Positive effects of public breeding on US rice yields under future climate scenarios.

In this study, we model and predict rice yields by integrating molecular marker variation, varietal productivity, and climate, focusing on the Southern U.S. rice-growing region. This region spans the states of Arkansas, Louisiana, Texas, Mississippi, and Missouri and accounts for 85% of total U.S. rice production. By digitizing and combining four decades of county-level variety acreage data (1970 to 2015) with varietal information from genotyping-by-sequencing data, we estimate annual historical county-level allele frequencies. These allele frequencies are used together with county-level weather and yield data to develop ten machine learning models for yield prediction. A two-layer meta-learner ensemble model that combines all ten methods is externally evaluated against observations from historical Uniform Regional Rice Nursery trials (1980 to 2018) conducted in the same states. Finally, the ensemble model is used with forecasted weather from the Coupled Model Intercomparison Project across the 110 rice-growing counties to predict production in the coming decades for Composite Variety Groups assembled based on year of release, breeding program, and several breeding trends. Results indicate positive effects over time of public breeding on rice resilience to future climates, and potential reasons are discussed.

Space weather disrupts nocturnal bird migration.

Space weather, including solar storms, can impact Earth by disturbing the geomagnetic field. Despite the known dependence of birds and other animals on geomagnetic cues for successful seasonal migrations, the potential effects of space weather on organisms that use Earth's magnetic field for navigation have received little study. We tested whether space weather geomagnetic disturbances are associated with disruptions to bird migration at a macroecological scale. We leveraged long-term radar data to characterize the nightly migration dynamics of the nocturnally migrating North American avifauna over 22 y. We then used concurrent magnetometer data to develop a local magnetic disturbance index associated with each radar station (ΔBmax), facilitating spatiotemporally explicit analyses of the relationship between migration and geomagnetic disturbance. After controlling for effects of atmospheric weather and spatiotemporal patterns, we found a 9 to 17% decrease in migration intensity in both spring and fall during severe space weather events. During fall migration, we also found evidence for decreases in effort flying against the wind, which may represent a depression of active navigation such that birds drift more with the wind during geomagnetic disturbances. Effort flying against the wind in the fall was most reduced under both overcast conditions and high geomagnetic disturbance, suggesting that a combination of obscured celestial cues and magnetic disturbance may disrupt navigation. Collectively, our results provide evidence for community-wide avifaunal responses to geomagnetic disturbances driven by space weather during nocturnal migration.

Refugee settlements are highly exposed to extreme weather conditions.

Involuntary displacement from conflict and other causes leads to clustering of refugees and internally displaced people, often in long-term settlements. Within refugee-hosting countries, refugee settlements are frequently located in isolated and remote areas, characterized by poor-quality land and harsh climatic conditions. Yet, the exposure of refugee settlements to climatic events is underresearched. In this article, we study the exposure of the 20 largest refugee settlements worldwide to extreme variations in climatic conditions. The analysis integrates exposure of camp locations compared to the national trends for both slow- and rapid-onset events and includes descriptive statistics, signal-to-noise analyses, and trend analyses. Our findings show that most refugee settlements included face relatively high exposure to slow-onset events, including high temperatures (for settlements in Kenya, Ethiopia, Rwanda, Sudan, and Uganda), low temperatures (in the case of Jordan and Pakistan), and low levels of rainfall (in Ethiopia, Rwanda, Kenya, and Uganda) compared to national averages. Our findings for rapid-onset events-heatwaves, coldwaves, and extreme rainfall-are less conclusive compared to country trends, although we find relatively high exposure to extreme rainfall in Cox's Bazar, Bangladesh. Our analyses confirm that refugee populations are exposed to extreme weather conditions postdisplacement, which, in combination with their sociopolitical exclusion, poses a threat to well-being and increased marginalization. Our findings call for an inclusive and integrated approach, including refugees and their host communities, in designing climate adaptation and sustainable development policies, in order to promote equitable sustainable development pathways in refugee-hosting countries.

Trends of extreme US weather events in the changing climate.

