COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data

Estimating soil N2O emissions induced by organic and inorganic fertilizer inputs using a Tier-2, regression-based meta-analytic approach for U.S. agricultural lands

Consistent methods are essential for generating country and region-specific estimates of greenhouse gas (GHG) emissions used for reporting and policymaking. The estimates of direct N2O emissions from U.S. agricultural soils have primarily relied on the use of emission factors (EFs, Tier-1) and process-based models (Tier-3). However, Tier-1 estimates are relatively crude while Tier-3 calculations can be costly. This work addressed this gap by developing a Tier-2, regression-based approach by leveraging a meta-database containing 1883 field N2O observations together with environmental and management covariates from 139 studies. Our results estimated higher monthly soil N2O emissions (N2Om, kg N/ha) during the growing season (0.38) than the fallow period (0.15), highlighting the importance of considering measurement periods when utilizing meta-databases for analyzing N2O drivers. Significantly different N2Om were found for tillage practices (conventional > no-till: 0.42 > 0.27), fertilizer type (liquid > solid manure: 0.55 > 0.32), and soil texture (fine > coarse: 0.36 > 0.22). The comparisons of the influence of crop type and rotation, water management, and soil order on N2O emissions are complicated by regional data availability and interactions among different factors. Additionally, the finding that N2O emissions reported based on area (N2Om), N input rate (EF), or yield can alter treatment rankings underscores the need to establish transparent criteria for rewarding or discouraging regionally-based management practices using N2O metrics. Finally, we show how General Linear Models (GLMs) can be used to estimate country and regional Tier-2 N2Om using a suite of covariates. Our GLMs identified tillage, water management, N input type and rate, soil properties, and elevation as the most influential covariates for the conterminous U.S. The limited accuracy of regional-scale GLMs, however, suggests the need to further improve the quality and availability of GHG and covariate data through concerted efforts in data collection.

Chronological dataset of soil respiration fluxes from a seasonally dry forest in Northwest México

Soil respiration (CO2 emission to the atmosphere from soils) is an important component of the global carbon cycle. In highly seasonal ecosystems the magnitudes and the underlying mechanisms that control soil respiration (RS) are still poorly understood and measurements are underrepresented in the global flux community. In this dataset, systematic and monthly measurements of RS were conducted with an infrared gas analyzer coupled to a static chamber during 2015, 2016, 2017 and 2019 in a tropical dry forest with a land use history from Northwestern México. These data is useful to assess the intra-annual and seasonal variations of RS at a highly seasonal dry forests and serves as a base line to benchmark soil carbon models in regional and global contexts. The data presented supports the research manuscript: "Soil respiration is influenced by seasonality, forest succession and contrasting biophysical controls in a tropical dry forest in Northwestern Mexico" from Vargas-Terminel et al. [1].

Wetting-induced soil CO2 emission pulses are driven by interactions among soil temperature, carbon, and nitrogen limitation in the Colorado Desert

Warming-induced changes in precipitation regimes, coupled with anthropogenically enhanced nitrogen (N) deposition, are likely to increase the prevalence, duration, and magnitude of soil respiration pulses following wetting via interactions among temperature and carbon (C) and N availability. Quantifying the importance of these interactive controls on soil respiration is a key challenge as pulses can be large terrestrial sources of atmospheric carbon dioxide (CO₂ ) over comparatively short timescales. Using an automated sensor system, we measured soil CO₂ flux dynamics in the Colorado Desert-a system characterized by pronounced transitions from dry-to-wet soil conditions-through a multi-year series of experimental wetting campaigns. Experimental manipulations included combinations of C and N additions across a range of ambient temperatures and across five sites varying in atmospheric N deposition. We found soil CO₂ pulses following wetting were highly predictable from peak instantaneous CO₂ flux measurements. CO₂ pulses consistently increased with temperature, and temperature at time of wetting positively correlated to CO₂ pulse magnitude. Experimentally adding N along the N deposition gradient generated contrasting pulse responses: adding N increased CO₂ pulses in low N deposition sites, whereas adding N decreased CO₂ pulses in high N deposition sites. At a low N deposition site, simultaneous additions of C and N during wetting led to the highest observed soil CO₂ fluxes reported globally at 299.5 μmol CO₂  m^-2  s^-1 . Our results suggest that soils have the capacity to emit high amounts of CO₂ within small timeframes following infrequent wetting, and pulse sizes reflect a non-linear combination of soil resource and temperature interactions. Importantly, the largest soil CO₂ emissions occurred when multiple resources were amended simultaneously in historically resource-limited desert soils, pointing to regions experiencing simultaneous effects of desertification and urbanization as key locations in future global C balance.

