长江流域安徽段生态系统服务价值与景观生态风险时空演变及其关联分析

贾艳艳, 唐晓岚, 任宇杰

南京林业大学学报(自然科学版) ›› 2022, Vol. 46 ›› Issue (3) : 31-40.

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南京林业大学学报(自然科学版) ›› 2022, Vol. 46 ›› Issue (3) : 31-40. DOI: 10.12302/j.issn.1000-2006.202108033
专题报道:长江大保护视域下的长江中游自然保护地及景观生态研究(执行主编 王浩)

长江流域安徽段生态系统服务价值与景观生态风险时空演变及其关联分析

作者信息 +

Spatial-temporal evolution and correlation analyses of ecosystem service values and landscape ecological risks in Anhui section of the Yangtze River basin

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文章历史 +

摘要

【目的】综合运用生态系统服务价值和景观生态风险评估,更好地为长江流域安徽段可持续发展提供决策支持,也为跨江区域生态环境管护提供一定参考。【方法】基于1995年、2005年和2015年安徽省土地利用数据,采用生态系统服务价值评估、景观生态风险评估和双变量空间自相关模型等方法,分析长江流域安徽段生态服务价值、生态风险时空变化及其关联特征。【结果】①1995—2015年研究区总生态系统服务价值呈减少趋势,减少率为0.54%;研究区以较高和中等生态服务价值等级为主,主要分布在长江沿岸、大别山区及皖南山区。②近20年长江流域安徽段生态风险整体呈升高趋势,以中、较低和低生态风险等级为主;空间上,较高和高风险区主要分布在长江沿岸及巢湖区域,并由集聚分布趋于连片扩张。③长江流域安徽段单位面积生态系统服务价值与生态风险之间存在空间正相关性,主要关系为高价值-高风险相关,即生态服务价值高的区域也是生态环境比较脆弱的区域,应特别关注。【结论】必须重视对湿地和林草景观的保护,加强以长江沿岸、巢湖区域为主的湿地生态保护和对大别山、皖南山区自然山体林草景观的保护与修复,将对提高长江流域安徽段生态系统服务功能和保护长江生态环境起着重要作用。

Abstract

【Objective】The comprehensive application of ecosystem service values and landscape ecological risk assessments can provide better decision support for the sustainable development of the Anhui section of the Yangtze River basin. Moreover, it can provide a reference for ecological environment management and protection in the trans-river region. 【Method】Based on land use data from Anhui Province in 1995, 2005 and 2015, ecosystem service value assessment, landscape ecological risk assessment and bivariate spatial autocorrelation were used to analyze spatiotemporal changes in ecological service values and ecological risks and their correlation characteristics in the Anhui section. 【Result】(1) From 1995 to 2015, the total ecosystem service values in the study area showed a decreasing trend, with a decreasing rate of 0.54%. The study area was dominated by medium-high and medium levels of ecological service values, which were mainly distributed along the Yangtze River, Dabie Mountain area, and southern Anhui Mountain area. (2) Over the past 20 years, the ecological risk of the Anhui section showed an overall increasing trend, and the ecological risk level was mainly medium, medium-low and low. In terms of spatial distribution, the medium-high and high-risk areas were mainly distributed along the Yangtze River and Chaohu Lake region and tended to expand from a concentrated distribution to a continuous distribution. (3) There was a positive spatial correlation between ecosystem service value per unit area and ecological risk in Anhui Province, and the main relationship was a high value-high risk correlation. In other words, the regions with high ecological service value were also those with relatively fragile ecological environments, which should receive special attention. 【Conclusion】It is necessary to focus on the protection of wetlands and forest and grass landscapes, strengthen the ecological protection of wetlands along the Yangtze River and Chaohu Lake, and protect and restore the natural forest and grass landscape in Dabie Mountain and the southern Anhui mountains. This approach would help improve the ecosystem service function of the Anhui section and protect the ecological environment of the Yangtze River.

