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The Ising model, initially proposed about 100 years ago to explain ferromagnetism and phase transitions, has become a central pillar of statistical physics and a powerful tool for diverse applications in other fields including environmental studies. In this paper, we introduce continuous spin values between −1 and +1 to a two-dimensional Ising model and utilize the generalized Ising lattice to simulate the dynamics of sea ice/water transition for a large area of 1500 km by 1500 km in the Arctic region. The simulation process follows the Metropolis-Hastings algorithm and incorporates an innovative factor to account for the inertia of spin value changes. Using the sea ice concentration data collected by the National Snow and Ice Data Center, our results exhibit striking similarity between the simulated and the observed ice melting and freezing dynamics, and two numerical measures from the simulation—the ice coverage percentage and the ice extent—match closely with the data statistics. Moreover, the model's best-fit parameters demonstrate the substantial impact of the external forces, which can be further enriched and linked to the environmental factors in other climate change research. [ABSTRACT FROM AUTHOR]

Reducing carbon dioxide (CO2) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO2 from various sources and deliver it to different sinks1,2. The quest for optimal solutions for specific source-sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design3 and engineers on optimizing processes4,5, which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant's lifetime, is typically one of the final steps6. Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.

Present and future climatic trends are expected to markedly alter water fluxes and stores in the hydrologic cycle. In addition, water demand continues to grow due to increased human use and a growing population. Sustainably managing water resources requires a thorough understanding of water storage and flow in natural, agricultural, and urban ecosystems. Measurements of stable isotopes of water (hydrogen and oxygen) in the water cycle (atmosphere, soils, plants, surface water, and groundwater) can provide information on the transport pathways, sourcing, dynamics, ages, and storage pools of water that is difficult to obtain with other techniques. However, the potential of these techniques for practical questions has not been fully exploited yet. Here, we outline the benefits and limitations of potential applications of stable isotope methods useful to water managers, farmers, and other stakeholders. We also describe several case studies demonstrating how stable isotopes of water can support water management decision-making. Finally, we propose a workflow that guides users through a sequence of decisions required to apply stable isotope methods to examples of water management issues. We call for ongoing dialogue and a stronger connection between water management stakeholders and water stable isotope practitioners to identify the most pressing issues and develop best-practice guidelines to apply these techniques.

Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species-environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold-adapted species was predicted to have high probabilities of extirpation across its current range-with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

San Fernando Valley spineflower (Chorizanthe parryi var. fernandina [S. Watson] Jeps.) (Polygonaceae) is an herbaceous annual plant, endemic to California, and until rediscovered in 1999 had been thought to be extinct for almost seven decades. Historically documented at 10 locations, it currently persists at 2, separated by approximately 27 km. State listed as endangered, a description of its genetic diversity and structure is of conservation interest. After determining a lack of variation in ploidy, we examined genetic variation from samples within both populations: a common garden study for potentially adaptive genetic variation in selected growth and phenological traits and analysis of single nucleotide polymorphisms identified through restriction-site associated DNA sequencing. Both measures indicated that this highly restricted taxon nevertheless harbors substantial levels of genetic diversity and has significant between- and within-population genetic structure. Combining approaches from population genomics and common garden studies provided more insight into the patterns and basis of genetic diversity than is typical for studies of non-model species. Although local adaptation was not specifically studied (i.e., via reciprocal transplant studies), the differences determined from these two independent lines of evidence indicate that mixing gene pools between populations is not recommended at this time. Further, with significant differences revealed among subpopulations, we caution against mixing genotypes across subpopulations for the most part, and without much more evidence that this would not pose a risk of outbreeding depression. The importance of supporting pollinator health and diversity is highlighted. With genetic diversity—particularly with an annual species—being dynamic, fluctuating with the usual processes and with contributions from the soil seedbank, we recommend periodic resampling to monitor genetic diversity and structure. Climate change is anticipated to contribute to this variability.

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Adenosine Deaminases Acting on RNA (ADARs) are enzymes that catalyze the conversion of adenosine to inosine in RNA duplexes. These enzymes can be harnessed to correct disease-causing G-to-A mutations in the transcriptome because inosine is translated as guanosine. Guide RNAs (gRNAs) can be used to direct the ADAR reaction to specific sites. Chemical modification of ADAR guide strands is required to facilitate delivery, increase metabolic stability, and increase the efficiency and selectivity of the editing reaction. Here, we show the ADAR reaction is highly sensitive to ribose modifications (e.g. 4'-C-methylation and Locked Nucleic Acid (LNA) substitution) at specific positions within the guide strand. Our studies were enabled by the synthesis of RNA containing a new, ribose-modified nucleoside analog (4'-C-methyladenosine). Importantly, the ADAR reaction is potently inhibited by LNA or 4'-C-methylation at different positions in the ADAR guide. While LNA at guide strand positions -1 and -2 block the ADAR reaction, 4'-C-methylation only inhibits at the -2 position. These effects are rationalized using high-resolution structures of ADAR-RNA complexes. This work sheds additional light on the mechanism of ADAR deamination and aids in the design of highly selective ADAR guide strands for therapeutic editing using chemically modified RNA.

Marine heatwaves (MHWs) have measurable impacts on marine ecosystems and reliant fisheries and associated communities. However, how MHWs translate to changes in fishing opportunities and the displacement of fishing fleets remains poorly understood. Using fishing vessel tracking data from the automatic identification system (AIS), we developed vessel distribution models for two pelagic fisheries targeting highly migratory species, the U.S. Atlantic longline and Pacific troll fleets, to understand how MHW properties (intensity, size, and duration) influence core fishing grounds and fleet displacement. For both fleets, MHW size had the largest influence on fishing ground area with northern fishing grounds gaining and southern fishing grounds decreasing in area. However, fleet displacement in response to MHWs varied between coasts, as the Atlantic longline fleet displaced farther in southern regions whereas the most northern and southern regions of the Pacific troll fleet shifted farther. Characterizing fishing fleet responses to these anomalous conditions can help identify regional vulnerabilities under future extreme events and aid in supporting climate-readiness and resilience in pelagic fisheries.

