Quantifying relative importance: computing standardized effects in models with binary outcomes

Sample size and power calculations for causal mediation analysis: A Tutorial and Shiny App

When designing a study for causal mediation analysis, it is crucial to conduct a power analysis to determine the sample size required to detect the causal mediation effects with sufficient power. However, the development of power analysis methods for causal mediation analysis has lagged far behind. To fill the knowledge gap, I proposed a simulation-based method and an easy-to-use web application ( https://xuqin.shinyapps.io/CausalMediationPowerAnalysis/ ) for power and sample size calculations for regression-based causal mediation analysis. By repeatedly drawing samples of a specific size from a population predefined with hypothesized models and parameter values, the method calculates the power to detect a causal mediation effect based on the proportion of the replications with a significant test result. The Monte Carlo confidence interval method is used for testing so that the sampling distributions of causal effect estimates are allowed to be asymmetric, and the power analysis runs faster than if the bootstrapping method is adopted. This also guarantees that the proposed power analysis tool is compatible with the widely used R package for causal mediation analysis, mediation, which is built upon the same estimation and inference method. In addition, users can determine the sample size required for achieving sufficient power based on power values calculated from a range of sample sizes. The method is applicable to a randomized or nonrandomized treatment, a mediator, and an outcome that can be either binary or continuous. I also provided sample size suggestions under various scenarios and a detailed guideline of app implementation to facilitate study designs.

Causal moderated mediation analysis: Methods and software

Research questions regarding how, for whom, and where a treatment achieves its effect on an outcome have become increasingly valued in substantive research. Such questions can be answered by causal moderated mediation analysis, which assesses the heterogeneity of the mediation mechanism underlying the treatment effect across individual and contextual characteristics. Various moderated mediation analysis methods have been developed under the traditional path analysis/structural equation modeling framework. One challenge is that the definitions of moderated mediation effects depend on statistical models of the mediator and the outcome, and no solutions have been provided when either the mediator or the outcome is binary, or when the mediator or outcome model is nonlinear. In addition, it remains unclear to empirical researchers how to make causal arguments of moderated mediation effects due to a lack of clarifications of the underlying assumptions and methods for assessing the sensitivity to violations of the assumptions. This article overcomes the limitations by developing general definition, identification, estimation, and sensitivity analysis for causal moderated mediation effects under the potential outcomes framework. We also developed a user-friendly R package moderate.mediation ( https://cran.r-project.org/web/packages/moderate.mediation/index.html ) that allows applied researchers to easily implement the proposed methods and visualize the initial analysis results and sensitivity analysis results. We illustrated the application of the proposed methods and the package implementation with a re-analysis of the National Evaluation of Welfare-to-Work Strategies (NEWWS) Riverside data.

Effects of seagrass restoration on coastal fish abundance and diversity

Restoration is accelerating to reverse global declines of key habitats and recover lost ecosystem functions, particularly in coastal ecosystems. However, there is high uncertainty about the long-term capacity of restored ecosystems to provide habitat and increase biodiversity and the degree to which these ecosystem services are mediated by spatial and temporal environmental variability. We addressed these gaps by sampling fishes biannually for 5-7 years (2012-2018) at 16 sites inside and outside a rapidly expanding restored seagrass meadow in coastal Virginia (USA). Despite substantial among-year variation in abundance and species composition, seine catches in restored seagrass beds were consistently larger (6.4 times more fish, p < 0.001) and more speciose (2.6 times greater species richness, p < 0.001; 3.1 times greater Hill-Shannon diversity, p = 0.03) than seine catches in adjacent unvegetated areas. Catches were particularly larger during summer than autumn (p < 0.01). Structural equation modeling revealed that depth and water residence time interacted to control seagrass presence, leading to higher fish abundance and richness in shallow, well-flushed areas that supported seagrass. Together, our results indicate that seagrass restoration yields large and consistent benefits for many coastal fishes, but that restoration and its benefits are sensitive to the dynamic seascapes in which restoration is conducted. Consideration of how seascape-scale environmental variability affects the success of habitat restoration and subsequent ecosystem function will improve restoration outcomes and the provisioning of ecosystem services.

