Corrigendum: Reductions in global biodiversity loss predicted from conservation spending.

This corrects the article DOI: 10.1038/nature24295.

A guide to qualitative attribution methods for evaluation in conservation.

Knowledge of what conservation interventions improve biodiversity outcomes, and in which circumstances, is imperative. Experimental and quasi-experimental methods are increasingly used to establish causal inference and build the evidence base on the effectiveness of interventions, but their ability to provide insight into how and under what conditions an intervention should be implemented to improve biodiversity outcomes faces limitations. A suite of attribution methods that leverage qualitative methods for causal inference is available but underutilized in conversation impact evaluation. This article provides a guide to 5 such qualitative attribution methods: contribution analysis, process tracing, realist evaluation, qualitative comparative analysis, and most significant change. It defines and introduces each method and then illustrates how they could be applied through a case study of community conservancies in Namibia. This guide provides examples of how qualitative attribution methods can advance knowledge of what works, in which contexts, and why in biodiversity conservation.

Guía para los métodos de atribución cualitativa para la evaluación en conservación Resumen El conocimiento sobre cuáles intervenciones de conservación son las que aumentan los resultados en biodiversidad y en cuáles circunstancias sucede esto es imperativo. Los métodos experimentales y semiexperimentales se usan cada vez más para establecer la inferencia casual y construir la base de evidencias sobre la efectividad de las intervenciones, pero su capacidad para proporcionar conocimiento sobre cómo y bajo cuáles condiciones se debería implementar una intervención para aumentar los resultados en biodiversidad enfrenta limitaciones. Un conjunto de métodos de atribución que impulse los métodos cualitativos para la inferencia casual se encuentra disponible pero poco utilizado en la evaluación de los impactos de conservación. Este artículo proporciona una guía para cinco de los métodos de atribución cualitativa: análisis de contribución, rastreo de procesos, evaluación realista, análisis cualitativo comparativo y el cambio más significativo. La guía define e introduce cada método y después ilustra cómo podrían aplicarse mediante un estudio de caso de conservación en Namibia. Esta guía proporciona ejemplos de cómo los métodos de atribución cualitativa pueden incrementar el conocimiento de qué funciona, en cuáles contextos y por qué en la conservación d la biodiversidad.

Reductions in global biodiversity loss predicted from conservation spending.

Halting global biodiversity loss is central to the Convention on Biological Diversity and United Nations Sustainable Development Goals, but success to date has been very limited. A critical determinant of success in achieving these goals is the financing that is committed to maintaining biodiversity; however, financing decisions are hindered by considerable uncertainty over the likely impact of any conservation investment. For greater effectiveness, we need an evidence-based model that shows how conservation spending quantitatively reduces the rate of biodiversity loss. Here we demonstrate such a model, and empirically quantify how conservation investment reduced biodiversity loss in 109 countries (signatories to the Convention on Biological Diversity and Sustainable Development Goals), by a median average of 29% per country between 1996 and 2008. We also show that biodiversity changes in signatory countries can be predicted with high accuracy, using a dual model that balances the effects of conservation investment against those of economic, agricultural and population growth (human development pressures). Decision-makers can use this model to forecast the improvement that any proposed biodiversity budget would achieve under various scenarios of human development pressure, and then compare these forecasts to any chosen policy target. We find that the impact of spending decreases as human development pressures grow, which implies that funding may need to increase over time. The model offers a flexible tool for balancing the Sustainable Development Goals of human development and maintaining biodiversity, by predicting the dynamic changes in conservation finance that will be needed as human development proceeds.

Navigating Multidimensional Social-Ecological System Trade-Offs across Sanitation Alternatives in an Urban Informal Settlement.

Urban growth in low- and middle-income countries has intensified the need to expand sanitation infrastructure, especially in informal settlements. Sanitation approaches for these settings remain understudied, particularly regarding multidimensional social-ecological outcomes. Guided by a conceptual framework (developed in parallel with this study) re-envisioning sanitation as a human-derived resource system, here we characterize existing and alternative sanitation scenarios in an informal settlement in Kampala, Uganda. Combining two core research approaches (household survey analysis, process modeling), we elucidate factors associated with user satisfaction and evaluate each scenario's resource recovery potential, economic implications, and environmental impacts. We find that existing user satisfaction is associated with factors including cleaning frequency, sharing, and type of toilets, and we demonstrate that alternative sanitation systems may offer multidimensional improvements over existing latrines, drying beds, and lagoons. Transitioning to anaerobic treatment could recover energy while reducing overall net costs by 26-65% and greenhouse gas emissions by 38-59%. Alternatively, replacing pit latrines with container-based facilities greatly improves recovery potential in most cases (e.g., a 2- to 4-fold increase for nitrogen) and reduces emissions by 46-79%, although costs increase. Overall, this work illustrates how our conceptual framework can guide empirical research, offering insight into sanitation for informal settlements and more sustainable resource systems.

