Browsing by Author "Thomas, R. Quinn"
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- Above-ground tree carbon storage in response to nitrogen deposition in the US is heterogeneous and may have weakenedClark, Christopher M.; Thomas, R. Quinn; Horn, Kevin J. (Springer Nature, 2023-02-14)Long-term nitrogen deposition may not provide sustained stimulation of tree carbon storage, suggest analyses of a tree inventory and growth for the contiguous US between 2000 and 2016, compared to data for the 1980s and 1990s. Changes in nitrogen (N) availability affect the ability for forest ecosystems to store carbon (C). Here we extend an analysis of the growth and survival of 94 tree species and 1.2 million trees, to estimate the incremental effects of N deposition on changes in aboveground C (dC/dN) across the contiguous U.S. (CONUS). We find that although the average effect of N deposition on aboveground C is positive for the CONUS (dC/dN = +9 kg C per kg N), there is wide variation among species and regions. Furthermore, in the Northeastern U.S. where we may compare responses from 2000-2016 with those from the 1980s-90s, we find the recent estimate of dC/dN is weaker than from the 1980s-90s due to species-level changes in responses to N deposition. This suggests that the U.S. forest C-sink varies widely across forests and may be weakening overall, possibly necessitating more aggressive climate policies than originally thought.
- Advancing lake and reservoir water quality management with near-term, iterative ecological forecastingCarey, 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.
- Alternate Trait-Based Leaf Respiration Schemes Evaluated at Ecosystem-Scale Through Carbon Optimization Modeling and Canopy Property DataThomas, R. Quinn; Williams, M.; Cavaleri, M. A.; Exbrayat, J. -F.; Smallman, T. L.; Street, L. E. (American Geophysical Union, 2019-12-25)Leaf maintenance respiration (Rleaf,m) is a major but poorly understood component of the terrestrial carbon cycle (C). Earth systems models (ESMs) use simple sub-models relating Rleaf,m to leaf traits, applied at canopy scale. Rleaf,m models vary depending on which leaf N traits they incorporate (e.g., mass or area based) and the form of relationship (linear or nonlinear). To simulate vegetation responses to global change, some ESMs include ecological optimization to identify canopy structures that maximize net C accumulation. However, the implications for optimization of using alternate leaf-scale empirical Rleaf,m models are undetermined. Here we combine alternate well-known empirical models of Rleaf,m with a process model of canopy photosynthesis. We quantify how net canopy exports of C vary with leaf area index (LAI) and total canopy N (TCN). Using data from tropical and arctic canopies, we show that estimates of canopy Rleaf,m vary widely among the three models. Using an optimization framework, we show that the LAI and TCN values maximizing C export depends strongly on the Rleaf,m model used. No single model could match observed arctic and tropical LAI-TCN patterns with predictions of optimal LAI-TCN. We recommend caution in using leaf-scale empirical models for components of ESMs at canopy-scale. Rleaf,m models may produce reasonable results for a specified LAI, but, due to their varied representations of Rleaf,mfoliar N sensitivity, are associated with different and potentially unrealistic optimization dynamics at canopy scale. We recommend ESMs to be evaluated using response surfaces of canopy C export in LAI-TCN space to understand and mitigate these risks.
- Analysis of Crop Phenology Using Time-Series MODIS Data and Climate DataRen, Jie; Campbell, James B. Jr.; Shao, Yang; Thomas, R. Quinn (2014)Understanding crop phenology is fundamental to agricultural production, management, planning and decision-making. In the continental United States, key phenological stages are strongly influenced by meteorological and climatological conditions. This study used remote sensing satellite data and climate data to determine key phenological states of corn and soybean and evaluated estimates of these phenological parameters. A time series of Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composites from 2001 to 2013 was analyzed with the TIMESAT program to automatically retrieve key phenological stages such as the start of season (emergence), peak (heading) and end of season (maturity). These stages were simulated with 6 hourly temperature data from 1980 to 2013 on the basis of crop model under the Community Land Model (CLM) (version 4.5). With these two methods, planting date, heading date, harvesting date, and length of growing season from 2001 to 2013 were determined and compared. There should be a good correlation between estimates derived from satellites and estimates produced with the climate data based on the crop model.
