Abstract:

Abstract. The Green Edge initiative was developed to investigate the processes controlling the primary productivity and fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797^??N, 63.7895^??W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea-ice cover from the surface to the bottom (at 360?m depth) to better understand the factors driving the PSB. Key variables, such as conservative temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured at the ice camp. Meteorological and snow-relevant variables were also monitored. Here, we present the results of a joint effort to tidy and standardize the collected datasets, which will facilitate their reuse in other Arctic studies. The dataset is available at https://doi.org/10.17882/59892 (Massicotte et al., 2019a).

Abstract: Abstract Many natural systems undergo critical transitions, i.e., sudden shifts from one dynamical regime to another. In the climate system, the atmospheric boundary layer can experience sudden transitions between fully turbulent states and quiescent, quasi-laminar states. Such rapid transitions are observed in polar regions or at night when the atmospheric boundary layer is stably stratified, and they have important consequences in the strength of mixing with the higher levels of the atmosphere. To analyze the stable boundary layer, many approaches rely on the identification of regimes that are commonly denoted as weakly and very stable regimes. Detecting transitions between the regimes is crucial for modeling purposes. In this work a combination of methods from dynamical systems and statistical modeling is applied to study these regime transitions and to develop an early warning signal that can be applied to nonstationary field data. The presented metric aims to detect nearing transitions by statistically quantifying the deviation from the dynamics expected when the system is close to a stable equilibrium. An idealized stochastic model of near-surface inversions is used to evaluate the potential of the metric as an indicator of regime transitions. In this stochastic system, small-scale perturbations can be amplified due to the nonlinearity, resulting in transitions between two possible equilibria of the temperature inversion. The simulations show such noise-induced regime transitions, successfully identified by the indicator. The indicator is further applied to time series data from nocturnal and polar meteorological measurements.

Abstract: Aim The conservation of biodiversity is hampered by data deficiencies, with many new species and subspecies awaiting description or reclassification. Population genomics and ecological niche modelling offer complementary new tools for uncovering functional units of phylogenetic diversity. We hypothesize that phylogenetically delineated lineages of gentoo penguins (Pygoscelis papua) distributed across Antarctica and sub-Antarctic Islands are subject to spatially explicit ecological conditions that have limited gene flow, facilitating genetic differentiation, and thereby speciation processes. Location Antarctica and sub-Antarctic area. Methods We identify divergent lineages for gentoo penguins using ddRAD-seq and mtDNA, and generated species distribution models (SDMs) based on terrestrial and marine parameters. Results Analyses of our genomic data supports the existence of four major lineages of gentoo penguin: (i) spanning the sub-Antarctic archipelagos north of the Antarctic Polar Front (APF); (ii) Kerguelen Island; (iii) South America; and (iv) across maritime Antarctic and the Scotia Arc archipelagos. The APF, a major current system around Antarctica, acts as the most important barrier separating regional sister lineages. Our ecological analyses spanning both the terrestrial (breeding sites) and marine (feeding sites) realms recover limited niche overlap among the major lineages of gentoo penguin. We observe this pattern to correspond more closely with regional differentiation of marine conditions than to terrestrial macroenvironmental features. Main conclusions Recognition of regional genetic lineages as discrete evolutionary entities that occupy distinct ecological niches and also differ morphologically should be considered a priority for conservation. Gentoo penguins provide a good example of how conservation policy can be directly impacted by new insights obtained through the integration of larger genomic datasets with novel approaches to ecological modelling. This is particularly pertinent to polar environments that are among the most rapidly changing environments on earth.