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• We incorporate spatial factors affecting carbon emissions as drivers into the RF-CA model. • We change the constraints in the CA model for land use change prediction. • We predicted the land use change of Shanghai in 2025 under a low-carbon scenario. As global climate change intensifies, climate protection is important for the sustainable development of human society. In the process of urbanization and industrialization, carbon dioxide emissions are an important factor contributing to global warming. Therefore, modelling projections of future urban land use under low-carbon scenarios are essential for sustainability policy development. Few studies have focused on the impact of carbon emissions on urban land use change in Shanghai, as current research has primarily concentrated on developing methods for urban land use modelling. This paper utilizes a cellular automata (CA) simulation model based on the Random Forest (RF) algorithm to select various spatial variables of carbon emissions as the driving factors that affect urban land use changes. These variables include traffic location factors, economic development factors, electricity consumption, and population density. In this study, remote sensing imagery of urban nighttime lighting is also used to construct a simulation model of land use types in Shanghai. The model is then used to analyze the contribution of carbon emission constraints to urban land use changes. Actual historical land use data from 2013 and 2019 are used for validation, and the prediction model is used to predict land use outcomes under different low-carbon scenarios in 2025. The model is validated by simulating multiple intra-city land use maps for 2019 (kappa = 0.88, OA=92.71 %). The method of out-of-bag error from the random forest is used to evaluate the significance of carbon emission constraints. Using the validated model, the constraints in the CA model are changed to predict the land use simulation results of Shanghai in 2025 under different low-carbon scenarios. In terms of significance, factors such as distance to power plants, distance to major roads, real GDP, and population density can all have a significant impact on changes in urban land use. By selecting the low-carbon scenario with the most appropriate thresholds for each driver, it is possible to obtain the land use simulation results of Shanghai in 2025 under the optimal low-carbon scenario, while ensuring the high accuracy of the RF-CA model and simultaneously reducing the impact of factors on the city's overall carbon emissions. This paper provides a scientific base for urban planners and scholars to thoughtfully design urban land use while cutting down on carbon emissions. Furthermore, it can aid government agencies in establishing associated planning approaches. [ABSTRACT FROM AUTHOR]

• Literature review papers related to the tourism-energy nexus are analyzed. • Four main groups are identified considering the quantitative methodology used. • Topics and discussions on the nexus between tourism and energy are developed. • Future research is discussed. The high dependence of tourism activities on energy consumption, and particularly on non-renewable energy, is a major barrier to building sustainable tourism models. For this reason, the analysis of tourism and energy use is a growing field of study within sustainability debates. Despite this, there is a gap in the literature and, to the best of our knowledge, there is no previous study that critically reviews the vast literature on the energy-tourism nexus. This paper aims to fill this gap in tourism knowledge. The main objective of this article is to conduct a systematic review of scientific studies with a quantitative empirical basis that examine this nexus, trying to answer the following questions: What are the main methodologies used to approach the tourism-energy nexus? which indicators or variables are relevant?; is there a consensus on the results?; and what are the main lines of discussion on the use of energy in tourism? To this end, we particularly focus on the main methodologies, results and perspectives during the period 2001–2021. A total of 1,189 articles were reviewed by abstract and title, 236 were included for the full review and 163 were finally selected. The results show how the nexus and energy dependence of tourism is assessed mainly from four major methodological groups: G1) econometric models, regressions and other statistical methodologies (67% of the sample); G2) surveys, questionnaires and energy audits (15%); G3) Life Cycle Analysis (13%) and G4) other approaches and environmental impact indicators to assess the relationship between energy and tourism (5%). The analysis between the causal relationships between tourism development, economic growth, energy use, environmental degradation and energy efficiency of accommodations are the main issues evaluated, considering a wide range of indicators/variables. Based on the gaps and limitations found in the literature review on tourism and energy, it is discussed how some findings should be interpreted with caution due to their methodological approaches and differences. Finally, some of the main lines of future research in this field are also presented. [ABSTRACT FROM AUTHOR]

• Framework to quantify collective and individual impacts of climate change and human activities on hydrological regimes. • Climate change and human activities have opposite effects on minimum flow and pulse indicators in the Ganjiang River bBasin. • Climate change and human activities exhibit a substantial synergistic effect on multiple aspects of hydrological regimes. Previous research rarely identified the synergistic effects of climate change and human activities on hydrological regimes, thus leading to an incomplete attribution of hydrological regime changes. To address this issue, this paper presents a complete approach for accurately quantifying these impacts. The framework integrates various methodologies, including the runoff abrupt change point judgment method for distinguishing pre- and post-impact periods, The Soil and Water Assessment Tool (SWAT) is used to isolate runoff processes influenced solely by climate change, the linear separation method for identifying runoff processes affected solely by human activities, and the Indicator of Hydrologic Alteration (IHA) for quantifying changes in hydrological regimes. Application of this framework to the Ganjiang River Basin (GRB) unveils significant alterations in hydrological regimes. This has resulted in a significant decline in aquatic organism species compared to the prior-impact period levels. Notably, climate change and human activities exert opposing effects on minimum flow indicators and flow pulse indicators in the GRB. Moreover, these factors exhibit a substantial synergistic effect on numerous indicators, resulting in hydrological regimes combined influenced by climate change and human activities being considerably different with the cumulative impact on hydrological regimes solely influenced by climate change and those solely influenced by human activities. Consequently, in future water management, it is crucial to recognize the positive role of prudent human activities in mitigating the adverse impacts of climate change. [ABSTRACT FROM AUTHOR]

• This study develops a disaster risk index (DRI) for assessing disaster risks in coastal communities. • Logit Boost ML model was found the optimal model for this research. • Gabura had the highest DRI value of 0.09, ahead of Southkhali (0.06) and Banishanta (0.04) unions. • The study underscores the importance of evolving from traditional approaches to advanced data-driven tools. Communities in disaster-prone coastal areas are more vulnerable to socioeconomic, environmental, and ecological problems. Knowing how disaster-prone coastal communities are, and, ideally, their resilience against current disaster risks, is an essential first step in reducing consequences. Therefore, this study aims to develop a disaster risk index (DRI) for assessing disaster risks in three coastal communities in southwest Bangladesh. Five machine learning (ML) models and holistic approaches were adopted to conduct the analysis. This study utilized ML-based feature selection methods and considered hazard, exposure, and vulnerability components to identify the most influential indicators for evaluating disaster risk. The researchers systematically developed six distinct feature sets using filter-based feature selection methods. Five ML models then evaluate these sets to determine the optimal set of features. Evaluation metrics were used to validate the performance of ML models, such as accuracy, precision, F-measure, recall, and the receiver operating characteristics (ROC) curve. Based on the Logit Boost ML model, the optimal feature set (set 3) had the best accuracy (0.997), precision (0.997), recall (0.997), F-measure (0.997), and ROC (0.996) compared to other feature selection sets. According to the findings, Gabura had the highest DRI value of 0.09, ahead of the Southkhali (0.06) and Banishanta (0.04) unions. The study underscores the importance of evolving from traditional approaches to advanced data-driven tools to understand disaster risks. The paper's findings can provide policymakers in coastal areas with new insight into the disaster risk differences among the inhabitants, leading to more effective disaster management practices and risk reduction strategies. [ABSTRACT FROM AUTHOR]

• Experts discussed indicators of agricultural vulnerability in Sweden. • AgroExplore enables interactive exploration and validation of indicators. • Thresholds of agricultural vulnerability indicators are context dependent. • New indicators for agricultural vulnerability are required. • Aggregating data to administrative units is problematic for several indicators. Agriculture is often described as one of the sectors most vulnerable to future climate change, and its vulnerability is commonly assessed through quantitative indices. However, such indices differ significantly depending on their selected indicators, weighting mechanisms, and summarizing methods, often leading to divergent assessments of vulnerability for the same geographic area. The use of generic indicators might also lead to a loss of information about contextual risks and vulnerabilities. This may reduce the perceived usefulness of indices among stakeholders. This study analyses the role of indicators in assessing agricultural vulnerability to climate change. It analyses how indices are understood and used through three separate focus group sessions, involving agricultural experts professionally active in south-eastern Sweden. The paper presents how agricultural practitioners perceive a set of common vulnerability indicators, presented through a visualization tool, and their relevance, logic, and applicability to assess and address vulnerability to climate change. The results of this study contribute with perspectives on (i) the relevance and applicability of the commonly used generic indicators for agricultural vulnerability (ii) the assumed correlation of indicators with climate vulnerability and (iii) the identification of missing vulnerability indicators. The study finds that commonly used vulnerability indicators are perceived hard to apply in practice, as definitions and thresholds are often depending on the geographical and temporal scale, as well as the regional context. Additional exposure factors that were identified included extreme events, such as heavy precipitation and external factors such as global food demand and trade-patterns. Further, participants expressed that it is important to include indices that combine effects of multiple climatic changes and in-direct factors, such as policies, regulations and measures. Inherent complexities, context dependencies, and multiple factors should further be included, but entail difficulties in developing suitable indicators. These factors must be addressed by a broader set of qualitative and quantitative indicators, and greater flexibility in the assessment methodology. The interactive vulnerability assessments presented in this paper indicate a need for an integration of quantitative and qualitative aspects and how such indicators could be developed and applied. [ABSTRACT FROM AUTHOR]

