Dynamic analysis of mixed forest species under climate change scenarios. (December 2021)

• Record Type: Journal Article
• Authors: Wen, Guowei; Ye, Xingzhuang; Lai, Wenfeng; Shi, Chenyang; Huang, Qiuliang; Ye, Liqi; Zhang, Guofang
• Is Part Of: Ecological indicators. Volume 133(2021)
• Publication Date: 2021-12
• Subjects: AUC The area under the receiver operating characteristic curve -- TNSFP Three-North Shelterbelt Project -- Maxent Maximum Entropy -- GARP Genetic Algorithm for Rule-set Prediction -- GLM Generalized Linear Model -- RF Random Forest -- RCP2.6 Under the condition of low greenhouse gas emissions -- RCP4.5 Under the condition of general greenhouse gas emissions -- RCP8.5 Under the condition of high greenhouse gas emissions -- GBIF Global Biodiversity Information Facility -- PPBC Plant Photo Dank of China -- NSII National Specimen Information Infrastructure -- RM Regularization Multiplier -- FC Feature Combination -- L Linear -- Q Quadratic -- T Threshold -- H Hinge -- AICC Akaike Information Criterion Correction -- PC Percent Contribution -- PI Permutation Importance -- ROC The Receiver Operating Characteristic -- FMC Fuzzy Mathematical Classification -- NDVI Normalized Difference Vegetation Index; Climate change -- Maxent model -- Potential suitable area -- Mixed forest -- Pinus tabuliformis -- Ostryopsis davidiana; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2021.108350
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Dynamic analysis of mixed forest species. Potential suitable range of simulated species. Dominant factors of species distribution. P. tabuliformis and O. davidiana are mixed tree species. R's ENMeval language package to optimize Maxent model. Abstract: The outstanding self-regulation ability of mixed forest plays an important role in maintaining ecosystem stability. However, in recent years, climate change has caused geographical changes of species. This paper studies the potential geographical location of mixed species for the first time, so as to formulate the planting plan of mixed species in suitable areas. Therefore, we use the species distribution model based on Maxent to predict the potential suitable area of Chinese Pinus tabuliformis and Ostryopsis davidiana mixed forest under the climate change scenario, and provide a scientific basis for expanding the construction of P. tabuliformis and O. davidiana mixed forest in the future under three greenhouse gas emission scenarios (RCP2.6, RCP4.5 and RCP8.5) of current and future climate (2041–2060 and 2081–2100). The simulation accuracy of Maxent model is verified by the area under receiver operating characteristic curve (AUC ). The results show that the distribution range of P. tabuliformis is much larger than that of O. davidiana in China. Under the current climate conditions, the overlapping area of medium to highly suitable growing areas of P. tabuliformis and O. davidiana is 64.40 × 10 4 km 2, accounting for 6.71% of China's land area, mainly distributed in most areas of North China, Northeast China (Western Liaoning), Northwest China (Shaanxi, Ningxia, the Southernmost part of Inner Mongolia and Eastern Gansu) and Central China (Northern Hubei). Under the future high concentration emission scenario (RCP8.5), the overlapping area of medium to highly suitable growing areas of P. tabuliformis and O. davidiana will be reduced. Under the scenario of medium concentration climate emission (RCP 4.5), the centroids of P. tabuliformis and O. davidiana tend to migrate from west to north. The annual mean temperature (bio1) has a significant effect on the geographical distribution of P. tabuliformis and O. davidiana . In addition, the mean temperature of the driest quarter (bio9) and annual precipitation (bio12) also have a significant impact on the geographical distribution of P. tabuliformis . Similarly, there are obvious factors on the geographical distribution of O. davidiana, as well as isothermality (bio3) and precipitation of the wettest quarter (bio16), indicating that the important climate factors affecting the geographical distribution of P. tabuliformis and O. davidiana are not completely consistent. We believe that mixed forests play a positive role in coping with climate change. The research results can help decision-makers to formulate adaptation countermeasures based on climate change.