The impacts of agroforestry on agricultural productivity, ecosystem services, and human well-being in low-and middle-income countries: An evidence and gap map.

Abstract

Agroforestry practices have been widely studied across L&MICs, but rigorous evidence on the effects of interventions designed to promote and support agroforestry on farmers’ land remains limited. Agroforestry, defined as the integration of trees and woody shrubs in crop and livestock production systems, is widely promoted as an effective means to address conservation and development objectives across the world. Governments, donors, and nongovernmental organizations (NGOs) have invested in a range of programs to spur agroforestry adoption, including farmer capacity development, tree germplasm provision, market development, and community advocacy. However, systematic understanding of the impacts of these programs and agroforestry practices more generally remains lacking. What is the aim of this EGM? This Campbell EGM presents the existing evidence for the impacts of agroforestry practices and interventions on agricultural productivity, ecosystem services, and human well-being compared to conventional agricultural or forestry practices. Unlike a systematic review, an EGM identifies what evidence exists, rather than summarizing effect size estimates. This EGM includes studies that evaluate the effects of agroforestry practices and interventions on agricultural productivity, ecosystem services, and human well-being. A total of 20,271 studies were identified. Only 396 of these met the inclusion criteria to be retained for the EGM. Of these studies, 344 examined the effects of agroforestry practices only, 40 examined the effects of agroforestry interventions, and 12 were systematic reviews (SRs). The studies spanned the period from 2000 to mid-2017, with India, Indonesia, China, and Ethiopia the most studied countries. Most of the studies were observational. Only eight studies used rigorous quasi-experimental methods to evaluate the impacts of agroforestry interventions. None of the included studies used experimental designs (random assignment). The eight impact evaluations came from different country contexts, with only Kenya having more than one study. The most studied interventions were incentive provision to motivate farmers to plant and maintain trees on their land, and farmer capacity development. Human well-being, particularly income and household expenditure, was the most studied outcome category for impact evaluations, followed by impacts on agricultural productivity, with minimal evidence for ecosystem services outcomes. Practices relating to the integration of crops and trees (agrisilviculture) comprised more than three quarters of the 344 studies on practices. In contrast to the intervention studies, ecosystem services was the most well-studied practice outcome category, followed by agricultural productivity, with minimal evidence for human well-being outcomes. Of the 12 included SRs focused on agroforestry practices, 11 were rated as high risk of bias, and only one was rated as medium risk of bias. Trees integrated with plantation crops was the most common agroforestry practice discussed in the reviews while ecosystem services was the most studied outcome. No SR examined the effects of agroforestry on human well-being. Our study reveals that rigorous evidence on the effects of agroforestry interventions on farmers’ land remains extremely limited. This finding is especially notable given the large volume of literature documenting the uptake of specific agroforestry practices and widespread promotion of agroforestry as a strategy to advance the 2030 UN Sustainable Development Goals (SDGs). The most urgent need in this field is to address the gap in primary evidence on the impacts of agroforestry interventions and on the impacts of agroforestry on social and economic outcomes. SR of the available studies on intervention impacts would be useful to establish a baseline and provide insights to inform future research, policy, and programming relating to agroforestry. The review authors searched for studies from 2000 to mid-2017. Agroforestry—the integration of trees with other agricultural practices on the same piece of land—is widespread across L&MICs. High-level policy documents in many L&MICs explicitly promote agroforestry and donors have invested billions of dollars in agroforestry interventions. Given its potential to boost food security while delivering other social and environmental objectives, agroforestry is seen as a key means to advance the 2030 UN SDGs. Despite a large body of agroforestry experience in L&MICs, systematic understanding of the social-ecological impacts of agroforestry remains lacking. This report summarizes the findings of an EGM to address this knowledge need. The EGM identifies, maps, and describes available evidence on the effect of agroforestry on agricultural productivity, ecosystem services, and human well-being in L&MICs, in addition