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Background: The adoption of innovative cropping systems with low pesticide inputs would reduce environmental degradation and dependency on the use of plant protection products. Evaluating the pesticide risk to human health is a growing concern in the assessment of the sustainability of cropping practices. The assessment of human health risks linked to pesticide use in either conventional or innovative cropping systems is poorly documented in the literature. Objectives: This study focused on the assessment of pesticide exposure and human health risks from pesticide use in arable cropping systems (two monoculture and one intercropping system) associated with the use of various tillage practices (conventional tillage, reduced tillage, and no tillage). Methods: Human exposure (operators and residents) and health risks from pesticide use were assessed and compared between three conventional and six innovative cropping systems. We used the previously published BROWSE (Bystanders, Residents, Operators, and WorkerS Exposure) model based on data collected from interviews with the farmers and expert knowledge to compare the human health risk from pesticide use in the Setif area. Environmental conditions and the physical characteristics of the farmers were collected on three different farms from 2019 to 2021. Results: The modelling results demonstrate that human exposure to pesticides was systematically high under conservation tillage (no or reduced tillage) and monoculture cropping (pea and barley) conditions. It was also confirmed that operators experienced the highest cumulated exposure to pesticides (56 mg kg−1 bw day−1), followed by resident children seven days after pesticide application (0.66 mg kg−1 bw day−1). BROWSE simulations showed that dermal absorption was the most dominant route and represented more than 98% of the total amount of pesticides applied in all cropping × tillage system combinations. Regarding the overall results of the simulated human health risk, barley-pea intercropping was the most interesting system to reduce the risks for both operators and residents for all tillage practices. In addition, intercropping combined with conventional tillage was the most sustainable cropping system in terms of both agronomic performance (crop yield, Land Equivalent Ratio) and human health risk. Furthermore, the availability of advanced crop protection equipment was associated with a significant decrease in exposure and human health risk for both operators and residents. Conclusions: The prediction of human health risks using BROWSE could help farmers to make the decision to adopt conventional barley-pea intercropping as a good alternative to barley monocultures and pea monocultures under conservation tillage.

International audience; The diversity of both pedoclimatic and socio-economic contexts in agricultural landscapes makes evaluating the impacts of climate change a challenge. Models are pertinent tools to quantitatively explore possible futures, and participatory approaches help account for local diversity. We developed a model through an approach that involves stakeholders in the model's construction and testing and in the discussion of results. We simulated spatially explicit impacts of climate change on water balance, grape phenology, and yield in a Mediterranean vineyard watershed for two climate scenarios. Results show a decrease in grape production of 7–14% by 2100. Yield decrease would be higher in irrigated high-yield areas despite a doubling of irrigation water supply. A forecasted 6 °C increase in temperature during berry ripening would threaten wine quality. The approach allows the communication of model results and limitations to stakeholders. It is a promising means of identifying potential local adaptations to climate change.

CONTEXT Climate change and variability have been identified as major threats to key sectors such as agriculture that drive economic growth and sustainable development in developing countries. The provision of tailored weather and climate information services (WCIS) that meet users' expectations can play an important role in helping decision makers adapt to and mitigate the effects of climate change and climate However, the evidence base showing the benefits of WCIS is still thin. OBJECTIVE This study analyzes the impact of uptake of tailored seasonal and daily weather forecasts that are mediated by a multidisciplinary working group (MWG) on crop productivity and household income of smallholder farmers in Senegal. METHODS A two-season balanced dataset in combination with panel econometrics was used to explore the impact of uptake of weather and climate information on crop income for farmers in Senegal. The data were complemented by participatory surveys that provide richer contextual information to explain the causal pathways that link farmers' uptake with increased crop income for farmers with access to the MWG. RESULTS AND CONCLUSIONS Results show that the use of weather and climate information increased the value of crop produce by between 10 and 25% for farmers with access to an MWG. Coordinated platforms that involve diverse stakeholders like the MWGs play a critical role in co-producing weather and climate information that are more usable to farmers, thereby improving uptake and livelihoods. The impact pathways and implications for policy are discussed. SIGNIFICANCE This study expands the limited evidence base on the role of weather and climate services in improving the livelihoods of smallholder by (i) going beyond the use of cross-sectional and using longitudinal data, (ii) analyzing causal impacts on farmer's livelihoods, i.e., crop yields and household income and (iii) using participatory approaches to better explain the causal impact pathways.

