气候变化情景下中国金荞麦适生区变化分析.

This study was combined 137 valid distribution points from the Chinese of Fagopyrum dibotrys with 32 environmental factors based on the MaxEnt model and the ArcGIS software. The aim was to investigate by screening the primary environmental factors affecting the distribution of ecological fitness for this species. In addition, we predicted the spatial distribution pattern of potential suitable areas and the trend of centroid change during the Last Glacial Maximum (LGM), the Middle Holocene (MH), the present, as well as in future (2041-2060, 2050s; 2061-2080, 2070s) under three different distinct greenhouse gas emission paths. The results showed that the area under curve (AUC) values obtained from the assessment of the MaxEnt model using the indicator training and test data were 0.928±0.005 and 0.916±0.027, indicating a high level of accuracy in the predictions of the model. The primary environmental factors that limit the distribution of the ecological suitability of Fagopyrum dibotrys include annual precipitation (915-1899mm), min temperature of the coldest month (-2.4-6.9℃), temperature seasonality (3031-6319), elevation (61-357.2m, 1540-3408m), mean diurnal range (7.5-10.9℃), average wind speed in July (0.6-1.9m·s-1), precipitation of the warmest quarter (506.8-1060.9mm), average wind speed in April (0.5-2.3m·s-1) and precipitation seasonality (45.4-84.9). Since the Last Glacial Maximum, the potential habitability zone of Fagopyrum dibotrys had showned a notable increase. This expansion had been particularly pronounced under the high and medium concentration greenhouse gas emission scenario projected for the future, with the largest expansion area reaching 45.93×104km2. The spatial distribution of this expansion primarily was concentrated in the vicinity of the Hengduan Mountain Range and the Qinling-Huaihe river. At the same time, the examination of the centroids indicated a tendency for the dispersion of Fagopyrum dibotrys to migrate towards higher latitudes and altitudes by an order of magnitude in response to climate change scenarios. [ABSTRACT FROM AUTHOR]