Geology topics

Ankur R. Desai

Publications and source records attributed to Ankur R. Desai.

16 recordsLinked to original sources

USGS2026

A cross-site comparison of ecosystem- and plot-scale methane fluxes across multiple sites

Wetland and upland ecosystems play significant but opposing roles in the global methane (CH 4 ) budget, acting as natural sources and sinks, respectively. Two of the most common approaches for measuring CH 4 fluxes (FCH 4 ) are chambers, which measure fluxes at fine spatial scales (ca. 1 m 2 ), and eddy covariance (EC) towers, which integrate fluxes across larger footprints (ca. 100–10 000 m 2 ). Although chamber and EC observations have been combined in various syntheses and databases to estimate CH 4 budgets, a unified cross-site evaluation of FCH 4 estimates at plot and ecosystem scales is lacking. As a first step toward a systematic spatiotemporal scaling of EC tower and chamber footprints, we quantified differences in site-level aggregate FCH 4 between EC and chamber measurements ( Δ FCH 4 ) across ten wetland and upland sites at half-hourly, hourly, daily, weekly, monthly, and annual timescales. We found that ecosystem-scale median FCH 4 was consistently higher than plot-scale FCH 4 at all temporal scales, with the smallest difference at the daily timescale (multi-site median Δ FCH 4 : 1.36 nmol m −2 s −1 ; median ecosystem-scale FCH 4 = 1.56 nmol m −2 s −1 , median plot-scale FCH 4 = 0.06 nmol m −2 s −1 ) and the largest at annual scales (2.58 nmol m −2 s −1 ; median ecosystem-scale FCH 4 = 25.91 nmol m −2 s −1 , median plot-scale FCH 4 = 6.55 nmol m −2 s −1 ). In general, the agreement between ecosystem- and plot-scale FCH 4 decreased with finer temporal resolution (from Spearman ρ = 0.95 at the annual scale to ρ = 0.65 at the half-hourly scale), while Δ FCH 4 variation was greatest at daily-to-annual scales. Key environmental predictors of Δ FCH 4 across the ten sites included plot-scale spatial heterogeneity, dominant vegetation type, vapor pressure deficit, atmospheric pressure, and friction velocity at the daily and monthly scales. Wind direction was a significant predictor only at the monthly scale, suggesting EC footprint effects at these sites. These findings suggest that accounting for variability in EC footprint extent, chamber measurement placement, and measurement artifacts is key to reconciling multi-scale FCH 4 observations across diverse ecosystems and refining CH 4 budgets.

Biogeosciences↗

USGS2024

Design, development, and implementation of IsoBank: A centralized repository for isotopic data

Stable isotope data have made pivotal contributions to nearly every discipline of the physical and natural sciences. As the generation and application of stable isotope data continues to grow exponentially, so does the need for a unifying data repository to improve accessibility and promote collaborative engagement. This paper provides an overview of the design, development, and implementation of IsoBank , a community-driven initiative to create an open-access repository for stable isotope data implemented online in 2021. A central goal of IsoBank is to provide a web-accessible database supporting interdisciplinary stable isotope research and educational opportunities. To achieve this goal, we convened a multi-disciplinary group of over 40 analytical experts, stable isotope researchers, database managers, and web developers to collaboratively design the database. This paper outlines the main features of IsoBank and provides a focused description of the core metadata structure. We present plans for future database and tool development and engagement across the scientific community. These efforts will help facilitate interdisciplinary collaboration among the many users of stable isotopic data while also offering useful data resources and standardization of metadata reporting across eco-geoinformatics landscapes.

PLoS ONE↗

USGS2023

On the relationship between aquatic CO2 concentration and ecosystem fluxes in some of the world’s key wetland types

To understand patterns in CO 2 partial pressure (P CO2 ) over time in wetlands’ surface water and porewater, we examined the relationship between P CO2 and land–atmosphere flux of CO 2 at the ecosystem scale at 22 Northern Hemisphere wetland sites synthesized through an open call. Sites spanned 6 major wetland types (tidal, alpine, fen, bog, marsh, and prairie pothole/karst), 7 Köppen climates, and 16 different years. Ecosystem respiration (R eco ) and gross primary production (GPP), components of vertical CO 2 flux, were compared to P CO2 , a component of lateral CO 2 flux, to determine if photosynthetic rates and soil respiration consistently influence wetland surface and porewater CO 2 concentrations across wetlands. Similar to drivers of primary productivity at the ecosystem scale, P CO2 was strongly positively correlated with air temperature (T air ) at most sites. Monthly average P CO2 tended to peak towards the middle of the year and was more strongly related to R eco than GPP. Our results suggest R eco may be related to biologically driven P CO2 in wetlands, but the relationship is site-specific and could be an artifact of differently timed seasonal cycles or other factors. Higher levels of discharge do not consistently alter the relationship between R eco and temperature normalized P CO2 . This work synthesizes relevant data and identifies key knowledge gaps in drivers of wetland respiration.

