• Energy Research

Previous research on the effects of tree species on soil processes has focused primarily on the role of leaf litter inputs. We quantified the extent to which arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) tree species influence soil microbial activity and nutrient availability through rhizosphere effects. Rhizosphere soil, bulk soil, and fine roots were collected from 12 monospecifc plots (six AM and six ECM tree species) planted on a common soil at the Turkey Hill Plantations in Dryden, New York. Rhizosphere effects were estimated by the percentage difference between rhizosphere and bulk soil samples for several assays. Rhizosphere effects on soil microbes and their activities were significant for ECM species but in only a few cases for AM species. In AM tree species, microbial biomass, net N mineralization, and phosphatase enzyme activity in the rhizosphere were 10-12% greater than in bulk soil. In ECM tree species, rhizosphere effects for microbial biomass, C mineralization rates, net N mineralization, and phosphatase activity were 25-30% greater than bulk soil, and significantly greater than AM rhizosphere effects. The magnitude of rhizosphere effects was negatively correlated with the degree of mycorrhizal colonization in AM tree species (r = -0.83) and with fine root biomass (r = -0.88) in ECM tree species, suggesting that different factors influence rhizosphere effects in tree species forming different mycorrhizal associations. Rhizosphere effects on net N mineralization and phosphatase activity were also much greater in soils with pH < 4.3 for both AM and ECM tree species, suggesting that soil pH and its relation to nutrient availability may also influence the magnitude of rhizosphere effects. Our results support the idea that tree roots stimulate nutrient availability in the rhizosphere, and that systematic differences between AM and ECM may result in distinctive rhizosphere effects for C, N, and P cycling between AM and ECM tree species.

AbstractGlobally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Fertilizer-induced reductions in CO(2) flux from soil ((F)CO(2)) in forests have previously been attributed to decreased carbon allocation to roots, and decreased decomposition as a result of nitrogen suppression of fungal activity. Here, we present evidence that decreased microbial respiration in the rhizosphere may also contribute to (F)CO(2) reductions in fertilized forest soils. Fertilization reduced (F)CO(2) by 16-19% in 65-yr-old plantations of northern red oak (Quercus rubra) and sugar maple (Acer saccharum), and in a natural 85-yr-old yellow birch (Betula allegheniensis) stand. In oak plots, fertilization had no effects on fine root biomass but reduced mycorrhizal colonization by 18% and microbial respiration by 43%. In maple plots, fertilization reduced root biomass, mycorrhizal colonization and microbial respiration by 22, 16 and 46%, respectively. In birch plots, fertilization reduced microbial respiration by 36%, but had variable effects on root biomass and mycorrhizal colonization. In plots of all three species, fertilization effects on microbial respiration were greater in rhizosphere than in bulk soil, possibly as a result of decreased rhizosphere carbon flux from these species in fertile soils. Because rhizosphere processes may influence nutrient availability and carbon storage in forest ecosystems, future research is needed to better quantify rhizo-microbial contributions to (F)CO(2).

AbstractProjected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi‐arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests ofENA, representing 24 species and 346 stands, to determine the broad‐scale drivers of drought sensitivity for the dominant trees inENA. Here we show that two factors—the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration;PET)—are stronger drivers of drought sensitivity than soil and stand characteristics. Drought‐induced reductions in tree growth were greatest when the droughts occurred during early‐season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highestPET). Further, mean species trait values (rooting depth and ψ50) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early‐seasonPETmay exacerbate these effects, and potentially offset gains in C uptake and storage inENAowing to other global change factors.

AbstractThe complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the fate and persistence of C under future climate scenarios. However, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding. This is necessary to capture the full value of a proxy in model parameters and in model outcomes. Here, we provide specific examples of proxy variables that could improve decision‐making, and modeling skill, while also encouraging continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil C cycling: metabolic quotient, clay content, and physical fractionation. We also consider how emerging data types, such as genome‐sequence data, can serve as proxies for microbial community activities. By examining some broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.

Abstract. Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha–1) at spatial scales ranging from 5 to 250 m (0.025–6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20–400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.