Prediction of Suitable Habitat for Lycophytes and Ferns in Northeast China: A Case Study on Athyrium brevifrons

Semiliquidambar cathayensis is a special and endangered plant in China, used for traditional Chinese medicine and in landscape applications. Predicting the impact of climate change on the distribution of S. cathayensis is crucial for its protection and the sustainable use of resources. We used the maximum entropy (MaxEnt) model optimized by the ENMeval data packet to analyze the potential geographic distribution changes of S. cathayensis in 12 provinces of Southern China for the different periods since the last interglacial period (LIG, 120–140 ka). Considering the potential geographic distribution changes in the province, and based on the two climate scenarios of Representative Concentration Pathways (RCP) 2.6 and RCP 8.5, the distribution range of S. cathayensis was analyzed and we predicted the range for the 2050s (average for 2041–2060) and 2070s (average for 2061–2080). The area under AUC (Area under the receiver operating characteristic (ROC) curve) is 0.9388 under these parameters, which indicates that the model is very accurate. We speculate that the glacial period refugia were the Nanling and Wuyi Mountains for S. cathayensis, and central and Western Fujian and Taiwan are likely to be the future climate refugia. In the mid-Holocene (MH, 6 ka), the growth habitat was 32.41% larger than the modern habitat; in the 2050s and 2070s (except RCP2.6–2070s), the growth habitat will shrink to varying degrees, so efforts to support its in situ and ex situ conservation are urgently needed. The jackknife test showed that the main factors affecting the geographical distribution of S. cathayensis were annual precipitation, precipitation of the wettest month, and precipitation of the driest month. The annual precipitation may be the key factor restricting the northward distribution of S. cathayensis. In general, the centroid of the distribution of S. cathayensis will move northward. The centroid of the adaptive habitats will move northward with the highest degree of climate abnormality. We think that Hainan Island is the most likely origin of S. cathayensis. These findings provide a theoretical basis for the establishment of genetic resources protection measures, the construction of core germplasm resources, and the study of the formation and evolution of Hamamelidaceae.

Section: Bioclimatic Predictors and Model Performancementioning

confidence: 56%

Distribution Pattern of Endangered Plant Semiliquidambar cathayensis (Hamamelidaceae) in Response to Climate Change after the Last Interglacial Period

Zhao

Zhang

et al. 2020

“…Although it is impossible to simulate the potential distribution of species with few sites, the prediction of the distribution pattern of D. validus is helpful for the discovery and conservation of narrow-range species in their corresponding habitats. Multi-model intercomparison studies have reported that the MaxEnt model, which is based on the maximum entropy principle, typically outperforms other SDMs in terms of high tolerance and high predictive accuracy, particularly for small sample sizes [56][57][58]. In this study, less distribution point information was used to predict the MaxEnt model, and the results showed that the cross-validation AUC of the D. validus model was 0.751 and the TSS value was 0.526, further supporting the suitability of our ArcGIS-based MaxEnt model.…”

Section: Discussionmentioning

confidence: 99%

Response of a Sylvan Moss Species (Didymodon validus Limpr.) with a Narrow Distribution Range to Climate Change

Wu,

Pan,

Bian

et al. 2023

Mosses are particularly susceptible to climate change owing to their close biological and ecological associations with climatic conditions. However, there is a limited understanding of the changes in distribution patterns of the moss species in forest ecosystems under climate change, especially in mosses with narrow ranges. Therefore, we reconstructed historical, simulated present, and predicted future potential distribution patterns of Didymodon validus, a narrow-range moss species in the forest ecosystem, using the MaxEnt model. The aim of this study was to explore its unique suitable habitat preference, the key environmental factors affecting its distribution, and the distributional changes of D. validus under climate change at a long spatial-time scale. Our findings indicate that the most suitable locations for D. validus are situated in high-altitude regions of southwestern China. Elevation and mean temperature in the wettest quarter were identified as key factors influencing D. validus distribution patterns. Our predictions showed that despite the dramatic climatic and spatial changes over a long period of time, the range of D. validus was not radically altered. From the Last Interglacial (LIG) to the future, the area of the highly suitable habitat of D. validus accounted for only 15.3%–16.4% of the total area, and there were weak dynamic differences in D. validus at different climate stages. Under the same climate scenarios, the area loss of suitable habitat is mainly concentrated in the northern and eastern parts of the current habitat, while it may increase in the southern and eastern margins. In future climate scenarios, the distribution core zone of suitable habitat will shift to the southwest for a short distance. Even under the conditions of future climate warming, this species may still exist both in the arid and humid regions of the QTP in China. In summary, D. validus showed cold and drought resistance. Our study provides important insights and support for understanding the impact of climate change on the distribution of D. validus, as well as its future distribution and protection strategies.

“…Species distribution models (SDMs) are the most powerful and widely used tools for evaluating geographical distributions in space and time and predicting species habitat preferences [11]. Among SDMs, the Bioclimate Analysis and Prediction System (BIOCLIM), the Ecological Niche Factor Analysis (ENFA), the Genetic Algorithm for Rule-Set Production (GARP), and Maximum Entropy Modeling (MaxEnt) have been commonly used in recent years [12].…”

Section: Introductionmentioning

confidence: 99%

Maximum Entropy Model Prediction of the Distributions of Two Sympatric Bean Weevil Species, Megabruchidius dorsalis (Fahraeus, 1839) and Bruchidius coreanus (Chûjô, 1937), under Various Climate Scenarios in Guizhou Province, China

Ma,

Peng,

Pan

et al. 2024

Megabruchidius dorsalis and Bruchidius coreanus are sympatric bean weevil species that bore into Gleditsia sinensis seeds, seriously affecting the commercial development of this plant. Here, we aimed to understand potential changes in the distribution of these two sympatric pests under current and future climate conditions to provide a reference for the prediction of their occurrence and facilitate their prevention and control. Based on empirical field data, we predicted the potential distribution of M. dorsalis and B. coreanus in suitable habitat areas using the MaxEnt model and explored the relationships among different spatiotemporal distributions using change analysis. Our findings showed that compared with the current situation, the suitable areas for M. dorsalis and B. coreanus were predicted to increase by 4.8141% and 3.1009%, respectively, in the future. Isothermality (BIO3), min temperature of coldest month (BIO6), and variance in precipitation (BIO15) in the coldest month were determined to be the main factors restricting the current distribution of M. dorsalis and B. coreanus. Areas currently suitable for the two species are mainly in the central region of Guizhou and are predicted to move eastward in the future. Significant area under the receiver operating characteristics curve values for M. dorsalis (0.878) and B. coreanus (0.833) indicated that MaxEnt could be used to predict the potential habitats of these weevils, providing valuable information to inform their control in Guizhou Province.