Studies of community assembly typically focus on the effects of abiotic environmental filters and stabilizing competition on functional trait dispersion within single trophic levels. Predation is a well-known driver of community diversity and composition, yet the role of functionally diverse predator communities in filtering prey community traits has received less attention. We examined functionally diverse communities of predators (fishes) and prey (epifaunal crustaceans) in eelgrass (Zostera marina) beds in two northern California estuaries to evaluate the filtering effects of predator traits on community assembly and how filters acting on predators influence their ability to mediate prey community assembly. Fish traits related to bottom orientation were correlated with more clustered epifauna communities, and epifauna were generally overdispersed while fishes were clustered, suggesting prey may be pushed to disparate areas of trait space to avoid capture by benthic sit-and-wait predators. We also found correlations between the trait dispersions of predator and prey communities that strengthened after accounting for the effects of habitat filters on predator dispersion, suggesting that habitat filtering effects on predator species pools may hinder their ability to affect prey community assembly. Our results present compelling observational evidence that specific predator traits have measurable impacts on the community assembly of prey, inviting experimental tests of predator trait means on community assembly and explicit comparisons of how the relative effects of habitat filters and intraguild competition on predators impact their ability to affect prey community assembly. Integrating our understanding of traits at multiple trophic levels can help us better predict the impacts of community composition on food web dynamics as regional species pools shift with climate change and anthropogenic introductions.

The proposed exploitation of the Jadar Valley lithium/borate deposit in Serbia, by the Rio Tinto Corporation, indicates that it would become large-scale processing of boron- and lithium-containing ore. It would be one of the world's very first lithium mines in populated and agricultural area. The company claims that the envisioned mining will be in accordance with environmental protection requirements. The Jadar Valley deposits have been claimed to cover 90% of Europe's current lithium needs. Yet, local opposition to the mining has arisen due to potential devastating impacts on groundwater, soil, water usage, biodiversity loss, and waste accumulation. Research drilling by the mining company has already produced environmental damage, with mine water containing high levels of boron leaking from exploratory wells and causing crops to dry out. Furthermore, our investigations reveal substantially elevated downstream concentrations of boron, arsenic, and lithium in nearby rivers as compared to upstream regions. Additionally, here we show that soil samples exhibit repeated breaches of remediation limit values with environmental consequences on both surface and underground waters. With the opening of the mine, problems will be multiplied by the tailings pond, mine wastewater, noise, air pollution, and light pollution, endangering the lives of numerous local communities and destroying their freshwater sources, agricultural land, livestock, and assets.

Indonesia faces significant air quality issues due to multiple emissions sources, including rapid urbanization and peatland fires associated with agricultural land management. Limited prior research has estimated the episodic shock of intense fires on morbidity and mortality in Indonesia but has largely ignored the impact of poor air quality throughout the year on biomarkers of cardiovascular disease risk. We conducted a cross-sectional study of the association between particulate matter less than 2.5 microns in diameter (PM2.5) and blood pressure. Blood pressure measurements were obtained from the fifth wave of the Indonesian Family Life Survey (IFLS5), an ongoing population-based socioeconomic and health survey. We used the GEOS-Chem chemical transport model to simulate daily PM2.5 concentrations at 0.5° × 0.625° resolution across the IFLS domain. We assessed the association between PM2.5 and diastolic and systolic blood pressure, using mixed effects models with random intercepts for regency/municipality and household and adjusted for individual covariates. An interquartile range increase in monthly PM2.5 exposure was associated with a 0.234 (95% CI: 0.003, 0.464) higher diastolic blood pressure, with a greater association seen in participants age 65 and over (1.16 [95% CI: 0.24, 2.08]). For the same exposure metric, there was a 1.90 (95% CI: 0.43, 3.37) higher systolic blood pressure in participants 65 and older. Our assessment of fire-specific PM2.5 yielded null results, potentially due to the timing and locations of health data collection. To our knowledge, this is the first study to provide evidence for an association between PM2.5 and blood pressure in Indonesia.

Urban air pollution can vary sharply in space and time. However, few monitoring strategies can concurrently resolve spatial and temporal variation at fine scales. Here, we present a new measurement-driven spatiotemporal modeling approach that transcends the individual limitations of two complementary sampling paradigms: mobile monitoring and fixed-site sensor networks. We develop, validate, and apply this model to predict black carbon (BC) using data from an intensive, 100-day field study in West Oakland, CA. Our spatiotemporal model exploits coherent spatial patterns derived from a multipollutant mobile monitoring campaign to fill spatial gaps in time-complete BC data from a low-cost sensor network. Our model performs well in reconstructing patterns at fine spatial and temporal resolution (30 m, 15 min), demonstrating strong out-of-sample correlations for both mobile (Pearson's R ∼ 0.77) and fixed-site measurements (R ∼ 0.95) while revealing features that are not effectively captured by a single monitoring approach in isolation. The model reveals sharp concentration gradients near major emission sources while capturing their temporal variability, offering valuable insights into pollution sources and dynamics.

Trade-offs are crucial for species divergence and reproductive isolation. Trade-offs between investment in growth versus defense against herbivores are implicated in tropical forest diversity. Empirically exploring the role of growth-defense trade-offs in closely related species' reproductive isolation can clarify the eco-evolutionary dynamics through which growth-defense trade-offs contribute to diversity. Costus villosissimus and C. allenii are recently diverged, interfertile, and partially sympatric neotropical understory plant species primarily isolated by divergent habitat adaptation. This divergent adaptation involves differences in growth rate, which may constrain investment in defense. Here, we investigate growth-defense trade-offs and how they relate to the divergent habitat adaptation that isolates these species. We characterize leaf toughness and chemistry, evaluate the feeding preferences of primary beetle herbivores in controlled trials and field-based experiments, and investigate natural herbivory patterns. We find clear trade-offs between growth and defense: slower-growing C. allenii has tougher leaves and higher defensive chemical concentrations than faster-growing C. villosissimus. Costus villosissimus has rapid growth-based drought avoidance, enabling growth in drier habitats with few specialist herbivores. Therefore, growth-defense trade-offs mediate synergistic biotic and abiotic selection, causing the divergent habitat adaptation that prevents most interspecific mating between C. villosissimus and C. allenii. Our findings advance understanding of ecological speciation by highlighting the interplay of biotic and abiotic selection that dictates the outcome of trade-offs.

