Temporal and Spatial Characteristics of Land Ecological Vulnerability in Songnen Plain, Heilongjiang Province
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摘要:目的 松嫩平原作为东北典型黑土地的集中分布区,面临着水土流失、土壤肥力下降等问题。综合评价松嫩平原的土地生态脆弱性,为该区域的土地资源利用和黑土地保障粮食安全提供依据。方法 采用“生态敏感性-生态恢复力-生态压力度”模型(S-R-P模型)和GIS技术,结合层次分析法和综合指数法,构建黑龙江省松嫩平原土地生态脆弱性评价指标体系,对2005、2010、2015、2020年研究区土地生态脆弱性进行评价,分析其各时期等级转化和时空分布特征。结果 黑龙江省内的松嫩平原土地处于轻度脆弱状态,土地生态脆弱性综合指数波动下降。2005 ~ 2020年,微度和轻度脆弱区面积分别增加3.37%和5.16%;中度、重度和极度脆弱区共减少8.53%。轻度脆弱区和微度脆弱区占比最大,主要分布在研究区的东北部和中部,共占80.96%;中度、重度和极度脆弱区主要分布于研究区中西部和南部,总占19.03%;土地生态脆弱性等级保持不变、上升和下降的区域分别占总面积的76.09%、5.52%和18.04%。结论 研究区土地生态脆弱性整体处于轻度脆弱状态且有改善的趋势,但其空间差异明显,需继续提高生态防护措施,加强对黑土地的保护和粮食安全的保障。Abstract:Objective Songnen Plain, as the concentrated distribution area of typical black land in northeast China, is faced with the problems of soil erosion and soil fertility decline. Comprehensive evaluation of land ecological vulnerability in Songnen Plain can provide a basis for land resource utilization and food security in this region.Method The evaluation index system of land ecological vulnerability in Songnen Plain of Heilongjiang Province was constructed by using Sensitivity-ecological, Resilience-ecological Pressure model (S-R-P model) and GIS technology, combined with Analytic Hierarchy Process (AHP) and comprehensive index method. The land ecological vulnerability in the study area was evaluated in 2005, 2010, 2015 and 2020. It also classified the calculated land ecological vulnerability index to express their spatial and temporal distribution and its hierarchical transformation characteristics.Result The study showed that the overall land ecological vulnerability in Songnen Plain was presented in a slightly vulnerability state and the comprehensive index of land ecological vulnerability fluctuated. From 2005 to 2020, the areas of micro and slightly vulnerable area increased by 3.37% and 5.16%, respectively. Moderate, severe and extremely vulnerable areas decreased by 7.04%, 1.46% and 0.03%, respectively. The proportion of micro vulnerable and slightly vulnerable area was the largest, accounting for 80.97%, mainly distributed in the northeast and central part of Songnen Plain. Moderate, severe and extremely vulnerable area were mainly distributed in the midwest and south of Songnen Plain, accounting for 19.03% in total. The areas of land ecological vulnerability remained unchanged, but the increased and decreased areas accounted for 5.52% and 18.04% of the total area.Conclusion The overall land ecological vulnerability in the study area is in a slightly vulnerability state, but the spatial difference is obvious. So the ecological protection measures should be continuously improved to strengthen the protection of black land and the guarantee of food security. This study can provide reference for local zoning management and sustainable development.
