Advance methodological approaches for carbon stock estimation in forest ecosystems

The forests are a key player in maintaining ecological balance on the earth. They not only conserve biodiversity, reduce soil erosion, and protect watersheds but also promote the above and below-ground ecosystem services. Forests are known as air cleaners on the planet and play a significant role in mitigating greenhouse gas (GHG) emissions into the atmosphere. As per programs launched in the Conference of Parties (COP) 26, there is a need to promote policies and programs to reduce the atmospheric carbon (C) through the forest ecosystem; it is because forests can capture the atmospheric CO₂ for a long time and help to achieve the goals of net-zero emission CO₂ on the earth. Therefore, there is an urgent need to know the advanced technological approaches for estimating C stock in forest ecosystems. Hence, the present article is aimed at providing a comprehensive protocol for the four C stock estimation approaches. An effort has also been made to compare these methods. This review suggests that tree allometry is the most common method used for the quantification of C stock, but this method has certain limitations. However, the review shows that accurate results can be produced by a combination of two or more methods. We have also analyzed the results of 42 research studies conducted for C stock assessment along with the factors determining the amount of C in different types of forests. The C stock in vegetation is affected by temporal and spatial variation, plantation age, land use, cropping pattern, management practices and elevation, etc. Nevertheless, the available results have a large degree of uncertainty mainly due to the limitations of the methods used. The review supports the conclusion that the uncertainty in C stock measurements can be addressed by the integration of the above-mentioned methods.

Understanding interactive processes: a review of CO2 flux, evapotranspiration, and energy partitioning under stressful conditions in dry forest and agricultural environments

Arid and semiarid environments are characterized by low water availability (e.g., in soil and atmosphere), high air temperature, and irregularity in the spatio-temporal distribution of rainfall. In addition to the economic and environmental consequences, drought also causes physiological damage to crops and compromises their survival in ecosystems. The removal of vegetation is responsible for altering the energy exchange of heat and water in natural ecosystems and agricultural areas. The fluxes of CO₂ are also changed, and environments with characteristics of sinks, which can be sources of CO₂ after anthropic disturbances. These changes can be measured through methods such as sap flow, eddy covariance, remote sensing, and energy balance. Despite the relevance of each method mentioned above, there are limitations in their applications that must be respected. Thus, this review aims to quantify the processes and changes of energy fluxes, CO₂, and their interactions with the surfaces of terrestrial ecosystems in dry environments. Studies report that the use of methods that integrate data from climate monitoring towers and remote sensing products helps to improve the accuracy of the determination of energy fluxes on a global scale, also helping to reduce the dissimilarity of results obtained individually. Through the collection of works in the literature, it is reported that several areas of the Brazilian Caatinga biome, which is a Seasonally Dry Tropical Forest have been suffering from changes in land use and land cover. Similar fluxes of sensible heat in areas with cacti and Caatinga can be observed in studies. On the other hand, one of the variables influenced mainly by air temperature is net radiation. In dry forest areas, woody species can store large amounts of carbon in their biomass above and belowground. The use of cacti can modify the local carbon budget when using tree crops together. Therefore, the study highlights the complexity and severity of land degradation and changes in CO₂, water, and energy fluxes in dry environments with areas of forest, grassland, and cacti. Vegetation energy balance is also a critical factor, as these simulations are helpful for use in forecasting weather or climate change. We also highlight the need for more studies that address environmental conservation techniques and cactus in the conservation of degraded areas.

Plant hydraulics, stomatal control, and the response of a tropical forest to water stress over multiple temporal scales

Many tropical regions are experiencing an intensification of drought, with increasing severity and frequency. The ecosystem response to these changes is still highly uncertain. On short time scales (from diurnal to seasonal), tropical forests respond to water stress by physiological controls, such as stomatal regulation and phenological adjustment, to cope with increasing atmospheric water demand and reduced water supply. However, the interactions among biological processes and co-varying environmental factors that determine the ecosystem-level fluxes are still unclear. Furthermore, climate variability at longer time scales, such as that generated by ENSO, produces less predictable effects because it depends on a highly stochastic combination of factors that might vary among forests and even between events in the same forest. This study will present some emerging patterns of response to water stress from 5 years of water, carbon, and energy fluxes observed on a seasonal tropical forest in central Panama, including an increase in productivity during the 2015 El Niño. These responses depend on the combination of environmental factors experienced by the forest throughout the seasonal cycle, in particular, increase in solar radiation, stimulating productivity, and increasing vapor pressure deficit (VPD) and decreasing soil moisture, limiting stomata opening. These results suggest a critical role of plant hydraulics in mediating the response to water stress over a broad range of temporal scales (diurnal, intraseasonal, seasonal, and interannual), by acclimating canopy conductance to light and VPD during different soil moisture regimes. A multilayer photosynthesis model coupled with a plant hydraulics scheme can reproduce these complex responses. However, results depend critically on parameters regulating water transport efficiency and the cost of water stress. As these costs have not been properly identified and quantified yet, more empirical research is needed to elucidate physiological mechanisms of hydraulic failure and recover, for example embolism repair and xylem regrowth.