Highlights • We divided the households in the YNL river region into three types. • We identified the determinants affecting the livelihood choice of sample households. • We made some policy recommendations to help the local people get rid of poverty. Abstract Governmental policies that can develop advantageous endogenous livelihood transition are of great importance for anti-poverty. However, the existing research finds that in the Tibetan Plateau, there is a certain contradiction between the poverty alleviation policies and the local farmers' needs, and thus the effect of these policies will be weakened and the goal of poverty alleviation be missed. It is therefore imperative to identify and analyze the factors influencing the livelihood choice so that policy makers and development practitioners can design policies that will tackle the poverty afflicting the majority of the local people. This paper provides a new method for anti-poverty policymaking and conducts a case study to enrich the safety net/cargo net paradigms. In this paper, household data in the YNL river region are used and a two-step clustering method is developed to classify these households into three types: hanging in (type I), stepping up (type II) and stepping out (type III). Then a multinomial logit model is adopted to identify determinants of households' livelihood choice. The results indicate that drought poses a significant negative impact on farmers' choice of type II, while household size, educational level of labor and medical expenditure have a significant positive impact on the choice of type II; spring frost, proportion of skilled training, borrowed money and the ratio of agricultural equipment have a significant positive impact on their choice of type III. Some anti-poverty policy implications are put forward in the last on the basis of these determinants. [ABSTRACT FROM AUTHOR]

• This paper aims at quantifying the factors affecting vegetation growth in the western of Inner Mongolia, and judging the relative contribution of natural factors and man-made factors. • It is obtained through geodetectors (GD) that Rainfall is the most important driving factor, with the q-value of 0.77 and GDP also having a huge impact on vegetation growth, q-value of 0.64. • Different from most studies, human activity also has a positive effect on vegetation growth. • The relative contribution of human activities reached 51.75%, slightly exceeding the influence of natural factors. Vegetation is an essential component of terrestrial ecosystems, and understanding the drivers of vegetation change is of great importance for ecological management. In recent years, vegetation growth has increased under the combined effect of global warming and human activities in Inner Mongolia. The net primary productivity (NPP) was used as an indicator to study the spatial and temporal changes in vegetation in the Qimeng Region (QR). The residual trend analysis method was used to analyze the relative contributions of climate variations (CV) and human activities (HA) to NPP changes across the QR, while their drivers were explored using a geographical detector approach to quantify the driving forces of NPP. The results show that (1) NPP exhibited a fluctuating growth trend from 2003 to 2020, with an overall growth rate of 2.91%/year. (2) Precipitation, GDP and population density were the dominant driving factors for the spatial distribution of NPP. The combined explanatory power of any two dominant factors exceeded the power of any dominant individual factor, and the interaction between climate and human factors had a significant effect on NPP. (3) The change in NPP was influenced by the combined effect of HA and CV, accounting for 37.69% of the total area, with the relative contribution of HA being 51.75%. Finally, the relative contribution of human activities was slightly higher than that of climate change, confirming the initial success of the Grain to Green Program as well as ecological conservation projects. This paper provides a scientific basis for the local government to carry out the conversion of cropland to forest. [ABSTRACT FROM AUTHOR]

Vulnerability of a socio-ecological system to one or more climatic hazards depends on climatic, geophysical, socio-economic and institutional factors. In addition, vulnerability is a scale- and place-dependent concept. While decision-making on adaptation is often made by local government, only a small number of local-scale assessments have been conducted. When indicators are used, global utility functions based on additive or multiplicative aggregation implicitly assume complete compensation between indicators, implying that one source of vulnerability (e.g., proximity to the sea) can always be compensated for by an advantage in another source (e.g., strong social or economic capital) when evidence shows that this is not always the case. This paper presents an indicator-based assessment of vulnerability of eight beaches in Shoalhaven, New South Wales, that are especially exposed to sea level rise. Its goal is twofold. First, it illustrates how indicator-based vulnerability assessments can be applied at a local scale – and not just sectoral, regional and national scales – with the aim of informing local government adaptation planning and resource allocation. In the process, models operationalising the concepts of exposure, sensitivity and adaptive capacity are developed for two valued attributes identified through discussions with the local council, namely the well-being of beach residents and the well-being of users of infrastructure systems located at the beaches. Second, the paper studies, for the first time, the way outranking procedures can be applied in real-life vulnerability assessments as a form of data aggregation that better reflects the non-compensatory nature of many vulnerability indicators. The strengths and weaknesses of the outranking approach are discussed, especially the extent to which the concepts of preference, indifference and dominance thresholds can be conveyed to, and their values elicited from, stakeholders. [ABSTRACT FROM AUTHOR]

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]

The earth’s climate system is highly nonlinear and the vulnerability of a community to a climate hazard is no exception. While this fact is widely accepted, indicator-based vulnerability assessments (IBVA) hardly ever take such nonlinearities into account. This is mainly due to the fact that the majority of assessment studies use methods based on Multiple Attribute Utility Theory (MAUT) (e.g. simple additive weight or multiplicative aggregation) to aggregate indicators. These methods convert all indicators into a global utility function and produce only a linear, threshold-free scaling of the effects of an indicator on vulnerability. In a previous paper, we showed that outranking procedures developed in decision-making science offer a more theoretically-sound approach to aggregation because they allow the analyst to incorporate the incommensurability, fuzziness and uncertainty associated with indicators. In this paper, we develop a new mathematical framework for vulnerability in order to clearly identify various sources of nonlinearity and incommensurability in vulnerability assessments. We then propose a new outranking formulation which can accommodate both and can be used to conduct assessments at different scales. We do so by introducing the concept of harm criterion as a mediator between an indicator and the vulnerability it represents. The new assessment approach can aggregate a mix of indicators with various degrees of subjectivity and non-linearity, without converting them into a single utility function and without requiring them to be mutually compensating. We illustrate the proposed approach by applying it to a simplified model of urban vulnerability to heat, focusing on the non-linear relationship between mortality and temperature above a ‘comfort temperature’, long evidenced in the epidemiological literature. We compare vulnerability rankings yielded by linear and non-linear characterizations of the relationship between temperature and mortality and find that the incorporation of non-linearity can have a significant impact on the rankings. [ABSTRACT FROM AUTHOR]

One proposed strategy to solve current environmental challenges is industrial and urban symbiosis (I/UrS); however, appropriate evaluation methods are needed so that the potential benefits of I/UrS can be quantified. Several evaluation methods have been applied separately to study I/UrS, but no integrated studies have been conducted by applying different methods in the same case study area. Therefore, this study aimed to establish a comprehensive framework to evaluate I/UrS by combining the material flow analysis (MFA), carbon footprint (CF) and emergy methods. First, we developed a unified database and step-by-step process to clarify the waste distribution and recycling processes in an industrial city. Then a baseline scenario and an I/UrS scenario were set up to define the baselines and effects of I/UrS and compare the results. Finally, the three methods were applied to identify physical features in the I/UrS system. The MFA-based results showed that the use of I/UrS led to a 6.4% reduction in the physical value of material use. The CF-based results indicated that reduction of waste and by-products results in a 13.8% reduction in CO 2 e emissions. The emergy-based results showed that, with the implementation of I/UrS, the value of the emergy sustainability index (excluding labor and services) improved greatly (a 49.2% emergy reduction) as compared with the baseline case (a 14.3% reduction). In addition, the effects of implementing I/UrS by waste and by-product exchanges for blast furnace slag, scrap steel, waste paper, and waste plastic were evaluated. Whereas the CF reductions of unit ton of blast furnace slag is relatively low, emergy reductions of that is comparatively high. If policymakers only consider CF results when addressing the issue of climate change, the effects on emergy will be underestimated in this case. We conclude that the main actors in this area release huge emissions, but they also have a high potential to reduce their environmental loads. In addition, with appropriate designs, waste paper and plastics recycling could be highly efficient. Finally, the integration of the three evaluation methods should contribute to creating a low carbon and more resource independent society. [ABSTRACT FROM AUTHOR]

