International audience | Diffuse phytosanitary pollution is a complex phenomenon to manage. Reducing this type of pollution is one of today’s key socio-economic and environmental challenges. At the regional level, few approaches enable the actors concerned to implement agricultural management strategies to reduce the use and impact of phytosanitary products. Our research problem focused on the consequences of intensive agriculture and, in particular, how to evaluate the impact of phytosanitary products on human health and the environment. In this article, we present the SimPhy simulation game which places the actors from a given region directly into a situation in which they manage farms whilst under pressure to reduce phytosanitaries (quantity and toxicity). The application focused on the Merja Zerga catchment area in Morocco. The region is dominated by intensive agriculture which is located upstream from a Ramsar-classified wetland area. The SimPhy simulation game is based on a decision support system-type tool. It allows us to anticipate the impact of regulations on farming systems. It also enables us to analyse the consequences of the actors’ strategies on farm economies, human health and the quality of ecosystems. Initial results from the SimPhy simulation game enabled the technicians from Agricultural Development Center (CDA) themselves to learn about managing agricultural production systems in a dynamic and interactive fashion. With the simulation game, it was possible to learn about the farmer's ability to adapt to new regulatory constraints, and the involved consequences for toxicity risks for human health and the environment.

Using structured surveys in 2008 and 2016, change in disease burden and use of chemical treatments in Bangladesh shrimp farm management was examined. Overall, disease burden had increased in all farms and was more polarized, with a fewer number of individual infectious diseases responsible for most disease in ponds. Farmers also reported physical deformities, nutritional deficiencies, and unknown diseases further indicating poor health of their stock. To combat the threat, more chemical treatments were used (5.2 treatments per farm in 2008 versus 28.8 in 2016), resulting in an average increase of 424% in the number of active substances entering shrimp ponds. Although there was a modest reduction in the use of antimicrobials, shrimp was being exposed to a wider range of chemicals during rearing. The subsequent concern for the environment, animal and human health demands further research to identify potential risks from residues of chemical products.

Inappropriate farm management practices can lead to increased agricultural inputs and changes in atmospheric greenhouse gas (GHG) emissions, impacting climate change. This study was initiated in 2012 to assess the potential for straw retention to mitigate the negative environmental impact of various cropping systems on the Songnen Plain using the life cycle assessment (LCA) method combined with field survey data. Straw retention (STR) and straw removal (STM) treatments were established in continuous corn (CC) and corn-soybean rotation (CS) systems in a split-plot experiment. The effects of straw retention on the carbon footprint (CF) of cropland under different cropping systems were compared. The CF under CC was 2434–2707 kg CO₂ ha⁻¹ year⁻¹, 49–57% higher than that under CS. Nitrogen fertilizer produced the most CO₂, accounting for 66–80% of the CF. The carbon balances of the CC and CS systems with STR were positive, with annual carbon sequestrations of 9633 and 2716 kg CO₂ ha⁻¹ year⁻¹, respectively. The carbon balance (CB) of CC-STR was 255% higher than that of CS-STR. This study demonstrates that STR under CC cultivation is an environmentally friendly practice for agricultural production, can help achieve high-yield and low-carbon production in rainfed cropland, and can support the sustainable development of grain production in Northeast China.

High intensity agricultural production systems are problematic not only for human health and the surrounding environment, but can threaten the provision of ecosystem services on which farm productivity depends. This research investigates the effects of management practices in Costa Rica on on-farm insect diversity, using three different types of banana farm management systems: high-input conventional system, low-input conventional system, and organic system. Insect sampling was done using pitfall and yellow bowl traps, left for a 24-h period at two locations inside the banana farm, at the edge of the farm, and in adjacent forest. All 39,091 individual insects were classified to family level and then morphospecies. Insect species community composition and diversity were compared using multivariate statistics with ordination analysis and Monte Carlo permutation testing, and revealed that each of the management systems were significantly different from each other for both trap types. Insect diversity decreased as management intensity increased. Reduced insect diversity resulted in fewer functional groups and fewer insect families assuming different functions essential to ecosystem health. Organic farms had similar species composition on the farm compared to adjacent forest sites, whereas species composition increasingly differed between farm and forest sites as management intensity increased. We conclude that while organic production has minimal impact on insect biodiversity, even small reductions in management intensity can have a significantly positive impact on on-farm insect biodiversity and functional roles supported.

The study evaluated the response of macroinvertebrate assemblages to changes in water quality in different land-use settings in Manyame catchment, Zimbabwe. Four land-use categories were identified: forested commercial farming, communal farming, Great Dyke mining (GDM) and urban areas. Macroinvertebrate community structure and physicochemical variables data were collected in two seasons from 41 sites following standard methods. Although not environmentally threatening, urban and GDM areas were characterised by higher conductivity, total dissolved solids, salinity, magnesium and hardness. Chlorides, total phosphates, total nitrogen, calcium, potassium and sodium were significantly highest in urban sites whilst dissolved oxygen (DO) was significantly higher in the forested commercial faming and GDM sites. Macroinvertebrate communities followed the observed changes in water quality. Macroinvertebrates in urban sites indicated severe pollution (e.g. Chironomidae) whilst those in forested commercial farming sites and GDM sites indicated relatively clean water (e.g. Notonemouridae). Forested watersheds together with good farm management practices are important in mitigating impacts of urbanisation and agriculture. Strategies that reduce oxygen-depleting substances must be devised to protect the health of Zimbabwean streams. The study affirms the wider applicability of the South African Scoring System in different land uses.

This study presents a meta-analysis of 12 experiments that quantify nitrate-N leaching losses from grazed pasture systems in alluvial sedimentary soils in Canterbury (New Zealand). Mean measured nitrate-N leached (kg N/ha × 100 mm drainage) losses were 2.7 when no urine was applied, 8.4 at the urine rate of 300 kg N/ha, 9.8 at 500 kg N/ha, 24.5 at 700 kg N/ha and 51.4 at 1000 kg N/ha. Lismore soils presented significantly higher nitrate-N losses compared to Templeton soils. Moreover, a multiple linear regression (MLR) model was developed to determine the key factors that influence nitrate-N leaching and to predict nitrate-N leaching losses. The MLR analyses was calibrated and validated using 82 average values of nitrate-N leached and 48 explanatory variables representative of nitrogen inputs and outputs, transport, attenuation of nitrogen and farm management practices. The MLR model (R ² = 0.81) showed that nitrate-N leaching losses were greater at higher urine application rates and when there was more drainage from rainfall and irrigation. On the other hand, nitrate leaching decreased when nitrification inhibitors (e.g. dicyandiamide (DCD)) were applied. Predicted nitrate-N leaching losses at the paddock scale were calculated using the MLR equation, and they varied largely depending on the urine application rate and urine patch coverage.