Re-Envisioning Sanitation As a Human-Derived Resource System.

Sanitation remains a global challenge, both in terms of access to toilet facilities and resource intensity (e.g., energy consumption) of waste treatment. Overcoming barriers to universal sanitation coverage and sustainable resource management requires approaches that manage bodily excreta within coupled human and natural systems. In recent years, numerous analytical methods have been developed to understand cross-disciplinary constraints, opportunities, and trade-offs around sanitation and resource recovery. However, without a shared language or conceptual framework, efforts from individual disciplines or geographic contexts may remain isolated, preventing the accumulation of generalized knowledge. Here, we develop a version of the social-ecological systems framework modified for the specific characteristics of bodily excreta. This framework offers a shared vision for sanitation as a human-derived resource system, where people are part of the resource cycle. Through sanitation technologies and management strategies, resources including water, organics, and nutrients accumulate, transform, and impact human experiences and natural environments. Within the framework, we establish a multitiered lexicon of variables, characterized by breadth and depth, to support harmonized understanding and development of models and analytical approaches. This framework's refinement and use will guide interdisciplinary study around sanitation to identify guiding principles for sanitation that advance sustainable development at the nature-society interface.

Targeting global conservation funding to limit immediate biodiversity declines.

Inadequate funding levels are a major impediment to effective global biodiversity conservation and are likely associated with recent failures to meet United Nations biodiversity targets. Some countries are more severely underfunded than others and therefore represent urgent financial priorities. However, attempts to identify these highly underfunded countries have been hampered for decades by poor and incomplete data on actual spending, coupled with uncertainty and lack of consensus over the relative size of spending gaps. Here, we assemble a global database of annual conservation spending. We then develop a statistical model that explains 86% of variation in conservation expenditures, and use this to identify countries where funding is robustly below expected levels. The 40 most severely underfunded countries contain 32% of all threatened mammalian diversity and include neighbors in some of the world's most biodiversity-rich areas (Sundaland, Wallacea, and Near Oceania). However, very modest increases in international assistance would achieve a large improvement in the relative adequacy of global conservation finance. Our results could therefore be quickly applied to limit immediate biodiversity losses at relatively little cost.

The impacts of agroforestry interventions on agricultural productivity, ecosystem services, and human well-being in low- and middle-income countries: A systematic review.

