Centennial-scale reductions in nitrogen availability in temperate forests of the United States.

Forests cover 30% of the terrestrial Earth surface and are a major component of the global carbon (C) cycle. Humans have doubled the amount of global reactive nitrogen (N), increasing deposition of N onto forests worldwide. However, other global changes-especially climate change and elevated atmospheric carbon dioxide concentrations-are increasing demand for N, the element limiting primary productivity in temperate forests, which could be reducing N availability. To determine the long-term, integrated effects of global changes on forest N cycling, we measured stable N isotopes in wood, a proxy for N supply relative to demand, on large spatial and temporal scales across the continental U.S.A. Here, we show that forest N availability has generally declined across much of the U.S. since at least 1850 C.E. with cool, wet forests demonstrating the greatest declines. Across sites, recent trajectories of N availability were independent of recent atmospheric N deposition rates, implying a minor role for modern N deposition on the trajectory of N status of North American forests. Our results demonstrate that current trends of global changes are likely to be consistent with forest oligotrophication into the foreseeable future, further constraining forest C fixation and potentially storage.

Mercury distribution across 14 U.S. Forests. Part I: spatial patterns of concentrations in biomass, litter, and soils.

Results from a systematic investigation of mercury (Hg) concentrations across 14 forest sites in the United States show highest concentrations in litter layers, strongly enriched in Hg compared to aboveground tissues and indicative of substantial postdepositional sorption of Hg. Soil Hg concentrations were lower than in litter, with highest concentrations in surface soils. Aboveground tissues showed no detectable spatial patterns, likely due to 17 different tree species present across sites. Litter and soil Hg concentrations positively correlated with carbon (C), latitude, precipitation, and clay (in soil), which together explained up to 94% of concentration variability. We observed strong latitudinal increases in Hg in soils and litter, in contrast to inverse latitudinal gradients of atmospheric deposition measures. Soil and litter Hg concentrations were closely linked to C contents, consistent with well-known associations between organic matter and Hg, and we propose that C also shapes distribution of Hg in forests at continental scales. The consistent link between C and Hg distribution may reflect a long-term legacy whereby old, C-rich soil and litter layers sequester atmospheric Hg depositions over long time periods. Based on a multiregression model, we present a distribution map of Hg concentrations in surface soils of the United States.

Quantifying change in distributions: a new departure index that detects, measures and describes change in distributions from population structures, size-classes and other ordered data.

Many statistics are available to compare distributions. Some are limited to nominal data while others, such as skew, Kullback-Leibler, Kolmogorov-Smirnov and the Gini coefficient, are useful for providing information about ordered distributions. While many of these tests are useful for determining properties of data in histograms, there has not been a test until now that allows for the detection of differences between distributions, describes the difference and is sensitive to the location of the departures. Such a test could be critical for comparing pre-and post-event distributions, such as a change in the distribution of biomass due to fire, for example, or for comparing data from different locations, such as soil size distributions, and even for evaluating economic disparity or examining differences in age demographics. We present a new statistic, a departure index, which allows a test distribution to be compared with any reference distribution. The resulting index contains information about the location, magnitude and direction of departure from the reference distribution to the test distribution. The departure index in turn provides a standardized response range that allows for a comparison of results from different analyses. A case study of actual fire data demonstrates the sensitivity and range of the test.