Correction: Emerging Evidence on the Effectiveness of Tropical Forest Conservation.

[This corrects the article DOI: 10.1371/journal.pone.0159152.].

Sunflower-Associated Reductions in Varroa Mite Infestation of Honey Bee Colonies.

Landscapes can affect parasite epidemiology in wild and agricultural animals. Honey bees are threatened by loss of floral resources and by parasites, principally the mite Varroa destructor and the viruses it vectors. Existing mite control relies heavily on chemical treatments that can adversely affect bees. Alternative, pesticide-free control methods are needed to mitigate infestation with these ectoparasites. Many flowering plants provide nectar and pollen that confer resistance to parasites. Enrichment of landscapes with antiparasitic floral resources could therefore provide a sustainable means of parasite control in pollinators. Floral rewards of Asteraceae plants can reduce parasitic infection in diverse bee species, including honey and bumble bees. Here, we tested the effects of sunflower (Helianthus annuus) cropland and pollen supplementation on honey bee resistance to macro- and microparasites. Although sunflower had nonsignificant effects on microparasites, We found that increased sunflower pollen availability correlated with reduced Varroa mite infestation in landscapes and pollen-supplemented colonies. At the landscape level, each doubling of sunflower crop area was associated with a 28% reduction in mite infestation. In field trials, late-summer supplementation of colonies with sunflower pollen reduced mite infestation by 2.75-fold relative to artificial pollen. United States sunflower crop acreage has declined by 2% per year since 1980, however, suggesting reduced availability of this floral resource. Although further research is needed to determine whether the observed effects represent direct inhibition of mite fecundity or mite-limiting reductions in honey bee brood-rearing, our findings suggest the potential for sunflower plantings or pollen supplements to counteract a major driver of honey bee losses worldwide.

Evidence for the impacts of agroforestry on ecosystem services and human well-being in high-income countries: a systematic map.

BACKGROUND: Agroforestry bridges the gap that often separates agriculture and forestry by building integrated systems to address both environmental and socio-economic objectives. Existing empirical research has suggested that agroforestry-the integration of trees with crops and/or livestock-can prevent environmental degradation, improve agricultural productivity, increase carbon sequestration, and support healthy soil and healthy ecosystems while providing stable incomes and other benefits to human welfare. However, the extent of the literature supporting or refuting these claims has not been well documented. This study addresses this research gap by collating and describing the evidence for the impacts of agroforestry on ecosystem services and human well-being in high-income countries and presents the characteristics and gaps in the literature. METHODS: We searched 5 primary databases and 24 organizational websites using a pre-defined search string designed to capture articles relating agroforestry practices and policy interventions to outcomes in high-income countries. Searches included peer-reviewed and grey literature published in the English language between January 1990 and June 2020. We screened the identified articles for inclusion or exclusion in two stages: title/abstract and full text. We extracted data from articles included at the full-text stage to form the map and associated database. For inclusion, the study in question must have assessed the impacts of the deliberate promotion and/or actual integration of woody perennials (trees, shrubs, etc.) with agricultural crops and/or animals. RESULTS: Our search returned 31,852 articles of which we included 585 primary articles, 6 ongoing primary articles, and 41 systematically conducted literature reviews. The articles spanned three decades and 31 countries. The most studied practices are on linear boundary plantings (hedgerows, shelterbelts, windbreaks, and riparian buffers) and silvopasture systems. The most studied outcome is regulation and maintenance of physical, chemical, and biological conditions as an ecosystem service, followed by agricultural yield and mediation of waste/toxics/other nuisances (nutrient runoff and carbon storage). CONCLUSIONS: Results highlight key evidence gaps and areas where research has concentrated. Knowledge on the impacts of specific policy interventions to promote agroforestry remains scarce. The impacts of actual agroforestry practices are more well-studied, but the kinds of practices studied are limited, with most research focusing on two-component systems consisting of a simple tree configuration with one crop or livestock species, such as shelterbelts, windbreaks, and hedgerows, riparian buffers, and scattered trees on farms with crops and/or livestock. Regulating ecosystem services outcomes are by far the most studied, followed by agricultural productivity (an aspect of provisioning ecosystem services), while evidence on human well-being remains limited. We also found geographic biases, with little to no evidence for many countries. These biases suggest the strong need for further research to build the evidence base on agroforestry across high-income countries. The results can inform future research and policy decisions by making the evidence easily accessible and highlighting knowledge gaps as well as areas with enough evidence to conduct further systematic review.

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.

The Use of Charitable Food Assistance Among Low-Income Households in the United States.

