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Wildfire modifies the short- and long-term exchange of carbon between terrestrial ecosystems and the atmosphere, with impacts on ecosystem services such as carbon uptake. Dry western US forests historically experienced low-intensity, frequent fires, with patches across the landscape occupying different points in the fire-recovery trajectory. Contemporary perturbations, such as recent severe fires in California, could shift the historic stand-age distribution and impact the legacy of carbon uptake on the landscape. Here, we combine flux measurements of gross primary production (GPP) and chronosequence analysis using satellite remote sensing to investigate how the last century of fires in California impacted the dynamics of ecosystem carbon uptake on the fire-affected landscape. A GPP recovery trajectory curve of more than five thousand fires in forest ecosystems since 1919 indicated that fire reduced GPP by 157:4 ± 7:3 g C m-2 y-1(mean ± SE, n = 1926) in the first year after fire, with average recovery to prefire conditions after ~12 y. The largest fires in forested ecosystems reduced GPP by 393:8 ± 15:7 g C m-2 y-1 (n = 401) and took more than two decades to recover. Recent increases in fire severity and recovery time have led to nearly 9:9 ± 3:5 MMT CO2 (3-y rolling mean) in cumulative forgone carbon uptake due to the legacy of fires on the landscape, complicating the challenge of maintaining California's natural and working lands as a net carbon sink. Understanding these changes is paramount to weighing the costs and benefits associated with fuels management and ecosystem management for climate change mitigation. [ABSTRACT FROM AUTHOR]

Climate change is amplifying both wildfire burned area and severity, as well as incidents of drought-induced tree mortality (dieback). Direct effects from climate change amplify wildfires and episodes of drought-induced dieback have well-known impacts on forest's ability to regulate climate, provide water, and store carbon. Less understood are how past disturbances produce interaction effects that can change subsequent disturbance occurrence and intensity, with implications for management decisions that can promote forest resistance and resilience. We constructed two parallel forest chrono-sequences by combining a geospatial database of historical fire with satellite and airborne observations of forests in the Sierra Nevada of California to assess the impact of fire history on vegetation recovery, water use (evapotranspiration), and drought-induced forest dieback. We used these data sets to assess two research questions: (1.) Does fire history amplify or reduce drought-dieback intensity? (2.) What mechanisms explain how fire-induced changes to forest structure and ET alter subsequent forest dieback intensity? We show that recent fire history decreased drought-induced forest dieback intensity, compared to unburned controls. These fire-affected forests were characterized by reduced tree cover and decreased evapotranspiration, which combined to increase drought resistance more than would be expected by either effect individually. Two decades post-fire, evapotranspiration returned to pre-fire conditions. Tree and shrub cover started to approach pre-fire conditions, except for high severity fires where decreased tree cover and increased shrub cover persisted. Field based research on fuels treatments suggests that fire history may also increase longer term forest resilience. In fire-prone conifer forests, interaction effects from recent low and moderate severity fires will increase drought resistance and perhaps longer-term forest stability. • Fire history reduced tree cover and water use and increased shrub cover. • Fire history decreased forest dieback intensity compared to unburned controls. • Reduced dieback intensity suggests an antagonistic interaction effect from fire history. • Prescribed fires and low and moderate severity wildfires increased forest resistance and perhaps resilience to drought. [ABSTRACT FROM AUTHOR]

Nature-based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem-scale carbon fluxes, for example, by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state-of-the-art remote sensing products and land-surface models are not yet being widely used to inform NbCS policymaking or implementation. As a result, there is a critical mismatch between the point-and tree-scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policymaking. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. We outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem-scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre-existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach. [ABSTRACT FROM AUTHOR]

