Grazing behaviour, urine composition and soil properties are key controls of N2O emission factors in the uplands

该项目的目的是开发一个更好的理解放牧行为，饲料选择，尿液成分和土壤条件之间的空间和时间的相互作用，并利用所获得的见解，以提高一氧化二氮（N2 O）排放量估计的准确性，从对比半改善和未改善的高地放牧牧场在英国。这是非常重要的，因为（1）尿斑是N2 O的重要来源;约。（2）高地系统N_2O损失具有很强的不确定性。目前估算尿斑排放量的方法忽略了牲畜饮食、土壤类型、土壤理化性质和气候对N2 O通量的影响。例如，尿中的氮含量随着蛋白质摄入量的变化而变化，尿中的代谢产物（已知会影响N2 O的产生）受到牲畜放牧的影响。不同高地地区的植被差异很大，两种系统都有饮食选择。因此，将尿液成分与动物的运动和饮食选择联系起来是很重要的。高地的土壤主要是泥炭和灰壤，含碳量高，pH值低，受凉爽潮湿的气候和地形的影响。这些因素也将发挥系统的控制率的N2 O通量可能会加剧尿液沉积。此外，在不同的高地地区的植被影响放养密度和随之而来的潜在尿斑重叠，导致不成比例的N2 O排放量在接收高N负荷率的地区。这些地区的土壤会因牲畜践踏而变得紧实，减少空气填充的孔隙空间，增加厌氧性，并通过反硝化作用增加N2 O损失的条件。因此，有必要建立尿液成分之间的关系，（放牧偏好的结果），土壤类型，土壤理化性质（这可能会受到地形对水文的影响）和气候的影响，以产生更好的N2 O通量估计，排放因子和畜牧业生产的碳足迹。我们将通过以下结合来解决这些知识差距：一）利用高分辨率遥感成像在对比鲜明的高地地区对控制一氧化二氮通量的“移动的”因素，即地形、土壤类型、植被类型和土壤压实情况进行精细测绘和观察排尿事件iii）从绵羊放牧的主要植被类型收集尿液并将尿液组成与饮食偏好相关联iv）在将收集的尿液施用到典型植被类型下的土壤后测量N2 O通量，并计算12个月期间尿液中一氧化二氮直接排放系数的可靠性v）采用重复控制试验研究了不同农田土壤N2 O排放通量的影响因素（例如改变尿液成分，含水量和压实度）vi）开发一个新的模型框架来预测动物占用的统计数据，并将预测的尿液排放量与景观的时空信息相结合-尺度解释因子，以量化的总N2 O排放量为高地牧场独特的是，我们将获得更好的理解空间和时间之间的相互作用的放牧模式，牧草的选择，尿液成分，土壤和气候因素和N2 O通量在高地系统。该项目的产出将与IPCC第1层和第2层方法进行比较，以估计英国牲畜放牧的N2 O排放量，并为标准清单方法的稳健和科学合理的改变提供基础，如果需要的话，沿着输入碳足迹和缓解措施的空间目标。

The aim of this project is to develop an improved understanding of the spatial and temporal interactions between grazing behaviour, forage selection, urine composition and edaphic conditions and to use the insights garnered to improve the accuracy of nitrous oxide (N2O) emission estimates from contrasting semi-improved and unimproved upland grazed pastures in the UK. This is of major importance because (1) urine patches are a significant source of N2O; ca. 19% of the total N2O losses from agriculture, and (2) N2O losses from upland systems are highly uncertain. Current methods of estimating emissions from urine patches ignore the effect that livestock diet, soil type, soil physico-chemical properties and climate have on N2O fluxes. For example, urine N content varies with protein intake, and the metabolic product in the urine (known to affect N2O production) is affected by what livestock graze. Vegetation in different upland areas varies enormously, with diet selection operating in both systems. Hence it is important to link urine composition to animal movement and diet selection.Soils in the uplands are dominated by peats and podzols with high carbon content and low pH, influenced by cool, wet climates and topography. These factors will also exert systematic controls on rates of N2O fluxes which are likely to be exacerbated following urine deposition. Moreover, the vegetation in different upland areas influences stocking densities and the consequent potential for urine patch overlap, resulting in disproportionate N2O emissions in areas receiving high N loading rates. Soil in these areas can become compacted due to livestock trampling, reducing air filled pore space, increasing anaerobicity and enhancing conditions for N2O losses via denitrification. It is, therefore, essential to establish the relationships between urine composition (the result of grazing preference), soil type, soil physico-chemical properties (which might be influenced by topographic effects on hydrology) and climate in order to generate improved N2O flux estimates, emission factors and carbon footprints from livestock production.We will address these knowledge gaps through a combination of: i) Fine-scale mapping of 'static' factors controlling N2O fluxes, i.e. topography, soil type, vegetation type and soil compaction, using high resolution remotely sensed imaging over contrasting upland areasii) Mapping of the 'mobile' factors controlling N2O fluxes, i.e. measuring livestock movement and grazing patterns in these two grassland systems using GPS collars, and observing urination eventsiii) Collection of urine from sheep grazing dominant vegetation types and relating the urine composition to dietary preferenceiv) Measurement of N2O fluxes following the application of collected urine to soil under typical vegetation types, and calculation of robust urine direct N2O emission factors over a 12 month periodv) Conducting controlled replicated experiments to explore the factors controlling N2O fluxes from soil from contrasting field sites (e.g. changing urine composition, water content and levels of compaction)vi) Developing a novel model framework to predict the statistics of animal occupancy and to integrate predicted urine emissions with spatial and temporal information of landscape-scale explanatory factors in order to quantify aggregate N2O emissions for upland pasturesUniquely, we will gain improved understanding of the spatial and temporal interactions between grazing patterns, forage choice, urine composition, soil and climate factors and N2O fluxes in upland systems. Outputs from the project will be compared with IPCC Tier 1 and Tier 2 approaches for estimating N2O emissions from livestock grazing in the UK and provide the basis for robust and scientifically defensible alterations to standard inventory approaches, if required, along with inputs to carbon footprinting and to the spatial targeting of mitigation practices.