On-site conversion of organic waste into biogas to satisfy consumer energy demand has the potential to realize energy equality and mitigate climate change reliably. However, existing methods ignore either real-time full supply or methane escape when supply and demand are mismatched. Here, we show an improved design of community biogas production and distribution system to overcome these and achieve full co-benefits in developing economies. We take five existing systems as empirical examples. Mechanisms of synergistic adjusting out-of-step biogas flow rates on both the plant-side and user-side are defined to obtain consumption-to-production ratios of close to 1, such that biogas demand of rural inhabitants can be met. Furthermore, carbon mitigation and its viability under universal prevailing climates are illustrated. Coupled with manure management optimization, Chinese national deployment of the proposed system would contribute a 3.77% reduction towards meeting its global 1.5 °C target. Additionally, fulfilling others' energy demands has considerable decarbonization potential.

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

Legacy effects describe the persistent, long-term impacts on an ecosystem following the removal of an abiotic or biotic feature. Redlining, a policy that codified racial segregation and disinvestment in minoritized neighborhoods, has produced legacy effects with profound impacts on urban ecosystem structure and health. These legacies have detrimentally impacted public health outcomes, socioeconomic stability, and environmental health. However, the collateral impacts of redlining on wildlife communities are uncertain. Here, we investigated whether faunal biodiversity was associated with redlining. We used home-owner loan corporation (HOLC) maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] across four cities in California and contributory science data (iNaturalist) to estimate alpha and beta diversity across six clades (mammals, birds, insects, arachnids, reptiles, and amphibians) as a function of HOLC grade. We found that in greenlined neighborhoods, unique species were detected with less sampling effort, with redlined neighborhoods needing over 8,000 observations to detect the same number of unique species. Historically redlined neighborhoods had lower native and nonnative species richness compared to greenlined neighborhoods across each city, with disparities remaining at the clade level. Further, community composition (i.e., beta diversity) consistently differed among HOLC grades for all cities, including large differences in species assemblage observed between green and redlined neighborhoods. Our work spotlights the lasting effects of social injustices on the community ecology of cities, emphasizing that urban conservation and management efforts must incorporate an antiracist, justice-informed lens to improve biodiversity in urban environments.

Net nitrogen mineralization (Nmin) and nitrification regulate soil N availability and loss after severe wildfires in boreal forests experiencing slow vegetation recovery. Yet, how microorganisms respond to postfire phosphorus (P) enrichment to alter soil N transformations remains unclear in N-limited boreal forests. Here, we investigated postfire N-P interactions using an intensive regional-scale sampling of 17 boreal forests in the Greater Khingan Mountains (Inner Mongolia-China), a laboratory P-addition incubation, and a continental-scale meta-analysis. We found that postfire soils had an increased risk of N loss by accelerated Nmin and nitrification along with low plant N demand, especially during the early vegetation recovery period. The postfire N/P imbalance created by P enrichment acts as a "N retention" strategy by inhibiting Nmin but not nitrification in boreal forests. This strategy is attributed to enhanced microbial N-use efficiency and N immobilization. Importantly, our meta-analysis found that there was a greater risk of N loss in boreal forest soils after fires than in other climatic zones, which was consistent with our results from the 17 soils in the Greater Khingan Mountains. These findings demonstrate that postfire N-P interactions play an essential role in mitigating N limitation and maintaining nutrient balance in boreal forests.

Contaminated drinking water from widespread environmental pollutants such as perfluoroalkyl and polyfluoroalkyl substances (PFAS) poses a rising threat to public health. PFAS monitoring in groundwater is limited and fails to consider pesticides found to contain PFAS as a potential contamination source. Given previous findings on the disproportionate exposure of communities of Color to both pesticides and PFAS, we investigated disparities in PFAS-contaminated pesticide applications in California based on community-level sociodemographic characteristics. We utilized statewide pesticide application data from the California Department of Pesticide Regulation and recently reported concentrations of PFAS chemicals detected in eight pesticide products to calculate the areal density of PFAS applied within 1 km of individual community water systems' (CWSs) supply wells. Spatial regression analyses suggest that statewide, CWSs that serve a greater proportion of Latinx and non-Latinx People of Color residents experience a greater areal density of PFAS applied and greater likelihood of PFAS application near their public supply wells. These results highlight agroecosystems as potentially important sources of PFAS in drinking water and identify areas that may be at risk of PFAS contamination and warrant additional PFAS monitoring and remediation.

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sectors, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, and play an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Insight M, MethaneAIR, and Scientific Aviation. Over a 6 week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1 to over 1,500 kg(CH4)/h. Aircraft consistently quantified releases above 10 kg(CH4)/h, and GHGSat-AV and Insight M detected emissions below 5 kg(CH4)/h. Fully blinded quantification estimates for platforms using downward-facing imaging spectrometers have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using continuous air sampling has a parity slope of 0.5 (R2 = 0.93). Results demonstrate that aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