关键词

生态系统服务价值 / 生态风险 / 时空关联 / 长江流域安徽段

Key words

ecosystem service value(ESV) / ecological risk / spatio-temporal correlation / Anhui section of the Yangtze River basin

引用本文

导出引用
贾艳艳, 唐晓岚, 任宇杰. 长江流域安徽段生态系统服务价值与景观生态风险时空演变及其关联分析[J]. 南京林业大学学报(自然科学版). 2022, 46(3): 31-40 https://doi.org/10.12302/j.issn.1000-2006.202108033
JIA Yanyan, TANG Xiaolan, REN Yujie. Spatial-temporal evolution and correlation analyses of ecosystem service values and landscape ecological risks in Anhui section of the Yangtze River basin[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2022, 46(3): 31-40 https://doi.org/10.12302/j.issn.1000-2006.202108033
中图分类号: X171;S759.9   

参考文献

[1]
OUYANG Z Y, ZHENG H, XIAO Y, et al. Improvements in ecosystem services from investments in natural capital[J]. Science, 2016, 352(6292):1455-1459.DOI: 10.1126/science.aaf2295.
[2]
陈利顶, 景永才, 孙然好. 城市生态安全格局构建:目标、原则和基本框架[J]. 生态学报, 2018, 38(12):4101-4108.
CHEN L D, JING Y C, SUN R H. Urban eco-security pattern construction:targets,principles and basic framework[J]. Acta Ecol Sin, 2018, 38(12):4101-4108.DOI: 10.5846/stxb201802270395.
[3]
李辉, 周启刚, 李斌, 等. 近30年三峡库区生态系统服务价值与生态风险时空变化及相关性研究[J]. 长江流域资源与环境, 2021, 30(3):654-666.
LI H, ZHOU Q G, LI B, et al. Spatiotemporal change and correlation analysis of ecosystem service values and ecological risk in Three Gorges reservoir area in the past 30 years[J]. Resour Environ Yangtze Basin, 2021, 30(3):654-666.DOI: 10.11870/cjlyzyyhj202103013.
[4]
COSTANZA R, D’ARGE R, DE GROOT R, et al. The value of the world’s ecosystem services and natural capital[J]. Ecol Econ, 1998, 25(1):3-15.DOI: 10.1016/S0921-8009(98)00020-2.
[5]
LAUTENBACH S, KUGEL C, LAUSCH A, et al. Analysis of historic changes in regional ecosystem service provisioning using land use data[J]. Ecol Indic, 2011, 11(2):676-687.DOI: 10.1016/j.ecolind.2010.09.007.
[6]
COSTANZA R, DE GROOT R, SUTTON P, et al. Changes in the global value of ecosystem services[J]. Glob Environ Change, 2014, 26:152-158.DOI: 10.1016/j.gloenvcha.2014.04.002.
[7]
SHAH S M, LIU G Y, YANG Q, et al. Emergy-based valuation of agriculture ecosystem services and dis-services[J]. J Clean Prod, 2019, 239:118019.DOI: 10.1016/j.jclepro.2019.118019.
[8]
于德永, 郝蕊芳. 生态系统服务研究进展与展望[J]. 地球科学进展, 2020, 35(8):804-815.
YU D Y, HAO R F. Research progress and prospect of ecosystem services[J]. Adv Earth Sci, 2020, 35(8):804-815.DOI: 10.11867/j.issn.1001-8166. 2020.069.
[9]
