Colgate University

Climate change is expected to induce shifts in the composition, structure and functioning of Arctic tundra ecosystems. Increases in the frequency and severity of tundra fires have the potential to catalyse vegetation transitions with far‐reaching local, regional and global consequences. We propose that post‐fire tundra recovery, coupled with climate change, may not necessarily lead to pre‐fire conditions. Our hypothesis, based on surveys and literature, suggests two climate–fire driven trajectories. One trajectory results in increased woody vegetation under low fire frequency; the other results in grass dominance under high frequency. Future research should address uncertainties regarding possible tundra ecosystem shifts linked to fires, using methods that encompass greater temporal and spatial scales than previously addressed. More case studies, especially in underrepresented regions and ecosystem types, are essential to broaden the empirical basis for forecasts and potential fire management strategies. Synthesis. Our review synthesises current knowledge on post‐fire vegetation trajectories in Arctic tundra ecosystems, highlighting potential transitions and alternative ecosystem states and their implications. We discuss challenges in defining and predicting these trajectories as well as future directions.

The vertebrate segmentation clock drives periodic somite segmentation during embryonic development. Her1 and Her7 clock proteins generate oscillatory expression of their own genes as well as that of deltaC in zebrafish. In turn, DeltaC and DeltaD ligands activate Notch signaling, which then activates transcription of clock genes in neighboring cells. While DeltaC and DeltaD proteins form homo- and heterodimers, only DeltaC-containing oscillatory dimers were expected to be functional. To investigate the contributions of DeltaC and DeltaD proteins on the transcription of her1 and her7 segmentation clock genes, we counted their transcripts by performing single molecule fluorescent in situ hybridization imaging in different genetic backgrounds of zebrafish embryos. Surprisingly, we found that DeltaD homodimers are also functional. We further found that Notch signaling promotes transcription of both deltaC and deltaD genes, thereby creating a previously unnoticed positive feedback loop. Our computational model highlighted the intriguing differential roles of DeltaC and DeltaD dimers on the clock synchronization and transcript numbers, respectively. We anticipate that a mechanistic understanding of the Notch signaling pathway will not only shed light on the mechanism driving robust somite segmentation but also inspire similar quantitative studies in other tissues and organs.

Neuromorphic computing takes biological inspiration to the device level aiming to improve computational efficiency and capabilities. One of the major issues that arises is the training of neuromorphic hardware systems. Typically training algorithms require global information and are thus inefficient to implement directly in hardware. In this paper we describe a set of reinforcement learning based, local weight update rules and their implementation in superconducting hardware. Using SPICE circuit simulations, we implement a small-scale neural network with a learning time of order one nanosecond per update. This network can be trained to learn new functions simply by changing the target output for a given set of inputs, without the need for any external adjustments to the network. Further, this architecture does not require programing explicit weight values in the network, alleviating a critical challenge with analog hardware implementations of neural networks.

Superconducting electronics is a promising technology for many future computing solutions including superconducting digital processors, superconducting neuromorphic circuits, and superconducting quantum computing, Josephson junctions are at the heart of all of these, and the ability to simulate the dynamics of circuits of Josephson junctions is essential for the progress of these fields. The state-of-art software for simulating classical Josephson junction circuits represents their dynamics using a system of differential-algebraic equations (DAEs). Solving DAEs can lead to potentially erroneous outputs due to poor error control. Here we present a method of simulating Josephson junction circuits based on graph theory that eliminates all algebraic equations to create a system of only Ordinary Differential Equations (ODEs). This system of ODEs can be solved using a variable-step solver, which allows more precise error control.

