Dataset Information

Sustainable grassland systems: a modelling perspective based on the North Wyke Farm Platform.

ABSTRACT: The North Wyke Farm Platform (NWFP) provides data from the field- to the farm-scale, enabling the research community to address key issues in sustainable agriculture better and to test models that are capable of simulating soil, plant and animal processes involved in the systems. The tested models can then be used to simulate how agro-ecosystems will respond to changes in the environment and management. In this study, we used baseline datasets generated from the NWFP to validate the Soil-Plant-Atmosphere Continuum System (SPACSYS) model in relation to the dynamics of soil water content, water loss from runoff and forage biomass removal. The validated model, together with future climate scenarios for the 2020s, 2050s and 2080s (from the International Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES): medium (A1B) and large (A1F1) emission scenarios), were used to simulate the long-term responses of the system with three contrasting treatments on the NWFP. Simulation results demonstrated that the SPACSYS model could estimate reliably the dynamics of soil water content, water loss from runoff and drainage, and cut biomass for a permanent sward. The treatments responded in different ways under the climate change scenarios. More carbon (C) is fixed and respired by the swards treated with an increased use of legumes, whereas less C was lost through soil respiration with the planned reseeding. The deep-rooting grass in the reseeding treatment reduced N losses through leaching, runoff and gaseous emissions, and water loss from runoff compared with the other two treatments.

SUBMITTER: Wu L

PROVIDER: S-EPMC5108350 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Sustainable grassland systems: a modelling perspective based on the North Wyke Farm Platform.

Wu L L Zhang X X Griffith B A BA Misselbrook T H TH

European journal of soil science 20151117 4

The North Wyke Farm Platform (NWFP) provides data from the field- to the farm-scale, enabling the research community to address key issues in sustainable agriculture better and to test models that are capable of simulating soil, plant and animal processes involved in the systems. The tested models can then be used to simulate how agro-ecosystems will respond to changes in the environment and management. In this study, we used baseline datasets generated from the NWFP to validate the Soil-Plant-A ...[more]

PMID: 27867312

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Project description:The North Wyke Farm Platform was established as a United Kingdom national capability for collaborative research, training and knowledge exchange in agro-environmental sciences. Its remit is to research agricultural productivity and ecosystem responses to different management practices for beef and sheep production in lowland grasslands. A system based on permanent pasture was implemented on three 21-ha farmlets to obtain baseline data on hydrology, nutrient cycling and productivity for 2 years. Since then two farmlets have been modified by either (i) planned reseeding with grasses that have been bred for enhanced sugar content or deep-rooting traits or (ii) sowing grass and legume mixtures to reduce nitrogen fertilizer inputs. The quantities of nutrients that enter, cycle within and leave the farmlets were evaluated with data recorded from sensor technologies coupled with more traditional field study methods. We demonstrate the potential of the farm platform approach with a case study in which we investigate the effects of the weather, field topography and farm management activity on surface runoff and associated pollutant or nutrient loss from soil. We have the opportunity to do a full nutrient cycling analysis, taking account of nutrient transformations in soil, and flows to water and losses to air. The NWFP monitoring system is unique in both scale and scope for a managed land-based capability that brings together several technologies that allow the effect of temperate grassland farming systems on soil moisture levels, runoff and associated water quality dynamics to be studied in detail.HighlightsCan meat production systems be developed that are productive yet minimize losses to the environment?The data are from an intensively instrumented capability, which is globally unique and topical.We use sensing technologies and surveys to show the effect of pasture renewal on nutrient losses.Platforms provide evidence of the effect of meteorology, topography and farm activity on nutrient loss.

Project description:Background: Development assistance for health (DAH) is an important mechanism for funding and technical support to low-income countries. Despite increased DAH spending, intractable health challenges remain. Recent decades have seen numerous efforts to reform DAH models, yet pernicious challenges persist amidst structural complexities and a growing number of actors. Systems-based approaches are promising for understanding these types of complex adaptive systems. This paper presents a systems-based understanding of DAH, including barriers to achieving sustainable and effective country-driven models for technical assistance and capacity strengthening to achieve better outcomes Methods: We applied an innovative systems-based approach to explore and map how donor structures, processes, and norms pose challenges to improving development assistance models. The system mapping was carried out through an iterative co-creation process including a series of discussions and workshops with diverse stakeholders across 13 countries. Results: Nine systemic challenges emerged: 1) reliance on external implementing partners undermines national capacity; 2) prioritizing global initiatives undercuts local programming; 3) inadequate contextualization hampers program sustainability; 4) decision-maker blind spots inhibit capacity to address inequities; 5) power asymmetries undermine local decision making; 6) donor funding structures pose limitations downstream; 7) program fragmentation impedes long-term country planning; 8) reliance on incomplete data perpetuates inequities; and 9) overemphasis on donor-prioritized data perpetuates fragmentation. Conclusions: These interconnected challenges illustrate interdependencies and feedback loops manifesting throughout the system. A particular driving force across these system barriers is the influence of power asymmetries between actors. The articulation of these challenges can help stakeholders overcome biases about the efficacy of the system and their role in perpetuating the issues. These findings indicate that change is needed not only in how we design and implement global health programs, but in how system actors interact. This requires co-creating solutions that shift the structures, norms, and mindsets governing DAH models.

