Jaclyn Hatala Matthes

Agricultural peatland restoration: effects of land-use change on greenhouse gas (CO2 and CH4) fluxes in the Sacramento-San Joaquin Delta

Agricultural drainage of organic soils has resulted in vast soil subsidence and contributed to increased atmospheric carbon dioxide (CO2) concentrations. The Sacramento-San Joaquin Delta in California was drained over a century ago for agriculture and human settlement and has since experienced subsidence rates that are among the highest in the world. It is recognized that drained agriculture in the Delta is unsustainable in the long-term, and to help reverse subsidence and capture carbon (C) there is an interest in restoring drained agricultural land-use types to flooded conditions. However, flooding may increase methane (CH4) emissions. We conducted a full year of simultaneous eddy covariance measurements at two conventional drained agricultural peatlands (a pasture and a corn field) and three flooded land-use types (a rice paddy and two restored wetlands) to assess the impact of drained to flooded land-use change on CO2 and CH4 fluxes in the Delta. We found that the drained sites were net C and greenhouse gas (GHG) sources, releasing up to 341 g C m(-2) yr(-1) as CO2 and 11.4 g C m(-2) yr(-1) as CH4. Conversely, the restored wetlands were net sinks of atmospheric CO2, sequestering up to 397 g C m(-2) yr(-1). However, they were large sources of CH4, with emissions ranging from 39 to 53 g C m(-2) yr(-1). In terms of the full GHG budget, the restored wetlands could be either GHG sources or sinks. Although the rice paddy was a small atmospheric CO2 sink, when considering harvest and CH4 emissions, it acted as both a C and GHG source. Annual photosynthesis was similar between sites, but flooding at the restored sites inhibited ecosystem respiration, making them net CO2 sinks. This study suggests that converting drained agricultural peat soils to flooded land-use types can help reduce or reverse soil subsidence and reduce GHG emissions.

The uncertain climate footprint of wetlands under human pressure

Significance Wetlands are unique ecosystems because they are in general sinks for carbon dioxide and sources of methane. Their climate footprint therefore depends on the relative sign and magnitude of the land–atmosphere exchange of these two major greenhouse gases. This work presents a synthesis of simultaneous measurements of carbon dioxide and methane fluxes to assess the radiative forcing of natural wetlands converted to agricultural or forested land. The net climate impact of wetlands is strongly dependent on whether they are natural or managed. Here we show that the conversion of natural wetlands produces a significant increase of the atmospheric radiative forcing. The findings suggest that management plans for these complex ecosystems should carefully account for the potential biogeochemical effects on climate. Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

Identifying scale‐emergent, nonlinear, asynchronous processes of wetland methane exchange

Methane (CH4) exchange in wetlands is complex, involving nonlinear asynchronous processes across diverse time scales. These processes and time scales are poorly characterized at the whole-ecosystem level, yet are crucial for accurate representation of CH4 exchange in process models. We used a combination of wavelet analysis and information theory to analyze interactions between whole-ecosystem CH4 flux and biophysical drivers in two restored wetlands of Northern California from hourly to seasonal time scales, explicitly questioning assumptions of linear, synchronous, single-scale analysis. Although seasonal variability in CH4 exchange was dominantly and synchronously controlled by soil temperature, water table fluctuations, and plant activity were important synchronous and asynchronous controls at shorter time scales that propagated to the seasonal scale. Intermittent, subsurface water table decline promoted short-term pulses of methane emission but ultimately decreased seasonal CH4 emission through subsequent inhibition after rewetting. Methane efflux also shared information with evapotranspiration from hourly to multiday scales and the strength and timing of hourly and diel interactions suggested the strong importance of internal gas transport in regulating short-term emission. Traditional linear correlation analysis was generally capable of capturing the major diel and seasonal relationships, but mesoscale, asynchronous interactions and nonlinear, cross-scale effects were unresolved yet important for a deeper understanding of methane flux dynamics. We encourage wider use of these methods to aid interpretation and modeling of long-term continuous measurements of trace gas and energy exchange.

