Global meta-analysis reveals overall higher nocturnal than diurnal activity in insect communities.

Insects sustain key ecosystem functions, but how their activity varies across the day-night cycle and the underlying drivers are poorly understood. Although entomologists generally expect that more insects are active at night, this notion has not been tested with empirical data at the global scale. Here, we assemble 331 quantitative comparisons of the abundances of insects between day and night periods from 78 studies worldwide and use multi-level meta-analytical models to show that insect activity is on average 31.4% (CI: -6.3%-84.3%) higher at night than in the day. We reveal diel preferences of major insect taxa, and observe higher nocturnal activity in aquatic taxa than in terrestrial ones, as well as in warmer environments. In a separate analysis of the small subset of studies quantifying diel patterns in taxonomic richness (31 comparisons from 13 studies), we detect preliminary evidence of higher nocturnal richness in tropical than temperate communities. The higher overall (but variable) nocturnal activity in insect communities underscores the need to address threats such as light pollution and climate warming that may disproportionately impact nocturnal insects.

Environmental effects and their impact on yield in adjacent experimental plots of high-stem and short-stem wheat varieties.

BACKGROUND: In regional wheat trials, when short-stem wheat varieties and high-stem wheat varieties are planted adjacent to each other in small plots, changes in their marginal plot environment can lead to bias in yield evaluation. Currently, there is no relevant research revealing the degree of their mutual influence. RESULTS: In a regional wheat experiment, when high-stem wheat varieties and short-stem wheat varieties were planted adjacent to one another, there was no significant change in soil temperature or humidity in the high-stem wheat variety experimental plot from November to May compared to the control plot, while the soil humidity in the short-stem wheat variety experimental plot was greater than that in the control plot. In May, the soil temperature of the short-stem wheat varieties in the experimental plot was lower than that in the control plot. Illumination of the wheat canopy in the high-stem wheat variety experimental plot had a significant positive effect in April and May, while illumination of the wheat canopy in the short-stem wheat variety experimental plot had a negative effect. The chlorophyll fluorescence parameters of flag leaves in the high-stem wheat variety experimental plots showed an overall increasing trend, while the chlorophyll fluorescence parameters of flag leaves in the experimental plots of short-stem wheat varieties showed a decreasing trend. The analysis of the economic yield, biological yield, and yield factors in each experimental plot revealed that the marginal effects of the economic yield and 1000-grain weight were particularly significant and manifested as positive effects in the high-stem wheat variety experimental plot and as negative effects in the short-stem wheat variety experimental plot. The economic yield of the high-stem wheat variety experimental plot was significantly greater than that of the control plot, the economic yield of the short-stem wheat variety experimental plot was significantly lower than that of the control plot, and the economic yield of the high-stem experimental plot was significantly greater than that of the short-stem experimental plot. When the yield of the control plot of the high-stem wheat varieties was compared to that of the control plot of the short-stem wheat varieties, the yield of the control plot of the short-stem wheat varieties was significantly greater than that of the control plot of the high-stem wheat varieties. CONCLUSIONS: Based on these findings, it is concluded that plots with high-stem and short-stem wheat varieties are adjacent in regional wheat trials, the plots of high-stem wheat varieties are subject to marginal positive effects, resulting in a significant increase in economic yield; the plots of short-stem wheat varieties are subject to marginal negative effects, resulting in a decrease in economic yield. This study reveals the mutual influence mechanism of environment and yield with adjacent planting of high-stem and short-stem wheat varieties in regional wheat trials, providing a useful reference and guidance for optimizing the layout of regional wheat trials.

Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi.