Traffic prediction in SDN for explainable QoS using deep learning approach

The radical increase of multimedia applications such as voice over Internet protocol (VOIP), image processing, and video-based applications require better quality of service (QoS). Therefore, traffic Predicting and explaining the prediction models is essential. However, elephant flows from those applications still needs to be improved to satisfy Internet users. Elephant flows lead to network congestion, resulting in packet loss, delay and inadequate QoS delivery. Recently, deep learning models become a good alternative for real-time traffic management. This research aims to design a traffic predicting model that can identify elephant flows to prevent network congestion in advance. Thus, we are motivated to develop elephant flow prediction models and explain those models explicitly for network administrators' use in the SDN network. H2O, Deep Autoencoder, and autoML predicting algorithms, including XGBoost, GBM and GDF, were employed to develop the proposed model. The performance of Elephant flow prediction models scored 99.97%, 99.99%, and 100% in validation accuracy of under construction error of 0.0003952, 0.001697, and 0.00000408 using XGBoost, GBM, and GDF algorithms respectively. The models were also explicitly explained using Explainable Artificial Intelligence. Accordingly, packet size and byte size attributes need much attention to detect elephant flows.

Organizational system thinking as a cognitive framework to meet climate targets

System thinking is a crucial cognitive framework to enable individual pro-environmental behavioral changes. Indeed, a large body of literature has shown a significant and positive association between individuals' system thinking capacities and perceptions of the threat posed by climate change. However, individual behavioral changes play a limited role in addressing climate change compared to large organizations involved in a significantly larger share of economic activities. Do organizations exhibit system thinking capacities? Here, we conjecture that system thinking is a cognitive framework observable at an aggregated group level and, therefore, organizations, not just individuals, can exhibit characteristic levels of system thinking. We conceptualize a definition of organizational system thinking and develop an empirical method to estimate it using a large body of textual data from business organizations. Then, we show that system thinking organizations are more likely to lower emissions and align them with the pathways required to meet the climate targets set by the Paris Agreement. Finally, we discussed the theoretical and policy implication of our study. Overall, our results suggest that system thinking is a relevant organization-level cognitive framework that can help organizations align their emissions with global climate targets.

Linking niche size and phylogenetic signals to predict future soil microbial relative abundances

Bacteria provide ecosystem services (e.g., biogeochemical cycling) that regulate climate, purify water, and produce food and other commodities, yet their distribution and likely responses to change or intervention are difficult to predict. Using bacterial 16S rRNA gene surveys of 1,381 soil samples from the Biomes of Australian Soil Environment (BASE) dataset, we were able to model relative abundances of soil bacterial taxonomic groups and describe bacterial niche space and optima. Hold out sample validated hypothetical causal networks (structural equation models; SEM) were able to predict the relative abundances of bacterial taxa from environmental data and elucidate soil bacterial niche space. By using explanatory SEM properties as indicators of microbial traits, we successfully predicted soil bacterial response, and in turn potential ecosystem service response, to near-term expected changes in the Australian climate. The methods developed enable prediction of continental-scale changes in bacterial relative abundances, and demonstrate their utility in predicting changes in bacterial function and thereby ecosystem services. These capabilities will be strengthened in the future with growing genome-level data.

The consequence of leaf life span to virus infection of herbivorous insects

Many herbivorous insects die of pathogen infections, though the role of plant traits in promoting the persistence of these pathogens as an indirect interaction is poorly understood. We tested whether winter leaf retention of bush lupines (Lupinus arboreus) promotes the persistence of a nucleopolyhedroviruses, thereby increasing the infection risk of caterpillars (Arctia virginalis) feeding on the foliage during spring. We also investigated whether winter leaf retention reduces viral exposure of younger caterpillars that live on the ground, as leaf retention prevents contaminated leaves from reaching the ground. We surveyed winter leaf retention of 248 lupine bush canopies across twelve sites and examined how it related to caterpillar infection risk, herbivory, and inflorescence density. We also manipulated the amount of lupine litter available to young caterpillars in a feeding experiment to emulate litterfall exposure in the field. Greater retention of contaminated leaves from the previous season increased infection rates of caterpillars in early spring. Higher infection rates reduced herbivory and increased plant inflorescence density by summer. Young caterpillars exposed to less litterfall were more likely to starve to death but less likely to die from infection, further suggesting foliage mediated exposure to viruses. We speculate that longer leaf life span may be an unrecognized trait that indirectly mediates top-down control of herbivores by facilitating epizootics.

