Grazing behaviour, urine composition and soil properties are key drivers of nitrous oxide emissions from livestock urine in the uplands (Uplands-N2O)

该项目的目的是更好地理解放牧行为、牧草选择、尿液成分和土壤条件之间的时空相互作用，并利用所获得的见解来提高对英国半改良和未改良旱地牧场一氧化二氮(N2O)排放量估计的准确性。这一点非常重要，因为(1)尿斑是N2O的重要来源；约占农业N2O总损失的19%，(2)旱地系统N2O损失高度不确定。目前估计尿斑排放量的方法忽略了牲畜饲料、土壤类型、土壤理化性质和气候对N2O通量的影响。例如，尿氮含量随着蛋白质摄入量的不同而变化，尿液中的代谢产物(已知会影响N2O的产生)受牲畜吃什么的影响。不同高地地区的植被差异很大，两个系统都有饮食选择。因此，将尿液成分与动物活动和食物选择联系起来是很重要的。高地土壤主要是泥炭和泥炭，受凉爽、潮湿的气候和地形的影响，碳含量高，pH低。这些因素还将对N2O通量的速率施加系统控制，而N2O通量在尿液沉积后可能会加剧。此外，不同高地地区的植被影响着种群密度和随之而来的尿斑重叠的可能性，导致在氮负荷率高的地区产生不成比例的N2O排放。这些地区的土壤会因为牲畜的践踏而变得紧实，减少了充满空气的孔隙空间，增加了厌氧性，并通过反硝化作用增加了N2O损失的条件。因此，必须建立尿液成分(放牧偏好的结果)、土壤类型、土壤物理化学性质(可能受地形对水文的影响)和气候之间的关系，以产生改进的N2O通量估计、排放因子和畜牧业生产的碳足迹。我们将通过以下组合来解决这些知识差距：i)使用高分辨率遥感成像在对比高地上绘制控制N2O通量的‘静态’因素图，即地形、土壤类型、植被类型和土壤压实；i)绘制控制N2O通量的‘移动’因子图；即使用GPS项圈在这两个草原系统中测量牲畜移动和放牧模式，并观察尿液事件。ii)从绵羊放牧的主要植被类型收集尿液，并将尿液成分与食物偏好联系起来。)测量在典型植被类型下将收集的尿液应用到土壤中后的N2O通量，并计算12个月期间的稳健尿液直接N2O排放因子)进行受控重复实验，以探索控制来自对比场地土壤的N2O通量的因素(例如，尿液成分的变化，水分含量和压实程度)vi)开发一个新的模型框架来预测动物占有率的统计数据，并将预测的尿液排放量与景观尺度解释因素的时空信息相结合。为了唯一地量化旱地牧场的N2O总排放量，我们将更好地理解放牧模式、饲料选择、尿液成分、土壤和气候因素以及旱地系统N2O通量之间的时空相互作用。该项目的输出将与IPCC第一级和第二级方法进行比较，以估计英国牲畜放牧产生的N2O排放量，并为必要时对标准清单方法进行强有力的、具有科学依据的改变提供基础，以及对碳足迹和缓解做法的空间目标的投入。

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 pastures Uniquely, 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.