to the evidence assessing the relationship between agroforestry practices and such outcomes. We systematically identified and mapped evidence on the effects of agroforestry in L&MICs according to a framework that included four broad practice types and six intervention types together with the three outcome categories of agricultural productivity, ecosystem services, and human well-being. We used a population, intervention, comparator, and outcome (PICO) framework as a basis for inclusion of studies in the EGM. The study population was farms and farming households in L&MICs. “Interventions” in this context included both interventions promoting agroforestry and studies of agroforestry practices applied by farmers in the absence of an external intervention. An alternative intervention or “business as usual” were both eligible comparators. Studies had to measure at least one outcome in the broad categories of agricultural productivity, ecosystem services, or human well-being. The decision to include studies of practices in the absence of interventions was motivated by the key role and prevalence of such studies relative to intervention research. The study design inclusion criteria reflect this choice. We included three types of studies: (a) quantitative impact evaluations, (b) SRs, and (c) observational studies. We excluded field trials that did not take place on farmer-managed land as our focus was on agroforestry effectiveness in “real world” settings. Results for studies assessing interventions and practices were analyzed and presented separately. To identify potential studies for inclusion we followed the search strategy from a published research protocol (Miller, Ordonez, Baylis, Hughes, & Rana, 2017). In October 2017, we searched six databases and 19 organization websites to identify potentially relevant studies published in English from 2000 to June 30, 2017. Search results were uploaded to EPPI Reviewer v4. A team of 14 reviewers were involved in study screening and data extraction. We first screened articles at title and abstract level and then screened the remaining studies at the full text level. A subset of studies (~10%) was double screened at title/abstract level by the lead reviewers. κ tests were used to ensure agreement among reviewers. At the full text level, results were spot-checked and all data extraction checked for accuracy by lead researchers. For each included study, we extracted the following data: bibliometric information, study description, information about the agroforestry intervention/practice, the study design and type, information on the outcome and indicator variables, and descriptions of any mechanism describing pathways between intervention and outcome. Only the included SRs were subject to critical appraisal; however, we recorded information about the study design type (e.g., experimental, quasiexperimental, before-after-control-impact, correlational) as an indicator of potential bias. We conducted quantitative analyses using R to create visual representations of our findings in the form of heatmaps and graphs. Our search returned 20,271 studies, of which 3,080 were removed as duplicates, leaving 16,535 studies that were screened on title and abstract. After title and abstract screening, there remained 1,557 studies which were screened at full text. We identified 12 SRs and 384 primary studies that met our inclusion criteria. Of the primary studies, 40 studies examined the impacts of specific agroforestry interventions, of which only eight used quantitative impact evaluation methods. The other 32 intervention studies measured the outcomes of an agroforestry intervention against a comparator, but they did not use experimental or quasiexperimental methods to account for nonrandom assignment to treatment and control groups. The other 344 primary studies examined the outcomes of agroforestry practices (without a specific intervention associated with the practice) against a nonagroforestry comparator. The eight impact evaluations came from different country contexts, with only Kenya yielding more than one study. Together, they examined four of the six intervention types in the EGM. The most studied interventions were incentive provision to motivate farmers to plant and maintain trees on their land (n = 4) and farmer capacity development (n = 4). Two studies included a component of enhancing access to tree germplasm, and one study included a community-level campaign and advocacy component. Several studies examined interventions with multiple components (e.g., incentive provision and farmer capacity development), so total intervention counts sum to more than the eight studies. We found no impact evaluations of two intervention types: market linkage facilitation and institutional and policy change. Human well-being, particularly income and household expenditure, was the most studied outcome category for impact evaluations, with five studies examining these aspects. Four studies assessed impacts on agricultural