The measured net ecosystem exchange (NEE) of CO2 between the ecosystem and the atmosphere reflects the balance between gross CO2 assimilation [gross primary production (GPP)] and ecosystem respiration (R-eco). For understanding the mechanistic responses of ecosystem processes to environmental change it is important to separate these two flux components. Two approaches are conventionally used: (1) respiration measurements made at night are extrapolated to the daytime or (2) light-response curves are fit to daytime NEE measurements and respiration is estimated from the intercept of the ordinate, which avoids the use of potentially problematic nighttime data. We demonstrate that this approach is subject to biases if the effect of vapor pressure deficit (VPD) modifying the light response is not included. We introduce an algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE, modified to account for the temperature sensitivity of respiration and the VPD limitation of photosynthesis. Including the VPD dependency strongly improved the model's ability to reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the reliability of R-eco estimates given that the reduction of GPP by VPD may be otherwise incorrectly attributed to higher R-eco. Results from this improved algorithm are compared against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 g C m(-2) yr(-1)), while errors arising from the random error (median absolute deviation: similar to 2 g C m(-2) yr(-1)) are negligible. Despite site-specific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and R-eco is not spurious but holds true when quasi-independent, i.e. daytime and nighttime based estimates are compared
Deforestation in mid-to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes [1][2][3] . In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback 4,5 . This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead 5 . Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner 6,7 . Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 6 0.44 K (mean 6 one standard deviation) northwards of 456 N and 0.21 6 0.53 K southwards. Below 356 N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models 8 .The latitudinal gradient of land-use impact is evident in the comparison of the surface air temperature recorded at FLUXNET (www.fluxnet.ornl.gov) forest towers 9 (Supplementary Table 1 and Supplementary Fig. 1) and surface weather stations in North America (Fig. 1a). Here we use the surface stations as proxies for cleared land. In accordance with the requirement of the World Meteorological Organization, these stations are located in open grassy fields that have biophysical characteristics similar to those of open land, such as being covered by snow in northern latitudes in the winter 10 . Latitude accounts for 31% of the variations in the temperature difference DT between the forest sites and the adjacent open lands (number of site pairs n 5 37). The rate of change in DT with latitude is 20.070 6 0.010 K per degree (mean 6 one standard error, s.e., P , 0.005). At these sites, the annual net all-wave radiation R n
The carbon balance of terrestrial ecosystems is particularly sensitive to climatic changes in autumn and spring, with spring and autumn temperatures over northern latitudes having risen by about 1.1 degrees C and 0.8 degrees C, respectively, over the past two decades. A simultaneous greening trend has also been observed, characterized by a longer growing season and greater photosynthetic activity. These observations have led to speculation that spring and autumn warming could enhance carbon sequestration and extend the period of net carbon uptake in the future. Here we analyse interannual variations in atmospheric carbon dioxide concentration data and ecosystem carbon dioxide fluxes. We find that atmospheric records from the past 20 years show a trend towards an earlier autumn-to-winter carbon dioxide build-up, suggesting a shorter net carbon uptake period. This trend cannot be explained by changes in atmospheric transport alone and, together with the ecosystem flux data, suggest increasing carbon losses in autumn. We use a process-based terrestrial biosphere model and satellite vegetation greenness index observations to investigate further the observed seasonal response of northern ecosystems to autumnal warming. We find that both photosynthesis and respiration increase during autumn warming, but the increase in respiration is greater. In contrast, warming increases photosynthesis more than respiration in spring. Our simulations and observations indicate that northern terrestrial ecosystems may currently lose carbon dioxide in response to autumn warming, with a sensitivity of about 0.2 PgC degrees C(-1), offsetting 90% of the increased carbon dioxide uptake during spring. If future autumn warming occurs at a faster rate than in spring, the ability of northern ecosystems to sequester carbon may be diminished earlier than previously suggested.
Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO 2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were 566-584, doi: 10.1111/j.1365-2486.2011.02562.x This article is a U.S. government work, and is not subject to copyright in the United States.Global Change Biology (2012) 18,typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m À2 yr À1 during the spring transition period and +75 ± 130 g C m À2 yr À1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO 2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models.
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