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Sorghum is an attractive feedstock for biobased fuel and chemical production because it is familiar to farmers, naturally drought tolerant, and versatile as a food, feed, and fuel crop. Although sorghum is a promising feedstock, particularly in regions that experience drought stress, little is known about how drought conditions impact the ease of conversion of sorghum to fuels and products. This study combines agronomic field trials with a high-throughput experimental pipeline to explore the field performance and liquid biofuel (bisabolene) yields resulting from three sorghum types (photosensitive forage sorghum, optimized grain sorghum, and drought-resistant grain sorghum) grown under pre- and postflowering water limitations in two different California locations. Multiple drought treatments are compared to the control, as the timing (preflowering versus postflowering) of drought stress elicits different survival strategies and corresponding impacts on yield and composition. Forage-type sorghum maintained the highest biomass yields across all irrigation conditions and locations. Glucose and xylose yields resulting from ionic liquid pretreatment and enzymatic saccharification were not significantly impacted by irrigation treatments but differed by location and genotype. However, Rhodosporidium toruloides grown on the resulting plant hydrolysates unexpectedly produced higher titers of bisabolene for drought-stressed sorghum samples regardless of genotype.

Polychlorinated biphenyls (PCBs) and their metabolites are linked to developmental neurotoxicity, but their levels in the gestational and lactational environment remain unexplored. This study investigated the effects of dietary exposure to the Fox River Mixture (FRM) on serum levels of PCBs and their metabolites in female C57BL/6 J mice. Mice were exposed to 0.1, 1.0, or 6.0 mg/kg body weight/day of FRM beginning two weeks before mating and throughout gestation and lactation. Serum samples collected from the dams at weaning were analyzed using gas chromatograph-tandem mass spectrometry and nontarget liquid chromatography-high resolution mass spectrometry. Results showed complex and dose-dependent differences in PCB and metabolite profiles. Untargeted metabolomics revealed alterations in metabolites involved in glucuronidation. Network analysis suggested disturbances in heme and amino acid metabolism associated with higher chlorinated PCBs. These findings suggested that PCBs and metabolites present in the gestational and lactation environment of mice may contribute to developmental neurotoxicity in rodents.

Climate change is dramatically altering the environmental context in which marine resources are harvested and managed. A growing field of academic literature has begun to explore the adaptive capacity of fishers and managers to respond to this change, but much of this field is abstract and theory-driven. Therefore, it is unclear whether this literature accurately reflects the adaptation priorities of fishery management practitioners, or whether there are gaps in the literature that these practitioners could fill with on-the-ground knowledge. Second, even if these principles of adaptive capacity are perfectly aligned with management practitioners’ priorities, it is unclear to what extent these principles are actively considered in the decision making process, and if not, why. This study seeks to address these questions by confronting fisheries professionals with academic ideas around adaptive capacity through a series of semi-structured interviews with federal fishery managers and scientists whose work informs decision making in the United States regional fishery management system. The study then uses these interviews to identify three low-cost, high-impact action items that could make concepts from the academic literature more accessible and useful to these practitioners and expand the literature by incorporating practitioners’ expertise. These action items are: 1) distinguish adaptive capacity from adaptive management, 2) use practitioner insights to contextualize the elements of adaptive capacity within the constraints and opportunities of governance systems, and 3) expand academic research to explicitly consider the capacity to adapt on appropriate timelines given the scale and pace of systemic change.

Results of previous research on chemigated imazamox for control of branched broomrape (Phelipanche ramosa) in processing tomatoes suggested potential soil-type differences in imazamox availability. Over two years, there were differences in crop-injury between two sites less than 30-km apart: imazamox-treated tomatoes in the Davis location had relatively minor early season injury while tomatoes at the Woodland location were severely injured or killed. The following study was conducted to investigate imazamox sorption in four California soils to determine if differences in herbicide adsorption played a role in variable crop-injury observed in the field trials. To determine the sorption capacity of imazamox of each soil, a batch-equilibrium study was conducted. There were significant differences in sorbed imazamox: the clay soil had the highest adsorption (Robert's Island: 742.5 pg µL-1 sorbed), followed by the sandy loam soil (Ripon: 723.9 pg µL-1 sorbed), while the loam soils from both trial sites (Davis: 704.2 pg µL-1 sorbed; Woodland: 699.9 pg µL-1 sorbed) had the lowest adsorption and were not significantly different from one another. Results from this study illustrate only minor differences in imazamox adsorption among the soils tested which suggests that soil type was likely not a major factor contributing to differences in crop-injury.

Palladium-encapsulated covalent organic frameworks (Pd/COFs) have garnered enormous attention in heterogeneous catalysis. However, the dominant ex situ encapsulation synthesis is tedious (multistep), time-consuming (typically 4 days or more), and involves the use of noxious solvents. Here we develop a mechanochemical in situ encapsulation strategy that enables the one-step, time-efficient, and environmentally benign synthesis of Pd/COFs. By ball milling COF precursors along with palladium acetate (Pd(OAc)2) in one pot under air at room temperature, Pd/COF hybrids were readily synthesized within an hour, exhibiting high crystallinity, uniform Pd dispersion, and superb scalability up to gram scale. Moreover, this versatile strategy can be extended to the synthesis of three Pd/COFs. Remarkably, the resulting Pd/DMTP-TPB showcases extraordinary activity (96-99% yield in 1 h at room temperature) and broad substrate scope (>10 functionalized biaryls) for the Suzuki-Miyaura coupling reaction of aryl bromides and arylboronic acids. Furthermore, the heterogeneity of Pd/DMTP-TPB is verified by recycling and leaching tests. The mechanochemical in situ encapsulation strategy disclosed herein paves a facile, rapid, scalable, and environmentally benign avenue to access metal/COF catalysts for efficient heterogeneous catalysis.

