Quantifying the role of fire in the Earth system – Part 2: Impact on the net carbon balance of global terrestrial ecosystems for the 20th century

Fire is the primary form of terrestrial ecosystem disturbance on a global scale. It affects the net carbon balance of terrestrial ecosystems by emitting carbon directly and immediately into the atmosphere from biomass burning (the fire direct effect), and by changing net ecosystem productivity and land-use carbon loss in post-fire regions due to biomass burning and fire-induced vegetation mortality (the fire indirect effect). Here, we provide the first quantitative assessment of the impact of fire on the net carbon balance of global terrestrial ecosystems during the 20th century, and investigate the roles of fire's direct and indirect effects. This is done by quantifying the difference between the 20th century fire-on and fire-off simulations with the NCAR Community Land Model CLM4.5 (prescribed vegetation cover and uncoupled from the atmospheric model) as a model platform. Results show that fire decreases the net carbon gain of global terrestrial ecosystems by 1.0 Pg C yr⁻¹ averaged across the 20th century, as a result of the fire direct effect (1.9 Pg C yr^−1) partly offset by the indirect effect (−0.9 Pg C yr^−1). Post-fire regions generally experience decreased carbon gains, which is significant over tropical savannas and some North American and East Asian forests. This decrease is due to the direct effect usually exceeding the indirect effect, while they have similar spatial patterns and opposite sign. The effect of fire on the net carbon balance significantly declines until ∼1970 with a trend of 8 Tg C yr⁻¹ due to an increasing indirect effect, and increases subsequently with a trend of 18 Tg C yr⁻¹ due to an increasing direct effect. These results help constrain the global-scale dynamics of fire and the terrestrial carbon cycle

Effects of soil rewetting and thawing on soil gas fluxes: a review of current literature and suggestions for future research

The rewetting of dry soils and the thawing of frozen soils are short-term, transitional phenomena in terms of hydrology and the thermodynamics of soil systems. The impact of these short-term phenomena on larger scale ecosystem fluxes is increasingly recognized, and a growing number of studies show that these events affect fluxes of soil gases such as carbon dioxide (CO<sub>2</sub>), methane (CH<sub>4</sub>), nitrous oxide (N<sub>2</sub>O), ammonia (NH<sub>3</sub>) and nitric oxide (NO). Global climate models predict that future climatic change is likely to alter the frequency and intensity of drying-rewetting events and thawing of frozen soils. These future scenarios highlight the importance of understanding how rewetting and thawing will influence dynamics of these soil gases. This study summarizes findings using a new database containing 338 studies conducted from 1956 to 2011, and highlights open research questions. The database revealed conflicting results following rewetting and thawing in various terrestrial ecosystems and among soil gases, ranging from large increases in fluxes to non-significant changes. Studies reporting lower gas fluxes before rewetting tended to find higher post-rewetting fluxes for CO<sub>2</sub>, N<sub>2</sub>O and NO; in addition, increases in N<sub>2</sub>O flux following thawing were greater in warmer climate regions. We discuss possible mechanisms and controls that regulate flux responses, and recommend that a high temporal resolution of flux measurements is critical to capture rapid changes in gas fluxes after these soil perturbations. Finally, we propose that future studies should investigate the interactions between biological (i.e., microbial community and gas production) and physical (i.e., porosity, diffusivity, dissolution) changes in soil gas fluxes, apply techniques to capture rapid changes (i.e., automated measurements), and explore synergistic experimental and modelling approaches

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spread over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activityinfo:eu-repo/semantics/publishedVersio

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decompose the precipitation response in the RCP8.5 scenario into a CO2 portion and a non-CO2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO2-/non-CO2-forcing decomposition is applied. The methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change

Representing the function and sensitivity of coastal interfaces in Earth system models

Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth\u27s climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface. Coastal systems are hotspots of ecological, geochemical and economic activity, yet their dynamics are not accurately represented in global models. In this Review, Ward and colleagues assess the current state of coastal science and recommend approaches for including the coastal interface in predictive models

The influence of soil communities on the temperature sensitivity of soil respiration

Soil respiration represents a major carbon flux between terrestrial ecosystems and the atmosphere, and is expected to accelerate under climate warming. Despite its importance in climate change forecasts, however, our understanding of the effects of temperature on soil respiration (RS) is incomplete. Using a metabolic ecology approach we link soil biota metabolism, community composition and heterotrophic activity, to predict RS rates across five biomes. We find that accounting for the ecological mechanisms underpinning decomposition processes predicts climatological RS variations observed in an independent dataset (n = 312). The importance of community composition is evident because without it RS is substantially underestimated. With increasing temperature, we predict a latitudinal increase in RS temperature sensitivity, with Q10 values ranging between 2.33 ±0.01 in tropical forests to 2.72 ±0.03 in tundra. This global trend has been widely observed, but has not previously been linked to soil communities

Comparing ecosystem and soil respiration : Review and key challenges of tower-based and soil measurements

The net ecosystem exchange (NEE) is the difference between ecosystem CO2 assimilation and CO2 losses to the atmosphere. Ecosystem respiration (R-eco), the efflux of CO2 from the ecosystem to the atmosphere, includes the soil-to-atmosphere carbon flux (i.e., soil respiration; R-soil) and aboveground plant respiration. Therefore, R-soil is a fraction of R-eco and theoretically has to be smaller than R-eco at daily, seasonal, and annual scales. However, several studies estimating R-eco with the eddy covariance technique and measuring R-soll within the footprint of the tower have reported higher R-soil than R-eco, at different time scales. Here, we compare four different and contrasting ecosystems (from forest to grasslands, and from boreal to semiarid) to test if measurements of R-eco are consistently higher than R-soil. In general, both fluxes showed similar temporal patterns, but R-eco, was not consistently higher than R-soil from daily to annual scales across sites. We identified several issues that apply for measuring NEE and measuring/upscaling R-soil that could result in an underestimation of R-eco and/or an overestimation of R-soil. These issues are discussed based on (a) nighttime measurements of NEE, (b) R-soil measurements, and (c) the interpretation of the functional relationships of these fluxes with temperature (i.e., Q(10)). We highlight that there is still a need for better integration of R-soil with eddy covariance measurements to address challenges related to the spatial and temporal variability of R-eco, and R-soil.Peer reviewe

Approaches for advancing scientific understanding of macrosystems

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them