Abstract: Breeding failure is expected to induce behavioural changes in central place foragers. Indeed, after a failed reproductive attempt, breeding individuals are relieved from having to return to their breeding site for reproductive duties and thus are less constrained than successful breeders in their movements during the remainder of the breeding season. Accordingly, they are expected to adjust their behaviour, travelling longer in distance and/or time to reach foraging grounds. They are also expected to use different foraging areas to decrease local intra-specific competition with successful breeders. We compared the at-sea behaviour and habitat use of successful and failed Indian yellow-nosed albatrosses nesting in Amsterdam Island, Southern Indian Ocean, during 2 chick-rearing seasons. Failed breeders exhibited the same at-sea foraging behaviour, travelling as far and as long as successful breeders. They also spent the same amount of time on their nest between at-sea trips. Nevertheless, habitat models revealed partial spatial segregation of failed breeders, which used specific foraging areas characterized by deeper and colder waters in addition to the areas they shared with successful breeders. Our study shows the importance of combining a range of analytical methods (spatial analysis, behavioural inferences with advanced movement models and habitat models) to infer the at-sea behaviour and habitat use of seabirds. It also stresses the importance of considering individual breeding status when aiming to understand the spatial distribution of individuals, especially when this information may have conservation implications.

Abstract: The IRAP Plasmasphere Ionosphere Model (IPIM) is an ionospheric model which describes the transport equations of ionospheric plasma species along magnetic closed field lines. As input, the previous iteration of IPIM used basic models to provide estimations of the solar wind conditions, convection, and precipitation within the ionosphere. In this presentation, we discuss the development of a new operational version of IPIM as part of the EUHFORIA project to monitor and forecast space weather conditions and hazards. The developments of the model include using in-situ solar wind observations from the OMNI data set, ionospheric radar data of plasma motions from the Super Dual Auroral Radar Network (SuperDARN), and precipitation data from the Ovation model, as inputs to the model. A new conductivity module for low latitudes has also been developed for help in the simulation of geomagnetically induced currents. We present the first results from the latest IPIM version which explore the ionosphere's response to different solar wind conditions, before focussing on an extreme coronal mass ejection on 14th July 2012 with clear magnetic cloud and southward magnetic field. For this event, we explore simulations of important plasma properties of the ionosphere and compare with previous model iterations and all available observations and hence describe the skill of using IPIM as a space weather forecasting tool.

Abstract:

Due to recent climate change conditions, i.e. increasing temperatures and changing precipitation patterns, arctic snow cover dynamics exhibit strong changes in terms of extent and duration. Arctic amplification processes and impacts are well documented expected to strengthen in coming decades. In this context, innovative observation methods are helpful for a better comprehension of the spatial variability of snow properties relevant for climate research and hydrological applications.

Microwave remote sensing provides exceptional spatial and temporal performance in terms of all-weather application and target penetration. Time-series of Synthetic Active Radar images (SAR) are becoming more accessible at different frequencies and polarimetry has demonstrated a significant advantage for detecting changes in different media. Concerning arctic snow monitoring, SAR sensors can offer continuous time-series during the polar night and with cloud cover, providing a consequent advantage in regard of optical sensors.

The aim of this study is dedicated to the spatial/temporal variability of snow in the Ny-Ålesund area on the Br∅gger peninsula, Svalbard (N 78°55’ / E 11° 55’). The TerraSAR-X satellite (DLR, Germany) operated at X-band (3.1 cm, 9.6 GHz) with dual co-pol mode (HH/VV) at 5-m spatial resolution, and with high incidence angles (36° to 39°) poviding a better snow penetration and reducing topographic constraints. A dataset of 92 images (ascending and descending) is available since 2017, together with a high resolution DEM (NPI 5-m) and consistent in-situ measurements of meteorological data and snow profiles including glaciers sites.

Polarimetric processing is based on the Kennaugh matrix decomposition, copolar phase coherence (CCOH) and copolar phase difference (CPD). The Kennaugh matrix elements K₀, K₃, K_4, and K₇ are, respectively, the total intensity, phase ratio, intensity ratio, and shift between HH and VV phase center. Their interpretation allows analysing the structure of the snowpack linked to the near real time of in-situ measurements (snow profiles).

The X-band signal is strongly influenced by the snow stratigraphy: internal ice layers reduce or block the penetration of the signal into the snow pack. The best R² correlation performances between estimated and measured snow heights are ranging from 0.50 to 0.70 for dry snow conditions. Therefore, the use of the X-band for regular snow height estimations remains limited under these conditions.

Conversely, this study shows the benefit of TerraSAR-X thanks to the Kennaugh matrix elements analysis. A focus is set on the Copolar Phase Difference (CPD, Leinss 2016) between VV and HH polarization: Φ CPD = Φ _VV – Φ _HH. Our results indicate that the CPD values are related to the snow metamorphism: positive values correspond to dry snow (horizontal structures), negative values indicate recrystallization processes (vertical structures).

Backscattering evolution in time offer a good proxy for meteorological events detection, impacting on snow metamorphism. Fresh snowfalls or melting processes can then be retrieved at the regional scale and linked to air temperature or precipitation measurements at local scale. Polarimetric SAR time series is therefore of interest to complement satellite-based precipitation measurements in the Arctic.

Abstract: Fossorial locomotion is often considered as the most energetically costly of all terrestrial locomotion. Small arctic rodents, such as lemmings, dig tunnels not only in the soil but also through the snowpack, which is present for over 8 months of the year. Lemmings typically dig in the softest snow layer called the depth hoar but with climate change, melt-freeze and rain-on-snow (ROS) events are expected to increase in the Arctic, leading to a higher frequency of hardened snowpacks. We assessed the impacts of snow hardness on the locomotion of two lemming species showing different morphological adaptations for digging. We hypothesized that an increase in snow hardness would (1) decrease lemming performance and (2) increase their effort while digging, but those responses would differ between lemming species. We exposed four brown lemmings (Lemmus trimucronatus) and three collared lemmings (Dicrostonyx groenlandicus) to snow of different hardness (soft, hard, and ROS) during 30-min trials (n = 63 trials) in a cold room and filmed their behavior. We found that the digging speed and tunnel length of both species decreased with snow hardness and density, underlining the critical role of snow properties in affecting lemming digging performance. During the ROS trials, time spent digging by lemmings increased considerably and they also started using their incisors to help break the hard snow, validating our second hypothesis. Overall, digging performance was higher in collared lemmings, the species showing more morphological adaptations to digging, than in brown lemmings. We conclude that the digging performance of lemming is highly dependent on snowpack hardness and that the anticipated increase in ROS events may pose a critical energetic challenge for arctic rodent populations.