Effects of Land Use/Cover on Regional Habitat Quality under Different Geomorphic Types Based on InVEST Model

Wang, Baixue; Cheng, Weiming

doi:10.3390/rs14051279

Cited by 61 publications

(36 citation statements)

References 88 publications

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“…In terms of regional human activities, the advantages and disadvantages of human activities in the three northeastern provinces to the natural environment also need to be comprehensively considered (Cheng et al, 2021). Due to industrial and agricultural construction, the unreasonable development and utilization of resources has led to the depletion of forest resources, the reduction of grassland resources and the saturation of cultivated land development (Wang and Cheng, 2022), which to some extent has an adverse impact on the vegetation coverage. However, the ecological environment management in the three northeast provinces has achieved initial results in human activities.…”

Section: Introductionmentioning

confidence: 99%

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Wang²,

Liu³

et al. 2022

Front. Environ. Sci.

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As the most important ecological barrier in eastern China, the three northeast provinces have extraordinary ecological significance. Their geographical location and climatic conditions make the distribution pattern of vegetation unique. Among them, climate change and human activities are the main factors affecting the richness and complexity of vegetation, climate change dominates the overall pattern of vegetation distribution, and regional human intervention locally changes the growth state of vegetation. Therefore, based on NDVI data of vegetation, meteorological data and socio-economic data, statistical methods such as Sen’s slope estimator, Mann-Kendall trend test, center of gravity transfer model, Hurst index and coefficient of variation were adopted to analyze the spatio-temporal changes and future trends in vegetation coverage; The use of Geographic detector to understand the relationship between NDVI to climate change and human activities. The results suggested that: 1) The three northeast provinces of China experienced an overall increasing NDVI at a rate of 0.016%/year from 2001 to 2020. The NDVI shows intensive heterogeneity in space, exhibiting a landscape of high in the East, low in the west, high in the north and low in the south; 2) The results of geographic detectors show that the temporal and spatial distribution pattern of vegetation NDVI is mainly determined by ≥ 10°C accumulated temperature, ≥ 0°C accumulated temperature, annual average temperature and land use type. The interaction between factors presents a bi-variable enhancement and nonlinear enhancement, and human activity factors enhance the contribution of climate factors. 3) Future changes in NDVI indicated that the vegetation coverage showed a trend of “overall improvement and regional degradation” from 2001 to 2020, and showed reverse persistence. The degraded area of vegetation will be more than the improved area. The research results will help the three northeast provinces cope with global climate change, enrich the research on the vegetation in the three northeastern provinces, and provide a scientific basis for formulating appropriate regional ecological protection policies.

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Section: Introductionmentioning

confidence: 99%

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Wang²,

Liu³

et al. 2022

Front. Environ. Sci.

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“…Due to a large amount of data collection required for evaluation based on indicator systems, more and more researchers are emphasizing the role of model methods in habitat quality evaluation (Polasky et al, 2011;Yan et al, 2017). Although model evaluation has certain limitations and is highly dependent on expert knowledge in determining indicators, it has obvious advantages over the large amount of data collected based on the evaluation of indicator systems (Wu et al, 2021a;Wang and Cheng, 2022). Among them, the InVEST-habitat quality model is widely used, which is flexible in its application and can replace complex methods such as species surveys, not only considers ecological processes, but also has a complete habitat quality evaluation system, reduces the randomness in the selection of evaluation indicators, and can evaluate habitat quality quickly (Xu et al, 2019;Kunwar et al, 2020;Wu et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

