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Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human‐earth systems interactions in ESMs. Plain Language Summary: Crops are increasingly being characterized in global land models because of their impact on local and regional climate. However, there is limited understanding of the impact of crop rotation and of different crop cultivars on carbon and energy fluxes from the land surface. Our study implements crop rotation and spatially varying crop parameters in the Energy Exascale Earth System Model Land Model and finds that doing so improves carbon and energy flux estimation from cropland area. These findings emphasize the importance of capturing agricultural management practices and variability in growth characteristics across different crop cultivars in global land models. Key Points: This study implements corn soybean rotation and spatially varying crop parameters in the Energy Exascale Earth System Land ModelThe model is calibrated and validated against observations collected at three AmeriFlux sites in the US MidwestWe find that spatially varying crop parameters resulted in improved flux estimation from cropland areas [ABSTRACT FROM AUTHOR]

Long‐running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO2) across the Chequamegon Ecosystem‐Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US‐WCr and US‐Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US‐Los and US‐ALQ), and a very tall (400 m) landscape‐level tower (US‐PFa). Together, they provided over 70 site‐years of observations. The 19‐tower Chequamegon Heterogenous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 campaign centered around US‐PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long‐term sites, but cross‐site coherence in interannual NEE in the earlier part of the record became weaker with time as non‐climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less‐insulated soils delayed start of spring green‐up. Higher CO2 increased maximum net assimilation parameters but not total gross primary productivity. Stand‐scale sites were larger net sinks than the landscape tower. Clustered, long‐term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space. Plain Language Summary: The terrestrial biosphere features the largest global sources and sinks of atmospheric carbon. Changes in growing season length, disturbance frequency, human management, increasing atmospheric carbon dioxide (CO2) concentrations, amount and timing of precipitation, and warmer air temperature all influence the carbon cycle. Observations from the global eddy covariance flux tower network have been key for diagnosing these changes. However, data from most sites are limited in length. Here, we explore how multi‐decadal carbon flux measurements from a cluster of flux towers in forests and wetlands in the upper Midwest USA respond to environmental change. Despite the proximity of the sites, year‐to‐year variation in carbon fluxes was rarely similar between sites. Surprisingly, warmer winters promoting earlier snowmelt led to later spring green‐up because soil temperature was colder. Impacts of higher CO2 and warmer temperature on annual carbon fluxes were limited but did influence factors linking carbon flux sensitivity to climate. Differences in flux magnitudes from a very tall tower flux to the network show that the whole does not seem to be simply a sum of its measured parts. More elaborate approaches may be needed to understand the processes that control carbon fluxes across large landscapes. Key Points: Multi‐decadal eddy covariance flux tower site cluster provides insight into variation of regional carbon cyclingVariation of carbon exchange in two forests, two wetlands, and a tall tower responded differently to weather, phenology, and disturbanceChallenges in upscaling fluxes indicate need for advances in aquatic observations, disturbance mapping, and flux footprint decomposition [ABSTRACT FROM AUTHOR]

Keywords: AmeriFlux; dual isotope approach; Péclet effect; precipitation; stable oxygen isotopes; stomatal conductance; tree rings; vapour pressure deficit (VPD) EN AmeriFlux dual isotope approach Péclet effect precipitation stable oxygen isotopes stomatal conductance tree rings vapour pressure deficit (VPD) 809 812 4 10/13/22 20221101 NES 221101 A reply to Lin et al. (2022) 'Do changes in tree-ring 18 O indicate changes in stomatal con... There is growing scientific consensus that rising atmospheric CO SB 2 sb concentrations have caused an increase in forest water-use efficiency (WUE), but the magnitude of this effect and the relative roles of enhanced photosynthesis vs reduced stomatal conductance ( I g i SB s sb ) are still under debate (Walker I et al i ., 2020). Detecting long-term changes in stomatal conductance: challenges and opportunities of tree-ring 18O proxy Dual isotope approach, Péclet effect, AmeriFlux, precipitation, stable oxygen isotopes, stomatal conductance, tree rings, vapour pressure deficit (VPD) Simulating oxygen isotope ratios in tree ring cellulose using a dynamic global vegetation model. [Extracted from the article]

Linking biometric measurements of stand‐level biomass growth to tower‐based measurements of carbon uptake—gross primary productivity and net ecosystem productivity—has been the focus of numerous ecosystem‐level studies aimed to better understand the factors regulating carbon allocation to slow‐turnover wood biomass pools. However, few of these studies have investigated the importance of previous year uptake to growth. We tested the relationship between wood biomass increment (WBI) and different temporal periods of carbon uptake from the current and previous years to investigate the potential lagged allocation of fixed carbon to growth among six mature, temperate forests. We found WBI was strongly correlated to carbon uptake across space (i.e., long‐term averages at the different sites) but on annual timescales, WBI was much less related to carbon uptake, suggesting a temporal mismatch between C fixation and allocation to biomass. We detected lags in allocation of the previous year's carbon uptake to WBI at three of the six sites. Sites with higher annual WBI had overall stronger correlations to carbon uptake, with the strongest correlations to carbon uptake from the previous year. Only one site had WBI with strong positive relationships to current year uptake and not the previous year. Forests with low rates of WBI demonstrated weak correlations to carbon uptake from the previous year and stronger relationships to current year climate conditions. Our work shows an important, but not universal, role of lagged allocation of the previous year's carbon uptake to growth in temperate forests. Plain Language Summary: We compared the interannual variability of stand‐level biomass growth (estimated from annual tree‐level measurements) to carbon uptake (measured from towers monitoring gas exchange over forest canopies) to identify temporal mismatches between the two processes. We used data from multiple forested sites with long‐term measurements of carbon uptake to ask the question: is there a consistent temporal offset between the uptake of carbon and the allocation to plant biomass? We found that the relationship between growth and carbon uptake varies among sites, and there was no consistent temporal offset between the uptake of carbon and allocation to biomass growth. Sites with higher growth rates had higher interannual variability, and more apparent coupling between biomass growth and carbon uptake from the previous year. Forests with lower growth rates had weaker relationships with carbon uptake and stronger coupling with current year environmental conditions. We demonstrate that temporal lags between carbon uptake and allocation to growth are not universal among these temperate forests, and the carry‐over of uptake stored from the previous year is not as critical in slow‐growing forests, compared to fast‐growing forests, likely due to lower demands for growth. This work helps to clarify the limitations on the growth of slow‐turnover wood biomass. Key Points: We found evidence for lags in allocation of previous year's carbon uptake to wood biomass increment (WBI) at three of six sites studiedSites with high annual WBI demonstrated strong correlations to carbon uptake, with the strongest correlations including previous year uptakeWBI was less tightly coupled to carbon uptake in less productive forests that also exhibited low interannual variability in WBI [ABSTRACT FROM AUTHOR]

