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Morin, Timothy H.

Publications and source records attributed to Morin, Timothy H..

12 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models–Advances, Applications, and Challenges

Earth System Models (ESMs) simulate the exchange of mass and energy between the land surface and the atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is the second most important greenhouse gas after carbon dioxide. There are growing concerns over the rapidly increasing methane concentration in the atmosphere, underscoring the need for accurate global modeling of its emissions using ESMs. Of the multitude of sources of methane globally, wetlands are the largest natural emitters for methane, leading to significant efforts targeting their representation in ESMs with a special focus on their methane emissions. In this review, we first provide a historical overview of including wetland–methane components in ESMs and how methane modeling approaches have evolved over time. Second, we discuss recent modeling advancements that show promise for improvements in methane emissions predictions, namely the coupling of surface and atmospheric modules of ESMs, the representation of microtopography and transport mechanisms, the resolution of microbial processes at different spatial–temporal scales, and the improved mapping of wetland area extent across the different wetland types. Third, we shed light on the different challenges hindering accurate estimations of wetland–methane emissions, as shown by the consistent discrepancy between bottom–up and top–down models' predictions. Finally, we emphasize that more detailed representation of biogeochemistry and dynamic hydrology while resolving the within–wetland vegetation heterogeneity should improve model predictions, especially when coupled with expanding ground–based measurement networks and high–resolution remote sensing mapping of methane–relevant variables, such as water elevation, water table depth, and methane concentration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Largely Ignored but Important Role of Non‐Rooted, Submersed Vegetation and Small Waterbodies on Greenhouse Gas Emissions

Abstract Small, shallow waterbodies are abundant globally and are associated with greenhouse gas (GHG) emissions disproportionate to their size. One reason for this is the prevalence of non‐rooted, submersed (NRS) macrophytes that often dominate these systems. Despite these plants' significant role in the carbon ecology of their ecosystems, they are often excluded from climate change models due, in part, to the lack of clarity of their effects. Theus et al. (2023, https://doi.org/10.1029/2023JG007758 ) provides new insights into the role that NRS macrophytes have on GHG emissions, demonstrating that increasing densities of these macrophytes lead to increases in both CO 2 and CH 4 gas fluxes. Here, we highlight the importance of both shallow waterbodies and NRS vegetation within the context of the field of aquatic ecosystem biogeochemistry. We identify a need for the inclusion of these drivers into climate change models based partly on the findings of Theus et al. (2023, https://doi.org/10.1029/2023JG007758 ).

Hassett, Erin↗
DOE OSTI2022

Water level changes in Lake Erie drive 21st century CO 2 and CH 4 fluxes from a coastal temperate wetland

