Virtual Only | Track 1 | Session 2. Ecological Networks Across Scales

While promoting socio-economic development, urbanization also poses significant challenges to the stability and sustainability of ecosystems in high-density cities and their surrounding areas. In this context, the construction of a scientific and rational ecological network has become a key path to alleviate the contradiction between urban expansion and ecological protection, and to promote the sustainable development of the region. However, traditional ecological network studies have mostly focused on natural or low-density areas, and there are limitations in the methods of constructing ecological networks in high-density built-up environments: although the existing models have taken into account to a certain extent the differential impacts of the intensity of human activities on the migration of species within the city, there is still room for improvement in the relevant studies; on the other hand, the current systematic integration of core habitat identification of indicator species and construction of landscape resistance surfaces is still insufficient, leading to the deviation of ecological corridor planning from urban development needs and limiting the effectiveness of planning practice. In order to address these gaps, this study has chosen the downtown area of Beijing, a key migration node on the East Asia-Australasia migration route, as a case study. A comprehensive research framework combining ecological source identification, resistance surface construction, and corridor simulation is adopted, aiming to balance the contradiction between the demands of rapid urbanisation and the construction of long-term ecological security patterns. Ecological source site identification was performed using the MaxEnt model and 2024 bird observation data to identify critical habitat areas. Corridor simulation uses minimum cumulative resistance (MCR) analysis to model potential ecological corridors by correcting resistance values using ecosystem sensitivity results. Network evaluation uses spatial syntax analysis to evaluate the connectivity, integrity and spatial hierarchy of the ecological network, and to identify key nodes and weak links in the ecological network. The results of the study showed that (1) the highly suitable bird habitats in the urban center of Beijing are mainly distributed in the areas around large parks such as the Olympic Forest Park and the Summer Palace and urban wetlands; (2) The corrected resistance surfaces based on ecological sensitivity significantly improved the accuracy of the model; (3) MCR simulation identified key ecological corridors, some disrupted by urban roads and dense buildings, requiring improved connectivity via ecological restoration or green infrastructure; (4) Spatial syntax showed moderate network connectivity, with critical hubs (e.g., green centers) and vulnerable breakpoints (e.g., road intersections) needing priority intervention. Based on this, the article proposes a tiered planning strategy: prioritizing the enhancement of the three-tier ecological hub functions centered on the Olympic Forest Park, the Summer Palace–Old Summer Palace Wetland System, and the Yongding River Ecological Corridor, and establishing a multi-tiered ecological network system. In the outskirts of the central urban area, efforts should be made to enhance the ecological connectivity of key areas such as the Wenyu River-Beiyun River Wetland Corridor and the West Mountain Lowland Belt. For transitional zones such as the urban green space patches along the Fifth Ring Road and the water system network of the Tongzhou Urban Sub-center, ecological restoration and landscape resilience enhancement projects should be advanced simultaneously. The article quantitatively analyses the coupling relationship between ecological suitability and human activities. Through a multi-scale network optimization scheme, it not only optimizes migration corridors for specific species but also reserves ecological resilience space to cope with future urban expansion. It provides a replicable technical path for coordinating biodiversity conservation and sustainable development goals in high-density cities

In the context of concurrent climate change and rapid urbanization, integrating ecological dimensions into urban resilience construction has become increasingly crucial. Contemporary planning methodologies often overlook the regulatory function of urban design elements. In high-density settlements, urban form exerts a significant influence on bird diversity levels by affecting habitat heterogeneity and species dispersal pathways. However, the multiscale, nonlinear regulatory mechanisms of urban form on biodiversity remain to be elucidated, impeding the harmonization of development intensity and ecological resilience objectives in spatial planning and diminishing the capacity of cities to contend with environmental fluctuations. To address this gap, this study aims to analyze the non-linear effects of urban form parameters and multidimensional variables, including habitat quality, connectivity, climatic factors, and anthropogenic disturbances, on bird diversity. Specifically, this study seeks to investigate how urban form influences avian diversity, with particular attention to threshold effects and interactions acting across local and regional scales. The ultimate goal is to explore strategies for harmonizing urban development and ecological resilience through the regulation of morphological parameters. Harbin's high-density settlements serve as the empirical focus, offering a foundation for resilience-oriented spatial planning. In this study, bird species data were collected from 456 sample sites within Harbin's high-density settlements, whereas built environment parameters (such as multi-scale building density, height, floor area ratio, and sky visibility factor), as well as habitat indicators (including NDVI, distance to large-scale green areas, distance to water sources), landscape diversity metrics reflecting connectivity, alongside control variables (like average annual temperature, precipitation, nighttime lighting, and population density) were derived. A boosted regression trees model was employed to analyze the nonlinear effects and scale dependence, and to quantify the complex interactions between variables and threshold characteristics. The investigation revealed substantial variations in the impact of urban form on bird diversity. At the local scale, higher building density and plot ratio were negatively correlated with diversity. Furthermore, a specific threshold for floor area ratio was identified, and the inhibitory effect stabilized after the building height exceeded a certain threshold. This finding indicates that microhabitats are sensitive to the intensity of development. At the regional scale, increasing building density was positively correlated with diversity, exhibiting a threshold inflection point. The floor area ratio demonstrated an inverted U-shaped relationship, indicating that moderate built environment agglomeration can support bird communities through resource replenishment and microhabitat heterogeneity. The theoretical underpinnings of the study reveal the pivotal function of urban form as an ecological regulator. Furthermore, it establishes a nonlinear synergistic framework between form parameters and biodiversity. At the practical level, we propose establishing a scale-nested planning control system, constraining the upper limit of localized floor area ratio and the lower limit of regional density. We also propose incorporating avian diversity simulation into the urban renewal assessment. This approach offers a pathway towards regulating morphological parameters scientifically, thereby facilitating the implementation of intensive development strategies, which balance high floor area ratios in specific zones with lower overall densities. Such strategies have been demonstrated to fulfill dual purposes: land conservation and biodiversity enhancement. Consequently, the approach offers a practical technical path to achieve synergistic sustainable urban growth alongside ecological resilience. It is of significant value for building climate-resilient spatial structures in rapidly urbanizing areas.

