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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13157-023-01722-2.

AmeriFlux BASE data pipeline to support network growth and data sharing

AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.

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

Wetlands are the largest natural source of methane (CH₄ ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH₄ , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH₄ 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 CH₄ 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, CH₄ production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH₄ emissions. Based on a sensitivity analysis, CH₄ 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 CH₄ transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH₄ production and CH₄ 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 CH₄ 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 CH₄ emissions across biomes. These processes and associated parameters for CH₄ emissions among and within the wetlands provide useful insights for interpreting observed net CH₄ fluxes, estimating sensitivities to biophysical variables, and modeling global CH₄ fluxes.

Detecting Hot Spots of Methane Flux Using Footprint-Weighted Flux Maps

In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH₄) flux. In the first part of the study, we used a CH₄ release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint-Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH₄ release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH₄ flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m^-2 s^-1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m^-2 s^-1. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy-covariance towers and creates important insights for the interpretation of hot spots of CH₄ flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH₄ flux.

Cross-biome synthesis of source versus sink limits to tree growth

Uncertainties surrounding tree carbon allocation to growth are a major limitation to projections of forest carbon sequestration and response to climate change. The prevalence and extent to which carbon assimilation (source) or cambial activity (sink) mediate wood production are fundamentally important and remain elusive. We quantified source-sink relations across biomes by combining eddy-covariance gross primary production with extensive on-site and regional tree ring observations. We found widespread temporal decoupling between carbon assimilation and tree growth, underpinned by contrasting climatic sensitivities of these two processes. Substantial differences in assimilation-growth decoupling between angiosperms and gymnosperms were determined, as well as stronger decoupling with canopy closure, aridity, and decreasing temperatures. Our results reveal pervasive sink control over tree growth that is likely to be increasingly prominent under global climate change.

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots, and microbes, and gradients in water potential drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in-situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely-sensed proxies. Together, these considerations offer a roadmap for clearer links between ecohydrological processes and the water potential gradients that have the 'potential' to substantially reduce conceptual and modeling uncertainties.

A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems

It is well documented that energy balance and other remote sensing-based evapotranspiration (ET) models face greater uncertainty over water-limited tree-grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass-dominated understory and tree-dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy-limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal-based three-source energy balance (3SEB) model, accommodating an additional vegetation source within the well-known two-source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy-covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m² ; MSG: LE RMSD ~90 W/m² ), improving over both TSEB and seasonally changing TSEB (TSEB-2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.

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

While wetlands are the largest natural source of methane (CH₄ ) to the atmosphere, they represent a large source of uncertainty in the global CH₄ budget due to the complex biogeochemical controls on CH₄ dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH₄ 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 CH₄ . 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 CH₄ 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 CH₄ emissions.

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] 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 CH4 production are thus needed to improve global CH4 budget assessments.

On the inter- and intra-annual variability of ecosystem evapotranspiration and water use efficiency of an oak savanna and annual grassland subjected to booms and busts in rainfall

Whether annual evapotranspiration of native ecosystems is increasing or decreasing with time as CO₂ concentrations are rising, the climate is warming and rainfall experiences booms and busts, remains an unanswered question in the field of global change biology. To answer this question, we measured evapotranspiration and carbon dioxide exchange over and under an oak savanna and over an annual grassland in the Mediterranean climate of California, USA, from 2001 through 2019 with the eddy covariance method; during this 19-year period, CO₂ rose 40 ppm, air temperature increased by 1°C and annual rainfall ranged between 133 and 890 mm/year. No temporal trend in evapotranspiration or water use efficiency was observed over this time duration. Many competing positive and negative feedbacks among stomatal sensitivity to carbon dioxide concentrations, soil moisture, and vapor pressure deficit, the impact of temperature on saturation vapor pressure and access to groundwater muted the response of evapotranspiration to its changing world when integrated to the ecosystem scale and annual time steps. At the intra-annual time scale, we found that plants transmit information on soil moisture status through their influence on the vapor pressure deficit of the atmospheric boundary layer. The inter-annual variations in evaporative water use by the savanna and annual grassland were relatively decoupled from the booms and busts in rainfall. Instead, variations in length of growing season and access to groundwater explained much of this year-to-year variation in annual evapotranspiration. The access of groundwater by the oak savanna may make these ecosystems more robust in a warmer world, than was previously thought. This is a scale emergent property that needs better consideration in coupled climate-ecosystem models.