The Noah‐MP land surface model (LSM) relies on the Monin‐Obukhov (M‐O) Similarity Theory (MOST) to calculate land‐atmosphere exchanges of water, energy, and momentum fluxes. However, MOST flux‐profile relationships neglect canopy‐induced turbulence in the roughness sublayer (RSL) and parameterize within‐canopy turbulence in an ad hoc manner. We implement a new physics scheme (M‐O‐RSL) into Noah‐MP that explicitly parameterizes turbulence in RSL. We compare Noah‐MP simulations employing the M‐O‐RSL scheme (M‐O‐RSL simulations) and the default M‐O scheme (M‐O simulations) against observations obtained from 647 Snow Telemetry (SNOTEL) stations and two AmeriFlux stations in the western United States. M‐O‐RSL simulations of snow water equivalent (SWE) outperform M‐O simulations over 64% and 69% of SNOTEL sites in terms of root‐mean‐square‐error (RMSE) and correlation, respectively. The largest improvements in skill for M‐O‐RSL occur over closed shrubland sites, and the largest degradations in skill occur over deciduous broadleaf forest sites. Differences between M‐O and M‐O‐RSL simulated snowpack are primarily attributable to differences in aerodynamic conductance for heat underneath the canopy top, which modulates sensible heat flux. Differences between M‐O and M‐O‐RSL within‐canopy and below‐canopy sensible heat fluxes affect the amount of heat transported into snowpack and hence change snowmelt when temperatures are close to or above the melting point. The surface energy budget analysis over two AmeriFlux stations shows that differences between M‐O and M‐O‐RSL simulations can be smaller than other model biases (e.g., surface albedo). We intend for the M‐O‐RSL physics scheme to improve performance and uncertainty estimates in weather and hydrological applications that rely on Noah‐MP. Plain Language Summary: Most widely used computer models of the land surface neglect canopy‐induced turbulence in calculations of heat, water, and momentum exchanges. Accounting for canopy‐induced turbulence is important because coherent eddies that form near the canopy top are responsible for generating most of the transportation of heat, water, and momentum, in and directly above the canopy. In 2007, 2008 scientists Ian N. Harman and John J. Finnigan developed a methodology that adapts contemporarily used equations in operational LSMs to account for canopy‐induced turbulence. In this study, we create a new physics option for the Noah with Multi‐Parameterization (Noah‐MP) LSM that accounts for canopy‐induced turbulence based on the Harman and Finnigan, 2007–2008 methodology. The primary focus of this study is to quantify differences between Noah‐MP snowpack simulations using the classical physics option that neglects canopy‐induced turbulence with the new physics option that accounts for canopy‐induced turbulence. Overall, simulations using the new physics option tend to have better agreement with ground‐based SWE observations across 647 validation sites within the western United States. We intend for the new physics scheme to improve weather and hydrological applications for operational modeling systems that rely on the Noah‐MP LSM. Key Points: This study presents a new physics option for Noah‐MP that accounts for canopy‐induced turbulence in the roughness sublayerSimulated SWE over shrublands using the new turbulence scheme agree more with observations than those using the traditional MOST schemeDifferences in snow simulations are mainly attributable to differences in aerodynamic resistance to sensible heat below the canopy top [ABSTRACT FROM AUTHOR]

Many secondary deciduous forests of eastern North America are approaching a transition in which mature early‐successional trees are declining, resulting in an uncertain future for this century‐long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem girdling‐induced mortality of >6,700 early‐successional Populus spp. (aspen) and Betula papyrifera (paper birch). Meteorological flux tower‐based C cycling observations from the 33‐ha treatment forest have been paired with those from a nearby unmanipulated forest since 2008. Following over a decade of observations, we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid‐late‐successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather with a rapid 1‐yr recovery of total leaf area index as mid‐late‐successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid‐late‐successional species dominance improved carbon‐use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid‐late‐successional species in the treatment forest, suggest changes in aboveground plant respiration and growth were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come. [ABSTRACT FROM AUTHOR]

Spatial estimates of crop evapotranspiration with high accuracy from the field to watershed scale have become increasingly important for water management, particularly over irrigated agriculture in semiarid regions. Here, we provide a comprehensive assessment on patterns of annual agricultural water use over California's Central Valley, using 30‐m daily evapotranspiration estimates based on Landsat satellite data. A semiempirical Priestley‐Taylor approach was locally optimized and cross‐validated with available field measurements for major crops including alfalfa, almond, citrus, corn, pasture, and rice. The evapotranspiration estimates explained >70% variance in daily measurements from independent sites with an RMSE of 0.88 mm day−1. When aggregated over the Valley, we estimated an average evapotranspiration of 820 ± 290 mm yr−1 in 2014. Agricultural water use varied significantly across and within crop types, with a coefficient of variation ranging from 8% for Rice (1,110 ± 85 mm yr−1) to 59% for Pistachio (592 ± 352 mm yr−1). Total water uses in 2016 increased by 9.6%, as compared to 2014, mostly because of land‐use conversion from fallow/idle land to cropland. Analysis across 134 Groundwater Sustainability Agencies (GSAs) further showed a large variation of agricultural evapotranspiration among and within GSAs, especially for tree crops, e.g., almond evapotranspiration ranging from 339 ± 80 mm yr−1 in Tracy to 1,240 ± 136 mm yr−1 in Tri‐County Water Authority. Continuous monitoring and assessment of the dynamics and spatial heterogeneity of agricultural evapotranspiration provide data‐driven guidance for more effective land use and water planning across scales. Key Points: A 30‐m daily evapotranspiration product estimated using regionally optimized approach and Landsat Analysis Ready Data Collection 1Assessment of agricultural consumptive water use over Central Valley provides critical guidance for sustainable groundwater managementLarge variation of water use was found, mostly due to crop diversity, age structure, and physiological factors [ABSTRACT FROM AUTHOR]