productivity, while only two focused on ecosystem services outcomes. Of the 12 included SRs focused on agroforestry practices, 11 were rated as high risk of bias, and only one was rated as medium risk of bias. Trees integrated with plantation crops was the most common agroforestry practice discussed in the reviews while ecosystem services was the most studied outcome. No SR examined the effects of agroforestry on human well-being. The 344 studies of agroforestry practices were relatively evenly spread across the major tropical and subtropical world regions, though some countries were relatively well studied (e.g., India, Indonesia, China, and Ethiopia, which collectively represent 45% of the total studies). There were hardly any studies from L&MICs in Europe and Central Asia and Middle East and North Africa regions. Practices relating to the integration of crops and trees—agrisilviculture—comprised more than three quarters (78%; n = 271) of the 344 studies on practices. In contrast to the intervention studies, ecosystem services was the most well-studied practice outcome category. The vast majority of included primary studies (96%) were correlation only studies that did not use an experimental, quasiexperimental, or other before-after-control-impact study design. All included studies did have a control group using a nonagroforestry practice (e.g., relating to agriculture or forestry) to compare impacts. The research on agroforestry practices has grown steadily, from <10 relevant studies in 2000 to nearly 50 in 2016. However, the volume of evidence on agroforestry interventions remained spotty and flat during the study period. Given our inclusion criteria, we did not include field trials, but our search revealed approximately 1,700 potentially relevant studies reporting on results of field trials or “efficacy studies.” A central finding of this EGM is that the evidence base on the effects of interventions promoting agroforestry on farmers’ land remains very limited. This result contrasts to the availability of hundreds of observational and experimental studies on the effect of agroforestry practices. Part of the reason for this finding is the complexity of many agroforestry systems and the relatively long time horizons required for interventions to generate results. For example, it may take many years beyond the scope of an intervention for trees to mature so that they yield useful products such as fruit, fodder, or timber, challenging efforts to monitor and evaluate intervention impacts beyond adoption of promoted practices. Our study reveals that rigorous evidence on the effects of agroforestry interventions on farmers’ land remains extremely limited. This finding is especially notable given the large volume of literature documenting the uptake of specific agroforestry practices and widespread promotion of agroforestry as a strategy to advance the 2030 UN SDGs. It is also somewhat surprising given the relative prevalence of impact evaluations in the related fields of agriculture and forestry. The complexity of agroforestry poses challenges for impact evaluation. But, given the potential of agroforestry to contribute to a number of the SDGs simultaneously, there is an urgent need to address such challenges and conduct more high-quality studies of the effects of agroforestry interventions on agricultural productivity, ecosystem services, and human wellbeing. The most urgent need in this field is to address the gap in primary evidence. However, SR of some of the available impact studies may be useful to establish a baseline. A review of the evidence on how incentive provision and farmer capacity development interventions affect all three outcome categories would be especially useful. Such synthesis would provide insights to inform future policy and programming relating to agroforestry interventions and also present an important baseline for future research. The integration of trees in agriculture is widespread across the L&MICs of Africa, Asia, and Latin America. Agroforestry practices, ranging from farmer-managed natural regeneration through to the intercropping of trees within annual crop fields and cultivation of forest gardens, are estimated to take place on nearly 50% of agricultural land in developing country regions (Zomer et al., 2014). Defined simply as “agriculture with trees” or more comprehensively as “the practice and science of the interface and interactions between agriculture and forestry, involving farmers, livestock, trees and forests at multiple scales” (World Agroforestry, 2017), agroforestry comprises an increasingly important strategy to increase farmer income and food production while advancing other social and environmental objectives. Proponents argue that agroforestry can provide basic subsistence, natural insurance, and a means to generate income and build assets for many rural households in L&MICs (Garrity et al., 2010; Miller, Muñoz-Mora, & Christiansen, 2017). Agroforestry can also generate environmental