Wetlands↗

USGS2023

Practical guide to measuring wetland carbon pools and fluxes

Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions.

Wetlands↗

USGS2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Global Change Biology↗

USGS2022

Causality guided machine learning model on wetland CH4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

Agricultural and Forest Meteorology↗

USGS2021

FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands

Methane (CH 4 ) emissions from natural landscapes constitute roughly half of global CH 4 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 CH 4 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 CH 4 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-CH 4 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 CH 4 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.

Earth System Science Data↗

USGS2021

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions.

Global Change Biology↗

USGS2021

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Wetland methane (CH 4 ) emissions ( FCH 4 ) are important in global carbon budgets and climate change assessments. Currently, FCH 4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH 4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that FCH 4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH 4 and temperature using observations from the FLUXNET-CH 4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH 4 and temperature, suggesting larger FCH 4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH 4 production are thus needed to improve global CH 4 budget assessments.

Nature Communications↗

USGS2021

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

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and 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 wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed 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 realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was 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 wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

Agricultural and Forest Meteorology↗

USGS2021

Lagged wetland CH4 flux response in a historically wet year

While a stimulating effect of plant primary productivity on soil carbon dioxide (CO 2 ) emissions has been well documented, links between gross primary productivity (GPP) and wetland methane (CH 4 ) emissions are less well investigated. Determination of the influence of primary productivity on wetland CH 4 emissions (FCH 4 ) is complicated by confounding influences of water table level and temperature on CH 4 production, which also vary seasonally. Here, we evaluate the link between preceding GPP and subsequent FCH 4 at two fens in Wisconsin using eddy covariance flux towers, Lost Creek (US-Los) and Allequash Creek (US-ALQ). Both wetlands are mosaics of forested and shrub wetlands, with US-Los being larger in scale and having a more open canopy. Co-located sites with multi-year observations of flux, hydrology, and meteorology provide an opportunity to measure and compare lag effects on FCH 4 without interference due to differing climate. Daily average FCH 4 from US-Los reached a maximum of 47.7 ηmol CH 4 m −2 s −1 during the study period, while US-ALQ was more than double at 117.9 ηmol CH 4 m −2 s −1 . The lagged influence of GPP on temperature-normalized FCH 4 ( T air -FCH 4 ) was weaker and more delayed in a year with anomalously high precipitation than a following drier year at both sites. FCH 4 at US-ALQ was lower coincident with higher stream discharge in the wet year (2019), potentially due to soil gas flushing during high precipitation events and lower water temperatures. Better understanding of the lagged influence of GPP on FCH 4 due to this study has implications for climate modeling and more accurate carbon budgeting.

Journal of Geophysical Research: Biogeosciences↗

USGS2019

Wind sheltering impacts on land-atmosphere fluxes over fens

Wetlands and their ability to mitigate climate change motivates restorative and protective action; however, scientific understanding of land-atmosphere interactions is restricted by our limited continuous observations of gaseous fluxes. Many wetlands are small in spatial scale and embedded in forested landscapes. Yet, little is known about how the relative sheltering of forests affects net carbon (C) and energy balance. Here, we analyze coterminous USGS and Ameriflux eddy covariance flux tower observations over three years in two shrub fens in Northern Wisconsin, one more sheltered (US-ALQ) than the other (US-Los). Unsurprisingly, the open site showed higher overall wind speeds. This should have implications for atmospheric fluxes in wetlands as wind-forced processes are essential in promoting gas exchange over water. While both sites had similar half-hourly net ecosystem exchange of CO2 (NEE) during daytime, there were significant differences in nighttime NEE, as well as in net radiation partitioning in early spring and late summer. Sensible heat (H) fluxes were smaller at the sheltered fen except for the months of July-September. In contrast, latent heat (LE) fluxes were higher in every month except July. Additionally, sheltered fen ecosystem respiration had a weaker linear correlation with air temperature (R: 0.08 versus 0.57 for the open fen). Our work suggests that canopy sheltering does not cause significant differences in half-hourly NEE during the day, but rather the largest differences such as lower CO2 emissions occur at nighttime due to higher variance at very low wind speeds. Sheltering also influenced direction of air flow, mean wind speeds in day versus night, energy balance, and sensible and latent heat fluxes. We discuss implications of these findings for wetland restoration.

Wisconsin↗

USGS2019

FLUXNET-CH4 synthesis activity: Objectives, observations, and future directions

This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH 4 ) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH 4 flux measurements globally, initial results comparing CH 4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH 4 fluxes across sites ranged from −0.2 ± 0.02 g C m –2 yr –1 for an upland forest site to 114.9 ± 13.4 g C m –2 yr –1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m –2 yr –1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH 4 flux across wetland sites globally. Water table position was positively correlated with annual CH 4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH 4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH 4 estimates due to gap-filling and random errors were on average ±1.6 g C m –2 yr –1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH 4 flux database, the controls on ecosystem CH 4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH 4 emissions.