A long‐standing goal of ecology has been to understand the cycling of carbon in forests. This has taken on new urgency with the need to address a rapidly changing climate. Forests serve as long‐term stores for atmospheric CO2, but their continued ability to take up new carbon is dependent on future changes in climate and other factors such as age. We have been measuring many aspects of carbon cycling at an unmanaged evergreen forest in central Maine, USA, for over 25 years. Here we use these data to address questions about the magnitude and control of carbon fluxes and quantify flows and uncertainties between the different pools. A key issue was to assess whether recent climate change and an aging tree population were reducing annual C storage. Total ecosystem C stocks determined from inventory and quantitative soil pits were about 23,300 g C m−2 with 46% in live trees, and 48% in the soil. Annual biomass increment in trees at Howland Forest averaged 161 ± 23 g C m−2 yr−1, not significantly different from annual net ecosystem production (NEP = −NEE) of 211 ± 40 g C m−2 y−1 measured by eddy covariance. Unexpectedly, there was a small but significant trend of increasing C uptake through time in the eddy flux data. This was despite the period of record including some of the most climate‐extreme years in the last 125. We find a surprising lack of influence of climate variability on annual carbon storage in this mature forest. Plain Language Summary: Trees remove carbon dioxide (CO2) from the atmosphere by photosynthesis and store it in chemical form in wood and other plant tissues. Much of the stored carbon ends up in the soil. Plants and soil organisms use some of the stored carbon to provide energy for growth and plant maintenance processes which releases CO2 back to the atmosphere. The movement of carbon atoms into and out of the forest and through the plants and soils is termed the "carbon cycle". We have been studying the carbon cycle of the Howland Forest in central Maine, an unmanaged evergreen forest with most trees between 100 and 200 years old. Over the last 25 years the forest has stored almost 3.5 tons of CO2 per acre each year, even though that timespan has included the warmest, wettest, and driest years in the last 125. Although the forest is maturing, it is storing on average a bit more carbon each year and there is as yet no clear reason why. Forest growth is a natural solution to the problem of too much CO2 in the atmosphere. This research helps show the longer‐term stability and viability of forests as natural climate solutions. Key Points: An unmanaged evergreen forest has been a net carbon sink for over 25 years and the sink strength has increased significantly with timeAnnual average carbon increment measured by eddy flux or inventory data are not significantly differentThe forest remained a robust C sink in the warmest, wettest, and driest years since 1895, indicating resistance to climate variability [ABSTRACT FROM AUTHOR]

Summary: Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near‐surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated.Here, we integrate on‐the‐ground phenological observations, leaf‐level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower‐based CO2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics.We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter‐dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy‐level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature‐based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color.These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color‐based vegetation indices. [ABSTRACT FROM AUTHOR]

Environmental observatory networks (EONs) provide information to understand and forecast the spatial and temporal dynamics of Earth's biophysical processes. Consequently, representativeness analyses are important to provide insights for improving EONs' management, design, and interpretation of their value‐added products. We assessed the representativeness of registered FLUXNET sites (n = 41, revised on September 2018) across Latin America (LA), a region of great importance for the global carbon and water cycles, which represents 13% of the world's land surface. Nearly 46% of registered FLUXNET sites are located in evergreen broad‐leaf forests followed by sites in woody savannas (∼20%). Representativeness analyses were performed using a 0.05° spatial grid for multiple environmental variables, gross primary productivity (GPP), and evapotranspiration (ET). Our results showed a potential representativeness of 34% of the surface area for climate properties, 36% for terrain parameters, 34% for soil resources, and 45% when all aforementioned environmental variables were summarized into a principal component analysis. Furthermore, there was a 48% potential representativeness for GPP and 34% for ET. Unfortunately, data from these 41 sites are not all readily available for the scientific community, limiting synthesis studies and model benchmarking/parametrization. The implication is that global/regional data‐driven products are forced to use information from FLUXNET sites outside LA to predict patterns in LA. Representativeness could increase to 86% (for GPP) and 80% (for ET) if 200 sites are optimally distributed. We discussed ongoing challenges, the need to enhance interoperability and data sharing, and promote monitoring efforts across LA to increase the accuracy of regional‐to‐global data‐driven products. Plain Language Summary: Environmental observatory networks (EONs) provide information to better understand, model, and forecast the spatial and temporal dynamics of Earth's biophysical processes. Consequently, representativeness analyses of EON's are important to provide insights for improving EONs' management, design, and interpretation of their value‐added products (e.g., datasets, model predictions). We assessed the representativeness of registered FLUXNET sites (n = 41, revised on September 2018) across Latin America (LA), a region of great importance for the global carbon and water cycles, which represents nearly 13% of the world's land surface area. Representativeness analyses were performed using multiple environmental variables, gross primary productivity (GPP), and evapotranspiration (ET) across LA. Our results showed potential spatial representativeness of 34% of the surface area for climate properties, 36% for terrain parameters, 34% for soil resources, and 45% when all aforementioned environmental variables were summarized. Furthermore, there was a 48% potential representativeness for GPP and 34% for ET. Our results represent a best‐case scenario because data from these 41 sites is not all readily available for the scientific community. We discussed the need to enhance collaboration, promote the participation of active/inactive sites to share information with local, regional and international networks, and promote monitoring efforts across this region of the world. Key Points: There is a need to promote data sharing and improve the representativeness of environmental networks across Latin AmericaCurrently, 48% of gross primary productivity and 34% of evapotranspiration patterns are represented by FLUXNET sitesData‐driven products are forced to use information outside Latin America to predict patterns within this region [ABSTRACT FROM AUTHOR]