A Review on Carbon Source and Sink in Arable Land Ecosystems

Arable land ecosystems are among the most important terrestrial systems. The issues of carbon sequestration and emission reductions in arable land ecosystems have received extensive attention. Countries around the world have actively issued policies to manage arable land ecosystems. At present, more than 100 countries have made carbon neutralization target commitments. Various arable land management measures and arable land planting strategies have important impacts on the carbon storage of arable land ecosystems. Research on arable land carbon is of great significance to global climate change. This study attempts to investigate the problems and deficiencies in the current research by summarizing a number of studies, including the main methods for the quantitative research of carbon sources and sinks as well as the influencing factors in these ecosystems. In this study, it is found that due to the differences of climate patterns, soil properties and management practices in arable land ecosystems, the factors affecting carbon sources and sinks are of great heterogeneity and complexity. Generally, variations in natural factors affect the carbon balance in different regions, while human management measures, such as irrigation, fertilization and the degree of agricultural mechanization, are the leading factors causing changes to carbon sources and sinks in these ecosystems. In addition, there are still great uncertainties in the evaluation of carbon sources and sinks in these ecosystems caused by different estimation models and methods. Therefore, emphasis should be placed on model parameter acquisition and method optimization in the future. This review provides a scientific basis for understanding carbon sources and sinks in arable land ecosystems, enhancing their carbon sink capacity and guiding low-carbon agriculture on arable land.

Would the obtainable gross primary productivity (GPP) products stand up? A critical assessment of 45 global GPP products

Gross primary productivity (GPP) is a vital variable of the global carbon cycle, but the quantification of global GPP is subject to significant uncertainty due to the lack of direct observations at a global scale. Here, we evaluated and compared 45 GPP products in terms of their applicability to different vegetation types at various spatiotemporal scales. The results show that 44 GPP products and obsGPP (Model Tree Ensemble GPP derived from observations and named obsGPP) have similar global patterns with correlation coefficients greater than 0.8 except for NGT, where GOSIF, RS, and BESS are prominent. GPP products have the greatest variation in Suriname, with a mean 75th and 25th percentile difference value of 0.4748 (normalized), and we recommend RS, SDGVM and LPJ-wsl as they provide GPP estimates close to the average GPP. In terms of seasonal estimations, considerable disagreement occurs among the GPP products in winter, with a range from 118.76 to 314.95 gC/m²/season, among which JULES has the closest GPP value to the average GPP estimation. For studies concerning vegetation types preference is given to the LUE average GPP. The 45 GPP products are more consistent on grasslands but, have obvious differences for savannas. All GPP products have their own specific spatiotemporal scales, such as global or national scales or different seasons and different vegetation types (forest, grasslands, etc.). This study provides guidelines for selecting GPP products.

Quantifying the Annual Cycle of Water Use Efficiency, Energy and CO2 Fluxes Using Micrometeorological and Physiological Techniques for a Coffee Field in Costa Rica