Evolution of habitat quality and analysis of influencing factors in the Yellow River Delta Wetland from 1986 to 2020

et al. 2022

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The assessment of habitat quality plays an important role in the effective conservation of wetland biodiversity. The Yellow River Delta Wetland is located in the intertwining zone of sea, terrestrial, and river ecosystems, increasing human activities and climate change posed a great threat to wetland biodiversity. This study first analyzed the spatial and temporal evolution characteristics of habitat quality in the Yellow River Delta Wetland under the evolution of the shoreline after runoff-sediment variability (1986–2020) using the InVEST-habitat quality model and then identified the dominant influence factors on habitat quality based on Geographical Detector. Finally, elasticity index was introduced to analyze the impacts of different reclamation activities on habitat quality. Results showed that the habitat quality decreased from 0.4798 in 1986 to 0.4078 in 2020, with high values of habitat quality concentrated in mudflat wetlands and low values of habitat quality concentrated in construction land and salt pans. The results of the Geographical Detector analysis showed that the influence of human activities, especially reclamation activities, had stronger effects on habitat quality than climatic factors. The elasticity index analysis showed that the elasticity of all three types of reclamation activities, namely, culture ponds, construction land, and salt pans, were negative from 1986 to 2005, 2005 to 2020, and 1986 to 2020. The reclamation activities had a negative impact on habitat quality. The habitat quality of the Yellow River Delta Wetland was most sensitive to the change in reclamation intensity of construction land from 1986 to 2020, and the sensitivity of the change of habitat quality to the change of reclamation intensity of culture ponds and salt pans was strengthening. This study explicitly revealed the effect of climate change and human activities on the habitat quality of the Yellow River Delta Wetland and proposed to analyze the response intensity of habitat quality to different reclamation activities by using the elasticity index, thus providing a scientific basis for mitigating the tradeoff between biodiversity conservation and rapid social development in the Yellow River Delta Wetland in the future.

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“…In recent years, with rapid urbanization, human activities have accelerated the change in land use patterns, which has led to changes in HQ [ 6 ]. Therefore, it is necessary to study the influence relationship between land use changes and HQ changes [ 7 , 8 ], which is important for achieving scientific land use planning and ecological environment protection.…”

Section: Introductionmentioning

confidence: 99%

Impact of Land Use Change on the Habitat Quality Evolution in Three Gorges Reservoir Area, China

Peng

Wang

Dong

et al. 2023

IJERPH

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Habitat quality (HQ) is an important indicator to characterize the level of biodiversity and ecosystem services, and can reflect the quality of the human living environment. Changes in land use can disturb regional HQ. Current research mostly focuses on assessing the good or bad quality of regional habitats, and less on the spatial response relationship between land use change and HQ, and even fewer studies on finely distinguishing the impact of land use types on HQ. Therefore, taking Three Gorges Reservoir Area (TGRA) of China as the study area, this paper first analyzes the land use change of study area by using the land use transfer matrix, land use rate model and landscape pattern index, and then combines the InVEST model with the multi-scale geographically weighted regression (MGWR) model to build a refined assessment framework to quantitatively assess the spatial and temporal evolution patterns of HQ, and then analyse in detail the spatial response relationship of each land use type change on the impact of HQ. The results showed that from 2000 to 2020, the land use in the TGRA shows a changing state of “urban expansion, cultivated land shrinkage, forest land growth, and grassland degradation”. With the change in land use, the habitat quality index (HQI) in the study area showed an “ increase first and then decline” change characteristics, and the HQ degradation was more obvious in the areas with intense human activities. The impact of land use change over the past 20 years on HQ in the TGRA has significant spatial and temporal heterogeneity, with changes in paddy and dryland having mainly negative impacts on HQ, and changes in sparse land, shrubland, and medium-cover grassland having mainly positive impacts on HQ. This paper mainly provides a research framework for refined assessment, and the results can provide scientific support for land planning and ecological protection in the TGRA, and the research methods and ideas can provide references for similar research.

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Effects of Land Use/Cover on Regional Habitat Quality under Different Geomorphic Types Based on InVEST Model

Cited by 61 publications

References 88 publications

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Evolution of habitat quality and analysis of influencing factors in the Yellow River Delta Wetland from 1986 to 2020

Impact of Land Use Change on the Habitat Quality Evolution in Three Gorges Reservoir Area, China

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