Radionuclide transport in smectite clay barrier systems used for nuclear waste disposal is controlled by diffusion, with adsorption significantly retarding transport rates. While a relatively minor component of spent nuclear fuel, 79Se is a major driver of the safety case for spent fuel disposal due to its long half-life (3.3 × 105 yr) and its low adsorption to clay (KD < 10 L/kg), thus a thorough understanding of Se diffusion through clay is critical for understanding the long-term safety of spent fuel disposal systems. Through-diffusion experiments with tritiated water (HTO, conservative tracer) and Se(VI) were conducted with a well-characterized, purified montmorillonite source clay (SWy-2) under a constant ionic strength (0.1 M) and three different electrolyte compositions: Na+, Ca2+, and a Na + -Ca2+ mixture at pH 6.5 in order to probe the effects of electrolyte composition and interlayer cation composition on clay microstructure, Se(VI) aqueous speciation, and ultimately diffusion. The results were modeled using a reactive transport modeling approach to determine values of porosity (ε), De (effective diffusion coefficient), and KD (distribution coefficient for adsorption). HTO diffusive flux was higher in Ca-montmorillonite (De = 1.68 × 10−10 m2 s−1) compared to Na-montmorillonite (De = 7.83 × 10−11 m2 s−1). This increase in flux is likely due to a greater degree of clay layer stacking in the presence of Ca2+ compared to Na+, which leads to larger inter-particle pores. Overall, the Se(VI) flux was much lower than the HTO flux due to anion exclusion, with Se(VI) flux following the order Ca (De = 1.03 × 10−11 m2 s−1) > Na–Ca (De = 2.12 × 10−12 m2 s−1) > Na (De = 1.28 × 10−12 m2 s−1). These differences in Se(VI) flux are due to a combination of factors, including (1) larger accessible porosity in Ca-montmorillonite due to clay layer stacking and smaller electrostatic effects compared to Na-montmorillonite, (2) larger accessible porosity for neutral-charge CaSeO4 species which makes up 32% of aqueous Se(VI) in the pure Ca system, and (3) possibly higher Se(VI) adsorption for Ca-montmorillonite. Through a combination of experimental and modeling work, this study highlights the compounding effects that electrolyte and counterion compositions can have on radionuclide transport through clay. Diffusion models that neglect these effects are not transferable from laboratory experimental conditions to in situ repository conditions.

Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM-FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold-induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

Tundra and boreal ecosystems encompass the northern circumpolar permafrost region and are experiencing rapid environmental change with important implications for the global carbon (C) budget. We analysed multi-decadal time series containing 302 annual estimates of carbon dioxide (CO2) flux across 70 permafrost and non-permafrost ecosystems, and 672 estimates of summer CO2 flux across 181 ecosystems. We find an increase in the annual CO2 sink across non-permafrost ecosystems but not permafrost ecosystems, despite similar increases in summer uptake. Thus, recent non-growing-season CO2 losses have substantially impacted the CO2 balance of permafrost ecosystems. Furthermore, analysis of interannual variability reveals warmer summers amplify the C cycle (increase productivity and respiration) at putatively nitrogen-limited sites and at sites less reliant on summer precipitation for water use. Our findings suggest that water and nutrient availability will be important predictors of the C-cycle response of these ecosystems to future warming.

Desk fans allow individual thermal adjustment in shared spaces which increases occupants' thermal satisfaction. When associated with the increase of room conditioning system setpoint temperature, they can also reduce energy use. In comparison to other Personal Comfort Systems (PCS), low-power desk fans can be very efficient for cooling. Nevertheless, previous studies identify some barriers to their implementation and show no clear guidelines on how to overcome them. Therefore, this study presents the results of a field implementation of desk fans in an open office in Brazil. The intervention consisted of providing one desk fan for each occupant and progressively increasing the setpoint temperature. Indoor thermal conditions were recorded simultaneously with occupants' thermal perception using sensors and surveys. Results show fans increased thermal satisfaction by 20 %. And, when fans were available, the preferred indoor air temperature increased by 1 °C. However, many constraints affect the results. Based on this experience, we propose guidelines for future implementation. We emphasize the need to understand the HVAC system, engage building operators, and apply gradual temperature modification. As occupants’ expectations had a great impact on the potential temperature extension, we suggest a way to limit temperature extension in future implementations.

Abstract: Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Extreme weather has a direct and significant impact on buildings and infrastructure, resulting in billions of dollars of damage each year. This problem continues to grow as climate patterns change and buildings are exposed to new and different hazards than what they were designed to withstand. In order to better plan for the long-range sustainment, restoration, modernization, and eventual recapitalization of these buildings, organizations with large building portfolios, such as the U.S. Department of Defense (DoD), must have an awareness of the risks that these extreme weather events present. This research aimed to develop an approach to estimate condition loss and reduction in service life for the components of a building due to extreme weather hazards, to understand the risks that may be present in certain buildings and building systems. To achieve this objective, a damage association matrix was developed that categorizes climate hazards, the damage modes that they produce, and the individual component types impacted. This damage matrix formally links state-of-the-art climate model output, which provides projections of the probability of various climate hazards with a damage effects model that quantifies the consequence on component-level condition and service life. This method is applied to an actual portfolio of buildings in a particular geographic location and with a pre-defined component inventory that comprises the building. This approach can be aggregated to the system-, facility-, and site-level thus helping support billions of dollars in recapitalization decisions related to restoration/modernization of facilities.

In response to increasingly severe weather conditions, optimization of building performance and investment provides an opportunity to consider co-benefits of thermal resilience during energy efficiency retrofits. This work aims to assess thermal resilience of buildings using building performance simulation to evaluate the indoor overheating risk under nine weather scenarios, considering historical (2010s), mid-term future (2050s), and long-term future (2090s) typical meteorological years, and heat wave years. Such an analysis is based on resilience profiles that combine six integrated indicators. A case study with a district of 92 buildings in Brazil was conducted, and a combination of strategies to improve thermal resilience was identified. Results reflect the necessity of planning for resilience in the context of climate change. This is because strategies recommended under current conditions might not be ideal in the future. Therefore, an adaptable design should be prioritized. Cooling energy consumption could increase by 48 % by the 2050s, while excessive overheating issues could reach 37 % of the buildings. Simple passive strategies can significantly reduce the heat stress. A comprehensive thermal resilience analysis should ultimately be accompanied by a thorough reflection on the stakeholders’ objectives, available resources, and planning horizon, as well as the risks assumed for not being resilient.

