Global Environmental Change最新文献

Land use is a key driver of the ongoing biodiversity crisis and therefore also a major opportunity for its mitigation. However, appropriately considering the diversity of land-use actors and activities in conservation assessments and planning is challenging. As a result, top-down conservation policy and planning are often criticized for a lack of contextual nuance widely acknowledged to be required for effective and just conservation action. To address these challenges, we have developed a conceptually consistent, scalable land system typology and demonstrated its usefulness for the world's tropical dry woodlands. Our typology identifies key land-use actors and activities that represent typical threats to biodiversity and opportunities for conservation action. We identified land systems in a hierarchical way, with a global level allowing for broad-scale planning and comparative work. Nested within it, a regionalized level provides social-ecological specificity and context. We showcase this regionalization for five hotspots of land-use change and biodiversity loss in dry woodlands in Argentina, Bolivia, Mozambique, India, and Cambodia. Unlike other approaches to present land use, our typology accounts for the complexity of overlapping land uses. This allows, for example, assessment of how conservation measures conflict with other land uses, understanding of the social-ecological co-benefits and trade-offs of area-based conservation, mapping of threats, or targeting area-based and actor-based conservation measures. Moreover, our framework enables cross-regional learning by revealing both commonalities and social-ecological differences, as we demonstrate here for the world's tropical dry woodlands. By bridging the gap between global, top-down, and regional, bottom-up initiatives, our framework enables more contextually appropriate sustainability planning across scales and more targeted and social-ecologically nuanced interventions.

European coal and carbon-intensive regions (CCIRs) face the intricate challenge of navigating destabilization-reconfiguration pathways, requiring a nuanced understanding of how phase-out intertwines with innovation and lock-in mechanisms. The success of this transformation depends on a multitude of factors, including socio-political, economic, and material conditions, as well as psychosocial and cultural dimensions of place. This study examines how feedback loops between structural factors (i.e., socio-political, socio-economic, and infrastructural) and sense of place can either disrupt or reinforce lock-in mechanisms and path dependency in CCIRs. The study focuses on Sulcis CCIR (Sardinia, Italy), where extractive and metal industries are deeply ingrained in the region's culture and economy. To reconstruct the trajectory of the CCIR and gain in depth understanding of feedback mechanisms of path dependency across time, we triangulate different data sources including policy documents, newspapers, participatory workshops, and interviews with key stakeholders. The findings reveal the profound influence of a sense of place grounded in a shared industrial myth along with associated place meanings, identities, and memories on lock-in mechanisms. Positive feedback loops between sense of place and structural factors of lock-in have legitimated the dominance of coal and carbon-intensive industries across time, impeding the recognition of the need for change and obscuring windows of opportunity for low-carbon transformation. Following the definite destabilization of coal, dominant place meanings are being actively challenged, while the legacy of sense of place is serving as a guiding frame for shaping the legitimacy and imaginaries of place transformation and defining a just transition pathway. The study discusses the importance of recognizing and addressing the role of sense of place and its interaction with structural factors in perpetuating lock-in to ensure effective deliberate destabilization efforts and navigate a just reconfiguration of CCIRs.

In light of societal shifts such as an aging population, delayed marriages, and higher rates of divorce, there's a notable rise in solitary living, affecting society, the economy, and the environment. To understand the implications of these demographic shifts, our research examines the nexus between solo living and its broader social-environmental consequences. Using Japan, one of the countries with the highest proportion of the elderly, as a reference, we explore the temporal fluctuations, gender-specific variances, and long-term trends in carbon footprints influenced by alterations in consumption behaviors. Results indicate that housing energy and food consumption remain the dominant carbon footprint contributors across all demographic sectors. Interestingly, single households present higher carbon footprints than non-single households, with those of single females surpassing their male counterparts due to increased household energy use and expenditures on clothing and healthcare. Following the demographic shifts, single households are expected to account for approximately 31.1% of Japan's emissions from households by 2040, challenging national decarbonization efforts due to their higher per capita emissions. This highlights the imperative for bespoke strategies, especially in resource allocation and sharing, to address the solo living challenge and ensure congruence with Japan's sustainability and decarbonization goals.

