Spatial assessment and management of regional ecosystem services in the Yangtze River Delta Region

The Yangtze River Delta (YRD) metropolitan region is one of the most rapidly urbanized regions in China and has experienced a remarkable period of population growth (at an annual growth rate of 3.0%), and urbanization (at an annual growth rate of 9.2%). Rapid urbanization has dramatically changed land use/land cover patterns and ecosystems in the region, causing widespread environmental problems such as habitat fragmentation, aggravation of environmental pollution, decline in biodiversity and ecosystem degredation. These problems have restricted the sustainable development of socio-economic system of the Yangtze River Delta Region. Facing the challenges, the Yangtze River Delta Region is carrying out the practice of regional integration planning and cooperation in environmental governance, which urgently needs the guidance of relevant theories and methods. Some of the key environmental policy pilots have been carried on in this region, such as the Ecological Red Line Policy (Bai et al, 2016; Lü et al, 2013). This policy has one of the main objectives of protecting important eco-function areas i.e. ecosystem service hot spots, to deliver services such as water storage, clean drinking water, and carbon sequestration, and to maintain ecological safety to support economic and social development, which an important policy orientation of ecosystem services approach.Ecosystem services are the contributions of ecosystem structure and function to human well-being, connecting natural and socio-economic systems. The ecosystem services approach is considered to be one of the important decision support tools for guiding and formulating environmental policies. Based on the theories and methods of ecosystem services, combined with local expert knowledge, remote sensing and GIS technologies, this dissertation aims is mainly to develop a comprehensive framework of ecosystem services assessment and decision support for rapid urbanization regions.Based on this framework, the spatial characteristics, supply-demand relationship and flow direction of ecosystem services in the Yangtze River Delta Region are analysed and evaluated. Main results of this thesis are as follows:(1) According to the characteristics of the regional ecosystems of the Yangtze River Delta Region, combined with local expert knowledge, the Burkhard’s scoring and assessment method of ecosystem services was improved, and the score matrix between twelve ecosystem types and twenty-three ecosystem services in the Yangtze River Delta Region was established.(2) Based on DPSIR model, the characteristics of the social-ecological complex ecosystem and change of ecosystem services in the Yangtze River Delta Region were analysed. The main ecological and environmental problems were identified. Causes and main driving forces of decline in ecosystem services were revealed in the region.(3) Based on ARCGIS platform, the status quo of ecosystem services in the Yangtze River Delta region was analysed and evaluated. The spatial differentiation characteristics and main impact factors of ecosystem services in the Yangtze River Delta region were clarified. The hot spots of total ecosystem services were aggregated in the southwest areas, while the cold spots were distributed in the middle and northeast areas of the region. The hot spots of supporting services and regulating services aggregately distributed in the southwest mountainous areas while hot spots of provisioning services mainly in the northeast plain, and high value of cultural services widespread in the waterbodies and southwest mountainous areas. The spatial heterogeneity is determined by biophysical features and land use types. Based on the assessment, six major ecosystem services functional zones were divided: (I) South Ecological Integrity Conservation Zone, (II) Southwest Mountainous and Hilly Forest Ecological Zone, (III) Northeast Plain Agriculture Ecological Zone, (IV) Middle Aquatic Ecological Conservation Zone, (V) Eastern Coastal Estuaries Ecological Zone, and (VI) Urban Development Area., and the corresponding management strategies on the basis of environmental problems and ecosystem services characteristics in each of the functional zones were put forward.(4) Using regional spatial data in net primary productivity, the quality levels of forest and cropland were graded and the previous scores of ecosystem services in forest and cropland were calibrated. Then, the hot spots and clustering patches of forest and farmland ecosystem services were identified by ARCGIS tools. Finally, the forest ecosystem conservation areas (red line) and cropland ecosystem conservation areas (red line) in the Yangtze River Delta region were delineated.(5) Based on the improved Burkhard’s supply-demand budget of ecosystem services method, the budgets of three regulating services (erosion regulating service, flood regulating service and water purification regulating service) of the sixteen core cities in the region were established, and the characteristics of surplus and deficit of three services of the cities in the region were analysed. Combing the budget with analysis of flow direction of ecosystem services, the potential provisioning cities and the benefiting cities of ecosystem services are identified. On the basis of the results, the potential model of regional inter-city environmental cooperation is proposed.This dissertation not only improves the methods of ecosystem service assessment and decision support in rapidly urbanized regions, but also makes contributions to the guidance in delineation of ecological red line, regional environmental cooperation and sustainable development in the Yangtze River Delta Region

Identifying hotspots and management of critical ecosystem services in rapidly urbanizing Yangtze River Delta Region, China

Rapid urbanization has altered many ecosystems, causing a decline in many ecosystem services, generating serious ecological crisis. To cope with these challenges, we presented a comprehensive framework comprising five core steps for identifying and managing hotspots of critical ecosystem services in a rapid urbanizing region. This framework was applied in the case study of the Yangtze River Delta (YRD) Region. The study showed that there was large spatial heterogeneity in the hotspots of ecosystem services in the region, hotspots of supporting services and regulating services aggregately distributing in the southwest mountainous areas while hotspots of provisioning services mainly in the northeast plain, and hotspots of cultural services widespread in the waterbodies and southwest mountainous areas. The regionalization of the critical ecosystem services was made through the hotspot analysis. This study provided valuable information for environmental planning and management in a rapid urbanizing region and helped improve China's ecological redlines policy at regional scale

Towards Trustworthy Explanation: On Causal Rationalization

With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts to account for the major variation in prediction. Yet, existing association-based approaches on rationalization cannot identify true rationales when two or more snippets are highly inter-correlated and thus provide a similar contribution to prediction accuracy, so-called spuriousness. To address this limitation, we novelly leverage two causal desiderata, non-spuriousness and efficiency, into rationalization from the causal inference perspective. We formally define a series of probabilities of causation based on a newly proposed structural causal model of rationalization, with its theoretical identification established as the main component of learning necessary and sufficient rationales. The superior performance of the proposed causal rationalization is demonstrated on real-world review and medical datasets with extensive experiments compared to state-of-the-art methods.Comment: In Proceedings of the 40th International Conference on Machine Learning (ICML) GitHub Repository: https://github.com/onepounchman/Causal-Retionalizatio