Anthropogenic heat (AH), i.e., waste heat from buildings to the ambient environment, increases urban air temperature and contributes to the urban heat island effect, which leads to more air-conditioning energy use and higher associated waste heat during summer, forming a positive feedback loop. This study used a bottom-up simulation approach to develop a dataset of the annual hourly AH profiles for 1.7 million buildings in Los Angeles (LA) County for the year 2018 aggregated at three spatial resolutions: 450 m, 12 km, and the census tract. Building AH exhibits strong seasonal and diurnal patterns, as well as large spatial variations across the urban areas. Building AH peaks in May and reaches a maximum of 878 W/m2 within one of several AH hotspots in the region. Among the three major AH components (surface convection, heat rejection from HVAC systems, and zonal air exchange), the surface convection component is the largest, accounting for 78% of the total building AH across LA County. Higher AH is attributed to large building density, a high percentage of industrial buildings, and older building stock. While AH peaks during the day, the resulting ambient temperature increases are much larger during the night. During the July 2018 heatwave in LA County, building AH (excluding the surface component) leads to a daily maximum ambient temperature increase of up to 0.6 °C and a daily minimum ambient temperature increase of up to 2.9 °C. It is recommended that reducing summer building AH should be considered by policy makers in developing mitigation measures for cities to transition to clean energy while improving heat resilience.

Climate change-induced shifts in snow storage and snowmelt patterns pose risks for adverse impacts to people, the environment, and irrigated agriculture. Existing research primarily focuses on evaluating these risks to irrigated agriculture at large scales, overlooking the role of local context in shaping risk dynamics. Consequently, many “at-risk” areas lack insight into how adaptation strategies for managing risk through water supply augmentation or water conservation vary across contexts and over time. To address this gap, we develop a comprehensive index for evaluating irrigated agriculture's risk and adaptation potential to changes in snow at local scales and apply it throughout the western US. Results confirm trends toward escalating risk for changes in snow storage and snowmelt patterns over the century. However, substantial heterogeneity in the extent and drivers of risk exists due to variability in localized interactions between declines in water supply (approximately −9% ± 13% by 2100) and increased agricultural demand (approximately 7% ± 5% by 2100). Despite an existing focus on supply augmentation as a critical adaptation strategy to reduce risk, we show its effectiveness diminishes for many areas over time, declining to an average of −54% of historical augmentation potential by 2100. Conserving water through historical changes in crop acreage and type emerges as a more stable adaptation measure, reducing demand by 7%–8% regardless of time. While particularly relevant for higher elevation, less intensive agricultural settings in snowmelt-dependent regions, findings underscore the need for strategies that support local-scale, context-appropriate adaptation to effectively manage escalating risk as snow changes.

Grasslands are one of the most common land-cover types, providing important ecosystem services globally, yet few studies have examined grassland critical-zone functioning throughout hillslopes. This study characterised a coastal grassland over a small hillslope at Point Reyes National Seashore, California, using multidisciplinary techniques, combining remotely-sensed, geophysical, plant, and soil measurements. Clustering techniques delineated the study area into four landscape zones, up-, mid-, and down-slope, and a bordering riparian ecotone, which had distinct environmental properties that varied spatially across the site, with depth, and time. Soil moisture increased with depth and down slope towards a bordering riparian zone, and co-varied with soil CO2 flux rates both spatially and temporally. This highlighted three distinct controls of soil moisture on soil respiration: CO2 fluxes were inhibited by high moisture content in the down-slope during the wet winter months, and converged across landscape positions in the dry summer months, while also displaying post-rain pulses. The normalised difference vegetation index (NDVI) ranged from 0.32 (September)–0.80 (April) and correlated positively with soil moisture and aboveground biomass, moving down slope. Yet, NDVI, aboveground biomass, and soil moisture were not correlated to soil organic carbon (SOC) content (0.4%–4.5%), which was highest in the mid-slope. The SOC content may instead be linked to shifts in dominant grassland species and their rhizosphere properties with landscape position. This multidisciplinary characterisation highlighted significant heterogeneity in grassland properties with landscape position, and demonstrated an approach that could be used to characterise other critical-zone environments on hillslopes.

Tropical Cyclones (TCs) inflict substantial coastal damages, making it pertinent to understand changing storm characteristics in the important nearshore region. Past work examined several aspects of TCs relevant for impacts in coastal regions. However, few studies explored nearshore storm intensification and its response to climate change at the global scale. Here, we address this using a suite of observations and numerical model simulations. Over the historical period 1979–2020, observations reveal a global mean TC intensification rate increase of about 3 kt per 24-hr in regions close to the coast. Analysis of the observed large-scale environment shows that stronger decreases in vertical wind shear and larger increases in relative humidity relative to the open oceans are responsible. Further, high-resolution climate model simulations suggest that nearshore TC intensification will continue to rise under global warming. Idealized numerical experiments with an intermediate complexity model reveal that decreasing shear near coastlines, driven by amplified warming in the upper troposphere and changes in heating patterns, is the major pathway for these projected increases in nearshore TC intensification.

The compound impacts of heatwaves and power outages pose a serious indoor heat-related health risk for residents living in disadvantaged communities (DACs) with limited or no air conditioning. In this study we selected 13 heat vulnerable multifamily buildings in El Monte, in Los Angeles County, and employed CityBES to evaluate their energy and thermal resilience performance. A retrofit package with seven passive and low-power active measures—cool roof, cool wall, window solar film, air sealing, internal blinds, natural ventilation, and ceiling fan—was evaluated under 2018 weather conditions and projected 2058 future weather conditions. Results show: (1) under the 2018 weather conditions, the retrofit package reduces the peak electricity load by 19 % and reduces the annual energy cost by $183 per housing unit; (2) the housing units without air conditioning would face heat danger conditions throughout the heatwave period. Although the retrofit package could reduce the heat danger hours by 50 % in 2018 and 34 % in 2058, air conditioning is a life-essential need for residents during heatwaves. These results indicate that, during the decision making of energy and climate retrofits for housing in DACs, policymakers and building owners should consider the co-benefits of reducing indoor heat-related mortality while reducing energy cost.

