Quantify Ecosystem Carbon Research Articles

Quantifying seaweed and seagrass beach deposits using high-resolution UAV imagery

Macroalgae and seagrass wash ashore by tidal waters and episodic events and create an ocean-to-land transport of carbon and nutrients. On land, these deposits (beach wrack) are consumed by macrofauna, remineralized by microorganisms, or washed back to the sea, during which recycling of carbon and nitrogen affect the biochemical cycles in coastal zones. Manual quantification of beach wracks is time-consuming and often difficult due to complex topography and remote locations. Here, we present a novel method using Unoccupied Aerial Vehicle (UAV) photogrammetry combined with in situ measurements of carbon and nitrogen contents of wrack to quantify marine carbon and nutrient deposits in beach zones. The UAV method was tested against placed cubes ranging from 125 to 88,218 cm3 and demonstrated a high accuracy (R2 > 0.99) for volume acquisition when compared to manual measurements. Also, the UAV-based assessments of the cross-sectional area of beach deposits demonstrated a high accuracy when compared to manual and high-precision GNSS (Global Navigation Satellite System) measurements without significant differences between the methods. This demonstrated that UAVs can provide detailed spatial maps, three-dimensional (3D) surface models, and accurate volumetric assessments of beach wrack deposits. In three case studies, combined with carbon and nitrogen measures, total organic carbon and nitrogen deposits in beach wracks were quantified ranging from 4.3 to 9.7 and from 0.3 to 0.5 kg per meter coastline, respectively. In conclusion, this UAV method demonstrated an effective tool to quantify ecosystem carbon and nitrogen deposits relevant to ecosystem assessments and quantification of blue carbon stocks. The method is optimal when the terrain below beach wrack deposits is known, as in the case with before-and-after or repeated surveys. Further, UAVs display strong time- and cost-effective advantages over manual methods which is amplified with increasing project scale. We propose it as a valuable method for multiple scientific and commercial applications related to environmental monitoring and management, including marine resource exploration and exploitation.

Can seasonal fire management reduce the risk of carbon loss from wildfires in a protected Guinea savanna?

AbstractFire is fundamental to the functioning of tropical savannas and routinely used as a management tool. Shifting prescribed burning from later to earlier in the growing season has the potential to reduce greenhouse gas emissions. However, large uncertainties surround the impact of seasonal burning on longer term plant and soil carbon sequestration. In this study, we quantify ecosystem carbon storage across burn seasons and histories in a wet‐to‐mesic Guinea tropical savanna in Mole National Park, Ghana. Aboveground (plant and litter) and belowground (soil plus roots) carbon storage was quantified across four burning seasons and histories: recent (<3 years) early‐season burns, recent late‐season burns, old (>4 years) late‐season burns, and long‐unburned (>15 years) sites. We found that recent late‐season burns significantly lowered belowground carbon storage to a depth of 17 cm compared with all other burn seasons and histories. Belowground carbon was 1.2 kg C m−2, or 27% lower, for recent late‐season burns compared with prescribed early‐season burns. However, in older late‐season burns sites, belowground carbon “recovered” after 4–13 burn years to comparable storage as long‐unburned and early‐season burn sites. For most aboveground carbon pools, there was no significant difference in carbon storage across burn seasons and histories, except higher aboveground tree carbon in long‐unburned sites. We suggest that observed changes in belowground carbon are likely due to the turnover and production of root carbon. Prescribed early‐season burning is promoted to reduce greenhouse gas emissions and our findings affirm that early‐season burning has limited impact on plant and soil carbon stocks compared with long‐unburned sites. While early‐season burning regimes will have some patches that become late‐season wildfires, our results suggest on balance early‐season burning regimes are a low‐risk land management practice in reducing plant and soil carbon storage losses and sustaining a patch‐mosaicked landscape with multiple other ecosystem service benefits for savannas.