Project description:PurposeIntensive livestock grazing has been associated with an increased risk of soil erosion and concomitant negative impacts on the ecological status of watercourses. Whilst various mitigation options are promoted for reducing livestock impacts, there is a paucity of data on the relationship between stocking rates and quantified sediment losses. This evidence gap means there is uncertainty regarding the cost-benefit of policy preferred best management.MethodsSediment yields from 15 hydrologically isolated field scale catchments on a heavily instrumented ruminant livestock farm in the south west UK were investigated over ~ 26 months spread across 6 years. Sediment yields were compared to cattle and sheep stocking rates on long-term, winter (November-April), and monthly timescales. The impacts of livestock on soil vegetation cover and bulk density were also examined. Cattle were tracked using GPS collars to determine how grazing related to soil damage.ResultsNo observable impact of livestock stocking rates of 0.15-1.00 UK livestock units (LU) ha-1 for sheep, and 0-0.77 LU ha-1 for cattle on sediment yields was observed at any of the three timescales. Cattle preferentially spent time close to specific fences where soils were visually damaged. However, there was no indication that livestock have a significant effect on soil bulk density on a field scale. Livestock were housed indoors during winters when most rainfall occurs, and best management practices were used which when combined with low erodibility clayey soils likely limited sediment losses.ConclusionA combination of clayey soils and soil trampling in only a small proportion of the field areas lead to little impact from grazing livestock. Within similar landscapes with best practice livestock grazing management, additional targeted measures to reduce erosion are unlikely to yield a significant cost-benefit.Supplementary informationThe online version contains supplementary material available at 10.1007/s11368-021-02909-y.

Project description:The data was collected in the Karagwe and Kyerwa districts of the Kagera region in north-west Tanzania. It encompasses 150 smallholder farming households, which were interviewed on the composition of their household, agricultural production and use of organic farm waste. The data covers the two previous rainy seasons and the associated vegetation periods between September 2016 and August 2017. The knowledge of experts from the following institutions was included in the discussion on the selection criteria: two local non-profit organisations, i.e., WOMEDA and the MAVUNO Project; the International Institute of Tropical Agriculture (IITA); and the National Land Use Planning Commission (NLUPC). Households were selected for inclusion if all of the following applied to them: 1) less than 10 acres of land (4.7 ha) registered in the village offices, 2) no agricultural training, and 3) decline in the fertility of their land since they started farming (self-reported). We selected 150 smallholder households out of a pool of 5,000 households known to WOMEDA in six divisions of the Kyerwa and Karagwe districts. The questionnaire contained 54 questions. The original language of the survey was Kiswahili. All interviews were audio recorded. The answers were digitalised and translated into English. The data set contains the raw data with 130 quantitative and qualitative variables. For quantitative variables, the only analysis that was made was the conversion of units, e.g., land area was converted from acres to hectares, harvest from buckets to kilograms and then to tons, and heads of livestock to Tropical Livestock Units (TLU). Qualitative variables were summarised into categories. All data has been anonymised. The data set includes geographical variables, household information, agricultural information, gender-specific responsibilities, economic data, farm waste management, and water, energy and food availability (Water-Energy-Food (WEF) Nexus). Variables are written in italics. The following geographical variables are part of the data set: district, division, ward, village, hamlet, longitude, latitude, and altitude. Household information includes start of farming, household size, gender and age of household members. Agricultural information includes land size, size of homegarden, crops, livestock and livestock keeping, trees, and access to forest. Gender-specific responsibilities includes producing and exchanging seeds, weed control, terracing, distributing organic material to the fields, care of annual and perennial crops, harvesting of crops, decisions about the harvest and animal products, selling and buying products, working on their own farm and off-farm, cooking, storing food, collecting and caring for drinking water, washing, and toilet cleaning. Economic data includes distance to the market, journey time to market, transport methods, labourers employed by the household, working off-farm, and assets such as type of house. Variables relevant to the WEF Nexus are drinking water source and treatment, meals per day, months without food, cooking fuel, and type of toilet. Variables on farm waste management are the use of crop residues, food and kitchen waste, livestock manure, cooking ash, animal bones, and human urine and faeces. The data can be potentially reused and further developed for the purpose of agricultural production analysis, socio-economic analysis, comparison to other regions, conceptualisation of waste and nutrient management, establishment of land use concepts, and further analysis on food security and healthy diets.

Dataset Information

Sustainable grassland systems: a modelling perspective based on the North Wyke Farm Platform.

Publications

Sustainable grassland systems: a modelling perspective based on the North Wyke Farm Platform.

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