Climate Resilience and Sustainability最新文献

Marine fauna, including coral reefs, exist under particular oceanographic and meteorological (metocean) processes that maintain water quality within the range limits to which they have adapted over millennia. Climate-induced changes to these metocean processes could alter ambient marine water quality to ranges beyond those limits and at rates faster than species can adapt. Extreme (or marginal) coral reefs, such as those in arid tropical regions, already exist at the limits of their ranges for water quality parameters such as temperature and turbidity. Here, we apply projected anomalies from ensemble climate models to the metocean processes that drive turbidity in the Exmouth Gulf region of north Western Australia where habitats of significant environmental value exist. We also apply projected sea surface temperature anomalies to look at how a combined effect of turbidity and temperature might impact important habitats. We find that turbidity is predicted to increase in some parts of the Gulf and decrease in others due to differing metocean drivers of turbidity throughout the region. Temperature anomalies reveal year-round increases in temperature consistent with current summer marine heat wave events (>2.5°C above mean temperatures). Climate models used in the predictions varied between themselves underscoring the importance of model choice and of using ensembles.

Urban green infrastructure (UGI) is a prominent concept toward climate adaptation and urban resilience, but it is also affected by droughts and heat. Hence, this study aims to advance the multi-assessment of drought and heat risks (DHRs) for UGI through the DHR assessment framework with conceptual and methodological features, paving the way toward knowledge creation and decision support. The framework was systematically developed, starting with defining the situation, analyzing concepts, and finally, constructing the framework. The situation is interpreted as a coupled human and natural system to represent the biophysical and immaterial elements, processes, and interrelations. Further, the concepts of risk, UGI, and ecosystem services lead to a risk system showing the compound hazards, the exposure, and the cascading vulnerabilities of the UGI. The DHR assessment framework distinguishes two stages, multi-risk analysis and multi-criteria risk evaluation. The analysis includes the definition and interpretation of the UGI situation under drought and heat conditions, analyzing the hazards, exposures, and vulnerabilities of the system, and translating the risk system into an indicator-based information system. Hereby, the vulnerability analysis of the biophysical UGI aspects comprises the susceptibility and resilience of UGI entities, as well as the degree to which providing ecosystem functions and services can be affected. The multi-criteria risk evaluation covers the assignment of thresholds and weights for indicators, in addition to the aggregation methods. The resulting framework intends to support local actors in the risk assessment of current and future conditions, fostering evidence-based decisions and interventions to deal with compound DHRs.

This study validates a novel structural reliability method, particularly suitable for high-dimensional green energy harvesting device dynamic systems, versus a well-established bivariate statistical method, known to accurately predict two-dimensional system extreme response contours. Classic reliability methods dealing with time series do not always have an advantage of dealing easily with dynamic system high dimensionality, along with complex cross-correlations among different system components. Energy harvesters constitute an important part of modern offshore green energy engineering; hence, proper experimental study along with safety and reliability analysis are of practical design and engineering importance. To study the performance of galloping energy harvesters, a series of laboratory wind tunnel tests have been conducted, selecting different wind speeds. This study illustrates the usage of the advocated novel reliability method, by analyzing bivariate statistics of experimental galloping energy harvester's dynamics. The bivariate statistics was extracted from available experimental results, more specifically for the device's voltage-force dataset. Advantage of the proposed methodology being that relatively short experimental data record may still yield meaningful design results, provided proper statistical methods have been applied. Safety and reliability are important engineering concerns for all kinds of green energy devices. In the case of measured device's structural response, an accurate prediction of system failure or damage probability is possible, as illustrated in this study. Distinctive advantage of advocated novel semi-analytical reliability methodology being the fact that it can tackle dynamic systems with practically unlimited number of dimensions (or components), along with complex nonlinear cross-correlations between different system key components.