Reliable partitioning of micrometeorologically measured evapotranspiration (ET) into evaporation (E) and transpiration (T) would greatly enhance our understanding of the water cycle and its response to climate change related shifts in local‐to‐regional climate conditions and rising global levels of vapor pressure deficit (VPD). While some methods on ET partitioning have been developed, their underlying assumptions make them difficult to apply more generally, especially in sites with large contributions of E. Here, we report a novel ET partitioning method using artificial neural networks (ANNs) in combination with a range of environmental input variables to predict daytime E from nighttime ET measurements. The study uses eddy covariance data from four restored wetlands in the Sacramento‐San Joaquin Delta, California, USA, as well as leaf‐level T data for validation. The four wetlands vary in their vegetation make‐up and structure, representing a range of ET conditions. The ANNs were built with increasing complexity by adding the input variable that resulted in the next highest average value of model testing R2 across all sites. The order of variable inclusion (and importance) was: VPD > gap‐filled sensible heat flux (H_gf) > air temperature (Tair) > friction velocity (u∗) > other variables. The model using VPD, H_gf, Tair, and u∗ showed the best performance during validation with independent data and had a mean testing R2 value of 0.853 (averaged across all sites, range from 0.728 to 0.910). In comparison to other methods, our ANN method generated T/ET partitioning results which were more consistent with CO2 exchange data especially for more heterogeneous sites with large E contributions. Our method improves the understanding of T/ET partitioning. While it may be particularly suited to flooded ecosystems, it can also improve T/ET partitioning in other systems, increasing our knowledge of the global water cycle and ecosystem functioning. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the effect of land cover, atmospheric subsidence, and advection on the annual dynamics of atmospheric boundary layer (ABL) height from two contrasting sites. The first site is the Walker Branch forest, a deciduous forest of temperate climate, complex topography, and cloudy summers. The second site is the Sacramento‐San Joaquin River Delta, a site of Mediterranean climate, flat terrain on a local scale, and clear summers. After testing a new algorithm to calculate ABL heights from 915 MHz radar wind profilers, we evaluated a hierarchy of three slab models to recreate the diurnal and annual patterns of ABL growth. We found that the lower ABL heights in the Delta, particularly during late summer, are driven by the combined effects of increased atmospheric subsidence and marine air advection. In both sites, the annual pattern of ABL height was strongly correlated to total daily incoming radiation, and in the Delta, the annual pattern of ABL height closely followed the seasonal patterns of sensible heat flux from a mosaic of different land covers. A land composite of latent and sensible heat fluxes obtained through a meso‐network of eddy covariance measurements and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission resulted in higher model skill, thus showing that land cover heterogeneity is an important driver of ABL growth. Model simulations show that in the Delta, restoring agricultural land to wetlands with large open water areas could result in a reduction of ABL height during those months with low subsidence and advection. Plain Language Summary: The height of the atmospheric boundary layer drives the dilution of contaminants and other trace gases; therefore, it is of vital importance for the creation of accurate atmospheric and weather models. In this study, we report on comparisons of boundary layer height from radar wind profilers against three models with different levels of complexity in two sites with contrasting land covers. The first site is the Walker Branch forest, a forest of temperate climate, complex topography, and cloudy summers. The second site is the Sacramento‐San Joaquin River Delta in California, a site of Mediterranean climate, flat terrain, and clear summers with high rates of atmospheric subsidence and cold‐air advection from the adjacent ocean. We demonstrate that the annual cycle in boundary layer height is mostly driven by daily solar radiation in both sites; however, the presence of different land covers also has an important effect on driving the boundary layer height annual pattern, especially for those times where there is low atmospheric subsidence and advection. These results can help to understand the effects of changes in land cover on the boundary layer height and the air quality within it. Key Points: Atmospheric boundary layer (ABL) height is studied using radar wind profilers and slab models in two contrasting ecosystems over annual time scalesAtmospheric subsidence and cold‐air advection limit the growth of the boundary layer during the summer in Northern CaliforniaLand‐cover‐mediated changes in ABL height are important but muted by strong subsidence and advection [ABSTRACT FROM AUTHOR]