Wetland water depth influences microbial and plant communities, which can alter the above- and below-ground carbon cycling of a wetland. Wetland water depths are likely to change due to shifting precipitation patterns, which will affect projections of greenhouse gas emissions; however, these effects are rarely incorporated into wetland greenhouse gas models. Seeking to address this gap, we used a mechanistic model, ecosys, to simulate a range of water depth scenarios in a temperate wetland, and analyzed simulated predictions of carbon dioxide (CO 2 ) andmethane (CH 4 ) fluxes over the 21st century. We tested our model using eddy covariance measurements of CO 2 and CH 4 fluxes collected at the Old Woman Creek National Estuarine Research Reserve (OWC) during 2015 and 2016. OWC is a lacustrine, estuarine, freshwater, mineral-soil marsh. An empirical model found that the wetland water depth is highly dependent on the water depth of the nearby Lake Erie. Future wetland surface water depths were modeled based on projection of Lake Erie's water depth using four separate NOAA projections, resulting in four wetland water-depth scenarios. Two of the four 21st century projections for Lake Erie water depths used in this study indicated that the water depth of the wetland would remain nearly steady; however, the other two indicated decreases in the wetland water depth. In our scenario where the wetland dries out, we project the wetland's climatological warming effect will decrease due to smaller CH 4 fluxes to the atmosphere and larger CO 2 uptake by the wetland. We also found that increased water level can lower emissions by shifting the site towards more open water areas, which have lower CH 4 emissions. We found that decreased water depths would cause more widespread colonization of the wetland by macrophyte vegetation. Using an empirical relationship, we also found that further drying could result in other, non-wetland vegetation to emerge, dramatically altering soil carbon cycling. In three of our four projections, we found that in general the magnitude of CO 2 and CH 4 fluxes steadily increase over the next 100 years in response to higher temperatures. However, in our driest simulations, we projected a different response due to increased oxidation of soil carbon, with CH 4 emissions decreasing substantially from an annual cumulative peak of 224.6 to a minimum of 104.7 gC m –2 year –1 . In that same simulation, net cumulative flux of CO 2 changed from being a sink of 56.5 gC m –2 year –1 to a source of 369.6 gCm –2 year –1 over the same period, despite a temperature increase from 13.7 °C to 14.2 °C. This temperature shift in our other three cases with greater water depths increased the source strength of CH 4 and the sink strength of CO 2 . Here, we conclude that the magnitude of wetland greenhouse-gas fluxes depended on the water depth primarily as it affected the areal percentage of the wetland available for plant colonization, but dramatic decreases in water depths could cause significant reductions in the wetland CH 4 fluxes, while simultaneously altering the wetland vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2021

FLUXNET-CH 4 : a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Methane (CH 4 ) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH 4 emissions due to quasi-continuous and high-temporal-resolution CH 4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH 4 Version 1.0, the first open-source global dataset of CH 4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH 4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH 4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH 4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH 4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20°S to 20°N) the spring onset of elevated CH 4 emissions starts 3 d earlier, and the CH 4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH 4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH 4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH 4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH 4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH 4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH 4 peak). FLUXNET-CH 4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH 4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH 4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Members of the Genus Methylobacter Are Inferred To Account for the Majority of Aerobic Methane Oxidation in Oxic Soils from a Freshwater Wetland

ABSTRACT Microbial carbon degradation and methanogenesis in wetland soils generate a large proportion of atmospheric methane, a highly potent greenhouse gas. Despite their potential to mitigate greenhouse gas emissions, knowledge about methane-consuming methanotrophs is often limited to lower-resolution single-gene surveys that fail to capture the taxonomic and metabolic diversity of these microorganisms in soils. Here our objective was to use genome-enabled approaches to investigate methanotroph membership, distribution, and in situ activity across spatial and seasonal gradients in a freshwater wetland near Lake Erie. 16S rRNA gene analyses demonstrated that members of the methanotrophic Methylococcales were dominant, with the dominance largely driven by the relative abundance of four taxa, and enriched in oxic surface soils. Three methanotroph genomes from assembled soil metagenomes were assigned to the genus Methylobacter and represented the most abundant methanotrophs across the wetland. Paired metatranscriptomes confirmed that these Old Woman Creek (OWC) Methylobacter members accounted for nearly all the aerobic methanotrophic activity across two seasons. In addition to having the capacity to couple methane oxidation to aerobic respiration, these new genomes encoded denitrification potential that may sustain energy generation in soils with lower dissolved oxygen concentrations. We further show that Methylobacter members that were closely related to the OWC members were present in many other high-methane-emitting freshwater and soil sites, suggesting that this lineage could participate in methane consumption in analogous ecosystems. This work contributes to the growing body of research suggesting that Methylobacter may represent critical mediators of methane fluxes in freshwater saturated sediments and soils worldwide. IMPORTANCE Here we used soil metagenomics and metatranscriptomics to uncover novel members within the genus Methylobacter . We denote these closely related genomes as members of the lineage OWC Methylobacter . Despite the incredibly high microbial diversity in soils, here we present findings that unexpectedly showed that methane cycling was primarily mediated by a single genus for both methane production (“ Candidatus Methanothrix paradoxum”) and methane consumption (OWC Methylobacter ). Metatranscriptomic analyses revealed that decreased methanotrophic activity rather than increased methanogenic activity possibly contributed to the greater methane emissions that we had previously observed in summer months, findings important for biogeochemical methane models. Although members of this Methylococcales order have been cultivated for decades, multi-omic approaches continue to illuminate the methanotroph phylogenetic and metabolic diversity harbored in terrestrial and marine ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Quantifying vegetation and canopy structural complexity from terrestrial LiDAR data using the FORESTR R package

