Abstract: Most of the microbial biogeographic patterns in the oceans have been depicted at the whole community level, leaving out finer taxonomic resolution (i.e., microdiversity) that is crucial to conduct intra-population phylogeographic study, as commonly done for macroorganisms. Here, we present a new approach to unravel the bacterial phylogeographic patterns combining community-wide survey by 16S rRNA gene metabarcoding and intra-species resolution through the oligotyping method, allowing robust estimations of genetic and phylogeographic indices, and migration parameters. As a proof-of-concept, we focused on the bacterial genus Spirochaeta across three distant biogeographic provinces of the Southern Ocean; maritime Antarctica, sub-Antarctic Islands, and Patagonia. Each targeted Spirochaeta operational taxonomic units were characterized by a substantial intrapopulation microdiversity, and significant genetic differentiation and phylogeographic structure among the three provinces. Gene flow estimations among Spirochaeta populations support the role of the Antarctic Polar Front as a biogeographic barrier to bacterial dispersal between Antarctic and sub-Antarctic provinces. Conversely, the Antarctic Circumpolar Current appears as the main driver of gene flow, connecting sub-Antarctic Islands with Patagonia and maritime Antarctica. Additionally, historical processes (drift and dispersal limitation) govern up to 86% of the spatial turnover among Spirochaeta populations. Overall, our approach bridges the gap between microbial and macrobial ecology by revealing strong congruency with macroorganisms distribution patterns at the populational level, shaped by the same oceanographic structures and ecological processes.

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: Most birds incubate their eggs, which requires time and energy at the expense of other activities. Birds generally have two incubation strategies: biparental where both mates cooperate in incubating eggs, and uniparental where a single parent incubates. In harsh and unpredictable environments, incubation is challenging due to high energetic demands and variable resource availability. We studied the relationships between the incubation behaviour of sandpipers (genus Calidris) and two environmental variables: temperature and a proxy of primary productivity (i.e. NDVI). We investigated how these relationships vary between incubation strategies and across species among strategies. We also studied how the relationship between current temperature and incubation behaviour varies with previous day's temperature. We monitored the incubation behaviour of nine sandpiper species using thermologgers at 15 arctic sites between 2016 and 2019. We also used thermologgers to record the ground surface temperature at conspecific nest sites and extracted NDVI values from a remote sensing product. We found no relationship between either environmental variables and biparental incubation behaviour. Conversely, as ground-surface temperature increased, uniparental species decreased total duration of recesses (TDR) and mean duration of recesses (MDR), but increased number of recesses (NR). Moreover, small species showed stronger relationships with ground-surface temperature than large species. When all uniparental species were combined, an increase in NDVI was correlated with higher mean duration, total duration and number of recesses, but relationships varied widely across species. Finally, some uniparental species showed a lag effect with a higher nest attentiveness after a warm day while more recesses occurred after a cold day than was predicted based on current temperatures. We demonstrate the complex interplay between shorebird incubation strategies, incubation behaviour, and environmental conditions. Understanding how species respond to changes in their environment during incubation helps predict their future reproductive success.