In October 2020, under COVID‐19 quarantine, AmeriFlux held its largest and one of its most successful annual meetings. Historically, ∼100 scientists attend; this meeting had over 400 registrants and participants. Participants expressed that this was among the best virtual meetings that they had ever attended, and 100% of post‐meeting survey respondents stated that they would attend again. Feedback revealed the meeting fostered a strong sense of connection to the AmeriFlux community, especially among early career and international scientists. How did a feeling of strong connection to the community arise from the seemingly cold and isolated structures of virtual meetings? The meeting emphasized Diversity, Equity, and Inclusion (DEI), which resulted in an unexpected enhancement of science communication and community connections. Additionally, the meeting experimented with an online virtual gaming‐like world (Gather.town), where users controlled video/audio‐enabled avatars in a conference center and poster hall environment to create spontaneous conversations and discussions. In lieu of a social‐bonding field trip, participants showed videos of their field sites accompanied by informal banter, which were watched in group settings in Gather. Social mixers were structured over Zoom breakout rooms that were limited in size to promote participation with accessible games. Science talks were selected based on appeal to a demographically diverse organizing committee, which enhanced appeal to a broad meeting audience. Finally, breakout reports were given not in the format of bullet point slides, but instead as creatively improvized fairytales, which dramatically enhanced engagement. Here, we describe some of the process that went into the AmeriFlux 2020 meeting. Keeping with the theme of experimenting and fairytales, we present this narrative in the form of a fairytale; and, without further ado... Key Points: Diversity, Equity, and Inclusion are keys to enhanced science communication and community connectionsLean‐in to experimenting with novel meeting tools and options for improved virtual meetingsStory telling as a means of effective science communication and engagement [ABSTRACT FROM AUTHOR]

We test the relationship between canopy photosynthesis and reflected near‐infrared radiation from vegetation across a range of functional (photosynthetic pathway and capacity) and structural conditions (leaf area index, fraction of green and dead leaves, canopy height, reproductive stage, and leaf angle inclination), weather conditions, and years using a network of field sites from across central California. We based our analysis on direct measurements of canopy photosynthesis, with eddy covariance, and measurements of reflected near‐infrared and red radiation from vegetation, with light‐emitting diode sensors. And we interpreted the observed relationships between photosynthesis and reflected near‐infrared radiation using simulations based on the multilayer, biophysical model, CanVeg. Measurements of reflected near‐infrared radiation were highly correlated with measurements of canopy photosynthesis on half‐hourly, daily, seasonal, annual, and decadal time scales across the wide range of function and structure and weather conditions. Slopes of the regression between canopy photosynthesis and reflected near‐infrared radiation were greatest for the fertilized and irrigated C4 corn crop, intermediate for the C3 tules on nutrient‐rich organic soil and nitrogen fixing alfalfa, and least for the native annual grasslands and oak savanna on nutrient‐poor, mineral soils. Reflected near‐infrared radiation from vegetation has several advantages over other remotely sensed vegetation indices that are used to infer canopy photosynthesis; it does not saturate at high leaf area indices, it is insensitive to the presence of dead legacy vegetation, the sensors are inexpensive, and the reflectance signal is strong. Hence, information on reflected near‐infrared radiation from vegetation may have utility in monitoring carbon assimilation in carbon sequestration projects or on microsatellites orbiting Earth for precision agriculture applications. Key Points: Reflected near‐infrared radiation is a strong proxy for canopy photosynthesisThis proxy works for a wide range of ecosystem structure and functionThe method has promise to be used for a variety of applications relating to carbon and water use [ABSTRACT FROM AUTHOR]

California is expected to experience great spatial/temporal variations evaporation. These variations arise from strong north‐south, east‐west gradients in rainfall and vegetation, strong interannual variability in rainfall (±30%) and strong seasonal variability in the supply and demand for moisture. We used the Breathing Earth System Simulator to evaluate the rates and sums of evaporation across California, over the 2001–2017 period. Breathing Earth System Simulator is a bottom‐up, biophysical model that couples subroutines that calculate the surface energy balance, photosynthesis, and stomatal conductance. The model is forced with high‐resolution remote sensing data (1 km).The questions we address are as follows: How much water is evaporated across the natural and managed ecosystems of California? How much does evaporation vary during the booms and busts in annual rainfall? and Is evaporation increasing with time due to a warming climate? Mean annual evaporation, averaged over the 2001–2017 period, was relatively steady (393 ± 21 mm/year) given the high interannual variation in precipitation (519 ± 140 mm/year). No significant trend in evaporation at the statewide level was detected over this time period, despite a background of a warming climate. Irrigated agricultural crops and orchards, at 1‐km scale, use less water than inferred estimates for individual fields. This leaves the potential for sharing water, a scarce resource, more equitably among competing stakeholders, for example, farms, fish, people, and ecosystems. Plain Language Summary: Many stakeholders are contending for the limited water budget that is available to California, the world's fifth largest economy. Yet the amount of water used by natural and managed ecosystems across the state is not well known. We produced a new, process‐oriented estimate of statewide water use by natural and managed ecosystems using a biophysical model forced with satellite remote sensing. Despite the booms and busts in rainfall over the 2001 to 2017 period, we find that statewide water use is conservative, compared to the annual variability in rainfall. Nor do we detect that statewide evaporation is increasing as the climate has warmed over this period. We find that crops use less water than conventional wisdom because a subset of fields across a 1‐km pixel are fallow and are at peak leaf area and maximum evaporation potential for a relatively short period. Forests, on the other hand, use more water than conventional wisdom because they have a long growing season and absorb more energy than crops. Our intent is to provide water managers with new information on water use to better share water among the various stakeholders, for example, agricultural, cities, fish, ground water reservoirs, and water quality. Key Points: We produced new granular information (1‐km resolution) on evaporation across California using the biophysical model, Breathing Earth System SimulatorAnnual variations in evaporation were highly damped (393 mm/year +/− 5%) relative to the booms and busts in rainfall between 2001 and 2017 (+/− 28%)Statewide evaporation is not increasing with global warming, over 17 years of inspection, because feedbacks dampen the response to a warming climate [ABSTRACT FROM AUTHOR]