The globally distributed marine alga Emiliania huxleyi has cooling effect on the Earth's climate. The population density of E. huxleyi is restricted by Nucleocytoviricota viruses, including E. huxleyi virus 201 (EhV-201). Despite the impact of E. huxleyi viruses on the climate, there is limited information about their structure and replication. Here, we show that the dsDNA genome inside the EhV-201 virion is protected by an inner membrane, capsid, and outer membrane. EhV-201 virions infect E. huxleyi by using fivefold vertices to bind to and fuse the virus' inner membrane with the cell plasma membrane. Progeny virions assemble in the cytoplasm at the surface of endoplasmic reticulum-derived membrane segments. Genome packaging initiates synchronously with the capsid assembly and completes through an aperture in the forming capsid. The genome-filled capsids acquire an outer membrane by budding into intracellular vesicles. EhV-201 infection induces a loss of surface protective layers from E. huxleyi cells, which enables the continuous release of virions by exocytosis.

Significant shifts in latitudinal optima of North American birds.

Changes in climate can alter environmental conditions faster than most species can adapt. A prediction under a warming climate is that species will shift their distributions poleward through time. While many studies focus on range shifts, latitudinal shifts in species' optima can occur without detectable changes in their range. We quantified shifts in latitudinal optima for 209 North American bird species over the last 55 y. The latitudinal optimum (m) for each species in each year was estimated using a bespoke flexible non-linear zero-inflated model of abundance vs. latitude, and the annual shift in m through time was quantified. One-third (70) of the bird species showed a significant shift in their optimum. Overall, mean peak abundances of North American birds have shifted northward, on average, at a rate of 1.5 km per year (±0.58 SE), corresponding to a total distance moved of 82.5 km (±31.9 SE) over the last 55 y. Stronger poleward shifts at the continental scale were linked to key species' traits, including thermal optimum, habitat specialization, and territoriality. Shifts in the western region were larger and less variable than in the eastern region, and they were linked to species' thermal optimum, habitat density preference, and habitat specialization. Individual species' latitudinal shifts were most strongly linked to their estimated thermal optimum, clearly indicating a climate-driven response. Displacement of species from their historically optimal realized niches can have dramatic ecological consequences. Effective conservation must consider within-range abundance shifts. Areas currently deemed "optimal" are unlikely to remain so.

Spatial versus spatio-temporal approaches for studying metacommunities: a multi-taxon analysis in Mediterranean and tropical temporary ponds.

Prior research on metacommunities has largely focused on snapshot surveys, often overlooking temporal dynamics. In this study, our aim was to compare the insights obtained from metacommunity analyses based on a spatial approach repeated over time, with a spatio-temporal approach that consolidates all data into a single model. We empirically assessed the influence of temporal variation in the environment and spatial connectivity on the structure of metacommunities in tropical and Mediterranean temporary ponds. Employing a standardized methodology across both regions, we surveyed multiple freshwater taxa in three time periods within the same hydrological year from multiple temporary ponds in each region. To evaluate how environmental, spatial and temporal influences vary between the two approaches, we used nonlinear variation partitioning analyses based on generalized additive models. Overall, this study underscores the importance of adopting spatio-temporal analytics to better understand the processes shaping metacommunities. While the spatial approach suggested that environmental factors had a greater influence, our spatio-temporal analysis revealed that spatial connectivity was the primary driver influencing metacommunity structure in both regions. Temporal effects were equally important as environmental effects, suggesting a significant role of ecological succession in metacommunity structure.

Vertical structural complexity of plant communities represents the combined effects of resource acquisition and environmental stress on the Tibetan Plateau.

The vertical structural complexity (VSC) of plant communities reflects the occupancy of spatial niches and is closely related to resource utilization and environmental adaptation. However, understanding the large-scale spatial pattern of VSC and its underlying mechanisms remains limited. Here, we systematically investigate 2013 plant communities through grid sampling on the Tibetan Plateau. VSC is quantified as the maximum plant height within a plot (Height-max), coefficient of variation of plant height (Height-var), and Shannon evenness of plant height (Height-even). Precipitation dominates the spatial variation in VSC in forests and shrublands, supporting the classic physiological tolerance hypothesis. In contrast, for alpine meadows, steppes, and desert grasslands in extreme environments, non-resource limiting factors (e.g., wide diurnal temperature ranges and strong winds) dominate VSC variation. Generally, with the shifting of climate from favorable to extreme, the effect of resource availability gradually decreases, but the effect of non-resource limiting factors gradually increases, and that the physiological tolerance hypothesis only applicable in favorable conditions. With the help of machine learning models, maps of VSC at 1-km resolution are produced for the Tibetan Plateau. Our findings and maps of VSC provide insights into macroecological studies, especially for adaptation mechanisms and model optimization.

