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Non-photosynthetic components within a forest ecosystem account for a large proportion of the canopy but are not involved in photosynthesis. Therefore, the accuracy of gross primary production (GPP) estimates is expected to improve by removing these components. However, their influence in GPP estimations has not been quantitatively evaluated for deciduous forests. Several vegetation indices have been used recently to estimate the fraction of photosynthetically active radiation absorbed by photosynthetic components ( FAPAR green ) for partitioning APAR green (photosynthetically active radiation absorbed by photosynthetic components). In this study, the enhanced vegetation index (EVI) estimated FAPAR green and to separate the photosynthetically active radiation absorbed by photosynthetic components ( APAR green ) from total APAR observations ( APAR total ) at two deciduous forest sites. The eddy covariance-light use efficiency (EC-LUE) algorithm was employed to evaluate the influence of non-photosynthetic components and to test the performance of APAR green in GPP estimation. The results show that the influence of non-photosynthetic components have a seasonal pattern at deciduous forest sites, large differences are observed with normalized root mean square error (RMSE*) values of APAR green -based GPP and APAR total -based GPP between tower-based GPP during the early and end stages, while slight differences occurred during peak growth seasons. In addition, daily GPP estimation was significantly improved using the APAR green -based method, giving a higher coefficient of determination and lower normalized root mean square error against the GPP estimated by the APAR total -based method. The results demonstrate the significance of partitioning APAR green from APAR total for accurate GPP estimation in deciduous forests. [ABSTRACT FROM AUTHOR]

Wetlands are the largest natural source of methane (CH4); however, the contribution of subtropical wetlands to global CH4 budgets is still unclear due to difficulties in accurately quantifying CH4 emissions from these complex ecosystems. Both direct (water management strategies) and indirect (altered weather patterns associated with climate change) anthropogenic influences are also leading to greater uncertainties in our ability to determine changes in CH4 emissions from these ecosystems. This study compares CH4 fluxes from two freshwater marshes with different hydroperiods (short versus long) in the Florida Everglades to examine temporal patterns and biophysical drivers of CH4 fluxes. Both sites showed similar seasonal patterns across years with higher CH4 release during wet seasons versus dry seasons. The long hydroperiod site showed stronger seasonal patterns and overall, emitted more CH4 than the short hydroperiod site; however, no distinctive diurnal patterns were observed. We found that air temperature was a significant positive driver of CH4 fluxes for both sites regardless of season. In addition, gross ecosystem exchange was a significant negative predictor of CH4 emissions in the dry season at the long hydroperiod site. CH4 fluxes were impacted by water level and its changes over site and season, and time scales, which are influenced by rainfall and water management practices. Thus with increasing water distribution associated the Comprehensive Everglades Restoration Plan we expect increases in CH4 emissions, and when couple with increased with projected higher temperatures in the region, these increases may be enhanced, leading to greater radiative forcing. [ABSTRACT FROM AUTHOR]

In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1–3.2 days decade−1) compared to the spring (0.9–1.5 days decade−1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling. [ABSTRACT FROM AUTHOR]

How aquatic primary productivity influences the carbon (C) sequestering capacity of wetlands is uncertain. We evaluated the magnitude and variability in aquatic C dynamics and compared them to net ecosystem CO2 exchange (NEE) and ecosystem respiration (Reco) rates within calcareous freshwater wetlands in Everglades National Park. We continuously recorded 30-min measurements of dissolved oxygen (DO), water level, water temperature (Twater), and photosynthetically active radiation (PAR). These measurements were coupled with ecosystem CO2 fluxes over 5 years (2012–2016) in a long-hydroperiod peat-rich, freshwater marsh and a short-hydroperiod, freshwater marl prairie. Daily net aquatic primary productivity (NAPP) rates indicated both wetlands were generally net heterotrophic. Gross aquatic primary productivity (GAPP) ranged from 0 to − 6.3 g C m−2 day−1 and aquatic respiration (RAq) from 0 to 6.13 g C m−2 day−1. Nonlinear interactions between water level, Twater, and GAPP and RAq resulted in high variability in NAPP that contributed to NEE. Net aquatic primary productivity accounted for 4–5% of the deviance explained in NEE rates. With respect to the flux magnitude, daily NAPP was a greater proportion of daily NEE at the long-hydroperiod site (mean = 95%) compared to the short-hydroperiod site (mean = 64%). Although we have confirmed the significant contribution of NAPP to NEE in both long- and short-hydroperiod freshwater wetlands, the decoupling of the aquatic and ecosystem fluxes could largely depend on emergent vegetation, the carbonate cycle, and the lateral C flux. [ABSTRACT FROM AUTHOR]