In situ observed data are commonly used as species occurrence response variables in species distribution models. However, the use of remotely observed data from high‐resolution multispectral remote‐sensing images as a source of presence/absence data for species distribution models remains under‐developed. Here, we describe an ensemble species distribution model of black microbial mats (Nostoc spp.) using presence/absence points derived from the unmixing of 4‐m resolution WorldView‐2 and WorldView‐3 images in the Lake Fryxell basin region of Taylor Valley, Antarctica. Environmental and topographical characteristics such as soil moisture, snow, elevation, slope, and aspect were used as predictor variables in our models. We demonstrate that we can build and run ensemble species distribution models using both dependent and independent variables derived from remote‐sensing data to generate spatially explicit habitat suitability maps. Snow and soil moisture were found to be the most important variables accounting for about 80% of the variation in the distribution of black mats throughout the Fryxell basin. This study highlights the potential contribution of high‐resolution remote‐sensing to species distribution modeling and informs new studies incorporating remotely derived species occurrences in species distribution models, especially in remote areas where access to in situ data is often limited.

This article develops a more‐than‐human conception of charisma to explain the interrelated magnetism of palaeontologists and prehistoric megafauna in the United States since the nineteenth century. It extends anthropological analysis of charisma to non‐human bodies, and argues that charisma is created by more‐than‐human processes involving tactile interactions among people and matter within particular social and political‐economic contexts. This historical and ethnographic study of a few iconic dinosaur specimens, and the famed scientists who have collected, studied, and mounted them, shows how the more‐than‐human charisma of vertebrate palaeontology has been shaped by the violent masculinity that rose to prominence in conjunction with the exploration and colonization of the western United States. It further demonstrates how the virile charisma of certain scientists and fossils continues to be a powerful force that mobilizes people to dedicate enormous resources and labour to them.

Objectives For LGBTQ+ communities, learning often happens among chosen families, including older adults. Building on Pierre Bourdieu’s theoretical concepts of capital (e.g., economic, social, cultural, symbolic) and queer theory of sexual capital, this article examines how LGBTQ+ chosen families share expertise to build knowledge and power across the life course. Methods Using a transformative sequential mixed methods design from a larger project, this subproject includes data from six intracategorical focus groups with multigenerational and multiracial LGBTQ+ participants (n=37), including older adults, in a Midwestern community to center their voices, understand their experiences within and outside LGBTQ+ communities, foreground experiences of LGBTQ+ aging, and explore challenges and supports. Results We identified three ways in which LGBTQ+ chosen families shared knowledge about various forms of capital: latent mentorship, bi- or multi-directional mentorship, and transgressive mentorship. We call these three types of knowledge sharing “mentorship in the margins,” in which knowledge is shared within and among communities whose intersecting positionalities both limit and expand ways to imagine mentorship for navigating structural barriers and social, economic, and political inequities, especially regarding shared housing, family formation, and marriage equality. Discussion The breadth and depth of multigenerational transfers of knowledge across the life course demonstrate the centrality of multigenerational chosen families for LGBTQ+ communities as they age, especially among multiply-minoritized communities (e.g., transgender women, BIPOC same-gender-loving communities). Knowledge shared among chosen families also reflects how “mentorship in the margins” builds individual and collective power that helps LGBTQ+ communities survive and thrive as they age.

Background Recently, microRNAs (miRNAs) have attracted significant interest as predictive biomarkers for various types of dementia, including Alzheimer's disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), normal pressure hydrocephalus (NPH), and mild cognitive impairment (MCI). Machine learning (ML) methods enable the integration of miRNAs into highly accurate predictive models of dementia. Objective To investigate the differential expression of miRNAs across dementia subtypes compared to normal controls (NC) and analyze their enriched biological and disease pathways. Additionally, to evaluate the use of these miRNAs in binary and multiclass ML models for dementia prediction in both overall and sex-specific datasets. Methods Using data comprising 1685 Japanese individuals (GSE120584 and GSE167559), we performed differential expression analysis to identify miRNAs associated with five dementia groups in both overall and sex-specific datasets. Pathway enrichment analyses were conducted to further analyze these miRNAs. ML classifiers were used to create predictive models of dementia. Results We identified novel differentially expressed miRNA biomarkers distinguishing NC from five dementia subtypes. Incorporating these miRNAs into ML classifiers resulted in up to a 27% improvement in dementia risk prediction. Pathway analysis highlighted neuronal and eye disease pathways associated with dementia risk. Sex-specific analyses revealed unique biomarkers for males and females, with miR-128-1-5 as a protective factor for males in AD, VaD, and DLB, and miR-4488 as a risk factor for female AD, highlighting distinct pathways and potential therapeutic targets for each sex. Conclusions Our findings support existing dementia etiology research and introduce new potential and sex-specific miRNA biomarkers.