Warming and drought weaken the carbon sink capacity of an endangered paleoendemic temperate rainforest in South America

Measurements of ecosystem carbon (C) fluxes in temperate forests are concentrated in the Northern Hemisphere, leaving the functionally diverse temperate forests in the Southern Hemisphere underrepresented. Here, we report three years (February 2018-January 2021) of C fluxes, studied with eddy-covariance and closed chamber techniques, in an endangered temperate evergreen rainforest of the long-lived paleoendemic South American conifer Fitzroya cupressoides. Using classification and regression trees we analyzed the most relevant drivers and thresholds of daily net ecosystem exchange (NEE) and soil respiration. The annual NEE showed that the forest was a moderate C sink during the period analyzed (-287±38 g C m^-2 year ^-1). We found that the capacity to capture C of the Fitzroya rainforests in the Coastal Range of southern Chile is optimal under cool and rainy conditions in the early austral spring (October-November) and decreases rapidly towards the summer dry season (January-February) and autumn. Although the studied forest type has a narrow geographical coverage, the gross primary productivity measured at the tower was highly representative of Fitzroya and other rainforests in the region. Our results suggest that C fluxes in paleoendemic cool F. cupressoides forests may be negatively affected by the warming and drying predicted by climate change models, reinforcing the importance of maintaining this and other long-term ecological research sites in the Southern Hemisphere.

Mechanistically-grounded pathways connect remotely sensed canopy structure to soil respiration

Variation in the soil-to-atmosphere C flux, or soil respiration (R_s), is influenced by a suite of biotic and abiotic factors, including soil temperature, soil moisture, and root biomass. However, whether light detection and ranging (lidar)-derived canopy structure is tied to soil respiration through its simultaneous influence over these drivers is not known. We assessed relationships between measures of above- and belowground vegetation density and complexity, and evaluated whether R_s is linked to remotely sensed canopy structure through pathways mediated by established biotic and abiotic mechanisms. Our results revealed that, at the stand-scale, canopy rugosity-a measure of complexity-and vegetation area index were coupled to soil respiration through their effects on light interception, soil microclimate, and fine root mass density, but this connection was stronger for complexity. Canopy and root complexity were not spatially coupled at the stand-scale, with canopy but not root complexity increasing through stand development. Our findings suggest that remotely sensed canopy complexity could be used to infer spatial variation in R_s, and that this relationship is grounded in known mechanistic pathways. The broad spatial inference of soil respiration via remotely sensed canopy complexity requires multi-site observations of canopy structure and R_s, which is possible given burgeoning open data from ecological networks and satellite remote sensing platforms.

Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO₂ exchange, soil CO₂ efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSC_i ), C translocation (dC_i ), and the biomass production efficiency (BPE_i ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dC_i and BPE_i varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPE_bgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil-plant-climate interactions.

Informing Nature-based Climate Solutions for the United States with the best-available science

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.

Low N2O and variable CH4 fluxes from tropical forest soils of the Congo Basin

Globally, tropical forests are assumed to be an important source of atmospheric nitrous oxide (N₂O) and sink for methane (CH₄). Yet, although the Congo Basin comprises the second largest tropical forest and is considered the most pristine large basin left on Earth, in situ N₂O and CH₄ flux measurements are scarce. Here, we provide multi-year data derived from on-ground soil flux (n = 1558) and riverine dissolved gas concentration (n = 332) measurements spanning montane, swamp, and lowland forests. Each forest type core monitoring site was sampled at least for one hydrological year between 2016 - 2020 at a frequency of 7-14 days. We estimate a terrestrial CH₄ uptake (in kg CH₄-C ha⁻¹ yr⁻¹) for montane (−4.28) and lowland forests (−3.52) and a massive CH₄ release from swamp forests (non-inundated 2.68; inundated 341). All investigated forest types were a N₂O source (except for inundated swamp forest) with 0.93, 1.56, 3.5, and −0.19 kg N₂O-N ha⁻¹ yr⁻¹ for montane, lowland, non-inundated swamp, and inundated swamp forests, respectively.