Inundated wetlands can potentially sequester substantial amounts of soil carbon (C) over the long-term because of slow decomposition and high primary productivity, particularly in climates with long growing seasons. Restoring such wetlands may provide one of several effective negative emission technologies to remove atmospheric CO2 and mitigate climate change. However, there remains considerable uncertainty whether these heterogeneous ecotones are consistent net C sinks and to what degree restoration and management methods affect C sequestration. Since wetland C dynamics are largely driven by climate, it is difficult to draw comparisons across regions. With many restored wetlands having different functional outcomes, we need to better understand the importance of site-specific conditions and how they change over time. We report on 21 site-years of C fluxes using eddy covariance measurements from five restored fresh to brackish wetlands in a Mediterranean climate. The wetlands ranged from 3 to 23 years after restoration and showed that several factors related to restoration methods and site conditions altered the magnitude of C sequestration by affecting vegetation cover and structure. Vegetation established within two years of re-flooding but followed different trajectories depending on design aspects, such as bathymetry-determined water levels, planting methods, and soil nutrients. A minimum of 55% vegetation cover was needed to become a net C sink, which most wetlands achieved once vegetation was established. Established wetlands had a high C sequestration efficiency (i.e. the ratio of net to gross ecosystem productivity) comparable to upland ecosystems but varied between years undergoing boom-bust growth cycles and C uptake strength was susceptible to disturbance events. We highlight the large C sequestration potential of productive inundated marshes, aided by restoration design and management targeted to maximise vegetation extent and minimise disturbance. These findings have important implications for wetland restoration, policy, and management practitioners. [ABSTRACT FROM AUTHOR]

The role of coastal mangrove wetlands in sequestering atmospheric carbon dioxide (CO2) and mitigating climate change has received increasing attention in recent years. While recent studies have shown that methane (CH4) emissions can potentially offset the carbon burial rates in low‐salinity coastal wetlands, there is hitherto a paucity of direct and year‐round measurements of ecosystem‐scale CH4 flux (FCH4) from mangrove ecosystems. In this study, we examined the temporal variations and biophysical drivers of ecosystem‐scale FCH4 in a subtropical estuarine mangrove wetland based on 3 years of eddy covariance measurements. Our results showed that daily mangrove FCH4 reached a peak of over 0.1 g CH4‐C m−2 day−1 during the summertime owing to a combination of high temperature and low salinity, while the wintertime FCH4 was negligible. In this mangrove, the mean annual CH4 emission was 11.7 ± 0.4 g CH4‐C m–2 year−1 while the annual net ecosystem CO2 exchange ranged between −891 and −690 g CO2‐C m−2 year−1, indicating a net cooling effect on climate over decadal to centurial timescales. Meanwhile, we showed that mangrove FCH4 could offset the negative radiative forcing caused by CO2 uptake by 52% and 24% over a time horizon of 20 and 100 years, respectively, based on the corresponding sustained‐flux global warming potentials. Moreover, we found that 87% and 69% of the total variance of daily FCH4 could be explained by the random forest machine learning algorithm and traditional linear regression model, respectively, with soil temperature and salinity being the most dominant controls. This study was the first of its kind to characterize ecosystem‐scale FCH4 in a mangrove wetland with long‐term eddy covariance measurements. Our findings implied that future environmental changes such as climate warming and increasing river discharge might increase CH4 emissions and hence reduce the net radiative cooling effect of estuarine mangrove forests. [ABSTRACT FROM AUTHOR]

