Agronomy for Sustainable Development最新文献

The occurrence and spread of invasive woody species are a truly global phenomenon, but tropical regions seem to be particularly vulnerable due to high rates of soil degradation in combination with climate change, and limited resources for containment. There is increasing awareness that complete eradication programs are often not effective. The existence of many “controversial species,” i.e., species with both negative and positive impacts, renders decision-making processes for management exceedingly complex. By providing a very extensive overview of the current state of knowledge on impacts and containment strategies of invasive woody species, we aim to help underpin such decisions. We discuss both negative impacts and potential benefits of invasive woody species, focusing on the two most important ones, namely animal fodder production and the positive impacts on soil functioning and soil quality. Invasive woody species can positively impact livestock production (1) indirectly by improving pasture quality because of improved soil quality and functioning, and (2) directly by supplying a high-quality protein component for animal fodder. Invasive woody species increase soil carbon sequestration and nitrogen and phosphorus availability depending on the density of the invader, its capacity to fix nitrogen, the quantity and quality of its litter, and the direct interactions between its roots and the soil microbial community. The balance between potential benefits and risks depends to a large extent on the interaction with the local environment (climate, soil, vegetation, and animals) and the socioeconomic context of each region. When an invasion process starts because there is no local predator, then management can target eradication or very strict containment. If the invasion is the result of strong disturbance of the ecosystem, then intensive but well-thought management of the invasive species would be the choice to be made, as this may help to restore the ecosystem.

Abstract

European farm households will face increasingly challenging conditions in the coming decades due to climate change, as the frequency and severity of extreme weather events rise. This study assesses the complex interrelations between external framework conditions such as climate change or adjustments in the agricultural price and subsidy schemes with farmers’ decision-making. As social aspects remain understudied drivers for agricultural decisions, we also consider value-based characteristics of farmers as internal factors relevant for decision-making. We integrate individual learning as response to extreme weather events into an agent-based model that simulates farmers’ decision-making. We applied the model to a region in Eastern Austria that already experiences water scarcity and increasing drought risk from climate change and simulated three future scenarios to compare the effects of changes in socio-economic and climatic conditions. In a cross-comparison, we then investigated how farmers can navigate these changes through individual adaptation. The agricultural trajectories project a decline of active farms between −27 and −37% accompanied by a reduction of agricultural area between −20 and −30% until 2053. The results show that regardless of the scenario conditions, adaptation through learning moderates the decline in the number of active farms and farmland compared to scenarios without adaptive learning. However, adaptation increases the workload of farmers. This highlights the need for labor support for farms.

This study is based on the observation that many digital tools and services for agriculture do not put farmers’ expectations and interests first, resulting in top-down research and development. On-Farm Experimentation (OFE) contributes to overcoming these limitations because it places farmers at the center of innovation processes, while ensuring rich interactions with various value chain actors. The richness of OFE is in part explained by the diversity of stakeholders involved and the co-learning that results from their interactions. Studies in management and social sciences show that such open innovation processes can be difficult to manage. Aligning the visions and interests of the different stakeholders, fostering the sharing of resources and knowledge to produce value, and sharing the value created in an equitable manner remain a real challenge. Although these issues can refine the understanding of the mechanisms that condition the success of OFE, they have yet to be sufficiently analyzed. Recent publications underline the need to explore the organizational and managerial aspects of OFE to facilitate its implementation in various contexts. This work proposes to fill this gap by providing ten key lessons for conducting OFE with the aim of creating shared value, i.e., developing innovative technologies and practices that benefit all parties but, first and foremost, farmers. These ten key lessons stem from the reflexive monitoring of an OFE process aimed at developing the SoYield® decision support system for helping mango value chain actors to estimate fruit production in Africa. This reflexive monitoring was conducted by the main actors involved in this process, namely, farmers, a private firm and research centers. These key lessons lay the foundations for strengthening a community of practice on OFE implementation and for facilitating its development worldwide. This study also provides insights into the contributions and limitations of digital tools for conducting OFE.