Trends in extreme 100-y events of temperature and rainfall amounts in the continental United States are estimated, to see effects of climate change. This is a nontrivial statistical problem because climate change effects have to be extracted from "noisy" weather data within a limited time range. We use nonparametric Bayesian methods to estimate the trends of extreme events that have occurred between 1979 and 2019, based on data for temperature and rainfall. We focus on 100-y events for each month in [Formula: see text] geographical areas looking at hourly temperature and 5-d cumulative rainfall. Distribution tail models are constructed using extreme value theory (EVT) and data on 33-y events. This work shows it is possible to aggregate data from spatial points in diverse climate zones for a given month and fit an EVT model with the same parameters. This surprising result means there are enough extreme event data to see the trends in the 41-y record for each calendar month. The yearly trends of the risk of a 100-y high-temperature event show an average 2.1-fold increase over the last 41 y of data across all months, with a 2.6-fold increase for the months of July through October. The risk of high rainfall extremes increases in December and January 1.4-fold, but declines by 22% for the spring and summer months.

Trends in surface equivalent potential temperature: A more comprehensive metric for global warming and weather extremes.

Trends in surface air temperature (SAT) are a common metric for global warming. Using observations and observationally driven models, we show that a more comprehensive metric for global warming and weather extremes is the trend in surface equivalent potential temperature (Thetae_sfc) since it also accounts for the increase in atmospheric humidity and latent energy. From 1980 to 2019, while SAT increased by 0.79[Formula: see text], Thetae_sfc increased by 1.48[Formula: see text] globally and as much as 4[Formula: see text] in the tropics. The increase in water vapor is responsible for the factor of 2 difference between SAT and Thetae_sfc trends. Thetae_sfc increased more uniformly (than SAT) between the midlatitudes of the southern hemisphere and the northern hemisphere, revealing the global nature of the heating added by greenhouse gases (GHGs). Trends in heat extremes and extreme precipitation are correlated strongly with the global/tropical trends in Thetae_sfc. The tropical amplification of Thetae_sfc is as large as the arctic amplification of SAT, accounting for the observed global positive trends in deep convection and a 20% increase in heat extremes. With unchecked GHG emissions, while SAT warming can reach 4.8[Formula: see text] by 2100, the global mean Thetae_sfc can increase by as much as 12[Formula: see text], with corresponding increases of 12[Formula: see text] (median) to 24[Formula: see text] (5% of grid points) in land surface temperature extremes, a 14- to 30-fold increase in frequency of heat extremes, a 40% increase in the energy available for tropical deep convection, and an up to 60% increase in extreme precipitation.

Association of weather variables with pathogens contributing to conjunctivitis worldwide.

PURPOSE: To identify weather variables associated with pathogens contributing to infectious conjunctivitis globally. METHODS: Sample collection and pathogen identification from patients with acute infectious conjunctivitis was performed from 2017 to 2023. We linked pathogens identified from 13 sites across 8 countries with publicly available weather data by geographic coordinates. Mixed effects logistic regression analysis was performed to estimate the associations between temperature, precipitation, and relative humidity exposures, and the prevalence of infection types (RNA virus, DNA virus, bacteria, and fungus). RESULTS: 498 cases from the United States, India, Nepal, Thailand, Burkina Faso, Niger, Vietnam, and Israel were included in the analysis. 8-day average precipitation (mm) was associated with increased odds of RNA virus infection (odds ratio (OR)=1.47, 95% confidence interval (CI): 1.12 to 1.93, P=0.01) and decreased odds of DNA infection (OR=0.62, 95% CI: 0.46 to 0.82, P<0.001). Relative humidity (%) was associated with increased odds of RNA virus infections (OR=2.64, 95% CI: 1.51 to 4.61, P<0.001), and fungal infections (OR=2.35, 95% CI: 1.19 to 4.66, P=0.01), but decreased odds of DNA virus (OR=0.58, 95%CI: 0.37 to 0.90, P=0.02) and bacterial infections (OR=0.42, 95% CI: 0.25 to 0.71, P<0.001). Temperature (°C) was not associated with ocular infections for any pathogen type. CONCLUSIONS: This study suggests that weather factors affect pathogens differently. Particularly, humidity and precipitation were predictors for pathogens contributing to conjunctivitis worldwide. Additional work is needed to clarify the effects of shifts in weather and environmental factors on ocular infectious diseases.

Integrated causal-predictive machine learning models for tropical cyclone epidemiology.

