Arachidonic Acid/ppara Enhancement of Ca2+-Regulated Exocytosis in Antral Mucous Cells of Guinea Pig

N is known to be the most limiting element for vegetation growth in temperate and boreal forests. The expected increases in global temperature are predicted to accelerate N mineralization, therefore incrementing N availability in the soil and affecting the soil C cycle as well. While there is an abundance of C data collected to fulfill the requirements for national GHG accounting, more limited information is available for soil N accumulation and storage in relation to forest categories and altitudinal gradients. The data collected by the second Italian National Forest Inventory, spanning a wide range of temperature and precipitation values (10° latitudinal range), represented a unique opportunity to calculate N content and C/N ratio of the different soil layers to a depth of 30 cm. Boosted Regression Tree (BRT) models were applied to investigate the main determinants of soil N distribution and C/N ratio. Forest category was shown to be the main explanatory factor of soil N variability in seven out of eight models, both for forest floor and mineral soil layers. Moreover latitude explained a larger share of variability than single climate variables. BRT models explained, on average, the 49% of the data variability, with the remaining fraction likely due to soil-related variables that were unaccounted for. Accurate estimations of N pools and their determinants in a climate change perspective are consequently required to predict the potential impact of their degradation on forest soil N pools

Intercomparison of MODIS Albedo Retrievals and In Situ Measurements Across the Global FLUXNET Network

Surface albedo is a key parameter in the Earth's energy balance since it affects the amount of solar radiation directly absorbed at the planet surface. Its variability in time and space can be globally retrieved through the use of remote sensing products. To evaluate and improve the quality of satellite retrievals, careful intercomparisons with in situ measurements of surface albedo are crucial. For this purpose we compared MODIS albedo retrievals with surface measurements taken at 53 FLUXNET sites that met strict conditions of land cover homogeneity. A good agreement between mean yearly values of satellite retrievals and in situ measurements was found (R(exp 2)= 0.82). The mismatch is correlated to the spatial heterogeneity of surface albedo, stressing the relevance of land cover homogeneity when comparing point to pixel data. When the seasonal patterns of MODIS albedo is considered for different plant functional types, the match with surface observation is extremely good at all forest sites. On the contrary, in non-forest sites satellite retrievals underestimate in situ measurements across the seasonal cycle. The mismatch observed at grasslands and croplands sites is likely due to the extreme fragmentation of these landscapes, as confirmed by geostatistical attributes derived from high resolution scenes

Intercomparison of MODIS albedo retrievals and in situ measurements across the global FLUXNET network

Surface albedo is a key parameter in the Earth's energy balance since it affects the amount of solar radiation directly absorbed at the planet surface. Its variability in time and space can be globally retrieved through the use of remote sensing products. To evaluate and improve the quality of satellite retrievals, careful intercomparisons with in situ measurements of surface albedo are crucial. For this purpose we compared MODIS albedo retrievals with surface measurements taken at 53 FLUXNET sites that met strict conditions of land cover homogeneity. A good agreement between mean yearly values of satellite retrievals and in situ measurements was found (r² = 0.82). The mismatch is correlated with the spatial heterogeneity of surface albedo, stressing the relevance of land cover homogeneity when comparing point to pixel data. When the seasonal patterns of MODIS albedo are considered for different plant functional types, the match with surface observations is extremely good at all forest sites. On the contrary, satellite retrievals at non-forested sites (grasslands, savannas, croplands) underestimate in situ measurements across the seasonal cycle. The mismatch observed at grassland and cropland sites is likely due to the extreme fragmentation of these landscapes, as confirmed by geostatistical attributes derived from high resolution scenes.Keywords: FLUXNET, Remote sensing, Validation, Surface albedo, Plant functional types, MODIS, Terrestrial ecosystem

Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

This is the publisher’s final pdf. The published article is copyrighted by American Geophysical Union and can be found at: http://sites.agu.org/.Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (V[subscript cm]), and quantum yield (alpha) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAI(F) for a large range of sites, comparable to the LAI[subscript M] derived from MODIS. There are discrepancies when LAI[subscript F] reach zero levels and LAI[subscript M] still provides a small positive value. We find that temperature is the most common constraint for LAI[subecript F] in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAI[subscript F] or LAI[subscript M](r² = 0.89). We investigated further the seasonal variation of ecosystem-scale parameters derived with LAI[subscript F]. V[subscript cm] has the largest seasonal variation. This holds for all vegetation types and climates. The parameter alpha is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen

The uncertain climate footprint of wetlands under human pressure

Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems,making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse– response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange

Experimental analysis of flux footprint for varying stability conditions in an alpine meadow

Eddy-covariance measurements, which were performed in the summer 2003 in an alpine grassland site, were used to determine the footprint of CO2 turbulent fluxes and to investigate its dependence on stability. The analysis is based on the spatial variability of carbon sinks generated by the difference in the time of the cutting of two concentric portions of the footprint, located outside and inside the fence surrounding the eddy tower, at approximately 30 m distance. Due to this time difference, turbulent flux measurements were performed both in homogeneous (BEFORE and AFTER cutting) and heterogeneous (BETWEEN cuts) condition of spatial sink distribution. The analysis is based exclusively on daytime measurements. Half-hourly records ranked in two stability classes were used to calculate light response functions separately for three 10-day periods (BEFORE, BETWEEN and AFTER cutting). The contribution of the area inside the fence to the total flux was determined for different photosynthetic photon flux density (PPFD) values considering the BETWEEN cuts light response curve as a weighted average of the BEFORE and AFTER ones. The weight of the BEFORE cutting light response curve has been analytically determined and corresponds to the flux fraction which originates from inside the fence. The experimental estimates of the relative importance of the area inside the fence produced values ranging from 30%, during stable conditions, and up to 80% during unstable conditions. These values derived from observations were later compared with the predictions of three analytical footprint models. One of the models systematically underestimated experimental observations, while observations concurred with the other two, particularly in moderately unstable conditions

Canopy architecture and turbulence structure in a coniferous forest

Synchronous sonic anemometric measurements at five heights within a mixed coniferous forest were used to test two different parameterisations ofcanopy architecture in the application of a second-order turbulence closure model. Inthe computation of the leaf drag area, the aerodynamic sheltering was replaced with anarchitectural sheltering, assumed to be analogous to the clumping index defined in radiativetransfer theory. Consequently, the ratio of leaf area density and sheltering factor was approximatedby the effective leaf area or the mean contact number, both obtained from the inversion of non-destructive optical measurements. The first parameter represents the equivalentrandomly dispersed leaf area in terms of shading, the second is the average number of leavesthat a straight line intercepts penetrating the canopy with a certain zenith angle. Theselection of this direction was determined by the analysis of the mean angle of the wind vectorduring sweep events. The drag coefficient values obtained from the inversion of themomentum flux equation, using the two proposed parameterisations, are in good agreement withvalues found in the literature. The predicted profiles of turbulence statistics reasonablymatch actual measurements, especially in the case of the mean contact numberparameterisation. The vertical profile of leaf drag area, obtained by forcing the turbulence modelto match the observed standard deviation of vertical velocity (w), is intermediatebetween the two empirical ones. Finally, the proposed canopy parameterisations were appliedto a Lagrangian transport model to predict vertical profiles of air temperature, H2O andCO2 concentration