Oil palm cultivation has environmental impacts, including those associated with nitrogen (N) losses. Improving management practices to optimise yield and N losses is critical. In order to identify the key management and site parameters driving yield and N losses, over a 25-year cycle, we undertook a Morris’s sensitivity analysis of the Agricultural Production Systems sIMulator oil palm model (APSIM-Oil palm), using 3 sites in Papua New Guinea. We selected 12 parameters and 3 outputs: yield, nitrous oxide (N2O) emissions and N leaching. The influence of the 12 parameters on the outputs depended on site characteristics, age of the palms, and climate. The most influential parameters for losses were N mineral fertiliser rate, drainage and fraction of legume in groundcover vegetation. The simulations suggested that APSIM-Oil palm is a useful tool for assessing management options for optimising yield and environmental outcomes in different environments. The results can also guide future measurements needed to improve N loss estimates, and further development of models and risk indicators.

We adopt a theory-based approach to synthesize research on the effectiveness of payments for environmental services in achieving environmental objectives and socio-economic co-benefits in varying contexts. Our theory of change builds on established conceptual models of impact pathways and highlights the role of (1) contextual dimensions (e.g., political, institutional, and socio-economic conditions, spatial heterogeneity in environmental service values and provision costs, and interactions with pre-existing policies), and (2) scheme design (e.g., payment type and level, contract length, targeting, and differentiation of payments) in determining environmental and socio-economic outcomes. To shed light on the overall effectiveness of payment schemes, and its determinants, we review counterfactual-based empirical evaluations, comparative analyses of case-studies, and meta-analyses. Our review suggests that program effectiveness often lags behind the expectations of early theorists. However, we also find that theory has advanced sufficiently to identify common reasons for why payment schemes fail or succeed. Moreover, payment schemes are often rolled out along with other policy instruments in so-called policy mixes. Advances in theory and evaluation research are needed to improve our understanding of how such policy mixes interact with the targeted social-ecological systems. © 2017

Background Interest in impact evaluation has grown rapidly as research funders increasingly demand evidence that their investments lead to public benefits. Aims This paper analyses literature to provide a new definition of research impact and impact evaluation, develops a typology of research impact evaluation designs, and proposes a methodological framework to guide evaluations of the significance and reach of impact that can be attributed to research. Method An adapted Grounded Theory Analysis of research impact evaluation frameworks drawn from cross-disciplinary peer-reviewed and grey literature. Results Recognizing the subjective nature of impacts as they are perceived by different groups in different times, places and cultures, we define research impact evaluation as the process of assessing the significance and reach of both positive and negative effects of research. Five types of impact evaluation design are identified encompassing a range of evaluation methods and approaches: i) experimental and statistical methods; ii) textual, oral and arts-based methods; iii) systems analysis methods; iv) indicator-based approaches; and v) evidence synthesis approaches. Our guidance enables impact evaluation design to be tailored to the aims and context of the evaluation, for example choosing a design to establish a body of research as a necessary (e.g. a significant contributing factor amongst many) or sufficient (e.g. sole, direct) cause of impact, and choosing the most appropriate evaluation design for the type of impact being evaluated. Conclusion Using the proposed definitions, typology and methodological framework, researchers, funders and other stakeholders working across multiple disciplines can select a suitable evaluation design and methods to evidence the impact of research from any discipline.

The assessment of the impacts of land-use and management on soil organic carbon (SOC) dynamics is a major environmental concern, as the soil carbon cycle underpins key ecosystem services. However, assessments based on short-term SOC dynamics face methodological and experimental difficulties. Hurisso et al. (2016) proposed a method to assess SOC dynamics by coupling two methods: Permanganate Oxidizable Carbon (POXC) and Basal Soil Respiration (BSR). This method has been used in laboratory on dried and re-wetted soil samples from temperate regions mainly. In our study, we adapted this method to the field and proposed a cost-effective in-field indicator combining the POXC and in situ Basal Soil Respiration (SituResp (R) method). We tested the indicator at four study sites (n = 169 points) within various tropical land-use and management contexts based on rubber, soybean and oil palm cropping systems respectively in Thailand, Cambodia and Indonesia. The results demonstrated the relevance, sensitivity and robustness of the POXC-SituResp (R) indicator to characterize the impact of a gradient of disturbance on SOC dynamics. The results also highlighted the potential of conservation agriculture (no-tillage and crops residues) and compost amendments to accumulate SOC. Rock-Eval (R) analysis showed that POXC-SituResp (R) indicator is negatively linked to excess of potentially mineralizable labile carbon. Carbon pools targeted by the POXC were specified by Rock-Eval (R) pyrolysis measurements to be a rather thermal resistant pool of SOC. Our study confirms that the integrated indicator based on POXC and BSR assess a relative carbon stabilization of SOC pools. This indicator can be measured in the field by a rapid and cost-effective method.