Infectious disease can shape community structure, particularly when pathogens affect foundation species. Seagrasses are foundation species that form meadows along coasts worldwide, controlling sediment deposition and biogeochemical cycling while supporting a diverse community of fish and invertebrates. These plants are hosts to wasting diseases that cause necrotic tissue lesions, which could alter seagrass value as food, habitat and mediators of ecosystem processes. However, such biotic interactions and influences on disease dynamics are still not well understood. We investigated whether a common herbivore affected the development of wasting disease on eelgrass. We measured the severity and prevalence of eelgrass wasting disease in a meadow across two summers through repeated field surveys. We assessed the role of the eelgrass herbivore on disease spread and growth using microcosm and mesocosm experiments. We further explored herbivore feeding preferences in a choice trial, which was paired with chemical analysis of plant tissue and analysed using a structural equation model. While the herbivore facilitates the growth of new disease lesions among isolated leaves, on balance they reduce lesion severity by more than 50% in comparison with no-herbivore controls in field-realistic settings. This was likely because the herbivore strongly prefers to eat diseased rather than healthy tissue, consuming nearly twice as much lesion area in choice trials. This preference arises from pathogen-driven changes in the host plant; lesioned tissue requires less force to penetrate than non-lesioned tissue. Additionally, as lesions increase in size, their polyphenolic concentrations drop, which further increases the magnitude of preference for lesioned tissue. Synthesis: These results suggest that these herbivores could help maintain disease in this system at a high prevalence (by facilitating disease development) but low severity (through preferential consumption), which is consistent with our field observations of nearly 100% prevalence and low severity in a natural bed where herbivore density is high. Describing such multi-species interactions in marine systems will advance our predictions of future disease states, as current understandings focus primarily on how environmental change contributes to pathogen outbreaks.

Host–microbiota interactions play a critical role in the hosts’ biology, and thus, it is crucial to elucidate the mechanisms that shape gut microbial communities. We leveraged threespine stickleback fish ( Gasterosteus aculeatus ) as a model system to investigate the contribution of host and environmental factors to gut microbiota variation. These fish offer a unique opportunity for experiments in naturalistic conditions; we reared benthic and limnetic ecotypes from three different lakes in experimental ponds, allowing us to assess the relative effects of shared environment (pond), geographic origin (lake-of-origin), trophic ecology and genetics (ecotype) and biological sex on gut microbiota α- and β-diversity. Host ecotype had the strongest influence on α-diversity, with benthic fish exhibiting higher diversity than limnetic fish, followed by the rearing environment. β-diversity was primarily shaped by rearing environment, followed by host ecotype, indicating that environmental factors play a crucial role in determining gut microbiota composition. Furthermore, numerous bacterial orders were differentially abundant across ponds, underlining the substantial contribution of environmental factors to gut microbiota variation. Our study illustrates the complex interplay between environmental and host ecological or genetic factors in shaping the stickleback gut microbiota and highlights the value of experiments conducted under naturalistic conditions for understanding gut microbiota dynamics.

Soil microorganisms help transform plant inputs into mineral-associated soil organic carbon (SOC) – the largest and slowest-cycling pool of organic carbon on land. However, the microbial traits that influence this process are widely debated. While current theory and biogeochemical models have settled on carbon-use efficiency (CUE) and growth rate as positive predictors of mineral-associated SOC, empirical tests are sparse, with contradictory observations. Using 13C-labeling of an annual grass (Avena barbata) under two moisture regimes, we found that microbial traits associated with formation of 13C-mineral-associated SOC varied by soil habitat, as did active microbial taxa and SOC chemical composition. In the rhizosphere, bacterial-dominated communities with fast growth, high biomass, and high extracellular polymeric substance (EPS) production were positively associated with 13C-mineral-associated SOC. In contrast, the detritusphere held communities dominated by fungi and more filamentous bacteria, and with greater exoenzyme activity; there, 13C-mineral-associated SOC was associated with slower microbial growth and lower microbial biomass. CUE was a negative predictor of 13C-mineral-associated SOC in both habitats. Using 13C-quantitative stable isotope probing, we found that the majority of 13C assimilation in the rhizosphere and detritusphere at week 12 of the experiment was performed by very few bacterial and fungal taxa (3–5% of the total taxa that assimilated 13C). Several complementary chemical analyses (13C-NMR, FTICR-MS, and STXM-NEXAFS) suggested that SOC in the rhizosphere had a more oxidized chemical signature, while SOC in the detritusphere had a less oxidized, more lignin-like chemical signature. Our findings challenge current theory by demonstrating that microbial traits linked with mineral-associated SOC are not universal, but vary with soil habitat and moisture conditions, and are shaped by a small number of active taxa. Emerging SOC models that explicitly reflect these interactions may better predict SOC storage, since climate change causes shifts in soil moisture regimes and the ratio of living versus decaying roots.

Mining activities put the Brazilian savannas, a global biodiversity hotspot, in danger of species and soil carbon losses. Experiments employing biosolids have been applied to rejuvenate this degraded ecosystem, but a lingering question yet to be answered is whether the microbiota that inhabits these impoverished soils can be recovered towards its initial steady state after vegetation recovery. Here, we selected an 18-year-old restoration chronosequence of biosolids-treated, untreated mining and native soils to investigate the soil microbiota recovery based on composition, phylogeny, and diversity, as well as the potential factors responsible for ecosystem recovery. Our results revealed that the soil microbiota holds a considerable recovery potential in the degraded Cerrado biome. Biosolids application not only improved soil health, but also led to 41.7 % recovery of the whole microbial community, featuring significantly higher microbiota diversity and enriched groups (e.g., Firmicutes) that benefit carbon storage compared to untreated mining and native soils. The recovered community showed significant compositional distinctions from the untreated mining or native soils, rather than phylogenetic differences, with physiochemical properties explaining 55 % of the overall community changes. This study advances our understanding of soil microbiota dynamics in response to disturbance and restoration by shedding light on its recovery associated with biosolid application in a degraded biodiverse ecosystem.

