Linking ecological degradation risk to identify ecological security patterns in a rapidly urbanizing landscape

Peng, Jian; Pan, Ying; Liu, Yanxu; Zhao, Huijuan; Wang, Yanglin

doi:10.1016/j.habitatint.2017.11.010

Cited by 400 publications

(217 citation statements)

References 71 publications

Supporting

Mentioning

213

Contrasting

Unclassified

Order By: Relevance

“…It is also an inherently abstract concept which tries to summarize the 'goodness' of an ecosystem in terms of its deviation from an ideal reference state [34]. It represents the overall ecological quality based on the spatial distance between habitat and threats caused by human activities, which can be weighed to take account of their impact [7,35]. Some researchers also define habitat quality, as a proxy of biodiversity, the capacity of the ecosystem to offer suitable conditions for the survival, reproduction, and population persistence [36].…”

mentioning

confidence: 99%

The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia

et al. 2020

View full text Add to dashboard Cite

The contribution of biodiversity to the global economy, human survival, and welfare has been increasing significantly, but the anthropogenic pressure as a threat to the pristine habitat has followed. This study aims to identify habitat suitability, analyze the change in habitat quality from 1988 to 2018, and to investigate the correlation between impact factors and habitat quality. The InVEST habitat quality model was used to analyze the spatiotemporal change in habitat quality in individual land-use types in the Winike watershed. Remote sensing data were used to analyze the land use/land cover changes. Nine threat sources, their maximum distance of impact, mode of decay, and sensitivity to threats were also estimated for each land-use cover type. The analysis illustrates that habitat degradation in the watershed was continuously increasing over the last three decades (1988 to 2018). Each threat impact factor and habitat sensitivity have increased for the last 30 years. The most contributing factor of habitat degradation was the 25.41% agricultural expansion in 2018. Population density, land-use intensity, elevation, and slope were significantly correlated with the distribution of habitat quality. Habitat quality degradation in the watershed during the past three decades suggested that the conservation strategies applied in the watershed ecosystem were not effective. Therefore, this study helps decision makers, particularly regarding the lack of data on biodiversity. It further looks into the conflict between economic development and conservation of biodiversity.

show abstract

mentioning

confidence: 99%

The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Although demand quantification is an obvious advantage compared with studies focusing on the identification of spatial pattern of ecosystem services (Peng, Yang, et al, ; Peng, Pan, Liu, Zhao, & Wang, ), there are still some limitations needing further improvement in this study. First, spatial distributions of three kinds of service land were obtained based on the simple overlaying of various key areas supplying ecosystem services, with equal weighting of each kind of ecosystem services.…”

Section: Discussionmentioning

confidence: 99%

Spatial identification of conservation priority areas for urban ecological land: An approach based on water ecosystem services

et al. 2019

Self Cite

View full text Add to dashboard Cite

How to effectively prevent land degradation and ecosystem deterioration in the process of urbanization has been the focus of land degradation researches in urban areas. Urban ecological land can be defined as the natural base on which a city relies to ecologically survive. It closely links the social economy with the natural eco‐environment, providing an important integrated approach to resolve the contradiction between urban expansion and natural ecosystems conservation in the process of urbanization. The research question addressed in this study is how to accurately identify the conservation priority areas for urban ecological land. Taking Zhuhai City, located in China, as an example, an approach based on seven kinds of water ecosystem services was put forward, combining social demand and natural supply for the services to determine service targets and conservation priority areas. The results showed that the conservation priority areas in Zhuhai City covered 868 km2, accounting for 51.03% of the total land area, which were mainly covered by woodlands or paddy fields and fish ponds. In addition, by synthesizing ecological importance and ecological sensitivity, management zones for urban ecological land were delineated, including 510 km2 of primary control areas and 358 km2 of secondary control areas. In the supply and demand view of water ecosystem services, this study put forward an integrated ecosystem‐based approach for conservation priority area identification of urban ecological land, aiming to prevent land degradation and achieve urban ecological sustainability.

show abstract

“…The hydrological resistance surface coefficients for the various land cover types are as follows: water area (1), forest land (150), cultivated land (200), grassland (150), unused land (300), and construction land (500). Since the urban ecological corridor has significantly been affected by anthropogenic disturbance, the impact of human interference on the corridor construction was reduced using the nighttime light index as correction to the MCR [32,37,38]:…”

Section: Ecological Source Identification Model Constructionmentioning

confidence: 99%

Construction of the Ecological Security Pattern of Urban Agglomeration under the Framework of Supply and Demand of Ecosystem Services Using Bayesian Network Machine Learning: Case Study of the Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China

2019

View full text Add to dashboard Cite

Coordinating ecosystem service supply and demand equilibrium and utilizing machine learning to dynamically construct an ecological security pattern (ESP) can help better understand the impact of urban development on ecological processes, which can be used as a theoretical reference in coupling economic growth and environmental protection. Here, the ESP of the Changsha–Zhuzhou–Xiangtan urban agglomeration was constructed, which made use of the Bayesian network model to dynamically identify the ecological sources. The ecological corridor and ecological strategy points were identified using the minimum cumulative resistance model and circuit theory. The ESP was constructed by combining seven ecological sources, “two horizontal and three vertical” ecological corridors, and 37 ecological strategy points. Our results found spatial decoupling between the supply and demand of ecosystem services (ES) and the degradation in areas with high demand for ES. The ecological sources and ecological corridors of the urban agglomeration were mainly situated in forestlands and water areas. The terrestrial ecological corridor was distributed along the outer periphery of the urban agglomeration, while the aquatic ecological corridor ran from north to south throughout the entire region. The ecological strategic points were mainly concentrated along the boundaries of the built-up area and the intersection between construction land and ecological land. Finally, the ecological sources were found primarily on existing ecological protection zones, which supports the usefulness of machine learning in predicting ecological sources and may provide new insights in developing urban ESP.

show abstract

Linking ecological degradation risk to identify ecological security patterns in a rapidly urbanizing landscape

Cited by 400 publications

References 71 publications

The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia

The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia

Spatial identification of conservation priority areas for urban ecological land: An approach based on water ecosystem services

Construction of the Ecological Security Pattern of Urban Agglomeration under the Framework of Supply and Demand of Ecosystem Services Using Bayesian Network Machine Learning: Case Study of the Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China

Contact Info

Product

Resources

About