Background: To improve estimates of net primary production for terrestrial ecosystems of the continental United States, we evaluated a new image fusion technique to incorporate high resolution Landsat land cover data into a modified version of the CASA ecosystem model. The proportion of each Landsat land cover type within each 0.004 degree resolution CASA pixel was used to influence the ecosystem model result by a pure-pixel interpolation method. Results: Seventeen Ameriflux tower flux records spread across the country were combined to evaluate monthly NPP estimates from the modified CASA model. Monthly measured NPP data values plotted against the revised CASA model outputs resulted in an overall R of 0.72, mainly due to cropland locations where irrigation and crop rotation were not accounted for by the CASA model. When managed and disturbed locations are removed from the validation, the R increases to 0.82. Conclusions: The revised CASA model with pure-pixel interpolated vegetation index performed well at tower sites where vegetation was not manipulated or managed and had not been recently disturbed. Tower locations that showed relatively low correlations with CASA-estimated NPP were regularly disturbed by either human or natural forces. [ABSTRACT FROM AUTHOR]

A simple and accurate method to estimate evapotranspiration (ET) is essential for dynamic monitoring of the Earth system at a large scale. In this paper, we developed an artificial neural network (ANN) model forced by remote sensing and AmeriFlux data to estimate ET. First, the ANN was trained with ET measurements made at 13 AmeriFlux sites and land surface products derived from satellite remotely sensed data (normalized difference vegetation index, land surface temperature and surface net radiation) for the period 2002-2006. ET estimated with the ANN was then validated by ET observed at five AmeriFlux sites during the same period. The validation sites covered five different vegetation types and were not involved in the ANN training. The coefficient of determination ( R) value for comparison between estimated and measured ET was 0.77, the root-mean-square error was 0.62 mm/d, and the mean residual was − 0.28. The simple model developed in this paper captured the seasonal and interannual variation features of ET on the whole. However, the accuracy of estimated ET depended on the vegetation types, among which estimated ET showed the best result for deciduous broadleaf forest compared to the other four vegetation types. [ABSTRACT FROM AUTHOR]

Understanding relationships between canopy structure and the seasonal dynamics of photosynthetic uptake of CO2 by forest canopies requires improved knowledge of canopy phenology at eddy covariance flux tower sites. We investigated whether digital webcam images could be used to monitor the trajectory of spring green-up in a deciduous northern hardwood forest. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Bartlett AmeriFlux site. Images were collected each day around midday. Red, green, and blue color channel brightness data for a 640 × 100-pixel region-of-interest were extracted from each image. We evaluated the green-up signal extracted from webcam images against changes in the fraction of incident photosynthetically active radiation that is absorbed by the canopy ( f APAR), a broadband normalized difference vegetation index (NDVI), and the light-saturated rate of canopy photosynthesis ( A max), inferred from eddy flux measurements. The relative brightness of the green channel (green %) was relatively stable through the winter months. A steady rising trend in green % began around day 120 and continued through day 160, at which point a stable plateau was reached. The relative brightness of the blue channel (blue %) also responded to spring green-up, although there was more day-to-day variation in the signal because blue % was more sensitive to changes in the quality (spectral distribution) of incident radiation. Seasonal changes in blue % were most similar to those in f APAR and broadband NDVI, whereas changes in green % proceeded more slowly, and were drawn out over a longer period of time. Changes in A max lagged green-up by at least a week. We conclude that webcams offer an inexpensive means by which phenological changes in the canopy state can be quantified. A network of cameras could offer a novel opportunity to implement a regional or national phenology monitoring program. [ABSTRACT FROM AUTHOR]