Following publication of the original article [1], the authors reported two errors in Fig. 1B and Fig. 2B. 1. The two EP + siGLO and DS + siGLO brightfield/β-gal images from Fig. 2A were accidentally duplicated in Fig. 1B. The images in Fig. 2A are correct. The images in Fig. 1B are replaced with representative images of untransfected EP and DS cells. The incorrect and the correct figure are given below. The incorrect Fig. 1: (Figure presented.) The correct Fig. 1: (Figure presented.) The replacement of these images does not change any of the other data in this figure, nor the conclusion of this figure. 2. The authors also noticed that the panels in Fig. 2B labelled with “DS” were incorrectly labelled. The bar charts and figure legend correctly state that these images are “DS + siGLO” images. These panels are now relabelled as “DS + siGLO”. This proposed relabelling does not change any of the other data in this figure, nor the conclusion of Fig. 2B. The incorrect and the correct figure are given below. The incorrect Fig. 2: (Figure presented.) The correct Fig. 2: (Figure presented.) In both instances, these errors do not change any data associated with these figures, nor do they change the conclusions of the corresponding figures and the paper.

Stabilizing climate requires reducing greenhouse gas (GHG) emissions and storing atmospheric carbon dioxide (CO2) in land or ocean systems. Soil management practices can reduce GHG emissions or sequester atmospheric CO2 into inorganic and organic forms. However, whether soil carbon strategies represent a viable and impactful climate mitigation pathway is uncertain. A specific question concerns the role that land-management practices and soil amendments can play in realizing California’s ambition for carbon neutrality by 2045. Here we examine the carbon flux impacts of soil conservation (i.e., compost, reduced tillage, cover crop) and enhanced silicate rock weathering (EW) practices at different areal extents of implementation in cropland, grassland, and savanna in California under two climate change cases. We show that with implementation areas of 15% or 50% of private cultivated land, grassland, and savanna in California, soil conservation practices alone can contribute 1.4 0.7 2.1 % ( − 1.8 − 0.9 − 2.7 Mt CO2eq y−1) and 4.6 2.3 6.9 % ( − 6.0 − 3.0 − 8.9 Mt CO2eq y−1) of the additional emissions reduction needed (beyond previous targets) to meet the 2045 net neutrality goal (−129.3 Mt CO2eq y−1), respectively, on an average annual basis, including climate uncertainty. Including EW in these scenarios increases the total contributions of management practices to 4.1 2.5 5.6 % ( − 5.2 − 3.2 − 7.3 Mt CO2eq y−1) and 13.5 8.2 18.6 % ( − 17.5 − 10.7 − 24.2 Mt CO2eq y−1), respectively, of this reduction. This highlights that the extent of implementation area is a major factor in determining benefits and that EW has the potential to make a real contribution to net reduction targets. Results are similar across climate cases, indicating that contemporary field data can be used to make future projections. With EW there remains mechanistic uncertainties, however, such as rock dissolution rate and environmental controls on weathering products, which require additional field research to improve understanding of the technological efficacy of this approach for California’s 2045 carbon neutrality goal.

Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant-environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co-occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process-based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above- and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade-offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast-growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf-to-stem ratio. However, contrary to our hypothesis, there were no differences in root-to-leaf ratio between perennial and annual or C4 and C3 plants. Our study provides species-specific and functional-type-specific allometry equations for both above- and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade-offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

The co-occurrence of cadmium (Cd) pollution and selenium (Se) deficiency commonly exists in global soils, especially in China. As a result, there is great interest in developing practical agronomic strategies to simultaneously achieve Cd remediation and Se mobilization in paddy soils, thereby enhancing food quality/safety. To this end, we conducted a field-plot trial on soils having high geological background levels of Cd (0.67 mg kg-1) and Se (0.50 mg kg-1). We explored 12 contrasting fertilizers (urea, potassium sulfate (K2SO4), calcium-magnesium-phosphate (CMP)), amendments (manure and biochar) and their combinations on Cd/Se bioavailability. Soil pH, total organic carbon (TOC), soil available Cd/Se, Cd/Se fractions and Cd/Se accumulation in different rice components were determined. No significant differences existed in mean grain yield among treatments. Results showed that application of urea and K2SO4 decreased soil pH, whereas the CMP fertilizer and biochar treatments increased soil pH. There were no significant changes in TOC concentrations. Three treatments (CMP, manure, biochar) significantly decreased soil available Cd, whereas no treatment affected soil available Se at the maturity stage. Four treatments (CMP, manure, biochar and manure＋urea＋CMP＋K2SO4) achieved our dual goal of Cd reduction and Se enrichment in rice grain. Structural equation modeling (SEM) demonstrated that soil available Cd and root Cd were negatively affected by pH and organic matter (OM), whereas soil available Se was positively affected by pH. Moreover, redundancy analysis (RDA) showed strong positive correlations between soil available Cd, exchangeable Cd and reducible Cd with grain Cd concentration, as well as between pH and soil available Se with grain Se concentration. Further, there was a strong negative correlation between residual Cd/Se (non-available fraction) and grain Cd/Se concentrations. Overall, this study identified the primary factors affecting Cd/Se bioavailability, thereby providing new guidance for achieving safe production of Se-enriched rice through fertilizer/amendment management of Cd-enriched soils.

Abstract: Earthquake nowcasting has been proposed as a means of tracking the change in large earthquake potential in a seismically active area. The method was developed using observable seismic data, in which probabilities of future large earthquakes can be computed using Receiver Operating Characteristic methods. Furthermore, analysis of the Shannon information content of the earthquake catalogs has been used to show that there is information contained in the catalogs, and that it can vary in time. So an important question remains, where does the information originate? In this paper, we examine this question using stochastic simulations of earthquake catalogs. Our catalog simulations are computed using an Earthquake Rescaled Aftershock Seismicity (“ERAS”) stochastic model. This model is similar in many ways to other stochastic seismicity simulations, but has the advantage that the model has only 2 free parameters to be set, one for the aftershock (Omori‐Utsu) time decay, and one for the aftershock spatial migration away from the epicenter. Generating a simulation catalog and fitting the two parameters to the observed catalog such as California takes only a few minutes of wall clock time. While clustering can arise from random, Poisson statistics, we show that significant information in the simulation catalogs arises from the “non‐Poisson” power‐law aftershock clustering, implying that the practice of de‐clustering observed catalogs may remove information that would otherwise be useful in forecasting and nowcasting. We also show that the nowcasting method provides similar results with the ERAS model as it does with observed seismicity.

