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Agroforestry is often seen as a sustainable land-use system for agricultural production providing ecosystem services. Intercropping with food crops leads to equal or higher productivity than monoculture and results in food production for industry and subsistence. Low rubber price and low labor productivity in smallholdings have led to a dramatic conversion of rubber plantations to more profitable crops. The literature analysis performed in this paper aimed at better understanding the ins and outs that could make rubber-based agroforestry more attractive for farmers. A comprehensive search of references was conducted in March 2023 using several international databases and search engines. A Zotero library was set up consisting of 415 scientific references. Each reference was carefully read and tagged in several categories: cropping system, country, main tree species, intercrop type, intercrop product, level of product use, discipline of the study, research topic, and intercrop species. Of the 232 journal articles, 141 studies were carried out on rubber agroforestry. Since 2011, the number of studies per year has increased. Studies on rubber-based agroforestry systems are performed in most rubber-producing countries, in particular in Indonesia, Thailand, China, and Brazil. These studies focus more or less equally on perennials (forest species and fruit trees), annual intercrops, and mixed plantations. Of the 47 annual crops associated with rubber in the literature, 20 studies dealt with rice, maize, banana, and cassava. Agronomy is the main discipline in the literature followed by socio-economy and then ecology. Only four papers are devoted to plant physiology and breeding. The Discussion Section has attempted to analyze the evolution of rubber agroforestry research, progress in the selection of food crop varieties adapted to agroforestry systems, and to draw some recommendations for rubber-based agroforestry systems associated with food crops.

The determination of changes in soil organic carbon (SOC) content under different cropping systems is necessary for policy development oriented towards soil conservation, C sequestration, and future C credit markets. The aim of this study was to generate an open SOC dataset resulting from a systematic literature search related to the agricultural systems for Southeast Asia. The dataset has 209 articles and 4341 observations on soils of cropping systems in this region from articles published between 1987 and 2023. This dataset included different management practices, land uses, soil sampling depth, and length of SOC content assessment. In addition, inherent features of crop production reported in the experiments were included in the dataset. This dataset can be applied to quantify and compare the impact of different land uses or management practices on SOC content, providing foundational knowledge towards identifying sustainable practices. Lastly, it is a useful guide for future regional SOC sequestration policies and the development of C credit markets.

Annual global coffee consumption growth (1–2%) has been largely met (>50%) mainly by Brazil and Vietnam through high-input monocrop system adoption. Smallholders account for >80% of global producers and >60% of global supply despite limited farm sizes (<2 ha), yields, and input usage. Production concentration in areas with high-yielding systems has fulfilled global demand growth while keeping coffee prices low. However, climate shocks demonstrate the vulnerability of all supply models, strengthening the voice of those advocating more resilient and diversified systems. We review current agroforestry knowledge to identify key trade-offs and synergies between sustainability/performance indicators (i.e. economic, environmental, and social) and explore pathways for a more sustainable coffee future with three examples representative of global coffee production system diversity.

This paper introduces a dataset of aerial imagery captured during the 2022 cocoa growing season in the central-western region of Côte d'Ivoire. The images were acquired using a multispectral camera mounted on a DJI Phantom 4 unmanned aerial vehicle (UAV). The agricultural land surveyed encompasses 10 different types of cocoa-based agroforestry systems, each ranging from 2.6ha to 8.3ha, totaling 7638 images and covering 30ha. The UAV mission was conducted at an altitude of 80 meters, with a side overlap of 70% and a front overlap of 80%. This configuration achieved ground sampling distances (GSD) ranging from 4.2 to 4.6 cm providing high-resolution detailed imagery of those lands. These high-resolution RGB and multispectral images can be used to characterize the structural complexity of the systems as well as the abundance, and the health of the trees in these cocoa-based systems. It can be a valuable resource for researchers in the fields of ecology, agriculture, and environmental monitoring. The dataset supports a wide range of applications, from precision agriculture to sustainable cocoa land use management, making it a pivotal tool for enhancing agricultural practices and ecosystem management in Ivorian regions facing environmental and economic challenges.

Enhancing food security in the Sahel through nature-based solutions is urgent given population growth, resource scarcity and climate change. Traditional agroforestry parklands are a farmer- and nature-based widespread form of ecological intensification which randomly integrates trees into crop fields. While most studies estimating crop yields in agroforestry have been conducted in controlled experimental settings, few have addressed the inherent variability in such highly heterogeneous systems. Thus, the purpose of this study is to benefit from a UAV-based proxy-sensing and machine learning approach to address the variability of pearl millet grain yield, according to the distance to randomly distributed trees in a traditional agroforestry system dominated by Faidherbia albida (i.e. groundnut basin of Senegal). 21 vegetation indices (VIs), 32 normalized difference texture indices (NDTIs) derived from multispectral drone images, and normalization variables for radiative conditions were used with yield data collected in 15 plots (around 1 ha each) and subplots (15 m 2 each) displayed at 3 distances from the tree over five cropping seasons (2018 - 2022). In this context, the optimal phenological stage was determined for predicting pearl millet grain yield, which proved to be the pre-heading period. This period was used as the basis for our machine learning model training dataset in the subplots. Two models, Random Forest (RF) and Gradient Boosting Machine (GBM) were compared by combining VIs, NDTIs and normalization variables. GBM was the best-performing model, explaining 78% of observed pearl millet yield variability over five years in the subplots, with a RMSE of 16 g. m −2 . This study revealed that NDTIs calculated from red and green bands were more influential for yield estimation than those based on near-infrared. These results were subsequently used to predict yield in all plots, resulting in a mean relative error of 17.5% between yields estimated by the farmers