Comparison of C3 Photosynthetic Responses to Light and CO2 Predicted by the Leaf Photosynthesis Models of Farquhar et al. (1980) and Goudriaan et al. (1985)

AbstractThe leaf photosynthesis models developed by Farquhar et al. (1980, https://doi.org/10.1007/BF00386231) (FvCB) and Goudriaan et al. (1985, https://doi.org/10.1007/978‐1‐4899‐3665‐3_10) (G85) are both used in Earth system and weather models to quantify ecosystem carbon assimilation. Despite their common role, a systematic comparison between these two photosynthesis models is currently lacking in scientific literature. In this technical report we compared the two models in a systematic way. Hereto we performed a comparative analysis of the model structures as well as the modeled responses of photosynthesis to light and CO2 at leaf level. To facilitate future model comparison, we also constructed a lookup table that presents FvCB model parameters fitted to CO2‐response curves from G85 in a wide natural range in photosynthetic capacity at standardized temperature. The structure of the FvCB model differs fundamentally from the G85 model as the FvCB model considers rate‐limiting processes due to Rubisco capacity, electron transport and triose phosphate utilization in parallel, whereas the G85 model considers Rubisco activity and triose phosphate utilization limitation to act in series scaled with quantum use efficiency. The models also differ fundamentally in terms of the parametrization of dark respiration. Still, both models calculate near‐similar responses of photosynthesis to changes in light and CO2 across a wide range in photosynthetic capacity with only two free parameters each. Our work thereby highlights functional similarities between these model approaches despite fundamental differences in model structure. Hence, standardized parameter sets that yield similar photosynthesis responses to light and CO2 may facilitate intercomparison of Earth system and weather models.

Discursive and biophysical dimensions of land sparing policies in Laos: Implications for greenhouse gas emissions and food security

Land-use competition between forest conservation and agricultural food production poses major threats to climate change mitigation and food security. Land sparing policies aim at reconciling this conundrum by intensifying agriculture while conserving forests, but scientific debates prevail about their effectiveness. To contribute to this debate, we analyze the discursive dimension of land sparing efforts and their biophysical implications for Lao PDR. Applying an interdisciplinary mixed-methods approach, we examine how Lao land-use policies legitimize land sparing at the cost of shifting cultivation and how land use changed between 2000 and 2019. We quantify ecosystem carbon fluxes and agricultural emissions and investigate trends in agricultural production and food security. We find that policy documents use both socio-economic and environmental arguments to substantiate land sparing at the expense of shifting cultivation. In biophysical terms, the stabilization of shifting cultivation enhanced the recovery of some forest areas resulting in gross carbon sequestration while ecosystems in total remained a net source of emissions. Concomitant agricultural intensification improved dietary energy supply, reduced the prevalence of undernourishment, and increased agricultural exports. However, cropland expansion and the intensification of agriculture entailed greenhouse gas emissions of similar extent as the continuing shifting cultivation, and could not prevent the prevalence of moderate or severe food insecurity in the total population until today. We conclude that the narrow focus of land-use policies on land sparing falls short in effectively balancing societal needs and ecosystem functions.

Increased Interception Induced by Vegetation Restoration Counters Ecosystem Carbon and Water Exchange Efficiency in China

AbstractChanges in ecosystem water use efficiency (WUE) and evapotranspiration (ET) that are driven by vegetation change can be used as metrics to quantify ecosystem carbon and water exchange. The effect of vegetation on WUE has been explored in the past through consideration of total ET. However, interception (Ei) doesn't directly participate in ecosystem carbon and water exchange, and uncertainty of modeled Ei, resulting in great uncertainty of ET partitioning and ecosystem WUE. Here, we estimated Ei in China using Gerrits' model, replacing the algorithm for Ei in the Priestley‐Taylor Jet Propulsion Laboratory (PT‐JPL) model. The modified PT‐JPL model was then incorporated into the analytical WUE model to estimate WUE over China for 2003–2011, and the results were validated against literature data (WUELiterature). To evaluate the net effect of vegetation restoration on WUE, we simulated WUE in three ways: with vegetation change; without vegetation change; and with vegetation change, but without any Ei changes caused by vegetation changes. In the study presented here, we demonstrate the WUE simulated by the analytical WUE model is significantly correlated with the WUELiterature (R2 = 0.76, p‐value < 0.001), and leaf area index contributes the most to the spatial variability of Ei/ET, ranging from 10% to 55%. Increased Ei weakened the effect of vegetation change on WUE by ∼51.3% during vegetation restoration in China; a reduction that was particularly marked in southern China. These findings highlight the importance of considering Ei when assessing the effects of vegetation change on ecosystem carbon and water exchange, and provide insights that are important for the sustainable management of vegetation change in China.