The management of climate-resilient grassland systems is important for stable livestock fodder production. In the face of climate change, maintaining productivity while minimizing yield variance of grassland systems is increasingly challenging. To achieve climate-resilient and stable productivity of grasslands, a better understanding of the climatic drivers of long-term trends in yield variance and its dependence on agronomic inputs is required. Based on the Park Grass Experiment at Rothamsted (UK), we report for the first time the long-term trends in yield variance of grassland (1965–2018) in plots given different fertilizer and lime applications, with contrasting productivity and plant species diversity. We implemented a statistical model that allowed yield variance to be determined independently of yield level. Environmental abiotic covariates were included in a novel criss-cross regression approach to determine climatic drivers of yield variance and its dependence on agronomic management. Our findings highlight that sufficient liming and moderate fertilization can reduce yield variance while maintaining productivity and limiting loss of plant species diversity. Plots receiving the highest rate of nitrogen fertilizer or farmyard manure had the highest yield but were also more responsive to environmental variability and had less plant species diversity. We identified the days of water stress from March to October and temperature from July to August as the two main climatic drivers, explaining approximately one-third of the observed yield variance. These drivers helped explain consistent unimodal trends in yield variance—with a peak in approximately 1995, after which variance declined. Here, for the first time, we provide a novel statistical framework and a unique long-term dataset for understanding the trends in yield variance of managed grassland. The application of the criss-cross regression approach in other long-term agro-ecological trials could help identify climatic drivers of production risk and to derive agronomic strategies for improving the climate resilience of cropping systems.

As an essential element of crop growth, phosphorus (P) plays an important role in maintaining agricultural sustainability and ecological balance. A quantitative understanding of agronomic and environmental soil P thresholds at the global scale is required to enhance P-use efficiency and crop productivity while preventing environmental P losses. To address this issue, we conducted a meta-analysis with 584 data observations from 175 studies in 326 locations to assess the critical soil P thresholds as related to crop type and soil properties. The results showed that the average agronomic soil P threshold across all crops was 19.36 mg·kg⁻¹ and the threshold was highest for vegetables (mean = 30.04 mg·kg⁻¹), intermediate for cereals (mean = 17.06 mg·kg⁻¹), and lowest for legumes (mean = 9.30 mg·kg⁻¹). In contrast, the mean environmental soil P threshold across soil textures was 48.56 mg·kg⁻¹. The environmental soil P threshold was significantly affected by soil texture and followed the order of clay > loam > sandy soils. Agronomic soil P thresholds correlated negatively with climate variables including mean annual temperature and mean annual precipitation, and positively with soil organic matter content. The environmental P thresholds correlated negatively with soil pH. Gradient-boosted regression tree statistical model analysis suggested that crop type and soil texture were the most important determinants of the variation in agronomic and environmental soil P thresholds, respectively. This study provides a first quantitative assessment of agronomic and environmental soil P thresholds for different crops, climates, and soil textures and should help improve the management of cropland P worldwide.

In rainfed crop production regions such as the US Corn belt, the existence of a shallow water table increases crop productivity, decreases inter-annual grain yield variability, and impacts environmental N losses. Understanding how climate and management scenarios influence water table depth is key to designing sustainable and profitable cropping systems. A concurrent cropping systems-level examination of how weather variability, climate change, and agronomic management affect water table dynamics is missing. To fill this knowledge gap, we developed a systems evaluation using APSIM framework with the objectives to (1) quantify how weather and agronomic management (subsurface drainage, tillage, crop sequences) affect the water table depth and its seasonal variability under present and future (2020 to 2080) climate scenarios and (2) develop functional relationships between water table depth and productivity and sustainability indicators to increase our knowledge base. We considered four US Corn Belt environments with various water table depth conditions. Results indicated that the water table depth was mostly dictated by weather conditions, with management to alter water table depth by up to 31% under present climate conditions and up to 6% under future climate projections. The overall ranking of management practices in terms of influence on water table depth was subsurface tile drainage > tillage > crop sequence. The water tables will become slightly deeper in the future, with an overall downward trend of 0.18 cm year⁻¹ (2020–2080), mostly driven by increased temperature and therefore evapotranspiration. For every degree increase in temperature, the water table depth deepened by about 8 cm. Water table depth affected crop yields, rooting depths, N₂O emissions, and runoff in different ways revealing important tradeoffs between productivity and sustainability metrics. Our study provides new insights into an important water source for crop production, which can inform decision-making and climate change adaptation strategies.

