Department of Forest Resources and Environmental Conservation

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Browsing Department of Forest Resources and Environmental Conservation by Subject "06 Biological Sciences"

Now showing 1 - 6 of 6
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    Assessing patterns of oak regeneration and C storage in relation to restoration-focused management, historical land use, and potential trade-offs
    Carter, David R.; Fahey, Robert T.; Dreisilker, Kurt; Bialecki, Margaret B.; Bowles, Marlin (2015-01-29)
    Restoration of composition, structure, and function in oak dominated ecosystems is the focus of management in temperate forests around the world. Land managers focused on oak ecosystem restoration are challenged by the legacy effects of complex land-use histories, urbanization, climate change, and potential stakeholder response to management. Trade-offs may exist between managing forests for climate mitigation (e.g., maximizing C storage or sequestration) and promoting shade-intolerant species historically associated with frequent or high-severity disturbances. This study assessed the potentially conflicting goals of sustained live biomass accrual and increased oak regeneration in the East Woods Natural Area at The Morton Arboretum in Lisle, IL, USA. We evaluated how biomass trends and oak regeneration were related to management regimes, land-use history, current stand structure and composition, and topoedaphic factors. Our results indicated no significant trade-off between sustained live biomass accrual and oak regeneration. Live biomass was increasing across the landscape (biomass increment averaged 18,186 kg ha-1 yr-1) and was not strongly related to differences in management or land-use history. Oak regeneration was rare, especially beyond the seedling stage (~226 seedlings and 9 saplings ha-11) and was also not strongly related to recent management. Our results indicate that even 20+ years of annual prescribed burning combined with understory thinning has failed to produce the open canopy conditions and high light availability that are necessary for successful oak recruitment. The absence of any trade-offs between biomass accrual and oak regeneration may, therefore, be largely related to the ineffectiveness of current management for promoting oak regeneration. More intensive management utilizing canopy manipulations could produce greater trade-offs, but is likely necessary to establish and release oak regeneration.
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    Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data-model comparison
    Cheng, 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.
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    Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model
    Kyker-Snowman, Emily; Lombardozzi, Danica L.; Bonan, Gordon B.; Cheng, Susan J.; Dukes, Jeffrey S.; Frey, Serita D.; Jacobs, Elin M.; McNellis, Risa; Rady, Joshua M.; Smith, Nicholas G.; Thomas, R. Quinn; Wieder, William W.; Grandy, A. Stuart (Wiley, 2021-09-20)
    Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change and broadening the impact of ecological research.
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    Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments
    Thomas, 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.
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    Long-term impacts of silvicultural treatments on wildland fuels and modeled fire behavior in the Ridge and Valley Province, Virginia (USA)
    Hahn, George E.; Coates, T. Adam; Aust, W. Michael; Bolding, M. Chad; Thomas-Van Gundy, Melissa A. (Elsevier, 2021-09-15)
    Active forest management operations, such as regeneration harvests, can reduce hazardous fuel loads and alter fuel structure, potentially minimizing extreme wildfire conditions while maintaining ecosystem services, such as wildlife habitat and water quality. Regeneration harvests of differing intensities (clearcut, high-retention shelterwood, and low-retention shelterwood) were first applied between 1995 and 1996 to three sites on the George Washington-Jefferson National Forest in the Ridge and Valley Province of Virginia, USA. Over two decades after the clearcut was conducted and 11–12 years after the overwood was removed in the shelterwood stands, woody debris, litter, and duff masses and depths were quantified. One-hour fuel loads were greater in clearcut units than in high-retention shelterwood, low-retention shelterwood, or control units. Ten-hour fuel loads were greater in clearcut and low-retention shelterwood units than in high-retention shelterwood and control units. No significant differences in 100-hour fuels were observed between treatments. Control units contained more rotten and total 1000-hour fuels than all other treatments. The total woody debris load was less in the clearcut and high-retention shelterwood than in the low-retention shelterwood and control. High-retention shelterwood woody fuel depth was greater than clearcut woody fuel depth. Litter and duff loads were less in treated units than in the control units. Total fuel load (woody fuel load + litter load + duff load) was greater in the control than the silvicultural treatments. Litter depth did not differ between treatments, while duff depth was greater in the control than in the treated units. Using the computer modeling software, BehavePlus 6.0.0, these alterations to fuel loads and depths led to increased values in the control units for six fire behavior parameters. Predicted surface flame length in the low-retention shelterwood was the only modeled value that was not less than control values. Overall, these results indicated that harvest intensity and timing may have long-term effects on down and dead woody fuels, forest floor depth, and potential fire behavior. Clearcutting reduced fire behavior most, followed by the high-retention shelterwood system. The potential differences in slash and debris generated by varying shelterwood systems may impact long-term fuel and fire dynamics.
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    Predicting bark thickness with one- and two-stage regression models for three hardwood species in the southeastern US
    Yang, Sheng-I; Radtke, Philip J. (Elsevier, 2022-01-01)
    Tree bark, as the outermost protective layer of tree stems, is an important indicator to evaluate the fire resistance properties of trees and to assess the tree mortality induced by fire. Despite its importance, many existing bark thickness models were not primarily developed for predicting bark thickness directly, i.e. with bark thickness as a response variable, and most past studies were focused on modeling bark thickness in conifers. Thus, the objective of this study was to compare the efficacy of various bark thickness models/methods for three common hardwood species in the southeastern US. A total number of 47,281 measurements from 2,070 trees were used in analysis. Results showed that bark thickness at breast height (1.37 m or 4.5 ft above ground) varies by tree size and species, which can be predicted by a species-specific linear regression model with DBH as a single predictor. To predict bark thickness profile, a combination of stem taper function and bark thickness model, a two-stage method, is suggested, which generally performs better than a single bark thickness function (one-stage method) in terms of bias and precision. For a given model form, the two-stage method produced more reliable prediction of bark thickness at upper and lower portions of tree stem than the one-stage method. With the three species examined, the segmented stem taper functions provided more accurate predictions than the variable-exponent function. The results of this study can provide guidance for ecologists and forest managers when selecting appropriate approaches to predict bark thickness.