Salinity is a major problem, impeding soil productivity, agricultural sustainability, and food security, particularly in dry regions. This study integrates quinoa, a facultative halophyte, into a pomegranate-based agroforestry with saline irrigation in northeast Morocco. We aim to explore this agroforestry model's potential in mitigating salinity's effects on quinoa's agronomic and biochemical traits and evaluate the land equivalent ratio (LER). Field experiments in 2020 and 2021 used a randomized block design with three replicates, including monocropping and agroforestry systems, two salinity levels (1.12 and 10.5 dS m−1), four quinoa genotypes (Titicaca, Puno, ICBA-Q4, ICBA-Q5), and a pomegranate control. Salinity significantly decreased total dry matter (40.5%), root dry matter (50.7%), leaf dry matter (39.2%), and root-to-shoot ratio (7.7%). The impact was more severe in monoculture than in agroforestry, reducing dry matter (47.6% vs. 30.7%), grain yield (46.3% vs. 26.1%), water productivity (47.5% vs. 23.9%), and total sugar (19.2% vs. 5.6%). LER averaged 1.86 to 2.21, indicating 86–121% higher productivity in agroforestry. LER averaged 1.85 at 1.12 dS m−1 and 2.18 at 10.5 dS m−1, reaching 2.21 with pomegranate-ICBA-Q5 combination. Quinoa–pomegranate agroforestry emerges as an innovative strategy, leveraging quinoa's salt resistance and agroforestry's potential to mitigate salinity impacts while enhancing land use efficiency.

Background: Soil animal communities include more than 40 higher-order taxa, representing over 23% of all described species. These animals have a wide range of feeding sources and contribute to several important soil functions and ecosystem services. Although many studies have assessed macroinvertebrate communities in Brazil, few of them have been published in journals and even fewer have made the data openly available for consultation and further use. As part of ongoing efforts to synthesise the global soil macrofauna communities and to increase the amount of openly-accessible data in GBIF and other repositories related to soil biodiversity, the present paper provides links to 29 soil macroinvertebrate datasets covering 42 soil fauna taxa, collected in various land-use systems in Brazil. A total of 83,085 georeferenced occurrences of these taxa are presented, based on quantitative estimates performed using a standardised sampling method commonly adopted worldwide to collect soil macrofauna populations, i.e. the TSBF (Tropical Soil Biology and Fertility Programme) protocol. This consists of digging soil monoliths of 25 x 25 cm area, with handsorting of the macroinvertebrates visible to the naked eye from the surface litter and from within the soil, typically in the upper 0-20 cm layer (but sometimes shallower, i.e. top 0-10 cm or deeper to 0-40 cm, depending on the site). The land-use systems included anthropogenic sites managed with agricultural systems (e.g. pastures, annual and perennial crops, agroforestry), as well as planted forests and native vegetation located mostly in the southern Brazilian State of Paraná (96 sites), with a few additional sites in the neighbouring states of São Paulo (21 sites) and Santa Catarina (five sites). Important metadata on soil properties, particularly soil chemical parameters (mainly pH, C, P, Ca, K, Mg, Al contents, exchangeable acidity, Cation Exchange Capacity, Base Saturation and, infrequently, total N), particle size distrib

Agroecology is highly promoted in research and development discourse as a holistic and effective response to climate change. The objective of this study is to contribute to the analysis of the existing evidence that agroecology enables climate change (CC) adaptation and mitigation in the agricultural systems of Latin America, a region known for pioneering the development of this science, praxis, and movement. We applied the PRISMA method to analyze the existing literature providing such evidence. Stakeholder interviews were used to obtain in-depth perceptions of agroecology's contributions to CC adaptation and mitigation from a wide range of actors and development practitioners based in Colombia, Ecuador, and Peru: farmers, NGO representatives, researchers, university program leaders, and public officials. From a total of 1821 initially identified articles, 62 were screened, and 24 case studies analyzed for methods and evidence provided. Twenty-six stakeholders were interviewed. Combining quantitative and qualitative assessment methods, the scientific literature shows that agroecological systems are appreciated for addressing resilience in a systemic way hence not just climate change per se. Mitigation was generally assess by quantitative approaches. Integrating stakeholders' discourse to our analysis highlighted their knowledge of underlying processes contributing to farm CC resilience, where crop and animal diversification and integration of trees into farming systems are central. Stakeholders attributed agroforestry and less use of synthetic fertilizers as important roles for mitigation. Our study highlights the pertinence of combining systematic analyses of the evidence and perceptions drawn from a plurality of stakeholders to recognize the positive contribution of agroecology to climate change adaptation and resilience. However, it also pointed to future research that further assesses the specific trade-offs and synergies between agroecological practices, mitig

