Modelling Mediterranean oak palaeolandscapes using the MaxEnt model algorithm: The case of the NE Iberia under the Middle Holocene climatic scenario

Mas, Bàrbara; Riera, Santiago; Allué, Ethel

doi:10.1016/j.ecoinf.2023.101984

Cited by 3 publications

(1 citation statement)

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“…Additionally, the predictive outcomes of the Maxent model can be clearly and intuitively visualized using ArcGIS (Geographic Information System), thus enhancing the model's usability (Moreno et al., 2011 ). Thus far, the Maxent model has successfully assessed the impacts of global climate change on species distribution (Mas et al., 2023 ; Shi et al., 2023 ). Additionally, it has guided the introduction and cultivation of ecological and economic tree species (Gong et al., 2022 ; Tafesse et al., 2023 ; Zhao, Deng, et al., 2021 ), addressed limitations of species interactions, aided in establishing and managing protected areas for endangered species (Dias et al., 2023 ; Liu et al., 2018 ), and simulated potential invasion ranges of alien invasive species (Lemke et al., 2011 ; Padalia et al., 2014 ).…”

Section: Introductionmentioning

confidence: 99%

The optimized Maxent model reveals the pattern of distribution and changes in the suitable cultivation areas for Reaumuria songarica being driven by climate change

Wang,

Li,

Zhang

et al. 2024

Ecology and Evolution

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Reaumuria songarica, a drought‐resistant shrub, is widely distributed and plays a crucial role in the northern deserts of China. It is a key species for desert rehabilitation and afforestation efforts. Using the Maxent model to predict suitable planting areas for R. songarica is an important strategy for combating desertification. With 184 occurrence points of R. songarica and 13 environmental variables, the optimized Maxent model has identified the main limiting factors for its distribution. Distribution patterns and variation trends of R. songarica were projected for current and future climates (2030s, 2050s, 2070s, and 2090s) and different scenarios (ssp_126, ssp_370, and ssp_585). Results show that setting parameters to RM (regulation multiplier) = 4 and FC (feature combination) = LQHPT yields a model with good accuracy and high reliability. Currently, R. songarica is primarily suitable for desert control in eight provinces and autonomous regions, including Inner Mongolia, Xinjiang, Qinghai, and Ningxia. The total suitable planting area is 148.80 × 104 km2, representing 15.45% of China's land area. Precipitation (Precipitation of the wettest month, Precipitation of the warmest quarter, and Annual precipitation) and Ultraviolet‐B seasonality are the primary environmental factors limiting the growth and distribution of R. songarica. Mean temperature of the warmest quarter is the primary factor driving changes in the distribution of suitable areas for R. songarica under future climate scenarios. In future climate scenarios, the suitable planting area of R. songarica will shrink, and the distribution center will shift towards higher latitude, potentially indicate further desertification. The area of highly suitable habitat has increased, while moderately and less suitable habitat areas have decreased. Increased precipitation within R. songarica's water tolerance range is favorable for its growth and reproduction. With changes in the suitable cultivation area for R. songarica, priority should be given to exploring and utilizing its germplasm resources. Introduction and cultivation can be conducted in expanding regions, while scientifically effective measures should be implemented to protect germplasm resources in contracting regions. The findings of this study provide a theoretical basis for addressing desertification resulting from climate change and offer practical insights for the development, utilization, introduction, and cultivation of R. songarica germplasm resources.

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