Tropical ecosystem conversion to agriculture has caused widespread habitat loss and created fragmented landscapes composed of remnant forest patches embedded in a matrix of agricultural land uses. Non-traditional agricultural export (NTAE) crops such as pineapple are rapidly replacing multiuse landscapes characterized by a diverse matrix of pasture and smallholder crops with intensive, large-scale, monoculture plantations. Using an interdisciplinary approach, we conduct a case study to examine the coupled social and ecological implications of agricultural intensification in this region, with larger application to regions experiencing similar patterns of agricultural intensification. Guided by frameworks from both political and landscape ecology, we: (1) describe the social and economic implications of pineapple expansion, specifically the concentration of land, labor and financial resources, (2) quantify pineapple cultivation's spatial characteristics, and (3) assess the effects of pineapple expansion on surrounding forest ecosystems, on the agricultural matrix and on biodiversity conservation. Our results indicate that pineapple production concentrates land, labor, and financial resources, which has a homogenizing effect on the agricultural economy in the study region. This constrains farm-based livelihoods, with larger implications for food security and agricultural diversity. Landscape ecology analyses further reveal how pineapple production simplifies and homogenizes the agricultural matrix between forest patches, which is likely to have a negative effect on biodiversity. To offset the effects of pineapple expansion on social and environmental systems, we recommend developing landscape level land use planning capacity. Furthermore, agricultural and conservation policy reform is needed to promote landscape heterogeneity and economic diversity within the agricultural sector. Our interdisciplinary research provides a detailed examination of the social and ecological impacts of agricultural intensification in a tropical landscape, and offers recommendations for improvement relevant not only to our study region but to the many other tropical landscapes currently undergoing non-traditional agricultural export driven agricultural intensification.

Northeastern Thailand is an essential production area for high-quality fragrant rice for both domestic use and export. While rain-fed conditions still largely prevail, plans to extend irrigation are being drafted. This paper compares the advantages of rice production under irrigation and rain-fed conditions in both environmental and economic terms. Indicators of techno-economic performances were combined with environmental impact indicators based upon life cycle assessment, energy and water use analyses. Data were collected in 2010 at the farm level in 43 households of Lam Sieo Yai Basin in North-Eastern Thailand, according to 3 cropping systems, namely wet-season rain-fed (Rw), wet-season irrigated (Iw) and dry-season irrigated (Id) systems. Eco-efficiency indicators were calculated as per impact category. Wide-ranging techno-economic performances and environmental impacts were observed, while cropping practices were found to be homogeneous. Differentiation of systems originated mostly from differences in yield, which were mostly impacted by water supply. Yields vary from 2625 kg/ha in the Iw system to 2375 in the Rw system and 2188 in the Id system. The results highlight the low performances of Id systems in both techno-economic and environmental terms. Id systems require mostly blue water, while the two other systems rely primarily on green water. Id systems also require more energy and labour, due to increased water management needs. Overall, the productivity of most production factors was found to be higher in Rw and Iw systems; this results in return on investment being slightly higher in the Iw system compared to the Rw system (0.12 kg/THB and 0.11 kg/THB, respectively) and is lowest in the Id system (0.1 kg/THB) where THB is Thai baht, currency of Thailand. In Id systems, farmers need to produce twice as much rice (0.41 kg) to obtain 1 THB of net income, compared to 0.23 and 0.25 kg for Iw and Rw respectively. Emissions proved relatively similar across all 3 systems, with the exception of CH 4 , which was markedly lower in Rw systems due to specific water and organic residue management. Id systems systematically emitted more nitrates, phosphates and pesticides into water sources. Rw systems showed the lowest environmental impacts per ha and per kg of paddy rice produced. GWP 100 was higher in Id systems (5.55 kg CO 2 -eq per kg of rice) compared to Iw (4.87) and Rw (2.97). Finally, Rw systems were found to be more eco-efficient in most impact categories, including Global Warming Potential. The total value product per kg of CO 2 -eq emitted is 4, 2.5 and 2.2 THB in Rw, Iw, and Id systems respectively. This paper further discusses the results in view of contrasting perspectives, including societal objectives, farmer income and environmental integrity, and possible irrigation development in Northeastern Thailand.

The objective of the work reported here was to reduce the uncertainty on the greenhouse gas balances of biofuels using agro-ecosystem modeling at a high resolution over the Ile-de-France region in Northern France. The emissions simulated during the feedstock production stage were input to a life-cycle assessment of candidate biofuel pathways: bioethanol from wheat, sugar-beet and miscanthus, and biodiesel from oilseed rape. Compared to the widely-used methodology based on fixed emission factors, ecosystem modeling lead to 55–70% lower estimates for N2O emissions, emphasizing the importance of regional factors. The life-cycle GHG emissions of first-generation biofuels were 50–70% lower than fossil-based equivalents, and 85% lower for cellulosic ethanol. When including indirect land-use change effects, GHG savings became marginal for biodiesel and wheat ethanol, but were positive due to direct effects for cellulosic ethanol.

