Plant species effects on soil nutrients and chemistry in arid ecological zones.

The presence of vegetation strongly influences ecosystem function by controlling the distribution and transformation of nutrients across the landscape. The magnitude of vegetation effects on soil chemistry is largely dependent on the plant species and the background soil chemical properties of the site, but has not been well quantified along vegetation transects in the Great Basin. We studied the effects of plant canopy cover on soil chemistry within five different ecological zones, subalpine, montane, pinyon-juniper, sage/Mojave transition, and desert shrub, in the Great Basin of Nevada all with similar underlying geology. Although plant species differed in their effects on soil chemistry, the desert shrubs Sarcobatus vermiculatus, Atriplex spp., Coleogyne ramosissima, and Larrea tridentata typically exerted the most influence on soil chemistry, especially amounts of K(+) and total nitrogen, beneath their canopies. However, the extent to which vegetation affected soil nutrient status in any given location was not only highly dependent on the species present, and presumably the nutrient requirements and cycling patterns of the plant species, but also on the background soil characteristics (e.g., parent material, weathering rates, leaching) where plant species occurred. The results of this study indicate that the presence or absence of a plant species, especially desert shrubs, could significantly alter soil chemistry and subsequently ecosystem biogeochemistry and function.

Do increased summer precipitation and N deposition alter fine root dynamics in a Mojave Desert ecosystem?

Climate change is expected to impact the amount and distribution of precipitation in the arid southwestern United States. In addition, nitrogen (N) deposition is increasing in these regions due to increased urbanization. Responses of belowground plant activity to increases in soil water content and N have shown inconsistent patterns between biomes. In arid lands, plant productivity is limited by water and N availability so it is expected that changes in these factors will affect fine root dynamics. The objectives of this study were to quantify the effects of increased summer precipitation and N deposition on fine root dynamics in a Mojave Desert ecosystem during a 2-year field experiment using minirhizotron measurements. Root length density, production, and mortality were measured in field plots in the Mojave Desert receiving three 25 mm summer rain events and/or 40 kg N ha(-1)  yr(-1) . Increased summer precipitation and N additions did not have an overall significant effect on any of the measured root parameters. However, differences in winter precipitation resulting from interannual variability in rainfall appeared to affect root parameters with root production and turnover increasing following a wet winter most likely due to stimulation of annual grasses. In addition, roots were distributed more deeply in the soil following the wet winter. Root length density was initially higher under canopies compared to canopy interspaces, but converged toward the end of the study. In addition, roots tended to be distributed more deeply into the soil in canopy interspace areas. Results from this study indicated that increased summer precipitation and N deposition in response to climate change and urbanization are not likely to affect fine root dynamics in these Mojave Desert ecosystems, despite studies showing aboveground plant physiological responses to these environmental perturbations. However, changes in the amount and possibly distribution of winter precipitation may affect fine root dynamics.

Concurrent and lagged impacts of an anomalously warm year on autotrophic and heterotrophic components of soil respiration: a deconvolution analysis.

*Partitioning soil respiration into autotrophic (R(A)) and heterotrophic (R(H)) components is critical for understanding their differential responses to climate warming. *Here, we used a deconvolution analysis to partition soil respiration in a pulse warming experiment. We first conducted a sensitivity analysis to determine which parameters can be identified by soil respiration data. A Markov chain Monte Carlo technique was then used to optimize those identifiable parameters in a terrestrial ecosystem model. Finally, the optimized parameters were employed to quantify R(A) and R(H) in a forward analysis. *Our results displayed that more than one-half of parameters were constrained by daily soil respiration data. The optimized model simulation showed that warming stimulated R(H) and had little effect on R(A) in the first 2 months, but decreased both R(H) and R(A) during the remainder of the treatment and post-treatment years. Clipping of above-ground biomass stimulated the warming effect on R(H) but not on R(A). Overall, warming decreased R(A) and R(H) significantly, by 28.9% and 24.9%, respectively, during the treatment year and by 27.3% and 33.3%, respectively, during the post-treatment year, largely as a result of decreased canopy greenness and biomass. *Lagged effects of climate anomalies on soil respiration and its components are important in assessing terrestrial carbon cycle feedbacks to climate warming.

Prolonged suppression of ecosystem carbon dioxide uptake after an anomalously warm year.

Terrestrial ecosystems control carbon dioxide fluxes to and from the atmosphere through photosynthesis and respiration, a balance between net primary productivity and heterotrophic respiration, that determines whether an ecosystem is sequestering carbon or releasing it to the atmosphere. Global and site-specific data sets have demonstrated that climate and climate variability influence biogeochemical processes that determine net ecosystem carbon dioxide exchange (NEE) at multiple timescales. Experimental data necessary to quantify impacts of a single climate variable, such as temperature anomalies, on NEE and carbon sequestration of ecosystems at interannual timescales have been lacking. This derives from an inability of field studies to avoid the confounding effects of natural intra-annual and interannual variability in temperature and precipitation. Here we present results from a four-year study using replicate 12,000-kg intact tallgrass prairie monoliths located in four 184-m(3) enclosed lysimeters. We exposed 6 of 12 monoliths to an anomalously warm year in the second year of the study and continuously quantified rates of ecosystem processes, including NEE. We find that warming decreases NEE in both the extreme year and the following year by inducing drought that suppresses net primary productivity in the extreme year and by stimulating heterotrophic respiration of soil biota in the subsequent year. Our data indicate that two years are required for NEE in the previously warmed experimental ecosystems to recover to levels measured in the control ecosystems. This time lag caused net ecosystem carbon sequestration in previously warmed ecosystems to be decreased threefold over the study period, compared with control ecosystems. Our findings suggest that more frequent anomalously warm years, a possible consequence of increasing anthropogenic carbon dioxide levels, may lead to a sustained decrease in carbon dioxide uptake by terrestrial ecosystems.

Atmospheric mercury exchange with a tallgrass prairie ecosystem housed in mesocosms.

This study focused on characterizing air-surface mercury Hg exchange for individual surfaces (soil, litter-covered soil and plant shoots) and ecosystem-level flux associated with tallgrass prairie ecosystems housed inside large mesocosms over three years. The major objectives of this project were to determine if individual surface fluxes could be combined to predict ecosystem-level exchange and if this low-Hg containing ecosystem was a net source or sink for atmospheric Hg. Data collected in the field were used to validate fluxes obtained in the mesocosm setting. Because of the controlled experimental design and ease of access to the mesocosms, data collected allowed for assessment of factors controlling flux and comparison of models developed for soil Hg flux versus environmental conditions at different temporal resolution (hourly, daily and monthly). Evaluation of hourly data showed that relationships between soil Hg flux and environmental conditions changed over time, and that there were interactions between parameters controlling exchange. Data analyses demonstrated that to estimate soil flux over broad temporal scales (e.g. annual flux) coarse-resolution data (monthly averages) are needed. Plant foliage was a sink for atmospheric Hg with uptake influenced by plant functional type and age. Individual system component fluxes (bare soil and plant) could not be directly combined to predict the measured whole system flux (soil, litter and plant). Emissions of Hg from vegetated and litter-covered soil were lower than fluxes from adjacent bare soil and the difference between the two was seasonally dependent and greatest when canopy coverage was greatest. Thus, an index of plant canopy development (canopy greenness) was used to model Hg flux from vegetated soil. Accounting for ecosystem Hg inputs (precipitation, direct plant uptake of atmospheric Hg) and modeled net exchange between litter-and-plant covered soils, the tallgrass prairie was found to be a net annual sink of atmospheric Hg.