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

该项目的目的是提高对放牧行为、饲料选择、尿液成分和土壤条件之间的时空相互作用的理解，并利用所获得的见解来提高对英国半改良和未改良高地放牧牧场的氧化亚氮（N2O）排放估计的准确性。这一点非常重要，因为：(1)尿斑是N2O的重要来源；大约19%的N2O总损失来自农业，以及(2)来自旱地系统的N2O损失高度不确定。目前估算尿斑排放的方法忽略了牲畜日粮、土壤类型、土壤理化性质和气候对N2O通量的影响。例如，尿N含量随蛋白质摄入量的变化而变化，尿液中的代谢产物（已知影响N2O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，饮食选择在两个系统中都起作用。因此，将尿液成分与动物运动和饮食选择联系起来是很重要的。高原土壤受凉爽、潮湿气候和地形的影响，以高碳含量和低pH值的泥炭和灰壤为主。这些因素也将对N2O通量率施加系统控制，这可能会在尿液沉积后加剧。此外，不同高原地区的植被影响了放养密度和由此产生的尿斑重叠的可能性，导致高氮负荷率地区的N2O排放不成比例。这些地区的土壤可能因牲畜踩踏而变得密实，减少了充满空气的孔隙空间，增加了厌氧性，并通过反硝化增强了N2O损失的条件。因此，有必要建立尿液成分（放牧偏好的结果）、土壤类型、土壤理化性质（可能受到地形对水文的影响）和气候之间的关系，以便更好地估算N2O通量、排放因子和畜牧生产的碳足迹。我们将通过以下方式解决这些知识差距：i)利用高分辨率遥感成像，对控制N2O通量的“静态”因素，即地形、土壤类型、植被类型和土壤压实度进行精细制图；ii)对控制N2O通量的“流动”因素进行制图，即利用GPS项圈测量这两个草地系统中的牲畜运动和放牧模式；ii)收集放牧优势植被类型绵羊的尿液，并将尿液成分与饲粮偏好联系起来；v)测量在典型植被类型下将收集的尿液施用于土壤后的N2O通量；并计算12个月期间尿液直接N2O排放因子)进行对照重复实验，以探索控制对比现场土壤N2O通量的因素(例如改变尿液成分；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与景观尺度解释因子的时空信息相结合，以量化高原牧场的N2O总排放量。土壤和气候因子与N2O通量。该项目的产出将与IPCC估计英国牲畜放牧产生的一氧化二氮排放量的第一级和第二级方法进行比较，并为必要时对标准清单方法进行强有力的、科学上站得住的修改提供基础，同时为碳足迹和减缓做法的空间目标提供投入。

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 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.