Theoretical model simulations for variations in thermal reaction norms

Thermal reaction norms for growth rates of six Emiliania huxleyi isolates originating from the central Atlantic (Azores, Portugal) and five isolates from the coastal North Atlantic (Bergen, Norway) were assessed. We used the template mode of variation model to decompose variations in growth rates into modes of biological interest: vertical shift, horizontal shift, and generalist-specialist variation. In line with the actual habitat conditions, isolates from Bergen (Bergen population) grew well at lower temperatures, and isolates from the Azores (Azores population) performed better at higher temperatures. The optimum growth temperature of the Azores population was significantly higher than that of the Bergen population. Neutral genetic differentiation was found between populations by microsatellite analysis. These findings indicate that E. huxleyi populations are adapted to local temperature regimes. Next to between-population variation, we also found variation within populations. Genotype-by-environment interactions resulted in the most pronounced phenotypic differences when isolates were exposed to temperatures outside the range they naturally encounter. Variation in thermal reaction norms between and within populations emphasizes the importance of using more than one isolate when studying the consequences of global change on marine phytoplankton. Phenotypic plasticity and standing genetic variation will be important in determining the potential of natural E. huxleyi populations to cope with global climate change.

Topsoil properties and abundance of Acari and Collembola species in northern Victoria Land, Antarctica

Soil fauna in the extreme conditions of Antarctica consists of a few microinvertebrate species patchily distributed at different spatial scales. Populations of the prostigmatic mite Stereotydeus belli and the collembolan Gressittacantha terranova from northern Victoria Land (Antarctica) were used as models to study the effect of soil properties on microarthropod distributions. In agreement with the general assumption that the development and distribution of life in these ecosystems is mainly controlled by abiotic factors, we found that the probability of occurrence of S. belli depends on soil moisture and texture and on the sampling period (which affects the general availability of water); surprisingly, none of the analysed variables were significantly related to the G. terranova distribution. Based on our results and literature data, we propose a theoretical model that introduces biotic interactions among the major factors driving the local distribution of collembolans in Antarctic terrestrial ecosystems.

Time-series of snow spectral albedo and superficial snow specific surface area at Dome C in Antarctica, 2012-2015

Spectral albedo has been measured at Dome C since December 2012 in the visible and near infrared (400 - 1050 nm) at sub-hourly resolution using a home-made spectral radiometer. Superficial specific surface area (SSA) has been estimated by fitting the observed albedo spectra to the analytical Asymptotic Approximation Radiative Transfer theory (AART). The dataset includes fully-calibrated albedo and SSA that pass several quality checks as described in the companion article. Only data for solar zenith angles less than 75° have been included, which theoretically spans the period October-March. In addition, to correct for residual errors still affecting data after the calibration, especially at the solar zenith angles higher than 60°, we produced a higher quality albedo time-series as follows: In the SSA estimation process described in the companion paper, a scaling coefficient A between the observed albedo and the theoretical model predictions was introduced to cope with these errors. This coefficient thus provides a first order estimate of the residual error. By dividing the albedo by this coefficient, we produced the "scaled fully-calibrated albedo". We strongly recommend to use the latter for most applications because it generally remains in the physical range 0-1. The former albedo is provided for reference to the companion paper and because it does not depend on the SSA estimation process and its underlying assumptions.