The presence of toxic metals in tobacco smoke is well documented. However, few studies have quantified trace metals in secondhand smoke (SHS) and thirdhand smoke (THS). Their presence in indoor air can contribute to nonsmokers’ exposures and health effects. In this study, emission and deposition rates of toxic trace metals were determined, and their airborne concentration in typical indoor scenarios was predicted. PM2.5 was collected on Teflon-coated filters at various times following a smoking event in a room-sized chamber over a 43 h period. The concentration of 28 trace metals was determined by extraction and analysis using inductively coupled plasma-triple quadrupole-mass spectrometry (ICP-QQQ-MS). Emission and indoor deposition rates of cadmium, arsenic, chromium, manganese, beryllium and selenium were determined, and used to predict concentrations expected in a smokers’ home and a smoking bar. In most of the considered scenarios, average indoor concentrations of Cd, As, and Cr exceeded their corresponding cancer risk thresholds and, in some cases, also noncancer reference exposure levels, more than 3 h after smoking ended. The fraction of cadmium that remained airborne was significantly higher than those of other metal traces and that of PM2.5, suggesting an association of Cd traces with small particles.

Substantially reducing methane emissions is the fastest way to repress near-term warming and is an essential prerequisite for reaching the 1.5 °C target. However, knowledge about the global invention trend, sectoral and national distribution and international diffusion of methane-targeted abatement technologies (MTATs) remains limited. On the basis of patent data, we identify more than 175,000 MTAT inventions applied between 1990 and 2019 by 133 countries or dependent territories. Our results revealed that after sustained growth of more than fourfold, the number of global high-quality MTAT inventions declined by 3.5% annually from 2010 to 2019. The sectoral and national-level distributions of MTAT inventions and methane emissions are strongly mismatched. Additionally, the international diffusion of MTATs is 11.1% lower than that of overall climate change mitigation technologies and most transfers occur between developed countries or flow to China, South Korea and Brazil; however, other developing countries and the least developed countries are rarely involved.

Wetland methane (CH4) emissions over the Boreal-Arctic region are vulnerable to climate change and linked to climate feedbacks, yet understanding of their long-term dynamics remains uncertain. Here, we upscaled and analysed two decades (2002-2021) of Boreal-Arctic wetland CH4 emissions, representing an unprecedented compilation of eddy covariance and chamber observations. We found a robust increasing trend of CH4 emissions (+8.9%) with strong inter-annual variability. The majority of emission increases occurred in early summer (June and July) and were mainly driven by warming (52.3%) and ecosystem productivity (40.7%). Moreover, a 2 °C temperature anomaly in 2016 led to the highest recorded annual CH4 emissions (22.3 Tg CH4 yr-1) over this region, driven primarily by high emissions over Western Siberian lowlands. However, current-generation models from the Global Carbon Project failed to capture the emission magnitude and trend, and may bias the estimates in future wetland CH4 emission driven by amplified Boreal-Arctic warming and greening.

Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.

Background: Rifampicin (RIF) is a key first-line drug used to treat tuberculosis, a primarily pulmonary disease caused by Mycobacterium tuberculosis. RIF resistance is caused by mutations in rpoB, at the cost of slower growth and reduced transcription efficiency. Antibiotic resistance to RIF is prevalent despite this fitness cost. Compensatory mutations in rpoABC genes have been shown to alleviate the fitness cost of rpoB:S450L, explaining how RIF resistant strains harbor this mutation can spread so rapidly. Unfortunately, the full set of RIF compensatory mutations is still unknown, particularly those compensating for rarer RIF resistance mutations. Objectives: We performed an association study on a globally representative set of 4,309 whole genome sequenced clinical M. tuberculosis isolates to identify novel putative compensatory mutations, determine the prevalence of known and previously reported putative compensatory mutations, and determine which RIF resistance markers associate with these compensatory mutations. Results and conclusions: Of the 1,079 RIF resistant isolates, 638 carried previously reported putative and high-probability compensatory mutations. Our strict criteria identified 46 additional mutations in rpoABC for which no strong prior evidence of their compensatory role exists. Of these, 35 have previously been reported. As such, our independent corroboration adds to the mounting evidence that these 35 also carry a compensatory role. The remaining 11 are novel putative compensatory markers, reported here for the first time. Six of these 11 novel putative compensatory mutations had two or more mutation events. Most compensatory mutations appear to be specifically compensating for the fitness loss due to rpoB:S450L. However, an outbreak of 22 closely related isolates each carried three rpoB mutations, the rare RIFR markers D435G and L452P and the putative compensatory mutation I1106T. This suggests compensation may require specific combinations of rpoABC mutations. Here, we report only mutations that met our very strict criteria. It is highly likely that many additional rpoABC mutations compensate for rare resistance-causing mutations and therefore did not carry the statistical power to be reported here. These findings aid in the identification of RIF resistant M. tuberculosis strains with restored fitness, which pose a greater risk of causing resistant outbreaks.

Open science is a global movement happening across all research fields. Enabled by technology and the open web, it builds on years of efforts by individuals, grassroots organizations, institutions, and agencies. The goal is to share knowledge and broaden participation in science, from early ideation to making research outputs openly accessible to all (open access). With an emphasis on transparency and collaboration, the open science movement dovetails with efforts to increase diversity, equity, inclusion, and belonging in science and society. The US Biden-Harris Administration and many other US government agencies have declared 2023 the Year of Open Science, providing a great opportunity to boost participation in open science for the oceans. For researchers day-to-day, open science is a critical piece of modern analytical workflows with increasing amounts of data. Therefore, we focus this article on open data science-the tooling and people enabling reproducible, transparent, inclusive practices for data-intensive research-and its intersection with the marine sciences. We discuss the state of various dimensions of open science and argue that technical advancements have outpaced our field's culture change to incorporate them. Increasing inclusivity and technical skill building are interlinked and must be prioritized within the marine science community to find collaborative solutions for responding to climate change and other threats to marine biodiversity and society.