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

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO₂ flux, commonly though imprecisely termed soil respiration (R_S ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency R_S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R_S , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Soil thawing regulates the spring growth onset in tundra and alpine biomes

Soil temperature remains isothermal at 0 °C and water shifts to a liquid phase during soil thawing. Vegetation may receive this process as a signal and a key to restore physiological activity. We aimed to show the relationship between the timing of soil thawing and the spring growth onset. We estimated the delay between the soil thawing and the spring growth onset in 78 sites of the FLUXNET network. We built a soil thawing map derived from modeling for the northern hemisphere and related it to the greenness onset estimated with satellite imagery. Spring onset estimated with GPP time series occurred shortly after soil surface thawing in tundra (1.1 ± 3.5 days) and alpine grasslands (16.6 ± 5.8 days). The association was weaker for deciduous forests (40.3 ± 4.2 days), especially where soils freeze infrequently. Needleleaved forests tended to start the growing season before the end of thawing (-17.4 ± 3.6 days), although observations from remote sensing (MODIS Land Cover Dynamics) indicated that the onset of greenness started after the thawing period (26.8 ± 3.2 days). This study highlights the role of soil temperature at the spring growth onset at high latitudes. Soil thawing becomes less relevant in temperate forests, where soil is occasionally frozen and other climate factors become more important.

Methane emissions reduce the radiative cooling effect of a subtropical estuarine mangrove wetland by half

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 (F_CH4 ) from mangrove ecosystems. In this study, we examined the temporal variations and biophysical drivers of ecosystem-scale F_CH4 in a subtropical estuarine mangrove wetland based on 3 years of eddy covariance measurements. Our results showed that daily mangrove F_CH4 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 F_CH4 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 F_CH4 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 F_CH4 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 F_CH4 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.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO₂, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Measurement(s)	net ecosystem exchange • carbon dioxide • water • energy
Technology Type(s)	eddy covariance • measurement device
Sample Characteristic - Environment	terrestrial biome • atmosphere
Sample Characteristic - Location	Earth (planet)

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12295910

Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis

Methane flux (FCH₄ ) measurements using the eddy covariance technique have increased over the past decade. FCH₄ measurements commonly include data gaps, as is the case with CO₂ and energy fluxes. However, gap-filling FCH₄ data are more challenging than other fluxes due to its unique characteristics including multidriver dependency, variabilities across multiple timescales, nonstationarity, spatial heterogeneity of flux footprints, and lagged influence of biophysical drivers. Some researchers have applied a marginal distribution sampling (MDS) algorithm, a standard gap-filling method for other fluxes, to FCH₄ datasets, and others have applied artificial neural networks (ANN) to resolve the challenging characteristics of FCH₄ . However, there is still no consensus regarding FCH₄ gap-filling methods due to limited comparative research. We are not aware of the applications of machine learning (ML) algorithms beyond ANN to FCH₄ datasets. Here, we compare the performance of MDS and three ML algorithms (ANN, random forest [RF], and support vector machine [SVM]) using multiple combinations of ancillary variables. In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH₄ and reduce the internal complexity of the algorithmic structures. We applied this approach to five benchmark FCH₄ datasets from both natural and managed systems located in temperate and tropical wetlands and rice paddies. Results indicate that PCA improved the performance of MDS compared to traditional inputs. ML algorithms performed better when using all available biophysical variables compared to using PCA-derived inputs. Overall, RF was found to outperform other techniques for all sites. We found gap-filling uncertainty is much larger than measurement uncertainty in accumulated CH₄ budget. Therefore, the approach used for FCH₄ gap filling can have important implications for characterizing annual ecosystem-scale methane budgets, the accuracy of which is important for evaluating natural and managed systems and their interactions with global change processes.