Although CO2 impacts the environment negatively, it can be a valuable resource due to its carbon content. The U.S. industry emits over 825 Mt of CO2 annually, with an expected increase in the future. This article analyzes 27 different technology combinations for capturing and using CO2 for industrial feedstocks, including the production of synthetic methane, methanol, and Fischer-Tropsch fuels. The study also estimates and compares the energy requirements for capturing and converting CO2 from 16 different industrial sources, as well as the energy requirements for hydrogen production through state-of-the-art and emerging electrolyzer technologies. Additionally, the study develops a combined scenario that outlines a design for applying an inclusive approach to achieve net-zero CO2 emissions in the industrial sector, incorporating multiple decarbonization measures. The results suggest that the use of CO2 for methane production has the potential to replace all natural gas demands considered in the base case and combined scenarios. However, using CO2 utilization-based Fischer-Tropsch products alone to replace naphtha feedstock and transportation fuels is not sufficient to achieve complete decarbonization in the studied end uses. CO2 utilization-based methanol could potentially substitute for several times the current U.S. methanol production and meet the current global demand for methanol. Moreover, the study conducts an economic analysis to estimate the costs of CO2 utilization, which vary for different industrial sectors and depend on the technologies employed. Overall, this study provides valuable information for policymakers and industry stakeholders who are striving to develop effective strategies to decarbonize the industrial sector.

This study investigates the relationship between temporal changes in temperatures characterizing local urban heat islands (UHIs) and heat-related illnesses (HRIs) in seven major cities of California. UHIs, which are a phenomenon that arises in the presence of impervious surfaces or the lack of green spaces exacerbate the effects of extreme heat events, can be measured longitudinally using satellite products. The two objectives of this study were: (1) to identify temperature trends in local temperatures to characterize UHIs across zip code tabulation areas (ZCTAs) in the seven observed cities over a 22-year period and (2) to use propensity score and inverse probability weighting to achieve exchangeability between different types of ZCTAs and assess the difference in hospital admissions recorded as HRIs attributable to temporal changes in UHIs. We use monthly land surface temperature data derived from MODIS Terra imagery from the summer months (June-September) from 2000 to 2022. We categorized ZCTAs (into three groups) based on their monthly land surface temperature trends. Of the 216 ZCTAs included in this study, the summertime land surface temperature trends of 43 decreased, while 161 remained unchanged, and 12 increased. Los Angeles had the greatest number of decreased ZCTAs, San Diego and San Jose had the highest number of increased ZCTAs. To analyze the number of monthly HRI attributable to changes in UHI, we used inverse probability of treatment weighting to analyze the difference in HRI between the years of 2006 and 2017 which were two major extreme heat events over the entire State. We observed an average reduction of 3.2 (95 % CI: 0.5; 5.9) HRIs per month and per ZCTAs in decreased neighborhoods as compared to unchanged. This study emphasizes the importance of urban climate adaptation strategies to mitigate the intensity and prevalence of UHIs to reduce health risks related to heat.

Harmful cyanobacteria blooms are a growing threat in estuarine waters as upstream blooms are exported into coastal environments. Cyanobacteria can produce potent toxins, one of which-hepatotoxic microcystins (MCs)-can persist and accumulate within the food web. Filter-feeding invertebrates may biomagnify toxins up to 100× ambient concentrations. As such, bivalves can be used as an environmentally relevant and highly sensitive sentinel for MC monitoring. To date there has been little research on cyanotoxin bioaccumulation in estuaries. The Sacramento-San Joaquin Delta (Delta) aquatic food web has undergone a profound change in response to widespread colonization of aquatic invasive species such as Asian clams (Corbicula fluminea) in the freshwater portion of the Delta. These clams are prolific-blanketing areas of the Delta at densities up to 1000 clams/m2 and are directly implicated in the pelagic organism decline of threatened and endangered fishes. We hypothesized that Asian clams accumulate MCs which may act as an additional stressor to the food web and MCs would seasonally be in exceedance of public health advisory levels. MCs accumulation in Delta Asian clams and signal crayfish (Pacifastacus leniusculus) were studied over a two-year period. ELISA and LC-MS analytical methods were used to measure free and protein-bound MCs in clam and crayfish tissues. We describe an improved MC extraction method for use when analyzing these taxa by LC-MS. MCs were found to accumulate in Asian clams across all months and at all study sites, with seasonal maxima occurring during the summer. Although MC concentrations rarely exceeded public health advisory levels, the persistence of MCs year-round still poses a chronic risk to consumers. Crayfish at times also accumulated high concentrations of MCs. Our results highlight the utility of shellfish as sentinel organisms for monitoring in estuarine areas.

Abstract: Advances in hierarchical modeling have improved estimation of ecological parameters from count data, especially those quantifying population abundance, distribution, and dynamics by explicitly accounting for observation processes, particularly incomplete detection. Even hierarchical models that account for incomplete detection, however, cannot compensate for data limitations stemming from poorly planned sampling. Ecologists therefore need guidance for planning count‐based studies that follow established sampling theory, collect appropriate data, and apply current modeling approaches to answer their research questions. We synthesize available literature relevant to guiding count‐based studies. Considering the central historical and ongoing contributions of avian studies to ecological knowledge, we focus on birds as a case study for this review, but the basic principles apply to all populations whose members are sufficiently observable to be counted. The sequence of our review represents the thought process in which we encourage ecologists to engage 1) the research question(s) and population parameters to measure, 2) sampling design, 3) analytical framework, 4) temporal design, and 5) survey protocol. We also provide 2 hypothetical demonstrations of these study plan components representing different research questions and study systems. Mirroring the structure of hierarchical models, we suggest researchers primarily focus on the ecological processes of interest when designing their approach to sampling, and wait to consider logistical constraints of data collection and observation processes when developing the survey protocol. We offer a broad framework for researchers planning count‐based studies, while pointing to relevant literature elaborating on particular tools and concepts.