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Keywords:
- Evaluation of land ecological vulnerability /
- S-R-P model /
- GIS /
- Songnen Plain
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表 1 松嫩平原土地生态脆弱性评价指标及权重
Table 1 Assessment index and weight of land ecological vulnerability index in Songnen Plain
目标层
Target layer准则层
Criterion layer要素层
Factor layer指标层
Index layer指标性质
Index property权重
Weight土地生态脆弱性评价 生态敏感性 地形因子 坡度 + 0.0195 坡向 + 0.0131 高程 − 0.0131 地形起伏度 + 0.0195 地表因子 植被覆盖度 − 0.1298 景观破碎度 + 0.1298 气象因子 年降水量 − 0.0112 年均气温 − 0.0112 年均相对湿度 − 0.0112 土壤因子 土壤侵蚀强度 + 0.0963 生态恢复力 活力 生物丰富度 − 0.1351 功能 居民点干扰 + 0.0624 生态压力度 人口压力因子 人口密度 + 0.1099 社会压力因子 GDP密度 + 0.1099 固定资产投资 + 0.0417 生产压力因子 农药化肥投入 + 0.0861 表 2 土地生态脆弱性分级标准
Table 2 Classification criteria for land ecological vulnerability
脆弱性程度
Degree of vulnerability指数标准化值
Exponential normalized value分级特征
Characteristics of level微度脆弱区 < 0.21 土地生态系统结构和功能完善,所承受生态压力小,土地生态系统稳定,抗干扰和自我恢复能力强 轻度脆弱区 0.21 ~ 0.29 土地生态系统结构和功能较为完善,所承受生态压力较小,土地生态系统较为稳定,抗干扰和自我恢复能力较强 中度脆弱区 0.29 ~ 0.37 土地生态系统结构和功能尚可维持,所承受生态压力接近生态阈值,土地生态系统不稳定,对外界干扰较为敏感,自我恢复能力较弱 重度脆弱区 0.37 ~ 0.50 土地生态系统结构和功能出现缺陷,所承受生态压力大,生态系统不稳定,对外界干扰敏感性强,受损后恢复难度大 极度脆弱区 > 0.50 土地生态系统结构和功能严重退化,所承受生态压力极大,生态系统极不稳定,对外界干扰极度敏感,受损后恢复难度极大 表 3 研究区2005 ~ 2020年各个时期土地生态脆弱性面积占比及变化
Table 3 The area proportion and change of land ecological vulnerability in each period from 2005 to 2020
年份
Year类型
Type微度脆弱区
Micro vulnerable area轻度脆弱区
Slightly vulnerable area中度脆弱区
Moderate vulnerable area重度脆弱区
Severe vulnerable area极度脆弱区
Extremely vulnerable area2005 面积(km2) 42831.74 80051.41 30051.16 4192.19 149.72 占比(%) 27.23 50.90 19.11 2.67 0.10 2010 面积(km2) 42450.04 77810.53 32300.26 4575.54 139.85 占比(%) 26.99 49.47 20.54 2.91 0.09 2015 面积(km2) 44842.28 85077.76 24687.52 2545.26 123.40 占比(%) 28.51 54.09 15.70 1.62 0.08 2020 面积(km2) 48128.57 88173.22 18979.77 1894.36 100.31 占比(%) 30.60 56.06 12.07 1.20 0.06 2005 ~ 2010 面积(km2) −381.71 −2240.88 2249.11 383.35 −9.87 占比(%) −0.24 −1.42 1.43 0.24 −0.01 2010 ~ 2015 面积(km2) 2392.24 7267.23 −7612.74 −2030.28 −16.45 占比(%) 1.52 4.62 −4.84 −1.29 −0.01 2015 ~ 2020 面积(km2) 3286.28 3095.46 −5707.75 −650.90 −23.09 占比(%) 2.09 1.97 −3.63 −0.41 −0.01 2005 ~ 2020 面积(km2) 5296.82 8121.81 −11071.39 −2297.83 −49.41 占比(%) 3.37 5.16 −7.04 −1.46 −0.03 表 4 2005 ~ 2020土地生态脆弱性转移矩阵(km2)
Table 4 Transfer matrix of land ecological vulnerability from 2005 to 2020
年份
Year脆弱性程度
Degree of
vulnerability微度脆弱区
Micro vulnerable
area轻度脆弱区
Slightly vulnerable
area中度脆弱区
Moderate vulnerable
area重度脆弱区
Severe vulnerable
area极度脆弱区
Extremely vulnerable