Though facing significant challenges, coffee (Coffea arabica) grown in Haitian agroforestry systems are important contributors to rural livelihoods and provide several ecosystem services. However, little is known about their genetic diversity and the variety mixtures used. In light of this, there is a need to characterize Haitian coffee diversity to help inform revitalization of this sector. We sampled 28 diverse farms in historically important coffee growing regions of northern and southern Haiti. We performed KASP-genotyping of SNP markers and HiPlex multiplex amplicon sequencing for haplotype calling on our samples, as well as several Ethiopian and commercial accessions from international collections. This allowed us to assign Haitian samples to varietal groups. Our analyses revealed considerable genetic diversity in Haitian farms, higher in fact than many farmers realized. Notably, genetic structure analyses revealed the presence of clusters related to Typica, Bourbon, and Catimor groups, another group that was not represented in our reference accession panel, and several admixed individuals. Across the study areas, we found both mixed-variety farms and monovarietal farms with the historical and traditional Typica variety. This study is, to our knowledge, the first to genetically characterize Haitian C. arabica variety mixtures, and report the limited cultivation of C. canephora (Robusta coffee) in the study area. Our results show that some coffee farms are repositories of historical, widely-abandoned varieties while others are generators of new diversity through genetic mixing.

"Why do many farmers still resist adopting and scaling agroforestry? Are the economic benefits not enough, or not perceived to be enough? Or are there other reasons? These are the questions that were asked when work began on Tropical Forest Issues 62. This issue contextualizes agroforestry in four introductory articles in terms of economic viability and resilience, gender inclusiveness, interactions with climate change and biodiversity and barriers to adoption. We then present 26 case studies from Africa, Asia, and Latin America that show the clear and tangible benefits from the adoption of agroforestry. These 26 examples of agroforestry at work, from a range of developing countries, all show that agroforestry provides direct and indirect benefits to farming families and the wider economy. The well-documented case studies show that agroforestry “works” — it contributes to improved livelihoods (including direct cash income), subsistence activities, employment and other community benefits. In highlighting the reasons for its success in a range of contexts, we hope to demonstrate that agroforestry can spread, encouraging other farmers to develop and expand more diversified, productive and resilient farming systems. Depending on the local context and individual traditions and perceptions, different farmers will have a preference for different agroforestry practices. This shows the importance of developing locally owned agroforestry production systems in order to achieve the full range of benefits. The articles in this issue describe a wide range of agroforestry practices from an array of environments and socioeconomic conditions.

Agroforestry is a promising way to sustain land use efficiency in semi-arid areas. In this study, we introduce quinoa as a drought- and salinity-tolerant crop in olive-based agroforestry. We investigated how the microclimate created by olive trees affects agronomic and biochemical traits in quinoa and evaluated the performance of this new olive-based agroforestry system in terms of land equivalent ratio (LER). Field experiments were carried out under two pedoclimatic conditions (S1) and (S2) using a randomized complete block design with two cropping systems (sole crop (SCS) and agroforestry (AFS) systems), four quinoa cultivars (Puno, Titicaca, ICBA-Q5, and ICBA-Q4) and one olive orchard as a control (OR) in each block. Our results show that AFS had lower grain yield (−45%), dry biomass (−49%), and crop water productivity (−44%), but higher plant height (12%), grain protein (4%), saponin (26%), total polyphenol (12%), and DPPH (9%) contents compared to SCS. The highest grain yield was recorded for Titicaca and ICBA-Q5 (1.6 t ha−1). The LER ranged from 1.57 to 2.07, indicating that the overall productivity was 57% to 107% higher in the agroforestry system compared with the monoculture. We suggest that quinoa–olive tree intercropping could be a promising agroecological practice under semi-arid conditions.

Many countries have integrated agroforestry into their sustainable development policies, particularly in Southeast Asia. In Timor-Leste, the national strategy to promote agroforestry has adopted a modern, technique-oriented approach focused on crop rotation, intercropping and agro-silvo-pasture. In so doing, it has largely overlooked the pre-existence, diversity and performance of traditional agroforestry systems (AFS). The data collected in seven villages located in four districts of the eastern municipalities of Timor-Leste identified five common AFS: home garden, crop field and fallow, young agroforest, forest garden and silvopastoralism. The combined use of the customary AFS by rural households depends on the households' ability to access the four types of capital (land, financial, labour and social) underpinning their development strategies. Four rural household archetypes were therefore distinguished. Six farming strategies used by these archetypes were identified: cattle specialisation, palm and tree product harvesting, crop intensification, diversification of off-farm and on-farm income, abandonment of farming, and survival. Each of these farming strategies combine certain customary AFS. The diversity and complexity of AFS require a better description of how they function and a better understanding of how they fit into the heterogeneous development strategies of rural households before actions are considered to improve their performance.