Season and herbivore defence trait mediate tri-trophic interactions in tropical rainforest

Bottom-up effects from host plants and top-down effects from predators on herbivore abundance and distribution vary with physical environment, plant chemistry, predator and herbivore trait and diversity. Tri-trophic interactions in tropical ecosystems may follow different patterns from temperate ecosystems due to differences in above abiotic and biotic conditions. We sampled leaf-chewing larvae of Lepidoptera (caterpillars) from a dominant host tree species in a seasonal rainforest in Southwest China. We reared out parasitoids and grouped herbivores based on their diet preferences, feeding habits and defence mechanisms. We compared caterpillar abundance with leaf numbers ('bottom-up' effects) and parasitoid abundance ('top-down' effects) between different seasons and herbivore traits. We found bottom-up effects were stronger than top-down effects. Both bottom-up and top-down effects were stronger in the dry season than in the wet season, which were driven by polyphagous rare species and host plant phenology. Contrary to our predictions, herbivore traits did not influence differences in the bottom-up or top-down effects except for stronger top-down effects for shelter-builders. Our study shows season is the main predictor of the bottom-up and top-down effects in the tropics and highlights the complexity of these interactions.

Climate change and commercial fishing practices codetermine survival of a long-lived seabird

Understanding the environmental mechanisms that govern population change is a fundamental objective in ecology. Although the determination of how top-down and bottom-up drivers affect demography is important, it is often equally critical to understand the extent to which, environmental conditions that underpin these drivers fluctuate across time. For example, associations between climate and both food availability and predation risk may suggest the presence of trophic interactions that may influence inferences made from patterns in ecological data. Analytical tools have been developed to account for these correlations, while providing opportunities to ask novel questions regarding how populations change across space and time. Here, we combine two modeling disciplines-path analysis and mark-recapture-recovery models-to explore whether shifts in sea-surface temperatures (SSTs) influenced top-down (entanglement in fishing equipment) or bottom-up (forage fish production) population constraints over 60 years, and the extent to which these covarying processes shaped the survival of a long-lived seabird, the Royal tern. We found that hemispheric trends in SST were associated with variation in the amount of fish harvested along the Atlantic coast of North America and in the Caribbean, whereas reductions in forage fish production were mostly driven by shifts in the amount of fish harvested by commercial fisheries throughout the North Atlantic the year prior. Although the indirect (i.e., stock depletion) and direct (i.e., entanglement) impacts of commercial fishing on Royal tern mortality has declined over the last 60 years, increased SSTs during this time period has resulted in a comparable increase in mortality risk, which disproportionately impacted the survival of the youngest age-classes of Royal terns. Given climate projections for the North Atlantic, our results indicate that threats to Royal tern population persistence in the Mid-Atlantic will most likely be driven by failures to recruit juveniles into the breeding population.

Habitat detection, habitat choice copying or mating benefits: What drives conspecific attraction in a nomadic songbird?