• This paper aimed to investigate the interactions between land use cover (LUC) and climate change (CC). • The results showed that the interactions between LUC and CC are both direct and indirect. • Arable and rangeland use changes affect CO2 emission in both direct and indirect ways. • Rising rangelands and reducing forest areas have indirectly increased surface temperature. • CC mitigation policies should be followed by considering both direct and indirect effects. Humanity deals with several challenges in this century such as climate change, land use, and land use/cover change (LUCC). Determining the patterns, developments, and consequences of LUCC issues for the livelihoods of people, especially poor people, is very important. Therefore, this paper aims to investigate the interactions between LUCC and climate change over the period of 1966–2015 (50 years) as a complex system at the global level. CO 2 emissions and surface temperature are considered as the main indicators of climate change (CC). The data were analyzed in time-oriented (time-based) and local or place-oriented (country-based) manners. The results showed that arable and rangeland use changes (LUC) affect CO 2 emissions in both direct and indirect ways. However, the direct effect of rangeland use change is positive, and its indirect effect is negative. In addition, deforestation has increased CO 2 emissions indirectly. LUCC can also change the ability of the ecosystem to deliver services to people, including biodiversity and other resources such as food, fiber, water, etc. Therefore, it is critical to determine the patterns, trends, and impacts of LUCC on CC. Thus, CC mitigation policies should be followed by considering both direct and indirect effects. Without a doubt, this will be realized when the decision and policymakers have a better understanding of the structure and interaction between CC, LUCC, and their components as a whole system. [ABSTRACT FROM AUTHOR]

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

• Collections of basic research for urban spatial planning. • Literatures of urban agglomerations, urban size, urban compactness, and urban form on carbon emission. • Urban spatial structure and carbon emissions research from a multi-ecosystem interaction framework. Carbon emission reduction is one of the key factors in global climate change and should be an important component in urban planning and management. A full understanding of the relationship between carbon emissions and urban spatial structure is necessary. This paper presents the research on this relationship from the perspectives of urban agglomeration, urban size, urban compactness, and urban form. The results revealed that: (1) there is still a lack of research on the spatial structures of urban agglomerations and their relationship with carbon emissions, so it is urgent to conduct indicators system design and empirical research; (2) two-dimensional indicators have frequently been used to describe urban form and urban compactness, but three-dimensional indicators, such as volume ratio and floor height, are also important indicators for policymaking; (3) higher urban complexity, irregularity, and fragmentation were believed to contribute to urban carbon emissions because of the lack of continuity and connectivity. This paper also proposes a comprehensive analytical framework for examining urban spatial structures and carbon emissions. We position the research on the relationship between urban spatial structure and carbon emissions as a bridge between human ecosystems and natural ecosystems. [ABSTRACT FROM AUTHOR]

The concept of resilience is increasingly used in academic and policy circles. To operationalize this concept and reduce the ambiguities surrounding it, since the turn of the century, various resilience assessment methodologies have been introduced. This paper provides a critical review of 36 selected community resilience assessment tools. These tools have been developed by a variety of entities, including national and local organizations, international donor organizations, and academic researchers. First, an overview of the selected tools is presented. This overview analysis shows that while some commonalities exist, there are also considerable differences between the tools. Next, based on literature review, an analytical framework is developed that identifies six criteria for evaluating performance of resilience assessment tools. These are, namely, addressing multiple dimensions of resilience, accounting for cross-scale relationships, capturing temporal dynamism, addressing uncertainties, employing participatory approaches, and developing action plans. Results show that limited success has been achieved in addressing these criteria. In terms of comprehensiveness, the environmental dimension has received relatively less attention in spite of its significance for building community resilience. Further improvements are needed to account for dynamics over time and across space. More attention to employing iterative processes that involve scenario-based planning is needed to better address challenges associated with uncertainties. Results also show that more attention needs to be paid to stakeholder participation in developing assessment tools. The paper concludes by highlighting several other areas of weakness that need to be addressed and discussing major challenges that still remain. [ABSTRACT FROM AUTHOR]

The UK Environmental Change Network (ECN), the UK's Long-Term Ecosystem Research (LTER) network, has now been operating for over twenty years. It was established in 1992 as a set of terrestrial sites at which sustained observations relevant to a range of ecological indicators and environmental parameters could be made. An additional ECN freshwater network was launched in 1994. In this paper we provide a brief history of the network, and describe its current structure and role within a complementary wider range of UK environmental monitoring and observation programmes that are either more focussed on specific parameters or habitats, or operate at different temporal and spatial scales. We then provide a review of the other papers within this Special Issue, which exemplifies the broad range of environmental concerns that ECN data and sites are helping to address. These include network-wide summaries of environmental and biological trends over the first two decades of monitoring, more site-specific assessment of the ecological impacts of local pressures resulting from changes in management, biological and ecosystem service indicator development, and the testing of new monitoring technologies. We go on to consider: (i) future directions of network development and adaptation in light of recently emerging environmental concerns, dwindling financial resources and the consequent need for greater efficiency; (ii) the desire for tighter integration with other monitoring and observation programmes both nationally internationally; (iii) opportunities raised by recent technological developments; and (iv) the need to process and make available data more rapidly to increase the capacity of ECN sites as early warning systems. In its first two decades of operation the ECN has accumulated a robust set of baseline data that describe environmental and biological variability across a range of habitats in unprecedented detail. With appropriate, informed development, these should prove invaluable in discerning the causes and consequences of environmental change for decades to come. [ABSTRACT FROM AUTHOR]

Indicator species (IS) are used to monitor environmental changes, assess the efficacy of management, and provide warning signals for impending ecological shifts. Though widely adopted in recent years by ecologists, conservation biologists, and environmental practitioners, the use of IS has been criticized for several reasons, notably the lack of justification behind the choice of any given indicator. In this review, we assess how ecologists have selected, used, and evaluated the performance of the indicator species. We reviewed all articles published in Ecological Indicators (EI) between January 2001 and December 2014, focusing on the number of indicators used (one or more); common taxa employed; terminology, application, and rationale behind selection criteria; and performance assessment methods. Over the last 14 years, 1914 scientific papers were published in EI, describing studies conducted in 53 countries on six continents; of these, 817 (43%) used biological organisms as indicators. Terms used to describe organisms in IS research included “ecological index”, “environmental index”, “indicator species”, “bioindicator”, and “biomonitor,” but these and other terms often were not clearly defined. Twenty percent of IS publications used only a single species as an indicator; the remainder used groups of species as indicators. Nearly 50% of the taxa used as indicators were animals, 70% of which were invertebrates. The most common applications behind the use of IS were to: monitor ecosystem or environmental health and integrity (42%); assess habitat restoration (18%); and assess effects of pollution and contamination (18%). Indicators were chosen most frequently based on previously cited research (40%), local abundance (5%), ecological significance and/or conservation status (13%), or a combination of two or more of these reasons (25%). Surprisingly, 17% of the reviewed papers cited no clear justification for their choice of indicator. The vast majority (99%) of publications used statistical methods to assess the performance of the selected indicators. This review not only improves our understanding of the current uses and applications of IS, but will also inform practitioners about how to better select and evaluate ecological indicators when conducting future IS research. [ABSTRACT FROM AUTHOR]

This paper addresses the use of impact indicators with respect to climate change in the 2007–2013 Rural Development Programme (RDP) of the European Union, with particular reference to the Scotland Rural Development Programme (SRDP). It concludes that the policy context has highlighted the need for the rural land use sector to respond to climate change but that the associated Common Monitoring and Evaluation Framework (CMEF) did not develop suitable indicators to assess the impact of SDRP measures on GHG emission mitigation. It suggests improved impact indicators based on the relationship between rural land use and greenhouse gas (GHG) emissions: first, an indicator based on net GHG emissions per holding; and a second based on net GHG emissions per unit volume of output. The paper points out the challenges in measuring land-based emissions accurately. It further proposes screening of RDP measures to ensure that climate change mitigation impacts are properly appraised. It is recognised that climate change policy in relation to rural land use is still at an early stage of development but greater sophistication of policy instrument design and evaluation will be required if the RDP is to contribute significantly to climate change policy objectives. [ABSTRACT FROM AUTHOR]