A new automated stem CO2 efflux chamber based on industrial ultra-low-cost sensors.

Tree autotrophic respiratory processes, especially stem respiration or stem CO2 efflux (Estem), are important components of the forest carbon budget. Despite efforts to investigate the controlling processes of Estem in recent years, a considerable lack in our knowledge remains on the abiotic and biotic drivers affecting Estem dynamics. It has been strongly advocated that long-term measurements would shed light onto those processes. The expensive scientific instruments needed to measure gas exchange have prevented Estem measurements from being applied on a larger temporal and spatial scale. Here, we present an automated closed dynamic chamber system based on inexpensive and industrially broadly applied CO2 sensors, reducing the costs for the sensing system to a minimum. The CO2 sensor was cross-calibrated with a commonly used gas exchange system in the laboratory and in the field, and we found very good accordance of these sensors. We tested the system under harsh tropical climatic conditions, characterized by heavy tropical rainfall events, extreme humidity and temperatures, in a moist lowland forest in Malaysia. We recorded Estem of three Dyera costulata (Miq.) trees with our prototype over various days. The variation of Estem was large among the three tree individuals and varied by 7.5-fold. However, clear diurnal changes in Estem were present in all three tree individuals. One tree showed high diurnal variation in Estem, and the relationship between Estem and temperature was characterized by a strong hysteresis. The large variations found within one single tree species highlight the importance of continuous measurement to quantify ecosystem carbon fluxes.

Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years

Quantifying ecosystem carbon fluxes and stocks is essential for better understanding the global carbon cycle and improving projections of the carbon-climate feedbacks. Remote sensing has played a vital role in this endeavor during the last five decades by quantifying carbon fluxes and stocks. The availability of satellite observations of the land surface since the 1970s, particularly the early 1980s, has made it feasible to quantify ecosystem carbon fluxes and stocks at regional to global scales. Here we provide a review of the advances in remote sensing of the terrestrial carbon cycle from the early 1970s to present. First, we present an overview of the terrestrial carbon cycle and remote sensing of carbon fluxes and stocks. Remote sensing data acquired in a broad wavelength range (visible, infrared, and microwave) of the electromagnetic spectrum have been used to estimate carbon fluxes and/or stocks. Second, we provide a historical overview of the key milestones in remote sensing of the terrestrial carbon cycle. Third, we review the platforms/sensors, methods, findings, and challenges in remote sensing of carbon fluxes. The remote sensing data and techniques used to quantify carbon fluxes include vegetation indices, light use efficiency models, terrestrial biosphere models, data-driven (or machine learning) approaches, solar-induced chlorophyll fluorescence (SIF), land surface temperature, and atmospheric inversions. Fourth, we review the platforms/sensors, methods, findings, and challenges in passive optical, microwave, and lidar remote sensing of biomass carbon stocks as well as remote sensing of soil organic carbon. Fifth, we review the progresses in remote sensing of disturbance impacts on the carbon cycle. Sixth, we also discuss the uncertainty and validation of the resulting carbon flux and stock estimates. Finally, we offer a forward-looking perspective and insights for future research and directions in remote sensing of the terrestrial carbon cycle. Remote sensing is anticipated to play an increasingly important role in carbon cycling studies in the future. This comprehensive and insightful review on 50 years of remote sensing of the terrestrial carbon cycle is timely and valuable and can benefit scientists in various research communities (e.g., carbon cycle, remote sensing, climate change, ecology) and inform ecosystem and carbon management, carbon-climate projections, and climate policymaking.