Contemporary resource management is doubly burdened by high rates of organic material disposal in landfills, generating potent greenhouse gases (GHG), and globally degraded soils, which threaten future food security. Expansion of composting can provide a resilient alternative, by avoiding landfill GHG emissions, returning valuable nutrients to the soil to ensure continued agricultural production, and sequestering carbon while supporting local communities. Recognizing this opportunity, California has set ambitious organics diversion targets in the Short-Lived Climate Pollutant Law (SB1383) which will require significant increases (5 to 8 million tonnes per year) in organic material processing capacity. This paper develops a spatial optimization model to consider how to handle this flow of additional material while achieving myriad social and ecological benefits through compost production. We consider community-based and on-farm facilities alongside centralized, large-scale infrastructure to explore decentralized and diversified alternative futures of composting infrastructure in the state of California. We find using a diversity of facilities would provide opportunity for cost savings while achieving significant emissions reductions of approximately 3.4 ± 1 MMT CO2e and demonstrate that it is possible to incorporate community protection into compost infrastructure planning while meeting economic and environmental objectives.

Recent research has shown that membrane trafficking plays an important role in canonical Wnt signaling through sequestration of the β-catenin destruction complex inside multivesicular bodies (MVBs) and lysosomes. In this study, we introduce Ouabain, an inhibitor of the Na,K-ATPase pump that establishes electric potentials across membranes, as a potent inhibitor of Wnt signaling. We find that Na,K-ATPase levels are elevated in advanced colon carcinoma, that this enzyme is elevated in cancer cells with constitutively activated Wnt pathway and is activated by GSK3 inhibitors that increase macropinocytosis. Ouabain blocks macropinocytosis, which is an essential step in Wnt signaling, probably explaining the strong effects of Ouabain on this pathway. In Xenopus embryos, brief Ouabain treatment at the 32-cell stage, critical for the earliest Wnt signal in development-inhibited brains, could be reversed by treatment with Lithium chloride, a Wnt mimic. Inhibiting membrane trafficking may provide a way of targeting Wnt-driven cancers.

Prenatal per- and poly-fluoroalkyl substances (PFAS) exposure may influence gestational outcomes through bioactive lipids─metabolic and inflammation pathway indicators. We estimated associations between prenatal PFAS exposure and bioactive lipids, measuring 12 serum PFAS and 50 plasma bioactive lipids in 414 pregnant women (median 17.4 weeks' gestation) from three Environmental influences on Child Health Outcomes Program cohorts. Pairwise association estimates across cohorts were obtained through linear mixed models and meta-analysis, adjusting the former for false discovery rates. Associations between the PFAS mixture and bioactive lipids were estimated using quantile g-computation. Pairwise analyses revealed bioactive lipid levels associated with PFDeA, PFNA, PFOA, and PFUdA (p < 0.05) across three enzymatic pathways (cyclooxygenase, cytochrome p450, lipoxygenase) in at least one combined cohort analysis, and PFOA and PFUdA (q < 0.2) in one linear mixed model. The strongest signature revealed doubling in PFOA corresponding with PGD2 (cyclooxygenase pathway; +24.3%, 95% CI: 7.3-43.9%) in the combined cohort. Mixture analysis revealed nine positive associations across all pathways with the PFAS mixture, the strongest signature indicating a quartile increase in the PFAS mixture associated with PGD2 (+34%, 95% CI: 8-66%), primarily driven by PFOS. Bioactive lipids emerged as prenatal PFAS exposure biomarkers, deepening insights into PFAS' influence on pregnancy outcomes.

Bottlenose dolphins (Tursiops truncatus) are keystone and sentinel species in the world's oceans. We studied correlations between per- and polyfluoroalkyl substances (PFAS) and their stress axis. We investigated associations between plasma biomarkers of 12 different PFAS variants and three cortisol pools (total, bound, and free) in wild T. truncatus from estuarine waters of Charleston, South Carolina (n = 115) and Indian River Lagoon, Florida (n = 178) from 2003 to 2006, 2010-2013, and 2015. All PFAS and total cortisol levels for these dolphins were previously reported; bound cortisol levels and free cortisol calculations have not been previously reported. We tested null hypotheses that levels of each PFAS were not correlated with those of each cortisol pool. Free cortisol levels were lower when PFOS, PFOA, and PFHxS biomarker levels were higher, but free cortisol levels were higher when PFTriA was higher. Bound cortisol levels were higher when there were higher PFDA, PFDoDA, PFDS, PFTeA, and PFUnDA biomarkers. Total cortisol was higher when PFOA was lower, but total cortisol was higher when PFDA, PFDoDA, PFTeA, and PFTriA were higher. Additional analyses indicated sex and age trends, as well as heterogeneity of effects from the covariates carbon chain length and PFAS class. Although this is a cross-sectional observational study and, therefore, could reflect cortisol impacts on PFAS toxicokinetics, these correlations are suggestive that PFAS impacts the stress axis in T. truncatus. However, if PFAS do impact the stress axis of dolphins, it is specific to the chemical structure, and could affect the individual pools of cortisol differently. It is critical to conduct long-term studies on these dolphins and to compare them to populations that have no or little expose to PFAS.

Aquaculture is one of the fastest-growing food sectors, producing almost 50% of fish for human consumption worldwide. However, relying on fish meal and oil for aquaculture diets is not sustainable economically or environmentally. Aquaculture feeds also contain terrestrial plant ingredients with indigestible forms of phosphorus (P), of which 70%–80% can be released into aquatic environments. This P influx contributes to eutrophication of freshwater ecosystems that can lead to anoxic conditions. This study explores a more sustainable diet for salmonids, an important and valuable seafood. Our aim was to test ingredients with highly digestible forms of P in nutritionally balanced portions to support fish growth and reduce P loading. We determined the digestibility of three feeds containing raw, extruded, and enzymatically processed microalgal co-product of Nannochloropsis oculata compared to a conventional diet. We also quantified how much P was retained and excreted. We detected highest growth in trout fed enzymatically processed co-product feed, though it was not statistically different (p = 0.846) from growth of fish fed the reference or other co-product diets. The enzyme-treated, microalgal co-product ingredient and diet had comparable values for P digestibility and solid P excretion to the reference diet, but the lowest average solid P excretion of all test diets. Trout fed the enzyme-treated diet had the highest P retention, while the reference diet had the lowest (p = 0.0429). Trout fed the enzyme-treated diet had the lowest (p = 0.0174) and negative dissolved P excretion, while those fed the reference diet had the highest. Results showed that enzyme-treated N. oculata co-product maintains digestibility, increases P retention, and reduces dissolved P excretion compared to the reference diet in rainbow trout. These findings encourage follow-up research to design and test growth performance of diets containing enzyme-treated microalgal co-product as sustainable trout aquafeed.

