Ammonia emissions from deciduous forest after leaf fall

The understanding of biochemical feedback mechanisms in the climate system is lacking knowledge in relation to bi-directional ammonia (NH3) exchange between natural ecosystems and the atmosphere. We therefore study the atmospheric NH3 fluxes during a 25-day period during autumn 2010 (21 October to 15 November) for the Danish beech forest Lille Bøgeskov to address the hypothesis that NH3 emissions occur from deciduous forests in relation to leaf fall. This is accomplished by using observations of vegetation status, NH3 fluxes and model calculations. Vegetation status was observed using plant area index (PAI) and leaf area index (LAI). NH3 fluxes were measured using the relaxed eddy accumulation (REA) method. The REA-based NH3 concentrations were compared to NH3 denuder measurements. Model calculations of the atmospheric NH3 concentration were obtained with the Danish Ammonia MOdelling System (DAMOS). The relative contribution from the forest components to the atmospheric NH3 flux was assessed using a simple two-layer bi-directional canopy compensation point model. A total of 57.7% of the fluxes measured showed emission and 19.5% showed deposition. A clear tendency of the flux going from deposition of −0.25 ± 0.30 μg NH3-N m−2 s−1 to emission of up to 0.67 ± 0.28 μg NH3-N m−2 s−1 throughout the measurement period was found. In the leaf fall period (23 October to 8 November), an increase in the atmospheric NH3 concentrations was related to the increasing forest NH3 flux. Following leaf fall, the magnitude and temporal structure of the measured NH3 emission fluxes could be adequately reproduced with the bi-directional resistance model; it suggested the forest ground layer (soil and litter) to be the main contributing component to the NH3 emissions. The modelled concentration from DAMOS fits well the measured concentrations before leaf fall, but during and after leaf fall, the modelled concentrations are too low. The results indicate that the missing contribution to atmospheric NH3 concentration from vegetative surfaces related to leaf fall are of a relatively large magnitude. We therefore conclude that emissions from deciduous forests are important to include in model calculations of atmospheric NH3 for forest ecosystems. Finally, diurnal variations in the measured NH3 concentrations were related to meteorological conditions, forest phenology and the spatial distribution of local anthropogenic NH3 sources. This suggests that an accurate description of ammonia fluxes over forest ecosystems requires a dynamic description of atmospheric and vegetation processes

Mapping leaf nitrogen and leaf area index in European landscapes using high spatial resolution satellite data and the REGularized canopy reFLECtance (REGFLEC) model

Leaf biochemistry and biophysical parameters are important for simulating soil‐vegetation‐atmosphere exchanges of energy, water, CO2 and ammonia. The accumulation of leaf nitrogen (N) in vegetation canopies is a major component of the ecosystem N balance, and leaf N concentration and leaf area index (LAI) are important determinants of the maximum CO2 uptake by plants and trees. In NEU, high spatial resolution remote sensing data from the SPOT satellite were acquired to prepare maps of leaf N and LAI for 5 European landscapes. Mapping was conducted using the REGFLEC model which is an automatic and image‐based methodology developed for regional chlorophyll (Cab) and LAI estimation (ie. Houborg and Andersen, JARS 3, 2009). REGFLEC combines models for atmospheric correction (6S), canopy reflectance (ACRM) and leaf optics (PROSPECT). Model performance previously proved promising in Denmark and in Maryland, USA. In this study, REGFLEC performance is evaluated and discussed using field measurements of leaf N, SPADmeter data and LAI in Denmark, Poland, Scotland, the Netherlands and Italy. The inverse model estimations of soil reflectance parameters and canopy parameters are discussed in relation to the prevailing soil types and vegetation characteristics of land cover classes across the 5 European landscapes

Daytime habitat selection for juvenile parr brown trout (Salmo trutta) in small lowland streams

Physical habitat is important in determining the carrying capacity of juvenile brown trout, and within freshwater management. Summer daytime physical habitat selection for the parr lifestage (7–20 cm) juvenile brown trout (Salmo trutta) was assessed in 6 small lowland streams. Habitat preference was determined for the four variables; water velocity, water depth, substrate and cover, and the preferences for physical habitat selection were expressed in terms of habitat suitability indices (HSI’s). The statistical confidence of HSI’s was evaluated using power analysis. It was found that a minimum of 22 fish observations was needed to have statistical confidence in the HSIs for water depth, and a minimum of 92 fish observations for water velocity during daytime summer conditions. Generally parr were utilising the deeper habitats, indicating preference for deeper water. Cover was also being selected for at all sites, but selection was inconsistent among sites for the variables substrate and velocity. The results indicate that during daytime summer conditions water depth is a significant variable for parr habitat selection in these small lowland streams, with cover also being important. Therefore, daytime refugia may be a critical limiting factor for parr in small lowland streams, and important for stream management actions under the Water Framework Directive

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales

Canopy-scale biophysical controls on transpiration and evaporation in the Amazon Basin

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales