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Overexploitation is the second biggest driver of global plant extinction. Meanwhile, useful plant species are vital to livelihoods across the world, with global conservation efforts increasingly applying the concept of 'conservation-through-use.' However, successfully balancing conservation and biodiversity use remains challenging. We reviewed literature on the sustainability of wild-collected plant use across the countries of Colombia, Ecuador, Peru, and Bolivia—a region of global importance for its biological and cultural richness. After applying defined search terms and a two-stage screening process, 68 articles were reviewed. The numbers which reported sustainable, unsustainable, or context-dependent outcomes were relatively even, but national differences emerged. Through narrative synthesis, we identified five key, reoccurring themes: plant biology; land tenure; knowledge, resource, and capacity; economics and market pressures; and institutional structures, policy, and legislation. Our results show the need for flexible, context-specific approaches and the importance of collaboration, with bottom-up management and conservation methods involving local communities and traditional ecological knowledge often proving most effective. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13280-021-01529-7.

Socioeconomic deprivation accounts for much of the spatial inequality in health in the UK, but a significant proportion remains unexplained. It is highly likely that the physical environment is a key factor in this unexplained variation. The role of the socioeconomic environment in health inequalities has been studied using small-area measures of multiple socioeconomic deprivation that capture the burden of socioeconomic adversity. Although similar composite measures of the physical environment would greatly assist investigations of environmental determinants of health no such measures are available. In this study we developed two small-area measures of health-related multiple physical environmental deprivation for the UK. A thorough review and evidence appraisal process was used to identify health-relevant dimensions of physical environmental deprivation. As a result we selected both health-detrimental (air pollution, cold climate, industrial facilities) and health-beneficial (ultraviolet radiation and green space) dimensions. Datasets describing each of the selected dimensions were acquired, and rendered to UK Census Area Statistics wards ( n = 10 654, average population = 5518). We developed two summary measures: the multiple environmental deprivation index (MEDIx) and classification (MEDClass). MEDIx, on an ordinal scale, can be used to distinguish areas exposed to greater or lesser environmental deprivation. MEDClass groups areas with similar environmental characteristics and will be useful for exploring health effects of specific types of environment. Mapping these measures demonstrated a wide variation in physical environmental deprivation across the UK. MEDIx revealed greater environmental deprivation in urban and industrial areas, and at more northerly latitudes. Although created using a different methodology MEDClass also differentiated these environmental types. We concluded that it is possible to capture and characterise multiple attributes of health-related physical environmental deprivation in the UK, at a small area level. The measures we developed offer opportunities to researchers and policy makers for developing our understanding of the role of exposure to multiple dimensions of physical environmental deprivation on health outcomes.

A debt-based economy requires the accumulation of more and more debt to finance economic growth, while future economic growth is needed to repay the debt, and so the cycle continues. Despite global debt reaching unprecedented levels, little research has been done to understand the impacts of debt dynamics on environmental sustainability. Here, we explore the environmental impacts of the debt-growth cycle in Indonesia, the world's largest debt-based producer of palm oil. Our empirical Agent-Based Model analyses the future effects (2018–2050) of power (im)balance scenarios between debt-driven economic forces (i.e. banks, firms), and conservation forces, on two ecosystem services (food production, climate regulation) and biodiversity. The model shows the trade-offs and synergies among these indicators for Business As Usual as compared to alternative scenarios. Results show that debt-driven economic forces can partially support environmental conservation, provided the state's role in protecting the environment is reinforced. Our analysis provides a lesson for developing countries that are highly dependent on debt-based production systems: sustainable development pathways can be achievable in the short and medium terms; however, reaching long-term sustainability requires reduced dependency on external financial powers, as well as further government intervention to protect the environment from the rough edges of the market economy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13280-019-01286-8) contains supplementary material, which is available to authorized users.

A debt-based economy cannot survive without economic growth. However, if private debt consistently grows faster than GDP, the consequences are financial crises and the current unprecedented level of global debt. This policy dilemma is aggravated by the lack of analyses factoring the impact of debt-growth cycles on the environment. What is really the relationship between debt and natural resource sustainability, and what is the role of debt in decoupling economic growth from natural resource availability? Here we present a conceptual Agent-Based Model (ABM) that integrates an environmental system into an ABM representation of Steve Keen's debt-based economic models. Our model explores the extent to which debt-driven processes, within debt-based economies, enhance the decoupling between economic growth and the availability of natural resources. Interestingly, environmental and economic collapse in our model are not caused by debt growth, or the debt-based nature of the economic system itself (i.e. the 'what'), but rather, these are due to the inappropriate use of debt by private actors (i.e. the 'how'). Firms inappropriately use bank credits for speculative goals–rather than production-oriented ones–and for exponentially increasing rates of technological development. This context creates temporal mismatches between natural resource growth and firms' resource extraction rates, as well as between economic growth and the capacity of the government to effectively implement natural resource conservation policies. This paper discusses the extent to which economic growth and the availability of natural resources can be re-coupled through a more sustainable use of debt, for instance by shifting mainstream banking forces to partially support environmental conservation as well as economic growth.

We explore the evolutionary nature of interactions between government policy, farm decision-making and ecosystem services in Shucheng County, Anhui Province, 1950–2015. Analyses of ecological, social and economic trends are complemented by interviews with local farmers. Since the Household Responsibility System started in 1980, there has been a trade-off between rising levels of provisioning services and falling levels of regulating services with evidence that critical thresholds have been passed for water quality. Using a Framework for Ecosystem Service Provision, we argue that farmers have acted only as ecosystem service providers and have not influenced the policies that have brought about the trade-offs. Over the period, ecological degradation is best described as an example of 'creeping normalcy' where cumulative conventional actions by individual farmers produce unsustainable losses in regulating services. The Chinese government should act to balance the various ecosystem services through valuation and national policy. In this respect, there is a need for agencies that can provide place-based advice to farmers that will allow them to maintain productivity levels while pursuing restorative actions. Even with new policies, the draw of urban employment, high production costs and an ageing population threaten the viability of farming in these marginal agricultural areas.

The expansion of land used for crop production causes variable direct and indirect greenhouse gas emissions, and other economic, social and environmental effects. We analyse the use of life cycle analysis (LCA) for estimating the carbon intensity of biofuel production from indirect land-use change (ILUC). Two approaches are critiqued: direct, attributional life cycle analysis and consequential life cycle analysis (CLCA). A proposed hybrid 'combined model' of the two approaches for ILUC analysis relies on first defining the system boundary of the resulting full LCA. Choices are then made as to the modelling methodology (economic equilibrium or cause–effect), data inputs, land area analysis, carbon stock accounting and uncertainty analysis to be included. We conclude that CLCA is applicable for estimating the historic emissions from ILUC, although improvements to the hybrid approach proposed, coupled with regular updating, are required, and uncertainly values must be adequately represented; however, the scope and the depth of the expansion of the system boundaries required for CLCA remain controversial. In addition, robust prediction, monitoring and accounting frameworks for the dynamic and highly uncertain nature of future crop yields and the effectiveness of policies to reduce deforestation and encourage afforestation remain elusive. Finally, establishing compatible and comparable accounting frameworks for ILUC between the USA, the European Union, South East Asia, Africa, Brazil and other major biofuel trading blocs is urgently needed if substantial distortions between these markets, which would reduce its application in policy outcomes, are to be avoided.

Many ecosystem services (ES) models exist to support sustainable development decisions. However, most ES studies use only a single modelling framework and, because of a lack of validation data, rarely assess model accuracy for the study area. In line with other research themeswhich have high model uncertainty, such as climate change, ensembles of ES models may better serve decision-makers by providing more robust and accurate estimates, as well as provide indications of uncertainty when validation data are not available. To illustrate the benefits of an ensemble approach, we highlight the variation between alternative models, demonstrating that there are large geographic regionswhere decisions based on individual models are not robust.We test if ensembles are more accurate by comparing the ensemble accuracy of multiple models for six ES against validation data across sub-Saharan Africa with the accuracy of individual models. We find that ensembles are better predictors of ES, being 5.0–6.1%more accurate than individualmodels.We also find that the uncertainty (i.e. variation among constituent models) of the model ensemble is negatively correlated with accuracy and so can be used as a proxy for accuracy when validation is not possible (e.g. in data-deficient areas or when developing scenarios). Since ensembles are more robust, accurate and convey uncertainty, we recommend that ensemble modelling should be more widely implemented within ES science to better support policy choices and implementation. ; The UK Ecosystem Services for Poverty Alleviation program (ESPA; www.espa.ac.uk) and 'EnsemblES - Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models and the Spanish Government through María de Maeztu excellence accreditation 2018-2021. ; http://www.elsevier.com/locate/scitotenv ; am2021 ; Zoology and Entomology

Faced with environmental degradation, governments worldwide are developing policies to safeguard ecosystem services (ES). Many ES models exist to support these policies, but they are generally poorly validated, especially at large scales, which undermines their credibility. To address this gap, we describe a study of multiple models of five ES, which we validate at an unprecedented scale against 1675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by the existing models. These potential ES models can also be used as inputs to new models for realised ES (use of charcoal, firewood, grazing resources and water), by adding information on human population density. We find that increasing model complexity can improve estimates of both potential and realised ES, suggesting that developing more detailed models of ES will be beneficial. Furthermore, in 85% of cases, human population density alone was as good or a better predictor of realised ES than ES models, suggesting that it is demand, rather than supply that is predominantly determining current patterns of ES use. Our study demonstrates the feasibility of ES model validation, even in data-deficient locations such as sub-Saharan Africa. Our work also shows the clear need for more work on the demand side of ES models, and the importance of model validation in providing a stronger base to support policies which seek to achieve sustainable development in support of human well-being.

Faced with environmental degradation, governments world-wide are developing policies to safeguard ecosystem services (ES). Many ES models exist to support these policies, but they are generally poorly validated, especially at large scales, which undermines their credibility. To address this gap, we describe a study of multiple models of five ES, which we validate at an unprecedented scale against 1,675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by existing models. These potential ES models can also be used as inputs to new models for realised ES (use of charcoal, firewood, grazing resources and water), by adding information on human population density. We find that increasing model complexity can improve estimates of both potential and realised ES, suggesting that developing more detailed models of ES will be beneficial. Furthermore, in 85% of cases, human population density alone was as good or a better predictor of realised ES than ES models, suggesting that it is demand, rather than supply that is predominantly determining current patterns of ES use. Our study demonstrates the feasibility of ES model validation, even in data-deficient locations such as sub-Saharan Africa. Our work also shows the clear need for more work on the supply-side of ES models, and the importance of model validation in providing a stronger base to support policies which seek to achieve sustainable development in support of human well-being.

Although satellite‐based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations – Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS‐EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS‐EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS‐EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long‐term coordinated actions. ; DSS, RS, DR and JP were financed by the EU BON project that is a Seventh Framework Programme funded by the European Union under Contract No. 308454. ; Peer reviewed