Energy and the Environment

In addition to habitat loss and fragmentation, demographic processes—the vagaries of births, deaths and sex ratio fluctuations—pose substantial threats to wild giant panda populations. Additionally, climate change and plans for the Giant Panda National Park may influence (in opposing directions) the extinction risk for wild giant pandas. The Fourth National Giant Panda Census showed pandas living in 33 isolated populations. An estimated 259 animals live in 25 of these groups, ~14% of the total population. We used individual-based models to simulate time series of these small populations for 100 years. We analysed the spatial pattern of their risk of extinction under current conditions and multiple climate change models. Furthermore, we consider the impact of the proposed Giant Panda National Park. Results showed that 15 populations face a risk >90%, and for 3 other populations the risk is >50%. Of the 15 most at-risk populations, national parks can protect only 3. Under the Representative Concentration Pathway 8.5 climate change scenario, the 33 populations will probably further divide into 56 populations. Some 41 of them will face a risk >50% and 35 face a risk >90%. Although national parks will probably connect some fragmented habitats, 26 populations will be outside national park planning. Our study gives practical advice for conservation policies and management and has implications for the conservation of other species in the world that live in isolated, fragmented habitats.

Natural infrastructure such as parks, forests, street trees, green roofs, and coastal vegetation is central to sustainable urban management. Despite recent progress, it remains challenging for urban decision-makers to incorporate the benefits of natural infrastructure into urban design and planning. Here, we present an approach to support the greening of cities by quantifying and mapping the diverse benefits of natural infrastructure for now and in the future. The approach relies on open-source tools, within the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software, that compute biophysical and socio-economic metrics relevant to a variety of decisions in data-rich or data-scarce contexts. Through three case studies in China, France, and the United States, we show how spatially explicit information about the benefits of nature enhances urban management by improving economic valuation, prioritizing land use change, and promoting inclusive planning and stakeholder dialogue. We discuss limitations of the tools, including modeling uncertainties and a limited suite of output metrics, and propose research directions to mainstream natural infrastructure information in integrated urban management.

Nature underpins human well-being in critical ways, especially in health. Nature provides pollination of nutritious crops, purification of drinking water, protection from floods, and climate security, among other well-studied health benefits. A crucial, yet challenging, research frontier is clarifying how nature promotes physical activity for its many mental and physical health benefits, particularly in densely populated cities with scarce and dwindling access to nature. Here we frame this frontier by conceptually developing a spatial decision-support tool that shows where, how, and for whom urban nature promotes physical activity, to inform urban greening efforts and broader health assessments. We synthesize what is known, present a model framework, and detail the model steps and data needs that can yield generalizable spatial models and an effective tool for assessing the urban nature–physical activity relationship. Current knowledge supports an initial model that can distinguish broad trends and enrich urban planning, spatial policy, and public health decisions. New, iterative research and application will reveal the importance of different types of urban nature, the different subpopulations who will benefit from it, and nature’s potential contribution to creating more equitable, green, livable cities with active inhabitants.

Climate change and human activities exert a wide range of stressors on urban coastal areas. Synthetical assessment of coastal vulnerability is crucial for effective interventions and long-term planning. However, there have been few studies based on integrative analyses of ecological and physical characteristics and socioeconomic conditions in urban coastal areas. This study developed a holistic framework for assessing coastal vulnerability from three dimensions - biophysical exposure, sensitivity and adaptive capacity - and applied it to the coast of Bohai Economic Rim, an extensive and important development zone in China. A composite vulnerability index (CVI) was developed for every 1 km2 segment of the total 5627 km coastline and the areas that most prone to coastal hazards were identified by mapping the distribution patterns of the CVIs in the present and under future climate change scenarios. The CVIs show a spatial heterogeneity, with higher values concentrated along the southwestern and northeastern coasts and lower values concentrated along the southern coasts. Currently, 20% of the coastlines with approximately 350,000 people are highly vulnerable to coastal hazards. With sea-level rises under the future scenarios of the year 2100, more coastlines will be highly vulnerable, and the amount of highly-threatened population was estimated to increase by 13–24%. Among the coastal cities, Dongying was categorized as having the highest vulnerability, mainly due to poor transportation and medical services and low GDP per capita, which contribute to low adaptive capacity. Our results can benefit decision-makers by highlighting prioritized areas and identifying the most important determinants of priority, facilitating location-specific interventions for climate-change adaptation and sustainable coastal management.