Roles of Reactive Carbonyl Species (RCS) in Plant Response to Abiotic Stress.

Abiotic and biotic stress conditions lead to production of reactive carbonyl species (RCS) which are lipid peroxide derivatives and have detrimental effects on plant cells especially at high concentrations. There are several molecules that can be classified in RCS; among them, 4-hydroxy-(E)-2-nonenal (HNE) and acrolein are widely recognized and studied because of their toxicity. The toxicity mechanisms of RCS are well known in animals but their roles in plant systems especially signaling aspects in metabolism need to be addressed. This chapter focuses on the production mechanisms of RCS in plants as well as how plants scavenge and modify them to prevent irreversible damage in the cell. We aimed to get a comprehensive look at the literature to summarize the signaling roles of RCS in plant metabolism and their interaction with other signaling mechanisms such as highly recognized reactive oxygen species (ROS) signaling. Changing climate promotes more severe abiotic stress effects on plants which also decrease yield on the field. The effects of abiotic stress conditions on RCS metabolism are also gathered in this chapter including their signaling roles during abiotic stresses. Different methods of measuring RCS in plants are also presented in this chapter to draw more attention to the study of RCS metabolism in plants.

Can Mercury Influence Carbon Dioxide Levels? Implications for the Implementation of the Minamata Convention on Mercury.

The Paris Agreement and the Minamata Convention on Mercury are two of the most important environmental conventions being implemented concurrently, with a focus on reducing carbon and mercury emissions, respectively. The relation between mercury and carbon influences the interactions and outcomes of these two conventions. This perspective investigates the link between mercury and CO2, assessing the consequences and exploring the policy implications of this link. We present scientific evidence showing that mercury and CO2 levels are negatively correlated under natural conditions. As a result of this negative correlation, the CO2 level under the current mercury reduction scenario is predicted to be 2.4-10.1 ppm higher than the no action scenario by 2050, equivalent to 1.0-4.8 years of CO2 increase due to human activity. The underlying causations of this negative correlation are complex and need further research. Economic analysis indicates that there is a trade-off between the benefits and costs of mercury reduction actions. As reducing mercury emission may inadvertently undermine efforts to achieve climate goals, we advocate for devising a coordinated implementation strategy for carbon and mercury conventions to maximize synergies and reduce trade-offs.

Paleoclimate data assimilation with CLIMBER-X: An ensemble Kalman filter for the last deglaciation.

Using the climate model CLIMBER-X, we present an efficient method for assimilating the temporal evolution of surface temperatures for the last deglaciation covering the period 22000 to 6500 years before the present. The data assimilation methodology combines the data and the underlying dynamical principles governing the climate system to provide a state estimate of the system, which is better than that which could be obtained using just the data or the model alone. In applying an ensemble Kalman filter approach, we make use of the advances in the parallel data assimilation framework (PDAF), which provides parallel data assimilation functionality with a relatively small increase in computation time. We find that the data assimilation solution depends strongly on the background evolution of the decaying ice sheets rather than the assimilated temperatures. Two different ice sheet reconstructions result in a different deglacial meltwater history, affecting the large-scale ocean circulation and, consequently, the surface temperature. We find that the influence of data assimilation is more pronounced on regional scales than on the global mean. In particular, data assimilation has a stronger effect during millennial warming and cooling phases, such as the Bølling-Allerød and Younger Dryas, especially at high latitudes with heterogeneous temperature patterns. Our approach is a step toward a comprehensive paleo-reanalysis on multi-millennial time scales, including incorporating available paleoclimate data and accounting for their uncertainties in representing regional climates.

