流域人类活动净氮输入量的估算、不确定性及影响因素

人类活动使得大量的氮素进入流域生态系统,大量氮的盈余导致了一系列生态环境问题的出现。为了评估人类活动对流域生态系统的影响,Howarth等于1996年提出了人类活动净氮输入(NANI)的概念。综述了当前人类活动净氮输入的估算方法、不确定性及影响因素,并得到以下结论:导致NANI估算结果的不确定性原因主要有:内涵分歧、数据来源、尺度转换、估算方法的分歧。影响NANI的主要因素包括:各输入项、人口密度、土地利用组成;对于各输入项而言,化肥施用是最主要的氮素输入来源,占人类活动净氮输入总量的79.0%,其次为作物固氮,占17.6%,食品/饲料氮净输入量占-14.5%,大气沉降占15.7%;对于人口密度,NANI随着人口密度的增大而增大,当人口密度高于100人/km2,人口密度对NANI的影响趋于稳定,其他因素起主导作用。对于土地利用组成:NANI与森林面积比例成负相关,而与耕地面积比例成正相关。

Accounting methods, uncertainties and influential factors of net anthropogenic nitrogen input (NANI)

Nitrogen (N) enrichment in watershed ecosystems is an issue of global concern. In many estuaries and coastal marine environments, biologically available N limits primary production. Human activities strongly influence the N loads to watersheds in a number of different ways, for example through fertilizer application driven by increased agricultural activities, or through N deposition as the result of increased industrial and traffic emissions. The increased N inputs are often accompanied by corresponding increases in riverine exports of N. Therefore it''s important to understand the sources of human-induced N inputs within watershed ecosystems and their contributions to the riverine exports. In the past few decades, a watershed-scale nutrient accounting method-Net Anthropogenic Nitrogen Input (NANI), which was originally proposed by Howarth et al., has been used as a simple yet powerful approach to estimate major anthropogenic sources of N to terrestrial and aquatic ecosystems. NANI accounts for the fluxes of atmospheric N deposition, fertilizer N application, agricultural N fixation and net food and feed imports, each of which represents a potentially important source of N in watersheds. Across a wide range of watersheds, NANI has been shown to be a good predictor of riverine N exports, and its magnitudes have strong relationships with hydro-climatic conditions such as precipitation, discharge and temperature. Despite of that the NANI approach has been applied in numerous regions worldwide, its limitations are evident. Firstly, NANI varies widely in the definition and component composition, depending on the data availability and local conditions such as climate and human activities, which makes it somewhat difficult to compare the NANI in a national or global perspective. Secondly, the methodological differences could result in great uncertainties in NANI estimation. Accounting NANI without considering the sources and influential factors of the uncertainties may generate unexpected errors. Thus a full understanding of the uncertainties of NANI approach would help us more accurately assess the human-induced N inputs in watersheds. This paper presents an extensive review of the literature on the methods, uncertainties and influential factors in NANI accounting. The main conclusions are: 1) NANI approach generally consists of the sum of N inputs in fertilizer, biological fixation, and atmospheric NO_y deposition, minus the net N exported from the basin in food and feed products. 2) the uncertainties in NANI accounting are mainly caused by variations in NANI definition, data sources, scale conversions and calculation methodologies; 3) NANI is mainly influenced by three factors including input components, the population density and composition of land use types. As to the input components, fertilizer application is the largest source of N, accounting for 79.0% of NANI, followed by the biological nitrogen fixation (17.6%), the atmospheric deposition (15.7%) and the net import of human food and animal feed (-14.5%). As to the population density, our analysis suggests a possible threshold at population density of 100 per/km², before which NANI values increases with population density and after that NANI remains at stable level. As to the composition of land use types, NANI is correlated negatively with the proportions of forest but positively with the proportions of arable lands.