area2005 ~ 2010 微度脆弱区 41912.03 919.72 0.00 0.00 0.00 轻度脆弱区 538.01 73422.55 6090.85 0.00 0.00 中度脆弱区 0.00 3468.26 25587.50 995.40 0.00 重度脆弱区 0.00 0.00 621.92 3539.01 31.26 极度脆弱区 0.00 0.00 0.00 41.13 108.59 2010 ~ 2015 微度脆弱区 41977.84 472.20 0.00 0.00 0.00 轻度脆弱区 2864.44 73608.47 1335.97 1.65 0.00 中度脆弱区 0.00 10964.19 21155.09 180.98 0.00 重度脆弱区 0.00 32.91 2196.46 2313.27 32.91 极度脆弱区 0.00 0.00 0.00 49.36 90.49 2015 ~ 2020 微度脆弱区 42039.62 2742.83 59.84 0.00 0.00 轻度脆弱区 5980.10 72425.47 6668.75 3.44 0.00 中度脆弱区 108.86 12948.84 11083.46 546.37 0.00 重度脆弱区 0.00 56.08 1164.42 1280.23 44.53 极度脆弱区 0.00 0.00 3.30 64.32 55.78 2005 ~ 2020 微度脆弱区 40292.98 2478.93 59.83 0.00 0.00 轻度脆弱区 7617.87 66807.70 5602.75 23.09 0.00 中度脆弱区 217.71 18169.13 11190.96 473.36 0.00 重度脆弱区 0.00 717.46 2119.64 1313.87 41.23 极度脆弱区 0.00 0.00 6.60 84.05 59.08 -
[1] Adger W N. Vulnerability[J]. Global environmental change, 2006, 16(3): 268 − 281. doi: 10.1016/j.gloenvcha.2006.02.006
[2] 徐广才, 康慕谊, 贺丽娜, 等. 生态脆弱性及其研究进展[J]. 生态学报, 2009, 29(5): 2578 − 2588. doi: 10.3321/j.issn:1000-0933.2009.05.047 [3] 张 帅, 董会忠, 曾文霞. 土地生态系统脆弱性时空演化特征及影响因素−以黄河三角洲高效生态经济区为例[J]. 中国环境科学, 2019, 39(4): 1696 − 1704. doi: 10.3969/j.issn.1000-6923.2019.04.043 [4] 张 龙, 宋 戈, 孟 飞, 等. 宁安市土地生态脆弱性时空变化分析[J]. 水土保持研究, 2014, 21(2): 133 − 137, 143. doi: 10.13869/j.cnki.rswc.2014.02.025 [5] 余文波. 江西省土地生态脆弱性动态评价及其调控对策研究[D]. 南昌: 江西农业大学. 2018. [6] 魏明欢, 胡波洋, 张贵军, 等. 山区县土地生态脆弱性动态变化分析−以青龙满族自治县为例[J]. 水土保持研究, 2018, 25(2): 322 − 327. doi: 10.13869/j.cnki.rswc.2018.02.046 [7] Jabbar M T, Zhou X. Eco-environmental change detection by using remote sensing and GIS techniques: a case study Basrah province, south part of Iraq[J]. Environmental Earth ences, 2011, 64(5): 1397 − 1407. doi: 10.1007/s12665-011-0964-5
[8] 王瑞君, 王仁德, 高士平, 等. 基于GIS的河北省土地沙化脆弱性评价与空间分异[J]. 江苏农业科学, 2016, 44(2): 395 − 398. doi: 10.15889/j.issn.1002-1302.2016.02.115 [9] 王春雨. 云南省土地系统脆弱性评价及时空分异研究[D]. 昆明: 云南财经大学, 2021. [10] 吴春生, 黄 翀, 刘高焕, 等. 基于模糊层次分析法的黄河三角洲生态脆弱性评价[J]. 生态学报, 2018, 38(13): 4584 − 4595. [11] Zou T, Yoshino K. Environmental vulnerability evaluation using a spatial principal components approach in the Daxing’anling region, China[J]. Ecological Indicators, 2017, 78: 405 − 415. doi: 10.1016/j.ecolind.2017.03.039
[12] 张慧琳, 吴攀升, 侯艳军. 五台山地区生态脆弱性评价及其时空变化[J]. 生态与农村环境学报, 2020, 36(8): 1026 − 1035. [13] 裴 欢, 王晓妍, 房世峰. 基于DEA的中国农业旱灾脆弱性评价及时空演变分析[J]. 灾害学, 2015, 30(2): 64 − 69. doi: 10.3969/j.issn.1000-811X.2015.02.012 [14] Džeroski S. Applications of symbolic machine learning to ecological modelling[J]. Ecological modelling, 2001, 146(1-3): 263 − 273. doi: 10.1016/S0304-3800(01)00312-X
[15] Hou K, Tao W, Wang L, et al. Study on hierarchical transformation mechanisms of regional ecological vulnerability and its applicability[J]. Ecological Indicators, 2020, 114: 106343. doi: 10.1016/j.ecolind.2020.106343
[16] Bawa K S, Joseph G, Setty S. Poverty, biodiversity and institutions in forest-agriculture ecotones in the Western Ghats and Eastern Himalaya ranges of India[J]. Agriculture, ecosystems & environment, 2007, 121(3): 287 − 295.