Shade trees in agroforestry systems confer ecosystem services, such as enhanced soil fertility from diverse litter inputs, microclimate regulation via shade, and disease mitigation through trophic and abiotic interactions. With this thriving role of agroforestry in sustainable agriculture, particularly for tree crops, systematic and reliable methods to select shade trees for specific agroecosystem outcomes are crucial. Plant functional traits offer a framework to describe, select and manage shade trees. Over the last decade, shade tree leaf functional traits and whole plant traits have been assessed in agroforestry systems. Yet, we lack amalgamated information on (i) what we know about shade tree trait relationships with functions to achieve desired agroecosystem outcomes, (ii) how decades of shade tree selection by farmers impacts agroforests inter- and intraspecific trait diversity, and (iii) which shade tree traits should be considered for achieving farmer priorities. We consolidate literature on Coffea arabica (coffee) and Theobroma cacao (cocoa) agroforestry systems to summarize the role of shade tree functional traits in three key ecosystem functions: soil fertility, microclimate modification and crop productivity. We compile global and regional datasets on tree functional trait diversity to show the functional space of agroforestry tree species compared with the overall functional space observed in plants. Despite, or maybe because of, high shade tree diversity, shade tree trait characterization remains coarse and commonly measured at the community scale in the literature. Based on published trait data, we show that farmers adjust the functional composition of shade trees to increase the recycling of soil nutrients (high leaf nitrogen), the production of wood (skewing towards lower wood densities) and the production of fruits (tendency towards high seed size). Common shade trees in coffee and cocoa systems fall in the mid-range of leaf acquisitive to conserva

Coffee beans are a major agricultural product and coffee is one of the most widely traded commodities and consumed beverages globally. Supply chains and cropping systems are very diverse, with contrasted potentials and performance, as well as environmental impacts. Life Cycle Assessment (LCA) studies are needed to inform on reduction in impacts, but there is a lack of comprehensive understanding of the variability of existing LCA results and impacts of the cropping systems and their trade-offs along the supply chains. In an attempt to address this knowledge gap, the paper presents a systematic literature review of coffee LCA, considering a total of 34 studies covering 234 coffee systems. Global warming potential (GWP) was the impact category most reported in the literature, but the results varied greatly at both the farm and drink levels. For the former, the GWP values ranged from 0.15 to 14.5 (median: 3.6) kg CO2 eq./kg green coffee beans and for the latter the values ranged from 2 to 23 (median: 8.8) kg CO2 eq./kg consumed coffee in drinks. Main contributors to the GWP of production of green coffee beans were land use change (LUC), fertilisers and wet processing. However, there were great inconsistencies across studies in terms of LUC accounting, field emissions and wet process modelling. Green coffee beans production was also the main contributor to the GWP of coffee consumed, followed by brewing and coffee cup washing. Some studies covered other impacts, in addition to GWP. At both the farm and drink levels, fertilisers and pesticides were the main contributors to eutrophication and acidification, and to ecotoxicity, respectively. Brewing was the second main contributor at the drink level, in some cases the top contributor for energy-related indicators. Assumptions on packaging, cup washing and waste disposal were highly variable across studies. Water impact indicators were hardly comparable due to the system variability and method inconsistencies. Given the lar

In recent decades, remote sensing has been shown to be useful for crop cover monitoring over smallholder agricultural landscapes, such as agroforestry parklands. However, the fraction of green vegetation cover (FCover) has received little attention. Indeed, the collection of FCover ground data representative of the within-field heterogeneity is time-consuming. Thus, this article aims to bridge this gap by proposing an original methodological framework combining FCover data derived from unmanned aerial vehicle (UAV) and Sentinel-2 (S2) images for estimating millet FCover at the landscape scale in an agroforestry parkland of the groundnut basin of Senegal during the 2021 and 2022 cropping seasons. UAV-based FCover was computed over a 3 m × 3 m grid using a thresholding approach for six dates over the cropping seasons and then used as ground observation for the upscaling of millet FCover at the landscape scale with S2 data. Various spectral vegetation indices and textural features were derived from S2, and several modeling approaches based on machine learning algorithms were benchmarked. Our results showed that the modeling approach using the full-time series in combination with a random forest algorithm was able to explain 73% (root mean square error = 12.13%) of the UAV-FCover variability after validation in 2021 and 2022. In addition, UAV images are suitable for consistent monitoring of millet FCover over heterogeneous agricultural landscapes by training S2 satellite images. To further check its robustness, this approach should be tested for different crops and practices across a variety of agricultural landscapes in sub-Saharan Africa.

