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Abstract. The Greenland Ice Sheet has become the largest single frozen source of global sea level rise following a pronounced increase in meltwater runoff in recent decades. The pivotal role of anomalous anticyclonic circulation patterns in facilitating this increase has been widely documented; however, this change in atmospheric circulation has coincided with a rapidly warming Arctic. While amplified warming at high latitudes has undoubtedly contributed to trends in Greenland's mass loss, the contribution of this shift in background conditions relative to changes in regional circulation patterns has yet to be quantified. Here, we apply the pseudo-global warming method of dynamical downscaling to estimate the contribution of the change in the thermodynamic background state under global warming to observed Greenland Ice Sheet surface mass loss since the turn of the century. Our analysis demonstrates that, had the recent atmospheric dynamical forcing of the Greenland Ice Sheet occurred under a preindustrial setting, anomalous surface mass loss would have been reduced by over 62 % relative to observations. We show that the change in the thermodynamic environment under amplified Arctic warming has augmented melt of the ice sheet via longwave radiative effects accompanying an increase in atmospheric water vapor content. Furthermore, the thermodynamic contribution to surface mass loss over the exceptional melt years of 2012 and 2019 was less than half that of the long-term average, demonstrating a reduced influence during periods of strong synoptic-scale atmospheric forcing. 

Structural elements are widespread across genomes, but their complexity and role in repeatedly driving local adaptation remain unclear. In this work, we use phased genome assemblies to show that adaptive divergence in cryptic color pattern in a stick insect is repeatedly underlain by structural variation, but not a simple chromosomal inversion. We found that color pattern in populations of stick insects on two mountains is associated with translocations that have also been inverted. These translocations differ in size and origin on each mountain, but they overlap partially and involve some of the same gene regions. Moreover, this structural variation is subject to divergent selection and arose without introgression between species. Our results show how the origin of structural variation provides a mechanism for repeated bouts of adaptation. 

Sponges (phylum Porifera) possess biochemical, cellular, and physiological traits with valuable biotechnical applications. However, our ability to harness these natural innovations is limited by a classification system that does not fully reflect their evolutionary history. In this study, we uncover numerous cryptic species within the genus Halichondria that are morphologically indistinguishable from the well-known Ha. panicea. Many of these species have habitat preferences and geographic distributions that strongly suggest they have been dispersed by human activity. Most of these species are broadly sympatric with their closest relatives, and these overlapping distributions allow us to use patterns of DNA variation to infer reproductive isolation between clades in nature. With reproductively isolated species thus delineated, we can use DNA states as taxonomic characters to formally describe them. Though much remains to be learned about these newly discovered species, the natural “common gardens” of these sponges in California, New York, and other locations provide opportunities to test hypotheses about their diversification in future work. 

Each view of our environment captures only a subset of our immersive surroundings. Yet, our visual experience feels seamless. A puzzle for human neuroscience is to determine what cognitive mechanisms enable us to overcome our limited field of view and efficiently anticipate new views as we sample our visual surroundings. Here, we tested whether memory-based predictions of upcoming scene views facilitate efficient perceptual judgments across head turns. We tested this hypothesis using immersive, head-mounted virtual reality (VR). After learning a set of immersive real-world environments, participants (n = 101 across 4 experiments) were briefly primed with a single view from a studied environment and then turned left or right to make a perceptual judgment about an adjacent scene view. We found that participants’ perceptual judgments were faster when they were primed with images from the same (vs. neutral or different) environments. Importantly, priming required memory: it only occurred in learned (vs. novel) environments, where the link between adjacent scene views was known. Further, consistent with a role in supporting active vision, priming only occurred in the direction of planned head turns and only benefited judgments for scene views presented in their learned spatiotopic positions. Taken together, we propose that memory-based predictions facilitate rapid perception across large-scale visual actions, such as head and body movements, and may be critical for efficient behavior in complex immersive environments.