H.E. Epstein | USGS Science

USGS2012

Sinks for nitrogen inputs in terrestrial ecosystems: a meta-analysis of 15 N tracer field studies

Effects of anthropogenic nitrogen (N) deposition and the ability of terrestrial ecosystems to store carbon (C) depend in part on the amount of N retained in the system and its partitioning among plant and soil pools. We conducted a meta-analysis of studies at 48 sites across four continents that used enriched 15 N isotope tracers in order to synthesize information about total ecosystem N retention (i.e., total ecosystem 15 N recovery in plant and soil pools) across natural systems and N partitioning among ecosystem pools. The greatest recoveries of ecosystem 15 N tracer occurred in shrublands (mean, 89.5%) and wetlands (84.8%) followed by forests (74.9%) and grasslands (51.8%). In the short term (<1 week after 15 N tracer application), total ecosystem 15 N recovery was negatively correlated with fine-root and soil 15 N natural abundance, and organic soil C and N concentration but was positively correlated with mean annual temperature and mineral soil C:N. In the longer term (3–18 months after 15 N tracer application), total ecosystem 15 N retention was negatively correlated with foliar natural-abundance 15 N but was positively correlated with mineral soil C and N concentration and C: N, showing that plant and soil natural-abundance 15 N and soil C:N are good indicators of total ecosystem N retention. Foliar N concentration was not significantly related to ecosystem 15 N tracer recovery, suggesting that plant N status is not a good predictor of total ecosystem N retention. Because the largest ecosystem sinks for 15 N tracer were below ground in forests, shrublands, and grasslands, we conclude that growth enhancement and potential for increased C storage in aboveground biomass from atmospheric N deposition is likely to be modest in these ecosystems. Total ecosystem 15 N recovery decreased with N fertilization, with an apparent threshold fertilization rate of 46 kg N·ha -1 ·yr -1 above which most ecosystems showed net losses of applied 15 N tracer in response to N fertilizer addition.

Ecology↗

USGS2005

Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach

Aim: To understand drivers of vegetation type distribution and sensitivity to climate change. Location: Interior Alaska. Methods: A logistic regression model was developed that predicts the potential equilibrium distribution of four major vegetation types: tundra, deciduous forest, black spruce forest and white spruce forest based on elevation, aspect, slope, drainage type, fire interval, average growing season temperature and total growing season precipitation. The model was run in three consecutive steps. The hierarchical logistic regression model was used to evaluate how scenarios of changes in temperature, precipitation and fire interval may influence the distribution of the four major vegetation types found in this region. Results: At the first step, tundra was distinguished from forest, which was mostly driven by elevation, precipitation and south to north aspect. At the second step, forest was separated into deciduous and spruce forest, a distinction that was primarily driven by fire interval and elevation. At the third step, the identification of black vs. white spruce was driven mainly by fire interval and elevation. The model was verified for Interior Alaska, the region used to develop the model, where it predicted vegetation distribution among the steps with an accuracy of 60-83%. When the model was independently validated for north-west Canada, it predicted vegetation distribution among the steps with an accuracy of 53-85%. Black spruce remains the dominant vegetation type under all scenarios, potentially expanding most under warming coupled with increasing fire interval. White spruce is clearly limited by moisture once average growing season temperatures exceeded a critical limit (+2 ??C). Deciduous forests expand their range the most when any two of the following scenarios are combined: decreasing fire interval, warming and increasing precipitation. Tundra can be replaced by forest under warming but expands under precipitation increase. Main conclusion: The model analyses agree with current knowledge of the responses of vegetation types to climate change and provide further insight into drivers of vegetation change. ?? 2005 Blackwell Publishing Ltd.

Journal of Biogeography↗