BACKGROUND: About 11% of US households are food insecure, and many of those households seek charitable food assistance (CFA). However, little is understood about the nutritional composition of the diets of households receiving CFA, or the relationship between CFA and Supplemental Nutrition Assistance Program (SNAP) usage among low-income households. OBJECTIVE: The aim of the study was to compare the nutritional quality of foods obtained by CFA clients to those of similar nonclients. Furthermore, the study examined the timing of CFA use relative to the timing of SNAP use among CFA clients during the week. DESIGN/PARTICIPANTS: Analyses were conducted using 2012 US Department of Agriculture National Household Food Acquisition and Purchase Survey (FoodAPS), which collected data for 4826 households' food acquisitions during a 7-day survey week. Sixty-seven households reported using CFAs during the survey week. MAIN OUTCOMES MEASURE: The nutritional quality of food was measured by the ratios between food acquisition quantities and the US Department of Agriculture Thrifty Food Plan consumption recommendations. The date of SNAP use was compared with that of CFA use for CFA clients who were also SNAP recipients. STATISTICAL ANALYSES PERFORMED: Propensity score matching was utilized to construct a matching sample of CFA clients and nonclients. T tests were used to compare the means of variables. RESULTS: CFA clients were more likely to be food insecure (48% vs 28%, P < .001) and less likely to have access to a car (61.2% vs 84.8%, P < .001) than CFA nonclients. CFAs represent an important source of foods for CFA clients, taking up 28% of their total food at home acquisitions. CFA clients obtained more nonstarchy vegetables than matched nonclients. Furthermore, among the 45% of CFA clients who also participated in SNAP, the majority (52.4%) of them used SNAP benefits within 10 days of SNAP benefits distribution while most (67.9%) of those households used CFAs starting on day 11 or later after SNAP benefits were allocated. CONCLUSIONS: CFAs provide a substantial portion of the diets of their clients and, in particular, for foods that constitute components of healthy diets. For the proportion of CFA clients who received SNAP, this study finds evidence that CFA clients relied more on CFAs when their SNAP benefits were likely to run low.

Conservation agriculture and climate resilience.

Agricultural productivity growth is vital for economic and food security outcomes which are threatened by climate change. In response, governments and development agencies are encouraging the adoption of 'climate-smart' agricultural technologies, such as conservation agriculture (CA). However, there is little rigorous evidence that demonstrates the effect of CA on production or climate resilience, and what evidence exists is hampered by selection bias. Using panel data from Zimbabwe, we test how CA performs during extreme rainfall events - both shortfalls and surpluses. We control for the endogenous adoption decision and find that use of CA in years of average rainfall results in no yield gains, and in some cases yield loses. However, CA is effective in mitigating the negative impacts of deviations in rainfall. We conclude that the lower yields during normal rainfall seasons may be a proximate factor in low uptake of CA. Policy should focus promotion of CA on these climate resilience benefits.

A Bio-Economic Case Study of Canadian Honey Bee (Hymenoptera: Apidae) Colonies: Marker-Assisted Selection (MAS) in Queen Breeding Affects Beekeeper Profits.

Over the past decade in North America and Europe, winter losses of honey bee (Hymenoptera: Apidae) colonies have increased dramatically. Scientific consensus attributes these losses to multifactorial causes including altered parasite and pathogen profiles, lack of proper nutrition due to agricultural monocultures, exposure to pesticides, management, and weather. One method to reduce colony loss and increase productivity is through selective breeding of queens to produce disease-, pathogen-, and mite-resistant stock. Historically, the only method for identifying desirable traits in honey bees to improve breeding was through observation of bee behavior. A team of Canadian scientists have recently identified markers in bee antennae that correspond to behavioral traits in bees and can be tested for in a laboratory. These scientists have demonstrated that this marker-assisted selection (MAS) can be used to produce hygienic, pathogen-resistant honey bee colonies. Based on this research, we present a beekeeping case study where a beekeeper's profit function is used to evaluate the economic impact of adopting colonies selected for hygienic behavior using MAS into an apiary. Our results show a net profit gain from an MAS colony of between 2% and 5% when Varroa mites are effectively treated. In the case of ineffective treatment, MAS generates a net profit benefit of between 9% and 96% depending on the Varroa load. When a Varroa mite population has developed some treatment resistance, we show that MAS colonies generate a net profit gain of between 8% and 112% depending on the Varroa load and degree of treatment resistance.

Goldilocks and the Raster Grid: Selecting Scale when Evaluating Conservation Programs.

