Construction of Evaluation Model for Soil and Water Conservation Function of Vegetation at Community Scale -Taking Jinzhai County, Anhui Province at Northern Foot of Dabie Mountains as an Example
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    Abstract:

    [Objetcive] An evaluation model for the soil and water conservation function of vegetation at community scale was explored in order to provide a reference for soil and water conservation and ecological construction of vegetation in the Dabie Mountains. [Methods] Based on existing research, through the bibliometric method and expert experience method, the primary selection index for soil and water conservation function of vegetation was established, including 30 items characterizing vegetation type, vegetation structure, terrain, and so on. The measured values of the indicators were obtained through field investigation, and the indicators were analyzed and measured by the random forest method and the decision tree method. A multiple stepwise regression relationship between the measured values of the indicators and soil erosion was established to construct an evaluation model for soil and water conservation function of vegetation at community scale. [Results] A global regression model based on a random forest (R2=0.71) was better than the local regression model based on a decision tree (R2=0.69). Based on the global regression model of random forest, an evaluation model which included slope, forest age, shrub coverage, grass coverage, and litter thickness was constructed. The soil conservation functions of vegetation in the study area followed the order of protection forest (0.705)> timber forest> (0.529) economic forest (0.513)> shrub-grass (0.457). [Conclusion] In the evaluation of vegetation soil and water conservation function at community scale, the model constructed by random forest method has strong applicability, operability and is easy to grasp.

    Reference
    [1] 杨勤科.区域水土流失监测与评价[M].河南郑州市:黄河水利出版社,2015.
    [2] 李凤霞,颜亮东,吴素霞,等.江河源地区草地植被变化特征及水土保持功能评价[J].草业科学,2007,24(7):6-11.
    [3] 马金平.植被保持水土效益研究综述[J].山西水土保持科技,2005(1):13-15.
    [4] 余新晓,毕华兴,朱金兆,等.黄土地区森林植被水土保持作用研究[J].植物生态学报,1997,21:433-440.
    [5] 刘纪根,张昕川,李力,等.紫色土坡面植被覆盖度对水土流失影响研究[J].水土保持研究,2015,22(3):16-20.
    [6] 符素华,刘宝元.土壤侵蚀量预报模型研究进展[J].地球科学进展,2002,17(1):78-84.
    [7] 韦红波.区域植被水土保持功能遥感评价研究[D].陕西杨凌:西北农林科技大学,2001.
    [8] 仲艳维.潮白河流域水土保持效益评价及生态补偿制度构建研究[D].北京:北京林业大学,2014.
    [9] 曹文洪,刘国彬,鲁胜力,等.我国水土保持科技近期进展与展望[J].中国水土保持,2013(5):14-18.
    [10] 韦红波,李锐,杨勤科.我国植被水土保持功能研究进展[J].植物生态学报,2002,26(4):489-496.
    [11] 李伯华,罗琴,刘沛林,等.基于Citespace的中国传统村落研究知识图谱分析[J].经济地理,2017,37(9):207-214.
    [12] 赵蓉英,许丽敏.文献计量学发展演进与研究前沿的知识图谱探析[J].中国图书馆学报,2010,36(5):60-68.
    [13] 韦菊玲,陈世清.基于Delphi法的城市森林可持续经营评价指标体系构建研究[J].林业调查规划,2016,41(1):76-82.
    [14] Breiman L. Random forests[J]. Machine Learning, 2001,45(1):5-32.
    [15] Kabacoff R I. R in Action[M]. New York:Manning Publications Company, 2011.81-85.
    [16] 吴迪,黎家作,张春平,等.县域尺度水土流失监测方法的应用及其结果与分析[J].中国水土保持科学,2015,13(4):74-79.
    [17] 黄思,唐晓,徐文帅,等.利用多模式集合和多元线性回归改进北京PM10预报[J].环境科学学报,2015,35(1):56-64.
    [18] 王全喜,孙鹏举,刘学录,等.基于随机森林算法的耕地面积预测及影响因素重要性分析:以甘肃省庆阳市为例[J].水土保持通报,2018,38(5):341-346.
    [19] 王库,史学正,于东升,等.红壤丘陵区LAI与土壤侵蚀分布特征的关系[J].生态环境,2006,15(5):1052-1055.
    [20] 黄进,张晓勉,张金池.开化生态公益林主要森林类型水土保持功能综合评价[J].水土保持研究,2010,17(3):87-91.
    [21] 张锐.重庆市四面山几种人工林的水土保持功能研究[D].北京:北京林业大学,2008.
    [22] 郑学良,陈丽华,李洪洋,等.基于水源涵养功能的辽东防护林体系健康评价[J].中国水土保持科学,2020,18(2):102-110.
    [23] 汪永英,段文标.小兴安岭南坡3种林型林地水源涵养功能评价[J].中国水土保持科学,2011,9(5):31-36.
    [24] 刘启慎.豫北太行山石灰岩区不同植被类型水保功能综述[J].河南林业科技,1995,15(4):9-12.
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张洪达,赵传普,戴玉婷,袁利,杨绮梦頔,吴傲,刘霞.群落尺度植被水土保持功能评价模型的构建——以大别山北麓安徽省金寨县为例[J].水土保持通报英文版,2022,42(1):122-129

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History
  • Received:August 01,2021
  • Revised:October 13,2021
  • Online: March 12,2022