Livestock production is central to the livelihoods of smallholder farmers in low- and middle-income countries, but livestock are often poorly fed which limits their potential for reducing poverty. Efforts to improve livestock nutrition are often driven by supply-push thinking and fail to engage meaningfully with farmers and the realities they face. The Feed Assessment Tool (FEAST) was developed as a way of involving farmers more closely in decision making on livestock feed improvement. FEAST is a participatory tool which uses focus group discussions and individual farmer interviews to develop a broad overview of the livestock farming system. FEAST has been applied in many countries in the last 10 years. Examples of intensive use come from the Accelerated Value Chain Development Project in Kenya and the Rwanda Dairy Development Project in Rwanda. In both cases the tool was used to inform feed options with strong input from farmers. Although the primary purpose of FEAST is to support improved feed strategies at farm level, the data collected through the FEAST app and published in FEAST reports are a rich information resource that can be useful for developing broader system-level understanding of livestock feed issues. FEAST data can be uploaded into a global data repository where they are available for researchers. These data are also used to generate visualizations of key feed metrics further extending the use of secondary data. FEAST is an example of a participatory tool that moves decision making in the direction of farmers, while providing insights to researchers working across farming systems. Its widespread use across many countries is an indication that it fills a gap in in the livestock feed development space. Its novelty lies in bridging the knowledge gap (both ways) between livestock researchers and small-scale livestock keepers.

Water scarcity threatens irrigated agriculture in sub-Saharan Africa (SSA). Knowledge of farmers’ perceptions and drivers for decision-making in view of coping with water scarcity is so far lacking but needed to improve local technologies and frame policies fostering their adoption. Here, for the first time, we investigated farmers’ perception of water scarcity, key adaptation strategies, and the determinants of their adoption in irrigated rice schemes in dry climatic zones of West Africa. We surveyed 572 farming households and conducted expert interviews with key informants in four contrasting irrigated rice schemes in Burkina Faso between April 2018 and August 2019. Information was gathered on biophysical field characteristics, grain yields, agronomic and water management practices, farmers’ perception of water scarcity, their adaptive responses, and social-economic attributes of adopting households. Nearly 80% of the respondents reported having experienced water scarcity during the past 5 years. To cope with the adverse effect of water scarcity, farmers implemented seventeen different adaptation strategies that could be categorized into seven groups. Most popular among those were “water and soil conservation practices” (consisting mainly of field bunding and leveling), “no rice cultivation,” and “crop rotation.” Farmers in drier areas (Sudano-Sahelian zone) were less likely to adopt and implement several adaptation strategies to water scarcity compared to farmers in wetter areas (Sudanian zone). Belonging to farming associations increased the probability of implementing several strategies to alleviate water scarcity, while female-headed households tended to have a lower propensity to adopt and implement concomitantly several adaptation strategies in comparison with their male counterpart. The dissemination of scheme- and household-specific technology options could contribute to mitigating water scarcity in irrigated rice-based systems in the dry climatic zones of West Africa, thus contributing to rural livelihood and food security.

The Alentejo region in Portugal is vital to the country’s beef industry and is home to 60% of the Portuguese beef cattle population. Farmers increasingly rely on imported synthetic fertilizer and feed. The uncertainty of global oil supply and indirect inputs calls into question the robustness of the beef farming system in Alentejo, defined as the capacity of the system to maintain its function (beef production) in spite of a disturbance (decreased input availability). An additional challenge is the need for reducing greenhouse gas emissions to meet decarbonization goals. At present, these challenges are being addressed through management practices such as expanding areas of high-yield sown biodiverse pastures and fattening steers partially on grass rather than concentrates. These practices have been shown to reduce greenhouse gas emissions, but their effect on the robustness of beef production when inputs are scarce is unknown. To fill this gap, we adapted a dynamic nitrogen mass flow model to assess herd dynamics and calculate a greenhouse gas emissions balance. We applied the model for seven scenarios corresponding to different combinations of management practices over 50 years with increasing input constraints. We estimated, without changes and without constraints, a greenhouse gas balance of 55 kgCO₂-e kg carcass⁻¹ year⁻¹ (100-years global warming potential). Without changes but faced with constraints, meat production dropped 60% (low long-term robustness) in 50 years while increasing by 17% the greenhouse gas balance. Our results showed that a combination of high-yield legume-rich pastures, maximization of grass intake, herd size reduction, and increased animal productivity allowed the smallest reduction of meat production (28%) and largest greenhouse gas emission reduction (30%, i.e., 38.9 kgCO₂-e kg carcass⁻¹ year⁻¹). This was the best, among the combination studied, at mitigating the trade-off between robust meat production and climate change mitigation.