Access to high quality spatial data raises fundamental questions about how to select the appropriate scale and unit of analysis. Studies that evaluate the impact of conservation programs have used multiple scales and areal units: from 5x5 km grids; to 30m pixels; to irregular units based on land uses or political boundaries. These choices affect the estimate of program impact. The bias associated with scale and unit selection is a part of a well-known dilemma called the modifiable areal unit problem (MAUP). We introduce this dilemma to the literature on impact evaluation and then explore the tradeoffs made when choosing different areal units. To illustrate the consequences of the MAUP, we begin by examining the effect of scale selection when evaluating a protected area in Mexico using real data. We then develop a Monte Carlo experiment that simulates a conservation intervention. We find that estimates of treatment effects and variable coefficients are only accurate under restrictive circumstances. Under more realistic conditions, we find biased estimates associated with scale choices that are both too large or too small relative to the data generating process or decision unit. In our context, the MAUP may reflect an errors in variables problem, where imprecise measures of the independent variables will bias the coefficient estimates toward zero. This problem may be pronounced at small scales of analysis. Aggregation may reduce this bias for continuous variables, but aggregation exacerbates bias when using a discrete measure of treatment. While we do not find a solution to these issues, even though treatment effects are generally underestimated. We conclude with suggestions on how researchers might navigate their choice of scale and aerial unit when evaluating conservation policies.

Emerging Evidence on the Effectiveness of Tropical Forest Conservation.

The PLOS ONE Collection "Measuring forest conservation effectiveness" brings together a series of studies that evaluate the effectiveness of tropical forest conservation policies and programs with the goal of measuring conservation success and associated co-benefits. This overview piece describes the geographic and methodological scope of these studies, as well as the policy instruments covered in the Collection as of June 2016. Focusing on forest cover change, we systematically compare the conservation effects estimated by the studies and discuss them in the light of previous findings in the literature. Nine studies estimated that annual conservation impacts on forest cover were below one percent, with two exceptions in Mexico and Indonesia. Differences in effect sizes are not only driven by the choice of conservation measures. One key lesson from the studies is the need to move beyond the current scientific focus of estimating average effects of undifferentiated conservation programs. The specific elements of the program design and the implementation context are equally important factors for understanding the effectiveness of conservation programs. Particularly critical will be a better understanding of the causal mechanisms through which conservation programs have impacts. To achieve this understanding we need advances in both theory and methods.

Evaluating heterogeneous conservation effects of forest protection in Indonesia.

Establishing legal protection for forest areas is the most common policy used to limit forest loss. This article evaluates the effectiveness of seven Indonesian forest protected areas introduced between 1999 and 2012. Specifically, we explore how the effectiveness of these parks varies over space. Protected areas have mixed success in preserving forest, and it is important for conservationists to understand where they work and where they do not. Observed differences in the estimated treatment effect of protection may be driven by several factors. Indonesia is particularly diverse, with the landscape, forest and forest threats varying greatly from region to region, and this diversity may drive differences in the effectiveness of protected areas in conserving forest. However, the observed variation may also be spurious and arise from differing degrees of bias in the estimated treatment effect over space. In this paper, we use a difference-in-differences approach comparing treated observations and matched controls to estimate the effect of each protected area. We then distinguish the true variation in protected area effectiveness from spurious variation driven by several sources of estimation bias. Based on our most flexible method that allows the data generating process to vary across space, we find that the national average effect of protection preserves an additional 1.1% of forest cover; however the effect of individual parks range from a decrease of 3.4% to an increase of 5.3% and the effect of most parks differ from the national average. Potential biases may affect estimates in two parks, but results consistently show Sebangau National Park is more effective while two parks are substantially less able to protect forest cover than the national average.

How effective are biodiversity conservation payments in Mexico?

We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled.

A spatially explicit estimate of avoided forest loss.

With the potential expansion of forest conservation programs spurred by climate-change agreements, there is a need to measure the extent to which such programs achieve their intended results. Conventional methods for evaluating conservation impact tend to be biased because they do not compare like areas or account for spatial relations. We assessed the effect of a conservation initiative that combined designation of protected areas with payments for environmental services to conserve over wintering habitat for the monarch butterfly (Danaus plexippus) in Mexico. To do so, we used a spatial-matching estimator that matches covariates among polygons and their neighbors. We measured avoided forest loss (avoided disturbance and deforestation) by comparing forest cover on protected and unprotected lands that were similar in terms of accessibility, governance, and forest type. Whereas conventional estimates of avoided forest loss suggest that conservation initiatives did not protect forest cover, we found evidence that the conservation measures are preserving forest cover. We found that the conservation measures protected between 200 ha and 710 ha (3-16%) of forest that is high-quality habitat for monarch butterflies, but had a smaller effect on total forest cover, preserving between 0 ha and 200 ha (0-2.5%) of forest with canopy cover >70%. We suggest that future estimates of avoided forest loss be analyzed spatially to account for how forest loss occurs across the landscape. Given the forthcoming demand from donors and carbon financiers for estimates of avoided forest loss, we anticipate our methods and results will contribute to future studies that estimate the outcome of conservation efforts.