- Anoxia decreases the magnitude of the carbon, nitrogen, and phosphorus sink in freshwatersCarey, Cayelan C.; Hanson, Paul C.; Thomas, R. Quinn; Gerling, Alexandra B.; Hounshell, Alexandria G.; Lewis, Abigail S.; Lofton, Mary E.; McClure, Ryan P.; Wander, Heather L.; Woelmer, Whitney M.; Niederlehner, B.R.; Schreiber, Madeline E. (Wiley, 2022-05-05)Oxygen availability is decreasing in many lakes and reservoirs worldwide, raising the urgency for understanding how anoxia (low oxygen) affects coupled biogeochemical cycling, which has major implications for water quality, food webs, and ecosystem functioning. Although the increasing magnitude and prevalence of anoxia has been documented in freshwaters globally, the challenges of disentangling oxygen and temperature responses have hindered assessment of the effects of anoxia on carbon, nitrogen, and phosphorus concentrations, stoichiometry (chemical ratios), and retention in freshwaters. The consequences of anoxia are likely severe and may be irreversible, necessitating ecosystem-scale experimental investigation of decreasing freshwater oxygen availability. To address this gap, we devised and conducted REDOX (the Reservoir Ecosystem Dynamic Oxygenation eXperiment), an unprecedented, 7-year experiment in which we manipulated and modeled bottom-water (hypolimnetic) oxygen availability at the whole-ecosystem scale in a eutrophic reservoir. Seven years of data reveal that anoxia significantly increased hypolimnetic carbon, nitrogen, and phosphorus concentrations and altered elemental stoichiometry by factors of 2–5× relative to oxic periods. Importantly, prolonged summer anoxia increased nitrogen export from the reservoir by six-fold and changed the reservoir from a net sink to a net source of phosphorus and organic carbon downstream. While low oxygen in freshwaters is thought of as a response to land use and climate change, results from REDOX demonstrate that low oxygen can also be a driver of major changes to freshwater biogeochemical cycling, which may serve as an intensifying feedback that increases anoxia in downstream waterbodies. Consequently, as climate and land use change continue to increase the prevalence of anoxia in lakes and reservoirs globally, it is likely that anoxia will have major effects on freshwater carbon, nitrogen, and phosphorus budgets as well as water quality and ecosystem functioning.
- Assessing Ecosystem State Space Models: Identifiability and EstimationSmith, John W.; Johnson, Leah R.; Thomas, R. Quinn (Springer, 2023-03)Hierarchical probability models are being used more often than non-hierarchical deterministic process models in environmental prediction and forecasting, and Bayesian approaches to fitting such models are becoming increasingly popular. In particular, models describing ecosystem dynamics with multiple states that are autoregressive at each step in time can be treated as statistical state space models (SSMs). In this paper, we examine this subset of ecosystem models, embed a process-based ecosystem model into an SSM, and give closed form Gibbs sampling updates for latent states and process precision parameters when process and observation errors are normally distributed. Here, we use simulated data from an example model (DALECev) and study the effects changing the temporal resolution of observations on the states (observation data gaps), the temporal resolution of the state process (model time step), and the level of aggregation of observations on fluxes (measurements of transfer rates on the state process). We show that parameter estimates become unreliable as temporal gaps between observed state data increase. To improve parameter estimates, we introduce a method of tuning the time resolution of the latent states while still using higher-frequency driver information and show that this helps to improve estimates. Further, we show that data cloning is a suitable method for assessing parameter identifiability in this class of models. Overall, our study helps inform the application of state space models to ecological forecasting applications where (1) data are not available for all states and transfers at the operational time step for the ecosystem model and (2) process uncertainty estimation is desired.