Terrestrial LiDAR (light detection and ranging) technologies have created new means of quantifying forest canopy structure, allowing not only the estimation of biomass, but also descriptions of the position and variability in canopy elements in space. Such measures provide novel structural information broadly useful to ecologists. There is a growing need for both a detailed taxonomy of forest canopy structural complexity (CSC) and open, transparent, and flexible tools to quantify complexity in ways that will advance foundational ecological knowledge of structure-function relationships. The CSC taxonomy we present groups structural descriptors into five categories: leaf area and density, canopy height, canopy arrangement, canopy openness, and canopy variability. This paper also introduces the r package forestr, the first open-source r package for the calculation of CSC metrics from terrestrial LiDAR data. The r package forestr is an analysis toolbox that works with portable canopy LiDAR (PCL) data and other pixelated/voxelized point clouds derived from terrestrial LiDAR scanning (TLS) data to calculate CSC metrics of interest to ecologists, modellers, forest managers, and remote sensing scientists.

52 ecosystem↗
DOE OSTI2017

Methanogenesis in oxygenated soils is a substantial fraction of wetland methane emissions

The current paradigm, widely incorporated in soil biogeochemical models, is that microbial methanogenesis can only occur in anoxic habitats. In contrast, here we show clear geochemical and biological evidence for methane production in well-oxygenated soils of a freshwater wetland. A comparison of oxic to anoxic soils reveal up to ten times greater methane production and nine times more methanogenesis activity in oxygenated soils. Metagenomic and metatranscriptomic sequencing recover the first near-complete genomes for a novel methanogen species, and show acetoclastic production from this organism was the dominant methanogenesis pathway in oxygenated soils. This organism, Candidatus Methanothrix paradoxum, is prevalent across methane emitting ecosystems, suggesting a global significance. Moreover, in this wetland, we estimate that up to 80% of methane fluxes could be attributed to methanogenesis in oxygenated soils. Together, our findings challenge a widely held assumption about methanogenesis, with significant ramifications for global methane estimates and Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Contrasting strategies of hydraulic control in two codominant temperate tree species

Biophysical controls on plant water status exist at the leaf, stem, and root levels. Therefore, we pose that hydraulic strategy is a combination of traits governing water use at each of these three levels. Here, we studied sap flux, stem water storage, stomatal conductance, photosynthesis, and growth of red oaks (Quercus rubra) and red maples (Acer rubrum). These species differ in stomatal hydraulic strategy and xylem architecture and may root at different depths. Stable isotope analysis of xylem water was used to identify root water uptake depth. Oaks were shown to access a deeper water source than maples. During non-limiting soil moisture conditions, transpiration was greater in maples than in oaks. However, during a soil dry down, transpiration and stem water storage decreased by more than 80% and 28% in maples but only by 31% and 1% in oaks. We suggest that the preferential use of deep water by red oaks allows the species to continue transpiration and growth during soil water limitations. In this case, deeper roots may provide a buffer against drought-induced mortality. Using 14 years of growth data, we show that maple growth correlates with mean annual soil moisture at 30 cm but oak growth does not. The observed responses of oak and maple to drought were not able to be explained by leaf and xylem physiology alone. Finally, we employed the Finite-difference Ecosystem-scale Tree Crown Hydrodynamics model version 2 plant hydrodynamics model to demonstrate the influence of root, stem, and leaf controls on tree-level transpiration. We conclude that all three levels of hydraulic traits are required to define hydraulic strategy.

54 ENVIRONMENTAL SCIENCES↗