Calibration Invariance of the MaxEnt Distribution in the Maximum Entropy Principle

Impact of climate change on the geographical distribution and niche dynamics of Gastrodia elata

Background

Gastrodia elata is widely used in China as a valuable herbal medicine. Owing to its high medicinal and nutrient value, wild resources of G. elata have been overexploited and its native areas have been severely damaged. Understanding the impacts of climate change on the distribution of this endangered species is important for the conservation and sustainable use of G. elata.

Methods

We used the optimized maximum entropy model to simulate the potential distribution of G. elata under contemporary and future time periods (1970-2000, 2050s, 2070s, and 2090s) and different climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Under these conditions, we investigated the key environmental factors influencing the distribution of G. elata as well as the spatial and temporal characteristics of its niche dynamics.

Results

With high Maxent model accuracy (AUCmean = 0.947 ± 0.012, and the Kappa value is 0.817), our analysis revealed that annual precipitation, altitude, and mean temperature of driest quarter are the most important environmental factors influencing the distribution of G. elata. Under current bioclimatic conditions, the potentially suitable area for G. elata in China is 71.98 × 10⁴ km², while the highly suitable region for G. elata growth is 7.28 × 10⁴ km². Our models for three future periods under four climate change scenarios indicate that G. elata can maintain stable distributions in southern Shaanxi, southwestern Hubei, and around the Sichuan basin, as these areas are highly suitable for its growth. However, the center of the highly suitable areas of G. elata shift depending on different climatic scenarios. The values of niche overlap for G. elata show a decreasing trend over the forecasted periods, of which the niche overlap under the SSP3-7.0 scenario shows the greatest decrease.

Discussions

Under the condition of global climate change in the future, our study provides basic reference data for the conservation and sustainable utilization of the valuable and endangered medicinal plant G. elata. It is important to carefully choose the protection area of G. elata wild resources according the suitable area conditions modeled. Moreover, these findings will be valuable for providing insights into the breeding and artificial cultivation of this plant, including the selection of suitable areas for planting.

Selection of renewable energy systems sites using the MaxEnt model in the Eastern Mediterranean region in Turkey

Global warming has become the center of worldwide environmental concerns, especially in recent years. One of the ways to deal with global warming that causes climate change is to adopt the renewable energy power technique. Different renewable energy sources such as solar, wind, hydro, ocean, geothermal, and bioenergy are currently the backbone of green and sustainable economic growth. However, renewable energy sites are directly or indirectly dependent on environmental, social, and technical criteria.The main objective of this paper is to identify potential best renewable energy site alternatives using the maximum entropy model (MaxEnt) and Geographical Information systems (GIS). Thus, the framework formed by the findings will guide investors in the renewable energy sector. The results showed that suitable areas for solar and wind were mainly located in the Hatay and Mersin of the Eastern Mediterranean Region in Turkey. The energy suitability site maps indicate that 8% (3.42 km²) and 3.39% (1554 km²) of the total study area have suitability and very suitability for solar and wind energy respectively. Moreover, it is seen that 44.82% (20,689km²) of the regions are the same when suitable and very suitable regions are overlaid for the installation of solar and wind energy sites. The receiver operating characteristic (ROC) curve was used to evaluate model performance. The area under the curve (AUC) values are calculated 0.87 and 0.95 for solar and wind energy, respectively. Relying on realistic data, this paper proposes an innovative method to identify suitable areas for solar and wind power plants. The maps obtained to contribute to renewable energy production will be useful for creating future strategies in the Mediterranean region.