Abstract: Increased rainfall variability due to climate change significantly impacts carbon and water cycling in ecosystems, but these impacts may be masked when using arbitrary annual reporting periods such as the calendar year, which may not have any relevance to natural annual ecosystem processes. A variety of alternative annual integration periods have been described for specific purposes or locations, but are of limited general applicability. Here, we present an eddy covariance data‐driven empirical method to determine a locally relevant annual time period. The method selects a start date for a locally relevant water year (LRWY) that maximizes correlation between annual precipitation (AP), and annual evapotranspiration (AET) and annual gross primary production. The method was tested using data from 2004 to 2013 for 2 Ameriflux sites (woodland and grassland) in Central Texas. The timeframe included periods of unusually high rainfall and periods of extreme drought. The highest correlation between AP, and AET and annual gross primary production was obtained with an LRWY beginning in mid‐September. Use of the LRWY better captured the impact of soil water recharge in the autumn on photosynthesis the following spring than did calendar years. Use of the LRWY also identified more annual periods in which AET exceeded AP, which more accurately reflected the impact of drought on ecosystems processes than did analysis based on calendar years. [ABSTRACT FROM AUTHOR]

Abstract: Aerodynamic canopy height (ha) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface‐atmosphere coupling. However, methods to estimate ha from data are limited. This synthesis evaluates the applicability and robustness of the calculation of ha from eddy covariance momentum‐flux data. At 69 forest sites, annual ha robustly predicted site‐to‐site and year‐to‐year differences in canopy heights (R2 = 0.88, 111 site‐years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons (R2 > 0.70 in 74 site‐years). Our results demonstrate the potential of flux‐derived ha determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large‐scale and time‐varying ha derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. [ABSTRACT FROM AUTHOR]

Ecosystems where carbon fluxes are being monitored on a global scale are strongly biased toward temperate Northern Hemisphere latitudes. However, forest and moorland ecosystems in the Southern Hemisphere may contribute significantly to the global and regional C balance and are affected by different climate systems. Here, we present the first data from an old-growth forest representative of temperate, broad-leaved rainforests from southern South America. Carbon fluxes monitored over two years using the eddy covariance technique showed that this rainforest acts as an annual sink (-238 ± 31 g C/m²). However, there were significant pulses of carbon emission associated with dry episodes during the summer months (i.e., peak of the growing season) and periods of significant carbon fixation during the cold austral winter, indicating that the carbon balance in this forest is very sensitive to climate fluctuations. The carbon fixation surges in winter seem to be related to the mild temperatures recorded during this period of the year under the prevailing oceanic climate. Winter carbon gain was more relevant in determining the annual carbon balance than summer pulse emissions. Regarding the annual carbon balance, this southern forest resembles the patterns observed in montane tropical forests more than the behavior of narrow-leaved evergreen temperate forests from the Northern Hemisphere. These patterns make this southern forest type relevant to understanding the mechanisms and thresholds that control ecosystem shifts from carbon sinks and sources and will provide key data to improve global dynamic vegetation models. [ABSTRACT FROM AUTHOR]

The North American Land Data Assimilation System project phase 2 (NLDAS-2) has run four land surface models for a 30-year (1979-2008) retrospective period. Land surface evapotranspiration (ET) is one of the most important model outputs from NLDAS-2 for investigating land-atmosphere interaction or to monitor agricultural drought. Here, we evaluate hourly ET using in situ observations over the Southern Great Plains (Atmospheric Radiation Measurement/Cloud and Radiation Testbed network) for 1 January 1997-30 September 1999 and daily ET u-sing in situ observations at the AmeriFlux network over the conterminous USA for an 8-year period (2000-2007). The NLDAS-2 models compare well against observations, with the National Centers for Environmental Prediction's Noah land surface model performing best, followed, in order, by the Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic models. Daily evaluation across the AmeriFlux network shows that for all models, performance depends on season and vegetation type; they do better in spring and fall than in winter or summer and better for deciduous broadleaf forest and grasslands than for croplands or evergreen needleleaf forest. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Despite the availability of numerous approaches to estimate potential evapotranspiration ( PET), temperature-based PET equations such as the Hamon equation and Thornthwaite equation are still used to predict changes in hydrology in a changing climate as temperature is one of the primary reported outputs from general circulation models. To isolate the actual dependence of PET on temperature, we analysed meteorological and energy balance measurements from five AmeriFlux deciduous forest sites in the eastern United States during periods with minimal soil moisture control on transpiration. For all five sites, when PET measurements with similar net radiation are grouped, temperature does not correlate to PET within each group. Conversely when PET measurements with similar temperature are grouped, net radiation strongly correlates to PET within each group. In terms of assessing standard PET models, when dormant and growing season PET are separated, we found that the Priestley-Taylor equation (a model primarily dependent on net radiation) consistently explained more of the variation in PET than temperature-based methods such as the Hamon equation (median R of 0·88 vs 0·66). We illustrate that the moderate ability of temperature-based equations to predict PET arises from the correlation between temperature and net radiation when the meteorological observations are averaged over at least several days. However, we suggest that because temperature is not the fundamental driver of PET and because the relationship between temperature and net radiation underlying temperature-based equations will shift with climate change, temperature-based equations in their current state will likely exaggerate PET in a changing climate. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon-LAnd Model Intercomparison Project (C-LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie-Ames-Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO2 measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO2 and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr−1 for CASA′ vs. 1.2 Pg C yr−1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM ( r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C-LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community-wide platform for model-data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C-LAMP are publicly available on the Earth System Grid. [ABSTRACT FROM AUTHOR]