• Vegetation response to drought can be inferred from correlating VAI and SPEI. • The strongest accumulation period for vegetation response is 6–8 months. • Trees and irrigated cropland are the least sensitive to drought. • Shrubland and rainfed cropland show the most sensitivity to drought. • The cumulative climate has a higher impact on vegetation than lag effects. Drought caused by climate change has significantly increased vegetation vulnerability in Afghanistan during the last decades. This paper investigates vegetation response to drought at multiple scales across the country based on historical data from 1980 to 2020. It explores the multiscale relationships between drought as indicated by the grid-based standardised precipitation evapotranspiration index (SPEI) and vegetation condition as represented by the satellite-derived vegetation anomaly index (VAI). It also examines the links of dominant land cover with drought and their implications for agriculture. We assess the spatiotemporal correlations by integrating TerraClimate grids with timeseries data sourced from NOAA AVHRR (National Oceanic and Atmospheric Administration Advanced Very High-Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer) images and ESA CCI (European Space Agency Climate Change Initiative) land cover maps. We evaluated the effect of cumulative drought on predominant land covers. Our results show years 2000–2001 and 2017–2018 as the driest in the last four decades, and vegetation substantially correlated to drought with spatial and temporal variations across Afghanistan. The most sensitive vegetation response months are June to July and the most significant cumulative drought impacts on vegetation are 6 to 8 months. The predominant land covers more prone to negative effects under severe drought are (in order) shrubland, rainfed cropland, grassland, trees, and irrigated cropland. These findings suggest the sensitivity of vegetation to drought that future national scale drought management should be focused on. This study also demonstrates the usefulness of open-access data to researchers and planners in data-poor countries. [ABSTRACT FROM AUTHOR]

• This paper provides a comprehensive conceptual analysis of disaster resilience in climate-vulnerable communities. • The research employs the Walker and Avant Method to elucidate the notion of resilience within the framework of climate vulnerability. • A practical framework and a set of ecological indicators are proposed for environmental impact assessments in disaster resilience. • The research provides tangible illustrations of the proposed approaches and indicators in practical contexts. Resilience is a prior term of debate in vulnerability research irrespective of discipline. Nowadays the resilience concept has been used abnormally in many cases without realizing its intended meaning. Therefore, this study clarifies the resilience concept in the context of climate vulnerability. An integrated review of the literature has been done by the PRISMA approach to identify the most relevant documents. Besides Walker and Avant Method has been used to analyze the concept of resilience. The use of concept in different disciplines, historical perspectives, dimensions, attributes, consequences, and relationship with vulnerability and adaptability have been reviewed to clarify it. This study also provides a theoretical and workable definition of resilience from the perspective of climate change and natural hazards. A conceptual framework has been developed with concept mapping, contributing to the existing debate on resilience study. A case analysis has been done by focusing on a climate-vulnerable community living in the riverine islands in Bangladesh. This article shows that socio-ecological systems approach to defining small island disaster resilience has shortcomings. Additionally, the research-policy divide in resilience studies is exacerbated by the paucity of studies that use the participatory approach to identify disaster resilience indicators. The study makes a compelling case for further research on how to turn academic discoveries into a resource that might benefit local people, particularly those on small islands. The study suggests that social community-based resilience should be developed to protect geographically isolated communities. [ABSTRACT FROM AUTHOR]

• The paper analysed a case study on the monitoring system of an Italian food company. • The study creates a tailor-made environmental Key Performance Indicators dashboard to assess corporate sustainability. • The study investigated rewards systems in the frame of Green Human Resource Management practices. • A final dashboard of around 70 indicators was then created and linked to employees' rewards. Assessing environmental performance, measuring the circular economy and quantifying decarbonization have become crucial in green management in recent years. Both scholars and practitioners have focused on different strategies to create performance indicators capable of tackling all these aspects. At the same time, companies have started connecting managers' and employees' incentives to the achievement of corporate goals. We analysed a case study of an Italian food company which uses environmental performance indicators to assess corporate sustainability and reward managers and employees. Through a series of interviews with members from all departments, we identified around 200 different key performance indicators, i.e., performance, commitment, control, reactivity, economic, consent, transversal and multifunctional. A final dashboard of around 70 indicators was then created and linked to employees' rewards. A tailor-made methodology was, thus, used to define target for the company's management by objectives, taking into account the trend of each indicator. This is the first attempt to investigate how a company can create an environmental performance indicator system to assess corporate sustainability and reward employees through management by objectives. Our study further extends not only the academic literature, but also provides a practical and operative contribution to all the companies that aim to create a new key performance indicator system. Lastly, we merged the management and strategies for promoting green practices amongst employees through a reward system with the environmental performance of each organisational department by creating a methodology to define management by objectives. [ABSTRACT FROM AUTHOR]

• The impact of precipitation, slope, and swamp wetland ratio on water yield is not affected by spatial scale and watershed. • Identifying key areas for ecosystem services combined with multiple scenarios can help to take ecological restoration. • The water yield in the Baihe basin is more sensitive on climate change, while the water yield in the Heihe basin is more easily affected by land use changes. • The economic development and ecosystem services can both be ensured by wetland ecological restoration. Water supply is one of the core ecosystem services functions for wetland. Due to the important status of Zoige wetland, assessment of water supply in Zoige wetland is significant for ecological security all over the world. In this paper, Heihe and Baihe basins in Zoige wetland were taken as research objects, the water yield module of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used to spatially quantify water supply, with the aims of revealing the driving mechanism of water supply under different basins and spatial scale. We observed the spatial pattern change of water yield under baseline and eleven future scenarios and used the ANOVA of repeated measures and multiple linear regression model to explore the patterns and driving factors of water supply in Heihe and Baihe rivers basins. The research results were as follow. (1) The precipitation is main factor to improve water yield, but this intensity is different in different basins and spatial scale. Topography, climate, vegetation, and percentage of wetland conditions have important impacts on water yield services. However, the impacts of these conditions on water yield were various significantly across different watersheds and spatial scales (excluding factors such as precipitation, slope, and percentage of swamp wetland). (2) The spatial pattern of water yield main was affected by land use change and the amount of water yield main was affected by future climate change. (3) Water yield in the Baihe basin was more sensitive to climate change, while the Heihe basin is more sensitive to land use changes. Wetland ecological restoration strategies can effectively improve regional water yield, especially in the Heihe basin. (4) In all scenarios, the southeast regions of the study region were both the main hot spots of water yield. Wetland ecological restoration strategies have added hot spots in the north regions of the Baihe river basin, reduced hot spots in the middle-south regions of the Heihe basin. [ABSTRACT FROM AUTHOR]

[Display omitted] • We develop a framework to estimate future Flood Regulation Service (FRS) dynamics. • The framework considers the joint impacts of both climate change and urbanization. • Future FRS supply–demand imbalance will continue to intensify. • Future impacts of climate change in Baiyangdian Lake Basin cannot be ignored. • Cities should actively adapt to climate change to reduce flood risks in the future. Estimating the supply–demand relationship's future dynamics and trend of Flood Regulation Service (FRS) is important for preventing flood risks and choose an appropriate future development path. Less attention has been given to assessing the future trends in this relationship under the joint influence of climate change and urbanization. This paper aims to quantify future trends in the FRS supply–demand relationship under the joint impacts of climate change and urbanization. To this end, we took the Baiyangdian Lake Basin as an example and developed a "Climate Change-Urbanization-FRS supply and demand" framework by combining future climate scenarios from the ScenarioMIP (Scenario Model Intercomparison Project) dataset and socioeconomic data from the SSPs (Shared Socioeconomic Pathways) to estimate the FRS supply and demand dynamics during the period from 2020 to 2050. The results show that the framework has a reasonable ability to estimate the FRS supply–demand relationship. The correlation coefficients between estimated supply–demand ratios and the historical values exceeded 0.9. The average FRS supply–demand ratio among the four scenarios shows a significantly downward trend between 2020 and 2050. The FRS is expected to decrease by 0.159 (36.6 %), resulting in the imbalanced area increasing from 38.3 km2 (4.1 % of the whole basin) to 11049.7 km2 (36.2 %). We believe that although urbanization is the dominant factor contributing to the intensified imbalance trend (with a contribution of 71.2 %), influences from climate change also cannot be ignored (with a contribution of 28.8 %). Therefore, adaptation actions to climate change should be actively taken to reduce urban flood risks in the future. [ABSTRACT FROM AUTHOR]