We test the relationship between canopy photosynthesis and reflected near‐infrared radiation from vegetation across a range of functional (photosynthetic pathway and capacity) and structural conditions (leaf area index, fraction of green and dead leaves, canopy height, reproductive stage, and leaf angle inclination), weather conditions, and years using a network of field sites from across central California. We based our analysis on direct measurements of canopy photosynthesis, with eddy covariance, and measurements of reflected near‐infrared and red radiation from vegetation, with light‐emitting diode sensors. And we interpreted the observed relationships between photosynthesis and reflected near‐infrared radiation using simulations based on the multilayer, biophysical model, CanVeg. Measurements of reflected near‐infrared radiation were highly correlated with measurements of canopy photosynthesis on half‐hourly, daily, seasonal, annual, and decadal time scales across the wide range of function and structure and weather conditions. Slopes of the regression between canopy photosynthesis and reflected near‐infrared radiation were greatest for the fertilized and irrigated C4 corn crop, intermediate for the C3 tules on nutrient‐rich organic soil and nitrogen fixing alfalfa, and least for the native annual grasslands and oak savanna on nutrient‐poor, mineral soils. Reflected near‐infrared radiation from vegetation has several advantages over other remotely sensed vegetation indices that are used to infer canopy photosynthesis; it does not saturate at high leaf area indices, it is insensitive to the presence of dead legacy vegetation, the sensors are inexpensive, and the reflectance signal is strong. Hence, information on reflected near‐infrared radiation from vegetation may have utility in monitoring carbon assimilation in carbon sequestration projects or on microsatellites orbiting Earth for precision agriculture applications. Key Points: Reflected near‐infrared radiation is a strong proxy for canopy photosynthesisThis proxy works for a wide range of ecosystem structure and functionThe method has promise to be used for a variety of applications relating to carbon and water use [ABSTRACT FROM AUTHOR]

There are few observational studies measuring the ecosystem‐scale productivity effects of changes in incident diffuse photosynthetically active radiation (PARdiffuse), especially related to wildfire smoke. Climate change‐induced increases to the duration and intensity of fire conditions have made smoke a common occurrence across western North America, with largely unquantified ecosystem feedbacks. Under equivalent amounts of radiation, increased atmospheric particulate matter could lead to a boost in productivity as scattering redistributes photons throughout multilayer canopies. In this work, we leverage a meso‐network of eddy covariance measurement sites across a unique array of managed and restored C3 and C4 canopy types to understand how recent wildfire smoke affected ecosystem productivity during the summer of 2018, an especially smoky year in the agriculturally productive Central Valley. We find that diffuse PARdiffuse increased by more than a third compared to the previous growing season, while total PAR was only slightly diminished. These conditions caused nearly a doubling of light use efficiency over the range of diffuse fraction observed, with the highest sensitivity to diffuse fraction exhibited by corn and alfalfa crops. We utilized an empirical model to assess the trade‐off between enhanced diffuse fraction and reduced total PAR. Under mean radiation conditions, daily integrated gross ecosystem productivity increased by 1.2–4.2% compared to the previous growing season. Finally, we explore the potential negative effect of heightened ozone, a copollutant often associated with wildfire. In addition to the effects of wildfire smoke, the results of this natural experiment can help validate future predictions of aerosol‐productivity feedbacks. Plain Language Summary: Exacerbated by climate change, wildfire smoke is becoming a more common occurrence, especially across western North America. While we know that wildfire smoke has negative health impacts for humans, there is evidence that it could increase plant productivity. This occurs due to the way that smoke scatters incoming sunlight, allowing the Sun's energy to reach further into dense plant canopies. Here, we measure the impacts of wildfire smoke on vegetation productivity across a range of vegetation types, all with different canopy structures and physiological function, during the summer of 2018, an especially smoky year in the agriculturally productive Central Valley. We find that smoky conditions increased the efficiency by which these plant canopies photosynthesized, leading to productivity increases, depending on trade‐offs with total light and other pollutants. Key Points: Historically large wildfires caused heightened smoke particulate that increased the fraction of diffuse radiation during the growing seasonLight use efficiency, the ratio of productivity to absorbed radiation, was nearly doubled during smoke events at crop and wetland land usesProductivity enhancements depend on the trade‐off between reduced total radiation and increased diffuse radiation [ABSTRACT FROM AUTHOR]