Strategic preparedness reduces the adverse health impacts of hurricanes and tropical storms, referred to collectively as tropical cyclones (TCs), but its protective impact could be enhanced by a more comprehensive and rigorous characterization of TC epidemiology. To generate the insights and tools necessary for high-precision TC preparedness, we introduce a machine learning approach that standardizes estimation of historic TC health impacts, discovers common patterns and sources of heterogeneity in those health impacts, and enables identification of communities at highest health risk for future TCs. The model integrates (i) a causal inference component to quantify the immediate health impacts of recent historic TCs at high spatial resolution and (ii) a predictive component that captures how TC meteorological features and socioeconomic/demographic characteristics of impacted communities are associated with health impacts. We apply it to a rich data platform containing detailed historic TC exposure information and records of all-cause mortality and cardiovascular- and respiratory-related hospitalization among Medicare recipients. We report a high degree of heterogeneity in the acute health impacts of historic TCs, both within and across TCs, and, on average, substantial TC-attributable increases in respiratory hospitalizations. TC-sustained windspeeds are found to be the primary driver of mortality and respiratory risks.

Contrasting seasonal responses to wind in migrating songbirds on a globally important flyway.

During spring migration, nocturnal migrants attempt to minimize their travel time to reach their breeding grounds early. However, how they behave and respond to unfavourable conditions during their springtime travels is much less understood. In this study, we reveal the effects of atmospheric factors on nocturnal bird migration under adverse conditions during spring and autumn, based on one of the most detailed bird migration studies globally, using radar data from 13 deployments over a period of seven years (2014-2020) in the Levant region. Using ERA5 reanalysis data, we found that migratory birds maintain similar ground speeds in both autumn and spring migrations, but during spring, when encountering unfavourable winds, they put more effort into maintaining their travel speed by increasing self-powered airspeed by 18%. Moreover, we report for the first time that spring migrants showed less selectivity to wind conditions and migrated even under unfavourable headwind and crosswind conditions. Interestingly, we discovered that temperature was the most important weather parameter, such that warm weather substantially increased migration intensities in both seasons. Our results enhance our understanding of bird migration over the Levant region, one of the world's largest and most important migration flyways, and the factors controlling it. This information is essential for predicting bird migration, which-especially under the ongoing anthropogenic changes-is of high importance.

Bt corn and cotton planting may benefit peanut growers by reducing aflatoxin risk.

Decades of studies have shown that Bt corn, by reducing insect damage, has lower levels of mycotoxins (fungal toxins), such as aflatoxin and fumonisin, than conventional corn. We used crop insurance data to infer that this benefit from Bt crops extends to reducing aflatoxin risk in peanuts: a non-Bt crop. In consequence, we suggest that any benefit-cost assessment of how transgenic Bt crops affect food safety should not be limited to assessing those crops alone; because the insect pest control offered by Bt crops affects the food safety profile of other crops grown nearby. Specifically, we found that higher Bt corn and Bt cotton planting rates in peanut-growing areas of the United States were associated with lower aflatoxin risk in peanuts as measured by aflatoxin-related insurance claims filed by peanut growers. Drought-related insurance claims were also lower: possibly due to Bt crops' suppression of insects that would otherwise feed on roots, rendering peanut plants more vulnerable to drought. These findings have implications for countries worldwide where policies allow Bt cotton but not Bt food crops to be grown: simply planting a Bt crop may reduce aflatoxin and drought stress in nearby food crops, resulting in a safer food supply through an inter-crop "halo effect."

Extreme Humid-Heat Exposure and Mortality Among Patients Receiving Dialysis.

RATIONALE & OBJECTIVE: Exposure to extreme heat events has been linked to increased morbidity and mortality in the general population. Patients receiving maintenance dialysis may be vulnerable to greater risks from these events, but this is not well understood. We characterized the association of extreme heat events and the risk of death among patients receiving dialysis in the United States. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Data from the US Renal Data System were used to identify adults living in US urban settlements prone to extreme heat who initiated maintenance dialysis between 1997 and 2016. EXPOSURE: An extreme heat event, defined as a time-updated heat index (a humid-heat metric) exceeding 40.6°C for≥2 days or 46.1°C for≥1day. OUTCOME: Death. ANALYTICAL APPROACH: Cox proportional hazards regression to estimate the elevation in risk of death during a humid-heat event adjusted for age, sex, year of dialysis initiation, dialysis modality, poverty level, and climate region. Interactions between humid-heat and these same factors were explored. RESULTS: Among 945,251 adults in 245 urban settlements, the mean age was 63 years, and 44% were female. During a median follow-up period of 3.6 years, 498,049 adults were exposed to at least 1 of 7,154 extreme humid-heat events, and 500,025 deaths occurred. In adjusted models, there was an increased risk of death (hazard ratio 1.18 [95% CI, 1.15-1.20]) during extreme humid-heat exposure. The relative mortality risk was higher among patients living in the Southeast (P<0.001) compared with the Southwest. LIMITATIONS: Possibility of exposure misclassification, did not account for land use and air pollution co-exposures. CONCLUSIONS: This study suggests that patients receiving dialysis face an increased risk of death during extreme humid-heat exposure. PLAIN-LANGUAGE SUMMARY: Patients who receive dialysis are vulnerable to extreme weather events, and rising global temperatures may bring more frequent extreme heat events. We sought to determine whether extreme heat exposure was associated with an increased risk of death in urban-dwelling patients receiving dialysis across the United States. We found that people receiving dialysis were more likely to die during extreme humid-heat events, defined by a heat index exceeding 40.6°C (105°F) for≥2 days or 46.1°C (115°F) for≥1day. These findings inform the nephrology community about the potential importance of protecting patients receiving maintenance dialysis from the risks associated with extreme heat.

