Suchergebnisse

International audience ; Meeting the UN Sustainable Development Goals requires reconciling development with biodiversity conservation. Governments and lenders increasingly call for major industrial developments to offset unavoidable biodiversity loss but there are few robust evaluations of whether offset interventions ensure no net loss of biodiversity. We focus on the biodiversity offsets associated with the high-profile Ambatovy mine in Madagascar and evaluate their effectiveness at delivering no net loss of forest. As part of their efforts to mitigate biodiversity loss, Ambatovy compensate for forest clearance at the mine site by slowing deforestation driven by small-scale agriculture elsewhere. Using a range of methods, including extensive robustness checks exploring 116 alternative model specifications, we show that the offsets are on track to avert as much deforestation as was caused by the mine. This encouraging result shows that biodiversity offsetting can contribute towards mitigating environmental damage from a major industrial development, even within a weak state, but there remain important caveats with broad application. Our approach could serve as a template to facilitate other evaluations and so build a stronger evidence-base of the effectiveness of no net loss interventions.

International audience ; Meeting the UN Sustainable Development Goals requires reconciling development with biodiversity conservation. Governments and lenders increasingly call for major industrial developments to offset unavoidable biodiversity loss but there are few robust evaluations of whether offset interventions ensure no net loss of biodiversity. We focus on the biodiversity offsets associated with the high-profile Ambatovy mine in Madagascar and evaluate their effectiveness at delivering no net loss of forest. As part of their efforts to mitigate biodiversity loss, Ambatovy compensate for forest clearance at the mine site by slowing deforestation driven by small-scale agriculture elsewhere. Using a range of methods, including extensive robustness checks exploring 116 alternative model specifications, we show that the offsets are on track to avert as much deforestation as was caused by the mine. This encouraging result shows that biodiversity offsetting can contribute towards mitigating environmental damage from a major industrial development, even within a weak state, but there remain important caveats with broad application. Our approach could serve as a template to facilitate other evaluations and so build a stronger evidence-base of the effectiveness of no net loss interventions.

International audience ; Meeting the UN Sustainable Development Goals requires reconciling development with biodiversity conservation. Governments and lenders increasingly call for major industrial developments to offset unavoidable biodiversity loss but there are few robust evaluations of whether offset interventions ensure no net loss of biodiversity. We focus on the biodiversity offsets associated with the high-profile Ambatovy mine in Madagascar and evaluate their effectiveness at delivering no net loss of forest. As part of their efforts to mitigate biodiversity loss, Ambatovy compensate for forest clearance at the mine site by slowing deforestation driven by small-scale agriculture elsewhere. Using a range of methods, including extensive robustness checks exploring 116 alternative model specifications, we show that the offsets are on track to avert as much deforestation as was caused by the mine. This encouraging result shows that biodiversity offsetting can contribute towards mitigating environmental damage from a major industrial development, even within a weak state, but there remain important caveats with broad application. Our approach could serve as a template to facilitate other evaluations and so build a stronger evidence-base of the effectiveness of no net loss interventions.

Rewilding as a conservation strategy is gaining increasing scientific, political and public attention, yet empirical evaluations of its impacts remain scarce, especially with regards to ecosystem services. We provide evidence of the change in three ecosystem services (timber [provisioning], pollination [regulating], and aesthetics [cultural]) from up to 27 years of a moorland rewilding strategy in the Scottish Highlands using a chronosequence of rewilded plots and adjacent controls. These services were assessed in the field and using online surveys. We found that rewilding increased aboveground woody biomass and restored natural tree recruitment processes, although the latter only emerged after at least 15 years of rewilding. Rewilding caused a linear increase in perceived aesthetic quality over the first 27 years, but had no effect on pollination visitation rates. Thus, we conclude that rewilding can be used for ecosystem service recovery in moorland landscapes, but that results vary depending on the preferred service.

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

Providing safe sanitation in the developing world is still a major hurdle to achieving Sustainable Development Goal number six, with 61% of the global population lacking safely managed sanitation services. Circular economy in the context of sanitation focuses on the whole sanitation chain which includes the provision of toilets, the collection of waste, treatment and transformation into sanitation-derived products including fertiliser, fuel and clean water. As well as potentially reducing the cost of toilet provision, a circular economy approach also has the potential to enable positive environmental and health impacts, unlike other systems where waste may be discharged untreated into the environment. The implementation of a system level transformation is not simple, considering operator capacity, lack of funding, slowly growing acceptance by local communities, and a policy landscape which can be inconsistent in its support for the circular economy. As India invests in long-term infrastructure to improve citizens' quality of life (e.g., Swachh Bharat Mission), it could incorporate circular economy principles into the design of infrastructure, creating effective urban nutrient and material cycles, enhancing economic development and welfare. This represents a significant opportunity for government and businesses in India to develop circular sanitation infrastructure to recover and valorise biological nutrients. After collecting information from five case studies across India, covering different treatment technologies, waste-derived products, markets and contexts; this research identifies the main barriers and enablers for circular sanitation business models to succeed. Whilst there were many different institutional and technological arrangements, common issues of managing and enforcing incoming waste and competing with chemical fertilisers were found.