Unravelling the age of fine roots of temperate and boreal forests

Fine roots support the water and nutrient demands of plants and supply carbon to soils. Quantifying turnover times of fine roots is crucial for modeling soil organic matter dynamics and constraining carbon cycle–climate feedbacks. Here we challenge widely used isotope-based estimates suggesting the turnover of fine roots of trees to be as slow as a decade. By recording annual growth rings of roots from woody plant species, we show that mean chronological ages of fine roots vary from <1 to 12 years in temperate, boreal and sub-arctic forests. Radiocarbon dating reveals the same roots to be constructed from 10 ± 1 year (mean ± 1 SE) older carbon. This dramatic difference provides evidence for a time lag between plant carbon assimilation and production of fine roots, most likely due to internal carbon storage. The high root turnover documented here implies greater carbon inputs into soils than previously thought which has wide-ranging implications for quantifying ecosystem carbon allocation.

Net ecosystem methane and carbon dioxide exchange in relation to heat and carbon balance in lowland tropical rice

This paper reports on the annual net ecosystem exchanges of methane (CH4), carbon dioxide (CO2), sensible heat (H) and latent heat (LE) fluxes between tropical lowland rice and atmosphere as well as quantification of annual net ecosystem carbon (C) balance. This study included both wet and dry rice seasons and fallow periods as well. Cumulative annual net ecosystem CO2 exchange (NEE) was −7.47Mg C ha−1 and net ecosystem CH4 exchange (NEME) was +419.68kg CH4 ha−1, respectively, which were higher than the reported values in the same ecology. The range of NEE was much wider in dry season compared to wet season. However, NEME did not vary considerably between the seasons. As a whole, integrated NEE was 52% higher in dry season, whereas, integrated NEME was 24% higher in wet season. In lowland rice ecology LE outweighed H. The NEME showed positive correlation with H and LE in dry season, but the relationship of NEME with LE in wet season was negative. That might be due to changes in processes driving the methanogenesis versus methanotrophy in relatively dry soil and or less transportation of CH4 from soil to atmosphere through rice. Annual global warming potential (GWP)-based C balance was done by considering net ecosystem production (NEP), rhizodeposition, algal biomass, root plus stubble biomass, ratoon and compost addition as ecosystem C input, whereas, NEME and nitrous oxide (N2O) emission, C removal through harvest and dissolved organic C as ecosystem C outflux. Although (GWP)-based CO2C equivalent of CH4 and N2O emissions were sources of C loss from lowland rice ecosystem, but taking into account all the components of C balance within the system, this ecology reflected a good potential to store considerable amount of carbon (1.04Mg C ha−1) and hence, acted as net C sink. Future challenge is to quantify ecosystem carbon budgeting either by considering all sources of energy input and output and/or by using life cycle assessment method in lowland ecology and its up scaling.

Application of Remote Sensing and Developed Allometric Models for Estimating Wood Carbon Stocks in a North-Western Miombo Woodland Landscape of Tanzania

Quantifying ecosystem carbon stocks is vital for understanding the relationship between changes in land use and cover (LULC) and carbon emissions; however, few studies have documented the impacts of carbon cycling on Miombo ecosystems. Here, we estimate the amounts of wood carbon which is stored and lost as a result of LULC changes in Kagoma Forest Reserve (KFR) for the periods between 1988 and 2010 using GIS data, Landsat imagery, and field observations. The land cover was captured on the basis of Landsat 5 TM and Landsat 7 ETM. The amounts of wood carbon stored and lost were estimated based on four previously developed allometric models. Spatial analysis of the Landsat images shows that in the year 1988, woodlands dominated the area by covering 32.66% whereas in the year 2010 the woodlands covered only 7.34% of the total area. The findings of the current study reveal that KFR had undergone notable changes in terms of LULC for the period of 1988–2010. It was estimated that the woodlands in the KFR lost an average of 4409.79 tCyr-1. In this study, the amount of carbon stocks stored was estimated to be 21457.02 tonnes in tree stem biomass based on the area (1226.12 ha) that was covered by woodlands. We estimated that an average of 17.79 tCh-1was stored in the Miombo woodlands based on the four models. The efforts to ensure sustainable management of the Miombo ecosystem can contribute to the creation of a considerable carbon sink.