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

The physics and ecology of mining carbon dioxide from the atmosphere by ecosystems

Reforesting and managing ecosystems have been proposed as ways to mitigate global warming and offset anthropogenic carbon emissions. The intent of our opinion piece is to provide a perspective on how well plants and ecosystems sequester carbon. The ability of individual plants and ecosystems to mine carbon dioxide from the atmosphere, as defined by rates and cumulative amounts, is limited by laws of physics and ecological principles. Consequently, the rates and amount of net carbon uptake are slow and low compared to the rates and amounts of carbon dioxide we release by fossil fuels combustion. Managing ecosystems to sequester carbon can also cause unintended consequences to arise. In this paper, we articulate a series of key take-home points. First, the potential amount of carbon an ecosystem can assimilate on an annual basis scales with absorbed sunlight, which varies with latitude, leaf area index and available water. Second, efforts to improve photosynthesis will come with the cost of more respiration. Third, the rates and amount of net carbon uptake are relatively slow and low, compared to the rates and amounts and rates of carbon dioxide we release by fossil fuels combustion. Fourth, huge amounts of land area for ecosystems will be needed to be an effective carbon sink to mitigate anthropogenic carbon emissions. Fifth, the effectiveness of using this land as a carbon sink will depend on its ability to remain as a permanent carbon sink. Sixth, converting land to forests or wetlands may have unintended costs that warm the local climate, such as changing albedo, increasing surface roughness or releasing other greenhouse gases. We based our analysis on 1,163 site-years of direct eddy covariance measurements of gross and net carbon fluxes from 155 sites across the globe.

Widespread inhibition of daytime ecosystem respiration

The global land surface absorbs about a third of anthropogenic emissions each year, due to the difference between two key processes: ecosystem photosynthesis and respiration. Despite the importance of these two processes, it is not possible to measure either at the ecosystem scale during the daytime. Eddy-covariance measurements are widely used as the closest 'quasi-direct' ecosystem-scale observation from which to estimate ecosystem photosynthesis and respiration. Recent research, however, suggests that current estimates may be biased by up to 25%, due to a previously unaccounted for process: the inhibition of leaf respiration in the light. Yet the extent of inhibition remains debated, and implications for estimates of ecosystem-scale respiration and photosynthesis remain unquantified. Here, we quantify an apparent inhibition of daytime ecosystem respiration across the global FLUXNET eddy-covariance network and identify a pervasive influence that varies by season and ecosystem type. We develop partitioning methods that can detect an apparent ecosystem-scale inhibition of daytime respiration and find that diurnal patterns of ecosystem respiration might be markedly different than previously thought. The results call for the re-evaluation of global terrestrial carbon cycle models and also suggest that current global estimates of photosynthesis and respiration may be biased, some on the order of magnitude of anthropogenic fossil fuel emissions.

A New Data Set to Keep a Sharper Eye on Land-Air Exchanges

FLUXNET15, the latest update of the longest global record of ecosystem carbon, water, and energy fluxes, features improved data quality, new data products, and more open data sharing policies.

Terrestrial Carbon Cycle Variability

A growing literature is reporting on how the terrestrial carbon cycle is experiencing year-to-year variability because of climate anomalies and trends caused by global change. As CO ₂ concentration records in the atmosphere exceed 50 years and as satellite records reach over 30 years in length, we are becoming better able to address carbon cycle variability and trends. Here we review how variable the carbon cycle is, how large the trends in its gross and net fluxes are, and how well the signal can be separated from noise. We explore mechanisms that explain year-to-year variability and trends by deconstructing the global carbon budget.

The CO ₂ concentration record is detecting a significant increase in the seasonal amplitude between 1958 and now. Inferential methods provide a variety of explanations for this result, but a conclusive attribution remains elusive. Scientists have reported that this trend is a consequence of the greening of the biosphere, stronger northern latitude photosynthesis, more photosynthesis by semi-arid ecosystems, agriculture and the green revolution, tropical temperature anomalies, or increased winter respiration.