Parsing the variability in CH4 flux at a spatially heterogeneous wetland: Integrating multiple eddy covariance towers with high‐resolution flux footprint analysis

Restored wetlands are a complex mosaic of open water and new and old emergent vegetation patches, where multiple environmental and biological drivers contribute to the measured heterogeneity in methane (CH4) flux. In this analysis, we replicated the measurements of CH4 flux using the eddy covariance technique at three tower locations within the same wetland site to parse the spatiotemporal variability in CH4 flux contributed by large-scale seasonal variations in climate and phenology and short-term variations in flux footprint movement over a mosaic of vegetation and open water. Using a hierarchical statistical model accounting for site-level environmental effects, tower-level footprint and biological effects, and temporal autocorrelation, we partitioned the key drivers of the daily CH4 flux variability among the three replicated towers. The daily mean air temperature and mean friction velocity, a measure of momentum transfer, explained a significant variability in CH4 flux across the three towers, and the abundance and spatial aggregation of vegetation in the flux footprint along with the daily gross primary productivity explained much of the tower-level variability. This statistical model captured 67% of the total variance in the daily integrated growing season CH4 fluxes at this site, which bridged an order of magnitude from 80 to 480 mg C m−2 d−1 during the measurement period from 10 May 2012 to 24 October 2012.

A general ecophysiological framework for modelling the impact of pests and pathogens on forest ecosystems.

Forest insects and pathogens (FIPs) have enormous impacts on community dynamics, carbon storage and ecosystem services, however, ecosystem modelling of FIPs is limited due to their variability in severity and extent. We present a general framework for modelling FIP disturbances through their impacts on tree ecophysiology. Five pathways are identified as the basis for functional groupings: increases in leaf, stem and root turnover, and reductions in phloem and xylem transport. A simple ecophysiological model was used to explore the sensitivity of forest growth, mortality and ecosystem fluxes to varying outbreak severity. Across all pathways, low infection was associated with growth reduction but limited mortality. Moderate infection led to individual tree mortality, whereas high levels led to stand-level die-offs delayed over multiple years. Delayed mortality is consistent with observations and critical for capturing biophysical, biogeochemical and successional responses. This framework enables novel predictions under present and future global change scenarios.

Biophysical controls on interannual variability in ecosystem-scale CO2 and CH4 exchange in a California rice paddy

We present 6.5 years of eddy covariance measurements of fluxes of methane (FCH4) and carbon dioxide (FCO2) from a flooded rice paddy in Northern California, USA. A pronounced warming trend throughout the study associated with drought and record high temperatures strongly influenced carbon (C) budgets and provided insights into biophysical controls of FCO2 and FCH4. Wavelet analysis indicated that photosynthesis (gross ecosystem production, GEP) induced the diel pattern in FCH4, but soil temperature (Ts) modulated its amplitude. Forward stepwise linear models and neural networking modeling were used to assess the variables regulating seasonal FCH4. As expected due to their competence in modeling nonlinear relationships, neural network models explained considerably more of the variance in daily average FCH4 than linear models. During the growing season, GEP and water levels typically explained most of the variance in daily average FCH4. However, Ts explained much of the interannual variability in annual and growing season CH4 sums. Higher Ts also increased the annual and growing season ratio of FCH4 to GEP. The observation that the FCH4 to GEP ratio scales predictably with Ts may help improve global estimates of FCH4 from rice agriculture. Additionally, Ts strongly influenced ecosystem respiration, resulting in large interannual variability in the net C budget at the paddy, emphasizing the need for long-term measurements particularly under changing climatic conditions.

The contribution of an overlooked transport process to a wetland's methane emissions

Wetland methane transport processes affect what portion of methane produced in wetlands reaches the atmosphere. We model what has been perceived to be the least important of these transport processes: hydrodynamic transport of methane through wetland surface water and show that its contribution to total methane emissions from a temperate freshwater marsh is surprisingly large. In our 1 year study, hydrodynamic transport comprised more than half of nighttime methane fluxes and was driven primarily by water column thermal convection occurring overnight as the water surface cooled. Overall, hydrodynamic transport was responsible for 32% of annual methane emissions. Many methane models have overlooked this process, but our results show that wetland methane fluxes cannot always be accurately described using only other transport processes (plant-mediated transport and ebullition). Modifying models to include hydrodynamic transport and the mechanisms that drive it, particularly convection, could help improve predictions of future wetland methane emissions.