Research Background: Under the dual goals of sustainable urban development and ecological protection, delving into the relationship between the supply and demand of urban ecosystem services, identifying the spatial patterns of supply and demand of urban ecosystem services and their driving factors has become a key issue in balancing urban development and ecological protection. With the continuous increase in the global urbanization rate, intense human activities have led to the continuous encroachment on natural ecosystems, resulting in a significant decline in the supply capacity of ecosystem services. Meanwhile, the demand for ecosystem services such as clean water, air purification, and food security from urban populations has continued to grow, making the supply-demand contradiction increasingly acute. Research Objectives: As a key link between natural ecosystems and human society, the imbalance in the supply and demand of ecosystem services can trigger multiple ecological risks. However, existing studies mostly focus on the examination of the current supply and demand situation, without delving into the driving factors. There is an urgent need to reconstruct the urban development paradigm from the perspective of the supply-demand matching of ecosystem services. Research Methods: By integrating the theory of ecosystem service supply and demand, a technical system for identifying and optimizing the spatial patterns of ecosystem service supply and demand in highly urbanized areas is established. The InVEST model is used to quantitatively identify the spatial patterns of ecosystem service supply and demand, and a supply-demand matching and spatial analysis model is constructed. The key factors influencing supply-demand matching and their spatiotemporal distribution characteristics are identified through a driving factor analysis model. Taking Nanjing, Jiangsu Province, China as an example: Firstly, multi-source data such as land use, DEM, climate, and socio-economic data for the years 2000, 2010, and 2020 are collected, unified in projection and standardized. Secondly, the InVEST model and RUSLE model are used to quantify the supply and demand of four ecosystem services: water production, food production, carbon sequestration, and soil conservation. The spatiotemporal characteristics are analyzed through the supply-demand ratio and spatial autocorrelation. Then, the main driving factors are screened through redundancy analysis, and the spatial heterogeneity of the driving factors is revealed through geographically weighted regression. Finally, based on the supply-demand ratio and driving factor clustering, Nanjing is divided into different functional zones and management measures are proposed. Main Findings: Based on the above techniques, the spatiotemporal distribution characteristics of ecosystem service supply and demand in Nanjing, Jiangsu Province, China, and the driving factors influencing the supply-demand ratio of ecosystem services are obtained. Ultimately, feasible planning guidance for urban construction from the perspective of ecosystem services is provided. Research significance: This study provides a methodological approach from the perspective of supply and demand for the refined management of ecosystem services in highly urbanized areas, which has scientific reference value for the construction of regional ecological security patterns and sustainable development decision-making.

