Macroinvertebrate abundance and proportion of trait categories in river biotopes across England and Wales

There is a long tradition of river monitoring using macroinvertebrate communities to assess environmental quality in Europe. A promising alternative is the use of species life-history traits. Both methods, however, have relied on the time-consuming identification of taxa. River biotopes, 1-100 m**2 'habitats' with associated species assemblages, have long been seen as a useful and meaningful way of linking the ecology of macroinvertebrates and river hydro-morphology and can be used to assess hydro-morphological degradation in rivers. Taxonomic differences, however, between different rivers had prevented a general test of this concept until now. The species trait approach may overcome this obstacle across broad geographical areas, using biotopes as the hydro-morphological units which have characteristic species trait assemblages. We collected macroinvertebrate data from 512 discrete patches, comprising 13 river biotopes, from seven rivers in England and Wales. The aim was to test whether river biotopes were better predictors of macroinvertebrate trait profiles than taxonomic composition (genera, families, orders) in rivers, independently of the phylogenetic effects and catchment scale characteristics (i.e. hydrology, geography and land cover). We also tested whether species richness and diversity were better related to biotopes than to rivers. River biotopes explained 40% of the variance in macroinvertebrate trait profiles across the rivers, largely independently of catchment characteristics. There was a strong phylogenetic signature, however. River biotopes were about 50% better at predicting macroinvertebrate trait profiles than taxonomic composition across rivers, no matter which taxonomic resolution was used. River biotopes were better than river identity at explaining the variability in taxonomic richness and diversity (40% and <=10%, respectively). Detailed trait-biotope associations agreed with independent a priori predictions relating trait categories to near river bed flows. Hence, species traits provided a much needed mechanistic understanding and predictive ability across a broad geographical area. We show that integration of the multiple biological trait approach with river biotopes at the interface between ecology and hydro-morphology provides a wealth of new information and potential applications for river science and management.

Ice characteristics, and mercury content of ice, air and underlying seawater in the eastern Beaufort Sea

The Arctic sea-ice environment has been undergoing dramatic changes in the past decades; to which extent this will affect the deposition, fate, and effects of chemical contaminants remains virtually unknown. Here, we report the first study on the distribution and transport of mercury (Hg) across the ocean-sea-ice-atmosphere interface in the Southern Beaufort Sea of the Arctic Ocean. Despite being sampled at different sites under various atmospheric and snow cover conditions, Hg concentrations in first-year ice cores were generally low and varied within a remarkably narrow range (0.5-4 ng/L), with the highest concentration always in the surface granular ice layer which is characterized by enriched particle and brine pocket concentration. Atmospheric Hg depletion events appeared not to be an important factor in determining Hg concentrations in sea ice except for frost flowers and in the melt season when snowpack Hg leaches into the sea ice. The multiyear ice core showed a unique cyclic feature in the Hg profile with multiple peaks potentially corresponding to each ice growing/melting season. The highest Hg concentrations (up to 70 ng/L) were found in sea-ice brine and decrease as the melt season progresses. As brine is the primary habitat for microbial communities responsible for sustaining the food web in the Arctic Ocean, the high and seasonally changing Hg concentrations in brine and its potential transformation may have a major impact on Hg uptake in Arctic marine ecosystems under a changing climate.

(Table 3) Air temperatures, and snow and ice characteristics of fresh and brackish water lakes in the Northwest Territories, Canada

The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80x100 m were used as ground-truth to evaluate the simulations. The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of -8.4 K and -8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (-5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R= -0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (-4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.

Properties of seawater (partial pressure of carbon dioxide (pCO2)) from a ProOceanus CO2-Pro sensor mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements of partial pressure of carbon dioxide (pCO2), using a ProOceanus CO2-Pro instrument mounted on the flowthrough system. This automatic sensor is fitted with an equilibrator made of gas permeable silicone membrane and an internal detection loop with a non-dispersive infrared detector of PPSystems SBA-4 CO2 analyzer. A zero-CO2 baseline is provided for the subsequent measurements circulating the internal gas through a CO2 absorption chamber containing soda lime or Ascarite. The frequency of this automatic zero point calibration was set to be 24 hours. All data recorded during zeroing processes were discarded with the 15-minute data after each calibration. The output of CO2-Pro is the mole fraction of CO2 in the measured water and the pCO2 is obtained using the measured total pressure of the internal wet gas. The fugacity of CO2 (fCO2) in the surface seawater, whose difference with the atmospheric CO2 fugacity is proportional to the air-sea CO2 fluxes, is obtained by correcting the pCO2 for non-ideal CO2 gas concentration according to Weiss (1974). The fCO2 computed using CO2-Pro measurements was corrected to the sea surface condition by considering the temperature effect on fCO2 (Takahashi et al., 1993). The surface seawater observations that were initially estimated with a 15 seconds frequency were averaged every 5-min cycle. The performance of CO2-Pro was adjusted by comparing the sensor outputs against the thermodynamic carbonate calculation of pCO2 using the carbonic system constants of Millero et al. (2006) from the determinations of total inorganic carbon (CT ) and total alkalinity (AT ) in discrete samples collected at sea surface. AT was determined using an automated open cell potentiometric titration (Haraldsson et al. 1997). CT was determined with an automated coulometric titration (Johnson et al. 1985; 1987), using the MIDSOMMA system (Mintrop, 2005). fCO2 data are flagged according to the WOCE guidelines following Pierrot et al. (2009) identifying recommended values and questionable measurements giving additional information about the reasons of the questionability.

Land Surface Temperature continuous time series from SSM/I passive microwave radiometers, over northern latitudes (Latitudes > 45°N), during summer snow free period (2000-2011), with links to NetCDF files

Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.