystems.
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