气候变化条件下山西翅果油树适宜分布区的空间迁移预测

doi:10.13287/j.1001-9332.201902.040

应用生态学报 ›› 2019, Vol. 30 ›› Issue (2): 496-502.doi: 10.13287/j.1001-9332.201902.040

气候变化条件下山西翅果油树适宜分布区的空间迁移预测

张殷波^1*,刘彦岚¹,秦浩²,孟庆欣¹

¹山西大学环境与资源学院, 太原 030006;
²山西财经大学统计学院, 太原 030006

收稿日期:2018-07-23 修回日期:2018-12-14 出版日期:2019-02-20 发布日期:2019-02-20
通讯作者: E-mail:zhangyinbo@sxu.edu.cn
作者简介:张殷波,女,1979年生,博士,副教授.主要从事生物多样性及其保护等研究.E-mail:zhangyinbo@sxu.edu.cn
基金资助:
本文由山西省回国留学人员科研项目(2017-022)和山西省自然科学基金项目(2011011031-1)资助

Prediction on spatial migration of suitable distribution of Elaeagnus mollis under climate change conditions in Shanxi Province, China.

ZHANG Yin-bo^1*, LIU Yan-lan¹, QIN Hao², MENG Qing-xin¹

¹Department of Environment and Resources, Shanxi University, Taiyuan 030006, China;
²School of Statistics, Shanxi University of Finance & Economics, Taiyuan 030006, China

Received:2018-07-23 Revised:2018-12-14 Online:2019-02-20 Published:2019-02-20
Supported by:
This work was supported by the Research Project of Returned Oversea Scholar of Shanxi, China (2017-022) and the Natural Science Foundation of Shanxi, China (2011011031-1).

摘要/Abstract

摘要： 气候变化对生物多样性的影响及其适应性直接关系着生物多样性保护的成效,预测未来气候变化条件下受威胁物种适宜生境的空间变化趋势对生物多样性保护具有重要的理论和实践意义.本文选取我国特有濒危植物翅果油树为研究对象,在区域尺度上预测气候变化条件下的物种适宜分布区,进而通过空间分析模拟不同气候变化情景下其适宜分布区的空间变化和迁移趋势.最大熵(Maxent)物种分布模型预测结果显示: 翅果油树的两个适宜分布区在未来气候变化情景下呈现不同的迁移趋势,吕梁山适生区呈现出纬度方向上的轻微波动,而中条山适生区则呈现出向高海拔地区迁移的趋势.适生区空间格局变化分析表明,翅果油树当前适生区的边界存在明显变化区域,包括新增适生区(零星分布在两个适生区的边缘地带,新增率为9.1%～20.9%)和丧失适生区(集中分布在吕梁山适生区北缘和中条山适生区东南部,丧失率为16.4%～31.2%),且两者对气候变化的响应较为敏感.利用分类统计工具Zonal计算得出,在未来气候变化条件下吕梁山适生区的中心点呈现向南迁移的趋势,最大迁移距离为7.451 km;中条山适生区的中心点则呈现出向西北迁移的趋势,最大迁移距离为8.284 km.表明山西翅果油树的分布对气候变化的响应较为剧烈.

