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William J. Parton

Publications and source records attributed to William J. Parton.

6 recordsLinked to original sources
USGS2025

Grass-Cast Southwest: A seasonal rangeland productivity forecast for the southwestern United States

Here, we present a first assessment of the US Department of Agriculture’s (USDA) “Grass-Cast Southwest,” which is a forecasting tool for rangeland aboveground net primary productivity (ANPP) for the southwest region of the United States. Our results show that ANPP forecasts in early April were relatively close to the observation-based ANPP estimates in late May for all years evaluated ( R = 0.6–0.9). The relatively high predictability of spring rangeland productivity in this region is likely because it is strongly driven by antecedent winter/early spring precipitation. Conversely, the first summer forecasts produced in June did not consistently predict the final observation-based ANPP estimates in late August ( R = −0.5–0.7), likely because summer rangeland productivity in this region is highly dependent on variable, less predictable precipitation from the North American Monsoon (NAM). Antecedent El Niño Southern Oscillation (ENSO) indices could be used to improve Grass-Cast Southwest performance in both the spring and summer. The ENSO JFM (January–March) index was significantly positively correlated with rangeland productivity during the spring season, whereas ENSO MAM (March–May) was significantly negatively correlated with rangeland productivity during the summer season.

Arizona, New Mexico↗
USGS2014

Forest Ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles

Eddy covariance nighttime fluxes are uncertain due to potential measurement biases. Many studies report eddy covariance nighttime flux lower than flux from extrapolated chamber measurements, despite corrections for low turbulence. We compared eddy covariance and chamber estimates of ecosystem respiration at the GLEES Ameriflux site over seven growing seasons under high turbulence (summer night mean friction velocity (u*) = 0.7 m s −1 ), during which bark beetles killed or infested 85% of the aboveground respiring biomass. Chamber-based estimates of ecosystem respiration during the growth season, developed from foliage, wood and soil CO 2 efflux measurements, declined 35% after 85% of the forest basal area had been killed or impaired by bark beetles (from 7.1 ±0.22 μmol m −2 s −1 in 2005 to 4.6 ±0.16 μmol m −2 s −1 in 2011). Soil efflux remained at ~3.3 μmol m −2 s −1 throughout the mortality, while the loss of live wood and foliage and their respiration drove the decline of the chamber estimate. Eddy covariance estimates of fluxes at night remained constant over the same period, ~3.0 μmol m −2 s −1 for both 2005 (intact forest) and 2011 (85% basal area killed or impaired). Eddy covariance fluxes were lower than chamber estimates of ecosystem respiration (60% lower in 2005, and 32% in 2011), but the mean night estimates from the two techniques were correlated within a year (r 2 from 0.18-0.60). The difference between the two techniques was not the result of inadequate turbulence, because the results were robust to a u* filter of > 0.7 m s −1 . The decline in the average seasonal difference between the two techniques was strongly correlated with overstory leaf area (r 2 =0.92). The discrepancy between methods of respiration estimation should be resolved to have confidence in ecosystem carbon flux estimates.

Wyoming↗
USGS2009

DayCent-Chem simulations of ecological and biogeochemical processes of eight mountain ecosystems in the United States

Atmospheric deposition of nitrogen (N) and sulfur (S) cause complex responses in ecosystems, from fertilization to forest ecosystem decline, freshwater eutrophication to acidification, loss of soil base cations, and alterations of disturbance regimes. DayCent-Chem, an ecosystem simulation model that combines ecosystem nutrient cycling and plant dynamics with aqueous geochemical equilibrium calculations, was developed to address ecosystem responses to combined atmospheric N and S deposition. It is unique among geochemically-based models in its dynamic biological cycling of N and its daily timestep for investigating ecosystem and surface water chemical response to episodic events. The model was applied to eight mountainous watersheds in the United States. The sites represent a gradient of N deposition across locales, from relatively pristine to N-saturated, and a variety of ecosystem types and climates. Overall, the model performed best in predicting stream chemistry for snowmelt-dominated sites. It was more difficult to predict daily stream chemistry for watersheds with deep soils, high amounts of atmospheric deposition, and a large degree of spatial heterogeneity. DayCent-Chem did well in representing plant and soil carbon and nitrogen pools and fluxes. Modeled stream nitrate (NO 3 - ) and ammonium (NH 4 + ) concentrations compared well with measurements at all sites, with few exceptions. Simulated daily stream sulfate (SO 4 2- ) concentrations compared well to measured values for sites where SO 4 2- deposition has been low and where SO 4 2- adsorption/desorption reactions did not seem to be important. The concentrations of base cations and silica in streams are highly dependent on the geochemistry and weathering rates of minerals in each catchment, yet these were rarely, if ever, known. Thus, DayCent-Chem could not accurately predict weathering products for some catchments. Additionally, few data were available for exchangeable soil cations or the magnitude of base cation deposition as a result of dry and fog inputs. The uncertainties related to weathering reactions, deposition, soil cation exchange capacity, and groundwater contributions influenced how well the simulated acid neutralizing capacity (ANC) and pH estimates compared to observed values. Daily discharge was well represented by the model for most sites. The chapters of this report describe the parameterization for each site and summarize model results for ecosystem variables, stream discharge, and stream chemistry. This intersite comparison exercise provided insight about important and possibly not well understood processes.

Scientific Investigations Report↗
USGS1997

Land cover characterization and land surface parameterization research

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Ecological Applications↗
USGS1994

Analysis of nitrogen saturation potential in Rocky Mountain tundra and forest: implications for aquatic systems

We employed grass and forest versions of the CENTURY model under a range of N deposition values (0.02–1.60 g N m −2 y −1 ) to explore the possibility that high observed lake and stream N was due to terrestrial N saturation of alpine tundra and subalpine forest in Loch Vale Watershed, Rocky Mountain National Park, Colorado. Model results suggest that N is limiting to subalpine forest productivity, but that excess leachate from alpine tundra is sufficient to account for the current observed stream N. Tundra leachate, combined with N leached from exposed rock surfaces, produce high N loads in aquatic ecosystems above treeline in the Colorado Front Range. A combination of terrestrial leaching, large N inputs from snowmelt, high watershed gradients, rapid hydrologic flushing and lake turnover times, and possibly other nutrient limitations of aquatic organisms constrain high elevation lakes and streams from assimilating even small increases in atmospheric N. CENTURY model simulations further suggest that, while increased N deposition will worsen the situation, nitrogen saturation is an ongoing phenomenon.

Biogeochemistry↗