At the global scale, variability in the terrestrial carbon cycle can be due to changes in constituent fluxes, gross primary productivity, plant respiration and heterotrophic (microbial) respiration, and losses due to fire, land use change, soil erosion, or harvesting. It remains controversial whether or not there is a significant trend in global primary productivity (due to rising CO ₂, temperature, nitrogen deposition, changing land use, and preponderance of wet and dry regions). The degree to which year-to-year variability in temperature and precipitation anomalies affect global primary productivity also remains uncertain. For perspective, interannual variability in global gross primary productivity is relatively small (on the order of 2 Pg-C y ^-1) with respect to a large and uncertain background (123 +/- 4 Pg-C y ^-1), and detected trends in global primary productivity are even smaller (33 Tg-C y ^-2). Yet residual carbon balance methods infer that the terrestrial biosphere is experiencing a significant and growing carbon sink. Possible explanations for this large and growing net land sink include roles of land use change and greening of the land, regional enhancement of photosynthesis, and down regulation of plant and soil respiration with warming temperatures. Longer time series of variables needed to provide top-down and bottom-up assessments of the carbon cycle are needed to resolve these pressing and unresolved issues regarding how, why, and at what rates gross and net carbon fluxes are changing.

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

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

Measuring fluxes of trace gases and energy between ecosystems and the atmosphere - the state and future of the eddy covariance method

The application of the eddy covariance flux method to measure fluxes of trace gas and energy between ecosystems and the atmosphere has exploded over the past 25 years. This opinion paper provides a perspective on the contributions and future opportunities of the eddy covariance method. First, the paper discusses the pros and cons of this method relative to other methods used to measure the exchange of trace gases between ecosystems and the atmosphere. Second, it discusses how the use of eddy covariance method has grown and evolved. Today, more than 400 flux measurement sites are operating world-wide and the duration of the time series exceed a decade at dozens of sites. Networks of tower sites now enable scientists to ask scientific questions related to climatic and ecological gradients, disturbance, changes in land use, and management. The paper ends with discussions on where the field of flux measurement is heading. Topics discussed include role of open access data sharing and data mining, in this new era of big data, and opportunities new sensors that measure a variety of trace gases, like volatile organic carbon compounds, methane and nitrous oxide, and aerosols, may yield.

Causality and persistence in ecological systems: a nonparametric spectral granger causality approach

Abstract Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made difficult by the action of periodic drivers overlapping the natural dynamics of the system. Periodicity in the drivers can often mask the self-sustained oscillations originating from the autonomous dynamics. While linear and direct causal relationships are commonly addressed in the time domain, using the well-established machinery of Granger causality (G-causality), the presence of periodic forcing requires frequency-based statistics (e.g., the Fourier transform), able to distinguish coupling induced by oscillations in external drivers from genuine endogenous interactions. Recent nonparametric spectral extensions of G-causality to the frequency domain pave the way for the scale-by-scale decomposition of causality, which can improve our ability to link oscillatory behaviors of ecological networks to causal mechanisms. The performance of both spectral G-causality and its conditional extension for multivariate systems is explored in quantifying causal interactions within ecological networks. Through two case studies involving synthetic and actual time series, it is demonstrated that conditional G-causality outperforms standard G-causality in identifying causal links and their concomitant timescales.

Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

Climate and vegetation controls on boreal zone energy exchange

The boreal forest, one of the world's larger biomes, is distinct from other biomes because it experiences a short growing season and extremely cold winter temperatures. Despite its size and impact on the earth's climate system, measurements of mass and energy exchange have been rare until the past five years. This paper overviews results of recent and comprehensive field studies conducted in Canada, Siberia and Scandinavia on energy exchanges between boreal forests and the atmosphere. How the boreal biosphere and atmosphere interact to affect the interception of solar energy and how solar energy is used to evaporate water and heat the air and soil is examined in detail. Specifically, we analyse the magnitudes, temporal and spatial patterns and controls of solar energy, moisture and sensible heat fluxes across the land-atmosphere interface. We interpret and synthesize field data with the aid of a soil-vegetation-atmosphere transfer model, which considers the coupling of the energy and carbon fluxes and nutrient status. Low precipitation and low temperatures limit growth of many boreal forests. These factors restrict photosynthetic capacity and lower root hydraulic conductivity and stomatal conductance of the inhabitant forests. In such circumstances, these factors interact to form a canopy that has a low leaf area index and exerts a significant resistance to evaporation. Conifer forests, growing on upland soils, for example, evaporate at rates between 25 and 75% of equilibrium evaporation and lose less than 2.5 mm day^-1 of water. The open nature of many boreal conifer forest stands causes a disproportionate amount of energy exchange to occur at the soil surface. The climatic and physiological factors that yield relatively low rates of evaporation over conifer stands also cause high rates of sensible heat exchange and the diurnal development of deep planetary boundary layers. In contrast, evaporation from broad-leaved aspen stands and fen/wetlands approach equilibrium evaporation rates and lose up to 6 mm day^-1 .

Arctic and boreal ecosystems of western North America as components of the climate system

Synthesis of results from several Arctic and boreal research programmes provides evidence for the strong role of high-latitude ecosystems in the climate system. Average surface air temperature has increased 0.3 °C per decade during the twentieth century in the western North American Arctic and boreal forest zones. Precipitation has also increased, but changes in soil moisture are uncertain. Disturbance rates have increased in the boreal forest; for example, there has been a doubling of the area burned in North America in the past 20 years. The disturbance regime in tundra may not have changed. Tundra has a 3-6-fold higher winter albedo than boreal forest, but summer albedo and energy partitioning differ more strongly among ecosystems within either tundra or boreal forest than between these two biomes. This indicates a need to improve our understanding of vegetation dynamics within, as well as between, biomes. If regional surface warming were to continue, changes in albedo and energy absorption would likely act as a positive feedback to regional warming due to earlier melting of snow and, over the long term, the northward movement of treeline. Surface drying and a change in dominance from mosses to vascular plants would also enhance sensible heat flux and regional warming in tundra. In the boreal forest of western North America, deciduous forests have twice the albedo of conifer forests in both winter and summer, 50-80% higher evapotranspiration, and therefore only 30-50% of the sensible heat flux of conifers in summer. Therefore, a warming-induced increase in fire frequency that increased the proportion of deciduous forests in the landscape, would act as a negative feedback to regional warming. Changes in thermokarst and the aerial extent of wetlands, lakes, and ponds would alter high-latitude methane flux. There is currently a wide discrepancy among estimates of the size and direction of CO₂ flux between high-latitude ecosystems and the atmosphere. These discrepancies relate more strongly to the approach and assumptions for extrapolation than to inconsistencies in the underlying data. Inverse modelling from atmospheric CO₂ concentrations suggests that high latitudes are neutral or net sinks for atmospheric CO₂ , whereas field measurements suggest that high latitudes are neutral or a net CO₂ source. Both approaches rely on assumptions that are difficult to verify. The most parsimonious explanation of the available data is that drying in tundra and disturbance in boreal forest enhance CO₂ efflux. Nevertheless, many areas of both tundra and boreal forests remain net sinks due to regional variation in climate and local variation in topographically determined soil moisture. Improved understanding of the role of high-latitude ecosystems in the climate system requires a concerted research effort that focuses on geographical variation in the processes controlling land-atmosphere exchange, species composition, and ecosystem structure. Future studies must be conducted over a long enough time-period to detect and quantify ecosystem feedbacks.

An analytical solution for coupled leaf photosynthesis and stomatal conductance models

Iterative solutions of coupled leaf photosynthesis and stomatal conductance equations sometimes yield bifurcated or chaotic solutions. An analytical solution for coupled leaf photosynthesis-stomatal conductance equations is preferred because an analytical model has specific and known roots, and partial derivatives can be taken to perform sensitivity analyses. I present an analytical solution for coupled leaf photosynthesis and stomatal conductance equations that are based on established biochemical and physiological theory.