Gross Ecosystem Product (GEP) is an aggregate measure of the monetary value of final ecosystem services, or the direct benefits that people derive from nature. In this study, we focus on the 'Chang-Zhu-Tan' (CZT) urban agglomeration—an emerging megacity of over 15 million people situated on the Yangtze River—as a case study of the dynamics of ecological production amidst rapid urbanization. In this study, we couple a spatial-temporal analysis of regional ecological change based on remote-sensing data with economic valuation methods (e.g. travel cost method) using official statistics and survey data. We find that while the land cover of natural ecosystems decreased slightly between 2000 and 2015, their quality—and therefore economic value—greatly improved. From 2000 to 2015, the GEP of CZT increased by 56.77%. In particular, the value of regulating services grew by 7.43% (calculated using inflation-adjusted prices). GEP can reflect nature's contribution to human well-being. At the same time, its long-term trends can serve as an indicator of the extent and quality of local and regional ecosystems, thereby providing a corrective or complement to more conventional measures of development. Although urbanization increases spatial constraints on the management of natural capital, progress in ecological protection and restoration can still improve the quality of ecosystems and the services they provide. Our study shows how GEP, and the value of natural capital it reflects, can grow amidst the pressures of rapid urbanization.

The restoration of ecosystems provides an important opportunity to improve the provision of ecosystem services. Achieving the maximum possible benefits from restoration with a limited budget requires knowing which places if restored would produce the best combination of improved ecosystem services. Using an ecosystem services assessment and optimization algorithm, we find choices that generate maximum benefits from ecosystem restoration. We applied a set of weights to integrate multiple services into a unified approach and find the optimal land restoration option given those weights. We then systematically vary the weights to find a Pareto frontier that shows potentially optimal choices and illustrates trade-offs among services. We applied this process to evaluate optimal restoration on Hainan Island, China, a tropical island characterized by multiple ecosystem service hotspots and conditions of poverty. We analyzed restoration opportunities with the goal of increasing a provisioning service, plantation revenue, and several water-related ecosystem services that contribute to improved water quality and flood mitigation. We found obvious spatial inconsistencies in the optimal location for maximizing separate services and tradeoffs in the provision of these services. Optimized land-use patterns greatly out-performed the non-target restoration scheme. When explicit consideration of the importance of poverty alleviation was taken into account, the location of the prioritized areas shifted and trade-offs among services varied. Our study emphasizes the importance of integrating social concerns into land-use planning to mitigate conflicts and improve equity, especially in the areas where poverty and hotspots of biodiversity and ecosystem services are highly geographically coincident.

Significance
To achieve sustainable development, there is a pressing need to move beyond conventional economic measures like gross domestic product (GDP). We develop gross ecosystem product (GEP), a measure that summarizes the value of the contributions of nature to economic activity. We illustrate the calculation of GEP in Qinghai Province, China, to show that the approach is tractable both across China and globally. Known as the water tower of Asia, Qinghai is the source of the Mekong, Yangtze, and Yellow Rivers and nearly two-thirds of GEP derives from water-related values. GEP was greater than GDP in Qinghai in 2000, and was three-fourths as large as GDP in 2015. China is using GEP to guide investments in ecosystem conservation and restoration.

Abstract
Gross domestic product (GDP) summarizes a vast amount of economic information in a single monetary metric that is widely used by decision makers around the world. However, GDP fails to capture fully the contributions of nature to economic activity and human well-being. To address this critical omission, we develop a measure of gross ecosystem product (GEP) that summarizes the value of ecosystem services in a single monetary metric. We illustrate the measurement of GEP through an application to the Chinese province of Qinghai, showing that the approach is tractable using available data. Known as the “water tower of Asia,” Qinghai is the source of the Mekong, Yangtze, and Yellow Rivers, and indeed, we find that water-related ecosystem services make up nearly two-thirds of the value of GEP for Qinghai. Importantly most of these benefits accrue downstream. In Qinghai, GEP was greater than GDP in 2000 and three-fourths as large as GDP in 2015 as its market economy grew. Large-scale investment in restoration resulted in improvements in the flows of ecosystem services measured in GEP (127.5%) over this period. Going forward, China is using GEP in decision making in multiple ways, as part of a transformation to inclusive, green growth. This includes investing in conservation of ecosystem assets to secure provision of ecosystem services through transregional compensation payments.