High resolution and low uncertainty deforestation maps covering large spatial areas in tropical countries are needed to plan efficient forest conservation and management programs such as REDD + (Reducing Emissions from Deforestation and Forest Degradation). Using an open-source free software (R, GRASS and QGis) and an original statistical approach combining multi-date land cover observations based on Landsat satellite images and the random forests classifier, we obtained up-to-date deforestation maps for the periods 2000–2005 and 2005–2010 with a minimum mapping unit of 0.36 ha for 7.7 M hectares, i.e. 40.3% of the tropical humid forest and 20.6% of the tropical dry forest in Madagascar. Uncertainty in deforestation on the maps was calculated by comparing the results of the classification to more than 30,000 visual interpretation points on a regular grid. We assessed accuracy on a per-pixel basis (confusion matrix) and by measuring the relative surface difference between wall-to-wall approach and point sampling. At the pixel level, user accuracy was 84.7% for stable land cover and 60.7% for land cover change. On average for the whole study area, we obtained a relative difference of 2% for stable land cover categories and 21.1% land cover change categories respectively between the wall-to-wall and the point sampling approach. Depending on the study area, our conservative assessment of annual deforestation rates ranged from 0.93 to 2.33%·yr− 1 for the humid forest and from 0.46 to 1.17%·yr− 1 for the dry forest. Here we describe an approach to obtain deforestation maps with reliable uncertainty estimates that can be transposed to other regions in the tropical world.

In the Congo Basin where most timber species are light-demanding, the low logging intensities commonly implemented (1–2 trees harvested ha −1 ) do not provide sufficient canopy gaps to ensure species regeneration. The regeneration of light-demanding timber species may therefore benefit from more intensive logging, or from post-harvest treatments such as thinning by poison girdling that increases light penetration. Little is known of the impact of post-harvest treatments on the floristic composition of tropical moist forests. This study therefore aimed to assess the effects of low and high selective logging (≃2.33 and 4.73 trees harvested ha −1 , and ≃4.96 and 9.16 m 2 ha −1 of basal area removed (logging + damage), respectively) – followed or not by thinning (≃21.14 trees thinned ha −1 , and ≃6.57 m 2 ha −1 of basal area removed) – on the floristic composition of a tropical moist forest in the Central African Republic, from 7 to 23 years after logging. We analyzed abundance data for 110 tree genera recorded every year for 14 years in 25 one-hectare permanent subplots. We used multivariate analysis to detect floristic variations between treatments and we assessed changes in floristic composition throughout the period. We compared floristic composition recovery between thinned and unthinned subplots, using unlogged subplots as a reference characterizing the pre-logging floristic composition. Logging and thinning had little impact on the floristic composition of the subplots as quantified 7 to 23 years later, though they did increase the proportion of pioneer species. Surprisingly, additional thinning at both logging levels failed to further distance floristic composition from that of the unlogged subplots, though it did increase disturbance intensity. Floristic composition recovery appeared to be facilitated when thinning was associated with logging. Thinning seemed to favor the growth and survival of non-pioneer species, to the detriment of pioneer species. These non-pioneer species could either be non-pioneer light demanders or shade-bearers. One explanation for this is that thinning by tree-poison girdling increased light availability without causing major damage to the forest, and thus increased the growth and survival of advance regeneration. The resulting enhanced competition then reduced the survival of pioneer species.

International audience; Cropping system models are powerful tools for regional impact assessment, but their input data requirements for large heterogeneous areas are difficult to fulfil. Hence, the objectives of this paper are to present low-data approaches for specifying detailed management data required by cropping system models, and for calibrating default crop parameters applied to 12 regions in the European Union (EU). Various downscaling and upscaling procedures for different data types are applied to address both objectives. The Agricultural Production and Externalities Simulator (APES) model is used for illustrative purposes. Combining easy-to-collect regional crop management information and expert knowledge enables to develop generic, expert-based rules for specifying crop management. Effects of these expert-based management rules on simulated yields and nitrogen leaching are illustrated using APES. Simulated yields of grain maize, soft wheat and durum wheat using default crop parameters for phenology are compared with crop yields observed in 12 EU regions. The accuracy of the simulated yields was variable, but generally poor. A regional calibration factor Kpheno is developed based on the temperature sum of the average sowing and harvest dates of the three crops in each region. Applying this calibration factor improved the simulated yields in all cases. Results suggest that it is possible to develop expert-based management rules and to capture yield variation across the EU by using the presented low-data approaches.