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.

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 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.

Background: Interest is growing in digital and telehealth delivery of mental health services, but data are scarce on outcomes in routine care. The federally funded Australian MindSpot Clinic provides online and telephone psychological assessment and treatment services to Australian adults. We aimed to summarise demographic characteristics and treatment outcomes of patients registered with MindSpot over the first 7 years of clinic operation. Methods: We used an observational design to review all patients who registered for assessment with the MindSpot Clinic between Jan 1, 2013, and Dec 31, 2019. We descriptively analysed the demographics, service preferences, and baseline symptoms of patients. Among patients enrolled in a digital treatment course, we evaluated scales of depression (Patient Health Questionnaire-9 [PHQ-9]) and anxiety (Generalized Anxiety Disorder 7-Item Scale [GAD-7]), as primary measures of treatment outcome, from the screening assessment to post-treatment and a 3 month follow-up. The Kessler Psychological Distress 10-Item Plus Scale was also used to assess changes in general distress and disability, and course satisfaction was measured post-treatment. Outcomes: A total of 121 652 screening assessments were started, of which 96 018 (78·9%) were completed. The mean age of patients was 35·7 years (SD 13·8) and 88 702 (72·9%) were women. Based on available assessment data, 36 866 (34·5%) of 106 811 participants had never previously spoken to a health professional about their symptoms, and most people self-reported symptoms of anxiety (88 879 [81·9%] of 108 494) or depression (78 803 [72·6%] of 108 494), either alone or in combination, at baseline. 21 745 patients started treatment in a therapist-guided online course, of whom 14 503 (66·7%) completed treatment (≥four of five lessons). Key trends in service use included an increase in the proportion of people using MindSpot primarily for assessment and information, from 52·6% in 2013 to 66·7% in 2019, while the proportion primarily seeking online treatment decreased, from 42·6% in 2013 to 26·7% in 2019. Effect sizes and percentage changes were large for estimated mean scores on the PHQ-9 and GAD-7 from assessment to post-treatment (PHQ-9, Cohen's d effect size 1·40 [95% CI 1·37-1·43]; and GAD-7, 1·45 [1·42-1·47]) and the 3 month follow-up (PHQ-9, 1·36 [1·34-1·38]; and GAD-7, 1·42 [1·40-1·44]); proportions of patients with reliable symptom deterioration (score increase of ≥6 points [PHQ-9] or ≥5 points [GAD-7]) were low post-treatment (of 13 058 respondents, 184 [1·4%] had symptom deterioration on the PHQ-9 and 282 [2·2%] on the GAD-7); and patient satisfaction rates were high (12 452 [96·6%] of 12 895 respondents would recommend the course and 12 433 [96·7%] of 12 860 reported the course worthwhile). We also observed small improvements in disability following treatment as measured by days out of role. Interpretation: Our findings indicate improvement in psychological symptoms and positive reception among patients receiving online mental health treatment. These results support the addition of digital services such as MindSpot as a component in contemporary national mental health systems. Funding: None. ; Funding agencies: Australian GovernmentAustralian GovernmentCGIAR

AbstractA billion rural people live near tropical forests. Urban populations need them for water, energy and timber. Global society benefits from climate regulation and knowledge embodied in tropical biodiversity. Ecosystem service valuations can incentivise conservation, but determining costs and benefits across multiple stakeholders and interacting services is complex and rarely attempted. We report on a 10-year study, unprecedented in detail and scope, to determine the monetary value implications of conserving forests and woodlands in Tanzania's Eastern Arc Mountains. Across plausible ranges of carbon price, agricultural yield and discount rate, conservation delivers net global benefits (+US$8.2B present value, 20-year central estimate). Crucially, however, net outcomes diverge widely across stakeholder groups. International stakeholders gain most from conservation (+US$10.1B), while local-rural communities bear substantial net costs (-US$1.9B), with greater inequities for more biologically important forests. Other Tanzanian stakeholders experience conflicting incentives: tourism, drinking water and climate regulation encourage conservation (+US$72M); logging, fuelwood and management costs encourage depletion (-US$148M). Substantial global investment in disaggregating and mitigating local costs (e.g., through boosting smallholder yields) is essential to equitably balance conservation and development objectives.