Assessment of river habitat quality in the Three Gorges Reservoir Region

Miao, 陈淼 Chen; Xiaolei, 苏晓磊 Su; Huimin, 黄慧敏 Huang; Ting, 高婷 Gao; Chengqiang, 党成强 Dang; Rong, 董蓉 Dong; Bo, 曾波 Zeng; Jianping, 陶建平 Tao

doi:10.5846/stxb201712212298

Cited by 3 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regional habitat quality refers to the assessment of the level of ecological environment quality in a specific region, which is currently the predominant research focus (Wang et al., 2023). According to that, its research methods can be divided into two categories: prediction of species‐specific habitat changes based on field survey data and species distribution model (Chen et al., 2019), and habitat quality model for habitat assessment. The former approach exhibited high accuracy but required significant time and labor resources, making it suitable only for small‐scale surveys such as sample points or transects, rather than comprehensive evaluations over long‐term time series (Fan, 2022; Tang et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Spatio‐Temporal Variations of Habitat Quality Under 8 SSP‐RCP Scenarios in China

Feng,

Zhai,

Song

et al. 2024

JGR Biogeosciences

View full text Add to dashboard Cite

Habitat quality is a key expression of ecosystem ability and the basis for effective species conservation and regional ecological environment improvement. However, most studies have focused on assessing habitat quality over historical periods, ignoring the influence of coupled future development paths and climate change. The present study addresses this issue by developing a spatial‐temporal variation analysis framework for assessing habitat quality in China, which integrates the Integrated Valuation of Ecosystem Services and Trade‐offs (InVEST) model with eight Earth system coupled scenarios (SSP‐RCP). The results showed that from 2020 to 2100, and under five scenarios (SSP2‐4.5, SSP3‐7.0, SSP4‐6.0, SSP5‐3.4, and SSP5‐8.5), habitat quality was generally stable and high, while under three scenarios (SSP1‐1.9, SSP1‐2.6, and SSP4‐3.4), it decreased. The SSP2‐4.5 scenario was significantly better than the SSP4‐3.4 scenario. In all scenarios, the influences of different development patterns on China's ecologically fragile areas were obvious and serious. In 2030 and 2060, the spatial distribution patterns of habitat degradation and habitat quality had similar characteristics. High habitat degradation values were mostly distributed east of the Heihe‐Tengchong Line, while low values were mainly distributed in the arid zone. The mean habitat degradation ranged between 0.0226 and 0.0302, and the degradation degree was relatively light. The habitat quality index mean was 0.5120–0.5376, indicating that the overall habitat quality was at the medium level. This study provides a potential ecological protection baseline for China based on habitat protection and provides an important reference for China's sustainable development.

show abstract

Section: Introductionmentioning

confidence: 99%

Spatio‐Temporal Variations of Habitat Quality Under 8 SSP‐RCP Scenarios in China

Feng,

Zhai,

Song

et al. 2024

JGR Biogeosciences

View full text Add to dashboard Cite

show abstract

“…The quantitative index method is to obtain the relevant parameters of habitat quality through eld investigation and construct an evaluation index system for comprehensive evaluation 7,8 . Due to the large amount of human and material resources invested in the evaluation process and the lack of universality, it is not suitable for large-scale regional and long-term time series research 9,10 . The model rule uses mathematical models to quantitatively assess habitat quality, which has the advantages of convenience, speed, and low cost 11 .ARti cial Intelligence for Ecosystem Services (ARIES), Social Values for Ecosystem Services (SoIVES), and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) are widely used in related research [12][13][14][15][16] .…”

Section: Introductionmentioning

confidence: 99%

Study of Spatiotemporal Variation and Driving Factors of Habitat Quality in the northern foothills of the Qinling Mountains:A Case Study of Xi'an, China

