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abstract: In recent years, ecological research has become increasingly synthetic, relying on revolutionary changes in data availability and accessibility. In spite of their strengths, these approaches may cause us to overlook natural history knowledge that is not part of the digitized English-language scientific record. Here, we combine historic and modern documents to quantify species-specific nesting habitat associations of bumblebees (Bombus spp. Latreille, 1802 Apidae). We compiled nest location data from 316 documents, of which 81 were non-English and 93 were published before 1950. We tested whether nesting traits show phylogenetic signal, examined relationships between habitat associations at different scales, and compared methodologies used to locate nests. We found no clear phylogenetic signals, but we found that nesting habitat associations were somewhat generalizable within subgenera. Landcover associations were related to nesting substrate associations; for example, surface-nesting species also tended to be associated with grasslands. Methodology was associated with nest locations; community scientists were most likely and researchers using nest boxes were least likely to report nests in human-dominated environments. These patterns were not apparent in past syntheses based only on the modern digital record. Our findings highlight the tremendous value of historic accounts for quantifying species’ traits and other basic biological knowledge needed to interpret global-scale patterns. 

Numerous declines have been documented across insect groups, and the potential consequences of insect losses are dire. Butterflies are the most surveyed insect taxa, yet analyses have been limited in geographic scale or rely on data from a single monitoring program. Using records of 12.6 million individual butterflies from >76,000 surveys across 35 monitoring programs, we characterized overall and species-specific butterfly abundance trends across the contiguous United States. Between 2000 and 2020, total butterfly abundance fell by 22% across the 554 recorded species. Species-level declines were widespread, with 13 times as many species declining as increasing. The prevalence of declines throughout all regions in the United States highlights an urgent need to protect butterflies from further losses. 

Abstract Schmidt’s game and other similar intersection games have played an important role in recent years in applications to number theory, dynamics, and Diophantine approximation theory. These games are real games, that is, games in which the players make moves from a complete separable metric space. The determinacy of these games trivially follows from the axiom of determinacy for real games, $$\mathsf {AD}_{\mathbb R}$$ , which is a much stronger axiom than that asserting all integer games are determined, $$\mathsf {AD}$$ . One of our main results is a general theorem which under the hypothesis $$\mathsf {AD}$$ implies the determinacy of intersection games which have a property allowing strategies to be simplified. In particular, we show that Schmidt’s $$(\alpha ,\beta ,\rho )$$ game on $$\mathbb R$$ is determined from $$\mathsf {AD}$$ alone, but on $$\mathbb R^n$$ for $$n \geq 3$$ we show that $$\mathsf {AD}$$ does not imply the determinacy of this game. We then give an application of simple strategies and prove that the winning player in Schmidt’s $$(\alpha , \beta , \rho )$$ game on $$\mathbb {R}$$ has a winning positional strategy, without appealing to the axiom of choice. We also prove several other results specifically related to the determinacy of Schmidt’s game. These results highlight the obstacles in obtaining the determinacy of Schmidt’s game from $$\mathsf {AD}$$ . 

ABSTRACT Transformation, the uptake of DNA directly from the environment, is a major driver of gene flow in microbial populations. In bacteria, DNA uptake requires a nuclease that processes dsDNA to ssDNA, which is subsequently transferred into the cell and incorporated into the genome. However, the process of DNA uptake in archaea is still unknown. Previously, we cataloged genes essential to natural transformation inMethanococcus maripaludis, but few homologs of bacterial transformation‐associated genes were identified. Here, we characterize one gene, MMJJ_16440 (named here asecnA), to be an extracellular nuclease. We show that EcnA is Ca²⁺‐activated, present on the cell surface, and essential for transformation. While EcnA can degrade several forms of DNA, the highest activity was observed with ssDNA as a substrate. Activity was also observed with circular dsDNA, suggesting that EcnA is an endonuclease. This is the first biochemical characterization of a transformation‐associated protein in a member of the archaeal domain and suggests that both archaeal and bacterial transformation initiate in an analogous fashion. 

Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question. 

The Informatics Skunkworks program provides a new framework for engaging undergraduates in research experiences, with a focus on the interface of data science and materials science. The program seeks to provide authentic research, engaged personal learning, and professional development while also being efficient, accessible, and scalable. Initially developed at the University of Wisconsin-Madison, participation continues to grow, with over 90 students engaged in research or training activities during the Fall 2021 semester from 4 institutions. The Skunkworks focuses on reducing barriers to engagement for mentors and students in undergraduate research by replacing bespoke and ad-hoc approaches with efforts and infrastructure that are reusable and scalable, including simplified standardized recruiting methods, online modular training resources, flexible undergraduate accessible software tools, long-term research projects with many similar but distinct components to engage large teams, and support from a learning community. For example, new students have the option to participate in a modular, self-paced, online onboarding curriculum that teaches students the basic skills needed for most data science projects, thereby dramatically reducing the mentor time needed to engage students with limited background in machine learning research. Projects are authentic research challenges that strive to allow for large flexible teams, thereby scaling up their impact from the typical engagement of just one or two students and allowing for extensive peer teaching. Throughout the program, professional development activities are efficiently delivered through standardized materials to teach critical research skills like record keeping, establishing group expectations and dynamics, and networking. These skills are also reinforced at workshop events hosted during the semester, which are effectively delivered online and yield growing impact for modest effort as the community grows. The program has been successfully implemented as evidenced by the last two semesters' evaluation findings through interviews, focus groups, and pre-post surveys. The students reported a positive attitude towards the program. Students' perception about machine learning knowledge and skills and their self-confidence improved after they got involved in the program. The instructors and mentors indicated positive teaching and mentoring experiences, and shared ideas on the further improvement of the program. Building on its early successes the team is continuing to implement evaluation data-driven improvements to the program with the goal of continuing to grow through new collaborations. 

We introduce the notion of [Formula: see text]-determinacy for [Formula: see text] a pointclass and [Formula: see text] an equivalence relation on a Polish space [Formula: see text]. A case of particular interest is the case when [Formula: see text] is the (left) shift-action of [Formula: see text] on [Formula: see text] where [Formula: see text] or [Formula: see text]. We show that for all shift actions by countable groups [Formula: see text], and any “reasonable” pointclass [Formula: see text], that [Formula: see text]-determinacy implies [Formula: see text]-determinacy. We also prove a corresponding result when [Formula: see text] is a subshift of finite type of the shift map on [Formula: see text].