Food-producing animals such as dairy cattle are potential reservoirs of antimicrobial resistance (AMR), with multidrug-resistant (MDR) organisms such as Escherichia coli observed in higher frequency in young calves compared to older cattle. In this study, we characterized the genomes of enteric MDR E. coli from pre-weaned dairy calves with and without diarrhea and evaluated the influence of host-level factors on genomic composition. Whole genome sequence comparative analysis of E. coli (n = 43) revealed substantial genomic diversity that primarily clustered by sequence type and was minimally driven by calf diarrheal disease status (healthy, diarrheic, or recovered), antimicrobial exposure, and dietary zinc supplementation. Diverse AMR genes (ARGs)-including extended-spectrum beta-lactamase genes and quinolone resistance determinants-were identified (n = 40), with unique sets of ARGs co-occurring in gene clusters with large AMR plasmids IncA/C2 and IncFIB(AP001918). Zinc supplementation was not significantly associated with the selection of individual ARGs in E. coli, however analysis of ARG and metal resistance gene pairs identified positive associations between certain aminoglycoside, beta-lactam, sulfonamide, and trimethoprim ARGs with acid, tellurium and mercury resistance genes. Although E. coli in this study lacked the typical virulence factors of diarrheagenic strains, virulence genes overlapping with those in major pathotypes were identified. Among the 103 virulence genes detected, the highest abundance and diversity of genes corresponded to iron acquisition (siderophores and heme uptake). Our findings indicate that the host-level factors evaluated in this study were not key drivers of genomic variability, but that certain accessory genes in enteric MDR E. coli may be enriched. Collectively, this work provides insight into the genomic diversity and host-microbe interface of MDR E. coli from pre-weaned dairy calves.

Background NOAA’s Hazard Mapping System (HMS) smoke product comprises smoke plumes digitised from satellite imagery. Recent studies have used HMS as a proxy for surface smoke presence. Aims We compare HMS with airport observations, air quality station measurements and model estimates of near-surface smoke. Methods We quantify the agreement in numbers of smoke days and trends, regional discrepancies in levels of near-surface smoke fine particulate matter (PM2.5) within HMS polygons, and separation of total PM2.5 on smoke and non-smoke days across the contiguous US and Alaska from 2010 to 2021. Key results We find large overestimates in HMS-derived smoke days and trends if we include light smoke plumes in the HMS smoke day definition. Outside the western US and Alaska, near-surface smoke PM2.5 within areas of HMS smoke plumes is low and almost indistinguishable across density categories, likely indicating frequent smoke aloft. Conclusions Compared with airport, Environmental Protection Agency (EPA) and model-derived estimates, HMS most closely reflects surface smoke in the Pacific and Mountain regions and Alaska when smoke days are defined using only heavy plumes or both medium and heavy plumes. Implications We recommend careful consideration of biases in the HMS smoke product for air quality and public health assessments of fires.

This theme issue investigates how 21st-century digital innovations are changing the nature and value of land, housing, and property. Contributors bring together an array of cases to understand how digitization is remaking land and housing on a global scale and, in turn, how existing property relations structure digital transformations in particular geographies. In this introduction to the theme issue, we outline how hype can be used as an analytical entry point to characterize the collection’s contribution, demonstrating how hype elides unequal relations of land and labor while stoking speculation in immovable property, even as it creates new markets for less tangible assets—whether rental data or virtual plots—that usher in new global connections and familiar market dynamics.

Abstract: Accurate, inexpensive and granular human poverty assessments are critical for data-driven policy decision-making. This research proposes a novel approach to computing poverty scores utilizing multispectral satellite images and indices calculated from census reference values. We show how this approach can leverage standard and sparse survey-based multidimensional poverty assessments at the municipal level to develop a deep learning architecture to obtain poverty scores at the residential block level. This method has the distinctive feature that the obtained inference corresponds to Multidimensional Measurement of Poverty generated by CONEVAL, the Mexican agency responsible for measuring poverty. We provide a reliable alternative to survey-based approaches with an $$R^2$$ R 2 of $$0.802\pm 0.022$$ 0.802 ± 0.022 for the lack of housing quality and spaces dimension. A convolutional neural network trained on multispectral satellite images and the lack of housing quality and spaces dimension, which is regressed from census reference variables corresponding to lack of water, electricity, sewage, concrete floor, toilet and occupancy level obtains an $$R^2$$ R 2 of 0.753. These results represent a significant step forward in including machine learning techniques to provide reliable information at reduced costs and a higher spatiotemporal frequency than traditional person-to-person surveys.

IntroductionMetabolic dysfunction-associated steatotic liver disease (MASLD) affects nearly 25% of the population and is the leading cause for liver-related mortality. Bariatric surgery is a well-known treatment for MASLD and obesity. Understanding the fundamental mechanisms by which bariatric surgery can alter MASLD can lead to new avenues of therapy and research. Previous studies have identified the microbiome's role in bariatric surgery and in inflammatory immune cell populations. The host innate immune system modulates hepatic inflammation and fibrosis, and thus the progression of MASLD. The precise role of immune cell types in the pathogenesis of MASLD remains an active area of investigation. The aim of this study was to understand the interplay between microbiota composition post-bariatric surgery and the immune system in MASLD.MethodsEighteen morbidly obese females undergoing sleeve gastrectomy were followed pre-and post-surgery. Stool from four patients, showing resolved MASLD post-surgery with sustained weight loss, was transplanted into antibiotic treated mice. Mice received pre-or post-surgery stool and were fed a standard or high-fat diet. Bodyweight, food intake, and physiological parameters were tracked weekly. Metabolic parameters were measured post-study termination.ResultsThe human study revealed that bariatric surgery led to significant weight loss (p > 0.05), decreased inflammatory markers, and improved glucose levels six months post-surgery. Patients with weight loss of 20% or more showed distinct changes in blood metabolites and gut microbiome composition, notably an increase in Bacteroides. The mouse model confirmed surgery-induced microbiome changes to be a major factor in the reduction of markers and attenuation of MASLD progression. Mice receiving post-surgery fecal transplants had significantly less weight gain and liver steatosis compared to pre-surgery recipients. There was also a significant decrease in inflammatory cytokines interferon gamma, interleukin 2, interleukin 15, and mig. This was accompanied by alterations in liver immunophenotype, including an increase in natural killer T cells and reduction of Kupfer cells in the post-surgery transplant group.DiscussionOur findings suggest surgery induced microbial changes significantly reduce inflammatory markers and fatty liver progression. The results indicate a potential causal link between the microbiome and the host immune system, possibly mediated through modulation of liver NKT and Kupffer cells.