Background: Agroforestry, the intentional integration of trees or other woody perennials with crops or livestock in production systems, is being widely promoted as a conservation and development tool to help meet the 2030 UN Sustainable Development Goals. Donors, governments, and nongovernmental organizations have invested significant time and resources into developing and promoting agroforestry policies and programs in low- and middle-income countries (LMICs) worldwide. While a large body of literature on the impacts of agroforestry practices in LMICs is available, the social-ecological impacts of agroforestry interventions is less well-studied. This knowledge gap on the effectiveness of agroforestry interventions constrains possibilities for evidence-based policy and investment decisions to advance sustainable development objectives. Objectives: The primary objective of this Campbell systematic review was to synthesize the available evidence on the impacts of agroforestry interventions in LMICs on agricultural productivity, ecosystem services, and human well-being. The secondary objectives were to identify key pathways through which agroforestry interventions lead to various outcomes and how the interventions affect different sub-groups of the population. Search Methods: This review is based on a previously created evidence and gap map (EGM) of studies evaluating the impacts of agroforestry practices and interventions on agricultural productivity, ecosystem services, and human well-being. We included published and unpublished literature in the English language covering the period between 2000 and October 20, 2017. We searched six academic databases and 19 organization websites to identify potentially relevant studies. The search was conducted for our EGM in mid-2017, and we did not conduct an additional search for this systematic review. Selection Criteria: We included randomized control trials (RCTs) and quasi-experimental studies assessing the effect of an agroforestry intervention on at least one outcome measure of agricultural productivity, ecosystem services, or human well-being for farmers and their farmland in LMICs. Agroforestry interventions include any program or policy designed to promote and support the adoption or maintenance of agroforestry practices, which include trees on farms, silvopasture, shade-grown crops, and homegardens with trees, among others. Moreover, the studies needed to include a nonagroforestry comparator, such as conventional agriculture or forestry systems or a before-after comparison. Data Collection and Analysis: We used a standardized data extraction spreadsheet to extract details about each included study. We also used a standardized form to assess risk of bias for each of the included studies in this SR. Meta-analysis techniques were used to combine and synthesize effect size estimates for the outcomes measures that had sufficient data. We used a random effects models for the meta-analyses and use Hedge's g (difference in means divided by the pooled standard deviation) to report effect size estimates. The outcomes without enough evidence for meta-analysis were discussed narratively. Main Results: We identified 11 studies across nine countries, all of which used quasi-experimental methods. Overall, the quality of the evidence base was assessed as being low. Studies were rated as having high or critical risk of bias if they failed to convincingly address more than one of the main potential sources of bias, namely selection bias, group equivalence, and spillover effects. Given the low number of studies and the high risk of bias of the evidence base, the results of this SR are limited and should be considered a baseline for future work. The results of the meta-analysis for impacts on yields indicated that agroforestry interventions overall may lead to a large, positive impact on yield (Hedge's g = 1.16 [-0.35, 2.67] (p = .13)), though there was high heterogeneity in the results (I 2 = 98.99%, τ 2 = 2.94, Q(df = 4) = 370.7). There were positive yield impacts for soil fertility replenishment practices, including incorporating trees in agricultural fields and improved fallow practices in fields where there are severe soil fertility issues. In other cases, incorporating trees into the production system reduced productivity and took land out of production for conservation benefits. These systems generally used an incentive provision scheme to economically offset the reductions in yields. The result of the meta-analysis on income suggests that agroforestry interventions overall may lead to a small, positive impact on income (Hedge's g = 0.12 [-0.06, 0.30] (p = .20)), with moderately high heterogeneity in the results (I 2 = 75.29%, τ 2 = 0.04, Q(df = 6) = 19.16). In cases where improvement yields were reported, there were generally attendant improvements in income. In the cases where payments were provided to offset the potential loss in yields, incomes also generally improved, though there were mixed results for the certification programs and the tenure security permitting scheme. One program, which study authors suggested may have been poorly targeted, had negative yield impacts. There was not enough comparable evidence to quantitatively synthesize the impacts of agroforestry interventions on nutrition and food security outcomes, though the results indicted positive or neutral impacts on dietary diversity and food intake were likely. Surprisingly, there was little evidence on the impacts of agroforestry interventions on environmental outcomes, and there was no consistency of environmental indicator variables used. However, what has been studied indicates that the environmental benefits are being achieved to at least some extent, consistent with the broader literature on agroforestry practices. The evidence base was insufficient to evaluate the interaction between environmental and social impacts. Several studies explicitly considered variable impacts across different population sub-groups, including differential impacts on small-holders versus large-holders, on woman-headed households versus male-headed households, and on richer groups versus poorer groups. Small-holder farmers typically experienced the most positive effect sizes due to the agroforestry interventions. Women and poorer groups had mixed outcomes relative to men and richer households, highlighting the importance of considering these groups in intervention design. Authors' Conclusions: There is limited evidence of the impacts of agroforestry interventions, restricting our ability to draw conclusions on the effect sizes of different intervention types. The existing evidence forms a baseline for future research and highlights the importance of considering equity and socio-economic factors in determining suitable intervention design. Some key implications for practice and policy include investing in programs that include pilot programs, funding for project evaluation, and that address key equity issues, such as targeting to smallholders, women, poor, and marginalized groups. Funding should also be given to implementing RCTs and more rigorous quasi-experimental impact evaluations of agroforestry interventions over longer time-periods to collect robust evidence of the effectiveness of various schemes promoting agroforestry practices.

Strengthen causal models for better conservation outcomes for human well-being.

BACKGROUND: Understanding how the conservation of nature can lead to improvement in human conditions is a research area with significant growth and attention. Progress towards effective conservation requires understanding mechanisms for achieving impact within complex social-ecological systems. Causal models are useful tools for defining plausible pathways from conservation actions to impacts on nature and people. Evaluating the potential of different strategies for delivering co-benefits for nature and people will require the use and testing of clear causal models that explicitly define the logic and assumptions behind cause and effect relationships. OBJECTIVES AND METHODS: In this study, we outline criteria for credible causal models and systematically evaluated their use in a broad base of literature (~1,000 peer-reviewed and grey literature articles from a published systematic evidence map) on links between nature-based conservation actions and human well-being impacts. RESULTS: Out of 1,027 publications identified, only ~20% of articles used any type of causal models to guide their work, and only 14 total articles fulfilled all criteria for credibility. Articles rarely tested the validity of models with empirical data. IMPLICATIONS: Not using causal models risks poorly defined strategies, misunderstanding of potential mechanisms for affecting change, inefficient use of resources, and focusing on implausible efforts for achieving sustainability.

Ensuring a Post-COVID Economic Agenda Tackles Global Biodiversity Loss.

The COVID-19 pandemic has caused dramatic and unprecedented impacts on both global health and economies. Many governments are now proposing recovery packages to get back to normal, but the 2019 Intergovernmental Science-Policy Platform for Biodiversity and Ecosystem Services Global Assessment indicated that business as usual has created widespread ecosystem degradation. Therefore, a post-COVID world needs to tackle the economic drivers that create ecological disruptions. In this perspective, we discuss a number of tools across a range of actors for both short-term stimulus measures and longer-term revamping of global, national, and local economies that take biodiversity into account. These include measures to shift away from activities that damage biodiversity and toward those supporting ecosystem resilience, including through incentives, regulations, fiscal policy, and employment programs. By treating the crisis as an opportunity to reset the global economy, we have a chance to reverse decades of biodiversity and ecosystem losses.

