Department of Forest Resources and Environmental Conservation
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Browsing Department of Forest Resources and Environmental Conservation by Subject "04 Earth Sciences"
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- Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data-model comparisonCheng, Susan J.; Hess, Peter G.; Wieder, William R.; Thomas, R. Quinn; Nadelhoffer, Knute J.; Vira, Julius; Lombardozzi, Danica L.; Gundersen, Per; Fernandez, Ivan J.; Schleppi, Patrick; Gruselle, Marie-Cecile; Moldan, Filip; Goodale, Christine L. (Copernicus, 2019-07-16)To accurately capture the impacts of nitrogen (N) on the land carbon (C) sink in Earth system models, model responses to both N limitation and ecosystem N additions (e.g., from atmospheric N deposition and fertilizer) need to be evaluated. The response of the land C sink to N additions depends on the fate of these additions: that is, how much of the added N is lost from the ecosystem through N loss pathways or recovered and used to increase C storage in plants and soils. Here, we evaluate the C-N dynamics of the latest version of a global land model, the Community Land Model version 5 (CLM5), and how they vary when ecosystems have large N inputs and losses (i.e., an open N cycle) or small N inputs and losses (i.e., a closed N cycle). This comparison allows us to identify potential improvements to CLM5 that would apply to simulated N cycles along the open-to-closed spectrum. We also compare the short-(< 3 years) and longerterm (5-17 years) N fates in CLM5 against observations from 13 long-term 15N tracer addition experiments at eight temperate forest sites. Simulations using both open and closed N cycles overestimated plant N recovery following N additions. In particular, the model configuration with a closed N cycle simulated that plants acquired more than twice the amount of added N recovered in 15N tracer studies on short timescales (CLM5: 46 ± 12 %; observations: 18 ± 12 %; mean across sites ±1 standard deviation) and almost twice as much on longer timescales (CLM5: 23±6 %; observations: 13±5 %). Soil N recoveries in simulations with closed N cycles were closer to observations in the short term (CLM5: 40 ± 10 %; observations: 54±22 %) but smaller than observations in the long term (CLM5: 59±15 %; observations: 69±18 %). Simulations with open N cycles estimated similar patterns in plant and soil N recovery, except that soil N recovery was also smaller than observations in the short term. In both open and closed sets of simulations, soil N recoveries in CLM5 occurred from the cycling of N through plants rather than through direct immobilization in the soil, as is often indicated by tracer studies. Although CLM5 greatly overestimated plant N recovery, the simulated increase in C stocks to recovered N was not much larger than estimated by observations, largely because the model's assumed C:N ratio for wood was nearly half that suggested by measurements at the field sites. Overall, results suggest that simulating accu rate ecosystem responses to changes in N additions requires increasing soil competition for N relative to plants and examining model assumptions of C V N stoichiometry, which should also improve model estimates of other terrestrial C-N processes and interactions.
- Effects of Large Wood on Floodplain Connectivity in a Headwater Mid-Atlantic StreamKeys, Tyler A.; Governer, Heather; Jones, C. Nathan; Hession, W. Cully; Hester, Erich T.; Scott, Durelle T. (2018-05-08)Large wood (LW) plays an essential role in aquatic ecosystem health and function. Traditionally, LW has been removed from streams to minimize localized flooding and increase conveyance efficiency. More recently, LW is often added to streams as a component of stream and river restoration activities. While much research has focused on the role of LW in habitat provisioning, geomorphic stability, and hydraulics at low to medium flows, we know little about the role of LW during storm events. To address this question, we investigated the role of LW on floodplain connectivity along a headwater stream in the Mid-Atlantic region of the United States. Specifically, we conducted two artificial floods, one with and one without LW, and then utilized field measurements in conjunction with hydrodynamic modeling to quantify floodplain connectivity during the experimental floods and to characterize potential management variables for optimized restoration activities. Experimental observations show that the addition of LW increased maximum floodplain inundation extent by 34%, increased floodplain inundation depth by 33%, and decreased maximum thalweg velocity by 10%. Model results demonstrated that different placement of LW along the reach has the potential to increase floodplain flow by up to 40%, with highest flooding potential at cross sections with high longitudinal velocity and shallow depth. Additionally, model simulations show that the effects of LW on floodplain discharge decrease as storm recurrence interval increases, with no measurable impact at a recurrence interval of more than 25 years.
- Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experimentsThomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; González-Benecke, Carlos; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O. (Copernicus, 2017-07-26)Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6ĝ€ × ĝ€105ĝ€km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.