Abstract: Multifunctional landscapes are characterized by various functions and values that sustain directly or indirectly the quality of human life, through the provision of natural capital flow. Primary production (PP), representing a measure of the solar energy captured by the system and available to drive its functioning, is recognized as a fundamental supporting service. Several biophysical modification and conversion altering the primary production are due to land-use change. Natural protected areas with a sustainable management of land-use could be able to guarantee the persistence of structure and processes (primary production) fundamental for the provision of natural capital. In this context, the aims of this paper are to investigate the spatial–temporal patterns of PP variability (1986–2010) in the Natural Protected Area of “Torre Guaceto” (southern Italy), taking into account land-cover change and climate conditions and looking at PP as a supporting service able to guarantee natural capital flow. In dealing with this issue, this paper aims at testing whether NDVI (Normalized Difference Vegetation Index) integrated with NDII (Normalized Difference Infrared Index) can be suitable surrogates for the assessment of shifts in the spatial–temporal dynamics of PP, useful to explore possible feedbacks related to conservation management choices in supporting natural capital flow. Therefore, the assessment of the complex spatial–temporal dynamics of natural vegetation has been performed by using NDVI and NDII. The results showed that after the establishment of the Natural Protected Area of “Torre Guaceto” in 2000, there has been an increase of NDVI that could represent an increase of PP. However, since PP depends also on water content, measured by NDII, a Pearson correlation analysis between NDII and land Surface Temperature (TS) has been carried out, demonstrating that low level of PP in 2005 was not imputable to climate conditions but to the worse quality of vegetation associated to the wetland due to aging phenomenon. In conclusion, to make the conservation management more effective it is not enough to identify and quantify the major landscape transformations and the underlying causes, but rather to detect the capability of new landscape patterns, in terms of configuration and composition, to sustain ecosystem services. The analysis of conservation management based on NDVI and NDII, used as surrogate to detect the maintenance of PP, appears to be very promising in order to develop better strategies for the adaptive management of natural protected areas. [Copyright &y& Elsevier]

Abstract: The paper gives an overview on the trends in the usage of landscape metrics as indicators for: land use changes, habitat functions (biodiversity, habitats), landscape regulating functions (fire control, microclimate control, etc.), and information functions (landscape aesthetics). We reviewed papers published in international peer-reviewed journals that are indexed by the Institute of Science Information (ISI) Web of Knowledge from 2000 to 2010. The terms “landscape metrics”, “landscape indexes” and “landscape indices” were searched. Our analysis showed that application of the landscape metrics to characterize various ecosystem services and landscape functions has broadened during the last 10 years. Number of studies related to regulating and information functions of landscapes is increasing. However, the main exploitation field of the metrics is evaluation the change in land use/land cover. [Copyright &y& Elsevier]

• An index of Sustainable Agriculture for the EU-28 over the period 2005–2014 is computed. • A Granger-causality test for panel data is implemented. • A negative bidirectional relationship between climate change and agricultural yields is verified. • A negative bidirectional relationship between climate change and sustainable agriculture is identified. • Conventional agriculture negatively affects sustainable agriculture. Agriculture and climate change are characterized by a complex cause-effect relationship. The agricultural sector generates significant quantities of gas emissions that affect climate. The rise in the concentration of greenhouse gases in the atmosphere, the increase in temperatures as well as changes in the precipitation regime have repercussions on the volume, quality and stability of the agricultural and zoo technical production, but also on the natural environment in which agriculture is practiced. Based on the above, the purpose of the paper is twofold. Firstly, through the Wroclaw Taxonomic Method, we construct a composite indicator, called the Index of Sustainable Agriculture (ISA), and analyse 28 countries that have joined the European Union from 1 July 2013 to today (EU-28) over the period 2005–2014, according to 16 variables. Secondly, the Granger-causality test for panel data is implemented in order to verify the causal relationship among the ISA, climate change and agricultural production. In other words, we test which of the three analyzed variables turns out to be the cause variable and which, instead, turns out to be the effect variable. Furthermore, we test if there is a bidirectional causality among the variables. This analysis provides a wide overview on how European countries rank according to the ISA and its three crucial pillars, i.e. environmental, economic and social. Moreover, important causality relationships among the ISA, climate changes (approximated by mean annual temperature and mean annual precipitation and provided by the Climate Research Unit (CRU) Time-Series (TS) Version 3.22 of the University of East Anglia) and agricultural production (approximated by wheat and spelt yields and provided by EUROSTAT) are identified. In particular, the following hypotheses are verified: 1) there is a negative bidirectional relationship between climate change and agricultural yields; 2) there is a negative bidirectional causal relationship between climate change and sustainable agriculture; 3) conventional agriculture negatively affects sustainable agriculture. [ABSTRACT FROM AUTHOR]

• The effect of wind has been taken into account in analyzing the dispersivity. • The method of asymptotic analysis is adopted to study the dispersivity. • The effect of ecological degradation has been taken into account. • The critical length and duration of the influenced region has been illustrated. The effect of global climate change is increasing and it can influence agriculture in many ways, especially in that it makes great threaten on agricultural water resources. Since agricultural water supply is a key issue for agricultural production, indicators for contaminant transport in wetlands should be considered in order to solve agricultural water pollution and promote water protection. In this paper, we analyze the environmental dispersion in a typical three-layer wetland flows with the effect of wind taken into account. The analytical solution for velocity distribution is rigorously derived and the dependence of characteristic parameters on averaged dimensionless velocity is recorded. The asymptotic analysis theory of Gill is employed to measure dispersivity for natural wetland flows with a commonly high Peclet number. Both velocity and environmental dispersion are significantly influenced by wind, in terms of its direction and the magnitude of force. The effects of hydraulics and ecological degradation are considered to obtain the analytical solution for the mean concentration and maximal critical length of the region influenced by the process of contaminant transport. [ABSTRACT FROM AUTHOR]

• We calculated carbon sequestration/emissions in agroecosystems in Hebei, China. • We measured agricultural production efficiency considering an undesirable output. • The annual average low-carbon agriculture production efficiency increased by 3.03%. • There were disparities of efficiency among cities owing to increased carbon emission. • Climate change had complex effects on low-carbon agricultural production. With the increase of greenhouse gas (GHG) emissions in the atmosphere, global greenhouse effects have intensified, thereby contributing to climate change. Agriculture contributes to climate change by increasing GHG emissions, and climate change in turn affects agricultural production. In this paper, we calculated carbon emissions and sequestration of agriculture in the 142 counties of Hebei Province, China, and analyzed their spatiotemporal distributions during 2000–2010. Considering net carbon emissions as an undesirable output, we then measured low-carbon agricultural production efficiency using a stochastic directional distance function. We further explored the impacts of climate change on low-carbon agricultural production. We found that carbon emissions in agriculture increased by 15.85% (650 million tons) during 2000–2010, while carbon sequestration in agroecosystems increased by 33.82% (13.8 million tons). The annual average low-carbon agricultural production efficiency increased by 3.03%. There were distinct disparities of efficiency among cities, with the highest efficiency in Chengde and Shijiazhuang. The efficiency in southeastern areas was lower than that in the northwest, owing to the increased carbon emissions. Temperature and precipitation had a positive effect on efficiency in Hebei, whereas extreme weather events caused lower efficiency. The results provide valuable references for developing sustainable, climate-resilient and adaptive agriculture under changing climatic conditions. [ABSTRACT FROM AUTHOR]

Highlights • We analyze the spatiotemporal pattern of the ECC on the Loess Plateau. • The average annual ECC is 577 ± 124 g C m−2 yr−1 during 1982–2012. • Due to revegetation, 26 counties have exceeded the ECC threshold. • 138 counties have water competition between ecosystems and socio-economic systems. • Under future climate change and growing water demand, ECC will increase by 6–36%. Abstract Revegetation, especially afforestation, has served as an important tool for controlling desertification. However, revegetation in water-limited regions will inevitably reduce the water available for socio-economic systems, which is poorly considered in decision-making on sustainable ecosystem management. This paper proposed a framework to determine the threshold of vegetation productivity (i.e., ecosystem carrying capacity), corresponding to available water resources for ecosystems (i.e., annual precipitation minus water demand for socio-economic systems) on the Loess Plateau. The average annual ecosystem carrying capacity (ECC) during 1982–2012 is 577 ± 124 g C m−2 yr−1, with spatial gradients increasing from northwest to southeast. Vegetation in rocky mountain areas has the largest value of 833 ± 200 g C m−2 yr−1. Factorial analysis suggests that changes in precipitation and human water use contributed to 55% and 45% of the multi-decadal changes in regional ECC, respectively. Meanwhile, due to revegetation, 26 counties on the Loess Plateau, mainly in the southeast and eastern parts, have exceeded the ECC threshold during the study period. An additional 138 counties have a high potential for water competition between the ecosystems and socio-economic systems. At the regional scale, there are 9 years (∼30% of the study period) during which the ECC threshold has been exceeded, especially after 1997. Considering the climate change in the future and the growing demand for water in socio-economic systems, the corresponding ECC threshold will increase by 6–36%. We believe that these findings can provide reference for policy-makers to make decisions towards ecosystem sustainability while meeting human needs for water resources. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The provision of multiple ecosystem services (ES) is analyzed using a sustainability perspective. • The sustainability of the patterns of multiple ES in the Venice lagoon has been explored. • Two aggregated indicators have been identified that reflect the unsustainability of ES provision. • A sustainability-driven analysis of ES can be applied in order to improve the Water Framework Directive implementation. • The analysis suggests the adoption of different management trajectories in confined and not-confined water bodies. Abstract The multiple ecosystem services (ES) co-produced by social-ecological systems include ES directly resulting from ecosystem functioning, and ES mediated by human activities, which can have negative effects on the system and on the ES provided. As a result, different patterns of multiple ES delivery can be characterized by sustainable or unsustainable trends over time, depending on the interactions occurring among ES. In this paper, a sustainability perspective was used for the identification of desirable and undesirable ES delivery patterns in the water bodies of the Venice lagoon (Italy). A set of 13 ES was quantitatively mapped for the lagoon's water bodies, and the trends of the ES provided by each water body have been explored through a modeling application. Two aggregated indicators, MED/DIR and PRESS/DIR, calculated based on the mapping outcomes, were found to be strongly associated with the modeled trends, and thus provide a synthetic indication of the potential (un)sustainability of the current ES provision. This sustainability-driven analysis paves the way for an operationalization of the ES concept in the context of the implementation of the EU Water Framework Directive (2000/60/EC). Based on the analysis of the relationships between multiple ES and ecological status, we suggest that ES could play a role in the selection of the biological quality elements, by prioritizing the metrics that are positively associated with the sustainable ES patterns. Adopting a perspective focused on sustainability, the ES concept can be used to define management trajectories that aim to reach the WFD targets through the management of unsustainable ES patterns, in the context of climate change. [ABSTRACT FROM AUTHOR]

