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The analysis of vulnerability of socio-ecological systems to threats of different types such as extreme climate events or change in land use draws attention to the factors and processes that determine whether the ecological, social and integrated socio-ecological systems are likely to experience harm due to exposure to the threat. During the last years there has been an increasing attention to the analysis of the vulnerability of socio-ecological systems when facing the lost or degradation of ecosystem services. However, despite the existence of conceptual frameworks and empirical applications to evaluate vulnerability of socio-ecological systems some open questions and challenges still remain. How to conceptually differentiate key concepts such as sensitivity, exposition, vulnerability and threat? How to consider the differences in socio-economic characteristics of the beneficiaries and in their capacity to adapt to new conditions of the ecological system? How to link ecological vulnerability with the social system analysis to obtain an integrated risk assessment of the socio-ecological system? This paper presents a conceptual framework for vulnerability assessment of socio-ecological systems that addresses the mentioned open questions based on a review of both theoretical and empirical literature related to vulnerability and socio-ecological systems. The paper identifies the attributes and indicators of the dimensions of vulnerability for understanding both the social vulnerability and ecological vulnerability separately and then jointly, in interaction with each other. The framework offers a way to communicate with practitioners and policy makers on identifying and improving the factors that reduce vulnerability. It can thus serve as a tool for targeting the implementation of policies and practices aimed at reducing vulnerability. [ABSTRACT FROM AUTHOR]

Understanding human and climate-induced vegetation changes could benefit regional ecological management. In this paper, a framework was established to quantify the relative contribution rates of human and climate factors to vegetation changes in Chongqing, China, from 2000 to 2015. MODIS NDVI time series data were collected, and land use data were produced using Landsat TM/OLI images. A combined analysis of land use and vegetation changes was conducted, and the residual trends method (RESTREND) was explored in the framework. The results showed that Chongqing experienced a significant vegetation increase from 2000 to 2015. The relative contribution rates of human activities and climate to the vegetation changes were 90.96% and 9.04%, respectively. These results indicate that human activities had a dominant role in vegetation restoration in Chongqing in 2000–2015. Throughout the study period, extensive land use changes occurred in Chongqing. During the study period, persistent forested land, farmland-forested land (a land use conversion type), persistent farmland, and grassland-forested land were the four most important land use (changed and unchanged) types attributed to the growing season NDVI (GSN) increases in Chongqing from 2000 to 2015. The contributions of these four land use types were 45.03%, 21.19%, 16.79% and 12.60%, respectively. The farmland-forested land was characterized as the most effective land use conversion type for vegetation restoration. The proposed framework allows for human and climate-induced vegetation changes to be quantitatively distinguished at the regional scale and provides the contribution rates of each changed and unchanged land use type. The framework is expected to be useful for regional ecological management and research. [ABSTRACT FROM AUTHOR]

Abstract: Soil is one of the most important and most complex natural resources, but current developments (urbanisation, erosion and climate change) increasingly threaten this valuable resource in Europe and worldwide. The main objective of this paper is to introduce how changes in soil quality were modelled in the SENSOR project through two indicators: soil carbon content and soil water erosion. Indicators were calculated using state variables and model variables that were mainly derived from the CLUE model which predicts land use change in response to policy scenarios. In the case of erosion, accuracy of the calculations was evaluated by comparing GIS data with the results of the PESERA project. The PESERA and SENSOR models predicted comparable soil loss for the first year in the NUTS-X regions of Europe that were analysed. The higher resolution national soil-loss prediction USLE map largely overestimated the amount of soil loss compared to the PESERA and the SENSOR models in the NUTS-X regions of Hungary. This discrepancy may result from technical or methodological differences such as the spatial reference framework (NUTS-X regions), spatial resolution or levels of data aggregation. The soil organic carbon loss predictions for the NUTS-X regions of Europe are displayed on maps and background data are given in tables. The greatest decreases in soil carbon content may be expected in some regions of Poland, Latvia, Lithuania, south-eastern UK and eastern Germany. The greatest increases in soil carbon content may be expected in central and eastern parts of the UK, in Ireland, in northern and central Sweden and Estonia, in Greece, in central and southern Italy, in the island of Sardinia and in some regions of Spain. As erosion strongly reduces soil productivity these predictions have not only environmental but also socio-economic implications. The results presented in this paper could be used at EU level to locate regions where negative changes in soil quality can be expected. [Copyright &y& Elsevier]