- Assessing opportunities and inequities in undergraduate ecological forecasting educationWillson, Alyssa M.; Gallo, Hayden; Peters, Jody A.; Abeyta, Antoinette; Watts, Nievita Bueno; Carey, Cayelan C.; Moore, Tadhg N.; Smies, Georgia; Thomas, R. Quinn; Woelmer, Whitney M.; McLachlan, Jason S. (Wiley, 2023-05)Conducting ecological research in a way that addresses complex, real-world problems requires a diverse, interdisciplinary and quantitatively trained ecology and environmental science workforce. This begins with equitably training students in ecology, interdisciplinary science, and quantitative skills at the undergraduate level. Understanding the current undergraduate curriculum landscape in ecology and environmental sciences allows for targeted interventions to improve equitable educational opportunities. Ecological forecasting is a sub-discipline of ecology with roots in interdisciplinary and quantitative science. We use ecological forecasting to show how ecology and environmental science undergraduate curriculum could be evaluated and ultimately restructured to address the needs of the 21(st) century workforce. To characterize the current state of ecological forecasting education, we compiled existing resources for teaching and learning ecological forecasting at three curriculum levels: online resources; US university courses on ecological forecasting; and US university courses on topics related to ecological forecasting. We found persistent patterns (1) in what topics are taught to US undergraduate students at each of the curriculum levels; and (2) in the accessibility of resources, in terms of course availability at higher education institutions in the United States. We developed and implemented programs to increase the accessibility and comprehensiveness of ecological forecasting undergraduate education, including initiatives to engage specifically with Native American undergraduates and online resources for learning quantitative concepts at the undergraduate level. Such steps enhance the capacity of ecological forecasting to be more inclusive to undergraduate students from diverse backgrounds and expose more students to quantitative training.
- Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model AssumptionsWieder, William R.; Lawrence, David M.; Fisher, Rosie A.; Bonan, Gordon B.; Cheng, Susan J.; Goodale, Christine L.; Grandy, A. Stuart; Koven, Charles D.; Lombardozzi, Danica L.; Oleson, Keith W.; Thomas, R. Quinn (American Geophysical Union, 2019-10-28)Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon-nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and—the newly developed—5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO2) enrichment with meta-analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET-MTE observations. Simulations with N and CO2 enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO2 enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections.
- Characterizing spatiotemporal variation in LAI of Virginia Pine PlantationsMcCurdy, Wyatt Conner (Virginia Tech, 2020-01-27)Loblolly pine is an important managed tree species within the southeastern United States, and better understanding spatial patterns in its productivity has potential to contribute to both modeling and management of the species. Using recently-created pine management maps specific to Virginia and empirical relationships predicting pine LAI from the Landsat satellite, we conducted a statewide analysis of temporal patterns in stand-level southern pine leaf area index (LAI) following clear-cut and planting. Here, using 28 years of Landsat time-series data for 13,140 stands that were clear-cut between 2014-2017, we examined 1) when LAI peaked over the rotation, and 2) how LAI in each stand compared to a recommended fertilization threshold of 3.5 LAI. We found that, on average, winter LAI reached a maximum of 2.02., which can be approximately doubled to give a summer LAI of 4.04, and within stand peak occurred between years 13 and 15. We also found that around 45.8% of stands achieved an LAI value higher than 3.5: a fertilization threshold recommended for managed stands in Virginia. The dataset produced by our analysis will bolster information required for modeling loblolly pines as a plant functional type in regional land simulations, and the finding that most stands are below the recommended LAI fertilization threshold will fuel further management-motivated research.
- Combined Carbon and Albedo Climate Forcing From Pine and Switchgrass Grown for BioenergyAhlswede, Benjamin J.; O'Halloran, Thomas L.; Thomas, R. Quinn (Frontiers, 2022-05-13)Expanding and restoring forests decreases atmospheric carbon dioxide, a natural solution for helping mitigate climate change. However, forests also have relatively low albedo compared to grass and croplands, which increases the amount of solar energy they absorb into the climate system. An alternative natural climate solution is to replace fossil fuels with bioenergy. Bioenergy crops such as switchgrass have higher albedo than forest ecosystems but absorb less total carbon over their lifetime. To evaluate trade-offs in the mitigation potential by pine and switchgrass ecosystems, we used eddy covariance net ecosystem exchange and albedo observations collected from planted pine forests and switchgrass fields in eastern North America and Canada to compare the net radiative forcing of these two ecosystems over the length of typical pine rotation (30 years). We found that pine had a net positive radiative forcing (warming) of 5.4 ± 2.8 Wm−2 when albedo and carbon were combined together (30 year mean). However the assumptions regarding the fate of harvested carbon had an important effect on the net radiative forcing. When we assumed all switchgrass carbon was emitted to the atmosphere while the harvested pine carbon was prevented from entering the atmosphere, the 30-year mean net radiative forcing reversed direction (−3.6 ± 2.8 Wm−2). Overall, while the pine ecosystem absorbed more carbon than the switchgrass, the difference in albedo was large enough to result in similar climate mitigation potential at the 30-year horizon between the two systems, whereby the direction and magnitude of radiative forcing depends on the fate of harvested carbon.