李青圃, 张正栋, 万露文, 等. 基于景观生态风险评价的宁江流域景观格局优化[J]. 地理学报, 2019, 74(7):1420-1437.
摘要
流域景观生态风险受到多源因素的综合作用,识别流域景观生态风险是实现景观格局优化的基础与前提,景观格局优化是应对生态风险的有效手段。以宁江流域为研究区,采用空间主成分分析法,从“自然—人类社会—景观格局”3个维度对流域景观生态风险进行综合评价,基于景观生态风险评价结果,构建累积阻力表面,利用最小累积阻力模型进行了流域景观格局的优化。结果表明:人类社会和景观格局因素对综合风险影响更为强烈,地形和距水体距离等自然因素对综合生态风险影响较弱;宁江流域整体景观生态风险偏大,较高景观生态风险区域位于流域西南部,面积为523.99 km <sup>2</sup>,占流域面积的36.06%;识别出流域生态源地为面积大于50 km <sup>2</sup>的林地和面积大于0.2 km <sup>2</sup>的水体。研究构建了15条生态廊道,一级生态廊道长度大于30000 m,二级生态廊道介于10000~30000 m之间,三级生态廊道长度在10000 m以内;识别了19个生态节点,形成了多层次生态网络。通过对比研究区景观格局优化前后的连通度发现,优化后流域整体景观格局连通度得到明显提升。
LI Q P, ZHANG Z D, WAN L W, et al. Landscape pattern optimization in Ningjiang River basin based on landscape ecological risk assessment[J]. Acta Geogr Sin, 2019, 74(7):1420-1437.DOI: 10.11821/dlxb201907011.
[10]
XING L, HU M S, WANG Y. Integrating ecosystem services value and uncertainty into regional ecological risk assessment:a case study of Hubei Province,central China[J]. Sci Total Environ, 2020, 740:140126.DOI: 10.1016/j.scitotenv.2020.140126.
[11]
李俊翰, 高明秀. 滨州市生态系统服务价值与生态风险时空演变及其关联性[J]. 生态学报, 2019, 39(21):7815-7828.
LI J H, GAO M X. Spatiotemporal evolution and correlation analysis of ecosystem service values and ecological risk in Binzhou[J]. Acta Ecol Sin, 2019, 39(21):7815-7828.DOI: 10.5846/stxb201809061899.
[12]
欧阳晓, 朱翔, 贺清云. 基于生态系统服务和生态系统健康的生态风险评价:以长株潭城市群为例[J]. 生态学报, 2020, 40(16):5478-5489.
OUYANG X, ZHU X, HE Q Y. Incorporating ecosystem services with ecosystem health for ecological risk assessment:case study in Changsha-Zhuzhou-Xiangtan urban agglomeration,China[J]. Acta Ecol Sin, 2020, 40(16):5478-5489.DOI: 10.5846/stxb201907071428.
[13]
陈峰, 李红波, 张安录. 基于生态系统服务的中国陆地生态风险评价[J]. 地理学报, 2019, 74(3):432-445.
摘要
传统的生态风险评价主要依据是点源性威胁、区域景观格局变化等生态实体特征指标,忽略了与实体功能属性密切相关的人类福祉因素。将生态系统服务纳入生态风险评价体系是一个新的研究思路。本文运用GIS和遥感技术重构了中国陆地生态系统服务的空间图谱,采用生态风险分析模型给出了基于生态系统服务的中国陆地生态风险格局的定量描述和空间分布,划定了不同置信水平下的生态风险管控优先区。结果表明:① 2000-2010年中国陆地生态系统年均总生态系统服务指数取值在0~2.17之间,年际间呈现小幅波动趋势,年平均总指数在0.30~0.57之间变化,其中24.7%的区域显著增加,主要分布在台湾、云贵高原及新疆西北内陆区,37.1%的区域显著减少,主要分布在东北、青藏高原及中东部地区;② 不同置信水平下的中国陆地生态系统服务存在的风险损失不尽相同。如当置信水平为90%时,总生态系统服务指数的可能损失比例为24.19%,生态风险指数为0.253。比较置信水平和生态风险指数间的关系,发现当置信水平较高时,生态系统服务蒙受风险的概率相应降低,但此时出现风险时所承受的损失也对应增加;③ 以90%置信水平为例,中国生态地理区划的风险特征表现为:平均生态系统服务风险指数居前列的六位依次为内蒙古高原生态区、华北平原生态区、黄土高原生态区、东北平原生态区、横断山生态区、青藏高原生态区,极重度风险所占区域面积比例依次为55.89%、26.63%、24.35%、20.62%、18.70%、25.12%。
