Spatio-temporal variations of habitat quality in the Greater Bay Area around Hangzhou Bay, based on LUCC and simulation
Yu He
A and Wanzheng Ai B *
A
B
Abstract
Habitat quality (HQ) is vital for achieving sustainable regional development. Understanding the spatial patterns and temporal evolution of HQ in the context of land use–cover change (LUCC) is crucial for promoting ecological civilisation and high-quality growth, especially for regions with rapid economic development.
In order to analyse the impact of LUCC on habitat quality in the coastal areas with frequent human activities.
This study focused on the Greater Bay Area around Hangzhou Bay and analysed the HQ on the basis of LUCC data during 2010–2020 by using the InVEST model and spatial autocorrelation analysis. Additionally, land-use data for multiple scenarios in 2030 were predicted using the PLUS model, and the variations in land use and HQ in the study region during 2020–2030 were assessed.
During 2010–2020, the construction land in the region expanded by 1932.79 km2, primarily at the expense of cropland and water areas. The mean HQ values were 0.6287, 0.6181 and 0.6037 for 2010, 2015 and 2020 respectively, indicating a continuous decline. Spatially, HQ exhibited strong clustering during this period. However, there was a clear trend of fragmentation and reduction in ‘high–high’ cluster areas along the coast, mostly owing to the transformation of water areas and wetlands into construction land and cropland. In the projected scenarios (natural development, ND; economic development, ED; crop protection, CP; and ecological protection, EP) for 2030, the mean HQ values are estimated to be 0.5881, 0.5837, 0.5915 and 0.5965 respectively. Compared with 2020, there will be a certain decrease in HQ, with the EP scenario showing the lowest decrease of 0.0052.
The HQ changes were closely linked to LUCC, the construction-land expansion was the main cause of HQ destruction in the Greater Bay Area around Hangzhou Bay. To alleviate the trend of declining HQ, it is essential to select appropriate development scenarios for each city in the region and coordinate the development of the cities.
These findings provide valuable insights for promoting sustainable economic growth in the Greater Bay Area around Hangzhou Bay.
Keywords: Greater Area around Hangzhou Bay, habitat quality, land use-cover change, InVEST model, LUCC, PLUS model, scenario simulation, spatial autocorrelation.
References
Ait El Haj F, Ouadif L, Akhssas A (2023) Simulating and predicting future land-use/land cover trends using CA–Markov and LCM models. Case Studies in Chemical and Environmental Engineering 7, 100342.
| Crossref | Google Scholar |
Anselin L (1995) Local indicators of spatial association—LISA. Geographical Analysis 27(2), 93-115.
| Crossref | Google Scholar |
Bao S, Yang F (2022) Spatio-temporal dynamic of the land use/cover change and scenario simulation in the Southeast Coastal Shelterbelt System Construction Project Region of China. Sustainability 14(14), 8952.
| Crossref | Google Scholar |
Berta Aneseyee A, Noszczyk T, Soromessa T, Elias E (2020) 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. Remote Sensing 12(7), 1103.
| Crossref | Google Scholar |
Brooks RP (1997) Improving habitat suitability index models. Wildlife Society Bulletin 25(1), 163-167.
| Google Scholar |
Chasia S, Olang LO, Sitoki L (2023) Modelling of land-use/cover change trajectories in a transboundary catchment of the Sio–Malaba–Malakisi Region in East Africa using the CLUE-s model. Ecological Modelling 476, 110256.
| Crossref | Google Scholar |
Chen K, Cong P, Qu L, Liang S, Sun Z, Han J (2023) Biological connectivity and its driving mechanisms in the Liaohe Delta wetland, China. Ecological Informatics 76, 102028.
| Crossref | Google Scholar |
Chen W, Zhang X, Huang Y (2021) Spatial and temporal changes in ecosystem service values in karst areas in southwestern China based on land use changes. Environmental Science and Pollution Research 28(33), 45724-45738.
| Crossref | Google Scholar | PubMed |
Delalieux S, Somers B, Haest B, Spanhove T, Vanden Borre J, Mücher CA (2012) Heathland conservation status mapping through integration of hyperspectral mixture analysis and decision tree classifiers. Remote Sensing of Environment 126, 222-231.
| Crossref | Google Scholar |
Fleskens L, Duarte F, Eicher I (2009) A conceptual framework for the assessment of multiple functions of agro-ecosystems: a case study of Trás-os-Montes olive groves. Journal of Rural Studies 25(1), 141-155.
| Crossref | Google Scholar |
Fu B, Xu P, Wang Y, Yan K, Chaudhary S (2018) Assessment of the ecosystem services provided by ponds in hilly areas. Science of The Total Environment 642, 979-987.