[17] Mörtberg U M, Balfors B, Knol W C. Landscape ecological assessment: A tool for integrating biodiversity issues in strategic environmental assessment and planning[J]. Journal of environmental management, 2007, 82(4): 457 − 470. doi: 10.1016/j.jenvman.2006.01.005
[18] Zhang X C, Ma C, Zhan S F, et al. Evaluation and simulation for ecological risk based on emergy analysis and Pressure-State-Response Model in a coastal city, China[J]. Procedia Environmental Sciences, 2012, 13: 221 − 231. doi: 10.1016/j.proenv.2012.01.021
[19] 周梦云, 蔡永立, 张瑞峰, 等. 宁夏贺兰山国家级自然保护区建立前后区域生态脆弱性时空格局变化研究[J]. 生态科学, 2019, 38(5): 78 − 85. doi: 10.14108/j.cnki.1008-8873.2019.05.011 [20] 贾晶晶, 赵 军, 王建邦, 等. 基于SRP模型的石羊河流域生态脆弱性评价[J]. 干旱区资源与环境, 2020, 34(1): 34 − 41. [21] Hong W, Jiang R, Yang C, et al. Establishing an ecological vulnerability assessment indicator system for spatial recognition and management of ecologically vulnerable areas in highly urbanized regions: A case study of Shenzhen, China[J]. Ecological indicators, 2016, 69: 540 − 547. doi: 10.1016/j.ecolind.2016.05.028
[22] Zhang X, Wang L, Fu X, et al. Ecological vulnerability assessment based on PSSR in Yellow River Delta[J]. Journal of Cleaner Production, 2017, 167: 1106 − 1111. doi: 10.1016/j.jclepro.2017.04.106
[23] 李芮芝, 胡希军, 杜心宇, 等. 基于SRP模型的南雄丹霞梧桐自然保护区生态脆弱性评价[J]. 西北林学院学报, 2021, 36(5): 152 − 160. doi: 10.3969/j.issn.1001-7461.2021.05.23 [24] 刘佳茹, 赵 军, 沈思民, 等. 基于SRP概念模型的祁连山地区生态脆弱性评价[J]. 干旱区地理, 2020, 43(6): 1573 − 1582. [25] Yang H, Zhai G, Zhang Y. Ecological vulnerability assessment and spatial pattern optimization of resource-based cities: a case study of Huaibei City, China[J]. Human and Ecological Risk Assessment:An International Journal, 2021, 27(3): 606 − 625. doi: 10.1080/10807039.2020.1744426
[26] Yijia Yang, Ge Song. Human disturbance changes based on spatiotemporal heterogeneity of regional ecological vulnerability: A case study of Qiqihaer city, northwestern Songnen Plain, China. Journal of Cleaner Production, 2020, 291: 125262.
[27] 《国家黑土地保护工程实施方案(2021 ~ 2025年)》, 中国, 2021. [28] 鞠正山. 重视黑土资源保护, 强化黑土退化防治[J]. 国土资源情报, 2016, (2): 22 − 25. [29] 廖 炜, 李 璐, 吴宜进, 等. 丹江口库区土地利用变化与生态环境脆弱性评价[J]. 自然资源学报, 2011, 26(11): 1879 − 1889. doi: 10.11849/zrzyxb.2011.11.007 [30] 马玉妍, 马艳敏, 于万辉, 等. 松嫩平原土地利用生态安全评价与预测[J]. 水土保持通报, 2014, 34(2): 262 − 266, 325. doi: 10.13961/j.cnki.stbctb.2014.02.054 [31] 陈 峰, 李红波. 基于GIS和RUSLE的滇南山区土壤侵蚀时空演变: 以云南省元阳县为例[J]. 应用生态学报, 2021, 32(2): 629 − 637. [32] 乌宁巴特, 刘新平, 马相平. 叶尔羌河流域土地生态脆弱性差异评价[J]. 干旱区地理, 2020, 43(3): 849 − 858. [33] 齐姗姗, 巩 杰, 钱彩云, 等. 基于SRP模型的甘肃省白龙江流域生态环境脆弱性评价[J]. 水土保持通报, 2017, 37(1): 224 − 228. [34] 李永化, 范 强, 王 雪, 等. 基于SRP模型的自然灾害多发区生态脆弱性时空分异研究――以辽宁省朝阳县为例[J]. 地理科学, 2015, 35(11): 1452 − 1459. [35] 张 泽, 胡宝清, 丘海红, 等. 基于山江海视角与SRP模型的桂西南−北部湾生态环境脆弱性评价[J]. 地球与环境, 2021, 49(3): 297 − 306. [36] Nguyen A K, Liou Y A, Li M H, et al. Zoning eco-environmental vulnerability for environmental management and protection[J]. Ecological Indicators, 2016, 69: 100 − 117. doi: 10.1016/j.ecolind.2016.03.026
[37] 韩继冲, 郭梦迪, 杨青林, 等. 川西北江河源区生态环境脆弱性评价[J]. 湖北农业科学, 2018, 57(9): 20 − 24. [38] Li A, Wang A, Liang S, et al. Eco-environmental vulnerability evaluation in mountainous region using remote sensing and GIS—A case study in the upper reaches of Minjiang River, China[J]. Ecological Modelling, 2006, 192(1-2): 175 − 187. doi: 10.1016/j.ecolmodel.2005.07.005
[39] 邵秋芳, 彭培好, 黄 洁, 等. 长江上游安宁河流域生态环境脆弱性遥感监测[J]. 国土资源遥感, 2016, 28(2): 175 − 181. [40] Si-Yuan W, Jing-Shi L, Cun-Jian Y. Eco-environmental vulnerability evaluation in the Yellow River Basin, China[J]. Pedosphere, 2008, 18(2): 171 − 182.
[41] 崔宁波, 巴雪真. 黑龙江省耕地生态安全压力与农业经济发展的脱钩分析[J]. 水土保持研究, 2021, 28(5): 308 − 315.