关键词: 翅果油树, Maxent, 空间格局, 气候变化, 迁移趋势

Abstract: The impacts of climate change on biodiversity and its adaptation will directly affect the efficiency of biodiversity conservation. Predicting spatial variation of suitable habitats of threatened species under future climate change has important theoretical and practical significance for biodiversity conservation. In this study, we predicted the suitable distribution of Elaeagnus mollis, an endemic endangered plant in China, under climate change at regional scales. Then, we simulated the spatial variation and migration tend of suitable distribution under different climate change scenarios by spatial analysis. The results from Maxent model showed that the two suitable distribution areas of E. mollis presented different migration trends under the future climate change scenarios: the suitable areas of Lyuliang Mountain would fluctuate slightly in latitudinal direction, while that in Zhongtiao Mountain would migrate to high elevation. Analysis of the spatial pattern change of the suitable areas indicated that the areas with obvious change occurred at the boundary of the suitable areas of E. mollis, including new suitable area and lost suitable area. The new suitable areas were scattered in the marginal of the original, with the increase rate of 9.1% to 20.9%, and the lost suitable areas were concentrated in the northern Lyuliang Mountain suitable areas and the southeast Zhongtiao Mountain suitable areas, with the loss rate of 16.4% to 31.1%. These regions were more sensitive to climate change. Using the classification statistical tool of Zonal, we found that the central points of the Lyuliang Mountain suitable areas showed southward migration trend under the future climate change, with the maximum migration distance of 7.451 km, while the center point of the Zhongtiao Mountain suitable areas showed migration trend to the northwest, with the maximum migration distance of 8.284 km. Our results indicated that the response of E. mollis distribution in Shanxi to climate change was intense.

Key words: climate change, spatial pattern, Elaeagnus mollis, Maxent, migration tend

张殷波,刘彦岚,秦浩,孟庆欣. 气候变化条件下山西翅果油树适宜分布区的空间迁移预测[J]. 应用生态学报, 2019, 30(2): 496-502.

ZHANG Yin-bo, LIU Yan-lan, QIN Hao, MENG Qing-xin. Prediction on spatial migration of suitable distribution of Elaeagnus mollis under climate change conditions in Shanxi Province, China.[J]. Chinese Journal of Applied Ecology, 2019, 30(2): 496-502.