Ferns have been considered ecological indicators of soil nutrient composition and can be adapted to limestone (calcicole), volcanic substrates (calcifuge), or both (generalists). However, how many species exhibit substrate preferences and how these substrates affect their leaf nutrient composition remains unclear. We studied the occurrence of fern species across 37 sites in Veracruz and Puebla, Mexico, identifying their possible soil preferences (limestone vs volcanic), and performing an elemental analysis (C, N, P, K, Na, Ca, Mg, S, Fe, Al, and Mn) of leaf tissues and underlying substrates. We found 13 species confined to limestone, five to volcanic substrates, and one generalist species on both substrates. Limestone substrates had higher Ca but lower Fe, Mn, and P concentrations than igneous substrates, and calcicole ferns had higher Ca, Mg, and N concentrations than calcifuge ferns, each independent from elevation. A further ordination based on nutrient composition split calcicole ferns into two groups. Group I had lower nutrient concentrations except for higher Al, Fe, and Mn concentrations, and group II showed the opposite nutrient pattern. Additionally, group I consisted of species growing mainly at higher elevations than group II. The soil generalist had higher Ca and Al concentrations on limestone than on volcanic substrates. Fern species differed considerably in nutrient composition even within calcicole and calcifuge groups and most leaf nutrients decreased with elevation. Calcium concentrations, however, were consistently higher in calcicole than in calcifuge ferns regardless of elevation and may serve as a nutrient indicator for limestone specialists.

In this paper, we discuss the development of a basic coalition bargaining simulation based on the post-election negotations in the German Bundestag. After several iterations and sharing the coalition with others, two of the original developers found their intended learning outcomes diverging (one using it primarily to teach bargaining and party fragmentation theoretically, the other to teach the German case more specifically and deeply) and found their approaches to breifing and debriefing students diverging as well. We then compare the two approaches taken to the SoTL literature on simulation, developing hypotheses about how different forms of debriefing and game design might suggest different briefing/debriefing plans while maintaining the same basic simulation. We then present a research design (and seek panel feedback) on how to test these hypotheses across different insitutions in the 2025/2026 academic year with more formalized lesson plans on briefing and debriefing.

The macroeconomic impact of changing central bank leadership is examined. We empirically show that frequent changes in central bank leadership are associated with more volatile inflation rates. To provide a structural explanation, we develop a new technique for estimating a nonlinear New Keynesian model where the central bank varies its response to inflation. For a mix of developed and developing countries, we find that the stance of monetary policy often changes across governor tenures; these changes explain between 10% and 23% of the variation in inflation.

Refractory black carbon (rBC) is a primary aerosol species, produced through incomplete combustion, that absorbs sunlight and contributes to positive radiative forcing. The overall climate effect of rBC depends on its spatial distribution and atmospheric lifetime, both of which are impacted by the efficiency with which rBC is transported or removed by convective systems. These processes are poorly constrained by observations. It is especially interesting to investigate rBC transport efficiency through the Asian Summer Monsoon (ASM) since this meteorological pattern delivers vast quantities of boundary layer air from Asia, where rBC emissions are high to the upper troposphere/lower stratosphere (UT/LS) where the lifetime of rBC is expected to be long. Here, we present in situ observations of rBC made during the Asian Summer Monsoon Chemistry and Climate Impact Project of summer, 2022. We use observed relationships between rBC and CO in ASM outflow to show that rBC is removed nearly completely (>98%) from uplifted air and that rBC concentrations in ASM outflow are statistically indistinguishable from the UT/LS background. We compare observed rBC and CO concentrations to those expected based on two chemical transport models and find that the models reproduce CO to within a factor of 2 at all altitudes whereas rBC is overpredicted by a factor of 20–100 at altitudes associated with ASM outflow. We find that the rBC particles in recently convected air have thinner coatings than those found in the UTLS background, suggesting transport of a small number of rBC particles that are negligible for concentration.