| Crossref | Google Scholar | PubMed |
Geng J, Shen S, Cheng C, Dai K (2022) A hybrid spatiotemporal convolution-based cellular automata model (ST-CA) for land-use/cover change simulation. International Journal of Applied Earth Observation and Geoinformation 110, 102789.
| Crossref | Google Scholar |
Glockmann M, Li Y, Lakes T, Kropp JP, Rybski D (2021) Quantitative evidence for leapfrogging in urban growth. Environment and Planning – B. Urban Analytics and City Science 49(1), 352-367.
| Crossref | Google Scholar |
Hawker L, Uhe P, Paulo L, Sosa J, Savage J, Sampson C, Neal J (2022) A 30 m global map of elevation with forests and buildings removed. Environmental Research Letters 17(2), 024016.
| Crossref | Google Scholar |
Herrera-Franco G, Escandón-Panchana P, Montalván FJ, Velastegui-Montoya A (2022) CLUE-S model based on GIS applied to management strategies of territory with oil wells – case study: Santa Elena, Ecuador. Geography and Sustainability 3(4), 366-378.
| Crossref | Google Scholar |
Hillard EM, Nielsen CK, Groninger JW (2017) Swamp rabbits as indicators of wildlife habitat quality in bottomland hardwood forest ecosystems. Ecological Indicators 79, 47-53.
| Crossref | Google Scholar |
Joseph GS, Mauda EV, Seymour CL, Munyai TC, Dippenaar-Schoeman A, Foord SH (2018) Landuse change in savannas disproportionately reduces functional diversity of invertebrate predators at the highest trophic levels: spiders as an example. Ecosystems 21, 930-942.
| Crossref | Google Scholar |
Lei J, Chen Y, Li L, Chen Z, Chen X, Wu T, Li Y (2022) Spatiotemporal change of habitat quality in Hainan Island of China based on changes in land use. Ecological Indicators 145, 109707.
| Crossref | Google Scholar |
Li S, Liu X, Li X, Chen Y (2017) Simulation model of land use dynamics and application: progress and prospects. Journal of Remote Sensing 21, 329-340.
| Google Scholar |
Liang X, Guan Q, Clarke KC, Liu S, Wang B, Yao Y (2021) Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: a case study in Wuhan, China. Computers, Environment and Urban Systems 85, 101569.
| Crossref | Google Scholar |
Liu MZ, Zhang HJ, Wang YF, Pei HW (2021) Characteristics of habitat quality in the agro-pastoral ecotone of northern China based on land uses. Soil and Water Conservation Research 28, 156-162.
| Google Scholar |
Liu X, Ma L, Li X, Ai B, Li S, He Z (2014) Simulating urban growth by integrating landscape expansion index (LEI) and cellular automata. International Journal of Geographical Information Science 28(1), 148-163.
| Crossref | Google Scholar |
Liu X, Wei M, Li Z, Zeng J (2022) Multi-scenario simulation of urban growth boundaries with an ESP-FLUS model: a case study of the Min Delta region, China. Ecological Indicators 135, 108538.
| Crossref | Google Scholar |
Lu Z, Song Q, Zhao J, Wang S (2023) Prediction and evaluation of ecosystem service value based on land use of the Yellow River Source Area. Sustainability 15(1), 687.
| Crossref | Google Scholar |
Mendoza-González G, Martínez ML, Lithgow D, Pérez-Maqueo O, Simonin P (2012) Land use change and its effects on the value of ecosystem services along the coast of the Gulf of Mexico. Ecological Economics 82, 23-32.
| Crossref | Google Scholar |
Pei M, Liu X, Wang J, Liu J, Zhao X, Li H, Wang R, Luo X, Xing L, Wang C, Zhao H (2023) Spatiotemporal characteristics and habitat quality analysis in the temperate desert sub-region of Ordos Plateau, China. Land 12(7), 1470.
| Crossref | Google Scholar |
Qiao X, Li Z, Lin J, Wang H, Zheng S, Yang S (2023) Assessing current and future soil erosion under changing land use based on InVEST and FLUS models in the Yihe River Basin, North China. International Soil and Water Conservation Research 12, 298-312.
| Crossref | Google Scholar |
Raji SA, Odunuga S, Fasona M (2022) Spatially explicit scenario analysis of habitat quality in a tropical semi-arid zone: case study of the Sokoto–Rima basin. Journal of Geovisualization and Spatial Analysis 6(1), 11.
| Crossref | Google Scholar |
Sallustio L, De Toni A, Strollo A, Di Febbraro M, Gissi E, Casella L, Geneletti D, Munafò M, Vizzarri M, Marchetti M (2017) Assessing habitat quality in relation to the spatial distribution of protected areas in Italy. Journal of Environmental Management 201, 129-137.