参考文献

[1] Zhang F (张峰). Study on Quantitative Ecology of Rare and Endangered Plant Elaeagnus mollis. Beijing: Science Press, 2012 (in Chinese)
[2] Xie S-L (谢树莲),Ling Y-H (凌云浩). The biology features and conservation of Elaeagnus mollis a rare and endangered plant species. Bulletin of Botanical Research (植物研究), 1997, 17(2): 153-157 (in Chinese)
[3] Wang Z-H (王志红), Zhang K (张坤), Zhou W-Z (周维芝), et al. Study on Elaeagnus mollis resource and its sustainable utilization in Shanxi. Journal of Shanxi University (Natural Science) (山西大学学报:自然科学版), 2002, 25(4): 358-360 (in Chinese)
[4] Chen IC, Hill JK, Ohlemüller R, et al. Rapid range shifts of species associated with high levels of climate warming. Science, 2011, 333: 1024-1026
[5] Pio DV, Engler R, Linder HP, et al. Climate change effects on animal and plant phylogenetic diversity in southern Africa. Global Change Biology, 2014, 20: 1538-1549
[6] Dieleman CM, Branfireun BA, McLaughlin JW, et al. Climate change drives a shift in peatland ecosystem plant community: Implications for ecosystem function and stability. Global Change Biology, 2015, 21: 388-395
[7] Ruiz-Labourdette D, Nogués-Bravo D, Ollero HS, et al. Forest composition in Mediterranean mountains is projected to shift along the entire elevational gradient under climate change. Journal of Biogeography, 2012, 39: 162-176
[8] Kozak KH, Graham CH, Wiens JJ. Integrating GIS-based environmental data into evolutionary biology. Trends in Ecology & Evolution, 2008, 23: 141-148
[9] Liu HY, Yin Y. Response of forest distribution to past climate change: An insight into future predictions. Chinese Science Bulletin, 2013, 58: 4426-4436
[10] Bellard C, Bertelsmeier C, Leadley P, et al. Impacts of climate change on the future of biodiversity. Ecology Letters, 2012, 15: 365-377
[11] Espndola A, Pellissier L, Maiorano L, et al. Predicting present and future intra-specific genetic structure through niche hind casting across 24 millennia. Ecology Letters, 2012, 15: 649-657
[12] Zhang Y-B (张殷波), Zhang F (张峰). Structural diversity of Elaeagnus mollis communities. Chinese Journal of Ecology (生态学杂志), 2012, 31(8): 1936-1941 (in Chinese)
[13] Zhang F (张峰), Shangguan T-L (上官铁梁). Study on the species diversity of Elaeagnus mollis community in Shanxi. Acta Phytoecologica Sinica (植物生态学报), 1999, 23(5): 471-474 (in Chinese)
[14] Zhang F (张峰), Shangguan T-L (上官铁梁). Niche characteristics of dominant populations in Elaeagnus mollis communities, Shanxi. Acta Botanica Boreali-Occidentalia Sinica (西北植物学报), 2004, 24(1): 70-74 (in Chinese)
[15] Zhang F (张峰), Shangguan T-L (上官铁梁). Population pattern of dominant species in Elaeagnus mollis communities, Shanxi. Acta Phytoecologica Sinica (植物生态学报), 2000, 24(5): 590-594 (in Chinese)
[16] Qin Y-Y (秦永燕), Wang Y-L (王祎玲), Zhang Q-D (张钦弟), et al. Analysis on the population genetic diversity of an endangered plant (Elaeagnus mollis) by SSR markers. Journal of Wuhan Botanical Research (武汉植物学研究), 2010, 28(4): 466-472 (in Chinese)
[17] Xu Q (许强), Lyu J-Z (吕金枝), Miao Y-M (苗艳明), et al. Spatial distribution patterns and association of major species in Elaeagnus mollis communities. Chinese Bulletin of Botany (植物学报), 2016, 51(1): 49-57 (in Chinese)
[18] Zhang F (张峰), Han S-Q (韩书权), Shangguan T-L (上官铁梁). Analysis on relationship between geographic distribution of Elaeagnus mollis and eco-environment factors in China. Journal of Shanxi University (Natural Science) (山西大学学报:自然科学版), 2001, 24(1): 86-88 (in Chinese)
[19] Zhang Y-B (张殷波), Gao C-H (高晨虹), Qin H (秦浩). Prediction of suitable distribution of Elaeagnus mollis and response to climate change based on the Maxent model. Chinese Journal of Applied Ecology (应用生态学报), 2018, 29(4): 1156-1162 (in Chinese)
[20] Graham MH. Confronting multicol linearity in ecological multiple regression. Ecology, 2003, 84: 2809-2815
[21] Pearson RG, Raxworthy CJ, Nakamura M, et al. Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar. Journal of Biogeography, 2006, 34: 102-117
[22] Xu W-H (徐卫华), Luo C (罗翀). Application of MAXENT model in Rhinopithecus roxllanae habitat assessment in Qinling Mountain. Forest Engineering (森林工程), 2010, 26(2): 1-6 (in Chinese)
[23] Swets JA. Measuring the accuracy of diagnostic systems. Science, 1988, 240: 1285-1293
[24] Raes N, Roos MC, Slik JWF, et al. Botanical richness and endemicity patterns of Borneo derived from species distribution models. Ecography, 2009, 32: 180-192
[25] Bateman BL, Vanderwal J, Williams SE, et al. Biotic interactions influence the projected distribution of a specialist mammal under climate change. Diversity and Distributions, 2012, 18: 861-872
[26] Zhang MG, Zhou ZK, Chen WY, et al. Major declines of woody plant species ranges under climate change in Yunnan, China. Diversity and Distributions, 2013, 20: 405-415
[27] Parmesan C. Ecological and evolutionary responses to recent climate change. Annual Review of Ecology, Evolution & Systematics, 2006, 37: 637-669
[28] Robertj W, David G, Javier G, et al. An elevational shift in butterfly species richness and composition accompanying recent climate change. Global Change Biology, 2007, 13: 1873-1887
[29] Wang G-X (王国祥), Liu X-Q (刘学勤), Qiao J (乔俊). Shanxi Forest. Beijing: China Forestry Press, 1992 (in Chinese)
[30] Yang K-M (杨克明), Liu Z-G (刘珍贵), Yang T-E (杨天恩). Seeding and forestation tests of Elaeagnus mollis at high cold and damp mountains. Nonwood Forest Research (经济林研究), 2010, 28 (4): 104-107 (in Chinese)
[31] Yang W-Z (杨文忠), Kang H-M (康洪梅), Xiang Z-Y (向振勇), et al. Methods and techniques for conserving wild plant species with extremely small populations. Journal of West China Forestry Science (西部林业科学), 2014, 43(5): 24-29 (in Chinese)

气候变化条件下山西翅果油树适宜分布区的空间迁移预测

Prediction on spatial migration of suitable distribution of Elaeagnus mollis under climate change conditions in Shanxi Province, China.