Afforestation of degraded areas was suggested as CO2 sink, contributing to climate change mitigation. Yet, few studies have assessed this sink by combining measurements on carbon (C) in the biomass and the soil, despite it being crucial to properly estimate the mitigation potential. Here, we assessed the combined C stocks of afforestation plots of different ages on former cropland in a Cambisol landscape in Extremadura, Spain. The plots were afforested with two native tree species (Quercus ilex L. and Quercus suber L. in a density ratio of 3:1), planted at several occasions between 1998 and 2011. Stocks of afforested areas in 2022 were compared to non-afforested negative controls on arable land, to a closeby olive grove and a forest with signs of degradation. Tree biomass was estimated from allometric equations, soil organic carbon (SOC) stocks were measured to 30 cm depth, based on equivalent soil mass. The biomass C accumulation rate in afforested plots increased with tree density and elevation (p < 0.05; range: 25 to 75 g C m−2 yr−1). SOC stocks, in contrast, were not significantly different in afforested and non-afforested plots at any depth and in tendency even lower in afforested plots younger than 20 years. Consequently, total (biomass plus soil) C stocks in afforested plots were not significantly higher than in non-afforested ones. Nevertheless, SOC stocks and contents between the tree rows were significantly lower compared to soil next to the trees in the olive grove (about 1200 vs. 2200 g C m−2 in the top 30 cm) and in tendency in the afforested plots (about 1200 vs. 1500 g C m−2 in the top 30 cm; p < 0.1). The fact that the degraded forest (about 6800 g C m−2) and the olive grove (about 5300 g C m−2) did have significantly higher total C stocks than the afforested and non-afforested sites (about 2300 and 1800 g C m−2) could indicate that afforestation could soon become a C sink. However, our study clearly shows that afforestation is not automatically a C

Due to the lack of studies about the sociocultural dimension of ecosystem services, we analyze in this work the perception of these benefits by family farmers who have agroforestry systems in the northeast of Pará, in the Amazon region. With this objective, we categorize forest restoration strategies based on primary data collection - interviews, semi structured questionnaire, illustrated questionnaire and Likert Scale. Through the relative perception based on the application of Likert scales, we observed that the farmers recognize the benefits provided by agroforest systems and natural landscapes, with high perception of ecosystem services in all the categories present in the Millennium ecosystem evaluation. Furthermore, the higher perceptions of ecosystem services are related to the group of farmers with a smaller area of forest reserve and bigger area of agroforest systems. The result suggests that loss of forest area, at the individual level, probably drives to a higher sense of the benefits of natural systems and thus, the increment in agroforestry systems constitutes an attempt to return to functions and benefits lost through environmental degradation over time. In general, support programs are necessary to strengthen the capacity of agroforestry systems to provide ecosystem services and increase biodiversity conservation.

In agricultural value chains, in particular cocoa, environmental, and social standards are becoming increasingly important in meeting sustainability challenges. The main aim of this article is to examine the role of certification primarily on the yields and incomes of cocoa farmers in the Central Cameroon region. From June to July 2017, a survey of certified and non-certified cocoa producers was conducted in the districts of Ngoumou and Mbangassina. At the end of the survey, a total sample of 114 certified and non-certified producers was obtained. Using the cost-benefit analysis, in this preliminary phase of the certification process, the results show that there is no significant difference in costs between certified and non-certified producers for each of the districts. There is also no price difference between certified and non-certified cocoa and the payment of the certification premium is not systematically distributed. However, the profit analysis shows on average significantly higher yields and profits for certified producers. Nevertheless, this increase in profits would mainly be due to the implementation of good agricultural practices rather than the certification itself. Additionally, the exploration of on farm income shows that cocoa-based households remain on average below the poverty line. One of the long-term challenges for the cocoa sector in Cameroon is to combine the government's objective of increasing production with that of improving quality. To this end, the advantages of the predominantly agroforestry systems present in Cameroon should be exploited to produce a critical mass of quality and sustainable cocoa that would allow a significant increase in producer prices.

Agroforestry systems can potentially increase tree diversity within agricultural landscapes, but to date, there is little understanding of the patterns of shade plant diversity within different agroforestry systems (AFS) at large spatial scales. Using compiled plant inventory data (from 23 sources, 2517 plots, and 148,255 individuals) encompassing four AFS (shaded coffee; shaded cocoa; dispersed trees on pastures; and live fences) across six countries in Central America we estimated different metrics of diversity to assess the conservation value of different AFS for shade plants. 458 shade plant species were recorded across the four agroforestry systems. Primary forest species accounted for 28% of the shade species recorded, but only 6% of the recorded individuals. No single AFS was consistently the most diverse across countries when considering rarefied species richness. Trees on pastures can potentially reach a similar species richness as cocoa and coffee systems but require sampled areas 7–30 times larger. In terms of composition, 29 species were shared across the agroforestry systems in different countries, illustrating the strong selection pressure of farmers for species that provide timber, firewood, and fruit. Our study highlights the potential contribution and limitations of different AFS for tree diversity conservation within agricultural landscapes.

Natural rubber is considered a strategic material for the development of Sri Lanka by the Ministry for Plantations. In response to climate change, the country has adopted a policy focusing on resilience and sustainable development. It is in this context that Ksapa initiated the RIVER project in 2022, aiming to develop a program to strengthen agricultural capacity in Sri Lanka. To carry out this project, the company commissioned YAPI Expertise to provide agroforestry intercropping models based on rubber trees with good agronomic performance and economically of interest to producers to diversify their sources of income. The RIVER project is implemented in two districts in south-eastern Sri Lanka: Moneragala and Ampara. This study began with an analysis of the literature in order to select crops that could be intercropped with rubber. In parallel, 80 interviews, prepared by YAPI Expertise, were conducted in the field by a local organisation, LOAM. The aim of these interviews was to identify rubber intercrop models already implemented in the study areas and to understand the reasons why farmers adopted these models. The interviews were analysed statistically by MCA and Chi². By combining these with the literature review, the study established 5 models (Pineapple model, Cocoa model, Banana model, Passion fruit model, Soursop model) for several intercrops that could be planted with rubber, with potential for adoption by local farmers. Finally, selection criteria were established for each model. Both their strong and weak points are presented, since an effective model cannot rely on agronomic analysis alone and it will be essential to adapt the choice of crops to the local market and to farmers' needs.