Phytophthora cinnamomi is a hemibiotrophic oomycete causing Phytophthora root rot in over 5,000 plant species, threatening natural ecosystems, forestry, and agriculture. Genomic studies of P. cinnamomi are limited compared to other Phytophthora spp. despite the importance of this destructive and highly invasive pathogen. The genome of two genetically and phenotypically distinct P. cinnamomi isolates collected from avocado orchards in California were sequenced using PacBio and Illumina sequencing. Genome sizes were estimated by flow cytometry and assembled de novo to 140-141 Mb genomes with 21,111-21,402 gene models. Genome analyses revealed that both isolates exhibited complex heterozygous genomes fitting the two-speed genome model. The more virulent isolate encodes a larger secretome and more RXLR effectors when compared to the less virulent isolate. Transcriptome analysis after P. cinnamomi infection in Arabidopsis thaliana, Nicotiana benthamiana, and Persea americana de Mill (avocado) showed that this pathogen deploys common gene repertoires in all hosts and host-specific subsets, especially among effectors. Overall, our results suggested that clonal P. cinnamomi isolates employ similar strategies as other Phytophthora spp. to increase phenotypic diversity (e.g., polyploidization, gene duplications, and a bipartite genome architecture) to cope with environmental changes. Our study also provides insights into common and host-specific P. cinnamomi infection strategies and may serve as a method for narrowing and selecting key candidate effectors for functional studies to determine their contributions to plant resistance or susceptibility.

Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow.

The complexity of information processing in the brain requires the development of technologies that can provide spatial and temporal resolution by means of dense electrode arrays paired with high-channel-count signal acquisition electronics. In this work, we present an ultra-low noise modular 512-channel neural recording circuit that is scalable to up to 4096 simultaneously recording channels. The neural readout application-specific integrated circuit (ASIC) uses a dense 8.2 mm × 6.8 mm 2D layout to enable high-channel count, creating an ultra-light 350 mg flexible module. The module can be deployed on headstages for small animals like rodents and songbirds, and it can be integrated with a variety of electrode arrays. The chip was fabricated in a TSMC 0.18 µm 1.8 V CMOS technology and dissipates a total of 125 mW. Each DC-coupled channel features a gain and bandwidth programmable analog front-end along with 14 b analog-to-digital conversion at speeds up to 30 kS/s. Additionally, each front-end includes programmable electrode plating and electrode impedance measurement capability. We present both standalone and in vivo measurements results, demonstrating the readout of spikes and field potentials that are modulated by a sensory input.

Abstract: Higher educational institutions tend to draw from mainstream approaches to environmentalism that reinforce race, class, and gender hierarchies around who constitutes “an environmentalist” and what activities constitute “environmentalism.” As a result, students of color and students from other marginalized backgrounds who often experience environmental degradation and catastrophe firsthand do not often see their experiences reflected in universities’ environmental programming, curricula, or research. Furthermore, faculty and staff who center issues of race, equity, power, and justice when addressing environmental topics tend to work in isolation from one another and their efforts are not well-coordinated. In this paper, we draw from the concept of “epistemic exclusion” (Settles et al. J Divers High Educ 14:493, 2021; J High Educ 93:31–55, 2022) to explain hidden biases that systematically devalue scholarship that does not fit mainstream parameters. We describe a research project focused on building more equity-centered environmental efforts at the University of California, Santa Cruz. We find that faculty and staff across divisions want to engage in more epistemically inclusive and equity-centered environmental work, but lack the institutional support and resources (e.g., knowledge, funding, time, incentives) to do so. Interestingly, only a few responses focused on the barriers and biases related to epistemic exclusion. Our findings suggest that more awareness is needed to identify, analyze, and challenge these less visible barriers to substantively work towards greater inclusivity in environmentalism.

The rhizosphere microbiome plays a crucial role in supporting plant productivity and ecosystem functioning by regulating nutrient cycling, soil integrity, and carbon storage. However, deciphering the intricate interplay between microbial relationships within the rhizosphere is challenging due to the overwhelming taxonomic and functional diversity. Here we present our systematic design framework built on microbial colocalization and microbial interaction, toward successful assembly of multiple rhizosphere-derived Reduced Complexity Consortia (RCC). We enriched co-localized microbes from Brachypodium roots grown in field soil with carbon substrates mimicking Brachypodium root exudates, generating 768 enrichments. By transferring the enrichments every 3 or 7 days for 10 generations, we developed both fast and slow-growing reduced complexity microbial communities. Most carbon substrates led to highly stable RCC just after a few transfers. 16S rRNA gene amplicon analysis revealed distinct community compositions based on inoculum and carbon source, with complex carbon enriching slow growing yet functionally important soil taxa like Acidobacteria and Verrucomicrobia. Network analysis showed that microbial consortia, whether differentiated by growth rate (fast vs. slow) or by succession (across generations), had significantly different network centralities. Besides, the keystone taxa identified within these networks belong to genera with plant growth-promoting traits, underscoring their critical function in shaping rhizospheric microbiome networks. Furthermore, tested consortia demonstrated high stability and reproducibility, assuring successful revival from glycerol stocks for long-term viability and use. Our study represents a significant step toward developing a framework for assembling rhizosphere consortia based on microbial colocalization and interaction, with future implications for sustainable agriculture and environmental management.

This paper examines the legacies of the emergence of the animal control and sheltering industry in the United States and their impact on contemporary public animal shelters. While decades of gradual reform have helped substantially reduce the number of animals entering shelters and being killed there, contemporary animal sheltering largely continues to follow the path set when animal sheltering developed in the late 1800s and early 1900s. Three key interrelated legacies of the pound model of early animal control and sheltering enduringly shape sheltering today: (1) the institutional culture of animal shelters grounded in the logics of caging and killing; (2) the lack of visibility and transparency, especially within government shelters; and (3) the economic logics of the pound model, including the disparities in sheltering resources across communities. Examining the origins of animal control and sheltering and identifying the specific legacies of this pound model within contemporary government-funded shelters improves understanding of why such shelters in the US have developed with a particular set of practices and ideologies, and thus provides an important footing for envisioning and enacting radical changes in animal sheltering.