Coffee is one of the most commonly traded agricultural commodities globally. It is important for the livelihoods of over 25 million families worldwide, but it is also a crop sensitive to climate change, which has forced producers to implement management practices with effects on carbon balance and water use efficiency (WUE) that are not well understood due to data scarcity. From this perspective, we propose crop canopy coupling to the atmosphere (Ώ) as an index of resilience and stability. We undertook an integrated observational approach for the scaling-up of measurements along the soil–plant–atmosphere continuum at different stages of the coffee crop phenological cycle. Additionally, we develop this perspective under pronounced climatic seasonality and variability, in order to assess carbon balance, WUE, and agroecosystem resilience in a sun-grown coffee field. Further, we devised a field layout that facilitates the measurement of intrinsic, instantaneous, and actual water use efficiency and the assessment of whether coffee fields differ in canopy structure, complexity, and agronomic management and whether they are carbon sources or sinks. Partitioning soil and canopy energy balances and fluxes in a sun-grown coffee field using eco-physiological techniques at the leaf and whole plant levels (i.e., sap flow and gas exchange), as proposed here, will allow the scaling-up to whole fields in the future. Eddy covariance was used to assess real-time surface fluxes of carbon, gross primary productivity (GPP), and evapotranspiration, as well as components of the energy balance and WUE. The preliminary results support the approach used here and suggested that coffee fields are CO2 sinks throughout the year, especially during fruit development, and that the influence of seasonality drives the surface–atmosphere coupling, which is dominant prior to and during the first half of the rainy season. The estimated WUE showed consistency with independent studies in coffee crops and a marked seasonality driven by the features of the rainy season. A plan for the arborization of the coffee agroecosystem is suggested and the implications for WUE are described. Future comparison of sun- and shade-grown coffee fields and incorporation of other variables (i.e., crop coefficient-KC for different leaf area index (LAI) values) will allow us to better understand the factors controlling WUE in coffee agroecosystems.

Drainage increases CO2 and N2 O emissions from tropical peat soils

Tropical peatlands are vital ecosystems that play an important role in global carbon storage and cycles. Current estimates of greenhouse gases from these peatlands are uncertain as emissions vary with environmental conditions. This study provides the first comprehensive analysis of managed and natural tropical peatland GHG fluxes: heterotrophic (i.e. soil respiration without roots), total CO₂ respiration rates, CH₄ and N₂ O fluxes. The study documents studies that measure GHG fluxes from the soil (n = 372) from various land uses, groundwater levels and environmental conditions. We found that total soil respiration was larger in managed peat ecosystems (median = 52.3 Mg CO₂  ha^-1  year^-1 ) than in natural forest (median = 35.9 Mg CO₂  ha^-1  year^-1 ). Groundwater level had a stronger effect on soil CO₂ emission than land use. Every 100 mm drop of groundwater level caused an increase of 5.1 and 3.7 Mg CO₂  ha^-1  year^-1 for plantation and cropping land use, respectively. Where groundwater is deep (≥0.5 m), heterotrophic respiration constituted 84% of the total emissions. N₂ O emissions were significantly larger at deeper groundwater levels, where every drop in 100 mm of groundwater level resulted in an exponential emission increase (exp(0.7) kg N ha^-1  year^-1 ). Deeper groundwater levels induced high N₂ O emissions, which constitute about 15% of total GHG emissions. CH₄ emissions were large where groundwater is shallow; however, they were substantially smaller than other GHG emissions. When compared to temperate and boreal peatland soils, tropical peatlands had, on average, double the CO₂ emissions. Surprisingly, the CO₂ emission rates in tropical peatlands were in the same magnitude as tropical mineral soils. This comprehensive analysis provides a great understanding of the GHG dynamics within tropical peat soils that can be used as a guide for policymakers to create suitable programmes to manage the sustainability of peatlands effectively.

Addressing Environmental Change through Emergent Integrated Environmental Observatories: A Case Study in the Czech Republic

A growing body of scientific evidence indicates that we have entered the Anthropocene Epoch. Many assert that society has exceeded sustainable ecological planetary boundaries and that altered biogeophysical processes are no longer reversible to natural rates of ecosystem functioning. To properly and successfully address societal needs for the future, more holistic and complex methods need to be applied at various spatial and temporal scales. The increasingly interconnected nature of human and natural environments—from individuals to large megacities and entire continents and from cells through ecosystems to the biosphere as a whole (e.g., as seen in the carbon cycle)—demand new and often interdisciplinary and international approaches to address emerging global challenges. With that perspective in mind, the Czech Republic’s National Climate Program was established in 1991 with the aim to understand the impact of global environmental change on society. The National Climate Program was updated in 2017 to formulate a new Climate Protection Policy. Here, we outline the multifaceted problems that climate change poses for the Czech Republic, as well as a new scientific infrastructure and approaches directed to better understanding the effects of climate change on our ecosystems, water resources, urban environment, agriculture, human health, and general economy.

Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records

The rate of change in atmospheric CO₂ is significantly affected by the terrestrial carbon sink, but the size and spatial distribution of this sink, and the extent to which it can be enhanced to mitigate climate change are highly uncertain. We combined carbon stock (CS) and eddy covariance (EC) flux measurements that were collected over a period of 15 years (2001-2016) in a 55 year old 30 km² pine forest growing at the semiarid timberline (with no irrigating or fertilization). The objective was to constrain estimates of the carbon (C) storage potential in forest plantations in such semiarid lands, which cover ~18% of the global land area. The forest accumulated 145-160 g C m^-2  year^-1 over the study period based on the EC and CS approaches, with a mean value of 152.5 ± 30.1 g C m^-2  year^-1 indicating 20% uncertainty in carbon uptake estimates. Current total stocks are estimated at 7,943 ± 323 g C/m² and 372 g N/m² . Carbon accumulated mostly in the soil (~71% and 29% for soil and standing biomass carbon, respectively) with long soil carbon turnover time (59 years). Regardless of unexpected disturbances beyond those already observed at the study site, the results support a considerable carbon sink potential in semiarid soils and forest plantations, and imply that afforestation of even 10% of semiarid land area under conditions similar to that of the study site, could sequester ~0.4 Pg C/year over several decades.

N2O Emissions From Two Agroecosystems: High Spatial Variability and Long Pulses Observed Using Static Chambers and the Flux-Gradient Technique

With the addition of nitrogen (N), agricultural soils are the main anthropogenic source of N2O, but high spatial and temporal variabilities make N2O emissions difficult to characterize at the field scale. This study used flux-gradient measurements to continuously monitor N2O emissions at two agricultural fields under different management regimes in the inland Pacific Northwest of Washington State, USA. Automated 16-chamber arrays were also deployed at each site; chamber monitoring results aided the interpretation of the flux gradient results. The cumulative emissions over the six-month (1 April-30 September) monitoring period were 2.4 ± 0.7 and 2.1 ± 2 kg N2O-N/ha at the no-till and conventional till sites, respectively. At both sites, maximum N2O emissions occurred following the first rainfall event after N fertilization, and both sites had monthlong emission pulses. The no-till site had a larger N2O emission factor than the Intergovernmental Panel on Climate Change Tier 1 emission factor of 1% of the N input, while the conventional-till site's emission factor was close to 1% of the N input. However, these emission factors are likely conservative. We estimate that the global warming potential of the N2O emissions at these sites is larger than that of the no-till conversion carbon uptake. We recommend the use of chambers to investigate spatiotemporal controls as a complementary method to micrometeorological monitoring, especially in systems with high variability. Continued monitoring coupled with the use of models is necessary to investigate how changing management and environmental conditions will affect N2O emissions.

Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variability and CO2 trends

Remote sensing (RS)-based models play an important role in estimating and monitoring terrestrial ecosystem gross primary productivity (GPP). Several RS-based GPP models have been developed using different criteria, yet the sensitivities to environmental factors vary among models; thus, a comparison of model sensitivity is necessary for analyzing and interpreting results and for choosing suitable models. In this study, we globally evaluated and compared the sensitivities of 14 RS-based models (2 process-, 4 vegetation-index-, 5 light-use-efficiency, and 3 machine-learning-based models) and benchmarked them against GPP responses to climatic factors measured at flux sites and to elevated CO₂ concentrations measured at free-air CO₂ enrichment experiment sites. The results demonstrated that the models with relatively high sensitivity to increasing atmospheric CO₂ concentrations showed a higher increasing GPP trend. The fundamental difference in the CO₂ effect in the models' algorithm either considers the effect of CO₂ through changes in greenness indices (nine models) or introduces the influences on photosynthesis (three models). The overall effects of temperature and radiation, in terms of both magnitude and sign, vary among the models, while the models respond relatively consistently to variations in precipitation. Spatially, larger differences among model sensitivity to climatic factors occur in the tropics; at high latitudes, models have a consistent and obvious positive response to variations in temperature and radiation, and precipitation significantly enhances the GPP in mid-latitudes. Compared with the results calculated by flux-site measurements, the model performance differed substantially among different sites. However, the sensitivities of most models are basically within the confidence interval of the flux-site results. In general, the comparison revealed that models differed substantially in the effect of environmental regulations, particularly CO₂ fertilization and water stress, on GPP, and none of the models performed consistently better across the different ecosystems and under the various external conditions.

