Tree xylem sapflow rates of 140-year-old Norway spruce (Picea abies) were scaled to the stand level and compared to canopy transpiration predicted by the stand gas exchange model STANDFLUX.Variation in sapflux densities between individual sensors was high (coef- ficient of variance = 0.4) and included both variation within and between trees, but it was not dif- ferent between two applied sapflow methodologies (radial flowmeter according to Granier, vari- able heating tissue heat balance method according to Cermák and Kucera).During the morning, a time-lag of typically 2 h elapsed between sapflow (E f ) and predicted canopy transpiration rate (E p ).During this time total water use was as high as 0.3 mm, which was less than the estimated capacity of easily available water in the tree canopy (0.45 mm, on average 14 L per tree).Canopy conductance derived from stand sapflow rates (g f ) and from STANDFLUX (g p ) was in the same range (g tmax : 10 mm s -1 ), but a stronger decline with increasing vapor pressure deficit of the air
Abstract Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO 2 based on 163 site‐years of eddy covariance data, from 39 northern‐hemisphere research sites located at latitudes ranging from ∼29°N to ∼64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.
Seasonal changes in canopy photosynthetic activity play an important role in carbon assimilation. However, few simulation models for estimating carbon balances have included them due to scarcity in quality data. This paper investigates some important aspects of the relationship between the seasonal trajectory of photosynthetic capacity and the time series of a common vegetation index (normalized difference vegetation index, NDVI), which was derived from on site micrometeorological measurements or smoothed and downscaled from satellite‐borne NDVI sensors. A parameter indicating the seasonality of canopy physiological activity, P E, was retrieved through fitting a half‐hour step process model, PROXELNEE, to gross primary production (GPP) estimates by inversion for carboxylation and light utilization efficiencies. The relative maximum rate of carboxylation (V rm), a parameter that indicates the seasonality of CO2 uptake potential under prevailing temperature, was then calculated from P E and daily average air temperature. Statistical analysis revealed that there were obvious exponential relationships between NDVI and the seasonal courses for both canopy physiological activities P E and V rm. Among them, the on‐site broadband NDVI provided a robust and consistent relationship with canopy physiological activities (R 2 = 0.84). The relationships between satellite‐borne NDVI time series with instantaneous canopy physiological activities at the time of satellite passing were also checked. The results indicate that daily step NDVI time series (data downscaled from composite temporal resolution NDVI) better represent the daily average activity of the canopy. These findings may enable us to retrieve the seasonal course of canopy physiological activity from widely available NDVI data series and, thus, to include it into carbon assimilation models. However, both smoothing methods for satellite‐borne NDVI time series may generate incorrect estimates and must be treated with care.
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