The transition between wintertime net carbon loss and springtime net carbon assimilation has an important role in controlling the annual rate of carbon uptake in coniferous forest ecosystems. We studied the contributions of springtime carbon assimilation to the total annual rate of carbon uptake and the processes involved in the winter-to-spring transition across a range of scales from ecosystem CO2 fluxes to chloroplast photochemistry in a coniferous, subalpine forest. We observed numerous initiations and reversals in the recovery of photosynthetic CO2 uptake during the initial phase of springtime recovery in response to the passage of alternating warm- and cold-weather systems. Full recovery of ecosystem carbon uptake, whereby the 24-h cumulative sum of NEE (NEEdaily) was consistently negative, did not occur until 3–4 weeks after the first signs of photosynthetic recovery. A key event that preceded full recovery was the occurrence of isothermality in the vertical profile of snow temperature across the snow pack; thus, providing consistent daytime percolation of melted snow water through the snow pack. Interannual variation in the cumulative annual NEE (NEEannual) was mostly explained by variation in NEE during the snow-melt period (NEEsnow-melt), not variation in NEE during the snow-free part of the growing season (NEEsnow-free). NEEsnow-melt was highest in those years when the snow melt occurred later in the spring, leading us to conclude that in this ecosystem, years with earlier springs are characterized by lower rates of NEEannual, a conclusion that contrasts with those from past studies in deciduous forest ecosystems. Using studies on isolated branches we showed that the recovery of photosynthesis occurred through a series of coordinated physiological and biochemical events. Increasing air temperatures initiated recovery through the upregulation of PSII electron transport caused in part by disengagement of thermal energy dissipation by the carotenoid, zeaxanthin. The availability of liquid water permitted a slightly slower recovery phase involving increased stomatal conductance. The most rate-limiting step in the recovery process was an increase in the capacity for the needles to use intercellular CO2, presumably due to slow recovery of Rubisco activity. Interspecific differences were observed in the timing of photosynthetic recovery for the dominant tree species. The results of our study provide (1) a context for springtime CO2 uptake within the broader perspective of the annual carbon budget in this subalpine forest, and (2) a mechanistic explanation across a range of scales for the coupling between springtime climate and the carbon cycle of high-elevation coniferous forest ecosystems. [ABSTRACT FROM AUTHOR]

Fluxes of carbon dioxide, water and sensible heat were measured using three different eddy covariance systems above the forest floor of a closed deciduous forest (leaf area index approx 6). The primary objective was to examine the representativeness of a single eddy covariance system in estimating soil respiration for time scales ranging from one-half hour to more than one week. Experiments were conducted in which the eddy covariance sensors were in one of three configurations: i) collocated, ii) separated horizontally or iii) separated vertically. A measure of the variation between the three systems (CV',related to the coefficient of variation) for half-hour carbon dioxide fluxes was 0.14 (collocated systems), 0.34 (vertically separated systems at 1, 2 and 4 m above the surface), and 0.57 (systems horizontally separated by 30 m). A similar variation was found for other scalar fluxes (sensible and latent heat). Variability between systems decreased as the number of half-hour sampling periods used to obtain mean fluxes was increased. After forty-eight hours (means from ninety-six half-hour samples), CV' values for carbon dioxide fluxes were 0.07, 0.09 and 0.16 in the collocated, vertically separated and horizontally separated experiments, respectively. The time dependence of variability has implications on the appropriateness of using short-term measurements in modelling validation studies. There are also implications concerning the appropriate number of half-hour samples necessary to obtain reliable causal relationships between flux data and environmental parameters. Based on the longer-term measurements, we also discuss the representativeness of a single eddy covariance system in long-term monitoring of soil respiration and evaporation beneath forest canopies using the eddy covariance method. [ABSTRACT FROM AUTHOR]

To assess annual budgets of CO2 exchange between the biosphere and atmosphere over representative ecosystems, long-term measurements must be made over ecosystems that do not exist on ideal terrain. How to interpret eddy covariance measurements correctly remains a major task. At present, net ecosystem CO2 exchange is assessed, by members of the micrometeorological community, as the sum of eddy covariance measurements and the storage of CO2 in the underlying air. This approach, however, seems unsatisfactory as numerous investigators are reporting that it may be causing nocturnal respiration flux densities to be underestimated. A new theory was recently published by Lee (1998, Agricultural and Forest Meteorology 91: 39–50) for assessing net ecosystem-atmosphere CO2 exchange (Ne) over non-ideal terrain. It includes a vertical advection term. We apply this equation over a temperate broadleaved forest growing in undulating terrain. Inclusion of the vertical advection term yields hourly, daily and annual sums of net ecosystem CO2 exchange that are more ecologically correct during the growing season. During the winter dormant period, on the other hand, corrected CO2 flux density measurements of an actively respiring forest were near zero. This observation is unrealistic compared to chamber measurements and model calculations. Only during midday, when the atmosphere is well-mixed, do measurements of Ne match estimates based on model calculations and chamber measurements. On an annual basis, sums of Ne without the advection correction were 40% too large, as compared with computations derived from a validated and process-based model. With the inclusion of the advection correction term, we observe convergence between measured and calculated values of Ne on hourly, daily and yearly time scales. We cannot, however, conclude that inclusion of a one-dimensional, vertical advection term into the continuity equation is sufficient for evaluating CO2 exchange over tall forests in complex terrain. There is an indication that the neglected term, ū}(∂ c/∂ x), is non-zero and that CO2 may be leaking from the sides of the control volume during the winter. In this circumstance, forest floor CO2 efflux densities exceed effluxes measured above the canopy. [ABSTRACT FROM AUTHOR]