- The combined effects of fertilization and relative water limitation on tissue water relations, hydraulic parameters and shallow root distribution in loblolly pine (Pinus taeda L.)Russell, Edward Morgan (Virginia Tech, 2019-08-27)One goal of this research was to characterize shoot tissue-level responses in loblolly pine to soil moisture limitation in combination with fertilization as well as to more severe soil moisture limitation. We found that neither fertilization alone, nor fertilization in combination with soil moisture limitation resulted in changes to shoot tissue water relations parameters classically characterized in drought response studies. More severe water limitation was necessary to elicit responses, and those responses had not been fully described previously. The more severe water limitation resulted in increased capacitance beyond turgor loss, increased relative water content at turgor loss, a more negative turgor loss point, an increased bulk modulus of elasticity, more negative osmotic potential at 100% relative water content, and an increased apoplastic water fraction. As there were indications of reduced water use and moisture stress in the absence of shoot level responses under less severe drought, such parameters are insufficient alone to characterize moisture stress in fertilized and in less severely water limited loblolly trees. Additionally, we sought a morphological or physiological explanation for the reduced transpiration and increased water use efficiency reported for fertilized trees in the Virginia Piedmont. Our characterizations of the responses of root distribution and hydraulics to limited soil moisture here complement existing research, which demonstrated changes to root distribution and hydraulics in response to fertilization. The responses we discovered in fertilized trees that accompanied reduced transpiration and increased water use efficiency that differed from responses to reduced soil moisture alone were primarily large decreases to shallow root presence. We found this to be readily quantified using measures of root length density. Decreases to whole-tree hydraulic conductivity were also shown to occur with fertilization and were shown not to occur in shoot tissue, suggesting limitation via rhizosphere or root xylem conductance. Our results support the supposition that fertilization narrows hydraulic safety margins and potentially predisposes loblolly trees to moisture stress, particularly prolonged, severe water limitation following fertilization. Finally, we tested the validity of throughfall exclusion for simulating reduced rainfall using a greenhouse 'split-pot' study, which applied spatially fixed heterogeneous soil moisture to young, well-watered loblolly pines. The 'split-pot' experiments demonstrated that spatially fixed soil moisture heterogeneity does not confound drought effects; needle area specific transpiration was not decreased, nor was water use efficiency increased. This supports the validity of inferences taken from drought simulation experiments with loblolly pine where throughfall exclusion troughs reduce soil moisture content in a consistent, spatially heterogeneous manner.
- A community convention for ecological forecasting: output files and metadata v1.0Dietze, Michael C.; Thomas, R. Quinn; Peters, Jody; Boettiger, Carl; Koren, Gerbrand; Shiklomanov, Alexey N.; Ashander, Jaime (Wiley, 2023-11-23)This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.
- Community Earth System Model Simulations Reveal the Relative Importance of Afforestation and Forest Management to Surface Temperature in Eastern North AmericaAhlswede, Benjamin J.; Thomas, R. Quinn (MDPI, 2017-12-13)Afforestation changes the land surface energy balance, though the effects on climate in temperate regions is uncertain, particularly the changes associated with forest management. In this study, we used idealized Community Earth System Model simulations to assess the influence of afforestation and afforestation management in eastern North America on climate via changes in the biophysics of the land surface. Afforestation using broadleaf deciduous trees maintained at high leaf area index (LAI) in the southern part of the study region provided the greatest climate benefit by cooling summer surface air temperatures (Tsa). In contrast, the greatest warming occurred in the northern extent of the study region when afforesting with needleleaf evergreen trees maintained at high LAI. Forest management had an equal or greater influence on Tsa than the overall decision to afforest land in the southern extent of the region. Afforestation had a greater influence on Tsa than forest management in the northern extent. Integrating our results, focused on biophysical processes, with other research quantifying carbon cycle sensitivity to management can help guide the use of temperate afforestation to optimize climate benefits. Further, our results highlight the potential importance of including forest management in simulations of past and future climate.