Density-dependent species interactions modulate alpine treeline shifts.

Species interactions such as facilitation and competition play a crucial role in driving species range shifts. However, density dependence as a key feature of these processes has received little attention in both empirical and modelling studies. Herein, we used a novel, individual-based treeline model informed by rich in situ observations to quantify the contribution of density-dependent species interactions to alpine treeline dynamics, an iconic biome boundary recognized as an indicator of global warming. We found that competition and facilitation dominate in dense versus sparse vegetation scenarios respectively. The optimal balance between these two effects was identified at an intermediate vegetation thickness where the treeline elevation was the highest. Furthermore, treeline shift rates decreased sharply with vegetation thickness and the associated transition from positive to negative species interactions. We thus postulate that vegetation density must be considered when modelling species range dynamics to avoid inadequate predictions of its responses to climate warming.

Clumped isotopes reveal relationship between mussel growth and river discharge.

Freshwater mussels preserve valuable information about hydrology, climate, and population dynamics, but developing seasonal chronologies can be problematic. Using clumped isotope thermometry, we produced high-resolution reconstructions of modern and historic (~ 1900) temperatures and δ18Owater from mussel shells collected from an impounded river, the Brazos in Texas, before and after damming. We also performed high-resolution growth band analyses to investigate relationships between mussel growth rate, rainfall, and seasonal temperature. Reconstructed δ18Owater and temperature vary little between the modern (3R5) and historic shell (H3R). However, a positive relationship between reconstructed δ18Owater and growth rate in H3R indicates that aside from diminished growth in winter, precipitation and flow rate are the strongest controls on mussel growth in both modern and pre-dam times. Overall, our results demonstrate (1) the impact, both positive and negative, of environmental factors such as flow alteration and temperature on mussel growth and (2) the potential for clumped isotopes in freshwater mussels as a paleohydrology and paleoclimate proxies in terrestrial environments.

Microbial evolution-An under-appreciated driver of soil carbon cycling.

Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.

Study on the outdoor thermal comfort of college students under different activity intensities in a high-altitude climate zone.

Introduction: Research on the outdoor thermal comfort (OTC) of a university campus is beneficial to the physical and mental health of college students. Methods: In this study, the OTC of students attending Tibet University in Lhasa, which experiences high-altitude cold climate conditions, under different activity intensities was studied using field measurements and a questionnaire survey. Results: With the increase in activity intensity, the comfort physiologically equivalent temperature (PET) value gradually increased in summer, while the comfortable PET value gradually decreased in winter. The most comfortable PET value is 17.6°C in summer and 11.5°C in winter. The neutral PET of Tibetan college students during outdoor activities in summer was 16.3°C, and the neutral PET of outdoor activities in winter was 12.1°C. Gender and ethnicity had different effects on thermal sensation under different activity intensities. Under vigorous-intensity activities, PET in winter and summer had the greatest influence on thermal sensation. The situation was different under moderate-intensity activity. PET had the greatest influence on thermal sensation in summer, and Tmrt had the greatest influence on thermal sensation in winter. Discussion: These findings provide a basis for an improved design of the outdoor environment under different outdoor activity intensities in high-altitude areas.

Uppermost global tree elevations are primarily limited by low temperature or insufficient moisture.

The impact of anthropogenic global warming has induced significant upward dispersal of trees to higher elevations at alpine treelines. Assessing vertical deviation from current uppermost tree distributions to potential treeline positions is crucial for understanding ecosystem responses to evolving global climate. However, due to data resolution constraints and research scale limitation, comprehending the global pattern of alpine treeline elevations and driving factors remains challenging. This study constructed a comprehensive quasi-observational dataset of uppermost tree distribution across global mountains using Google Earth imagery. Validating the isotherm of mean growing-season air temperature at 6.6 ± 0.3°C as the global indicator of thermal treeline, we found that around two-thirds of uppermost tree distribution records significantly deviated from it. Drought conditions constitute the primary driver in 51% of cases, followed by mountain elevation effect which indicates surface heat (27%). Our analyses underscore the multifaceted determinants of global patterns of alpine treeline, explaining divergent treeline responses to climate warming. Moisture, along with temperature and disturbance, plays the most fundamental roles in understanding global variation of alpine treeline elevation and forecasting alpine treeline response to ongoing global warming.