Cellular adaptation to external signals is essential for biological functions, and it is an important field of interest in systems biology. This study examines the impact of cooperativity on the adaptation response of the Incoherent Feedforward Loop (IFFL) network motif to various signal profiles. Through comprehensive simulations, we studied how the IFFL motif responds to constant and pulse-type signals under varying levels of cooperativity. The results of our study demonstrate that positive cooperativity generally enhances the system’s ability to adapt to different signal profiles. Nevertheless, given specific signal profiles, higher levels of cooperativity may decrease the system’s adaptability. On the other hand, the adaptive response breaks down for negative cooperativity. For constant signals, increased positive cooperativity leads to a response with higher amplitude, and it accelerates the response time but delays the return time required to settle back down to the pre-stimulus state. Upon signal cessation, high positive cooperativity not only slows the system’s response and return times but, in some cases, can lead to a complete temporary halt in response. For the pulse-like signal, cooperativity increases the maximum amplitude of the oscillatory response. These insights highlight the delicate balance between cooperativity and signal profile in cellular adaptation mechanisms involving the IFFL network motif.

Arctic ecosystems are experiencing extreme climatic, biotic and physical disturbance events that can cause substantial loss of plant biomass and productivity, sometimes at scales of >1000 km². Collectively known as browning events, these are key contributors to the spatial and temporal complexity of Arctic greening and vegetation dynamics. If we are to properly understand the future of Arctic terrestrial ecosystems, their productivity, and their feedbacks to climate, understanding browning events is essential. Here we bring together understanding of browning events in Arctic ecosystems to compare their impacts and rates of recovery, and likely future changes in frequency and distribution. We also seek commonalities in impacts across these contrasting event types. We find that while browning events can cause high levels of plant damage (up to 100% mortality), ecosystems have substantial capacity for recovery, with biomass largely re-established within five years for many events. We also find that despite the substantial loss of leaf area of dominant species, compensatory mechanisms such as increased productivity of undamaged subordinate species lessen the impacts on carbon sequestration. These commonalities hold true for most climatic and biotic events, but less so for physical events such as fire and abrupt permafrost thaw, due to the greater removal of vegetation. Counterintuitively, some events also provide conditions for greater productivity (greening) in the longer-term, particularly where the disturbance exposes ground for plant colonisation. Finally, we find that projected changes in the causes of browning events currently suggest many types of events will become more frequent, with events of tundra fire and abrupt permafrost thaw expected to be the greatest contributors to future browning due to their severe impacts and occurrence in many Arctic regions. Overall, browning events will have increasingly important consequences for ecosystem structure and function, and for feedback to climate.

Recent efforts to disseminate a coordinated, international standard for urban carbon accounting reflect new interests to reframe urban environments as central to global climate goals. Advocates emphasize how local policy based on standardized accounting methods will be more effective and that global knowledge over climate progress will be enhanced. As part of a decentralized international regime, more standardized measurement tools to quantify the effects of local action are seen as central to building the legitimacy of local climate action. However, others express concerns that accountability to global metrics undermines the democratic nature of local action and that the resources required to compile more complex and comprehensive carbon inventories exceed the benefits. This article examines these debates through a spatial analysis of a new urban carbon accounting standard, the Global Protocol for Community-Scale Greenhouse Gas Initiatives (GPC). Two key spatial dimensions are interrogated: the work of the GPC in locating carbon in territorially defined space, and the effects of a common standard in making carbon mobile across geographies and deterritorializing the urban environment as part of an evolving global climate regime. I argue that examining the GPC through a spatial lens makes legible how new dynamics of power and authority are being expressed over urban environments. Following an analysis on the GPC's territorial accounting method, I turn to explore the importance of new scalar relations in elevating the role of urban environments in global politics. Particular attention is given to the popular urban measurement and reporting discourses shared by international urban policy networks that have helped coordinate new global compliance expectations for local governments. The article concludes by discussing important implications to understanding the effects of a standardized measurement framework and considerations for future research.