Abstract: Wetlands are the largest source of methane (CH4) globally, yet our understanding of how process‐level controls scale to ecosystem fluxes remains limited. It is particularly uncertain how variable soil properties influence ecosystem CH4 emissions on annual time scales. We measured ecosystem carbon dioxide (CO2) and CH4 fluxes by eddy covariance from two wetlands recently restored on peat and alluvium soils within the Sacramento–San Joaquin Delta of California. Annual CH4 fluxes from the alluvium wetland were significantly lower than the peat site for multiple years following restoration, but these differences were not explained by variation in dominant climate drivers or productivity across wetlands. Soil iron (Fe) concentrations were significantly higher in alluvium soils, and alluvium CH4 fluxes were decoupled from plant processes compared with the peat site, as expected when Fe reduction inhibits CH4 production in the rhizosphere. Soil carbon content and CO2 uptake rates did not vary across wetlands and, thus, could also be ruled out as drivers of initial CH4 flux differences. Differences in wetland CH4 fluxes across soil types were transient; alluvium wetland fluxes were similar to peat wetland fluxes 3 years after restoration. Changing alluvium CH4 emissions with time could not be explained by an empirical model based on dominant CH4 flux biophysical drivers, suggesting that other factors, not measured by our eddy covariance towers, were responsible for these changes. Recently accreted alluvium soils were less acidic and contained more reduced Fe compared with the pre‐restoration parent soils, suggesting that CH4 emissions increased as conditions became more favorable to methanogenesis within wetland sediments. This study suggests that alluvium soil properties, likely Fe content, are capable of inhibiting ecosystem‐scale wetland CH4 flux, but these effects appear to be transient without continued input of alluvium to wetland sediments. [ABSTRACT FROM AUTHOR]

Abstract: Land use change and management affect climate by altering both the biogeochemical and biophysical interactions between the land and atmosphere. Whereas climate policy often emphasizes the biogeochemical impact of land use change, biophysical impacts, including changes in reflectance, energy partitioning among sensible and latent heat exchange, and surface roughness, can attenuate or enhance biogeochemical effects at local to regional scales. This study analyzes 3 years (2015–2017) of turbulent flux and meteorological data across three contrasting wetland restoration sites and one agricultural site, colocated in the Sacramento‐San Joaquin Delta, California, USA, to understand if the biophysical impacts of freshwater wetland restoration can be expected to attenuate or enhance the potential biogeochemical benefits. We show that despite absorbing more net radiation, restored wetlands have the potential to cool daytime surface temperature by up to 5.1  °C, as compared to a dominant drained agricultural land use. Wetland canopy structure largely determines the magnitude of surface temperature cooling, with wetlands that contain areas of open water leading to enhanced nighttime latent heat flux and reduced diurnal temperate range. Daytime surface cooling could be important in ameliorating physiological stress associated with hotter and drier conditions and could also promote boundary layer feedbacks at the local to regional scale. With a renewed focus on the mitigation and adaptation potential of natural and working lands, we must better understand the role of biophysical changes, especially in novel land use transitions like wetland restoration. [ABSTRACT FROM AUTHOR]

Abstract: Peatland drainage is an important driver of global soil carbon loss and carbon dioxide (CO2) emissions. Restoration of peatlands by reflooding reverses CO2 losses at the cost of increased methane (CH4) emissions, presenting a biogeochemical compromise. While restoring peatlands is a potentially effective method for sequestering carbon, the terms of this compromise are not well constrained. Here we present 14 site years of continuous CH4 and CO2 ecosystem‐scale gas exchange over a network of restored freshwater wetlands in California, where long growing seasons, warm weather, and managed water tables result in some of the largest wetland ecosystem CH4 emissions recorded. These large CH4 emissions cause the wetlands to be strong greenhouse gas sources while sequestering carbon and building peat soil. The terms of this biogeochemical compromise, dictated by the ratio between carbon sequestration and CH4 emission, vary considerably across small spatial scales, despite nearly identical wetland climate, hydrology, and plant community compositions. [ABSTRACT FROM AUTHOR]

