Abstract: The ocean’s meso- and submeso-scales (1-100 km, days to weeks) host features like filaments and eddies that have a key structuring effect on phytoplankton distribution, but that due to their ephemeral nature, are challenging to observe. This problem is exacerbated in regions with heavy cloud coverage and/or difficult access like the Southern Ocean, where observations of phytoplankton distribution by satellite are sparse, manned campaigns costly, and automated devices limited by power consumption. Here, we address this issue by considering high-resolution in-situ data from 18 bio-logging devices deployed on southern elephant seals (Mirounga leonina) in the Kerguelen Islands between 2018 and 2020. These devices have submesoscale-resolving capabilities of light profiles due to the high spatio-temporal frequency of the animals’ dives (on average 1.1 +-0.6 km between consecutive dives, up to 60 dives per day), but observations of fluorescence are much coarser due to power constraints. Furthermore, the chlorophyll a concentrations derived from the (uncalibrated) bio-logging devices’ fluorescence sensors lack a common benchmark to properly qualify the data and allow comparisons of observations. By proposing a method based on functional data analysis, we show that a reliable predictor of chlorophyll a concentration can be constructed from light profiles (14 686 in our study). The combined use of light profiles and matchups with satellite ocean-color data enable effective (1) homogenization then calibration of the bio-logging devices’ fluorescence data and (2) filling of the spatial gaps in coarse-grained fluorescence sampling. The developed method improves the spatial resolution of the chlorophyll a field description from ~30 km to ~12 km. These results open the way to empirical study of the coupling between physical forcing and biological response at submesoscale in the Southern Ocean, especially useful in the context of upcoming high-resolution ocean-circulation satellite missions.

Abstract: Arctic soils are constantly subjected to microbial invasion from either airborne, marine, or animal sources, which may impact local microbial communities and ecosystem functioning. However, in winter, Arctic soils are isolated from outside sources other than snow, which is the sole source of microorganisms. Successful colonisation of soil by snow microorganisms depends on the ability to survive and compete of both, the invading and resident community. Using shallow shotgun metagenome sequencing and amplicon sequencing, this study monitored snow and soil microbial communities throughout snow melt to investigate the colonisation process of Arctic soils. Microbial colonisation likely occurred as all the characteristics of successful colonisation were observed. The colonising microorganisms originating from the snow were already adapted to the local environmental conditions and were subsequently subjected to many similar conditions in the Arctic soil. Furthermore, competition-related genes (e.g. motility and virulence) increased in snow samples as the snow melted. Overall, one hundred potentially successful colonisers were identified in the soil and, thus, demonstrated the deposition and growth of snow microorganisms in soils during melt.

Abstract: Animal tracking has afforded insights into patterns of space use in numerous species and thereby informed area-based conservation planning. A crucial consideration when estimating spatial distributions from tracking data is whether the sample of tracked animals is representative of the wider population. However, it may also be important to track animals in multiple years to capture changes in distribution in response to varying environmental conditions. Using GPS-tracking data from 23 seabird species, we assessed the importance of multi-year sampling for identifying important sites for conservation during the chick-rearing period, when seabirds are most spatially constrained. We found a high degree of spatial overlap among distributions from different years in most species. Multi-year sampling often captured a significantly higher portion of reference distributions (based on all data for a population) than sampling in a single year. However, we estimated that data from a single year would on average miss only 5 % less of the full distribution of a population compared to equal-sized samples collected across three years (min: −0.3 %, max: 17.7 %, n = 23). Our results suggest a key consideration for identifying important sites from tracking data is whether enough individuals were tracked to provide a representative estimate of the population distribution during the sampling period, rather than that tracking necessarily take place in multiple years. By providing an unprecedented multi-species perspective on annual spatial consistency, this work has relevance for the application of tracking data to informing the conservation of seabirds.

Abstract: In ecology and evolution, the small population paradigm posits that reduced genetic variation will result in limited phenotypic variation that, in turn, will affect population resilience and potential for adaptation. Over the last decade though, such a paradigm has been questioned, with evidence that mechanisms independent of genetic variation may be also important in shaping phenotypic variation. However, there are few large-scale empirical examples, especially from aquatic ecosystems. Using the large-scale natural experiment afforded by the global invasion of brown trout (Salmo trutta), we quantify standing phenotypic variation in morphology among different introduced ranges, relative to the native range. By using shape variation and morphological integration as indicators of phenotypic variation, we show that neither founding population size nor time since founding (i.e., effect of selection regime) are correlated to the amount of morphological variation, contrarily to common expectations. Beyond founding population size and time since founding, the amount of morphological variation is mostly controlled by factors at the population level rather than at the region level, and is not lower in invaded regions compared to the native range. These results suggest that the dynamics of phenotypic variation may be largely independent of population size and mostly determined by site-specific patterns of selection.