- The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing UncertaintyLawrence, David M.; Fisher, Rosie A.; Koven, Charles D.; Oleson, Keith W.; Swenson, Sean C.; Bonan, Gordon B.; Collier, Nathan; Ghimire, Bardan; van Kampenhout, Leo; Kennedy, Daniel; Kluzek, Erik; Lawrence, Peter J.; Li, Fang; Li, Hongyi; Lombardozzi, Danica L.; Riley, William J.; Sacks, William J.; Shi, Mingjie; Vertenstein, Mariana; Wieder, William R.; Xu, Chonggang; Ali, Ashehad A.; Badger, Andrew M.; Bisht, Gautam; van den Broeke, Michiel; Brunke, Michael A.; Burns, Sean P.; Buzan, Jonathan; Clark, Martyn; Craig, Anthony; Dahlin, Kyla; Drewniak, Beth; Fisher, Joshua B.; Flanner, Mark; Fox, Andrew M.; Gentine, Pierre; Hoffman, Forrest; Keppel-Aleks, Gretchen; Knox, Ryan; Kumar, Sanjiv; Lenaerts, Jan; Leung, L. Ruby; Lipscomb, William H.; Lu, Yaqiong; Pandey, Ashutosh; Pelletier, Jon D.; Perket, Justin; Randerson, James T.; Ricciuto, Daniel M.; Sanderson, Benjamin M.; Slater, Andrew; Subin, Zachary M.; Tang, Jinyun; Thomas, R. Quinn; Martin, Maria Val; Zeng, Xubin (American Geophysical Union, 2019-10-19)The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.
- A Continental-Scale Investigation of Factors Controlling the Vulnerability of Soil Organic Matter in Mineral Horizons to DecompositionWeiglein, Tyler Lorenz (Virginia Tech, 2019-07-30)Soil organic matter (SOM) is the largest terrestrial pool of organic carbon (C), and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic climate change. Despite the importance of SOM in the global C cycle, our understanding of the controls on SOM stabilization and decomposition is still developing, and as such, SOM dynamics are a source of major uncertainty in current Earth system models (ESMs), which reduces the effectiveness of these models in predicting the efficacy of climate change mitigation strategies. To improve our understanding of controls on SOM decomposition at scales relevant to such modeling efforts, A and upper B horizon soil samples from 22 National Ecological Observatory Network (NEON) sites spanning the conterminous U.S. were incubated for 52 weeks under conditions representing site-specific mean summer temperature and horizon-specific field capacity (-33 kPa) water potential. Cumulative CO2 respired was periodically measured and normalized by soil organic C content to obtain cumulative specific respiration (CSR). A two-pool decomposition model was fitted to the CSR data to calculate decomposition rates of fast- (kfast) and slow-cycling pools (kslow). Post-LASSO best subsets multiple linear regression was used to construct horizon-specific models of significant predictors for CSR, kfast, and kslow. Significant predictors for all three response variables consisted mostly of proximal factors related to clay-sized fraction mineralogy and SOM composition. Non-crystalline minerals and lower SOM lability negatively affected CSR for both A and B horizons. Significant predictors for decomposition rates varied by horizon and pool. B horizon decomposition rates were positively influenced by nitrogen (N) availability, while an index of pyrogenic C had a negative effect on kfast in both horizons. These results reinforce the recognized need to explicitly represent SOM stabilization via interactions with non-crystalline minerals in ESMs, and they also suggest that increased N inputs could enhance SOM decomposition in the subsoil, highlighting another mechanism beyond shifts in temperature and precipitation regimes that could alter SOM decomposition rates.