Variability in three Pacific teleconnection patterns are examined to see if net carbon exchange at a low-elevation, old-growth forest is affected by climatic changes associated with these periodicities. Examined are the Pacific Decadal Oscillation (PDO), Pacific/North American Oscillation (PNA) and El Niño-Southern Oscillation (ENSO). We use 9 years of eddy covariance CO2, H2O and energy fluxes measured at the Wind River AmeriFlux site, Washington, USA and 8 years of tower-pixel remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to address this question. We compute a new Composite Climate Index (CCI) based on the three Pacific Oscillations to divide the measurement period into positive- (2003 and 2005), negative- (1999 and 2000) and neutral-phase climate years (2001, 2002, 2004, 2006 and 2007). The forest transitioned from an annual net carbon sink (NEP=+217 g C m−2 yr−1, 1999) to a source (NEP=−100 g C m−2 yr−1, 2003) during two dominant teleconnection patterns. Net ecosystem productivity (NEP), water use efficiency (WUE) and light use efficiency (LUE) were significantly different ( P<0.01) during positive (NEP=−0.27 g C m−2 day−1, WUE=4.1 mg C g−1 H2O, LUE=0.94 g C MJ−1) and negative (NEP=+0.37 g C m−2 day−1, WUE=3.4 mg C g−1 H2O, LUE=0.83 g C MJ−1) climate phases. The CCI was linked to variability in the MODIS Enhanced Vegetation Index (EVI) but not to MODIS Fraction of absorbed Photosynthetically Active Radiation (FPAR). EVI was highest during negative climate phases (1999 and 2000) and was positively correlated with NEP and showed potential for using MODIS to estimate teleconnection-driven anomalies in ecosystem CO2 exchange in old-growth forests. This work suggests that any increase in the strength or frequency of ENSO coinciding with in-phase, low frequency Pacific oscillations (PDO and PNA) will likely increase CO2 uptake variability in Pacific Northwest conifer forests. [ABSTRACT FROM AUTHOR]

The article presents the study that uses archived networked digital cameras (webcams) imagery to record the spatial and temporal variation in forest canopies' autumn and spring phenology. It notes the imagery used were those from a deciduous, northern hardwood site and from a coniferous, boreal transition site. It cites its findings that the rate and timing of spring development and autumn senescence differ across the canopy, with high variability in autumn than spring.

While numerous algorithms exist for predicting incident atmospheric long-wave radiation under clear ( L clr) and cloudy skies, few comparisons have been published to assess the accuracy of the different algorithms. Virtually no comparisons have been made for both clear and cloudy skies across multiple sites. This study evaluates the accuracy of 13 algorithms for predicting incident long-wave radiation under clear skies, ten cloud correction algorithms, and four algorithms for all-sky conditions using data from 21 sites across North America and China. Data from five research sites were combined with publicly available data from nine sites in the AmeriFlux network for initial evaluation and optimization of cloud cover estimates; seven additional AmeriFlux sites were used as an independent test of the algorithms. Clear-sky algorithms that excelled in predicting L clr were the Dilley, Prata, and Ångström algorithms. Root mean square deviation (RMSD) between predicted and measured 30-minute or hourly L clr averaged approximately 23 W m−2 for these three algorithms across all sites, while RMSD of daily estimates was as low as 14 W m−2. Cloud-correction algorithms of Kimball, Unsworth, and Crawford described the data best when combined with the Dilley clear-sky algorithm. Average RMSD across all sites for these three cloud corrections was approximately 24 to 25 W m−2 for 30-minute or hourly estimates and approximately 15 to 16 W m−2 for daily estimates. The Kimball and Unsworth cloud corrections require an estimate of cloud cover, while the Crawford algorithm corrects for cloud cover directly from measured solar radiation. Optimum limits in the clearness index, defined as the ratio of observed solar radiation to theoretical terrestrial solar radiation, for complete cloud cover and clear skies were suggested for the Kimball and Unsworth algorithms. Application of the optimized algorithms to seven independent sites yielded similar results. On the basis of the results, the recommended algorithms can be applied with reasonable accuracy for a wide range of climates, elevations, and latitudes. [ABSTRACT FROM AUTHOR]

The article reports on the roles played by advective fluxes to the process of net ecosystem exchange in a highly elevated subalpine forest. This study done at the Niwot Ridge AmeriFlux site in Colorado, involved measurements of the vertical and horizontal advective carbon dioxide fluxes. It utilized a number of towers as measurement approach. Results show that low surface friction velocities noted comparatively high rates of horizontal and vertical advective fluxes. Moreover, horizontal advetive flux was confined to thin layers of subcanopy air, while the observed vertical advective flux is from above the canopy.

Tower-based eddy covariance measurements of forest-atmosphere carbon dioxide (CO2) exchange from many sites around the world indicate that there is considerable year-to-year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem respiration, Reco, and gross photosynthesis, Pgross) into two main effects: variation in environmental drivers (air and soil temperature, solar radiation, vapor pressure deficit, and soil water content) and variation in the biotic response to this environmental forcing (as characterized by the model parameters). The model is applied to a 9-year data set from the Howland AmeriFlux site, a spruce-dominated forest in Maine, USA. Gap-filled flux measurements at this site indicate that the forest has been sequestering, on average, 190 g C m−2 yr−1, with a range from 130 to 270 g C m−2 yr−1. Our fitted model predicts somewhat more uptake (mean 270 g C m−2 yr−1), but interannual variation is similar, and wavelet variance analyses indicate good agreement between tower measurements and model predictions across a wide range of timescales (hours to years). Associated with the interannual variation in NEE are clear differences among years in model parameters for both Reco and Pgross. Analysis of model predictions suggests that, at the annual time step, about 40% of the variance in modeled NEE can be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing. As model predictions are aggregated at longer timescales (from individual days to months to calendar year), variation in environmental drivers becomes progressively less important, and variation in the biotic response becomes progressively more important, in determining the modeled flux. There is a strong negative correlation between modeled annual Pgross and Reco ( r=−0.93, P≤0.001); two possible explanations for this correlation are discussed. The correlation promotes homeostasis of NEE: the interannual variation in modeled NEE is substantially less than that for either Pgross or Reco [ABSTRACT FROM AUTHOR]