Carbon capture and storage (CCS) technology, considered as a pivotal tool in mitigating climate change within the fossil energy system, particularly in China, has experienced slower development than expected. The exploration of direct incentive policies to facilitate its growth remains relatively underdeveloped. This study developed a hybrid dynamic computable general equilibrium (CGE) model to simulate the substantial impacts of CCS incentive policies on China within the context of carbon neutrality target. Two potential incentive policies, carbon emission trading system (ETS) and 45Q tax credit, were simulated, with different sectoral coverage. The results indicate that CCS technologies can reduce carbon emissions by 960 ∼ 1,604 MtCO₂ annually by 2060 through the strategic implementation of these incentive policies. The 45Q tax credit demonstrates its effectiveness in promoting early-stage research and development (R&D) and demonstration of CCS, while the ETS policy facilitates the commercial development of CCS in the later stage of development. By 2060, the implementation of CCS incentive policies could potentially result in 7.7 ∼ 17.4 % reduction in China’s primary energy consumption, 71.2 ∼ 82.7 % decrease in the carbon price of ETS and 5.64 ∼ 6.59 % increase in the GDP compared with the no-policy scenario. In addition, the sectoral output in various sectors and the welfare of urban and rural households also increase. This paper provides an important reference for the realization of China’s carbon neutrality goal and the model framework can be applied to other countries.

As individuals and households have increasingly suffered the effects of climate change, substantial research has focused on understanding behavioral adaptation, the process of individuals and households responding to climate change to reduce future risk and improve well-being. However, this research is limited by the challenge of evaluating adaptation and differentiating it from coping. The theoretical literature suggests that planned, proactive, and transformative responses are more consistent with the concept of adaptation, while autonomous, reactive, and incremental efforts are more consistent with the concept of coping. We developed an index based on these features for evaluating behavioral responses to climate change in terms of coping and adaptation. We tested the index with a regression model of variables theorized to foster adaptation. Our empirical context was small woodland owners responding to climate change-related stressors (storms, insect and disease outbreaks, winter thaws, droughts, heat waves, and wildfires) by managing their forests in the Northwoods, USA. We found that a small but notable proportion of the owners exhibited behavior more consistent with adaptation than coping. A larger proportion of owners exhibited behavior more consistent with coping than adaptation. The greatest proportion exhibited mixed coping-adaptation behavior, confirming theories that coping and adaptation occur on a continuum, with interplay between the two. We also found the regression model explained how consistent their responses were with adaptation relative to coping. Our findings advance scholarly understanding of behavioral adaptation and how to evaluate it more consistently and coherently. Our findings also enhance practical understanding of how small woodland owners adapt to climate change.

Scenario development and analysis is an important methodological approach in the assessment of global environmental change. Scenarios are used to assess climate change and its impacts on societies, economies, and ecosystems, and identify, test, and improve policy responses to manage the negative consequences of a changing environment. Evaluation of scenarios, especially global scenarios widely used in the climate research and policy community, is therefore urgently needed. While the quality and usefulness of individual scenarios have been extensively examined through a wide array of criteria, standards for systematic evaluation of scenario sets are only emerging. Scenario diversity (i.e., diversity between individual scenarios in a set) has been advanced as a measure to assess the quality of global scenario sets. In this paper, we use scenario diversity analysis, a systematic and transparent quantitative method, to examine six major global scenario sets with regards to scenario set diversity. Results show that the assessed scenario sets show relatively good performance with regards to scenario set diversity. However, the use of classic methods for building scenario architectures and the number of scenarios included in a set raise important questions about the potential trade-offs between covering a bigger space of futures possibilities and adding redundancy to the scenario set.

Oil palm is the dominant global oil crop due to its high productivity and diversified usage in many sectors. Since the late 20^th century, oil palm cultivations proliferated in Southeast Asia, West Africa, and Latin America. However, global market factors, different national and regional policies, and smallholder versus commercial planting regimes in different areas lead to significant differences in economic benefits and environmental problems from deforestation and loss of biodiversity. We investigated changes in global and national distributions against suitability and indices of tree age distribution change for industrial oil palm (IOP) and smallholder oil palm (SOP). Spatial and temporal change analyses show that: i) For most tree ages, the proportion of global oil palm planting in suitable areas was less than 50%, but the impact of temporal regimes, from possible market factors and local policies, on planting structure should not be neglected; ii) Central America, South America, and West Africa were less suitable for oil palm cultivation compared to Southeast Asia. While, as two dominant oil palm planting countries, Indonesia and Malaysia had relatively low planting suitability, with 39.23% of Indonesia’s IOP, 44.85% of Indonesia’s SOP, 30.90% of Malaysia’s IOP and 18.77% of Malaysia’s SOP in highly and most suitable intervals; iii) There exist clear differences between IOP and SOP in terms of suitability, planting structure and spatial expansion patterns; iv) Hysteresis effect exists between latecomers (countries in West Africa and Latin America) and forerunner (Indonesia and Malaysia) in terms of spatial expansion; v) The spatial expansion patterns of oil palm planting centers have obvious scale effects for both IOP and SOP, with clear inter-country and intra-country differences. This paper reinterprets the global distribution of tree age and spatial expansion pattern and recommends scientific strategies to guide site selection and planting structure that enable oil palm cultivation for sustainable development.

