摘要:中华猕猴桃为中国特有果种，由于其独特的口感和较高的经济价值，近年来种植规模逐年扩大。在引种过程中，由于缺乏合理的布局规划和适生性分析，出现了品种单一化、易感病虫害等问题。近年来四川、陕西、贵州、重庆和湖北等猕猴桃主产省份相继开展了猕猴桃气候适宜性区划的研究，但目前的研究多未考虑未来气候变化对猕猴桃种植分布的影响，且伴随着气候变化的加剧，已有的研究结果已不能完全适应实际生产的需求。本文运用生态位模型软件MaxEnt，模拟和预测气候变化背景下大尺度范围中华猕猴桃适生区分布及其变化的可行性，以利于科学地优化产业结构、促进产业发展。基于当前数据和IPCC AR5提出的3种气候情景以及中华猕猴桃的分布信息，采用MaxEnt生态位模型和ArcGIS预测了中华猕猴桃的适生区及未来的变化趋势，用受试者工作特征曲线（receiver operating characteristic curve，ROC曲线）检测模型精度、刀切法（Jackknife test）筛选主导环境变量。结果表明，基于当前和未来情景构建的中华猕猴桃地理分布模型的AUC（area under curve）值均达到"极好"的标准，说明模型预测结果可用于本研究。当前气候条件下，中华猕猴桃的高适生区主要在四川、陕西、重庆、湖北、贵州、浙江、湖南、安徽、河南、江苏和甘肃等省份，面积达1.01×106 km2。中适生区则以高适生区为中心向外扩散，包括河南、湖北、安徽、江苏和山东等地，面积为6.79×105 km2。RCP2.6和RCP4.5排放情景下，中华猕猴桃高适生区的分布、面积及中心点位置都有所不同，面积均呈增加趋势；RCP8.5排放情景下，高适生区面积呈减少趋势。RCP4.5和RCP8.5排放情景下，中华猕猴桃高适生区中心点均有向北移动趋势。MaxEnt模型对未来气候变化条件下中华猕猴桃适生区的准确模拟与预测具有潜在应用价值，对该果树的气候适宜性区划具有重要指导意义。
关键词:中华猕猴桃/
MaxEnt模型/
环境变量/
气候变化/
适生区分析/
典型浓度路径情景
Abstract:Kiwifruit (Actinidia spp.), belonged to Actinidiaceae, is a type of perennial deciduous woody liana and an important class of berry fruit. With rich sugar, protein, amino acids, vitamins and especially high vitamin C content, the kiwifruit is known as "the king of the fruit" and has a good market prospect. A. chinensis is a species endemic in China with a fast-expanding planting area due to its unique subtle flavor and high economic value. Optimization of planting scale and distribution of the crop has been the major concern for regional planning. The objective of this study was to test and determine the possibility of using the MaxEnt (the maximum entropy) model to simulate and predict future large-scale distribution of A. chinensis. Based on current environmental factors, three future climate scenarios suggested in the IPCC fifth report and current distribution sites of A. chinensis, we used the MaxEnt model in combination with ArcGIS to predict the potential geographic distribution and trend of change of A. chinensis in China. The dominant factors were chosen by using the Jackknife test and the Receiver Operating Characteristic (ROC) curve was used to evaluate the simulation. The results showed that high value of area under curve (AUC) denoted good results which significantly differed from random predictions. Based on the evaluation criterion, the accuracies of the predictions of A. chinensis potential distribution in the current and future periods were excellent. The predicted result of the MaxEnt model was imported into ArcGIS10.0 for further analysis and showed that under present climatic conditions, the total suitable area was 26.92% of the total land area in China. The potential distribution was highly consistent with the locations of specimen records and field surveys. The highly suitable areas were in Sichuan, Shaanxi, Chongqing, Hubei, Guizhou, Zhejiang, Hunan, Anhui, Henan, Jiangsu and Gansu Provinces. The areas of highly suitable habitat in the main producing provinces were analyzed statistically. The results showed that under the current conditions, the most suitable area for A. chinensis cultivation was 1.01×106 km2, accounting for 38.94% of the total suitable areas. The moderately suitable areas were in Henan, Hubei, Anhui and Shandong Provinces, with the area of 6.79×105 km2, accounting for 26.26% of the total suitable areas. Comparison of future suitable areas with current suitable areas showed that areas of high suitability increased under scenarios RCP2.6 and RCP4.5, but decreased under scenario RCP8.5. Under scenarios RCP4.5 and RCP8.5, the mean center of highly suitable area of A. chinensis moved northward. The result showed that the MaxEnt model was highly reliable in determining not only the range of geographic distribution of A. chinensis, but also in identifying dominant environmental factors driving the geographic distribution. Whereas climate was a decisive factor in species distribution, change in distribution pattern of species was the most direct effect of climate change. The results provided a critical reference base for A. chinensis plantation pattern and countermeasures to cope with climate change in China.
Key words:Actinidia chinensis/
MaxEnt model/
Environmental variables/
Climate change/
Suitable area analysis/
Representative concentration pathway scenario
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