Variation of energy and carbon fluxes from a restored temperate freshwater wetland and implications for carbon market verification protocols

Temperate freshwater wetlands are among the most productive terrestrial ecosystems, stimulating interest in using restored wetlands as biological carbon sequestration projects for greenhouse gas reduction programs. In this study, we used the eddy covariance technique to measure surface energy carbon fluxes from a constructed, impounded freshwater wetland during two annual periods that were 8 years apart: 2002–2003 and 2010–2011. During 2010–2011, we measured methane (CH4) fluxes to quantify the annual atmospheric carbon mass balance and its concomitant influence on global warming potential (GWP). Peak growing season fluxes of latent heat and carbon dioxide (CO2) were greater in 2002–2003 compared to 2010–2011. In 2002, the daily net ecosystem exchange reached as low as −10.6 g C m−2 d−1, which was greater than 3 times the magnitude observed in 2010 (−2.9 g C m−2 d−1). CH4 fluxes during 2010–2011 were positive throughout the year and followed a strong seasonal pattern, ranging from 38.1 mg C m−2 d−1 in the winter to 375.9 mg C m−2 d−1 during the summer. The results of this study suggest that the wetland had reduced gross ecosystem productivity in 2010–2011, likely due to the increase in dead plant biomass (standing litter) that inhibited the generation of new vegetation growth. In 2010–2011, there was a net positive GWP (675.3 g C m−2 yr−1), and when these values are evaluated as a sustained flux, the wetland will not reach radiative balance even after 500 years.

Benchmarking historical CMIP5 plant functional types across the Upper Midwest and Northeastern United States

Centennial-scale climate-ecosystem feedbacks are a major source of predictive uncertainty for land-atmosphere fluxes of energy, carbon, and water. Accurate representations of plant functional type (PFT) distributions through time and space are required for modeling centennial-scale feedbacks within Earth system models (ESMs). We tested the ability of ESMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to capture historical PFT distributions at the time of Euro-American settlement in the Northeastern United States against a new subcontinental-scale data set of historical tree abundances derived from forest composition surveys. To identify and diagnose errors in ESM-simulated PFT distributions and quantify impacts on modeled albedo, net primary productivity, and transpiration, we analyzed actual and modeled PFT distributions with respect to historical mean annual climate and modeled elasticity among PFTs, climate, and vegetation-atmosphere fluxes. Historical PFT distributions were poorly matched between ESMs and the settlement-era data, often due to inaccurate PFT-climate relationships within ESMs, particularly for evergreen trees. Some models exhibited large local, but regionally compensating, errors in simulated albedo, net primary productivity, and transpiration due to inaccurate PFT distributions, while others had systematic regional biases in vegetation-atmosphere fluxes. Internal variable elasticity varied among ESMs, and these differences closely corresponded to model skill in predicting PFT distributions. New historical benchmarks like the settlement-era vegetation data provide opportunities to confront ESMs, parse sources of error, and improve simulations of historical and future vegetation-atmosphere feedbacks.

Changes in Forest Composition, Stem Density, and Biomass from the Settlement Era (1800s) to Present in the Upper Midwestern United States

EuroAmerican land use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Gridded (8×8km) estimates of pre-settlement (1800s) forests from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan) using 19th Century Public Land Survey (PLS) records provide relative composition, biomass, stem density, and basal area for 26 tree genera. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection. We compare pre-settlement to modern forests using Forest Inventory and Analysis (FIA) data, with respect to structural changes and the prevalence of lost forests, pre-settlement forests with no current analogue, and novel forests, modern forests with no past analogs. Differences between PLSS and FIA forests are spatially structured as a result of differences in the underlying ecology and land use impacts in the Upper Midwestern United States. Modern biomass is higher than pre-settlement biomass in the northwest (Minnesota and northeastern Wisconsin, including regions that were historically open savanna), and lower in the east (eastern Wisconsin and Michigan), due to shifts in species composition and, presumably, average stand age. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 29% of all FIA cells, while 25% of pre-settlement forests no longer exist in a modern context. Lost forests are centered around the forests of the Tension Zone, particularly in hemlock dominated forests of north-central Wisconsin, and in oak-elm-basswood forests along the forest-prairie boundary in south central Minnesota and eastern Wisconsin. Novel FIA forest assemblages are distributed evenly across the region, but novelty shows a strong relationship to spatial distance from remnant forests in the upper Midwest, with novelty predicted at between 20 to 60km from remnants, depending on historical forest type. The spatial relationships between remnant and novel forests, shifts in ecotone structure and the loss of historic forest types point to significant challenges to land managers if landscape restoration is a priority in the region. The spatial signals of novelty and ecological change also point to potential challenges in using modern spatial distributions of species and communities and their relationship to underlying geophysical and climatic attributes in understanding potential responses to changing climate. The signal of human settlement on modern forests is broad, spatially varying and acts to homogenize modern forests relative to their historic counterparts, with significant implications for future management.