Tropical rainforest carbon sink declines during El Niño as a result of reduced photosynthesis and increased respiration rates

Changes in tropical forest carbon sink strength during El Niño Southern Oscillation (ENSO) events can indicate future behavior under climate change. Previous studies revealed ˜6 Mg C ha^-1  yr^-1 lower net ecosystem production (NEP) during ENSO year 1998 compared with non-ENSO year 2000 in a Costa Rican tropical rainforest. We explored environmental drivers of this change and examined the contributions of ecosystem respiration (RE) and gross primary production (GPP) to this weakened carbon sink. For 1998-2000, we estimated RE using chamber-based respiration measurements, and we estimated GPP in two ways: using (1) the canopy process model MAESTRA, and (2) combined eddy covariance and chamber respiration data. MAESTRA-estimated GPP did not statistically differ from GPP estimated using approach 2, but was ˜ 28% greater than published GPP estimates for the same site and years using eddy covariance data only. A 7% increase in RE (primarily increased soil respiration) and a 10% reduction in GPP contributed equally to the difference in NEP between ENSO year 1998 and non-ENSO year 2000. A warming and drying climate for tropical forests may yield a weakened carbon sink from both decreased GPP and increased RE. Understanding physiological acclimation will be critical for the large carbon stores in these ecosystems.

Grazing effects on surface energy fluxes in a desert steppe on the Mongolian Plateau

Quantifying the surface energy fluxes of grazed and ungrazed steppes is essential to understand the roles of grasslands in local and global climate and in land use change. We used paired eddy-covariance towers to investigate the effects of grazing on energy balance (EB) components: net radiation (R_n ), latent heat (LE), sensible heat (H), and soil heat (G) fluxes on adjacent grazed and ungrazed areas in a desert steppe of the Mongolian Plateau for a two-year period (2010-2012). Near 95% of R_n was partitioned as LE and H, whereas the contributions of G and other components of the EB were 5% at an annual scale. H dominated the energy partitioning and shared ~50% of R_n . When comparing the grazed and the ungrazed desert steppe, there was remarkably lower R_n and a lower H, but higher G at the grazed site than at the ungrazed site. Both reduced available energy (R_n - G) and H indicated a "cooling effect" feedback onto the local climate through grazing. Grazing reduced the dry year LE but enhanced the wet year LE. Energy partitioning of LE/R_n was positively correlated with the canopy conductivity, leaf area index, and soil moisture. H/R_n was positively correlated with the vapor pressure deficit but negatively correlated with the soil moisture. Boosted regression tree results showed that LE/R_n was dominated by soil moisture in both years and at both sites, while grazing shifted the H/R_n domination from temperature to soil moisture in the wet year. Grazing not only caused an LE shift between the dry and the wet year, but also triggered a decrease in the H/R_n because of changes in vegetation and soil properties, indicating that the ungrazed area had a greater resistance while the grazed area had a greater sensitivity of EB components to the changing climate.

Forest ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles

Eddy covariance nighttime fluxes are uncertain due to potential measurement biases. Many studies report eddy covariance nighttime flux lower than flux from extrapolated chamber measurements, despite corrections for low turbulence. We compared eddy covariance and chamber estimates of ecosystem respiration at the GLEES Ameriflux site over seven growing seasons under high turbulence [summer night mean friction velocity (u*) = 0.7 m s(-1)], during which bark beetles killed or infested 85% of the aboveground respiring biomass. Chamber-based estimates of ecosystem respiration during the growth season, developed from foliage, wood, and soil CO2 efflux measurements, declined 35% after 85% of the forest basal area had been killed or impaired by bark beetles (from 7.1 ± 0.22 μmol m(-2) s(-1) in 2005 to 4.6 ± 0.16 μmol m(-2) s(-1) in 2011). Soil efflux remained at ~3.3 μmol m(-2) s(-1) throughout the mortality, while the loss of live wood and foliage and their respiration drove the decline of the chamber estimate. Eddy covariance estimates of fluxes at night remained constant over the same period, ~3.0 μmol m(-2) s(-1) for both 2005 (intact forest) and 2011 (85% basal area killed or impaired). Eddy covariance fluxes were lower than chamber estimates of ecosystem respiration (60% lower in 2005, and 32% in 2011), but the mean night estimates from the two techniques were correlated within a year (r(2) from 0.18 to 0.60). The difference between the two techniques was not the result of inadequate turbulence, because the results were robust to a u* filter of >0.7 m s(-1). The decline in the average seasonal difference between the two techniques was strongly correlated with overstory leaf area (r(2) = 0.92). The discrepancy between methods of respiration estimation should be resolved to have confidence in ecosystem carbon flux estimates.