Conspecific attraction during habitat selection is common among animals, but the ultimate (i.e. fitness-related) reasons for this behaviour often remain enigmatic. We aimed to evaluate the following three hypotheses for conspecific attraction during the breeding season in male Wood Warblers (Phylloscopus sibilatrix): the habitat detection hypothesis, the habitat choice copying hypothesis and the female preference hypothesis. These hypotheses make different predictions with respect to the relative importance of social and nonsocial information during habitat assessment, and whether benefits accrue as a consequence of aggregation. We tested the above hypotheses using a combination of a 2-year playback experiment, spatial statistics and mate choice models. The habitat detection hypothesis was the most likely explanation for conspecific attraction and aggregation in male Wood Warblers, based on the following results: (1) males were attracted to conspecific song playbacks, but fine-scale habitat heterogeneity was the better predictor of spatial patterns in the density of settling males; (2) male pairing success did not increase, but instead slightly decreased, as connectivity with other males (i.e. the number and proximity of neighbouring males) increased. Our study highlights how consideration of the process by which animals detect and assess habitat, together with the potential fitness consequences of resulting aggregations, are important for understanding conspecific attraction and spatially clustered distributions.

A Pleistocene legacy structures variation in modern seagrass ecosystems

Sustaining biodiversity and ecosystems in the long term depends on their adjustment to a rapidly changing climate. By characterizing the structure of the marine plant eelgrass and associated communities at 50 sites across its broad range, we found that eelgrass growth form and biomass retain a legacy of Pleistocene range shifts and genetic bottlenecks that in turn affect the biomass of algae and invertebrates that fuel coastal food webs. The ecosystem-level effects of this ancient evolutionary legacy are comparable to or stronger than effects of current environmental forcing, suggesting that this economically important ecosystem may be unable to keep pace with rapid global change.

Distribution of Earth’s biomes is structured by the match between climate and plant traits, which in turn shape associated communities and ecosystem processes and services. However, that climate–trait match can be disrupted by historical events, with lasting ecosystem impacts. As Earth’s environment changes faster than at any time in human history, critical questions are whether and how organismal traits and ecosystems can adjust to altered conditions. We quantified the relative importance of current environmental forcing versus evolutionary history in shaping the growth form (stature and biomass) and associated community of eelgrass (Zostera marina), a widespread foundation plant of marine ecosystems along Northern Hemisphere coastlines, which experienced major shifts in distribution and genetic composition during the Pleistocene. We found that eelgrass stature and biomass retain a legacy of the Pleistocene colonization of the Atlantic from the ancestral Pacific range and of more recent within-basin bottlenecks and genetic differentiation. This evolutionary legacy in turn influences the biomass of associated algae and invertebrates that fuel coastal food webs, with effects comparable to or stronger than effects of current environmental forcing. Such historical lags in phenotypic acclimatization may constrain ecosystem adjustments to rapid anthropogenic climate change, thus altering predictions about the future functioning of ecosystems.

Effects of Waterbird Herbivory on Dominant Perennial Herb Carex thunbergii in Shengjin Lake

Abundant food resources in riparian zones provide efficient foraging sites for waterbirds. Herbivory is a key ecosystem process that has widely recognized effects on primary production and vegetation structure and composition. However, there is limited understanding of impacts of waterbird herbivory on riparian zone vegetation. In this study, a bird exclosure experiment with five levels of foraging intensities (no foraging, very little foraging, light foraging, moderate foraging and heavy foraging) was set up in Shengjin Lake to study the effects of waterbird foraging on the community structure of sedge meadows and individual traits of the dominant plant Carex thunbergii. Foraging intensity had little effect on community structure. The dry mass of C. thunbergii decreased with the increasing foraging time. Waterbird foraging reduced leaf dry mass under heavy foraging by 27.7% and root dry mass by 45.6% compared to CK (no foraging). Waterbird foraging increased allocation to shoot growth but had a weak effect on elemental allocation of C. thunbergii. The foraging intensity significantly affected the morphological traits of C. thunbergii. The results of structural equation modeling showed that RSR (root: shoot ratio represents the ratio of dry mass) and RL (root length) are key traits in driving the dry mass decline in the presence of bird foraging. This study may contribute to a better understanding of the adaptability of perennial herb plants to waterbird foraging and maintain the healthy development of wetland ecosystems.