Carbon factors and models for forest carbon estimates for the 2005–2011 National Greenhouse Gas Inventories of the United States

Most nations have ratified the United Nations Framework Convention on Climate Change, and are mandated to report National Greenhouse Gas Inventories, including the land use, land use change and forestry sector when it is significant. Participating countries commonly use data from national forest inventories as a basis for their forest-related emissions estimates. The estimates are required to be consistent, comparable among parties, transparent, and well-documented. To help meet these requirements, we describe the data and methods used to calculate the forest carbon component of the United States’ greenhouse gas emissions and sinks which we provided to the US Environmental Protection Agency to be compiled for the submission years 2005–2011. Past forest inventories were not designed to measure or take samples of data directly related to quantifying ecosystem carbon stocks necessary for greenhouse gas reporting. This study provides information used to bridge that gap and enable harmonized reporting. Specifically, we provide the forest inventory plot-data-to-carbon-stock conversion factors and associated uncertainty bounds in use for the reporting years prior to the availability of more directly measured or sampled carbon stocks. The factors are similar to default values supplied by the Intergovernmental Panel on Climate Change and current scientific literature. Overall, this approach indicates that forest ecosystems of the United States sequester approximately 170 Tg of carbon per year, which represents a net annual increase of half a percent of forest carbon stocks.

Modelling temperature acclimation effects on the carbon dynamics of forest ecosystems in the conterminous United States

ABSTRACTThe projected rise in temperature in the 21st century will alter forest ecosystem functioning and carbon dynamics. To date, the acclimation of plant photosynthesis to rising temperature has not been adequately considered in earth system models. Here we present a study on regional ecosystem carbon dynamics under future climate scenarios incorporating temperature acclimation effects into a large-scale ecosystem model, the terrestrial ecosystem model (TEM). We first incorporate a general formulation of the temperature acclimation of plant photosynthesis into TEM, and then apply the revised model to the forest ecosystems of the conterminous United States for the 21st century under the future Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) climate scenarios A1FI, A2, B1 and B2. We find that there are significant differences between the estimates of carbon dynamics from the previous and the revised models. The largest differences occur under the A1FI scenario, in which the model that considers acclimation effects predicts that the region will act as a carbon sink, and that cumulative carbon in the 21st century will be 35 Pg C higher than the estimates from the model that does not consider acclimation effects. Our results further indicate that in the region there are spatially different responses to temperature acclimation effects. This study suggests that terrestrial ecosystem models should take temperature acclimation effects into account so as to more accurately quantify ecosystem carbon dynamics at regional scales.

Ecosystem carbon storage capacity as affected by disturbance regimes: A general theoretical model

Disturbances have been recognized as a key factor shaping terrestrial ecosystem states and dynamics. A general model that quantitatively describes the relationship between carbon storage and disturbance regime is critical for better understanding large scale terrestrial ecosystem carbon dynamics. We developed a model (REGIME) to quantify ecosystem carbon storage capacities (E[x]) under varying disturbance regimes with an analytical solution E[x] = U · τE · , where U is ecosystem carbon influx, τE is ecosystem carbon residence time, and τ1 is the residence time of the carbon pool affected by disturbances (biomass pool in this study). The disturbance regime is characterized by the mean disturbance interval (λ) and the mean disturbance severity (s). It is a Michaelis‐Menten‐type equation illustrating the saturation of carbon content with mean disturbance interval. This model analytically integrates the deterministic ecosystem carbon processes with stochastic disturbance events to reveal a general pattern of terrestrial carbon dynamics at large scales. The model allows us to get a sense of the sensitivity of ecosystems to future environmental changes just by a few calculations. According to the REGIME model, for example, approximately 1.8 Pg C will be lost in the high‐latitude regions of North America (&gt;45°N) if fire disturbance intensity increases around 5.7 time the current intensity to the end of the twenty‐first century, which will require around 12% increases in net primary productivity (NPP) to maintain stable carbon stocks. If the residence time decreased 10% at the same time additional 12.5% increases in NPP are required to keep current C stocks. The REGIME model also lays the foundation for analytically modeling the interactions between deterministic biogeochemical processes and stochastic disturbance events.