Explaining long-term outcome trajectories in social-ecological systems.

Improved knowledge of long-term social and environmental trends and their drivers in coupled human and natural systems is needed to guide nature and society along a more sustainable trajectory. Here we combine common property theory and experimental impact evaluation methods to develop an approach for analyzing long-term outcome trajectories in social-ecological systems (SESs). We constructed robust counterfactual scenarios for observed vegetation outcome trajectories in the Indian Himalaya using synthetic control matching. This approach enabled us to quantify the contribution of a set of biophysical and socioeconomic factors in shaping observed outcomes. Results show the relative importance of baseline vegetation condition, governance, and demographic change in predicting long-term ecological outcomes. More generally, the findings suggest the broad potential utility of our approach to analyze long-term outcome trajectories, target new policy interventions, and assess the impacts of policies on sustainability goals in SESs across the globe.

Enhancing the engagement of U.S. private foundations with conservation science.

Funding for conservation is limited, and its investment for maximum conservation gain can likely be enhanced through the application of relevant science. Many donor institutions support and use science to pursue conservation goals, but their activities remain relatively unfamiliar to the conservation-science community. We examined the priorities and practices of U.S.-based private foundations that support biodiversity conservation. We surveyed 50 donor members of the Consultative Group on Biological Diversity (CGBD) to address three questions: (1) What support do CGBD members provide for conservation science? (2) How do CGBD members use conservation science in their grant making and strategic thinking? (3) How do CGBD members obtain information about conservation science? The 38 donor institutions that responded to the survey made $340 million in grants for conservation in 2005, including $62 million for conservation science. Individual foundations varied substantially in the proportion of conservation funds allocated to science. Foundations also varied in the ways and degree to which they used conservation science to guide their grant making. Respondents found it "somewhat difficult" to stay informed about conservation science relevant to their work, reporting that they accessed conservation science information mainly through their grantees. Many funders reported concerns about the strategic utility of funding conservation science to achieve conservation gains. To increase investment by private foundations in conservation science, funders, researchers, and conservation practitioners need to jointly identify when and how new scientific knowledge will lower barriers to conservation gains. We envision an evolving relationship between funders and conservation scientists that emphasizes primary research and synthesis motivated by (1) applicability, (2) human-ecosystem interactions, (3) active engagement among scientists and decision makers, and (4) broader communication of relevant scientific information.

Neuropsychological Profiles of Written Expression Learning Disabilities Determined by Concordance-Discordance Model Criteria.

Children with specific learning disabilities (SLD) have disparate neuropsychological processing deficits that interfere with academic achievement in spelling, writing fluency, and/or written expression (WE). Although there are multiple potential causes of WE SLD, there is a paucity of research exploring this critical academic skill from a neuropsychological perspective. This study examined the neuropsychological profiles of WE SLD subtypes defined using the concordance-discordance model (C-DM) of SLD identification. Participants were drawn from a sample of 283 children (194 boys, 89 girls) aged 6 years to 16 years old (M(age) = 9.58 years, SD = 2.29 years) referred for comprehensive neuropsychological evaluations in school settings and subsequently selected based on C-DM determined spelling, writing fluency, and WE SLD. WE SLD subtypes differed on several psychomotor, memory, and executive function measures (F range = 2.48-5.07, p range = .049 to <.001), suggesting that these children exhibit distinct patterns of neuropsychological processing strengths and weaknesses. Findings have relevance for differential diagnosis of WE subtypes, discriminating WE SLD subtypes from low WE achievement, and developing differentiated evidence-based instruction and intervention for children with WE SLD. Limitations and future research will be addressed.

Utilization of the comprehensive trail making test as a measure of executive functioning in children and adolescents with traumatic brain injuries.

Traumatic brain injury (TBI) often results in long-term negative effects in attention, memory, perception, language, and executive functioning. Children and adolescents are the most vulnerable as TBIs are the leading cause of death and disability for this age group. Despite these high proportions and detrimental effects, few studies have utilized a developmentally appropriate, standardized measure to assess executive functioning within a pediatric TBI population. The current study compared children and adolescents who had sustained a TBI with a non-injured, matched control group on executive functioning using the Comprehensive Trail Making Test (CTMT). Data analyses revealed significant differences between groups on the CTMT Composite Index, each individual trail, and a combination of trails but with no within-group differences. Confirmatory factor analysis revealed that a single-factor model was a better fit for the present sample of TBI participants than the two-factor model evident within the CTMT standardization sample.