Spatiotemporal evolution and multi-scenario prediction of habitat quality in the Yellow River Basin

被引:4
作者
Chen, Yanglong [1 ,2 ,3 ,4 ]
He, Zhilin [1 ,2 ,3 ,4 ]
Yue, Tianming [1 ,2 ,3 ,4 ]
Mu, Weichen [1 ,2 ,3 ,4 ]
Qin, Fen [1 ,2 ,3 ,4 ]
机构
[1] Henan Univ, Coll Geog & Environm Sci, Kaifeng, Peoples R China
[2] Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng, Peoples R China
[3] Henan Univ, Henan Ind Technol Acad Spatio Temporal Big Data, Kaifeng, Peoples R China
[4] Henan Univ, Henan Technol Innovat Ctr Spatial Temporal Big Dat, Kaifeng, Peoples R China
来源
FRONTIERS IN ECOLOGY AND EVOLUTION | 2023年 / 11卷
关键词
PLUS model; InVEST model; Yellow River Basin; habitat quality; multi-scenario prediction; ecological conservation and high-quality development; LAND-USE SIMULATION; ECOSYSTEM-SERVICE; MODEL; DYNAMICS; AREA; FLUS;
D O I
10.3389/fevo.2023.1226676
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
IntroductionThe Yellow River Basin (YRB) is not only a vital area for maintaining ecological security but also a key area for China's economic and social development. Understanding its land-use change trends and habitat quality change patterns is essential for regional ecological conservation and effective resource allocation.MethodsThis study used the patch-generating land-use simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models to analyze and predict the spatial and temporal trends of habitat quality in the YRB from 2000 to 2030 under natural development (ND) and ecological conservation and high-quality development (ECD) scenarios. The PLUS model was used to predict land-use change in 2030 under different scenarios, after which the InVEST model was used to obtain the habitat quality distribution characteristics from the 2000-2030 period.Results(1) The mean values of habitat quality in the YRB in 2000, 2010, and 2020 were 0.6849, 0.6992, and 0.7001, respectively. The mean habitat quality values were moderately high. Spatial distribution characteristics were high in the west and low in the east and along the water. In 2030, habitat quality (0.6993) started to decline under ND, whereas under ECD, there was an indication of substantial improvement in habitat quality (0.7186). (2) The mean habitat degradation values in 2000, 2010, and 2020 were 0.0223, 0.0219, and 0.0231, respectively. The level of habitat degradation showed a decreasing trend, followed by an increasing trend with a stable spatial distribution pattern. The mean level of habitat degradation in 2030 (0.0241) continued to increase under ND, while a substantial decrease in the level of habitat degradation occurred under ECD (0.0214), suggesting that the level of habitat degradation could be effectively contained under the ECD scenario. (3) During the study period, the conversion of building land-both negative and positive-had the most pronounced impact on habitat quality per unit area. Further, the conversion of grassland was shown to be a key land transformation that may either lead to the deterioration or improvement of the ecological environment. The results provide scientifific theoretical support and a decision basis for ecological conservation and the high-quality development of the YRB.
引用
收藏
页数:17
相关论文
共 45 条
  • [1] The Multiscale Integrated Model of Ecosystem Services (MIMES): Simulating the interactions of coupled human and natural systems
    Boumans, Roelof
    Roman, Joe
    Altman, Irit
    Kaufman, Les
    [J]. ECOSYSTEM SERVICES, 2015, 12 : 30 - 41
  • [2] The extrapolation of social landscape values to a national level in New Zealand using landscape character classification
    Brown, Greg
    Brabyn, Lars
    [J]. APPLIED GEOGRAPHY, 2012, 35 (1-2) : 84 - 94
  • [3] Effects of Increasing Urbanization on the Ecological Integrity of Open Space Preserves
    Esbah, Hayriye
    Cook, Edward A.
    Ewan, Joseph
    [J]. ENVIRONMENTAL MANAGEMENT, 2009, 43 (05) : 846 - 862
  • [4] Stream Physical Characteristics Impact Habitat Quality for Pacific Salmon in Two Temperate Coastal Watersheds
    Fellman, Jason B.
    Hood, Eran
    Dryer, William
    Pyare, Sanjay
    [J]. PLOS ONE, 2015, 10 (07):
  • [5] 基于FLUS和InVEST模型的南京市生境质量多情景预测
    高周冰
    王晓瑞
    隋雪艳
    汪翔
    范业婷
    朱青
    吕立刚
    [J]. 农业资源与环境学报, 2022, 39 (05) : 1001 - 1013
  • [6] Integrating ecosystem-service tradeoffs into land-use decisions
    Goldstein, Joshua H.
    Caldarone, Giorgio
    Duarte, Thomas Kaeo
    Ennaanay, Driss
    Hannahs, Neil
    Mendoza, Guillermo
    Polasky, Stephen
    Wolny, Stacie
    Daily, Gretchen C.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 109 (19) : 7565 - 7570
  • [7] Hall LS, 1997, WILDLIFE SOC B, V25, P173
  • [8] Swamp rabbits as indicators of wildlife habitat quality in bottomland hardwood forest ecosystems
    Hillard, Elizabeth M.
    Nielsen, Clayton K.
    Groninger, John W.
    [J]. ECOLOGICAL INDICATORS, 2017, 79 : 47 - 53
  • [9] Multi-Scenario Simulations of Land Use and Habitat Quality Based on a PLUS-InVEST Model: A Case Study of Baoding, China
    Hu, Nan
    Xu, Dong
    Zou, Ning
    Fan, Shuxin
    Wang, Peiyan
    Li, Yunyuan
    [J]. SUSTAINABILITY, 2023, 15 (01)
  • [10] Ecological response to urban development in a changing socio-economic and climate context: Policy implications for balancing regional development and habitat conservation
    Huang, Junlong
    Tang, Zhuo
    Liu, Dianfeng
    He, Jianhua
    [J]. LAND USE POLICY, 2020, 97