Interpreting post-drought rewetting effects on soil and ecosystem carbon dynamics in a Mediterranean oak savannah

A transient increase in soil carbon dioxide efflux after rewetting of previously dry soils, termed the Birch effect, can significantly influence the ecosystem carbon balance. This has generally been related to increased soil microbial respiration in response to a temporal increase in labile soil carbon. In order to quantify ecosystem carbon losses by the Birch effect and to trace the underlying biogeochemical processes, we monitored the effects of first natural rain pulses on soil and ecosystem carbon dioxide fluxes and their isotopic composition (δ 13C) after an extended summer drought in a Mediterranean oak woodland. While GPP was affected negatively, rain largely enhanced soil respiratory processes, which increased their relative contribution to NEE by up to 95%, resulting in a significant net carbon loss from the ecosystem. This was reflected by high correlation ( r 0.91) between the two fluxes. Further, isotopic composition of soil respiration (δ 13C S) explained on average 71% of the isotopic composition of ecosystem respiration (δ 13C R). We found a strong relationship between soil moisture and the increase in soil respiration ( R S) and NEE, indicating that the Birch effect observed during this study did not result from a transient increase in labile soil carbon but from a gradual (several days) moisture response of size and/or activity of the soil microbial community. We also observed large variation in δ 13C of soil and ecosystem respired CO 2 that corresponded to the rain pulses with enrichment of up to 8 and 6‰, respectively, and a subsequent depletion to initial values during the following dry days, which might be explained by increased relative contribution of soil microbial communities from deeper soil layers to overall soil respiration, a switch in the respired carbon source (e.g. anaplerotic carbon) and changes in apparent fractionation during the mineralization of soil organic matter after the depletion of labile carbon pools.

Revisiting Soil Carbon and Nitrogen Sampling

Increasing atmospheric carbon dioxide and its feedbacks with global climate have sparked renewed interest in quantifying ecosystem carbon (C) budgets, including quantifying belowground pools. Belowground nutrient budgets require accurate estimates of soil mass, coarse fragment content, and nutrient concentrations. It has long been thought that the most accurate measurement of soil mass and coarse fragment content has come from excavating quantitative soil pits. However, this methodology is labor intensive and time consuming. We propose that diamond-tipped rotary cores are an acceptable if not superior alternative to quantitative soil pits for the measurement of soil mass, coarse fragment content, C and total nitrogen (N) concentrations. We tested the rotary core methodology against traditional quantitative pits at research sites in California, Nevada, and New York. We found that soil cores had 16% higher estimates of less than 2-mm soil mass than estimates obtained from quantitative pits. Conversely, soil cores had 8% lower estimates of coarse fragment mass compared with quantitative pits. There were no statistical differences in measured C or N concentrations between the two methods. At the individual site level, differences in estimates for the two methods were more pronounced, but there was no consistent tendency for cores to overestimate or underestimate a soil parameter when compared with quantitative pits.