Zoonotic spillover and extreme weather events drive the global outbreaks of airborne viral emerging infectious diseases.

Outbreaks of airborne viral emerging infectious diseases (EIDs) cause an increasing burden on global public health, particularly with a backdrop of intensified climate change. However, infection sources and drivers for outbreaks of airborne viral EIDs remain unknown. Here, we aim to explore the driving mechanisms of outbreaks based on the one health perspective. Outbreak information for 20 types of airborne viral EIDs was collected from the Global Infectious Disease and Epidemiology Network database and a systematic literature review. Four statistically significant and high-risk spatiotemporal clusters for airborne viral EID outbreaks were identified globally using multivariate scan statistic tests. There were 112 outbreaks with clear infection sources, and zoonotic spillover was the most common source (95.54%, 107/112). Since 1970, the majority of outbreaks occurred in healthcare facilities (24.82%), followed by schools (17.93%) and animal-related settings (15.93%). Significant associations were detected between the number of earthquakes, storms, duration of floods, and airborne viral EIDs' outbreaks using a case-crossover study design and multivariable conditional logistic regression. These findings implied that zoonotic spillover and extreme weather events are driving global outbreaks of airborne viral EIDs, and targeted prevention and control measures should be made to reduce the airborne viral EIDs burden.

Extremes of snow and temperature affect patterns of genetic diversity and differentiation in the alpine butterfly Parnassius smintheus.

Weather is an important short-term, local driver of population size and dispersal, which in turn contribute to patterns of genetic diversity and differentiation within species. Climate change is leading to greater weather variability and more frequent extreme weather events. While the effects of long-term and broad-scale mean climate conditions on genetic variation are well studied, our understanding of the effects of weather variability and extreme conditions on genetic variation is less developed. We assessed the influence of temperature and snow depth on genetic diversity and differentiation of populations of the alpine butterfly, Parnassius smintheus. We examined the relationships between a suite of variables, including those representing extreme conditions, and population-level genetic diversity and differentiation across 1453 single nucleotide polymorphisms, using both linear and gravity models. We additionally examined effects of land cover variables known to influence dispersal and gene flow in this species. We found that extreme low temperature events and the lowest recorded mean snow depth were significant predictors of genetic diversity. Extreme low temperature events, mean snow depth and land cover resistance were significant predictors of genetic differentiation. These results are congruent with known effects of early winter weather on population size and habitat connectivity on dispersal in P. smintheus. Our results demonstrate the potential for changes in the frequency or magnitude of extreme weather events to alter patterns of genetic diversity and differentiation.

Source-sink relationships during grain filling in wheat in response to various temperature, water deficit and nitrogen deficit regimes.

