Predicting Forest N Dynamics Using Ecosystem-Scale 15-N Tracers

9408794 Nadelhoffer该项目的目标是测试和改进森林养分循环的计算机模型，通过整合正在进行的研究信息，在缅因州和马萨诸塞州森林使用天然存在的，非放射性同位素氮（15 N）作为示踪剂。 这些15 N示踪剂研究是独特的，因为它们采用大规模的示踪剂-无论是在大型地块与完整的，成熟的树木，或在整个森林流域（10公顷）。 我们在生态系统尺度上使用15 N示踪剂，使我们能够测量不同的植被（如树叶，木材，树种）和土壤（矿物土壤，森林地面，凋落物）池作为“汇”人为N输入到森林的重要性。 作为这些实验的结果，15 N的分布在我们的森林样地和实验集水区现在显着不同的15 N分布在天然林。 随着氮在这些森林中继续循环，即使没有额外的15 N加入，15 N示踪剂也将继续重新分布。 这为测试和改进森林生态系统的模拟模型提供了一个独特的机会，这些模型被用来预测森林对气候变化和慢性大气氮沉降的反应，这种反应现在发生在北方半球工业化地区的顺风处。 利用我们的大规模示踪剂研究获得的信息改进这些模型，将使我们更好地了解养分循环、森林生长和生态系统排水水质之间的相互作用，并更好地预测森林生态系统对气候和空气质量变化的反应。

9408794 Nadelhoffer The goal of this project is to test and improve computer models of forest nutrient cycles by incorporating information from on-going studies in Maine and Massachusetts forests using a naturally occurring, non-radioactive isotope of nitrogen (15N) as a tracer. These 15N tracer studies are unique in that they employ tracers at large scales--either on large plots with intact, mature trees, or in entire forested watersheds (10 hectares). Our use of 15N tracers at ecosystem scales has allowed us to measure the importance's of different vegetation (e.g. leaves, wood, tree species) and soil (mineral soil, forest floor, litter) pools as "sink" for anthropogenic N inputs to forest. As a result of these experiments, the distributions of 15N in our forest plots and experimental catchment now differ markedly from 15N distributions in natural forest. As nitrogen continues to cycle within these forests, the 15N tracers will continue to be redistributed even though no additional 15N will be added. This poses a unique opportunity to test and refine simulation models of forest ecosystems that are being used to predict responses of forests to a changing climate and chronic atmospheric N deposition that is now occurring downwind of industrialized regions of the northern hemisphere. Improving these models using information derived from our large-scale tracer studies will lead to a better understanding of the interactions between nutrient cycles, forest growth and ecosystem drainage water quality and to better predictions of forest ecosystem responses to changes in climate and air quality.