Above- and Belowground Carbon Stocks in a Miombo Woodland Landscape of Mozambique

Quantifying ecosystem carbon stocks is vital for understanding the relationship between changes in land use and carbon dioxide emissions. Here, we estimate carbon stocks in an area of miombo woodland in Mozambique, by identifying the major carbon stocks and their variability. Data on the biomass of tree stems and roots, saplings, and soil carbon stocks are reported and compared with other savannas systems around the globe. A new allometric relationship between stem diameter and tree stem and root biomass is presented, based on the destructive harvest of 29 trees. These allometrics are combined with an inventory of 12,733 trees on 58 plots over an area of 27ha. Ecosystem carbon stocks totaled 110tC/ha, with 76tC/ha in the soil carbon pool (to 50cm depth), 21.2tC/ha in tree stem biomass, 8.5tC/ha in tree coarse root biomass, and 3.6tC/ha in total sapling biomass. Plot-level tree root:stem (R:S) ratio varied from 0.27 to 0.58, with a mean of 0.42, slightly higher than the mean reported for 18 other savanna sites with comparable aboveground biomass (R:S=0.35). Tree biomass (stem1root) ranged from 3.1 to 86.5tC/ha, but the mean (32.1tC/ha) was well constrained (95% CI 28‐36.6). In contrast, soil carbon stocks were almost uniformly distributed and varied from 32 to 133tC/ha. Soil carbon stocks are thus the major uncertainty in the carbon storage of these woodlands. Soil texture explained 53 percent of the variation in soil carbon content, but only 13 percent of the variation in woody carbon stocks. The history of disturbance (fire, elephants, logging/charcoal production, and shifting cultivation) is likely to decouple changes in woody carbon stocks from soil carbon stocks, mediated by tree‐grass interactions.

The ecohydrologic significance of hydraulic redistribution in a semiarid savanna

Recent studies have illuminated the process of hydraulic redistribution, defined as the translocation of soil moisture via plant root systems, but the long‐term ecohydrologic significance of this process is poorly understood. We investigated hydraulic redistribution (HR) by Prosopis velutina Woot. (velvet mesquite) in an upland savanna ecosystem over a two‐year period. Our goal was to quantify patterns of HR by mesquite roots and assess how this affects tree water use and productivity. We used the heat ratio method to monitor bi‐directional sap flow, an analog of HR, in both lateral and tap roots. Additionally, we monitored soil water content and used the eddy covariance technique to quantify ecosystem carbon dioxide and water exchange. Mesquite roots redistributed large amounts of water throughout the year, even during periods of canopy dormancy. Dormant season precipitation (November–March) was often taken up by shallow lateral roots and transferred downward in the soil profile by deeper lateral and tap roots. Such a transfer was also apparent when the trees were active and moisture from summer rainfall was plant available in the upper soil layers. As the upper soil layers dried, sap flow moving toward the canopy in the lateral roots diminished and water use from deeper soils increased via the taproots. The relationship between root sap flow and above‐canopy fluxes suggested that deeper “stored” water from HR allowed the trees to transpire more in the spring that followed a winter with significant downward redistribution. Patterns of lateral and tap root sap flow also implied that redistribution may extend the growing season of the trees after summer rains have ended and surface soils are dry, thus allowing the trees to photosynthesize through periods of seasonal drought. The large hydrologic magnitude and the ecological effects of HR we studied, along with mounting evidence of this process occurring in many other ecosystems, indicates that HR should be accounted for in many ecohydrologic modeling efforts.

Modeling nighttime ecosystem respiration from measured CO2 concentration and air temperature profiles using inverse methods