Bulletin of the American Meteorological Society↗

USGS2018

Toward a social-ecological theory of forest macrosystems for improved ecosystem management

The implications of cumulative land-use decisions and shifting climate on forests, require us to integrate our understanding of ecosystems, markets, policy, and resource management into a social-ecological system. Humans play a central role in macrosystem dynamics, which complicates ecological theories that do not explicitly include human interactions. These dynamics also impact ecological services and related markets, which challenges economic theory. Here, we use two forest macroscale management initiatives to develop a theoretical understanding of how management interacts with ecological functions and services at these scales and how the multiple large-scale management goals work either in consort or conflict with other forest functions and services. We suggest that calling upon theories developed for organismal ecology, ecosystem ecology, and ecological economics adds to our understanding of social-ecological macrosystems. To initiate progress, we propose future research questions to add rigor to macrosystem-scale studies: (1) What are the ecosystem functions that operate at macroscales, their necessary structural components, and how do we observe them? (2) How do systems at one scale respond if altered at another scale? (3) How do we both effectively measure these components and interactions, and communicate that information in a meaningful manner for policy and management across different scales?

Forests↗

USGS2015

Landscape-level terrestrial methane flux observed from a very tall tower

Simulating the magnitude and variability of terrestrial methane sources and sinks poses a challenge to ecosystem models because the biophysical and biogeochemical processes that lead to methane emissions from terrestrial and freshwater ecosystems are, by their nature, episodic and spatially disjunct. As a consequence, model predictions of regional methane emissions based on field campaigns from short eddy covariance towers or static chambers have large uncertainties, because measurements focused on a particular known source of methane emission will be biased compared to regional estimates with regards to magnitude, spatial scale, or frequency of these emissions. Given the relatively large importance of predicting future terrestrial methane fluxes for constraining future atmospheric methane growth rates, a clear need exists to reduce spatiotemporal uncertainties. In 2010, an Ameriflux tower (US-PFa) near Park Falls, WI, USA, was instrumented with closed-path methane flux measurements at 122 m above ground in a mixed wetland–upland landscape representative of the Great Lakes region. Two years of flux observations revealed an average annual methane (CH 4 ) efflux of 785 ± 75 mg C CH 4 m −2 yr −1 , compared to a mean CO 2 sink of −80 g C CO 2 m −2 yr −1 , a ratio of 1% in magnitude on a mole basis. Interannual variability in methane flux was 30% of the mean flux and driven by suppression of methane emissions during dry conditions in late summer 2012. Though relatively small, the magnitude of the methane source from the very tall tower measurements was mostly within the range previously measured using static chambers at nearby wetlands, but larger than a simple scaling of those fluxes to the tower footprint. Seasonal patterns in methane fluxes were similar to those simulated in the Dynamic Land Ecosystem Model (DLEM), but magnitude depends on model parameterization and input data, especially regarding wetland extent. The model was unable to simulate short-term (sub-weekly) variability. Temperature was found to be a stronger driver of regional CH 4 flux than moisture availability or net ecosystem production at the daily to monthly scale. Taken together, these results emphasize the multi-timescale dependence of drivers of regional methane flux and the importance of long, continuous time series for their characterization.

Wisconsin↗

USGS2011

Effects of biotic disturbances on forest carbon cycling in the United States and Canada

Forest insects and pathogens are major disturbance agents that have affected millions of hectares in North America in recent decades, implying significant impacts to the carbon (C) cycle. Here, we review and synthesize published studies of the effects of biotic disturbances on forest C cycling in the United States and Canada. Primary productivity in stands was reduced, sometimes considerably, immediately following insect or pathogen attack. After repeated growth reductions caused by some insects or pathogens or a single infestation by some bark beetle species, tree mortality occurred, altering productivity and decomposition. In the years following disturbance, primary productivity in some cases increased rapidly as a result of enhanced growth by surviving vegetation, and in other cases increased slowly because of lower forest regrowth. In the decades following tree mortality, decomposition increased as a result of the large amount of dead organic matter. Net ecosystem productivity decreased immediately following attack, with some studies reporting a switch to a C source to the atmosphere, and increased afterward as the forest regrew and dead organic matter decomposed. Large variability in C cycle responses arose from several factors, including type of insect or pathogen, time since disturbance, number of trees affected, and capacity of remaining vegetation to increase growth rates following outbreak. We identified significant knowledge gaps, including limited understanding of carbon cycle impacts among different biotic disturbance types (particularly pathogens), their impacts at landscape and regional scales, and limited capacity to predict disturbance events and their consequences for carbon cycling. We conclude that biotic disturbances can have major impacts on forest C stocks and fluxes and can be large enough to affect regional C cycling. However, additional research is needed to reduce the uncertainties associated with quantifying biotic disturbance effects on the North American C budget.

Global Change Biology↗