Every human needs sufficient, safe, and nutritious food to live an active and healthy life. Climate change, especially more frequent extreme climate events, increasingly affects crop yields. Unpredictable losses in crop production pose a high risk to our food systems, thus threatening agricultural producers and consumers worldwide. This study analyzes the effect of climate change on wheat, maize, and barley yield anomalies for the major producing countries in the EU. Applying the Random Forest machine learning model, climate indicators, comprising mean and extreme climate conditions, explain 18% of crop yield anomalies across crops and countries from 1961 to 2020. The predictive power of climate indicators is highest for maize with 24%, followed by barley with 22% and wheat with 3%. However, mean climate indicators are stronger associated with crop yield anomalies than extreme climate indicators. Temperature- and soil moisture–related indicators are more important than precipitation-related indicators. The results reveal a nonlinear relationship between climate indicators and crop yields. Thresholds lead to a sharp decrease or increase in crop yields. Under SSP3-7.0, rising temperatures tend to increase crop yield losses until 2100 without effective adaptation measures. The impact of changing soil moisture–related indicators depends on crop and country. Our study discusses adaptation strategies but also emphasizes the relevance of global mitigation efforts to reduce climate-induced crop risk and to improve our food system's resilience.

A major limiting factor affecting the uptake of conservation agriculture practices in smallholder farming systems in sub-Saharan Africa is the limited availability of sufficient crop residues for use as surface mulch. This paper assesses the trade-offs in crop residue utilization among smallholder farmers and its implications for soil management in the face of climate change risks in northern Ghana. The paper triangulated data from 350 household surveys with participatory key informant interviews from seven selected communities in three districts of northern Ghana. The problem confrontation index (PCI) was adopted to identify and rank the challenges associated with farmers’ decision to use crop residues, while a multivariate probit model was used to analyse and predict the factors that influence farmers’ choice of crop residue management practices. Results showed that crop residues were used as cooking fuel in households (21%), livestock feed (21%), left on the farm to decompose as mulch (34%) or burned to clear the land (24%). Key challenges identified included high labour cost (PCI = 404), high labour intensity (PCI = 388), the cost and transport for collection and storage of externally sourced crop residue (PCI = 383) and the low benefit from crop residue to farm output/soil fertility (PCI = 339). Results from the multivariate probit model revealed that household and farm variables, institutional and socio-psychological factors, and experience of some climate shocks all influence farmers’ choice of crop residue management practices. Crop residue use and management practices adopted were determined by factors including the crops being grown, challenges faced by farmers and the management options available. The study recommends the need for the Government of Ghana to empower farmers through the provision of technical knowledge and machinery for the sustainable utilization of crop residues due to the high labour intensity and cost associated with such practices.

This paper reviewed a body of literature on climate adaptation options in sub-Saharan Africa's (SSA) smallholding agriculture and complemented it with a case study involving experts interviews, focus group discussions, large-scale household surveys, and farmer practices observation while drawing insight from the concept of “everyday adaptation and interrupted agency” and agency theory to assess farmer perceived limitations with climate-smart agriculture (CSA) and climate-wise food systems (CWFS) practices for climate adaptation in the SSA. The study noted that the narrow focus on CSA and/or CWFS as a silver bullet for climate change adaptation suitable for smallholding agriculture ignores food producers’ agency to undermine sustainable and inclusive adaptation solutions. Moreover, smallholder farmers’ everyday climate adaptation practices could be grouped into three categories; on-farm adaptation, off-farm adaptation, and Indigenous agroecological adaptation options. The on-farm adaptation options are usually agriculture intensification and extensification. The off-farm adaptation options include livelihood diversification activities, petty trading, seasonal labor jobs, and migration. The Indigenous agroecological adaptation strategy uses observing nature and weather elements to predict the onset of the rainy season. The study noted that smallholders’ adaptation options, which is an expression of their agency, are motivated by smallholders’ desire to be resilient to changing climate, increase productivity and income, and social network influence but not necessarily because the strategy is being promoted by the government or Non-Governmental Organizations (NGOs). Therefore, we propose a sustainable food agency (SFA)—a multifaceted blended constellation of climate adaptation and mitigation strategies, as the best approach to addressing the climate crises in the SSA. The SFA allows individuals or groups to decide what climate change adaptation options best work for them to adapt to changing climate and produce and distribute their food without undermining the economic, social, and environmental bases that generate food security and nutrition for present and future generations.