Infectious Diseases in a Changing Climate.

This JAMA Insights in the Climate Change and Health series discusses the importance of clinicians having awareness of changes in the geographic range, seasonality, and intensity of transmission of infectious diseases to help them diagnose, treat, and prevent these diseases.

Revealing legacy effects of extreme droughts on tree growth of oaks across the Northern Hemisphere.

Forests are undergoing increasing risks of drought-induced tree mortality. Species replacement patterns following mortality may have a significant impact on the global carbon cycle. Among major hardwoods, deciduous oaks (Quercus spp.) are increasingly reported as replacing dying conifers across the Northern Hemisphere. Yet, our knowledge on the growth responses of these oaks to drought is incomplete, especially regarding post-drought legacy effects. The objectives of this study were to determine the occurrence, duration, and magnitude of legacy effects of extreme droughts and how that vary across species, sites, and drought characteristics. The legacy effects were quantified by the deviation of observed from expected radial growth indices in the period 1940-2016. We used stand-level chronologies from 458 sites and 21 oak species primarily from Europe, north-eastern America, and eastern Asia. We found that legacy effects of droughts could last from 1 to 5 years after the drought and were more prolonged in dry sites. Negative legacy effects (i.e., lower growth than expected) were more prevalent after repetitive droughts in dry sites. The effect of repetitive drought was stronger in Mediterranean oaks especially in Quercus faginea. Species-specific analyses revealed that Q. petraea and Q. macrocarpa from dry sites were more negatively affected by the droughts while growth of several oak species from mesic sites increased during post-drought years. Sites showing positive correlations to winter temperature showed little to no growth depression after drought, whereas sites with a positive correlation to previous summer water balance showed decreased growth. This may indicate that although winter warming favors tree growth during droughts, previous-year summer precipitation may predispose oak trees to current-year extreme droughts. Our results revealed a massive role of repetitive droughts in determining legacy effects and highlighted how growth sensitivity to climate, drought seasonality and species-specific traits drive the legacy effects in deciduous oak species.

Land potential assessment and trend-analysis using 2000-2021 FAPAR monthly time-series at 250 m spatial resolution.

The article presents results of using remote sensing images and machine learning to map and assess land potential based on time-series of potential Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) composites. Land potential here refers to the potential vegetation productivity in the hypothetical absence of short-term anthropogenic influence, such as intensive agriculture and urbanization. Knowledge on this ecological land potential could support the assessment of levels of land degradation as well as restoration potentials. Monthly aggregated FAPAR time-series of three percentiles (0.05, 0.50 and 0.95 probability) at 250 m spatial resolution were derived from the 8-day GLASS FAPAR V6 product for 2000-2021 and used to determine long-term trends in FAPAR, as well as to model potential FAPAR in the absence of human pressure. CCa 3 million training points sampled from 12,500 locations across the globe were overlaid with 68 bio-physical variables representing climate, terrain, landform, and vegetation cover, as well as several variables representing human pressure including: population count, cropland intensity, nightlights and a human footprint index. The training points were used in an ensemble machine learning model that stacks three base learners (extremely randomized trees, gradient descended trees and artificial neural network) using a linear regressor as meta-learner. The potential FAPAR was then projected by removing the impact of urbanization and intensive agriculture in the covariate layers. The results of strict cross-validation show that the global distribution of FAPAR can be explained with an R2 of 0.89, with the most important covariates being growing season length, forest cover indicator and annual precipitation. From this model, a global map of potential monthly FAPAR for the recent year (2021) was produced, and used to predict gaps in actual vs. potential FAPAR. The produced global maps of actual vs. potential FAPAR and long-term trends were each spatially matched with stable and transitional land cover classes. The assessment showed large negative FAPAR gaps (actual lower than potential) for classes: urban, needle-leave deciduous trees, and flooded shrub or herbaceous cover, while strong negative FAPAR trends were found for classes: urban, sparse vegetation and rainfed cropland. On the other hand, classes: irrigated or post-flooded cropland, tree cover mixed leaf type, and broad-leave deciduous showed largely positive trends. The framework allows land managers to assess potential land degradation from two aspects: as an actual declining trend in observed FAPAR and as a difference between actual and potential vegetation FAPAR.