CHEN F, LI H B, ZHANG A L. Ecological risk assessment based on terrestrial ecosystem services in China[J]. Acta Geogr Sin, 2019, 74(3):432-445.DOI: 10.11821/dlxb201903003.
[14]
付梦娣, 唐文家, 刘伟玮, 等. 基于生态系统服务视角的生态风险评估及生态修复空间辨识:以长江源区为例[J]. 生态学报, 2021, 41(10):3846-3855.
FU M D, TANG W J, LIU W W, et al. Ecological risk assessment and spatial identification of ecological restoration from the ecosystem service perspective:a case study in source region of Yangtze River[J]. Acta Ecol Sin, 2021, 41(10):3846-3855.DOI: 10.5846/stxb202004200948.
[15]
宫继萍, 石培基, 杨雪梅. 黑河中游土地生态价值及生态风险动态研究:以甘肃省民乐县为例[J]. 土壤, 2012, 44(5):846-852.
GONG J P, SHI P J, YANG X M. Changes of land ecosystem value and ecological risk in middle reaches of Heihe River:a case study in Minle County of Gansu Province[J]. Soils, 2012, 44(5):846-852.DOI: 10.13758/j.cnki.tr.2012.05.009.
[16]
JIA Y Y, TANG X L, LIU W. Spatial-temporal evolution and correlation analysis of ecosystem service value and landscape ecological risk in Wuhu City[J]. Sustainability, 2020, 12(7):2803.DOI: 10.3390/su12072803.
[17]
黄晓梅, 程先富. 安徽省沿江地区暴雨洪涝灾害危险性评估[J]. 安徽师范大学学报(自然科学版), 2019, 42(2):151-158.
HUANG X M, CHENG X F. Evaluation about the flood hazard mainly caused by rainstorms in the area along the Yangtze River in Anhui Province[J]. J Anhui Norm Univ (Nat Sci),2019, 42(2):151-158.DOI: 10.14182/J.cnki.1001-2443.2019.02.009.
[18]
欧阳志云, 朱春全. 长江流域生物多样性格局与保护图集[M]. 北京: 科学出版社, 2011.
[19]
刘纪远, 宁佳, 匡文慧, 等. 2010-2015年中国土地利用变化的时空格局与新特征[J]. 地理学报, 2018, 73(5):789-802.
摘要
土地利用/覆被变化是人类活动对地球表层及全球变化影响研究的重要内容。本文基于Landsat 8 OLI、GF-2等遥感图像和人机交互解译方法,获取的土地利用数据实现了中国2010-2015年土地利用变化遥感动态监测。应用土地利用动态度、年变化率等指标,从全国和分区角度揭示了2010-2015年中国土地利用变化的时空特征。结果表明:2010-2015年中国建设用地面积共增加24.6×10<sup>3</sup> km<sup>2</sup>,耕地面积共减少4.9×10<sup>3</sup> km<sup>2</sup>,林草用地面积共减少16.4×10<sup>3</sup> km<sup>2</sup>。2010-2015年与2000-2010年相比,中国土地利用变化的区域空间格局基本一致,但分区变化呈现新的特征。东部建设用地持续扩张和耕地面积减少,变化速率有所下降;中部建设用地扩张和耕地面积减少速度增加;西部建设用地扩张明显加速,耕地面积增速进一步加快,林草面积减少速率增加;东北地区建设用地扩展持续缓慢,耕地面积稳中有升,水旱田转换突出,林草面积略有下降。从“十二五”期间国家实施的主体功能区布局来看,东部地区的土地利用变化特征与优化和重点开发区的国土空间格局管控要求基本吻合;中部和西部地区则面临对重点生态功能区和农产品主产区相关土地利用类型实现有效保护的严峻挑战,必须进一步加大对国土空间开发格局的有效管控。
LIU J Y, NING J, KUANG W H, et al. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015[J]. Acta Geogr Sin, 2018, 73(5):789-802.DOI: 10.11821/dlxb201805001.
[20]
谢高地, 张彩霞, 张雷明, 等. 基于单位面积价值当量因子的生态系统服务价值化方法改进[J]. 自然资源学报, 2015, 30(8):1243-1254.
XIE G D, ZHANG C X, ZHANG L M, et al. Improvement of the evaluation method for ecosystem service value based on per unit area[J]. J Nat Resour, 2015, 30(8):1243-1254.DOI: 10.11849/zrzyxb.2015.08.001.
