Department of Forest Resources and Environmental Conservation

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

Now showing 1 - 7 of 7
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    Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting
    Carey, Cayelan C.; Woelmer, Whitney M.; Lofton, Mary E.; Figueiredo, Renato J.; Bookout, Bethany J.; Corrigan, Rachel S.; Daneshmand, Vahid; Hounshell, Alexandria G.; Howard, Dexter W.; Lewis, Abigail S. L.; McClure, Ryan P.; Wander, Heather L.; Ward, Nicole K.; Thomas, R. Quinn (2021-01-18)
    Near-term, iterative ecological forecasts with quantified uncertainty have great potential for improving lake and reservoir management. For example, if managers received a forecast indicating a high likelihood of impending impairment, they could make decisions today to prevent or mitigate poor water quality in the future. Increasing the number of automated, real-time freshwater forecasts used for management requires integrating interdisciplinary expertise to develop a framework that seamlessly links data, models, and cyberinfrastructure, as well as collaborations with managers to ensure that forecasts are embedded into decision-making workflows. The goal of this study is to advance the implementation of near-term, iterative ecological forecasts for freshwater management. We first provide an overview of FLARE (Forecasting Lake And Reservoir Ecosystems), a forecasting framework we developed and applied to a drinking water reservoir to assist water quality management, as a potential open-source option for interested users. We used FLARE to develop scenario forecasts simulating different water quality interventions to inform manager decision-making. Second, we share lessons learned from our experience developing and running FLARE over 2 years to inform other forecasting projects. We specifically focus on how to develop, implement, and maintain a forecasting system used for active management. Our goal is to break down the barriers to forecasting for freshwater researchers, with the aim of improving lake and reservoir management globally.
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    Diversity-invasibility across an experimental disturbance gradient in Appalachian forests
    Belote, R. T.; Jones, R. H.; Hood, S. M.; Wender, B. W. (Ecological Society of America, 2008-01)
    Research examining the relationship between community diversity and invasions by normative species has raised new questions about the theory and management of biological invasions. Ecological theory predicts, and small-scale experiments confirm, lower levels of nonnative species invasion into species-rich compared to species-poor communities, but observational studies across a wider range of scales often report positive relationships between native and nonnative species richness. This paradox has been attributed to the scale dependency of diversity-invasibility relationships and to differences between experimental and observational studies. Disturbance is widely recognized as an important factor determining invasibility of communities, but few studies have investigated the relative and interactive roles of diversity and disturbance on nonnative species invasion. Here, we report how the relationship between native and nonnative plant species richness responded to an experimentally applied disturbance gradient (from no disturbance up to clearcut) in oak-dominated forests. We consider whether results are consistent with various explanations of diversity-invasibility relationships including biotic resistance, resource availability, and the potential effects of scale (I m 2 to 2 ha). We found no correlation between native and normative species richness before disturbance except at the largest spatial scale, but a positive relationship after disturbance across scales and levels of disturbance. Post-disturbance richness of both native and normative species was positively correlated with disturbance intensity and with variability of residual basal area of trees. These results suggest that more nonnative plants may invade species-rich communities compared to species-poor communities following disturbance.
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    From concept to practice to policy: modeling coupled natural and human systems in lake catchments
    Cobourn, Kelly M.; Carey, Cayelan C.; Boyle, Kevin J.; Duffy, Christopher J.; Dugan, Hilary A.; Farrell, Kaitlin J.; Fitchett, Leah Lynn; Hanson, Paul C.; Hart, Julia A.; Henson, Virginia Reilly; Hetherington, Amy L.; Kemanian, Armen R.; Rudstam, Lars G.; Shu, Lele; Soranno, Patricia A.; Sorice, Michael G.; Stachelek, Joseph; Ward, Nicole K.; Weathers, Kathleen C.; Weng, Weizhe; Zhang, Yu (Ecological Society of America, 2018-05-03)
    Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well‐developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual–empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi‐disciplinary tool that captures diverse processes that operate at multiple scales, including land‐management decision‐making, hydrologic‐solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross‐disciplinary dialogue to move CNHS lake‐catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision‐making and policy.
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    Granular measures of agricultural land use influence lake nitrogen and phosphorus differently at macroscales
    Stachelek, Joseph; Weng, W.; Carey, Cayelan C.; Kemanian, Armen R.; Cobourn, Kelly M.; Wagner, Tyler K.; Weathers, Kathleen C.; Soranno, Patricia A. (2020-12)
    Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake's watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near-stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near-stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake-specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality.