Abstract: The goal of this paper is to introduce a statistical concept to derive ecological classifications of terrestrial and marine environments. Such ecological regionalisations reflect spatial combinations of biotic and abiotic characteristics and therefore may serve for environmental planning and monitoring issues. Referring to two case studies the paper presents how to calculate and map ecological defined regions from geodata by use of decision tree models and GIS-techniques. The first study deals with marine environments, exemplified by benthic habitats in the North Sea. The second study is on an ecological land classification of Europe which was computed using surface data on potential natural vegetation, elevation, soil texture and several climatic elements. Both the marine and the terrestrial ecoregions maps were combined with exposure data provided by environmental monitoring activities. The ecological land classification of Europe was intersected with measurement data on the metal loads in mosses taken from the German part of UN ECE moss surveys. In this way, the temporal development of the metal bioaccumulation within ecoregions since 1990 was assessed. The benthic habitat map was used to regionalise the temporal trend of the temperature conditions near the sea floor for the months of July and January from 1995 to 2000 by analysing these measurements according to the spatial categories of the habitat map. In the future, both ecological regionalisations should be used as a spatial framework for the analysis of up-to-date meteorological and phenological data in order to disclose climate change induced impacts. [Copyright &y& Elsevier]

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]

Graphical abstract This work was supported by the Woolf Fisher Trust and the Cambridge Commonwealth, European and International Trust, in the form of a Woolf Fisher Scholarship (2014). Highlights • Few studies explore the processes and possible impacts of adaptation constraints. • A lack of empirical depth means that they are often ignored in policy formulation. • This paper proposes a method for exploring the empirics of adaptation constraints. • Numerical preference functions are estimated for 15 salient constraints. • These constraints could be modelled quantitatively and should no longer be ignored. Abstract The concept of adaptation constraints has become well known in the climate change literature. It describes impediments to the process of adaptation that could in principle be overcome but often are not. Many adaptation constraints have been identified and described in the literature across a wide range of contexts, and the importance of their influence on climate change adaptation is clear. However most studies have focussed on describing constraints rather than exploring their origins, processes, and possible impacts. As a consequence, it has been difficult to operationalise the concept to provide information meaningful to decision makers. This study demonstrates an approach to estimating empirically the processes and the impacts of adaptation constraints, based on a case-study of farmers in New Zealand. It combines established social scientific methods to explore the processes underlying a range of adaptation constraints and estimate the impacts that these constraints may have. The approach can be used to explore further the social and economic impacts of adaptation constraints. This information can then be used to consider sub-optimal adaptation to climate change more fully, and paves the way for policy responses that are more conscious of the human elements of climate change adaptation. [ABSTRACT FROM AUTHOR]

Highlights • An integrated approach is developed for environmental sustainability. • Climate variability has significant impacts on local environmental sustainability. • Rio Grande Basin is sustainable under current climate conditions. • Rio Grande Basin will become less sustainable in the late 21st century. Abstract Extreme weather events have been affecting local environmental sustainability. Previous literature in this field evaluates environmental sustainability based mainly on past and current resource consumption and availability, however, knowledge about the status and potential changes of environmental sustainability under future climate extremes is missing. This paper proposes an integrated approach (combining the Ecological Footprint Analysis with econometric regressions) to predict future environmental sustainability under different climate scenarios. Based on the case study of the U.S. Rio Grande Basin, the results show that this region has been sustainable in 1982–2012, although sustainability levels have been declining over time. In addition, projections for the future show that the entire region will most likely move away from sustainability by the end of this century under the high emission scenario (e.g., RCP8.5). These findings are relevant for sustainable resource management and allocation of local environmental resources as well as for decision-making support regarding climate risk adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

• Recent research on the B&R eco-environment is reviewed. • The B&R is likely to face environmental challenges due to its fragile background. • Four key aspects of the ecological environment are studied. • Sustainable development should be promoted under socioeconomic frameworks for the B&R. • Future research directions for improving the B&R eco-environments are proposed. The Belt and Road Initiative (BRI) will play an essential role in boosting the world's economy. However, the main portion of the Belt and Road (B&R) is in arid, semi-arid, or sub-humid fragile ecological regions, which with global climate change and the intensification of human activities will face many pressing environmental challenges in the future. Despite this, in the existing research on the B&R, papers in the field of natural sciences are less than 1.2–4.3% of the total number of papers on the main databases, which is far lower than the coverage in humanities and social sciences. And those focused on the ecological and environmental issues along the B&R are even fewer, so necessary understanding of both the risks and adequate mitigation measures remains unclear. This paper systematically reviews the relevant research on the eco-environments along the B&R, and summarizes it in terms including of spatial patterns and cognition, cost efficiency and evaluation, ecological security and evaluation, ecological footprint and carrying capacity. It further suggests that a better understanding of environmental changes and their effects on the B&R is needed. Additionally, it is essential that the potential positive socio-economic impacts for the future under the BRI are sustainable. Finally, future research directions are proposed to improve for the better eco-environments in B&R regions with consideration of global changes. [ABSTRACT FROM AUTHOR]

• A single year was divided into three different seasons. • The impact of human activities and climate change on runoff were quantified. • The main factors of runoff changes caused by human activities were analyzed. The Yongding River has ceased to flow due to the impact of human activities and climate change, inducing environmental degradation. Analyzing the driving factors is vital for environmental restoration and water resources allocation, but it is challenging especially at seasonal scale. In this paper, the monthly abcd model was constructed for the Yongding River basin and two sub-basins, namely Yanghe and Sangganhe, to quantify the relative contribution of climate change and human activities to runoff decrease. The results show that the annual runoff in the basin has been declining significantly since the 1980s, up to 30 mm/year. Human activities are the main influencing factors, with 108% contribution in the entire Yongding River basin, 122% and 98% in Yanghe and Sanggan sub-basins, respectively. The impact of human activities on runoff varies in different seasons, which is highest in the wet season, followed by irrigation season and dry season. The impact of human activities is more pronounced in July-September due to water withdrawal for irrigation and operation rules of reservoirs, which is twice as much as that in April-June. A stricter management system can alleviate the impact of human activities on runoff change. [ABSTRACT FROM AUTHOR]

• A general framework for predicting flow and biodiversity changes under future climate change is proposed. • Discharge is consistently on the rise, reaching a maximum in the late 21st century. • Hydrological regimes change significantly and integrated degree of hydrological variation will reach a moderate level. • Shannon Index values show increasing trends and fluvial biodiversity is improved. Scientific evaluation of the eco-hydrological regimes is of great significance for water resource management and aquatic ecosystem protection. The paper took the western route source areas (WRSA) of the South-to-North Water Diversion Project (SNWDP) as the research region. In order to quantify climate-induced eco-hydrological effects, a general framework was proposed to predict changes in flow regimes and fluvial biodiversity under climate change: The coupling of Global Climate Models (GCMs) and the Distributed Time Variant Gain Model (DTVGM) was used to simulate discharge under different climate conditions. Based on Indicators of Hydrologic Alteration (IHA), changes in eco-hydrological regimes were evaluated by using the Range of Variability Approach (RVA), assessment of overall hydrological change degree (D 0), and Shannon index (SI). Changes in discharge, flow regimes, and fluvial biodiversity of WRSA were analyzed during the projected period (2041–2100) compared to the base period (1960–2014). According to the projections, under four SSPs-RCPs scenarios, the future discharge of WRSA increases significantly compared to the base period. D 0 of WRSA is moderately or severely changed, and hydrological changes are mainly reflected in high flows such as monthly median flows during flood season, maximum flows, and high pulse duration. While flow regimes are disturbed, SI values of WRSA keep rising and the biodiversity is improved. The increase of discharge and SI becomes progressively greater with elevated radiation intensity, and the quantity of severely altered indicators of IHA increases. In conclusion, future hydrological alterations in SNWDP are expected to further intensify with higher levels of climate change, and these changes are generally conducive to the improvement of fish biodiversity. [ABSTRACT FROM AUTHOR]