The Congo Basin is home to the second largest stretch of continuous tropical forest, but the magnitude of greenhouse fluxes are poorly understood. Here the authors analyze gas samples and find the region is not actually a hotspot of N2O emissions.

Spatial biases of information influence global estimates of soil respiration: How can we improve global predictions?

Soil respiration (Rs), the efflux of CO₂ from soils to the atmosphere, is a major component of the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The global soil respiration database (SRDB) is a compilation of in situ Rs observations from around the globe that has been consistently updated with new measurements over the past decade. It is unclear whether the addition of data to new versions has produced better-constrained global Rs estimates. We compared two versions of the SRDB (v3.0 n = 5173 and v5.0 n = 10,366) to determine how additional data influenced global Rs annual sum, spatial patterns and associated uncertainty (1 km spatial resolution) using a machine learning approach. A quantile regression forest model parameterized using SRDBv3 yielded a global Rs sum of 88.6 Pg C year^-1 , and associated uncertainty of 29.9 (mean absolute error) and 57.9 (standard deviation) Pg C year^-1 , whereas parameterization using SRDBv5 yielded 96.5 Pg C year^-1 and associated uncertainty of 30.2 (mean average error) and 73.4 (standard deviation) Pg C year^-1 . Empirically estimated global heterotrophic respiration (Rh) from v3 and v5 were 49.9-50.2 (mean 50.1) and 53.3-53.5 (mean 53.4) Pg C year^-1 , respectively. SRDBv5's inclusion of new data from underrepresented regions (e.g., Asia, Africa, South America) resulted in overall higher model uncertainty. The largest differences between models parameterized with different SRDVB versions were in arid/semi-arid regions. The SRDBv5 is still biased toward northern latitudes and temperate zones, so we tested an optimized global distribution of Rs measurements, which resulted in a global sum of 96.4 ± 21.4 Pg C year^-1 with an overall lower model uncertainty. These results support current global estimates of Rs but highlight spatial biases that influence model parameterization and interpretation and provide insights for design of environmental networks to improve global-scale Rs estimates.

Extreme heat events heighten soil respiration

In the wake of climate change, extreme events such as heatwaves are considered to be key players in the terrestrial biosphere. In the past decades, the frequency and severity of heatwaves have risen substantially, and they are projected to continue to intensify in the future. One key question is therefore: how do changes in extreme heatwaves affect the carbon cycle? Although soil respiration (Rs) is the second largest contributor to the carbon cycle, the impacts of heatwaves on Rs have not been fully understood. Using a unique set of continuous high frequency in-situ measurements from our field site, we characterize the relationship between Rs and heatwaves. We further compare the Rs response to heatwaves across ten additional sites spanning the contiguous United States (CONUS). Applying a probabilistic framework, we conclude that during heatwaves Rs rates increase significantly, on average, by ~ 26% relative to that of non-heatwave conditions over the CONUS. Since previous in-situ observations have not measured the Rs response to heatwaves (e.g., rate, amount) at the high frequency that we present here, the terrestrial feedback to the carbon cycle may be underestimated without capturing these high frequency extreme heatwave events.

Long term effects of fire on the soil greenhouse gas balance of an old-growth temperate rainforest

Forest fires can cause great changes in the composition, structure and functioning of forest ecosystems. We studied the effects of a fire that occurred >50 years ago in a temperate rainforest that caused flooding conditions in a Placic Andosol to evaluate how long these effects last; we hypothesized that the effects of fire on the soil greenhouse gas (GHG) balance could last for many years. We made monthly measurements of fluxes of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) during two years of soils in an unburned forest (UF) and a nearby site that burned >50 years ago (BS). Our results show that CO₂ emissions from soils were higher in the UF than in the BS, and positively correlated with temperature and negatively with soil water content at both sites. Both sites were net CH₄ sinks (higher in the UF) and fluxes correlated positively with soil water content and negatively with temperature (stronger relation in the BS). Emissions of N₂O were low at both sites and showed correlation with friction velocity at the UF site. The soil GHG balance showed that the UF emitted about 80% more than the BS (5079 ± 1772 and 2815 ± 1447 g CO₂-eq m^-2 y^-1, respectively). Combining our measured fluxes with data of CO₂ net ecosystem exchange, we estimated that at the ecosystem level, the UF was a GHG sink while the BS was a source, showing a long-lasting effect of the fire and the importance of preserving these forest ecosystems.