El Niño Southern Oscillation (ENSO) enhances CO2 exchange rates in freshwater Marsh ecosystems in the Florida everglades

This research examines the relationships between El Niño Southern Oscillation (ENSO), water level, precipitation patterns and carbon dioxide (CO₂) exchange rates in the freshwater wetland ecosystems of the Florida Everglades. Data was obtained over a 5-year study period (2009–2013) from two freshwater marsh sites located in Everglades National Park that differ in hydrology. At the short-hydroperiod site (Taylor Slough; TS) and the long-hydroperiod site (Shark River Slough; SRS) fluctuations in precipitation patterns occurred with changes in ENSO phase, suggesting that extreme ENSO phases alter Everglades hydrology which is known to have a substantial influence on ecosystem carbon dynamics. Variations in both ENSO phase and annual net CO₂ exchange rates co-occurred with changes in wet and dry season length and intensity. Combined with site-specific seasonality in CO₂ exchanges rates, El Niño and La Niña phases magnified season intensity and CO₂ exchange rates at both sites. At TS, net CO₂ uptake rates were higher in the dry season, whereas SRS had greater rates of carbon sequestration during the wet season. As La Niña phases were concurrent with drought years and extended dry seasons, TS became a greater sink for CO₂ on an annual basis (−11 to −110 g CO₂ m⁻² yr⁻¹) compared to El Niño and neutral years (−5 to −43.5 g CO₂ m⁻² yr⁻¹). SRS was a small source for CO₂ annually (1.81 to 80 g CO₂ m⁻² yr⁻¹) except in one exceptionally wet year that was associated with an El Niño phase (−16 g CO₂ m⁻² yr⁻¹). Considering that future climate predictions suggest a higher frequency and intensity in El Niño and La Niña phases, these results indicate that changes in extreme ENSO phases will significantly alter CO₂ dynamics in the Florida Everglades.

Traceable calibration, performance metrics, and uncertainty estimates of minirhizotron digital imagery for fine-root measurements

Even though fine-root turnover is a highly studied topic, it is often poorly understood as a result of uncertainties inherent in its sampling, e.g., quantifying spatial and temporal variability. While many methods exist to quantify fine-root turnover, use of minirhizotrons has increased over the last two decades, making sensor errors another source of uncertainty. Currently, no standardized methodology exists to test and compare minirhizotron camera capability, imagery, and performance. This paper presents a reproducible, laboratory-based method by which minirhizotron cameras can be tested and validated in a traceable manner. The performance of camera characteristics was identified and test criteria were developed: we quantified the precision of camera location for successive images, estimated the trueness and precision of each camera's ability to quantify root diameter and root color, and also assessed the influence of heat dissipation introduced by the minirhizotron cameras and electrical components. We report detailed and defensible metrology analyses that examine the performance of two commercially available minirhizotron cameras. These cameras performed differently with regard to the various test criteria and uncertainty analyses. We recommend a defensible metrology approach to quantify the performance of minirhizotron camera characteristics and determine sensor-related measurement uncertainties prior to field use. This approach is also extensible to other digital imagery technologies. In turn, these approaches facilitate a greater understanding of measurement uncertainties (signal-to-noise ratio) inherent in the camera performance and allow such uncertainties to be quantified and mitigated so that estimates of fine-root turnover can be more confidently quantified.

In situ CO2 efflux from leaf litter layer showed large temporal variation induced by rapid wetting and drying cycle

We performed continuous and manual in situ measurements of CO2 efflux from the leaf litter layer (R(LL)) and water content of the leaf litter layer (LWC) in conjunction with measurements of soil respiration (RS) and soil water content (SWC) in a temperate forest; our objectives were to evaluate the response of R(LL) to rainfall events and to assess temporal variation in its contribution to R(S). We measured R(LL) in a treatment area from which all potential sources of CO2 except for the leaf litter layer were removed. Capacitance sensors were used to measure LWC. R(LL) increased immediately after wetting of the leaf litter layer; peak R(LL) values were observed during or one day after rainfall events and were up to 8.6-fold larger than R(LL) prior to rainfall. R(LL) declined to pre-wetting levels within 2-4 day after rainfall events and corresponded to decreasing LWC, indicating that annual R(LL) is strongly influenced by precipitation. Temporal variation in the observed contribution of R(LL) to RS varied from nearly zero to 51%. Continuous in situ measurements of LWC and CO2 efflux from leaf litter only, combined with measurements of RS, can provide robust data to clarify the response of R(LL) to rainfall events and its contribution to total R(S).