• Tree ring is an ideal indicator of annual total grain production parameters. • Tree growth synchronized with grain production, and concurrent response to climate. • Reconstruction of total grain productivity based on dendrochronology. • To explore the relationship between total grain sown area and climate change. Climate change affects the growth of regional vegetation; both trees and grain crops often change concurrently, such that the annual radial growth of trees shows consistent inter-annual variations with the total grain crop productivity. However, it remains unclear whether they exhibit concurrent responses to climate factors, and that there lacks of the study on long-term high-resolution variations of grain crops productivity. This paper employs a Pinus massoniana tree-ring series from the Tongbai Mountains to analyze the correlations between tree-ring chronology, local climate data and grain productivity indicators (i.e., total sown grain areas (TSA), total grain outputs (TGO), and average grain yield per hectare (YPH)) of Henan Province in central China. The results indicate that temperature in March and August was the main limiting factor on tree growth, and the best concurrent relationship with tree growth was TSA, which has a correlation of 0.747 (p < 0.001) during 1959–2020. Therefore, a 124-year TSA series in Henan Province was reconstructed using tree-ring data from the Tongbai Mountains, which reveals there were two distinct low periods of total grain sown area in the 1920 s-1930 s and 1980 s-2000 s. There are significant cycles of about 2.57a (p < 0.01), 2.89a (p < 0.05), and 10.95a (p < 0.1), indicating that vegetation growth might be affected by large-scale climate forcing, such as ENSO (2-7a cycle) and sunspot activity (11a cycle). Overall, this study outlines a new approach to understand long-term changes in grain production, which is conducive to grain management and socioeconomic sustainability. [ABSTRACT FROM AUTHOR]

• Mudflats conditions in the UK are unfavourable and managing them is a challenge. • Benthic species and shorebirds can be used as indicators of mudflat conditions. • Shannon's diversity index and AMBI results may provide different results. • A lack of monitoring data for UK mudflats makes effective conservation difficult. Intertidal mudflats are highly productive coastal habitats, serving as a transition zone between terrestrial and marine ecosystems and providing a wealth of ecosystem services, including providing nursery and feeding grounds for many species of conservation and commercial importance. These habitats are important for wintering shorebirds and waders, which depend on them for food, nesting, and migration. Their importance was formally recognised in 1971 following the Ramsar Convention on Wetlands of International Importance, yet their conservation status remains largely uncertain as they are difficult to survey, and a complete understanding of their complex biophysical processes has yet to be established. While intertidal mudflats are found all around the UK coastline, there are few routine field surveys of these habitats, making effective conservation in the face of rising anthropogenic and climate pressures challenging. Marine protected areas (MPAs) across the UK list mudflats and sandflats not covered by seawater at low tide as a designation feature separate from saltmarshes, but they are often managed together – where management exists. A lack of resources has resulted in several paper parks around the UK, where MPAs are designated but not adequately monitored or managed. This study explores the use of population data of benthic species and shorebirds as a proxy for temporal changes in mudflat conditions, focusing on two MPAs in the Irish Sea, Strangford Lough in Northern Ireland, and the Solway Firth in Scotland/England. It finds that the two methods together can provide information useful to support MPA management, but this approach is hampered by poor availability of sufficient data. Such data limitation can impact what it means to achieve or maintain favourable conditions for these habitats. [ABSTRACT FROM AUTHOR]

• Based on the principles of SPEI, we develop a GDAI. • The relationship between GDAI and AI is closer. • The correlation between GDAI and SPEI is also better. Climate change has increased the risk of drought in both arid and non-arid regions of the globe. Therefore, in order to monitor and evaluate global drought and aridity, based on the principle of standardized precipitation evapotranspiration index (SPEI), this paper selected precipitation and potential evapotranspiration data and used a frequency calculation method to develop a multi-scale global drought aridity index (GDAI) that concurrently considers spatial and temporal variation characteristics: the spatiotemporal standardized precipitation evapotranspiration index. The index was compared with the aridity index (AI) and SPEI. The results showed that the correlation coefficients between GDAI and AI were greater than 0.8 in most areas, and the relationship was closer and could reveal the global aridity and wetness zoning. In addition, the correlation between GDAI and SPEI was also better, which could capture the temporal change characteristics of drought. Moreover, this study also compared the grades of GDAI and SPEI with the actual drought grades in Yunnan from September 2009 to August 2010, and found that GDAI was better than SPEI, and GDAI was the most accurately evaluated at the 3 month time scale, with an accuracy rate of 86.11%. Therefore, this index is more helpful for the assessment and monitoring of global drought and aridity. [ABSTRACT FROM AUTHOR]

• Automated Content Analysis provides clarity to 1116 articles on coastal zone indicators. • Quadruple Helix Stakeholders from Ghana provide clear insight to indicator needs. • Literature and stakeholder-based (Ghana) indicator sub-categories are combined • New indicator sub-categories are proposed for current frameworks (e.g. CHW). • Further research to visualize indicators should strengthen coastal zone management. Coastal zone management is a pressing matter, especially in developing countries, which are highly vulnerable to the effects of climate change. Human systems are underrepresented in the vast array of indicators aimed at assisting coastal zone management decisions. Clearly, there is room to better capture natural and human system relationships and interactions in coastal area assessments. A case in point is the well-known Coastal Hazard Wheel (CHW). Hence three main objectives guide this paper: (i) Analysing the existing set of indicator themes and categories in coastal areas; (ii) Contrasting this set of indicators with the perceived needs of local coastal stakeholders from a developing country; and (iii) Proposing indicator categories to be included as part of a systemic coastal zone management framework. To this end, we undertook an automated content analysis of 1116 peer-reviewed articles on the subject matter. The analysis and a stringent set of criteria led to 40 articles that were reviewed to identify suitable indicators. In parallel, field research in Ghana allowed for a set of indicators from the quadruple helix stakeholders operating in coastal zones to be elicited. Contrasting the two sets of indicators resulted in three situations. The first involves 14 indicator categories that co-occur in the literature and the detected needs from local coastal stakeholders. In the second situation, the categories mentioned in the literature were those not mentioned at local level. A third situation appeared when the local coastal stakeholders mentioned categories of indicators that were not identified in the reviewed literature. After examining each case, we advocate for the indicators in the first situation to be incorporated into the current coastal indicator monitoring frameworks (for example by upgrading the CHW). The unique contribution of this paper is the combination of literature and stakeholder-based indicator sub-categories that should be added to the current set of coastal monitoring frameworks. [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]

This article presents a comprehensive literature review of Vertical Greenery System (VGS) in tropical areas, its benefits, its carbon sequestration potential and its calculation methodologies, and its potential for urban heat island (UHI) and climate change mitigation. The contemporary VGS has evolved from the seventh-century beginnings of the Hanging Gardens of Babylon to the vertical urban farms of today in Singapore and Japan. The VGS has demonstrated a significant role in mitigating urban climate change impacts by the potential use of carbon sequestration from vegetation. However, studies on carbon sequestration rate and the methodologies used for calculation are still rather vague. Therefore, this paper reviews existing methodologies for evaluating carbon sequestration rates in tropical climate plants and makes suggestions of potential plants for optimum carbon sequestering. [ABSTRACT FROM AUTHOR]

Due to steadily increasing resource demand and accompanying raising public awareness, a variety of assessment methodologies evaluating resource use and its consequences were published in the last years. Existing methodologies are typically developed considering the specific characteristics of one particular resource type and as consequence are not suitable for cross-cutting assessment of different resource types. This paper proposes an 3-step approach for combining different resource use assessment methodologies allowing for a consistent assessment of product systems using different resource types. The first steps evaluate if the considered dimensions, categories, indicators, indicator models and underlying data are consistent. When this is the case, they can be included in the combined methodology without further adjustments. Differences are identified simultaneously and addressed in the subsequent steps. Within the steps guidance is provided on how the dimensions, categories and indicators of the methodologies can be adjusted to fit in the combined methodology. In a case study the proposed approach is applied to two methodologies developed by the authors assessing abiotic (ESSENZ method) and biotic resources and raw materials (BIRD method). The ESSENZ method consists of four dimensions, which are quantified by overall 21 categories and indicators. The BIRD method takes into account five dimensions and 24 corresponding categories and indicators. As none of the considered dimension of the two methodologies match, comparison of the considered resource types as well as application in a case study is not possible. By applying the proposed approach all five dimensions and 25 of the overall 27 categories and indicators can be integrated in the combined approach for a consistent assessment of abiotic and biotic resources and raw materials. The obtained combined methodology is then applied to three shelves made out of metal, wood and plastic. It could be shown that the introduced approach provides meaningful guidance on how to combine different resource use assessment methodologies and increases the findings gained from a combined and consistent assessment. [ABSTRACT FROM AUTHOR]