A major challenge for quantifying ecosystem carbon budgets from micrometeorological methods remains nighttime ecosystem respiration. An earlier study utilized a constrained source optimization (CSO) method using inverse Lagrangian dispersion theory to infer the two components of ecosystem respiration (aboveground and forest floor) from measured mean CO2 concentration profiles within the canopy. This method required measurements of within‐canopy mean velocity statistics and did not consider local thermal stratification. We propose a Eulerian version of the CSO method (CSOE) to account for local thermal stratification within the canopy for momentum and scalars using higher‐order closure principles. This method uses simultaneous mean CO2 concentration and air temperature profiles within the canopy and velocity statistics above the canopy as inputs. The CSOE was tested at a maturing loblolly pine plantation over a 3‐year period with a mild drought (2001), a severe drought (2002), and a wet year (2003). Annual forest floor efflux modeled with CSOE averaged 111 g C m−2 less than that estimated using chambers during these years (2001: 1224 versus 1328 gCm−2; 2002: 1127 versus 1230 gCm−2; 2003: 1473 versus 1599 gCm−2). The modeled ecosystem respiration exceeded estimates from eddy covariance measurements (uncorrected for storage fluxes) by at least 25%, even at high friction velocities. Finally, we showed that the CSOE annual nighttime respiration values agree well with independent estimates derived from the intercept of the ecosystem light‐response curve from daytime eddy covariance CO2 flux measurements.

Calibrating soil respiration measures with a dynamic flux apparatus using artificial soil media of varying porosity

SummaryMeasurement of soil respiration to quantify ecosystem carbon cycling requires absolute, not relative, estimates of soil CO2 efflux. We describe a novel, automated efflux apparatus that can be used to test the accuracy of chamber‐based soil respiration measurements by generating known CO2 fluxes. Artificial soil is supported above an air‐filled footspace wherein the CO2 concentration is manipulated by mass flow controllers. The footspace is not pressurized so that the diffusion gradient between it and the air at the soil surface drives CO2 efflux. Chamber designs or measurement techniques can be affected by soil air volume, hence properties of the soil medium are critical. We characterized and utilized three artificial soils with diffusion coefficients ranging from 2.7 × 10−7 to 11.9 × 10−7 m2 s−1 and porosities of 0.26 to 0.46. Soil CO2 efflux rates were measured using a commercial dynamic closed‐chamber system (Li‐Cor 6400 photosynthesis system equipped with a 6400‐09 soil CO2 flux chamber). On the least porous soil, small underestimates (&lt; 5%) of CO2 effluxes were observed, which increased as soil diffusivity and soil porosity increased, leading to underestimates as high as 25%. Differential measurement bias across media types illustrates the need for testing systems on several types of soil media.

Modelling night‐time ecosystem respiration by a constrained source optimization method

AbstractOne of the main challenges to quantifying ecosystem carbon budgets is properly quantifying the magnitude of night‐time ecosystem respiration. Inverse Lagrangian dispersion analysis provides a promising approach to addressing such a problem when measured mean CO2 concentration profiles and nocturnal velocity statistics are available. An inverse method, termed ‘Constrained Source Optimization’ or CSO, which couples a localized near‐field theory (LNF) of turbulent dispersion to respiratory sources, is developed to estimate seasonal and annual components of ecosystem respiration. A key advantage to the proposed method is that the effects of variable leaf area density on flow statistics are explicitly resolved via higher‐order closure principles. In CSO, the source distribution was computed after optimizing key physiological parameters to recover the measured mean concentration profile in a least‐square fashion. The proposed method was field‐tested using 1 year of 30‐min mean CO2 concentration and CO2 flux measurements collected within a 17‐year‐old (in 1999) even‐aged loblolly pine (Pinus taeda L.) stand in central North Carolina. Eddy‐covariance flux measurements conditioned on large friction velocity, leaf‐level porometry and forest‐floor respiration chamber measurements were used to assess the performance of the CSO model. The CSO approach produced reasonable estimates of ecosystem respiration, which permits estimation of ecosystem gross primary production when combined with daytime net ecosystem exchange (NEE) measurements. We employed the CSO approach in modelling annual respiration of above‐ground plant components (c. 214 g C m−2 year−1) and forest floor (c. 989 g C m−2 year−1) for estimating gross primary production (c. 1800 g C m−2 year−1) with a NEE of c. 605 g C m−2 year−1 for this pine forest ecosystem. We conclude that the CSO approach can utilise routine CO2 concentration profile measurements to corroborate forest carbon balance estimates from eddy‐covariance NEE and chamber‐based component flux measurements.