When vegetation change alters ecosystem water availability

The combined effects of vegetation and climate change on biosphere-atmosphere water vapor (H2 O) and carbon dioxide (CO2 ) exchanges are expected to vary depending, in part, on how biotic activity is controlled by and alters water availability. This is particularly important when a change in ecosystem composition alters the fractional covers of bare soil, grass, and woody plants so as to influence the accessibility of shallower vs. deeper soil water pools. To study this, we compared 5 years of eddy covariance measurements of H2 O and CO2 fluxes over a riparian grassland, shrubland, and woodland. In comparison with the surrounding upland region, groundwater access at the riparian sites increased net carbon uptake (NEP) and evapotranspiration (ET), which were sustained over more of the year. Among the sites, the grassland used less of the stable groundwater resource, and increasing woody plant density decoupled NEP and ET from incident precipitation (P), resulting in greater exchange rates that were less variable year to year. Despite similar gross patterns, how groundwater accessibility affected NEP was more complex than ET. The grassland had higher respiration (Reco ) costs. Thus, while it had similar ET and gross carbon uptake (GEP) to the shrubland, grassland NEP was substantially less. Also, grassland carbon fluxes were more variable due to occasional flooding at the site, which both stimulated and inhibited NEP depending upon phenology. Woodland NEP was large, but surprisingly similar to the less mature, sparse shrubland, even while having much greater GEP. Woodland Reco was greater than the shrubland and responded strongly and positively to P, which resulted in a surprising negative NEP response to P. This is likely due to the large accumulation of carbon aboveground and in the surface soil. These long-term observations support the strong role that water accessibility can play when determining the consequences of ecosystem vegetation change.

Spatial variation in soil properties among North American ecosystems and guidelines for sampling designs

Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (T_s) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure T_s to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than T_s at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our continental-scale understanding of soil behavior.

Comparison of NO(x) fluxes measured by eddy covariance to emission inventories and land use

Uncertainty in emission inventories remains a critical limitation of air quality modeling and management. Using eddy covariance, we measured surface-atmosphere exchange fluxes of nitrogen oxides (NO(x)) at the neighborhood scale at 13 sites in the Norfolk, Virginia area to estimate emissions, to evaluate official inventories, and to quantify relationships between emissions and land use. Average daytime fluxes ranged from 0.4 μg m(-2) s(-1) at a site near open water to 9.5 μg m(-2) s(-1) at a site dominated by vehicle traffic. NO(x) fluxes were correlated with both road density and medium- plus high-intensity development, confirming that both motor vehicles and sources associated with development are responsible for NO(x) emissions in urban areas. Spatially averaged NO(x) fluxes measured by eddy covariance agreed to within 3% with the National Emission Inventory (NEI) but were 2.8 times higher than those in the corresponding grid cell of an emission inventory developed for air quality modeling. These average fluxes were 4.6, 4.5, and 1.7 μg m(-2) s(-1), respectively. Uncertainty in the inventories appears to be dominated by the nonroad mobile source category. It is especially important to know NO(x) emissions accurately because in certain photochemical regimes, reducing NO(x) emissions can exacerbate secondary pollutant formation.

Cyclic occurrence of fire and its role in carbon dynamics along an edaphic moisture gradient in longleaf pine ecosystems

Fire regulates the structure and function of savanna ecosystems, yet we lack understanding of how cyclic fire affects savanna carbon dynamics. Furthermore, it is largely unknown how predicted changes in climate may impact the interaction between fire and carbon cycling in these ecosystems. This study utilizes a novel combination of prescribed fire, eddy covariance (EC) and statistical techniques to investigate carbon dynamics in frequently burned longleaf pine savannas along a gradient of soil moisture availability (mesic, intermediate and xeric). This research approach allowed us to investigate the complex interactions between carbon exchange and cyclic fire along the ecological amplitude of longleaf pine. Over three years of EC measurement of net ecosystem exchange (NEE) show that the mesic site was a net carbon sink (NEE = −2.48 tonnes C ha⁻¹), while intermediate and xeric sites were net carbon sources (NEE = 1.57 and 1.46 tonnes C ha⁻¹, respectively), but when carbon losses due to fuel consumption were taken into account, all three sites were carbon sources (10.78, 7.95 and 9.69 tonnes C ha⁻¹ at the mesic, intermediate and xeric sites, respectively). Nonetheless, rates of NEE returned to pre-fire levels 1–2 months following fire. Consumption of leaf area by prescribed fire was associated with reduction in NEE post-fire, and the system quickly recovered its carbon uptake capacity 30–60 days post fire. While losses due to fire affected carbon balances on short time scales (instantaneous to a few months), drought conditions over the final two years of the study were a more important driver of net carbon loss on yearly to multi-year time scales. However, longer-term observations over greater environmental variability and additional fire cycles would help to more precisely examine interactions between fire and climate and make future predictions about carbon dynamics in these systems.