benefits, including carbon storage, biodiversity conservation, clean water, erosion control, and soil fertility, while enhancing resilience of agricultural lands in the face of climate-related stresses (FAO, 2013; Garrity et al., 2010; Jose, 2009; Kalaba, Chirwa, Syampungani, & Ajayi, 2010; Mbow, Smith, Skole, Duguma, & Bustamante, 2014). In addition, studies also suggest agroforestry has the potential to increase agricultural productivity (Garrity et al., 2010; Pretty & Bharucha, 2014; Sileshi, Akinnifesi, Ajayi, & Place, 2008; Waldron, Justicia, & Smith, 2015). Given these potential benefits, agroforestry has been widely promoted in L&MICs. It is expected to play a key role in delivering the UN SDGs (United Nations, 2015; Waldron et al., 2017; World Agroforestry, 2017). Government extension agencies, NGOs, and a range of donor agencies have long provided support to agroforestry systems and practices. Since the 1992 UN Earth Summit in Rio, international aid donors have invested more than U.S. $10 billion in agroforestry projects (AidData, 2017; activity code: 31220.07) in L&MICs (Tierney et al., 2011). The largest donor, the World Bank, continues to emphasize agroforestry in its policy documents, including major commitments to ensure its agricultural investments are “climate smart” by 2020 (World Bank 2016). High-level policy documents in many L&MICs now explicitly call for the integration of trees into farming systems (e.g., national policies of Government of India, 2014; Republic of Kenya, 2014; and Government of Malawi, 2011) and there is growing interest in promoting agroforestry as part of sustainable intensification initiatives that reconcile agricultural production with the provision of other important ecosystem services (FAO 2013; Pretty, 2018). A large body of literature on agroforestry in L&MICs has accumulated, but systematic understanding of the effects of agroforestry on social and ecological outcomes within and across diverse contexts is missing. This lack of knowledge, in turn, constrains the ability of policymakers, practitioners, and researchers to make effective decisions relating to agroforestry programming and investments. This EGM provides such an overview. Specifically, the EGM identifies, collects, maps, and describes available high-quality evidence on the effects of interventions promoting agroforestry on agricultural productivity, ecosystem services, and human well-being in the L&MICs of Africa, Asia, and Latin America. It shows areas of high, low, or nonexistent evidence, as well as varying levels of robustness relative to study design. This EGM differs from other EGMs in that we also included and describe the literature on agroforestry practices that may have been put in place without being promoted by any specific intervention. The motivation for this decision was twofold. First, the uptake of agroforestry practices need not rely on external interventions and, second, “adoption studies” have been especially prominent in this field. Farmer capacity development through training, extension, the provision of other advisory services and technical information, demonstration sites, participatory trials, and other modes of action learning. Enhancing access to tree germplasm through the direct provision of tree seedlings/seeds and linking farmers to and/or strengthening the capacity of tree germplasm suppliers. Community-level campaigning and advocacy encouraging large numbers of community members to plant trees on their farms and/or pursue specific agroforestry practices. Incentive provision through direct payments to farmers for planting and caring for trees on their farms and the receipt of premiums for particular agricultural commodities, for example, for shade grown coffee. Market linkage facilitation for a greater and/or more favorable integration of smallholders into tree-product value chains. Policy and institutional change for a more enabling environment that promotes the uptake of agroforestry and/or enables its potential benefits to be better realized. Although there is wide variation in the practices promoted, agroforestry interventions typically encourage farmers to take up several complementary practices to meet multiple social-ecological objectives (Waldron et al., 2017). For example, planting of tree species that will generate productive uses only over the long-term may be promoted at the same time as crops and shrubs that provide benefits in the near term. We present a classification scheme for a range of agroforestry practices in Table 1. Figure 1 presents a simplified and generic theory of change which may underlie an agroforestry intervention (either explicitly or implicitly). The first required step is successful mobilization and engagement of farmers. The second step represents a given intervention, such as farmer capacity development or facilitating access to appropriate tree germplasm. At least the first and, in many cases, both are required for significant and appropriate adoption of the