[21]
CHEN W X, ZHAO H B, LI J F, et al. Land use transitions and the associated impacts on ecosystem services in the middle reaches of the Yangtze River Economic Belt in China based on the geo-informatic Tupu method[J]. Sci Total Environ, 2020, 701:134690.DOI: 10.1016/j.scitotenv.2019.134690.
[22]
贾艳艳, 唐晓岚, 刘振威, 等. 长江沿岸芜湖区段景观生态风险时空演变分析[J]. 中南林业科技大学学报, 2019, 39(11):78-87.
JIA Y Y, TANG X L, LIU Z W, et al. Analysis on spatiotemporal evolution of landscape ecological risk in Wuhu section along the Yangtze River[J]. J Central South Univ For Technol, 2019, 39(11):78-87.DOI: 10.14067/j.cnki.1673-923x.2019.11.012.
[23]
唐晓岚, 包文渊, 贾艳艳, 等. 太湖风景区古村古镇景观生态风险分析[J]. 南京林业大学学报(自然科学版), 2018, 42(2):105-112.
TANG X L, BAO W Y, JIA Y Y, et al. Study on ancient village and town landscape ecological risk in Taihu scenic area[J]. J Nanjing For Univ (Nat Sci Ed), 2018, 42(2):105-112.DOI: 10.3969/j.issn.1000-2006.201702034.
[24]
LIU Y C, LIU Y X, LI J L, et al. Evolution of landscape ecological risk at the optimal scale:a case study of the open coastal wetlands in Jiangsu,China[J]. Int J Environ Res Public Heal, 2018, 15(8):1691.DOI: 10.3390/ijerph15081691.
[25]
黄木易, 何翔. 近20年来巢湖流域景观生态风险评估与时空演化机制[J]. 湖泊科学, 2016, 28(4):785-793.
HUANG M Y, HE X. Landscape ecological risk assessment and its mechanism in Chaohu basin during the past almost 20 years[J]. J Lake Sci, 2016, 28(4):785-793.DOI: 10.18307/2016.0411.
[26]
奚世军, 安裕伦, 李阳兵, 等. 基于景观格局的喀斯特山区流域生态风险评估:以贵州省乌江流域为例[J]. 长江流域资源与环境, 2019, 28(3):712-721.
XI S J, AN Y L, LI Y B, et al. Ecological risk assessment of Karst mountain watershed based on landscape pattern: a case study of Wujiang River basin in Guizhou Province[J]. Resour Environ Yangtze Basin, 2019, 28(3):712-721.DOI: 10.11870/cjlyzyyhj201903022.
[27]
ANSELIN L. Local indicators of spatial association: LISA[J]. Geogr Anal, 1995, 27(2):93-115.DOI: 10.1111/j.1538-4632.1995.tb00338.x.
[28]
ORD J K, GETIS A. Local spatial autocorrelation statistics:distributional issues and an application[J]. Geogr Anal, 1995, 27(4):286-306.DOI: 10.1111/j.1538-4632.1995.tb00912.x.
[29]
WARTENBERG D. Multivariate spatial correlation:a method for exploratory geographical analysis[J]. Geogr Anal, 1985, 17(4):263-283.DOI: 10.1111/j.1538-4632.1985.tb00849.x.

基金

国家自然科学基金项目(31270746)
山东省自然科学基金项目(ZR2021QD124)

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