Annual budgets and fitted temperature response curves for soil respiration and ecosystem respiration provide useful information for partitioning annual carbon budgets of ecosystems, but they may not adequately reveal seasonal variation in the ratios of these two fluxes. Soil respiration ( Rs) typically contributes 30–80% of annual total ecosystem respiration ( Reco) in forests, but the temporal variation of these ratios across seasons has not been investigated. The objective of this study was to investigate seasonal variation in the Rs/ Reco ratio in a mature forest dominated by conifers at Howland, ME, USA. We used chamber measurements of Rs and tower-based eddy covariance measurements of Reco. The Rs/ Reco ratio reached a minimum of about 0.45 in the early spring, gradually increased through the late spring and early summer, leveled off at about 0.65 for the summer, and then increased again to about 0.8 in the autumn. A spring pulse of aboveground respiration presumably causes the springtime minimum in this ratio. Soil respiration ‘catches up’ as the soils warm and as root growth presumably accelerates in the late spring, causing the Rs/ Reco ratios to increase. The summertime plateau of Rs/ Reco ratios is consistent with summer drought suppressing Rs that would otherwise be increasing, based on increasing soil temperature alone, thus causing the Rs/ Reco ratios to not increase as soils continue to warm. Declining air temperatures and litter fall apparently contribute to increased Rs/ Reco ratios in the autumn. Differences in phenology of growth of aboveground and belowground plant tissues, mobilization and use of stored substrates within woody plants, seasonal variation in photosynthate and litter substrates, and lags between temperature changes of air and soil contribute to a distinct seasonal pattern of Rs/ Reco ratios. [ABSTRACT FROM AUTHOR]

The partitioning of soil respiration rates into the component processes of rhizospheric respiration (because of live roots and those microorganisms that subsist on root exudations) and heterotrophic respiration (because of decomposer microorganisms that subsist on the oxidation of soil organic matter) is difficult to accomplish through experimental observation. In order to minimize disturbance to the soil and maximize preservation of the natural relationships among roots, rhizospheric microorganisms, and decomposers, we conducted a girdling experiment in a subalpine forest dominated by lodgepole pine trees. In two separate years, we girdled trees in small forest plots (5–7 m in diameter) and trenched around the plots to sever invading roots in order to experimentally stop the transport of photosynthate from needles to roots, and eliminate rhizospheric respiration. Soil respiration rates in plots with trees girdled over 1 year prior to measurement were higher than those in plots with trees girdled 2–3 months prior to measurement. These results suggest that any stimulation of respiration because of the experimental artifact of fine root death and addition of labile carbon to the pool of decomposer substrates is slow, and occurs beyond the first growing season after girdling. Compared with control plots with nongirdled trees, soil respiration rates in plots with girdled trees were reduced by 31–44% at the mid-summer respiratory maximum. An extreme drought during one of the 2 years used for observations caused greater reductions in the heterotrophic component of soil respiration compared with the rhizospheric component. In control plots, we observed a pulse in K2SO4-extractable carbon during the spring snowmelt period, which was absent in plots with girdled trees. In control plots, soil microbial biomass increased from spring to summer, coincident with a seasonal increase in the rhizospheric component of soil respiration. In plots with girdled trees, the seasonal increase in microbial biomass was lower than in control plots. These results suggest that the observed seasonal increase in rhizospheric respiration rate in control plots was because of an increase in rhizospheric microbial biomass following ‘soil priming’ by a spring-time pulse in dissolved organic carbon. Winter-time, beneath-snow microbial biomass was relatively high in control plots. Soil sucrose concentrations were approximately eight times higher during winter than during spring or summer, possibly being derived from the mechanical damage of shallow roots that use sucrose as protection against low-temperature extremes. The winter-time sucrose pulse was not observed in plots with girdled trees. The results of this study demonstrate that (1) the rhizospheric component of soil respiration rate at this site is significant in magnitude, (2) the heterotrophic component of soil respiration rate is more susceptible to seasonal drought than the rhizospheric component, and (3) the trees in this ecosystem exert a major control over soil carbon dynamics by ‘priming’ the soil with sugar exudates during the late-spring snowmelt period and releasing high concentrations of sucrose to the soil during winter. [ABSTRACT FROM AUTHOR]

Theδ13 Cvalues of atmospheric carbon dioxide (CO2) can be used to partition global patterns of CO2 source/sink relationships among terrestrial and oceanic ecosystems using the inversion technique. This approach is very sensitive to estimates of photosynthetic13 Cdiscrimination by terrestrial vegetation (ΔA), and depends onδ13 Cvalues of respired CO2 fluxes (δ13 CR). Here we show that by combining two independent data streams– the stable isotope ratios of atmospheric CO2 and eddy-covariance CO2 flux measurements– canopy scale estimates ofΔA can be successfully derived in terrestrial ecosystems. We also present the first weekly dataset of seasonal variations inδ13 CR from dominant forest ecosystems in the United States between 2001 and 2003. Our observations indicate considerable summer-time variation in the weekly value ofδ13 CR within coniferous forests (4.0‰ and 5.4‰ at Wind River Canopy Crane Research Facility and Howland Forest, respectively, between May and September). The monthly mean values ofδ13 CR showed a smaller range (2–3‰), which appeared to significantly correlate with soil water availability. Values ofδ13 CR were less variable during the growing season at the deciduous forest (Harvard Forest). We suggest that the negative correlation betweenδ13 CR and soil moisture content observed in the two coniferous forests should represent a general ecosystem response to the changes in the distribution of water resources because of climate change. Shifts inδ13 CR andΔA could be of sufficient magnitude globally to impact partitioning calculations of CO2 sinks between oceanic and terrestrial compartments. [ABSTRACT FROM AUTHOR]

Seven years of carbon dioxide flux measurements indicate that a∼90-year-old spruce dominated forest in Maine, USA, has been sequestering 174±46 g C m−2 yr−1 (mean±1 standard deviation, nocturnal friction velocity (u*) threshold>0.25 m s−1). An analysis of monthly flux anomalies showed that above-average spring and fall temperatures were significantly correlated with greater monthly C uptake while above-average summer temperatures were correlated with decreased net C uptake. Summer months with significantly drier or wetter soils than normal were also characterized by lower rates of C uptake. Years with above-average C storage were thus typically characterized by warmer than average spring and fall temperatures and adequate summer soil moisture.Environmental and forest–atmosphere flux data recorded from a second tower surrounded by similar forest, but sufficiently distant that flux source regions (‘footprints’), did not overlap significantly showed almost identical temperature and solar radiation conditions, but some differences in energy partitioning could be seen. Half-hourly as well as integrated (annual) C exchange values recorded at the separate towers were very similar, with average annual net C uptake differing between the two towers by<6%. Interannual variability in net C exchange was found to be much greater than between tower variability. Simultaneous measurements from two towers were used to estimate flux data uncertainty from a single tower. Carbon-flux model parameters derived independently from each flux tower data set were not significantly different, demonstrating that flux towers can provide a robust method for establishing C exchange model parameters. [ABSTRACT FROM AUTHOR]

