Data set status is ongoing, which indicates that data is still being collected
Mesquite litter mass loss from decomposition associated with soil-litter mixing.
Decomposition models typically under-predict decomposition relative to observed rates in drylands. This discrepancy indicates a significant gap in our mechanistic understanding of carbon and nutrient cycling in these systems. Recent research suggests that certain drivers of decomposition that are often not explicitly incorporated into models (e.g., photodegradation and soil-litter mixing; SLM) may be important in drylands, and their exclusion may, in part, be responsible for model under-predictions. To assess the role of SLM, litterbags were deployed in the Chihuahuan Desert and interrelationships between vegetation structure, SLM, and rates of decomposition were quantified. Vegetation structure was manipulated to simulate losses of grass cover from livestock grazing and shrub encroachment. I hypothesized that reductions in grass cover would promote SLM and accelerate mass loss by improving conditions for microbial decomposition.
For more see: Hewins, D. B., S. R. Archer, G. S. Okin, R. L. McCulley, and H. L. Throop. 2013. Soil-litter mixing accelerates decomposition in a Chihuahuan Desert grassland. Ecosystems 16:183-195
The effect of vegetation structure on soil-litter mixing (SLM) and decomposition was explicitly tested in a litterbag experiment on a Chihuahuan Desert grassland site where vegetation cover was manipulated to simulate the progressive loss of grass cover accompanying livestock grazing and woody plant encroachment. We hypothesized that (i) reductions in grass cover would destabilize soi
The effect of vegetation structure on soil-litter mixing (SLM) and decomposition was explicitly tested in a litterbag experiment on a Chihuahuan Desert grassland site where vegetation cover was manipulated to simulate the progressive loss of grass cover accompanying livestock grazing and woody plant encroachment. We hypothesized that (i) reductions in grass cover would destabilize soils and promote SLM, and (ii) that SLM would enhance microbial abundance and alter microbial community composition in ways that accelerate decomposition. To test our hypotheses, we quantified mass loss, and chemistry of litter incubated on sites with experimental reductions in grass cover (0 to 100% removals) over a 12-month period. This dataset is of the percent carbon, percent nitrogen, and the carbon to nitrogen ratio.
The goal of this sampling effort is to describe the vegetation response to treatments. Data were collected following the line-point intercept method (Herrick et al.
2009). Although the original LPI data set was in multivariate form with separate columns for canopy layers and soil surface, this data set has been transposed into vertical form, implementing a “layer” variable, so that all species and soil surface codes appear in one column. Within each exclosure, 4837 points were sampled with the following exceptions:
Precipitation at 1 minute intervals for rain gauges 2-5 with R1 excluded due to periods of interruption. Spatially averaged rainfall over the watershed is calculated in this dataset based on relative coverage of each rain gauge determined from a Theissen polygon map.
This files presents all of the flux data post-EdiRe processing at 30 minute resolution. Included in this file is: Ux = Mean wind speed in the x-direction, Uy = mean wind speed in the y-direction, Uz = mean wind speed in the z-direction, Co2 = CO2 atmospheric concentrations, H2O = Water atmospheric concentrations, Press = barometric pressure, Air Temp = atmospheric temperature, wind speed = mea
n wind speed towards 216 degrees from north, H Flux = sensible heat flux, LE Flux = latent heat flux, C Flux = carbon flux.
Distance of crust surface to a crossbar set into the soil. Three "torvane" measurements that measure the torque needed to break the crust is also recorded. These measurements are made monthly near each of three monitoring towers (East, Middle, West) on the Scrape Site.