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	胡爱莲, 杨娟, 刘宝林, 邹瑜. 广西沿海红树林潜在适宜区变化及互花米草入侵威胁的预测 [J]. 应用生态学报, 2024, 35(3): 669-677.
[2]	贾丁一, 郭荣朋, 丘伟国, 巫志龙, 林森, 胡喜生. 不同等级道路对生态网络的影响——以福州市为例 [J]. 应用生态学报, 2024, 35(2): 489-500.
[3]	李京忠, 辛振华, 谢潇, 薛冰, 任婉侠. 半干旱区植被覆盖时空变化特征及其对气候变化的响应: 以锡林郭勒盟为例 [J]. 应用生态学报, 2024, 35(1): 80-86.
[4]	杨振康, 杨婉蓉, 刘志娟, 高伟达, 任图生, 沈彦俊, 杨晓光. 气候变化对东北三省土壤风蚀的影响 [J]. 应用生态学报, 2023, 34(9): 2429-2435.
[5]	谢卓洪, 雷敏, 刘利杰, 莫燕卿, 战国强, 刘萍. 珠三角城市群景观生态格局评价与优化 [J]. 应用生态学报, 2023, 34(9): 2481-2488.
[6]	冷鹏, 王建青, 谭云燕, 邵亚军, 王丽燕, 施秀珍, 张国友. 大气CO₂和O₃浓度升高对水稻根际土壤胞外酶活性的影响 [J]. 应用生态学报, 2023, 34(8): 2185-2193.
[7]	邢衍阔, 康斌, 鹿志创, 高祥刚, 王震, 田甲申. 气候变化条件下太平洋丽龟的适宜生境及其变化 [J]. 应用生态学报, 2023, 34(8): 2267-2273.
[8]	夏卓异, 苏杰, 尹海伟, 孔繁花. 气候变化背景下中国朱鹮适宜生境时空格局 [J]. 应用生态学报, 2023, 34(6): 1467-1473.
[9]	张达, 曾坚, 艾合麦提·那麦提. 高强度开发地区鸟类自然保护地保护空缺识别——以天津市为例 [J]. 应用生态学报, 2023, 34(6): 1621-1629.
[10]	刘伟, 李旭琴, 李忠伦, 李英, 油志远, 蒋勇, 阮光华, 鲁碧耕, 杨楠. 四川贡嘎山中华斑羚和中华鬣羚的时空分布及重叠性 [J]. 应用生态学报, 2023, 34(6): 1630-1638.
[11]	邵明勤, 王剑颖, 丁红秀. 中国白鹤越冬适宜生境模拟及种群扩张驱动因素 [J]. 应用生态学报, 2023, 34(6): 1639-1648.
[12]	张辉盛, 徐琳, 吕韦韦, 周昱, 王卫锋, 高瑞贺, 崔绍朋, 张志伟. 扶桑绵粉蚧多维气候生态位保守性与入侵风险 [J]. 应用生态学报, 2023, 34(6): 1649-1658.
[13]	王子文, 尹进, 王星, 陈越, 毛子昆, 蔺菲, 巩宗强, 王绪高. 辽宁省入侵植物曼陀罗的生境适宜性评价——基于Biomod2组合模型 [J]. 应用生态学报, 2023, 34(5): 1272-1280.
[14]	李春波, 张园, 刘雅各, 吴家兵, 王安志. 长白山自然保护区总初级生产力时空变化特征及其影响因素 [J]. 应用生态学报, 2023, 34(5): 1341-1348.
[15]	白金珂, 李笑雨, 王力. 1980s与2020s青藏高原南部土壤质量变化 [J]. 应用生态学报, 2023, 34(5): 1367-1374.