What is the most ecologically-meaningful metric of nitrogen deposition?
What is the most ecologically-meaningful metric of nitrogen deposition?
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DOI：
10.1016/j.envpol.2019.01.059
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发表时间：
2019-04
影响因子：
8.9
通讯作者：
R. Payne;C. Campbell;A. Britton;R. Mitchell;R. Pakeman;L. Jones;L. Ross;C. Stevens;C. Field;S. Caporn;J. Carroll;J. Edmondson;E. Carnell;S. Tomlinson;A. Dore;N. Dise;U. Dragosits
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文献类型：
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作者：
R. Payne;C. Campbell;A. Britton;R. Mitchell;R. Pakeman;L. Jones;L. Ross;C. Stevens;C. Field;S. Caporn;J. Carroll;J. Edmondson;E. Carnell;S. Tomlinson;A. Dore;N. Dise;U. Dragosits
氮沉降对全球陆地生态系统构成严重威胁，管理这一威胁是空气污染科学和政策的一个重要重点。为了理解和管理氮沉降的影响，我们需要准确反映氮沉降对环境的压力，并对氮沉降及其影响随时间的变化做出反应的指标。在英国，通常使用的度量标准是1-3年的总氮沉降量，尽管有证据表明，氮在许多生态系统中积累，低水平暴露的影响可能需要相当长的时间才能形成。N沉降模型的改进现在允许开发包含长期污染历史以及当前暴露的度量。在这里，我们测试了替代氮沉降指标解释英国半自然栖息地植被组成变异的潜力。我们收集了来自1683个站点的5479个样方的36个独立数据集，代表48,332条发生记录，并使用冗余分析来检验基于国家污染物沉积模型的33个备选N指标的解释力。即使考虑到植被变化的其他大规模驱动因素，我们也发现了令人信服的证据，证明氮沉积对数据集和栖息地的影响。包含长期N沉降轨迹的指标一致地解释了比1-3 年 N沉降更大的成分差异。不同生境和相似指标之间的结果存在相当大的差异，但总的来说，我们建议用30年的累积沉积移动窗口来代表对植物群落的影响，以便在科学、政策和管理中应用。
Nitrogen (N) deposition poses a severe risk to global terrestrial ecosystems, and managing this threat is an important focus for air pollution science and policy. To understand and manage the impacts of N deposition, we need metrics which accurately reflect N deposition pressure on the environment, and are responsive to changes in both N deposition and its impacts over time. In the UK, the metric typically used is a measure of total N deposition over 1–3 years, despite evidence that N accumulates in many ecosystems and impacts from low-level exposure can take considerable time to develop. Improvements in N deposition modelling now allow the development of metrics which incorporate the long-term history of pollution, as well as current exposure. Here we test the potential of alternative N deposition metrics to explain vegetation compositional variability in British semi-natural habitats. We assembled 36 individual datasets representing 48,332 occurrence records in 5479 quadrats from 1683 sites, and used redundancy analyses to test the explanatory power of 33 alternative N metrics based on national pollutant deposition models. We find convincing evidence for N deposition impacts across datasets and habitats, even when accounting for other large-scale drivers of vegetation change. Metrics that incorporate long-term N deposition trajectories consistently explain greater compositional variance than 1–3 year N deposition. There is considerable variability in results across habitats and between similar metrics, but overall we propose that a thirty-year moving window of cumulative deposition is optimal to represent impacts on plant communities for application in science, policy and management.