As globalization accelerates, how traditional industrial bases can achieve a coordinated transformation of both economy and ecology has become a key issue in global industrial transition. Existing research mainly focuses on economic and social policies, but lacks exploration of the spatial coupling mechanisms between ecological restoration and economic revitalization in the context of resilience and ecological renaissance. In the process of ecological restoration, heavy industrial regions often face intertwined socio-economic and ecological spatial challenges, including exacerbated inequalities, ecosystem degradation, and spatial fragmentation, which in turn hinder coordinated regional development. This study aims to explore the spatial coupling relationship between ecological restoration and economic revitalization in abandoned heavy industrial areas within the context of ecological-economic transition, as well as their spatial distribution characteristics and underlying mechanisms. Taking the ecological restoration of the River Leven catchment in the UK as a case study, this research integrates GIS spatial analysis and multiple regression methods to investigate the spatial coupling mechanisms between land re-greening and socio-economic revitalization. Firstly, remote sensing data and urban statistical data are used to obtain the Normalized Difference Vegetation Index (NDVI) for each spatial unit within the catchment, reflecting the status of ecological restoration. In addition, data on regional Gross Domestic Product (GDP), employment rate, and the Index of Multiple Deprivation (IMD) are collected to comprehensively assess regional economic revitalization and social vulnerability. Using GIS platforms for spatial registration and overlay analysis, the study reveals the spatial distribution characteristics, clustering patterns, and spatial heterogeneity of land re-greening and socio-economic revitalization at the catchment scale. Furthermore, multiple regression and geographically weighted regression (GWR) are employed to analyze the spatial correlations. The results show that the degree of land re-greening and the level of socio-economic revitalization in the River Leven catchment are significantly positively correlated in spatial terms. High-value clusters are mainly concentrated in the mid-upper reaches of the catchment and surrounding western settlements, such as Kinross, where ecological restoration has been particularly effective and economic and social conditions are generally favorable. In contrast, the lower reaches of the catchment, including Levenmouth and its surrounding areas, appear as high-deprivation zones on the Index of Multiple Deprivation (IMD) map, indicating relatively weaker economic and social conditions. The results of multiple regression and geographically weighted regression (GWR) further reveal that for every 0.1 increase in NDVI, GDP rises by approximately 2.7% and employment rate by 1.9%, while the Index of Multiple Deprivation (IMD) decreases, indicating that ecological restoration has significantly improved the economic and social conditions in disadvantaged areas. It is noteworthy that the distribution of ecological restoration investment within the catchment is uneven. For example, the cumulative area of ecological restoration land in the mid-upper reaches and western regions (such as around Kinross) accounts for 41.3% of the total catchment, while the ecological restoration coverage rate in high-deprivation areas is less than 15%. This disparity in distribution has also exacerbated local economic and social inequalities. This study confirms the spatial coupling mechanisms between ecological restoration and economic revitalization in the transformation of heavy industrial regions. The spatial disparities in land ecological restoration directly affect both the equity and pace of socio-economic revitalization. Future socio-economic policies should focus on the coordination of land ecological restoration, promoting the allocation of ecological restoration resources towards disadvantaged and high-deprivation areas. This will deepen the understanding of synergistic mechanisms within the ecological-economic-social system and enhance the overall social inclusiveness and resilience of the region.

The United Nations Environment Programme reports that the overexploitation of global resources and unsustainable production practices are causing destructive impacts on Earth's ecosystems. Over the past decade, China's urbanization rate has increased from 30% to 70%, with the majority of cities experiencing a period of rapid development. However, the rapid urbanization of most Chinese counties is based on resource consumption. This phenomenon leads to severe environmental degradation and resource depletion in urban areas, urgently requiring a comprehensive investigation. Not only China faces this challenge, but many countries worldwide are also dealing with the intensifying issues of energy consumption and pollution, which pose a significant challenge to the Sustainable Development Goals. Previous analyses from a basin perspective have predominantly focused on the municipal level, with a lack of exploration at the county level. For the Middle Yellow River region, characterized by its ecological fragility and dense population, conducting research on urbanization level (UL) and resource environment carrying capacity (RECC) is of urgent practical significance. However, current research in this field still falls short in unifying the definitions of UL and RECC, as well as in the precision of model calculations. With this in mind, our study focuses on the Middle Yellow River Basin, conducting empirical analysis at the county level. This study is based on data from 223 districts and counties in the Middle Yellow River Basin for the years 2015, 2018, and 2021. It employs an improved coupling coordination degree model (CCDM) and a geographically and temporally weighted regression model (GTWR), introducing a more comprehensive indicator system to assess the synergistic relationship between UL and RECC. The study also explores the spatiotemporal dynamic evolution characteristics. The results indicate that 1) the UL in the Middle Yellow River Basin generally shows an upward trend with significant spatial heterogeneity, which is gradually narrowing year by year. Low-value areas are mainly distributed along the river, while high-value areas are gradually shifting towards county towns. 2) The RECC generally shows a downward trend with marked spatial heterogeneity. High-value RECC areas are concentrated in the river valley plains and some central cities, while low-value areas appear in the loess gully regions. 3) The CCD in the Middle Yellow River Basin increases year by year, also exhibiting significant spatial heterogeneity. Areas with higher levels of economic and technological development, especially provincial capitals and central cities, tend to have higher CCD values. 4) The main drivers affecting CCD value changes in the region's districts and counties have shifted from resource and environmental factors to those considering population and economic urbanization. Positive drivers now include population urbanization indicators, while negative drivers focus on economic and social urbanization aspects. Overall, our study uses an optimized coupling coordination degree model to provide a multi-dimensional perspective for assessing urbanization levels and resource environment carrying capacity. Our research results offer a reference path for counties in ecologically fragile areas to coordinate social development with ecological protection, promoting the sustainable development of the region's territorial space.