Distributional change in suitable areas for Toona sureni based on MaxEnt model
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摘要: 气候变化通过改变物种的生境进而影响生物多样性。紫椿是一种具有高生态、经济、药用价值的用材树种，在我国与其他香椿属物种一起被称为“中国桃花心木”。了解该物种对生境要求、评价其生境质量、预测其适生区分布有助于紫椿的保护、引种及其人工林的发展。MaxEnt模型的优点在于能利用现存不完整、小样本、离散型分布数据构建物种适生区预测模型，且用受试者工作曲线下面积(AUC)检验预测模型的精度，面积越大精度越高。研究应用紫椿在云南分布数据及MaxEnt软件构建其适生区分布模型，结果表明：适生区分布模型平均训练AUC和平均测试AUC分别为0.959和0.818，说明对紫椿适生区的预测是可靠的；温度季节性变化的标准差、最冷月最低温(℃)、最干季度平均温度(℃)、最冷季度降水量(mm)、年均温变化范围是决定紫椿适生区分布的重要因素。对当代和未来(21世纪50年代，21世纪70年代)气候变暖条件下(RCP2.6情景)的紫椿在云南省和全国适生区面积进行了计算，结果直观、定量反映了气候变化下紫椿适生区的变迁，预测云南省及全国的紫椿适生区随全球变暖而萎缩。Abstract: Climate change influences biodiversity by altering the habitat of species in ecosystem. Toona sureni is a timber plant with high ecological, economic and medicinal value. It is called "Chinese mahogany" in China with other species in Toona. Understanding the habitat requirements, evaluating habitat quality and predicting the species' potential habitat are significant for protecting T.sureni, as well as for its protection introduction and plantation. Because of the advantages of using presence-only data and performing well with small sample sizes, incomplete data and gaps, MaxEnt model was employed to simulate the habitat suitability distribution, and the area under the receive operating characteristic curve(AUC)was used to examine the model's accuracy, the larger the AUC is, the more accurate the prediction is. So, based on the distribution of T. sureni in Yunnan Province of southwestern China, the MaxEnt model was used to set up its distributional model of potential habitat. The results showed that the mean training AUC and mean test AUC were 0.959 and 0.818, respectively. It is illustrated that the prediction of T.sureni's suitable habitats was reliable. Five variables, namely standard deviation of temperature seasonal change, minimum temperature of the coldest month(℃), mean temperature of the driest quarter(℃), precipitation of the coldest quarter (mm), range of annual temperature were significant factors determining T. sureni 's suitable habitat. Habitat suitability for current and future climate warming(2050s, 2070s) under scenario RCP2.6 in Yunnan Province and China was calculated. The study reports the intuitive and quantitative predictions of climate change on T. sureni species' suitable habitats. The habitat suitability of T.sureni in Yunnan Province and China is predicted to deteriorate with global warming.
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Keywords:
- Toona sureni /
- MaxEnt /
- global warming /
- distributional area change
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图 3 7个变量因子响应曲线
Figure 3. Response curves of 7 environmental variables in Toona sureni's habitat distribution model
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图 4 紫椿分布记录点及在云南不同时期的适生区分布预测
A.分布记录点；B.当代(1950—2000年)适生区地理分布预测图；C.21世纪50年代(2050s)适生区地理分布预测图; D.21世纪70年代(2070s)适生区地理分布预测图。
Figure 4. Predicted distribution map of suitable region under different climate conditions for Toona sureni in Yunnan Province
A, the sample record point of Toona sureni in this study; B, predicted distribution map under the current climate conditions(1950—2000); C, predicted distribution map under the 2050s climate conditions; D, predicted distribution map under the 2070s climate conditions.
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图 5 紫椿分布记录点及在中国不同时期的适生区分布预测
A.分布记录点；B.当代(1950—2000年)适生区地理分布预测图；C.21世纪50年代(2050s)适生区地理分布预测图; D.21世纪70年代(2070s)适生区地理分布预测图。
Figure 5. Predicted distribution map of suitable region under different climate conditions for Toona sureni in China
A, the sample record point of Toona sureni in this study; B, predicted distribution map under the current climate conditions(1950—2000); C, predicted distribution map under the 2050s climate conditions; D, predicted distribution map under the 2070s climate conditions.
表 1 生物气候指标
Table 1 Bioclimate variables
代码 Code 描述 Description bio1 年均温 Annual mean temperature bio2 昼夜温差月均值 Monthly mean diurnal temperature range bio3 等温性 Isothermality (bio2/bio7×100) bio4 温度季节性变化的标准差 Standard deviation of temperature seasonal change bio5 最暖月最高温 Max. temperature of the warmest month bio6 最冷月最低温 Min. temperature of the coldest month bio7 年均温变化范围 Range of annual temperature bio8 最湿季度平均温度 Mean temperature of the wettest quarter bio9 最干季度平均温度 Mean temperature of the driest quarter bio10 最暖季度平均温度 Mean temperature of the warmest quarter bio11 最冷季度平均温度 Mean temperature of the coldest quarter bio12 年均降水量 Annual average precipitation bio13 最湿月降水量 Precipitation of the wettest month bio14 最干月降水量 Precipitation of the driest month bio15 降水量变异系数 CV of precipitation bio16 最湿季度降水量 Precipitation of the wettest quarter bio17 最干季度降水量 Precipitation of the driest quarter bio18 最暖季度降水量 Precipitation of the warmest quarter bio19 最冷季度降水量 Precipitation of the coldest quarter alti 海拔 Altitude 
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表 2 不同时期紫椿在云南省及全国的适生面积预测
Table 2 Predicted suitable region under different climate conditions for Toona sureni in Yunnan Province and China km2
区域 District 年代 Decade 总适生区
Total suitable region低度适生区
Lowly suitable region中度适生区
Moderately suitable region高度适生区
Highly suitable region云南省 Yunnan 1950—2000 102115 63678 34226 4211 2050s 66937 40491 20313 6133 2070s 65766 42876 20385 2505 全国 China 1950—2000 110023 70237 35575 4211 2050s 68109 41660 20316 6133 2070s 71238 47951 20782 2505
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