[Display omitted] • Past LULC changes can be divided into two stages: (I) accelerated evolution stage (1980–2010), and (II) stable evolution stage (2010–2020). • Carbon storage presented a high-low-high distribution pattern from north to south. • Areas with a rapid urbanization process exhibited more obvious changes in carbon storage dynamics. • Rapid LULC dynamics have reduced the carbon sequestration capacity of the ecosystem. • The implementation of ecological conservation could increase the carbon fixation in ecosystems. Land use/land cover (LULC) change has greatly altered ecosystem carbon storage capacity and can eventually profoundly impact global climate change. Characterizing the LULC change and its impact on ecosystem carbon storage in coastal areas is greatly significant to comprehensively understanding the influences of human activities on ecosystems. Based on LULC data, this paper combined CA-Markov and InVEST models to evaluate the past, present, and future LULC change and its impact on ecosystem carbon storage in coastal areas of China. The results showed that past LULC change in coastal areas can be divided into two stages: (I) accelerated evolution stage (1980–2010), and (II) stable evolution stage (2010–2020). Changes in LULC types have led to a downward trend in ecosystem carbon storage, with a cumulative loss of 0.39 Pg and 0.15 Pg during the two stages, respectively. Spatially, carbon storage presented a high-low-high spatial distribution pattern from north to south. Temporally, areas with a rapid urbanization process exhibited more obvious changes in carbon storage dynamics. Compared with the natural change scenario, the areas with LULC types conversion under the ecological conservation scenario in 2050 will be lower due to the limitation of ecological protection, and it caused carbon storage reduction will slow down. Rapid LULC dynamics, that a large area of farmland, unused land and, water have been converted into construction land, reduced the carbon sequestration capacity of the ecosystem. This study will provide reliable references and precise data support for coastal management and decision-making. [ABSTRACT FROM AUTHOR]

Abstract: Upland waters are located upstream of the areas of direct human disturbance and intensive land use through industry, agriculture and urbanisation and are valued particularly as sources of potable water and as biodiverse freshwater habitats. Nonetheless, the impact of human activity can be detected even in some of the most remote lakes on the planet due to the effects of long-range transport of air pollutants and global climate change. In the UK, upland waters are threatened by a range of pressures including not only atmospheric deposition of acidic compounds, trace metals and organic pollutants, but also climate change, nutrient enrichment by deposited nitrogen and changing land-use or land management regimes. The threat from acid deposition has declined sharply since the 1980s but its legacy remains a major concern; recovery is taking place but even assuming a complete chemical and biological recovery to a pre-industrial baseline were possible, dynamic models suggest that this could take another 100 years. However, current climate change projections suggest that by then, UK upland waters will become much warmer, with lower summer streamflows, higher winter streamflows and a much reduced or even absent influence of snowfall and lake ice-cover. Hence there is no rationale for aspiring to the return of pre-industrial “reference” conditions because climate change is likely to shift the climatic baseline at an unprecedented rate. Meanwhile, expansion of forest planting, changing grazing regimes and management measures for peatland restoration, among other land-use pressure, will affect upland catchments in the UK with potentially major repercussions for aquatic ecosystems, both positive and negative. The challenge for scientists, policymakers and other stakeholders in the uplands is to determine not only the trajectory of change in upland waters, but also to define the ecological endpoints needed to provide the optimum range of ecosystem services for society. Integrated monitoring of the kind exemplified by the papers in this volume is a fundamental prerequisite in this regard. [Copyright &y& Elsevier]

Abstract: The paper presents the use of indicators in a site-specific assessment method for strategic environmental assessment in regional land use planning (here: SEA-REP). It is explained with the example of the state of environment indicator ‘LUCCA 4—Urban Areas at Risk of Flooding’, how SEA as a decision-aiding instrument can contribute to the prevention of conflicts with policy for adaptation to climate change. The method begins with the determination of impact factors for SEA. In the presented study, the physical impact factors of land consumption, land use change, and directed flooding were recognised. A core problem during the selection of indicators for land uses for the adaptation to climate change (here: LUCCA) and the derivation of assessment thresholds was a lack of region-wide policy objectives for the protection of land and resources. Therefore, in a second step, regional environmental orientation objectives were derived from national and EU environmental policy. A standard method for the selection of LUCCA indicators and the derivation of assessment thresholds for conflict analysis is described. Three classes of conflict classification for regional plan designations on the individual site are proposed. It is recommended that future adaptation measures of regional land use planning should be designations of specific land uses as priority areas for urban areas prone to flood risk. [Copyright &y& Elsevier]

• The crop yield deviations are more susceptible to change in temperature. • The level of climate change induced risk amounts to 1.3-5.3% of the average yields. • The risk leads to a considerable change in cropland use in Chinese farms. • Changing cropland use structure is an effective strategy of mitigating the risk. This paper estimates the climate change induced risk for 14 crops measured by the yield deviation using the panel data from seven counties in Jiangsu province in China from 1998 to 2017, and then investigates the risk effect on cropland use in a representative farm using the survey data and the MOTAD model. The results show that the crop yield deviation are more susceptible to change in temperature than that in sunlight and precipitation. The crop-specific risk level amounts to 1.3–5.3% of the average yields. The risk leads to reducing the cultivated areas by 6% and also causes a significant change in cropland use. As an effective adaptation strategy of mitigating the climate change induced risk, the farms should reduce the total cultivated area by about 15% in comparison with the observed situation while the cropland use structure should be adjusted accordingly. More cropland should be allocated to wheat, peanut and cotton but the other crop areas should be reduced or maintained. [ABSTRACT FROM AUTHOR]