En Côte d'Ivoire, l'agroforesterie devient une notion incontournable après une déforestation massive pour les cultures de plantation. Depuis les années 2010, le terme se généralise dans le vocabulaire politique, les normes internationales de durabilité et la communication des entreprises chocolatières. Cette note examine comment l'agroforesterie s'est imposée dans l'agenda politique ivoirien. Adoptant une approche compréhensive et à partir d'une soixantaine d'entretiens et des documents politiques, elle analyse la manière dont la notion d'agroforesterie est mobilisée en Côte d'Ivoire, les instruments de sa promotion et les controverses qu'elle suscite. D'abord, ce travail montre que la mise à l'agenda de l'agroforesterie en Côte d'Ivoire se fait suivant des canaux pluriels. Différents instruments de promotion de l'agroforesterie se côtoient, tels que les normes de certification privée, la norme africaine régionale de durabilité pour le cacao, les paiements pour services environnementaux ou encore un dispositif national dit " Agro-Forêt ", issu du nouveau Code forestier. Ensuite, malgré le consensus sur la promotion de l'agroforesterie, sa définition large permet à des acteurs aux intérêts divergents de s'approprier le concept. Ce travail met par ailleurs en évidence la pluralité des objectifs et des perspectives que recouvre la notion en Côte d'Ivoire. Il identifie ainsi des controverses concernant les critères du système agroforestier, sa finalité, la place des agriculteurs, l'échelle d'analyse et la temporalité à considérer. En définitive, cette note contribue à expliciter les traductions politiques plurielles d'une notion issue des sciences. Les liens complexes entre les recherches biophysiques et la pratique politique soulignent l'importance de prendre en compte cette interface pour une meilleure conception de l'agroforesterie et une transition efficace.

L'émergence de l'agroforesterie en Côte d'Ivoire est devenue une priorité nationale. Le secteur agricole du pays génère 70 % des recettes d'exportation, emploie les deux tiers de la population active et contribue à un tiers du PIB. Cependant, ces performances économiques remarquables reposent sur une agriculture de rente qui se développe au détriment des forêts naturelles, entraînant l'un des taux de déforestation les plus alarmants au monde. Pour faire face à cette situation, l'État ivoirien promeut l'agroforesterie comme solution, en particulier dans le secteur du cacao. Cependant, une analyse fine de l'origine des arbres présents dans les champs suggère que l'agroforesterie en Côte d'Ivoire peut être divisée en deux catégories : l'agroforesterie de reforestation, qui permet de reconstituer le couvert forestier en associant progressivement des arbres aux cacaoyers, et l'agroforesterie de déforestation, qui dégrade et appauvrit la couverture forestière en convertissant les forêts naturelles en systèmes agroforestiers. Il est crucial de distinguer ces deux formes d'agroforesterie afin de développer des politiques qui encouragent la reforestation plutôt que la déforestation. Il est également nécessaire de mettre en place des indicateurs dynamiques qui permettent d'évaluer les trajectoires agroforestières des champs dans le temps et, ainsi, de favoriser un engagement à long terme des agriculteurs dans l'augmentation de la couverture forestière.

Duru et al. (Agron Sustain Dev 35:1259-1281, 2015) highlighted a missing tool for studying and improving the performance of cropping systems in the transition to highly diversified agriculture. In response, this paper proposes a concept for designing, modeling, monitoring, and auditing desired ecosystem services, in intercropping and agroforestry systems. We have labelled this concept ESSU (Ecosystem Services functional Spatial Unit). It delimits the smallest spatial unit encompassing all the interacting species and other functional components (e.g., crops, trees, livestock, spontaneous vegetation, semi-natural habitats such as hedges, ditches, forest patches, and animals) that together provide a specified set of ecosystem services. The novel ESSU concept allows representation of an entire diversified agroecosystem by the repetition of the spatial unit that provides the same sets of targeted ecosystem services as the agroecosystem it represents. It can then be used for various activities, such as the (i) design of more efficient agroecological systems according to the targeted ecosystem services; (ii) rapid audit of farming practices for biodiversity/resilience across large tracts of farmland as part of achieving Sustainable Development Goal 2 targets of sustainable food systems; and (iii) modeling such diversified agroecosystems using a motif adapted to represent the targeted ecosystem services and the species spacing design. We demonstrate that the ESSU concept is highly flexible and applicable to a wide range of diversified agroecosystems, like arable intercropping, crop-tree intercropping, tree-tree agroforestry, and agro-pastoralism. We also show its relevance and suitability for representing temporal changes over 1 year, across several years, and over decades, indicating its generalizability and flexibility. We argue that ESSU could open new theoretical and practical research avenues for the study of diversified agroecosystems. Considered with all the knowledg