- The contribution of wildland fire emissions to deposition in the US: implications for tree growth and survival in the NorthwestKoplitz, Shannon N.; Nolte, Christopher G.; Sabo, Robert D.; Clark, Christopher M.; Horn, Kevin J.; Thomas, R. Quinn; Newcomer-Johnson, Tamara A. (2021-02)Ecosystems require access to key nutrients like nitrogen (N) and sulfur (S) to sustain growth and healthy function. However, excessive deposition can also damage ecosystems through nutrient imbalances, leading to changes in productivity and shifts in ecosystem structure. While wildland fires are a known source of atmospheric N and S, little has been done to examine the implications of wildland fire deposition for vulnerable ecosystems. We combine wildland fire emission estimates, atmospheric chemistry modeling, and forest inventory data to (a) quantify the contribution of wildland fire emissions to N and S deposition across the U S, and (b) assess the subsequent impacts on tree growth and survival rates in areas where impacts are likely meaningful based on the relative contribution of fire to total deposition. We estimate that wildland fires contributed 0.2 kg N ha(-1) yr(-1) and 0.04 kg S ha(-1) yr(-1) on average across the U S during 2008-2012, with maxima up to 1.4 kg N ha(-1) yr(-1) and 0.6 kg S ha(-1) yr(-1) in the Northwest representing over similar to 30% of total deposition in some areas. Based on these fluxes, exceedances of S critical loads as a result of wildland fires are minimal, but exceedances for N may affect the survival and growth rates of 16 tree species across 4.2 million hectares, with the most concentrated impacts occurring in Oregon, northern California, and Idaho. Understanding the broader environmental impacts of wildland fires in the U S will inform future decision making related to both fire management and ecosystem services conservation.
- 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.
- Eddy Covariance Data Reveal That a Small Freshwater Reservoir Emits a Substantial Amount of Carbon Dioxide and MethaneHounshell, Alexandria G.; D'Acunha, Brenda M.; Breef-Pilz, Adrienne; Johnson, Mark S.; Thomas, R. Quinn; Carey, Cayelan C. (American Geophysical Union, 2023-03-14)Small freshwater reservoirs are ubiquitous and likely play an important role in global greenhouse gas (GHG) budgets relative to their limited water surface area. However, constraining annual GHG fluxes in small freshwater reservoirs is challenging given their footprint area and spatially and temporally variable emissions. To quantify the GHG budget of a small (0.1 km2) reservoir, we deployed an Eddy covariance (EC) system in a small reservoir located in southwestern Virginia, USA over 2 years to measure carbon dioxide (CO2) and methane (CH4) fluxes near-continuously. Fluxes were coupled with in situ sensors measuring multiple environmental parameters. Over both years, we found the reservoir to be a large source of CO2 (633–731 g CO2-C m−2 yr−1) and CH4 (1.02–1.29 g CH4-C m−2 yr−1) to the atmosphere, with substantial sub-daily, daily, weekly, and seasonal timescales of variability. For example, fluxes were substantially greater during the summer thermally stratified season as compared to the winter. In addition, we observed significantly greater GHG fluxes during winter intermittent ice-on conditions as compared to continuous ice-on conditions, suggesting GHG emissions from lakes and reservoirs may increase with predicted decreases in winter ice-cover. Finally, we identified several key environmental variables that may be driving reservoir GHG fluxes at multiple timescales, including, surface water temperature and thermocline depth followed by fluorescent dissolved organic matter. Overall, our novel year-round EC data from a small reservoir indicate that these freshwater ecosystems likely contribute a substantial amount of CO2 and CH4 to global GHG budgets, relative to their surface area.
- Embedding communication concepts in forecasting training increases students' understanding of ecological uncertaintyWoelmer, Whitney M.; Moore, Tadhg N.; Lofton, Mary E.; Thomas, R. Quinn; Carey, Cayelan C. (Wiley, 2023-08)Communicating and interpreting uncertainty in ecological model predictions is notoriously challenging, motivating the need for new educational tools, which introduce ecology students to core concepts in uncertainty communication. Ecological forecasting, an emerging approach to estimate future states of ecological systems with uncertainty, provides a relevant and engaging framework for introducing uncertainty communication to undergraduate students, as forecasts can be used as decision support tools for addressing real-world ecological problems and are inherently uncertain. To provide critical training on uncertainty communication and introduce undergraduate students to the use of ecological forecasts for guiding decision-making, we developed a hands-on teaching module within the Macrosystems Environmental Data-Driven Inquiry and Exploration (EDDIE; MacrosystemsEDDIE.org) educational program. Our module used an active learning approach by embedding forecasting activities in an R Shiny application to engage ecology students in introductory data science, ecological modeling, and forecasting concepts without needing advanced computational or programming skills. Pre- and post-module assessment data from more than 250 undergraduate students enrolled in ecology, freshwater ecology, and zoology courses indicate that the module significantly increased students' ability to interpret forecast visualizations with uncertainty, identify different ways to communicate forecast uncertainty for diverse users, and correctly define ecological forecasting terms. Specifically, students were more likely to describe visual, numeric, and probabilistic methods of uncertainty communication following module completion. Students were also able to identify more benefits of ecological forecasting following module completion, with the key benefits of using forecasts for prediction and decision-making most commonly described. These results show promise for introducing ecological model uncertainty, data visualizations, and forecasting into undergraduate ecology curricula via software-based learning, which can increase students' ability to engage and understand complex ecological concepts.