China increasingly engages in environmental diplomacy through South-South cooperation across the developing world. Since 2019, the rise of the discourse of Nature-based Solutions (NbS) within this cooperation has been exponential. Coined just over ten years ago, NbS refers to the underexplored potential of leveraging the natural world to address socio-environmental challenges. The concept finds particular resonance in China, where it demonstrates strong parallels with the domestically-pioneered concept of Ecological Civilization – the ruling paradigm when it comes to all realms of Chinese environmental governance. Building on the global discourse, NbS has been adapted to the Chinese context, creating what some call “Chinese-style” NbS that prioritizes large-scale interventions and ecological engineering over grassroots preservation. China’s NbS are not only being pursued domestically, but also increasingly abroad through the country’s Belt and Road Initiative. From Southeast and Central Asia to Africa and Latin America, this article surveys Chinese-led or financed projects that fall under the broad umbrella of NbS. We provide a comparative analysis of these interventions – or the conspicuous lack of such interventions – to show the current status and future prospects for China’s growing sphere of influence when it comes to advancing NbS in the Global South. We find that China’s embrace of this concept in environmental diplomacy is directly related to the potential for NbS to serve as a tool for helping the country’s vision of an Ecological Civilization “go global.” The consonance between the rhetoric of NbS and Ecological Civilization, combined with the global reach of NbS, provides a powerful platform for taking Chinese environmental discourse to the global level.

Protected Areas such as national parks are increasingly implemented to achieve the long-term conservation of nature and the provision of ecosystem services, hence preventing biodiversity loss. We study the environmental and socioeconomic impacts generated by eight Italian National Parks. We estimate the impacts i) on the short and medium term, ii) on the local population and on the neighboring areas (i.e., their spillovers), and iii) differentiating the analysis by the macro-geographical context in which National Parks are embedded (i.e., north, center, and south of Italy). The analysis is based on the combination of the Propensity Score Matching with the Doubly Robust Difference-in-Differences estimator. We find that the National Parks have a positive and increasing-over-time impact on the share of forested areas. Moreover, from the socioeconomic point of view, their impact has been positive on the number of local units, workers employed (especially in the tourism sector), and the number of incoming work commuters, but negative on the number of agricultural holdings. However, these results depend on the geographical contexts, i.e., most of the positive socioeconomic impacts are in the north. Finally, we find (positive) spillover in terms of forested areas, but non-significant socioeconomic ones.

Deforestation is a leading contributor to greenhouse gas emissions globally. Understanding the direct drivers of forest loss is essential for developing targeted forest conservation and management policies. However, this data is hard to collect at scale due to the complexity of forest loss drivers and expertise required for accurately identifying them. To address this challenge, we developed a deep learning model called ForestNet which uses publicly available satellite imagery to automatically classify the drivers of primary forest loss. We validated ForestNet on a test set of expert-annotated forest loss events and showed that ForestNet achieved high performance across four major driver classes. We used ForestNet to identify these drivers on over 2 million forest loss events in Indonesia between 2012 and 2019, with significant improvement in spatial and temporal resolution over previously available data. We found that plantations and smallholder agriculture were the primary direct drivers of deforestation in Indonesia during this period, accounting for 64 % of total forest loss. Deforestation has decreased steadily since 2012 after increasing steadily from 2001 to 2009 and peaking from 2009 to 2012, trends that we found are primarily due to changes in plantation-driven deforestation. Our approach can serve as a general framework for scalably attributing deforestation to specific drivers and can be extended to other regions of interest, providing a flexible and cost-effective way for countries to regularly monitor, understand, and address their unique and dynamic drivers of deforestation.