Background: Worldwide coffee production, especially Arabica coffee, is threatened by climatic change, plants diseases and vulnerability of smallholders. Meanwhile, consumers' demand for socially and environmentally sustainable products is steadily increasing, driving the engagement of stakeholders in agro-ecological and social initiatives. Here we present a new organizational model, the “Coffee agroforestry business-driven cluster” (CaFC), which aims at preserving ecosystems while offering producers a fair income. Based on an original local micro value-chain dedicated to sustainable production of high-quality Arabica coffee under agroforestry systems, the CaFC model stands out by addressing the issues around plantation renovation, a crucial process that requires considerable investments from producers. Methods: Based on a pilot project in Nicaragua, we illustrate how the operational principles of CaFC can be applied in a real setting. Using data shared by key stakeholders involved in the project, we assess the profitability of the CaFC model by comparing different scenarios and applying sensitivity analysis. We then reflect on the reproducibility of the model in other contexts, building on lessons learned from ongoing implementations in Vietnam and Cameroon. Results: For producers renovating their plantations, the CaFC model consistently outperforms other scenarios, offering high quality premiums coupled with capacity building, access to highly productive varieties that perform well under agroforestry systems and adapted credit with favourable repayment schemes. Implementation in Vietnam and Cameroon show that the model can be successfully replicated with some adaptation to local contexts. These cases also highlight the importance of mutual interests, trust and communication in enabling collaboration between stakeholders. Conclusions: The CaFC model has great potential for positive environmental and economic impact and offers strong incentives for stakeholders invol

Research has demonstrated that intraspecific functional trait variation underpins plant responses to environmental variability. However, few studies have evaluated how trait variation shifts in response to plant pathogens, even though pathogens are a major driver of plant demography and diversity, and despite evidence of plants expressing distinct strategies in response to pathogen pressures. Understanding trait-pathogen relationships can provide a more realistic understanding of global patterns of functional trait variation. We examined leaf intraspecific trait variability (ITV) in response to foliar disease severity, using Coffea arabica cv. Caturra as a model species. We quantified coffee leaf rust (CLR) severity—a fungal disease prominent in coffee systems—and measured key coffee leaf functional traits under contrasting, but widespread, management conditions in an agroforestry system. We found that coffee plants express significant ITV, which is largely related to shade tree treatment and leaf position within coffee canopy strata. Yet within a single plant canopy stratum, CLR severity increased with increasing resource conserving trait values. However, coffee leaves with visible signs of disease expressed overall greater resource acquiring trait values, as compared to plants without visible signs of disease. We provide among the first evidence that leaf traits are correlated with foliar disease severity in coffee, and that functional trait relationships and syndromes shift in response to increased disease prevalence in this plant-pathogen system. In doing so, we address a vital gap in our understanding of global patterns of functional trait variation and highlight the need to further explore the potential role of pathogens within established global trait relationships and spectra.

Until recently, little or no use was made of fiscal instruments for forest protection in developing countries. The rise of independent third-party certification systems since the 1990s opens new perspectives for using taxation as an incentive. In the forestry sector, certification has developed significantly in Central Africa but reached a plateau in the last ten years, apparently due to the reorientation of timber export flows towards Asian markets that do not demand certified products. Fiscal incentives, through tax cuts for responsible producers, could compensate for the absence of price premiums but would diminish public revenues. The principle of the "bonus-malus" (feebates) seems promising to the extent that it does not reduce government budgetary revenues (budget neutrality). Bonus-malus schemes can also promote certified "zero deforestation" or "grown in agroforestry" agricultural production, especially cocoa, a significant driver of deforestation in Africa. Governments can select one or several certification schemes, private or public ones, and target fiscal incentives related to these certified products. The peculiarity of a bonus-malus system is that the revenues generated by the malus are expected to decrease progressively (with the adoption of certification), requiring a reduction of the bonus rates in order to respect budget neutrality. Adopting such a scheme would create winners and losers, therefore, complementary policy measures targeting small-scale producers are desirable.

The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = −6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies.

Heat and drought stresses have become more frequent and intense in the Mediterranean, strongly influencing arable crop phenology, growth, and grain yield. Agroforestry systems can effectively buffer the adverse climate conditions and stabilize or even increase crop yield under climate change. However, the positive effects of agroforestry remain uncertain due to the possible intense competition between trees and crops, especially for legume crops that have been less studied than cereals in such context. This study aimed to assess the response of the phenology, growth, grain yield, and yield-related traits of chickpea (Cicer arietinum), faba bean (Vicia faba), and lentil (Lens culinaris) to olive-based agroforestry (AFS) as compared to sole crops system (SCS) in the South of the Mediterranean. We conducted a field experiment during two growing seasons marked by an intense drought, either at the beginning (year 1) or at the end (year 2) of the crop cycle. Crop growth and yield were lower in year 1 than in year 2, reflecting the adverse growing conditions caused by the early drought. They were also lower in AFS than in SCS for both years, indicating that trees had competitive effects on crops. In year 1, the yield loss of grains in AFS was 66 % for lentil, 47 % for chickpea, and 43 % for faba bean compared to SCS, confirming the greater shade sensitivity of lentil. In year 2, the reduction was significantly smaller and was about 46 %, 34 %, 38 % for lentil, chickpea and, faba bean, respectively. The number of pods and grains were the most affected yield components by agroforestry and drought timing across the three legumes crops. Similar responses were found when comparing crops at different distances to trees within the AFS field. Crops generally had lower biomass and yield, explained by fewer pods and grains, on the northern side of trees compared to the southern side of trees or the middle of tree inter-rows, causing significant spatial heterogeneity in crops. Howeve