Small Island Developing States (SIDS) are generally considered highly vulnerable to climate change because they suffer from most common environmental problems due to their smallness, remoteness and exposure to natural hazards, though they contribute less to climate change. However, international cooperation can improve the negative impacts of climate change by incentivizing adaptation policies. The vulnerability assessment becomes crucial because it can be used to allocate the international cooperation resources targeted to adaptation plans. The aim of this paper is to assess of the vulnerability in Small Island Developing States. Using a comprehensive dataset including 32 variables, we synthetize the vulnerability with a composite indicator. Then, we analyze the vulnerability’s dynamics over time from 2009 to 2014. Lastly, we explore the dimensions of vulnerability to assess those that have a greater weight on overall vulnerability. Our findings show that the vulnerability of Small Island Developing States is partly driven by common characteristics, such as isolation and extreme exposure to the effects of climate change, but the degree of vulnerability of identified dimensions is different among countries. Our results give indications to better target development aid, giving suggestions on the more relevant dimensions for action to reduce the vulnerability of each country. [ABSTRACT FROM AUTHOR]

A vast amount of knowledge and experience on coping with climatic variability and extreme weather events exists within local communities, and indigenous coping strategies are important elements of successful adaptation plans. Traditional knowledge can help to provide efficient, appropriate and time-tested ways of responding to climate change especially in far-flung communities. However, little is known about how traditional coping strategies translate into adaptation to long-term changes, and to what degree they prevent pro-active, transformational responses to climate change. This paper assesses the use of climate related information for communities in the Himalayan foothills of rural India, and reports on the barriers to adaptation planning and actions. Surveys have been carried out to analyze the current practices and the role of information in planning for climate change adaptation in the rural areas of the Nainital region of India located in Western Himalaya. Respondents perceive the local climate change, the intensity of change, and the negative impacts on the community and landscape. Decreases in water quantity and changes in precipitation patterns are among the major concerns for respondents, however, communities have begun to use traditional knowledge and historical climate information for developing strategies suitable to cope with impacts of climate change. Going forward, additional information is needed to match the high priority community needs with viable adaptation strategies. Lack of money, lack of access to information, and lack of awareness or understanding are considered the three largest hurdles besides low priority for adaptation, recognized by community members as barriers to adaptation planning and actions. Adaptation plans must be integrated into both top-down and bottom-up approaches to plan for enabling sustainable development and the efficient use of information for adaptation. Finally, traditional knowledge seems to be useful not only in contrasting climate change impacts, but also in recovering several ecosystem services that work all together for enanching the quality of life of villagers at local scale. [ABSTRACT FROM AUTHOR]

Climate change will affect the future availability of water resources for agriculture. An understanding of the impact of future climate change on regional agricultural water use can provide a basis for regional agricultural production and water management. This paper evaluated the agricultural water demand under three future climate change scenarios in the Loess Plateau of northern Shaanxi (LPNS), China. The results showed that in the scenarios RCP2.6, RCP4.5, and RCP8.5, the temperature, effective precipitation, and relative humidity were on the rise, the wind speed decreased slightly, and the trend of sunshine duration was unclear. The irrigation water requirements of the main crops exhibited a downward trend under future climate change scenarios. The decreasing trend of the irrigation water requirement was highest in the RCP8.5 (−0.90%) scenario, followed by the RCP4.5 (−0.77%/year) and the RCP2.6 (−0.30%/year) scenarios. Based on the impact of the changes in the evapotranspiration of future crops and the effective precipitation in the RCP2.6 scenario, the irrigation water requirements of the agricultural industry showed a downward trend and decreased from 1.84 × 10 9 m 3 /year (2010–2014 average) to 1.29 × 10 9 m 3 /year (2040–2049 average); the irrigation water requirements of the agricultural industry showed a significant downward trend (P < 0.05) in the RCP4.5 and RCP8.5 scenarios, decreasing from 1.84 × 10 9 m 3 /year (2010–2014 average) to 1.20 × 10 9 m 3 /year (2040–2049 average) and 1.15 × 10 9 m 3 /year (2040–2049 average), respectively. Future research should be aimed at improving the regional climate downscaling and developing a better understanding of the responses of agriculture to regional climate change. [ABSTRACT FROM AUTHOR]

• We proposed a hybrid approach to evaluate the water quality considering input uncertainty. • Proposed model integrated Monte Carlo simulation, CRITC methods and VIKOR. • The proposed model was applied to Songhua river tributary to verify its effectiveness. • The PLUS model has advantages over the other analyzed models. Under the dual influence of global climate change and human activities, river water environment is facing more and more serious problems and challenges. Assessing river water quality is of great significance for promoting regional sustainable development. Currently, traditional water quality assessment methods usually do not consider the uncertainty of water quality data in the collection process, which limits the application of these methods. In order to overcome the above shortcomings, this study constructed a water quality assessment method by integrating Monte Carlo method (MC), CRITIC and VIKOR methods, and applied it to assess the quality of water in the Songhua River tributary. Results indicate that: (1) The water quality assessment of the two sampling points in the study area is level III, which is consistent with the actual situation; (2) This method can overcome the uncertainty caused by sampling error and improve the credibility of water quality evaluation results; (3) Total nitrogen (TN), potassium permanganate index (PPI) and ammonia nitrogen (NH 3 -N) are more evaluation factors related to the evaluation results. When the decision coefficient mechanism λ is taken [0.1–0.5], the outcomes are in line with the real quality of the water. In addition, we recommend that the distribution profile generated based on the measured data should obey the probability distribution density curve that decreases from the middle to the tail of both sides. The findings of this paper can provide a scientific basis for decision makers to carry out water quality restoration and management. [ABSTRACT FROM AUTHOR]

Abstract: The International Landscape Ecology Conference on “Landscape Structures, Functions and Management: Response to Global Ecological Change” hosted by the Faculty of Forestry and Wood Technology, Mendel University in Brno and the Faculty of Science, Charles University in Prague (Czech Republic) in association with the Czech regional chapter of the International Association for Landscape Ecology (CZ-IALE), and supported by the Ministry of the Environment of the Czech Republic, was held from September 3–7, 2010 in Brno, Czech Republic. At 9 parallel symposia of this meeting, 107 oral presentations (including 10 keynote speeches) and 64 posters by representatives from 19 countries were presented. The primary goals of the conference were to provide a forum for the dissemination and discussion of recent research findings, to explore future directions for water management at the landscape level and to foster interdisciplinary collaboration between researchers of all ages and from many countries. This editorial briefly describes the conference, which served as the source of the selected papers, and explains the main aspects of these papers. It highlights papers on issues related to water management under changing climate and land use at landscape and watershed levels, presented mostly at the session on functional water management through land use change. [Copyright &y& Elsevier]

Sclerochronological studies based on hard structures of marine organisms are valuable tools—both for reconstructing past climate conditions and for predicting future impacts of environmental changes on marine resources. Existing archives, which house millions of fish otoliths (ear stones) constitute an excellent basis for such research; but, they remain underutilized. The objective of this project was to identify the factors that influence the annual growth patterns of the European flounder ( Platichthys flesus ) based on an analysis of otolith increments. We applied linear mixed models to develop a 74-year long chronology that reflects the inter-annual variations in flounder growth rates using otolith samples collected from 1957 to 2016 in the southern part of the Baltic Sea, which is considered to be highly vulnerable to global climate change. By analyzing the widths of otolith increments we revealed the existence of common environmental factors that influence fish growth. Using a mixed modeling framework, we incorporated a recent method to identify the optimal time window for climatic factors and showed that the most significant effect of the mean Baltic Sea Index occurs during August–December, while mean sea surface temperature is most significant from April–June. Change point analysis on the developed chronology identified major alterations occurred in flounder growth in 1988, 1992 and 2006. This result is in accord with published studies on regime shifts in the Baltic Sea ecosystem. This paper reports information concerning the response of the commercially important European flounder to the changing environment that may support future ecosystem-based management of fish stocks. Moreover, the results also highlight the potential for applying biochronological techniques to identify rapid regime shifts in marine ecosystems. [ABSTRACT FROM AUTHOR]