Effects of Environment Change Scenarios on the Potential Geographical Distribution of Cunninghamia lanceolata (Lamb.) Hook. in China

Modeling Forest Response to Climate Change

Marano,

Dalmonech,

Collalti

2024

Modeling the Impacts of Climate Change on Potential Distribution of Betula luminifera H. Winkler in China Using MaxEnt

Yang,

Xiang,

et al. 2024

Betula luminifera H. Winkler, a fast-growing broad-leaved tree species native to China’s subtropical regions, possesses significant ecological and economic value. The species’ adaptability and ornamental characteristics make it a crucial component of forest ecosystems. However, the impacts of global climate change on its geographical distribution are not well understood, necessitating research to predict its potential distribution shifts under future climate scenarios. Our aims were to forecast the impact of climate change on the potential suitable distribution of B. luminifera across China using the MaxEnt model, which is recognized for its high predictive accuracy and low sample data requirement. Geographical coordinate data of B. luminifera distribution points were collected from various databases and verified for redundancy. Nineteen bioclimatic variables were selected and screened for correlation to avoid overfitting in the model. The MaxEnt model was optimized using the ENMeval package, and the model accuracy was evaluated using the Akaike Information Criterion Correction (delta.AICc), Training Omission Rate (OR10), and Area Under the Curve (AUC). The potential distribution of B. luminifera was predicted under current and future climate scenarios based on the Shared Socio-economic Pathways (SSPs). The optimized MaxEnt model demonstrated high predictive accuracy with an AUC value of 0.9. The dominant environmental variables influencing the distribution of B. luminifera were annual precipitation, minimum temperature of the coldest month, and standard deviation of temperature seasonality. The potential suitable habitat area and its geographical location were predicted to change significantly under different future climate scenarios, with complex dynamics of habitat expansion and contraction. The distribution centroid of B. luminifera was also predicted to migrate, indicating a response to changing climatic conditions. Our findings underscore the importance of model optimization in enhancing predictive accuracy and provide valuable insights for the development of conservation strategies and forest management plans to address the challenges posed by climate change.

Landscape Dynamics, Succession, and Forecasts of Cunninghamia lanceolata in the Central Producing Regions of China

Liu,

Zhong,

Chen

et al. 2024

Cunninghamia lanceolata (Lamb.) Hook accounts for 12% of the total forest area in southern China, second only to Masson pine forests, and is an important part of the forest landscape in this region, which has a significant impact on the overall forest structure in southern China. In this study, we used kernel density analysis, landscape index calculation, variance test, and Markov prediction to analyze and forecast the evolution trend of landscape pattern in the central area of C. lanceolata in ten years. The objective is to investigate the change trend of the spatial pattern of C. lanceolata landscape in the long time series and its possible impact on zonal vegetation, as well as the macro-succession trend of C. lanceolata under the current social and economic background, and to make a scientific and reasonable prediction of its future succession trend. The current and future forecast results show that the landscape fragmentation degree of C. lanceolata is intensified, the erosion of bamboo forest is continuously intensified, and the landscape quality is continuously low. These results provide a reference for the future development direction of C. lanceolata and emphasize the need for targeted C. lanceolata management strategies in the future development of C. lanceolata, emphasizing the strengthening of monitoring, controlling harvesting, and managing bamboo competition in order to balance wood production with landscape quality and ecosystem stability.