This study investigates spatial-temporal trends in N2O emissions from coffee production systems in Costa Rica with a focus on the effects of nitrogen fertilisation, topography and soil type. This is done by combining (i) multi-year continuous dynamic chamber measurements from sites with different fertilisation levels, (ii) static chamber measurements taken along a typical sloping coffee field and (iii) measurements from a laboratory incubation experiment with nutrient addition to different soil types. In the field and in the laboratory, additions included standard NPK fertiliser, ammonium nitrate (NH4NO3) as well as potassium nitrate (KNO3). Soils in a laboratory experiment were incubated under both drained and flooded conditions. Continuous measurements from automatic chambers show that annual N2O fluxes were dominated by bursts over few weeks following N-fertilisation with peak emissions up to 60 g N-N2O ha−1 day−1. A two-month slope experiment with static chambers after KNO3-fertilisation with 90 kg N ha−1 showed N2O significant differences between the highest daily emission rates from the top and the bottom of the slope (134 ± 20 g N-N2O ha−1 and 336 ± 104 g N-N2O ha−1, respectively) which can be explained by NO3- transport downhill and flooded conditions favouring denitrification at the bottom of the slope. Incubation experiments indicate that denitrification is the main process controlling N2O emissions but also that nitrification can result in low N2O emission rates under drained conditions. It can be concluded that the reported N2O emissions from the coffee agroforestry systems are generally low, but may be underestimated, as both poorly drained depressions functioning as N2O hotspots as well as temporal N2O bursts need to be taken into account.

Cocoa production has been one of the main drivers of forest loss in West Africa. In the resulting post-forest landscapes, agroforestry has often been recognised as a solution to reconcile the preservation of trees and agriculture. Thus, a large number of tree plantation programs have been carried out in cocoa fields. Despite these major investments, the success of these plantations as a tool for "reforestation" of landscapes and sustainable timber production has never really been evaluated in fields where remnant trees, spontaneous trees and (trans)planted trees coexist. To quantify the current and future timber resource, we inventoried all trees in 150 cocoa fields distributed along the bioclimatic and historical gradients of the cocoa production area of Côte d'Ivoire, the world's leading producer. Our results show that (i) 19.6% of all associated trees are timber species, (ii) in plots where farmers actually introduced trees by planting, only 13.1% of trees have been (trans)planted, (iii) 69.7% of the current timber volume comes from remnant trees and (iv) spontaneous trees constitute 77% of the future timber resource. Based on our results, we propose 23 species along with their cultivation methods for the renewal of timber resource in cocoa fields. Overall, our results show the failure of plantation programs in cocoa fields and suggest to bet on natural regeneration to sustainably provide timber wood. Consequently, private companies supplying trees to farmers should focus on species that are complementary to those already present in natural regeneration. At the landscape level, remnant trees and residual forests should be preserved to maintain propagule sources. Finally, investments in reforestation of cocoa fields should be redirected towards training small farmers in silvicultural management techniques such as assisted natural regeneration and tree pruning.

Identifying the drivers of soil organic carbon (SOC) stock changes is of the utmost importance to contribute to global challenges like climate change, land degradation, biodiversity loss, or food security. Evaluating the impacts of land use and management practices in agriculture and forestry on SOC is still challenging. Merging datasets or making databases interoperable is a promising way, but still has several semantic challenges. So far, a comprehensive thesaurus and classification of management practices in agriculture and forestry has been lacking, especially while focusing on SOC storage. Therefore, the aim of this paper is to present a first comprehensive thesaurus for management practices driving SOC storage (DATA4C+). The DATA4C+ thesaurus contains 224 classified and defined terms related to land management practices in agriculture and forestry. It is organized as a hierarchical tree reflecting the drivers of SOC storage. It is oriented to be used by scientists in agronomy, forestry, and soil sciences with the aim of uniformizing the description of practices influencing SOC in their original research. It is accessible in Agroportal (http://agroportal.lirmm.fr/ontologies/DATA4CPLUS, last access: 24 March 2022) to enhance its findability, accessibility, interoperability, and reuse by scientists and others such as laboratories or land managers. Future uses of the DATA4C+ thesaurus will be crucial to improve and enrich it, but also to raise the quality of meta-analyses on SOC, and ultimately help policymakers to identify efficient agricultural and forest management practices to enhance SOC storage.