Abstract Temporal trends in photosynthetic capacity are a critical factorin determining the seasonality and magnitude of ecosystem carbonfluxes. At a mixed deciduous forest in the south-eastern United States (Walker Branch Watershed, Oak Ridge, TN, USA), we independently measured seasonal trends in photosynthetic capacity (using single-leaf gas exchange techniques) and the whole-canopycarbon flux (using the eddy covariance method). Soil respiration was also measured using chambers and an eddy covariance system beneath the canopy. These independent chamber and eddy covariance measurements, along with a biophysical model (CANOAK), areused to examine how leaf age affects the seasonal pattern of carbon uptake during the growing season. When the measured seasonality in photosynthetic capacity is representedin the CANOAK simulations, there is good agreement with the eddy covariance data on the seasonal trends in carbon uptake. Removing the temporal trends in the simulations by using the early season maximum value of photosynthetic capacity over the entire growing season over estimates the annual carbon uptake by about 300 g C m-2 year-1 – halfthe total estimated annual net ecosystem exchange. Alternatively, use of the mean value of photosynthetic capacity incorrectly simulates the seasonality in carbon uptake by the forest. In addition to changes related to leaf development and senescence, photosynthetic capacitydecreased in the middle and late summer, even when leaf nitrogenwas essentially constant. When only these middle and late summer reductions were neglected in the model simulations, CANOAK still overestimated the carbon uptake by an amount comparable to 25% ofthe total annual net ecosystem exchange. [ABSTRACT FROM AUTHOR]

Abstract The fractional absorption of photosynthetically active radiation (f PAR ) is frequently a key variable in models describing terrestrial ecosystem–atmosphere interactions, carbon uptake, growth and biogeochemistry. We present a novel approach to the estimation of the fraction of incident photosynthetically active radiation absorbed by the photosynthetic components of a plant canopy (f Chl ). The method uses micrometeorological measurements of CO2 flux and incident radiation to estimate light response parameters from which canopy structure is deduced. Data from two Ameriflux sites in Oklahoma, a tallgrass prairie site and a wheat site, are used to derive 7-day moving average estimates of f Chl during three years (1997–1999). The inverse estimates are compared to long-term field measurements of PAR absorption. Good correlations are obtained when the field-measured f PAR is scaled by an estimate of the green fraction of total leaf area, although the inverse technique tends to be lower in value than the field measurements. The inverse estimates of f Chl using CO2 flux measurements are different from measurements of f PAR that might be made by other, more direct, techniques. However, because the inverse estimates are based on observed canopy CO2 uptake, they might be considered more biologically relevant than direct measurements that are affected by non-physiologically active components of the canopy. With the increasing number of eddy covariance sites around the world the technique provides the opportunity to examine seasonal and inter-annual variation in canopy structure and light harvesting capacity at individual sites. Furthermore, the inverse f Chl provide a new source of data for development and testing of f PAR retrieval using remote sensing. New remote sensing algorithms, or adjustments to existing algorithms, might... [ABSTRACT FROM AUTHOR]

Abstract We studied net ecosystem CO2 exchange (NEE) dynamics in a high-elevation, subalpine forest in Colorado, USA, over a two-year period. Annual carbon sequestration for the forest was 6.71 mol C m-2 (80.5 g C m-2 ) for the year between November 1, 1998 and October 31, 1999, and 4.80 mol C m-2 (57.6 g C m-2 ) for the year between November 1, 1999 and October 31, 2000. Despite its evergreen nature, the forest did not exhibit net CO2 uptake during the winter, even during periods of favourable weather. The largest fraction of annual carbon sequestration occurred in the early growing-season; during the first 30 days of both years. Reductions in the rate of carbon sequestration after the first 30 days were due to higher ecosystem respiration rates when mid-summer moisture was adequate (as in the first year of the study) or lower mid-day photosynthesis rates when mid-summer moisture was not adequate (as in the second year of the study). The lower annual rate of carbon sequestration during the second year of the study was due to lower rates of CO2 uptake during both the first 30 days of the growing season and the mid-summer months. The reduction in CO2 uptake during the first 30 days of the second year was due to an earlier-than-normal spring warm-up, which caused snow melt during a period when air temperatures were lower and atmospheric vapour pressure deficits were higher, compared to the first 30 days of the first year. The reduction in CO2 uptake during the mid-summer of the second year was due to an extended drought, which was accompanied by reduced latent heat exchange and increased sensible heat exchange. Day-to-day variation in the daily integrated NEE during the summers of both years was high, and was correlated with frequent convective storm clouds and concomitant variation in the photosynthetic photon flux density (PPFD). Carbon sequestration rates were... [ABSTRACT FROM AUTHOR]

SummaryCarbon dioxide, water vapour, and sensible heat fluxes were measured above and within a spruce dominated forest near the southern ecotone of the boreal forest in Maine, USA. Summer, mid-day carbon dioxide uptake was higher than at other boreal coniferous forests, averaging about – 13 μmol CO2 m–2 s–1. Nocturnal summer ecosystem respiration averaged ≈ 6 μmol CO2 m–2 s–1 at a mean temperature of ≈ 15 °C. Significant ecosystem C uptake began with the thawing of the soil in early April and was abruptly reduced by the first autumn frost in early October. Half-hourly forest CO2 exchange was regulated mostly by the incident photosynthetically active photon flux density (PPFD). In addition to the threshold effects of freezing temperatures, there were seasonal effects on the inferred photosynthetic parameters of the forest canopy. The functional response of this forest to environmental variation was similar to that of other spruce forests. In contrast to reports of carbon loss from northerly boreal forest sites, in 1996 the Howland forest was a strong carbon sink, storing about 2.1 t C ha–1. [ABSTRACT FROM AUTHOR]