promoted agroforestry practices and/or tree germplasm. Following such adoption, several intermediary outcomes are then expected. For example, farmers may see improved soil health and other ecosystem services, such as water filtration, that then increase crop productivity or reduce production costs and, therefore, increase returns. Some participants in the intervention may find that increased use and availability of tree/shrub fodder leads to increases in milk and other livestock production and returns. Selling other agroforestry products such as timber, firewood, and fruit, is also expected to increase and diversify income and food sources (Mbow, Van Noordwijk, et al., 2014; Sharma et al., 2016; Waldron et al., 2017). These changes may have differential effects depending on gender. Together, these intermediate outcomes are expected to interact together to bolster household resilience to shocks, as well as overall household income food and nutritional security. These positive benefits—and the broader context in which this stylized theory of change is embedded—will then affect further household investment in agroforestry. As described above, agroforestry systems and practices are widespread across L&MICs and have increasingly been seen as a solution for boosting food security, addressing environmental degradation, and contributing to a range of other development policy objectives (Garrity et al., 2010; Waldron et al., 2017). Nevertheless, financing and effective promotion of agroforestry and other nonmainstream agricultural approaches remains limited in many contexts (DeLonge, Miles, & Carlisle, 2016; Horlings & Marsden, 2011; IPES-Food 2016). Instead, high-input, mechanized approaches to agriculture predominate. Over the past half century, these approaches have become conventional, leading to major increases in yields and helping to feed much of the world's population (Iaastd, 2009; Pretty & Bharucha, 2014; The Government Office for Science, 2011). However, these benefits have brought with them sometimes steep social and environmental costs, including biodiversity loss, climate change, land degradation, water pollution, and negative effects on human health (Brawn, 2017; Horrigan, Lawrence, & Walker, 2002; Iaastd 2009; Maxwell, Fuller, Brooks, & Watson, 2016; Pretty & Bharucha, 2014). Farmers, consumers, and policymakers increasingly recognize these costs and seek viable alternatives that can simultaneously address food security concerns while delivering other social and environmental benefits. Agroforestry represents one such potential alternative, but there is an important need to systematically identify what kinds of interventions and practices have worked to deliver these benefits and understand potential trade-offs involved. Evidence on the effectiveness of agroforestry is, therefore, needed to inform broader debates and investment decisions relating to sustainable agricultural intensification. Despite the long history of agroforestry systems and practices, agroforestry as a specific science and specific policy domain emerged only in the 1960s and 1970s. National governments, NGOs, research organizations, and aid agencies alike began to embrace the idea and to develop, test, and support a wide range of agroforestry practices (Nair, 1993). As the field has matured, a substantial literature on the adoption and impacts of agroforestry practices in L&MICs has developed. However, syntheses of evidence of what agroforestry practices have been effective, under what circumstances, and why remains lacking. Recent systematic maps (SMs) and SRs have begun to shed light on the effects of agroforestry practices on specific outcomes, such as agricultural productivity and ecosystem service provision (Reed et al., 2017; Rosenstock et al., 2016; Thorn et al., 2015). Cheng et al. (2019) examine the impacts of forestry and agroforestry interventions on poverty. The recently published SR by Reed et al. (2017) synthesizes existing evidence on the indirect effects that forest- and tree-related ecosystem services have had on food production in the tropics. Two recent EGMs related to forests (Puri, Nath, Bhatia, & Glew, 2016; Snilstveit et al., 2016) include agroforestry, with some attention to existing evidence on effects on environmental and social outcomes in L&MICs. These reviews provided valuable information for this EGM, which is broader in scope geographically and in outcomes considered. As detailed below, this EGM includes all L&MICs, not just tropical ones, and direct and indirect effects of agroforestry interventions on a range of outcomes. We are aware of no EGM, SM, or SR that summarizes empirical studies on the causal effects of agroforestry interventions in L&MICs, particularly outside the context of tightly controlled, research station-based experimental trials. There are two primary audiences for this EGM. First, we expect that researchers on agroforestry and broader sustainability issues will use the results to inform further investigations