This study assessed the energy-saving and climate-adaptive potential of cool skin and ventilated cavity skin facade technologies in Seoul's high-rise apartment buildings. We created weather scenarios for historical, mid-term future, and long-term future conditions using Coordinated Regional Downscaling EXperiment (CORDEX) method. Building energy simulations were conducted on a South Korean high-rise apartment model to evaluate their performance under different weather conditions. The results indicate that cool skin and ventilated cavity skin technologies can save cooling energy during summers but lead to heating energy penalties in winters. Ventilated cavity skin outperforms cool skin, offering better cooling energy savings and reduced heating penalties. Combining both technologies yields the highest overall energy savings, with 7 %, 9 %, and 10 % cooling energy savings for cool skin, ventilated cavity skin, and the combined package, respectively. However, cool skin increases heating energy consumption by 5 %, while ventilated cavity skin has minimal impact on heating energy. These envelope technologies also reduce peak electricity demand by at least 5 %, 8 %, and 9 %, respectively. They contribute to heat stress reduction, enhance resilience, and decrease extreme heat risks for occupants during power outages by at least 18 % under various weather conditions. Considering the prevalence of aging high-rise apartments in South Korea, adopting these envelope renovation strategies can effectively reduce cooling loads, enhance thermal comfort, and boost resilience under future climates, while avoiding costly reconstruction.

As social media is increasingly used by communities to understand and cope with environmental hazards, understanding how people use social media before, during, and after disasters can support disaster response and recovery efforts. This paper presents an empirical application of Houston et al.’s (Disasters 39:1–22, 2015) functional framework for disaster social media, using the case of Twitter use during and after Hurricane María. Our research aims to (1) identify the predominant patterns of Twitter usage and content dissemination during the Hurricane María crisis and (2) validate and refine the functional framework for disaster social media with a case study of the hurricane that hit Puerto Rico in 2017. We find that people in the US used Twitter mainly to access news of the hurricane, express emotions (both negative and positive), and to understand socio-political events shaping the response and recovery. Most tweets came from individuals rather than organizations, and most were sent as the hurricane was designated as category four and approached Puerto Rico, with far fewer posts after landfall. These findings highlight the importance of individuals sharing and accessing vital information when official outlets are absent or limited and the relatively short-lived attention to slow recovery processes.

The aerobic hyperthermophile "Fervidibacter sacchari" catabolizes diverse polysaccharides and is the only cultivated member of the class "Fervidibacteria" within the phylum Armatimonadota. It encodes 117 putative glycoside hydrolases (GHs), including two from GH family 50 (GH50). In this study, we expressed, purified, and functionally characterized one of these GH50 enzymes, Fsa16295Glu. We show that Fsa16295Glu is a β-1,3-endoglucanase with optimal activity on carboxymethyl curdlan (CM-curdlan) and only weak agarase activity, despite most GH50 enzymes being described as β-agarases. The purified enzyme has a wide temperature range of 4-95°C (optimal 80°C), making it the first characterized hyperthermophilic representative of GH50. The enzyme is also active at a broad pH range of at least 5.5-11 (optimal 6.5-10). Fsa16295Glu possesses a relatively high kcat/KM of 1.82 × 107 s-1 M-1 with CM-curdlan and degrades CM-curdlan nearly completely to sugar monomers, indicating preferential hydrolysis of glucans containing β-1,3 linkages. Finally, a phylogenetic analysis of Fsa16295Glu and all other GH50 enzymes revealed that Fsa16295Glu is distant from other characterized enzymes but phylogenetically related to enzymes from thermophilic archaea that were likely acquired horizontally from "Fervidibacteria." Given its functional and phylogenetic novelty, we propose that Fsa16295Glu represents a new enzyme subfamily, GH50_3.

This paper introduces an innovative approach to 3D environmental mapping through the integration of a compact, handheld sensor package with a two-stage sensor fusion pipeline. The sensor package, incorporating LiDAR, IMU, RGB, and thermal cameras, enables comprehensive and robust 3D mapping of various environments. By leveraging Simultaneous Localization and Mapping (SLAM) and thermal imaging, our solution offers good performance in conditions where global positioning is unavailable and in visually degraded environments. The sensor package runs a real-time LiDAR-Inertial SLAM algorithm, generating a dense point cloud map that accurately reconstructs the geometric features of the environment. Following the acquisition of that point cloud, we post-process these data by fusing them with images from the RGB and thermal cameras and produce a detailed, color-enriched 3D map that is useful and adaptable to different mission requirements. We demonstrated our system in a variety of scenarios, from indoor to outdoor conditions, and the results showcased the effectiveness and applicability of our sensor package and fusion pipeline. This system can be applied in a wide range of applications, ranging from autonomous navigation to smart agriculture, and has the potential to make a substantial benefit across diverse fields.

Estimating relative abundance is critical for informing conservation and management efforts and for making inferences about the effects of environmental change on populations. Freshwater fisheries span large geographic regions, occupy diverse habitats and consist of varying species assemblages. Monitoring schemes used to sample these diverse populations often result in populations being sampled at different times and under different environmental conditions. Varying sampling conditions can bias estimates of abundance when compared across time, location and species, and properly accounting for these biases is critical for making inferences. We develop a joint species distribution model (JSDM) that accounts for varying sampling conditions due to the environment and time of sampling when estimating relative abundance. The novelty of our JSDM is that we explicitly model sampling effort as the product of known quantities based on time and gear type and an unknown functional relationship to capture seasonal variation in species life history. We use the model to study relative abundance of six freshwater fish species across the state of Minnesota, USA. Our model enables estimates of relative abundance to be compared both within and across species and lakes, and captures the inconsistent sampling present in the data. We discuss how gear type, water temperature and day of the year impact catchability for each species at the lake level and throughout a year. We compare our estimates of relative abundance to those obtained from a model that assumes constant catchability to highlight important differences within and across lakes and species. Synthesis and applications: Our method illustrates that assumptions relating indices of abundance to observed catch data can greatly impact model inferences derived from JSDMs. Specifically, not accounting for varying sampling conditions can bias inference of relative abundance, restricting our ability to detect responses to management interventions and environmental change. While our focus is on freshwater fisheries, this model architecture can be adopted to other systems where catchability may vary as a function of space, time and species.