Grain filling is a critical process for improving crop production under adverse conditions caused by climate change. Here, using a quantitative method, we quantified post-anthesis source-sink relationships of a large data set to assess the contribution of remobilized pre-anthesis assimilates to grain growth for both biomass and nitrogen. The data set came from 13 years' semi-controlled field experimentation, in which six bread wheat genotypes were grown at plot scale under contrasting temperature, water, and nitrogen regimes. On average, grain biomass was ~10% higher than post-anthesis aboveground biomass accumulation across regimes and genotypes. Overall, the estimated relative contribution (%) of remobilized assimilates to grain biomass became increasingly significant with increasing stress intensity, ranging from virtually nil to 100%. This percentage was altered more by water and nitrogen regimes than by temperature, indicating the greater impact of water or nitrogen regimes relative to high temperatures under our experimental conditions. Relationships between grain nitrogen demand and post-anthesis nitrogen uptake were generally insensitive to environmental conditions, as there was always significant remobilization of nitrogen from vegetative organs, which helped to stabilize the amount of grain nitrogen. Moreover, variations in the relative contribution of remobilized assimilates with environmental variables were genotype-dependent. Our analysis provides an overall picture of post-anthesis source-sink relationships and pre-anthesis assimilate contributions to grain filling across (non-)environmental factors, and highlights that designing wheat adaption to climate change should account for complex multi-factor interactions.

Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish.

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5-28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage and geographic region: it was stronger in the juvenile life stage than in the adult life stage and in the northern sub-region than in the southern sub-region. Spatial synchrony of trout populations extended to 100-200 km but was much weaker than that of climate variables such as temperature, precipitation, and stream flow. Early life stage abundance changed over time due to annual variation in summer temperature and winter and spring stream flow conditions. Climate effects on abundance differed between sub-regions and among local populations within sub-regions, indicating multiple cross-scale interactions where climate interacted with local habitat to generate only a modest pattern of population synchrony over space. Overall, our analysis showed higher degrees of response heterogeneity of local populations to climate variation and consequently population asynchrony than previously shown based on analysis of individual, geographically restricted datasets. This response heterogeneity indicates that certain local segments characterized by population asynchrony and resistance to climate variation could represent unique populations of this iconic native coldwater fish that warrant targeted conservation. Advancing the conservation of this species can include actions that identify such priority populations and incorporate them into landscape-level conservation planning. Our approach is applicable to other widespread aquatic species sensitive to climate change.

A modest increase in fire weather overcomes resistance to fire spread in recently burned boreal forests.

Recently burned boreal forests have lower aboveground fuel loads, generating a negative feedback to subsequent wildfires. Despite this feedback, short-interval reburns (≤20 years between fires) are possible under extreme weather conditions. Reburns have consequences for ecosystem recovery, leading to enduring vegetation change. In this study, we characterize the strength of the fire-fuel feedback in recently burned Canadian boreal forests and the weather conditions that overwhelm resistance to fire spread in recently burned areas. We used a dataset of daily fire spread for thousands of large boreal fires, interpolated from remotely sensed thermal anomalies to which we associated local weather from ERA5-Land for each day of a fire's duration. We classified days with >3 ha of fire growth as spread days and defined burned pixels overlapping a fire perimeter ≤20 years old as short-interval reburns. Results of a logistic regression showed that the odds of fire spread in recently burned areas were ~50% lower than in long-interval fires; however, all Canadian boreal ecozones experienced short-interval reburning (1981-2021), with over 100,000 ha reburning annually. As fire weather conditions intensify, the resistance to fire spread declines, allowing fire to spread in recently burned areas. The weather associated with short-interval fire spread days was more extreme than the conditions during long-interval spread, but overall differences were modest (e.g. relative humidity 2.6% lower). The frequency of fire weather conducive to short-interval fire spread has significantly increased in the western boreal forest due to climate warming and drying (1981-2021). Our results suggest an ongoing degradation of fire-fuel feedbacks, which is likely to continue with climatic warming and drying.

Unravelling the role of tropical cyclones in shaping present species distributions.

Driven by climate change, tropical cyclones (TCs) are predicted to change in intensity and frequency through time. Given these forecasted changes, developing an understanding of how TCs impact insular wildlife is of heightened importance. Previous work has shown that extreme weather events may shape species distributions more strongly than climatic averages; however, given the coarse spatial and temporal scales at which TC data are often reported, the influence of TCs on species distributions has yet to be explored. Using TC data from the National Hurricane Center, we developed spatially and temporally explicit species distribution models (SDMs) to examine the role of TCs in shaping present-day distributions of Puerto Rico's 10 Anolis lizard species. We created six predictor variables to represent the intensity and frequency of TCs. For each occurrence of a species, we calculated these variables for TCs that came within 500 km of the center of Puerto Rico and occurred within the 1-year window prior to when that occurrence was recorded. We also included predictor variables related to landcover, climate, topography, canopy cover and geology. We used random forests to assess model performance and variable importance in models with and without TC variables. We found that the inclusion of TC variables improved model performance for the majority of Puerto Rico's 10 anole species. The magnitude of the improvement varied by species, with generalist species that occur throughout the island experiencing the greatest improvements in model performance. Range-restricted species experienced small, almost negligible, improvements but also had more predictive models both with and without the inclusion of TC variables compared to generalist species. Our findings suggest that incorporating data on TCs into SDMs may be important for modeling insular species that are prone to experiencing these types of extreme weather events.