General guidance for custom-built structural equation models

Structural Equation Modelling (SEM) represents a quantitative methodology for specifying and evaluating causal network hypotheses. The application of SEM typically involves the use of specialised software packages that implement estimation procedures and automate model checking and the output of summary results. There are times when the specification details an investigator wishes to implement to represent their data relationships are not supported by available SEM packages. In such cases, it may be desirable to develop and evaluate SE models “by hand”, using specialised regression tools. In this paper, I demonstrate a general approach to custom-built applications of SEM. The approach illustrated can be used for a wide array of specialised applications of non-linear, multi-level and other custom specifications in SE models.

Exploring multitrophic interactions in oilseed rape fields reveals the prevailing role of Carabidae

In cropped fields, birds are often at the highest position in the food chain, feeding on pest arthropods and their intermediate predators in a process known as intraguild predation. The net effects of bird predation on phytophagous insect populations (feeding on plants) are difficult to predict without comprehensively describing prey-predator communities and their complex interplay. We sampled bird and arthropod communities in 30 oilseed rape fields in the spring of 2019 and 2020 in France. To assess the top-down control of arthropods by birds, we used a vertebrate exclusion experiment. Using a taxonomic and functional trait-based approach, we determined the direct and indirect influences of birds on arthropod predators and phytophagous insect populations in arable crops. We observed a negative relationship between the abundance of Carabidae and phytophagous insects but not with the other predator group suggesting the key role of Carabidae on phytophagous insects in agroecosystem. We found no statistical evidence of intraguild predation from birds toward intermediate predators. Despite the lack of overall effect of predator functional diversity on their prey, we highlighted the negative relationship between the functional complementarity (through functional evenness) of Carabidae and the abundance of phytophagous insects. This result suggests that functional complementarity between Carabidae species could help to reduce phytophagous insect populations. We analyzed the effect of agricultural practices on these multitrophic interactions, showing that pesticide intensity only had detrimental effects on Carabidae abundance, while the frequency of tillage did not affect the studied communities. Complementary indices used to depict communities are helpful to better understand the mechanisms underlying trophic relationships.

Altitude and latitude have different effects on population characteristics of the widespread plant Anthyllis vulneraria

Widespread plants may provide natural models for how population processes change with temperature and other environmental variables and how they may respond to global change. Similar changes in temperature can occur along altitudinal and latitudinal gradients, but hardly any study has compared the effects of the two types of gradients. We studied populations of Anthyllis vulneraria along a latitudinal gradient from Central Europe to the range limit in the North and an altitudinal gradient in the Alps from 500 m to the altitudinal limit at 2500 m, both encompassing a change in annual mean temperature of c. 11.5 °C. Plant size and reproduction decreased, but plant density increased along both gradients, indicating higher recruitment and demographic compensation among vital rates. Our results support the view that demographic compensation may be common in widespread species in contrast to the predictions of the abundant centre model of biogeography. Variation in temperature along the gradients had the strongest effects on most population characteristics, followed by that in precipitation, solar radiation, and soil nutrients. The proportion of plants flowering, seed set and seed mass declined with latitude, while the large variation in these traits along the altitudinal gradient was not related to elevation and covarying environmental variables like annual mean temperature. This suggests that it will be more difficult to draw conclusions about the potential impacts of future climate warming on plant populations in mountains, because of the importance of small-scale variation in environmental conditions.

Species richness is more important for ecosystem functioning than species turnover along an elevational gradient

Many experiments have shown that biodiversity enhances ecosystem functioning. However, we have little understanding of how environmental heterogeneity shapes the effect of diversity on ecosystem functioning and to what extent this diversity effect is mediated by variation in species richness or species turnover. This knowledge is crucial to scaling up the results of experiments from local to regional scales. Here we quantify the diversity effect and its components-that is, the contributions of variation in species richness and species turnover-for 22 ecosystem functions of microorganisms, plants and animals across 13 major ecosystem types on Mt Kilimanjaro, Tanzania. Environmental heterogeneity across ecosystem types on average increased the diversity effect from explaining 49% to 72% of the variation in ecosystem functions. In contrast to our expectation, the diversity effect was more strongly mediated by variation in species richness than by species turnover. Our findings reveal that environmental heterogeneity strengthens the relationship between biodiversity and ecosystem functioning and that species richness is a stronger driver of ecosystem functioning than species turnover. Based on a broad range of taxa and ecosystem functions in a non-experimental system, these results are in line with predictions from biodiversity experiments and emphasize that conserving biodiversity is essential for maintaining ecosystem functioning.