on these topics, including new empirical research, as well as SRs of specific linkages and further evidence synthesis. Results should be of wide interest to researchers in a range of institutions, from CGIAR centers to universities. The second main anticipated audience is decision-makers for whom agroforestry is already or potentially of interest. This includes relevant ministries and programs in governments and donor agencies, as well as NGO and other advocacy and implementing organization staff. The overall aim of this EGM is to identify, map, and describe existing evidence on the effects of agroforestry interventions on agricultural productivity, ecosystem services and human well-being in L&MICs. The results will inform the scope of a planned SR on this topic. What are the extent and characteristics of empirical evidence on the effects of agroforestry interventions and practices on agricultural productivity, ecosystem services, and human well-being in L&MICs? What are the major gaps in the primary evidence base? What are the agroforestry intervention/practice and outcome areas with potential for evidence synthesis? Our framework follows standard practice for EGMs (Snilstveit, Vojtkova, Bhavsar, & Gaarder, 2013), with rows in a matrix representing interventions and columns outcomes. Below we detail these two dimensions of the matrix as well as describe the PICO component that we examined. To identify the effect of an intervention or practice, a study needs to include both adopters (or program participants) and a comparator. A comparator is defined as a farm or household that does not adopt a given practice identified in Table 1, or is not exposed to a specific agroforestry intervention. Specifically, eligible comparisons included land or households where agroforestry was not practiced or promoted but another land use was in place (e.g., agriculture, primary forest, or secondary forest/forest plantation). For observational studies, a farm or household before agroforestry promotion or adoption of a given agroforestry practice began was also an eligible comparator. The population of interest was farms and those that live and farm on them in L&MICs using a system that falls within the definition of agroforestry. The overall intervention category for our EGM is “agroforestry” defined as “a collective name for land-use systems and technologies where woody perennials (trees, shrubs, palms, bamboos, etc.) are deliberately used on the same land-management units as agricultural crops and/or animals, in some form of spatial arrangement or temporal sequence” (Nair, 1993). In the field of agroforestry, there are multiple strands of literature, including studies of the impacts of specific agroforestry practices and systems and studies of the impacts of specific interventions designed to spur the adoption of agroforestry to yield more distal social-ecological impacts. The “intervention” axis in this EGM therefore includes both categories. To capture the wide diversity of practices that might fall under this definition and present them in a coherent way, we subdivided agroforestry into the practice types listed in Table 1. This set of practice types is based on the classification system proposed by Nair (1985, 1993) and updated by Sinclair (1999), Torquebiau (2000), and Atangana et al. (2014). From a policy perspective, it is especially useful to know what kinds of interventions might most effectively promote agroforestry practices to yield desired social-ecological outcomes. The EGM, therefore, also includes studies that examine specific types of interventions designed to promote agroforestry. The intervention types are summarized in Table 2. We present the main matrices of interventions and practices in two ways: (a) a simplified typology of interventions and practices using the broad agroforestry systems listed in Table 1 and (b) a more detailed version with the specific interventions and practices listed in Table 1. The columns of the EGM matrix comprise three broad outcome categories: (a) agricultural productivity, (b) ecosystem services, and (c) human well-being. Studies that focused exclusively on the adoption of a particular agroforestry technique or species without reference to effects on outcomes were excluded. Specific outcome categories under agricultural productivity comprise factor productivity, including yield, and profitability. Ecosystem services outcomes were first classified under three broad categories: (a) provisioning, (b) regulation and maintenance, and (c) cultural services. Outcomes were then further divided into a number of specific categories following the Common International Classification of Ecosystem Services (CICES) developed by the European Environmental Agency (Haines-Young & Potschin, 2012) and presented in Table 3. CICES builds from the seminal Millennium Ecosystem Assessment (2005), The Economics of Ecosystems and Biodiversity (Kumar, 2012), and other ecosystem services classification schemes. For human well-being