Habitat alteration or climate: What drives the densities of an invading ungulate?

Anthropogenic habitat alteration and climate change are two well-known contributors to biodiversity loss through changes to species distribution and abundance; yet, disentangling the effects of these two factors is often hindered by their inherent confound across both space and time. We leveraged a contrast in habitat alteration associated with the jurisdictional boundary between two Canadian provinces to evaluate the relative effects of spatial variation in habitat alteration and climate on white-tailed deer (Odocoileus virginianus) densities. White-tailed deer are an invading ungulate across much of North America, whose expansion into Canada's boreal forest is implicated in the decline of boreal caribou (Rangifer tarandus caribou), a species listed as Threatened in Canada. We estimated white-tailed deer densities using 300 remote cameras across 12 replicated 50 km2 landscapes over 5 years. White-tailed deer densities were significantly lower in areas where winter severity was higher. For example, predicted deer densities declined from 1.83 to 0.35 deer/km2 when winter severity increased from the lowest value to the median value. There was a tendency for densities to increase with increasing habitat alteration; however, the magnitude of this effect was approximately half that of climate. Our findings suggest that climate is the primary driver of white-tailed deer populations; however, understanding the mechanisms underpinning this relationship requires further study of over-winter survival and fecundity. Long-term monitoring at the invasion front is needed to evaluate the drivers of abundance over time, particularly given the unpredictability of climate change and increasing prevalence of extreme weather events.

Subarctic winter warming promotes soil microbial resilience to freeze-thaw cycles and enhances the microbial carbon use efficiency.

Climate change is predicted to cause milder winters and thus exacerbate soil freeze-thaw perturbations in the subarctic, recasting the environmental challenges that soil microorganisms need to endure. Historical exposure to environmental stressors can facilitate the microbial resilience to new cycles of that same stress. However, whether and how such microbial memory or stress legacy can modulate microbial responses to cycles of frost remains untested. Here, we conducted an in situ field experiment in a subarctic birch forest, where winter warming resulted in a substantial increase in the number and intensity of freeze-thaw events. After one season of winter warming, which raised mean surface and soil (-8 cm) temperatures by 2.9 and 1.4°C, respectively, we investigated whether the in situ warming-induced increase in frost cycles improved soil microbial resilience to an experimental freeze-thaw perturbation. We found that the resilience of microbial growth was enhanced in the winter warmed soil, which was associated with community differences across treatments. We also found that winter warming enhanced the resilience of bacteria more than fungi. In contrast, the respiration response to freeze-thaw was not affected by a legacy of winter warming. This translated into an enhanced microbial carbon-use efficiency in the winter warming treatments, which could promote the stabilization of soil carbon during such perturbations. Together, these findings highlight the importance of climate history in shaping current and future dynamics of soil microbial functioning to perturbations associated with climate change, with important implications for understanding the potential consequences on microbial-mediated biogeochemical cycles.

Divergent ecological responses to typhoon disturbance revealed via landscape-scale acoustic monitoring.

Climate change is increasing the frequency, intensity, and duration of extreme weather events across the globe. Understanding the capacity for ecological communities to withstand and recover from such events is critical. Typhoons are extreme weather events that are expected to broadly homogenize ecological dynamics through structural damage to vegetation and longer-term effects of salinization. Given their unpredictable nature, monitoring ecological responses to typhoons is challenging, particularly for mobile animals such as birds. Here, we report spatially variable ecological responses to typhoons across terrestrial landscapes. Using a high temporal resolution passive acoustic monitoring network across 24 sites on the subtropical island of Okinawa, Japan, we found that typhoons elicit divergent ecological responses among Okinawa's diverse terrestrial habitats, as indicated by increased spatial variability of biological sound production (biophony) and individual species detections. This suggests that soniferous communities are capable of a diversity of different responses to typhoons. That is, spatial insurance effects among local ecological communities provide resilience to typhoons at the landscape scale. Even though site-level typhoon impacts on soundscapes and bird detections were not particularly strong, monitoring at scale with high temporal resolution across a broad spatial extent nevertheless enabled detection of spatial heterogeneity in typhoon responses. Further, species-level responses mirrored those of acoustic indices, underscoring the utility of such indices for revealing insight into fundamental questions concerning disturbance and stability. Our findings demonstrate the significant potential of landscape-scale acoustic sensor networks to capture the understudied ecological impacts of unpredictable extreme weather events.