CO2, NOx, and particle emissions from aircraft and support activities at a regional airport

The goal of this research was to quantify emissions of carbon dioxide (CO(2)), nitrogen oxides (NO(x)), particle number, and black carbon (BC) from in-use aircraft and related activity at a regional airport. Pollutant concentrations were measured adjacent to the airfield and passenger terminal at the Roanoke Regional Airport in Virginia. Observed NO(x) emission indices (EIs) for jet-powered, commuter aircraft were generally lower than those contained in the International Civil Aviation Organization databank for both taxi (same as idle) and takeoff engine settings. NO(x) EIs ranged from 1.9 to 3.7 g (kg fuel)(-1) across five types of aircraft during taxiing, whereas EIs were consistently higher, 8.8-20.6 g (kg fuel)(-1), during takeoff. Particle number EIs ranged from 1.4 × 10(16) to 7.1 × 10(16) (kg fuel)(-1) and were slightly higher in taxi mode than in takeoff mode for four of the five types of aircraft. Diurnal patterns in CO(2) and NO(x) concentrations were influenced mainly by atmospheric conditions, while patterns in particle number concentrations were attributable mainly to patterns in aircraft activity. CO(2) and NO(x) fluxes measured by eddy covariance were higher at the terminal than at the airfield and were lower than found in urban areas.

Amazon rainforest exchange of carbon and subcanopy air flow: Manaus LBA site--a complex terrain condition

On the moderately complex terrain covered by dense tropical Amazon Rainforest (Reserva Biologica do Cuieiras—ZF2—02°36′17.1′′ S, 60°12′24.4′′ W), subcanopy horizontal and vertical gradients of the air temperature, CO₂ concentration and wind field were measured for the dry and wet periods in 2006. We tested the hypothesis that horizontal drainage flow over this study area is significant and can affect the interpretation of the high carbon uptake rates reported by previous works at this site. A similar experimental design as the one by Tóta et al. (2008) was used with a network of wind, air temperature, and CO₂ sensors above and below the forest canopy. A persistent and systematic subcanopy nighttime upslope (positive buoyancy) and daytime downslope (negative buoyancy) flow pattern on a moderately inclined slope (12%) was observed. The microcirculations observed above the canopy (38 m) over the sloping area during nighttime presents a downward motion indicating vertical convergence and correspondent horizontal divergence toward the valley area. During the daytime an inverse pattern was observed. The micro-circulations above the canopy were driven mainly by buoyancy balancing the pressure gradient forces. In the subcanopy space the microcirculations were also driven by the same physical mechanisms but probably with the stress forcing contribution. The results also indicated that the horizontal and vertical scalar gradients (e.g., CO₂) were modulated by these micro-circulations above and below the canopy, suggesting that estimates of advection using previous experimental approaches are not appropriate due to the tridimensional nature of the vertical and horizontal transport locally. This work also indicates that carbon budget from tower-based measurement is not enough to close the system, and one needs to include horizontal and vertical advection transport of CO₂ into those estimates.

Estimating annual CO(2) flux for Lutjewad station using three different gap-filling techniques

Long-term measurements of CO(2) flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset of hourly CO(2) flux measurements collected in Lutjewad, over a flat agriculture area near the Wadden Sea dike in the north of the Netherlands. The dataset was separated in two subsets: a learning and a validation set. The performances of gap-filling techniques were analysed by calculating statistical criteria: coefficient of determination (R(2)), root mean square error (RMSE), mean absolute error (MAE), maximum absolute error (MaxAE), and mean square bias (MSB). The gap-fill accuracy is seasonally dependent, with better results in cold seasons. The highest accuracy is obtained using ANN technique which is also less sensitive to environmental/seasonal conditions. We argue that filling gaps directly on measured CO(2) fluxes is more advantageous than the common method of filling gaps on calculated net ecosystem change, because ANN is an empirical method and smaller scatter is expected when gap filling is applied directly to measurements.