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    Lake thermal structure drives interannual variability in summer anoxia dynamics in a eutrophic lake over 37 years
    Ladwig, Robert; Hanson, Paul C.; Dugan, Hilary A.; Carey, Cayelan C.; Zhang, Yu; Shu, Lele; Duffy, Christopher J.; Cobourn, Kelly M. (2021-02-25)
    The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics, nutrient loads, meteorology) as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal timescales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic-ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37 year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an optimization algorithm to improve the fit between observed and simulated data. We calculated stability indices (Schmidt stability, Birgean work, stored internal heat), identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the interannual variation in summer anoxia, we applied a random-forest classifier and multiple linear regressions to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production). Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50-60 d. The summer heat budget, the timing of thermal stratification, and the gross primary production in the epilimnion prior to summer stratification were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. Interannual variability in anoxia was largely driven by physical factors: earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. A measured step change upward in summer anoxia in 2010 was unexplained by the GLM-AED2 model. Although the cause remains unknown, possible factors include invasion by the predacious zooplankton Bythotrephes longimanus. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region.
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    A Near-Term Iterative Forecasting System Successfully Predicts Reservoir Hydrodynamics and Partitions Uncertainty in Real Time
    Thomas, R. Quinn; Figueiredo, Renato J.; Daneshmand, Vahid; Bookout, Bethany J.; Puckett, Laura K.; Carey, Cayelan C. (2020-11)
    Freshwater ecosystems are experiencing greater variability due to human activities, necessitating new tools to anticipate future water quality. In response, we developed and deployed a real-time iterative water temperature forecasting system (FLARE-Forecasting Lake And Reservoir Ecosystems). FLARE is composed of water temperature and meteorology sensors that wirelessly stream data, a data assimilation algorithm that uses sensor observations to update predictions from a hydrodynamic model and calibrate model parameters, and an ensemble-based forecasting algorithm to generate forecasts that include uncertainty. Importantly, FLARE quantifies the contribution of different sources of uncertainty (driver data, initial conditions, model process, and parameters) to each daily forecast of water temperature at multiple depths. We applied FLARE to Falling Creek Reservoir (Vinton, Virginia, USA), a drinking water supply, during a 475-day period encompassing stratified and mixed thermal conditions. Aggregated across this period, root mean square error (RMSE) of daily forecasted water temperatures was 1.13 degrees C at the reservoir's near-surface (1.0 m) for 7-day ahead forecasts and 1.62 degrees C for 16-day ahead forecasts. The RMSE of forecasted water temperatures at the near-sediments (8.0 m) was 0.87 degrees C for 7-day forecasts and 1.20 degrees C for 16-day forecasts. FLARE successfully predicted the onset of fall turnover 4-14 days in advance in two sequential years. Uncertainty partitioning identified meteorology driver data as the dominant source of uncertainty in forecasts for most depths and thermal conditions, except for the near-sediments in summer, when model process uncertainty dominated. Overall, FLARE provides an open-source system for lake and reservoir water quality forecasting to improve real-time management.
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    Soil Bacterial and Fungal Communities Exhibit Distinct Long-Term Responses to Disturbance in Temperate Forests
    Osburn, Ernest D.; McBride, Steven Glynn II; Aylward, Frank O.; Badgley, Brian D.; Strahm, Brian D.; Knoepp, Jennifer D.; Barrett, John E. (2019-12-11)
    In Appalachian ecosystems, forest disturbance has long-term effects on microbially driven biogeochemical processes such as nitrogen (N) cycling. However, little is known regarding long-term responses of forest soil microbial communities to disturbance in the region. We used 16S and ITS sequencing to characterize soil bacterial (16S) and fungal (ITS) communities across forested watersheds with a range of past disturbance regimes and adjacent reference forests at the Coweeta Hydrologic Laboratory in the Appalachian mountains of North Carolina. Bacterial communities in previously disturbed forests exhibited consistent responses, including increased alpha diversity and increased abundance of copiotrophic (e.g., Proteobacteria) and N-cycling (e.g., Nitrospirae) bacterial phyla. Fungal community composition also showed disturbance effects, particularly in mycorrhizal taxa. However, disturbance did not affect fungal alpha diversity, and disturbance effects were not consistent at the fungal class level. Co-occurrence networks constructed for bacteria and fungi showed that disturbed communities were characterized by more connected and tightly clustered network topologies, indicating that disturbance alters not only community composition but also potential ecological interactions among taxa. Although bacteria and fungi displayed different long-term responses to forest disturbance, our results demonstrate clear responses of important bacterial and fungal functional groups (e.g., nitrifying bacteria and mycorrhizal fungi), and suggest that both microbial groups play key roles in the long-term alterations to biogeochemical processes observed following forest disturbance in the region.