Advances and knowledge gaps on climate change impacts on honey bees and beekeeping: A systematic review.

The Western honey bee Apis mellifera is a managed species that provides diverse hive products and contributing to wild plant pollination, as well as being a critical component of crop pollination systems worldwide. High mortality rates have been reported in different continents attributed to different factors, including pesticides, pests, diseases, and lack of floral resources. Furthermore, climate change has been identified as a potential driver negatively impacting pollinators, but it is still unclear how it could affect honey bee populations. In this context, we carried out a systematic review to synthesize the effects of climate change on honey bees and beekeeping activities. A total of 90 articles were identified, providing insight into potential impacts (negative, neutral, and positive) on honey bees and beekeeping. Interest in climate change's impact on honey bees has increased in the last decade, with studies mainly focusing on honey bee individuals, using empirical and experimental approaches, and performed at short-spatial (<10 km) and temporal (<5 years) scales. Moreover, environmental analyses were mainly based on short-term data (weather) and concentrated on only a few countries. Environmental variables such as temperature, precipitation, and wind were widely studied and had generalized negative effects on different biological and ecological aspects of honey bees. Food reserves, plant-pollinator networks, mortality, gene expression, and metabolism were negatively impacted. Knowledge gaps included a lack of studies at the apiary and beekeeper level, a limited number of predictive and perception studies, poor representation of large-spatial and mid-term scales, a lack of climate analysis, and a poor understanding of the potential impacts of pests and diseases. Finally, climate change's impacts on global beekeeping are still an emergent issue. This is mainly due to their diverse effects on honey bees and the potential necessity of implementing adaptation measures to sustain this activity under complex environmental scenarios.

La abeja occidental Apis mellifera es una especie manejada que proporciona diversos productos de la colmena y servicios de polinización, los cuales son cruciales para plantas silvestres y cultivos en todo el mundo. En distintos continentes se han registrado altas tasas de mortalidad, las cuales son atribuidas a diversos factores, como el uso de pesticidas, plagas, enfermedades y falta de recursos florales. Además, el cambio climático ha sido identificado como un potencial factor que afecta negativamente a los polinizadores, pero aún no está claro cómo podría afectar a las poblaciones de abejas melíferas. En este contexto, realizamos una revisión sistemática de la literatura disponible para sintetizar los efectos del cambio climático en las abejas melíferas y las actividades apícolas. En total, se identificaron 90 artículos que proporcionaron información sobre los posibles efectos (negativos, neutros y positivos) en las abejas melíferas y la apicultura. El interés por el impacto del cambio climático en las abejas melíferas ha aumentado en la última década, con estudios centrados principalmente en individuos de abejas melíferas, utilizando enfoques empíricos y experimentales y realizados a escalas espaciales (<10 km) y temporales (<5 años) cortas. Además, los análisis ambientales fueron basaron principalmente en datos a corto plazo (meteorológicos) y se concentraron sólo en algunos países. Variables ambientales como la temperatura, las precipitaciones y el viento fueron ampliamente estudiadas y tuvieron efectos negativos generalizados sobre distintos aspectos biológicos y ecológicos de las abejas melíferas. Además, las reservas alimenticias, las interacciones planta-polinizador, la mortalidad, la expresión génica y el metabolismo se vieron afectados negativamente. Entre los vacios de conocimiento cabe mencionar la falta de estudios a nivel de colmenar y apicultor, la escasez de estudios de predicción y percepción, la escasa representación de las grandes escalas espaciales y a mediano plazo, el déficit de análisis climáticos y la escasa comprensión de los impactos potenciales de plagas y enfermedades. Por último, las repercusiones del cambio climático en la apicultura mundial siguen siendo un tema emergente, que debe estudiarse en los distintos países. Esto se debe principalmente a sus diversos efectos sobre las abejas melíferas y a la necesidad potencial de aplicar medidas de adaptación para mantener esta actividad crucial en escenarios medioambientales complejos.