Climate vulnerability could be influenced by transforming demographic, technological, cultural, political and economic factors, which cuts across global, regional, national and local scales. Such social transformations result in positive and negative outcomes, with implications for the adaptive capacities of resource-poor households, especially those headed by women. However, these transformations are usually not integrated in climate vulnerability assessments. Based on insights from a stakeholders’ brainstorming workshop and the synthesis of information from traditional literature review, this paper contributes to better understanding of the intersections of social transformation with climate vulnerabilities in the Upper West Region of Ghana. The review indicates that the region is experiencing social transformation triggered by technological, demographic and cultural factors, with implications for climate resilience building. For example, compared to the last decade, there is now an increased use of mobile phones, resulting in improved access to e-extension and climate-smart agriculture services. At the same time, an emerging trend of land commodification is driving poor households to sell or lease farming lands. Within the context of these transformations, climate vulnerability is still assessed through approaches that mainly focus on a ‘static’ view of the extent of exposure to climate hazards and their impacts on rural livelihoods. A social transformation analysis that promotes a systematic investigation of the transforming factors is proposed as an effective approach for vulnerability assessment in climate adaptation planning. This approach provides critical reflections on, and sustainable resilience interventions for addressing both changing biophysical and social vulnerabilities of rural communities.

Current discourse relating to climate change, conflict, migration (CCM), and the causal links thereof, is polarized. It is widely acknowledged that climate change will have a detrimental effect on quality of life, and that this impact will not be homogeneous across the globe. However, proposed causal links among CCM remain contentious. This paper argues that to better grasp the implications of climate change on global society and security, it is vital to develop a more systemic understanding of the interplay among CCM. Although this nexus is already recognized, studies to date have tended to be qualitative and statistical evidence of multivariate causality has been lacking, where quantitative analysis is present, it has typically been limited to two components at a time; few studies have addressed the nexus holistically, making research conclusions sometimes difficult to reconcile. Hence, by reviewing literature from a broad range of sources, this paper suggests a suite of systemic and quantitative approaches with which to address the CCM nexus. This review critically assesses the existing research approaches employed across a range of examples and suggests how leveraging the power of ‘big data’ and modelling the nexus as a complex system encapsulating both human and environmental drivers could offer new insights, especially for those looking to explore the increasing number of ‘what if’ scenarios relating to climate and human dynamics.

Greenhouse gas (GHG) emissions have increased globally 10% in the last decade, but there is a large variation in emissions trajectories by country. Understanding the main drivers of recent changes in GHG emissions is important to guide effective climate action. Using a narrative scoping review of academic literature, we access 648 abstracts and review 30 studies to identify statistically significant independent variables that were associated with GHG emissions nationally and multinationally (i.e., in country groupings) during or overlapping the period 2010–2019. We describe the findings in terms of potential reasons for the positive or negative associations, outline the strength of associations relative to other variables within the same study, and compare the associations to findings in other studies. We find that population, energy consumption, and gross domestic product (GDP) per capita are the most common independent variables associated with increases in GHG emissions, whereas the square of GDP per capita and renewable energy production are associated with GHG reductions. We assign GHG drivers to seven categories: economic, energy, demographic, technology innovation, transportation, policy, and others. We conclude by discussing implications for future research and climate policy.

Climate change is causing serious challenges for smallholder farm households, especially in sub-Saharan Africa. The overarching objectives of this study are as follows: (i) to estimate household resilience and vulnerability indices, (ii) identify factors that explain these indices and (iii) to examine the impact of climate-smart agriculture (CSA) on households’ resilience and vulnerability, and (iv) to identify which CSA package performs better in enhancing resilience and reducing vulnerability. For this study, 278 farm households from 4 districts and 8 kebeles from the Central Rift Valley (CRV) of Ethiopia were randomly selected using a three-stage proportional to size sampling procedure. Cross-sectional data applying a structured and pretested survey questionnaire was collected for 2020/21 production season. Household resilience and vulnerability indices were estimated using resilience index and measurement analysis and indicators approaches, respectively. Multinomial endogenous switching regression was used to estimate the average treatment effects (ATEs) of the adoption of CSA practices on households’ resilience and vulnerability. The results show that livestock holding, land size, level of education, and state of food consumption are major explaining factors of resilience, whereas educational level of households, livestock holding, and access to credit are found to be major factors explaining vulnerability. The estimated ATEs indicate that households which adopted more diversified combinations of CSA packages were more resilient and less vulnerable than non-adopter households. The impacts of soil fertility management and conservation agriculture practices have better performance in improving resilience, whereas conservation agriculture and small-scale irrigation performed better in reducing the vulnerability of rural households in CRV. Boosting resilience and reducing vulnerability, hence, requires scaling up CSA among smallholder farmers by diversifying and raising farm households’ income, educational status, and livestock holding.