The energy delivered to the land surface via insolation is a primary driver of evapotranspiration (ET)—the exchange of water vapor between the land and atmosphere. Spatially distributed ET products are in great demand in the water resource management community for real-time operations and sustainable water use planning. The accuracy and deliverability of these products are determined in part by the characteristics and quality of the insolation data sources used as input to the ET models. This paper investigates the practical utility of three different insolation datasets within the context of a satellite-based remote sensing framework for mapping ET at high spatiotemporal resolution, in an application over the Sacramento–San Joaquin Delta region in California. The datasets tested included one reanalysis product: The Climate System Forecast Reanalysis (CFSR) at 0.25° spatial resolution, and two remote sensing insolation products generated with geostationary satellite imagery: a product for the continental United States at 0.2°, developed by the University of Wisconsin Space Sciences and Engineering Center (SSEC) and a coarser resolution (1°) global Clouds and the Earth's Radiant Energy System (CERES) product. The three insolation data sources were compared to pyranometer data collected at flux towers within the Delta region to establish relative accuracy. The satellite products significantly outperformed CFSR, with root-mean square errors (RMSE) of 2.7, 1.5, and 1.4 MJ·m−2·d−1 for CFSR, CERES, and SSEC, respectively, at daily timesteps. The satellite-based products provided more accurate estimates of cloud occurrence and radiation transmission, while the reanalysis tended to underestimate solar radiation under cloudy-sky conditions. However, this difference in insolation performance did not translate into comparable improvement in the ET retrieval accuracy, where the RMSE in daily ET was 0.98 and 0.94 mm d−1 using the CFSR and SSEC insolation data sources, respectively, for all the flux sites combined. The lack of a notable impact on the aggregate ET performance may be due in part to the predominantly clear-sky conditions prevalent in central California, under which the reanalysis and satellite-based insolation data sources have comparable accuracy. While satellite-based insolation data could improve ET retrieval in more humid regions with greater cloud-cover frequency, over the California Delta and climatologically similar regions in the western U.S., the CFSR data may suffice for real-time ET modeling efforts. [ABSTRACT FROM AUTHOR]

The ability to accurately monitor and anticipate changes in consumptive water use associated with changing land use and land management is critical to developing sustainable water management strategies in water-limited climatic regions. In this paper, we present an application of a remote sensing data fusion technique for developing high spatiotemporal resolution maps of evapotranspiration (ET) at scales that can be associated with changes in land use. The fusion approach combines ET map timeseries developed using an multi-scale energy balance algorithm applied to thermal data from Earth observation platforms with high spatial but low temporal resolution (e.g., Landsat) and with moderate resolution but frequent temporal coverage (e.g., MODIS (Moderate Resolution Imaging Spectroradiometer)). The approach is applied over the Sacramento-San Joaquin Delta region in California—an area critical to both agricultural production and drinking water supply within the state that has recently experienced stresses on water resources due to a multi-year (2012–2017) extreme drought. ET “datacubes” with 30-m resolution and daily timesteps were constructed for the 2015–2016 water years and related to detailed maps of land use developed at the same spatial scale. The ET retrievals are evaluated at flux sites over multiple land covers to establish a metric of accuracy in the annual water use estimates, yielding root-mean-square errors of 1.0, 0.8, and 0.3 mm day−1 at daily, monthly, and yearly timesteps, respectively, for all sites combined. Annual ET averaged over the Delta changed only 3 mm year−1 between water years, from 822 to 819 mm year−1, translating to an area-integrated total change in consumptive water use of seven thousand acre-feet (TAF). Changes were largest in areas with recorded land-use change between water years—most significantly, fallowing of crop land presumably in response to reductions in water availability and allocations due to the drought. Moreover, the time evolution in water use associated with wetland restoration—an effort aimed at reducing subsidence and carbon emissions within the inner Delta—is assessed using a sample wetland chronosequence. Region-specific matrices of consumptive water use associated with land use changes may be an effective tool for policymakers and farmers to understand how land use conversion could impact consumptive use and demand. [ABSTRACT FROM AUTHOR]