Large-genome bacteriophages (jumbo phages) of the proposed family Chimalliviridae assemble a nucleus-like compartment bounded by a protein shell that protects the replicating phage genome from host-encoded restriction enzymes and DNA-targeting CRISPR-Cas nucleases. While the nuclear shell provides broad protection against host nucleases, it necessitates transport of mRNA out of the nucleus-like compartment for translation by host ribosomes, and transport of specific proteins into the nucleus-like compartment to support DNA replication and mRNA transcription. Here, we identify a conserved phage nuclear shell-associated protein that we term Chimallin C (ChmC), which adopts a nucleic acid-binding fold, binds RNA with high affinity in vitro, and binds phage mRNAs in infected cells. ChmC also forms phase-separated condensates with RNA in vitro. Targeted knockdown of ChmC using mRNA-targeting dCas13d results in accumulation of phage-encoded mRNAs in the phage nucleus, reduces phage protein production, and compromises virion assembly. Taken together, our data show that the conserved ChmC protein plays crucial roles in the viral life cycle, potentially by facilitating phage mRNA translocation through the nuclear shell to promote protein production and virion development.

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

The costs of foraging can be high while also carrying significant risks, especially for consumers feeding at the top of the food chain. To mitigate these risks, many predators supplement active hunting with scavenging and kleptoparasitic behaviours, in some cases specializing in these alternative modes of predation. The factors that drive differential utilization of these tactics from species to species are not well understood. Here, we use an energetics approach to investigate the survival advantages of hunting, scavenging and kleptoparasitism as a function of predator, prey and potential competitor body sizes for terrestrial mammalian carnivores. The results of our framework reveal that predator tactics become more diverse closer to starvation, while the deployment of scavenging and kleptoparasitism is strongly constrained by the ratio of predator to prey body size. Our model accurately predicts a behavioural transition away from hunting towards alternative modes of predation with increasing prey size for predators spanning an order of magnitude in body size, closely matching observational data across a range of species. We then show that this behavioural boundary follows an allometric power-law scaling relationship where the predator size scales with an exponent nearing 3/4 with prey size, meaning that this behavioural switch occurs at relatively larger threshold prey body size for larger carnivores. We suggest that our approach may provide a holistic framework for guiding future observational efforts exploring the diverse array of predator foraging behaviours.

With increased interest in forest restoration comes an urgent need to provide accurate, scalable, and cost‐effective monitoring tools. The ubiquity of smartphones has led to a surge in monitoring apps. We reviewed and assessed monitoring apps found through web searches and conversations with practitioners. We identified 42 apps that (1) automatically monitor indicators or (2) facilitate data entry. We selected the five most promising from the first category, based on their relevance, availability, stability, and user support. We compared them to traditional field techniques in a well‐studied restoration project in Costa Rica. We received further feedback from 15 collaborator organizations that evaluated these in their corresponding field restoration sites. Diameter measurements correlated well with traditional tape‐based measurements (R2 = 0.86–0.89). Canopy openness and ground cover showed weaker correlations to densiometer and quadrat cover measurements (R2 = 0.42–0.51). Apps did not improve labor efficiency but do preclude the purchase of specialized field equipment. The apps reviewed here need further development and validation to support monitoring adequately, especially in the tropics. Estimates of development and maintenance costs, as well as statistics on user uptake, are required for cost‐effective development. We recommend a coordinated effort to develop dedicated restoration monitoring apps that can speed up and standardize the collection of indicators and provide evidence on restoration outcomes alongside a centralized repository of this information.

Permafrost stability is significantly influenced by the thermal buffering effects of snow and active-layer peat soils. In the warm season, peat soils act as a barrier to downward heat transfer mainly due to their low thermal conductivity. In the cold season, the snowpack serves as a thermal insulator, retarding the release of heat from the soil to the atmosphere. Currently, many global land models overestimate permafrost soil temperature and active layer thickness (ALT), partially due to inaccurate representations of soil organic matter (SOM) density profiles and snow thermal insulation. In this study, we evaluated the impacts of SOM and snow schemes on ALT simulations at pan-Arctic permafrost sites using the Energy Exascale Earth System Model (E3SM) land model (ELM). We conducted simulations at the Circumpolar Active Layer Monitoring (CALM) sites across the pan-Arctic domain. We improved ELM-simulated site-level ALT using a knowledge-based hierarchical optimization procedure and examined the effects of precipitation-phase partitioning methods (PPMs), snow compaction schemes, and snow thermal conductivity schemes on simulated snow depth, soil temperature, ALT, and CO2 fluxes. Results showed that the optimized ELM significantly improved agreement with observed ALT (e.g. RMSE decreased from 0.83 m to 0.15 m). Our sensitivity analysis revealed that snow-related schemes significantly impact simulated snow thermal insulation levels, soil temperature, and ALT. For example, one of the commonly used snow thermal conductivity schemes (quadratic Sturm or SturmQua) generally produced warmer soil temperatures and larger ALT compared to the other two tested schemes. The SturmQua scheme also amplified the model’s sensitivity to PPMs and predicted deeper ALTs than the other two snow schemes under both current and future climates. The study highlights the importance of accurately representing snow-related processes and peat soils in land models to enhance permafrost dynamics simulations.