This study examines the intersection of archaeological data and community narratives in interpreting the Ifugao Rice Terraces in the Philippines, a UNESCO World Heritage Site. Long regarded as 2000-year-old symbols of an uncolonized cultural past, recent research challenges this view, suggesting a 16th-century origin coinciding with Spanish contact. The longstanding characterization of the Ifugao Rice Terraces as 2000-year-old monuments cemented a perception of Ifugao culture as static and unchanging, overshadowing the dynamic cultural practices that have persisted and evolved over the centuries. It is crucial to recognize that these terraces are not frozen in time but are active representations of Ifugao’s living culture, which has continually adapted to social, environmental, and historical changes while maintaining its distinct identity. This paradigm shift, supported by radiocarbon dating and ethnohistorical analysis, aligns more closely with local oral histories and portrays the Ifugao not as passive inheritors of tradition but as active participants in their history. We argue for the integration of scientific data with community stories, presenting a holistic understanding of the terraces as dynamic elements of Ifugao resilience and identity. The findings advocate a move away from romanticized historical interpretations toward a narrative that respects the complexity and adaptability of Indigenous cultural landscapes.

Clinicopathologic data in dogs with prostate cancer (PCa) may aid in the differentiation between tumor types and subsequent treatment decisions; however, these data are often unreported. Demographic, clinicopathologic, cytologic, histologic and survival data from dogs with primary prostatic adenocarcinoma (PRAD) (n = 56) and primary prostatic transitional cell carcinoma (P-TCC) (n = 74) were acquired from a tertiary veterinary teaching hospital from 1992 to 2022. Red blood cell distribution width (RDW) to albumin ratio (RAR) was evaluated for diagnostic utility in differentiating between PRAD and P-TCC. Sections from PRAD tumors (n = 50) were stained for androgen receptor (AR) expression, and laboratory data were compared between AR positive (AR+) and AR negative (AR-) groups. RDW was increased in PRAD, while albumin was decreased (p < 0.05). P-TCC was associated with Melamed-Wolinska bodies (MWB) and necrosis on cytology (p < 0.05). RAR had acceptable diagnostic utility in the differentiation of PCa tumors (AUC = 0.7; p < 0.05). Survival rates and metastases were equivocal. AR+ and AR- PRAD tumors did not differ in clinicopathologic data or survival (p > 0.05). In conclusion, hypoalbuminemia was significantly associated with PRAD and decreased survival, while MWB and necrosis were significantly associated with P-TCC on cytology. These clinicopathologic data may help clinicians differentiate between these tumors ante mortem to guide appropriate treatment and intervention.

BackgroundInteraction through movement can be used as a marker to understand and model interspecific and intraspecific species dynamics, and the collective behavior of animals sharing the same space. This research leverages the time-geography framework, commonly used in human movement research, to explore the dynamic patterns of interaction between Indochinese tigers (Panthera tigris corbeti) in the western forest complex (WEFCOM) in Thailand.MethodsWe propose and assess ORTEGA, a time-geographic interaction analysis method, to trace spatio-temporal interactions patterns and home range shifts among tigers. Using unique GPS tracking data of tigers in WEFCOM collected over multiple years, concurrent and delayed interaction patterns of tigers are investigated. The outcomes are compared for intraspecific tiger interaction across different genders, relationships, and life stages. Additionally, the performance of ORTEGA is compared to a commonly used proximity-based approach.ResultsAmong the 67 tracked tigers, 42 show concurrent interactions at shared boundaries. Further investigation of five tigers with overlapping home ranges (two adult females, a male, and two young male tigers) suggests that the mother tiger and her two young mostly stay together before their dispersal but interact less post-dispersal. The male tiger increases encounters with the mother tiger while her young shift their home ranges. On another timeline, the neighbor female tiger mostly avoids the mother tiger. Through these home range dynamics and interaction patterns, we identify four types of interaction among these tigers: following, encounter, latency, and avoidance. Compared to the proximity-based approach, ORTEGA demonstrates better detects concurrent mother-young interactions during pre-dispersal, while the proximity-based approach misses many interactions among the dyads. With larger spatial buffers and temporal windows, the proximity-based approach detects more encounters but may overestimate the duration of interaction.ConclusionsThis research demonstrates the applicability and merits of ORTEGA as a time-geographic based approach to animal movement interaction analysis. We show time geography can develop valuable, data-driven insights about animal behavior and interactions. ORTEGA effectively traces frequent encounters and temporally delayed interactions between animals, without relying on specific spatial and temporal buffers. Future research should integrate contextual and behavioral information to better identify and characterize the nature of species interaction.

Cyanobacteria in polar environments face environmental challenges, including cold temperatures and extreme light seasonality with small diurnal variation, which has implications for polar circadian clocks. However, polar cyanobacteria remain underrepresented in available genomic data, and there are limited opportunities to study their genetic adaptations to these challenges. This paper presents four new Antarctic cyanobacteria metagenome-assembled genomes (MAGs) from microbial mats in Lake Vanda in the McMurdo Dry Valleys in Antarctica. The four MAGs were classified as Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, Microcoleus sp. MP8IB2.171, and Leptolyngbyaceae cyanobacterium MP9P1.79. The MAGs contain 2.76 Mbp - 6.07 Mbp, and the bin completion ranges from 74.2-92.57%. Furthermore, the four cyanobacteria MAGs have average nucleotide identities (ANIs) under 90% with each other and under 77% with six existing polar cyanobacteria MAGs and genomes. This suggests that they are novel cyanobacteria and demonstrates that polar cyanobacteria genomes are underrepresented in reference databases and there is continued need for genome sequencing of polar cyanobacteria. Analyses of the four novel and six existing polar cyanobacteria MAGs and genomes demonstrate they have genes coding for various cold tolerance mechanisms and most standard circadian rhythm genes with the Leptolyngbya sp. BulkMat.35 and Leptolyngbyaceae cyanobacterium MP9P1.79 contained kaiB3, a divergent homolog of kaiB.