| Crossref | Google Scholar | PubMed |
Sherrouse BC, Semmens DJ, Ancona ZH (2022) Social Values for Ecosystem Services (SolVES): open-source spatial modeling of cultural services. Environmental Modelling & Software 148, 105259.
| Crossref | Google Scholar |
Sun X, Jiang Z, Liu F, Zhang D (2019) Monitoring spatio-temporal dynamics of habitat quality in Nansihu Lake basin, eastern China, from 1980 to 2015. Ecological Indicators 102, 716-723.
| Crossref | Google Scholar |
Tang F, Fu M, Wang L, Zhang P (2020) Land-use change in Changli County, China: predicting its spatio-temporal evolution in habitat quality. Ecological Indicators 117, 106719.
| Crossref | Google Scholar |
Tang J, Zhou L, Dang X, Hu F, Yuan B, Yuan Z, Wei L (2023) Impacts and predictions of urban expansion on habitat quality in the densely populated areas: a case study of the Yellow River Basin, China. Ecological Indicators 151, 110320.
| Crossref | Google Scholar |
Terrado M, Sabater S, Chaplin-Kramer B, Mandle L, Ziv G, Acuña V (2016) Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning. Science of The Total Environment 540, 63-70.
| Crossref | Google Scholar | PubMed |
Wang Z, Li X, Mao Y, Li L, Wang X, Lin Q (2022) Dynamic simulation of land use change and assessment of carbon storage based on climate change scenarios at the city level: a case study of Bortala, China. Ecological Indicators 134, 108499.
| Crossref | Google Scholar |
Wei L, Zhou L, Sun D, Yuan B, Hu F (2022) Evaluating the impact of urban expansion on the habitat quality and constructing ecological security patterns: a case study of Jiziwan in the Yellow River Basin, China. Ecological Indicators 145, 109544.
| Crossref | Google Scholar |
Wei Q, Abudureheman M, Halike A, Yao K, Yao L, Tang H, Tuheti B (2022) Temporal and spatial variation analysis of habitat quality on the PLUS–InVEST model for Ebinur Lake Basin, China. Ecological Indicators 145, 109632.
| Crossref | Google Scholar |
Wu J, Li X, Luo Y, Zhang D (2021) Spatiotemporal effects of urban sprawl on habitat quality in the Pearl River Delta from 1990 to 2018. Scientific Reports 11(1), 13981.
| Crossref | Google Scholar | PubMed |
Xu X, Yang G, Tan Y (2019) Identifying ecological red lines in China’s Yangtze River Economic Belt: a regional approach. Ecological Indicators 96, 635-646.
| Crossref | Google Scholar |
Xu Z, Wang Y, Sun G, Chen Y, Ma Q, Zhang X (2023) Generating gridded gross domestic product data for china using geographically weighted ensemble learning. ISPRS International Journal of Geo-Information 12(3), 123.
| Crossref | Google Scholar |
Yang C, Li Q, Zhao T, Liu H, Gao W, Shi T, Guan M, Wu G (2019) Detecting spatiotemporal features and rationalities of urban expansions within the Guangdong–Hong Kong–Macau Greater Bay Area of China from 1987 to 2017 using time-series landsat images and socioeconomic data. Remote Sensing 11(19), 2215.
| Crossref | Google Scholar |
Yang H, Xu W, Yu J, Xie X, Xie Z, Lei X, Wu Z, Ding Z (2023) Exploring the impact of changing landscape patterns on ecological quality in different cities: a comparative study among three megacities in eastern and western China. Ecological Informatics 77, 102255.
| Crossref | Google Scholar |
Ye H, Song Y, Xue D (2022) Multi-Scenario Simulation of Land Use and Habitat Quality in the Guanzhong Plain Urban Agglomeration, China. International Journal of Environmental Research and Public Health 19(14), 8703.
| Crossref | Google Scholar | PubMed |
Zhang D, Wang X, Qu L, Li S, Lin Y, Yao R, Zhou X, Li J (2020) Land use/cover predictions incorporating ecological security for the Yangtze River Delta region, China. Ecological Indicators 119, 106841.
| Crossref | Google Scholar |
Zhang S, Yang P, Xia J, Wang W, Cai W, Chen N, Hu S, Luo X, Li J, Zhan C (2022) Land use/land cover prediction and analysis of the middle reaches of the Yangtze River under different scenarios. Science of The Total Environment 833, 155238.
| Crossref | Google Scholar | PubMed |
Zhang X, Song W, Lang Y, Feng X, Yuan Q, Wang J (2020) Land use changes in the coastal zone of China’s Hebei Province and the corresponding impacts on habitat quality. Land Use Policy 99, 104957.
| Crossref | Google Scholar |