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To reveal the key factors influencing vegetation productivity in sandy lands, we conducted a comprehensive analysis of vegetation productivity on regional scale, pixel scale, and plot scale of the sandy lands in northwes-tern Liaoning Province, based on soil physicochemical data, topographical data, climate data, and the intrinsic characteristics of vegetation. On the regional scale, we established a random forest model to explore the impact of topographical factors, climate factors, and vegetation characteristics on vegetation productivity. On the pixel scale, we performed a correlation analysis between vegetation cover and climate factors. On the plot scale, we combined the physicochemical properties of 234 soil samples with topographical factors and vegetation characteristics, and utilized the random forest model to calculate the importance values of each factor. The results showed that soil nutrients could explain 24.8% of the spatial variation in net primary productivity when other factors were excluded. When introducing topographical factors into the model, the model could explain 40% variation of net primary productivity. When further incorporating fractional vegetation coverage and leaf area index into the model, the model could explain 72.8% variation of net primary productivity. Our findings suggested that fractional vegetation coverage and leaf area index were the most influential factors affecting vegetation productivity in this area. Topographical factors ranked second, followed by climate factors, which had a relatively small impact.

Distribution and protection of Thesium chinense Turcz. under climate and land use change.

Wild medicinal plants are prominent in the field of Traditional Chinese Medicine (TCM), but their availability is being impacted by human activities and ecological degradation in China. To ensure sustainable use of these resources, it is crucial to scientifically plan areas for wild plant cultivation. Thesium chinense, a known plant antibiotic, has been overharvested in recent years, resulting in a sharp reduction in its wild resources. In this study, we employed three atmospheric circulation models and four socio-economic approaches (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to investigate the primary environmental factors influencing the distribution of T. chinense. We also examined changes in its suitable area using the Biomod2 package. Additionally, we utilized the PLUS model to project and analyze future land use changes in climate-stable regions for T. chinense. Our planning for wild tending areas of T. chinense was facilitated by the ZONATION software. Over the next century, the climate-stable regions for T. chinense in China is approximately 383.05 × 104 km2, while the natural habitat in this region will progressively decline. Under the current climate conditions, about 65.06% of the habitats in the high suitable areas of T. chinense are not affected by future land use changes in China. Through hotspot analysis, we identified 17 hotspot cities as ideal areas for the wild tending of T. chinense, including 6 core hotspot cities, 6 sub-hotspot cities, and 5 fringe hotspot cities. These findings contribute to a comprehensive research framework for the cultivation planning of T. chinense and other medicinal plants.

Weather or not-Global climate databases: Reliable on tropical mountains?

Global, spatially interpolated climate datasets such as WorldClim and CHELSA, widely used in research, are based on station data, which are rare in tropical mountains. However, such biodiversity hotspots are of high ecological interest and require accurate data. Therefore, the quality of such gridded datasets needs to be assessed. This poses a kind of dilemma, as proving the reliability of these potentially weakly modelled data is usually not possible due to the lack of stations. Using a unique climate dataset with 170 stations, mainly from the montane and alpine zones of sixteen mountains in Tanzania including Kilimanjaro, we show that the accuracy of such datasets is very poor. Not only is the maximum amount of mean annual precipitation drastically underestimated (partly more than 50%), but also the elevation of the precipitation maximum deviates up to 850m. Our results show that, at least in tropical regions, they should be used with greater caution than before.