- Evaluating the interactions of crop management, carbon cycling, and climate using Earth system modeling and remote sensingGraham, Michael William (Virginia Tech, 2019-08-27)Crop management practices, such as soil tillage and crop residue management, are land management activities with potentially large impacts on carbon (C) cycling and climate at the global scale. Improvements in crop management practices, such as conservation tillage or 'no-till' (NT), have been proposed as climate change mitigation measures because such practices may alter C cycles through increased sequestration of soil C in agricultural soils. Despite their potential importance, regional to global scale data are lacking for many crop management practices, and few studies have evaluated the potential impact of the full range of crop management practices on C cycling and climate at the global scale. However, monitoring of crop management practices is crucial for assessing spatial variations in management intensity and informing policy decisions. Inclusion of crop management practices in Earth system models used for assessing global climate is a key requirement for evaluating the overall effects of different crop management practices on C cycling and their potential to mitigate climate change. Studies in this dissertation seek to address these issues by: (1) evaluating the efficacy of remote sensing methods for monitoring differences in soil tillage and crop residue management practices in Iowa; (2) incorporating soil tillage practices into an Earth system model and assessing the potential for soil C sequestration and climate change mitigation through adoption of NT practices; (3) assessing the historical impact of including the full range of crop management practices (residue harvest, grain harvest, soil tillage, irrigation, and fertilization) on changes in C cycling associated with land use and land cover change (LULCC) to crops in an Earth system model. The remote sensing study found that performance of the minimum Normalized Difference Tillage Index (minNDTI) method for assessing differences in tillage and residue management was below average compared to previous studies, even when using imagery from both Landsat 8 and Sentinel-2A sensors. Accurate assessment of these practices using minNDTI was hindered by issues with image quality and inability to obtain sufficient cloud-free, time series imagery during the critical planting window. Remote sensing research aimed at obtaining regional to global scale data on tillage and residue management practices is likely to continue to face these issues in the future, but further research should incorporate additional sensors and assess the efficacy of the minNDTI method for multiple locations and years. Adoption of NT practices in the Community Land Model, which is the land component of the Community Earth System Model, resulted in a cumulative soil C sequestration of 6.6 – 14.4 Pg C from 2015 – 2100 under a future climate change scenario (Representative Concentration Pathway 8.5), and cumulative soil C sequestration was equal to approximately one year of present-day fossil fuel emissions. Adjusting for areas where NT is already practiced had minor impacts on cumulative soil C storage, reducing gains in soil C from NT adoption by 0.4 – 0.9 Pg C globally. These results indicate that soil C sequestration and potential for climate change mitigation through NT may be more limited than has been anticipated elsewhere. Soil C sequestration via NT adoption was highest in temperate regions of developed countries with high initial soil C contents, indicating these areas should be targeted for NT adoption. Simulating the full range of crop management practices in the Community Land Model resulted in an increase in C emissions due to LULCC of 29 – 38 Pg C compared to scenarios with generic crops and model defaults. Individual crop management practices with the largest impact on LULCC emissions were crop residue harvest (18 Pg C), followed by grain harvest (9 Pg C) and soil tillage (5 Pg C). Although implementation of crop residue harvest and soil tillage was extreme in this study, these results imply that Earth system models may underestimate emissions from LULCC by excluding the full range of crop management practices. Studies in this dissertation corroborate the importance of crop management practices for C cycling and climate, but further research on these management practices is needed in terms of data collection, improving process-level understanding, and inclusion of these practices in Earth system models.
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