Ma,

Wang,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

The goal of this study is to analyze spatiotemporal transform in Xi 'an section of the northern foothills of the Qinling Mountains from 1990 to 2020. By visualizing temporal and spatial changes in habitat quality using InVEST model and land use data, and analyzing factors that affecting habitat quality by Geo-detector; showing that the cultivated land, grassland, and water decreased by 16.40%, 74.37%, and 35.39%, respectively, while the area of forest land and construction land increased, among which the construction land increased by 117.70%, the largest increase, and the forest land increased by 8.47% during study periods. The main changes in land use are the conversion of cultivated land into forest land and construction land, and the conversion of grassland into forest land and cultivated land. During 1990–2020, the average habitat quality index showing a slow decreasing from 0.8617 to 0.8585. The spatial distribution of habitat quality index showed a trend of "high in the south, moderate in the north, and low in the northwest". The high habitat quality was mainly concentrated in the southern forest land, the middle habitat quality was mainly distributed in the northern cultivated land, and the low habitat quality was mainly distributed in the northwest construction land. The land use type has great influence on habitat quality, on top of it, the interaction between any two factors are stronger the just one factor. Last, the temporal and spatial variation of habitat quality is influenced by both natural and unnatural factors.

show abstract

“…The quantitative index method is to obtain the relevant parameters of habitat quality through field investigation and construct an evaluation index system for comprehensive evaluation (Wynne and Cote, 2007;Yang et al, 2021a). Due to the large amount of human and material resources invested in the evaluation process and the lack of universality, it is not suitable for large-scale regional and long-term time series research (Chen et al, 2019;Muñoz-Barcia et al, 2019). The model rule uses mathematical models to quantitatively assess habitat quality, which has the advantages of convenience, speed, and low cost (Moreina et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Study of spatiotemporal variation and driving factors of habitat quality in the northern foothills of the Qinling Mountains: a case study of Xi’an, China

Ma,

Wang,

Wang

et al. 2023

Front. Ecol. Evol.

View full text Add to dashboard Cite

As earth surface human activities become more frequent, global ecosystem service functions and especially biodiversity maintenance functions are challenged. This study aimed to analyze spatiotemporal changes in Xi‘an section of the northern foothills of the Qinling Mountains from 1990 to 2020. Temporal and spatial changes in habitat quality in the study area were visualized using InVEST model and land use data, and factors affecting habitat quality were analyzed using Geodetector. The results showed that during the study period, the cultivated land, grassland, and water decreased by 16.40%, 74.37%, and 35.39%, respectively, while the area of forest land and construction land increased, among which the construction land increased by 117.70%, the largest increase, and the forest land increased by 8.47%. The main changes in land use are the conversion of cultivated land into forest land and construction land, and the conversion of grassland into forest land and cultivated land. During the period 1990–2020, the average habitat quality index in the study area changed from 0.8617 to 0.8585, showing a slow decreasing trend. The spatial distribution of habitat quality showed a trend of “high in the south, moderate in the north, and low in the northwest”. The high habitat quality was mainly concentrated in the southern forest land, the middle habitat quality was mainly distributed in the northern cultivated land, and the low habitat quality was mainly distributed in the northwest construction land. The land use type has a great influence on habitat quality, and the interaction between any two factors is stronger than that of a single factor. The temporal and spatial variation of habitat quality is influenced by both natural and human factors. This study provides a theoretical basis for ecological protection and nature reserve planning in the Qinling Mountains region.

show abstract

Assessment of river habitat quality in the Three Gorges Reservoir Region

Cited by 3 publications

References 0 publications

Spatio‐Temporal Variations of Habitat Quality Under 8 SSP‐RCP Scenarios in China

Spatio‐Temporal Variations of Habitat Quality Under 8 SSP‐RCP Scenarios in China

Study of Spatiotemporal Variation and Driving Factors of Habitat Quality in the northern foothills of the Qinling Mountains:A Case Study of Xi'an, China

Study of spatiotemporal variation and driving factors of habitat quality in the northern foothills of the Qinling Mountains: a case study of Xi’an, China

Contact Info

Product

Resources

About