Sexual, allometric and forest cover effects on giant anteaters' movement ecology

Knowing the influence of intrinsic and environmental traits on animals’ movement is a central interest of ecology and can aid to enhance management decisions. The giant anteater (Myrmecophaga tridactyla) is a vulnerable mammal that presents low capacity for physiological thermoregulation and uses forests as thermal shelters. Here, we aim to provide reliable estimates of giant anteaters’ movement patterns and home range size, as well as untangle the role of intrinsic and environmental drivers on their movement. We GPS-tracked 19 giant anteaters in Brazilian savannah. We used a continuous-time movement model to estimate their movement patterns (described by home range crossing time, daily distance moved and directionality), and provide an autocorrelated kernel density estimate of home range size. Then, we used mixed structural equations to integratively model the effects of sex, body mass and proportion of forest cover on movement patterns and home range size, considering the complex net of interactions between these variables. Male giant anteaters presented more intensive space use and larger home range than females with similar body mass, as it is expected in polygynous social mating systems. Males and females increased home range size with increasing body mass, but the allometric scaling of intensity of space use was negative for males and positive for females, indicating different strategies in search for resources. With decreasing proportion of forest cover inside their home ranges, and, consequently, decreasing thermal quality of their habitat, giant anteaters increased home range size, possibly to maximize the chances of accessing thermal shelters. As frequency and intensity of extreme weather events and deforestation are increasing, effective management efforts need to consider the role of forests as an important thermal resource driving spatial requirements of this species. We highlight that both intrinsic and environmental drivers of animal movement should be integrated to better guide management strategies.

Impact of the COVID-19 pandemic on change in sleep patterns in an exploratory, cross-sectional online sample of 79 countries

OBJECTIVES

To describe changes in sleep patterns during the coronavirus disease 2019 (COVID-19) pandemic, develop profiles according to these patterns, and assess sociodemographic, economic, COVID-19 related, and sleep and mental health factors associated with these profiles.

DESIGN, SETTING, AND PARTICIPANTS

A 25-minute online survey was distributed worldwide through social media from 5/21/2020 to 7/1/2020.

MEASUREMENTS

Participants reported sociodemographic/economic information, the impact of the pandemic on major life domains, insomnia and depressive symptoms, and changes in sleep midpoint, time-in-bed, total sleep time (TST), sleep efficiency (SE), and nightmare and nap frequency from prior to during the pandemic. Sleep pattern changes were subjected to latent profile analysis. The identified profiles were compared to one another on all aforementioned factors using probit regression analyses.

RESULTS

The sample of 991 participants (ages: 18-80 years; 72.5% women; 60.3% residing outside of the United States) reported significantly delayed sleep midpoint, reductions in TST and SE, and increases in nightmares and naps. Over half reported significant insomnia symptoms, and almost two-thirds reported significant depressive symptoms. Latent profile analysis revealed 4 sleep pattern change profiles that were significantly differentiated by pre-pandemic sleep patterns, gender, and various COVID-19-related impacts on daily living such as severity of change in routines, and family stress and discord.

CONCLUSIONS

In an international online sample, poor sleep and depressive symptoms were widespread, and negative shifts in sleep patterns from pre-pandemic patterns were common. Differences in sleep pattern response to the COVID-19 crisis suggest potential and early targets for behavioral sleep health interventions.

Synergistic Effects of Rooted Aquatic Vegetation and Drift Wrack on Ecosystem Multifunctionality

Ecosystem multifunctionality is an increasingly popular concept used to approximate multifaceted ecosystem functioning, which in turn may help advance ecosystem-based management. However, while experimental studies have shown a positive effect of diversity on multifunctionality, observational studies from natural systems—particularly aquatic—are scarce. Here, we tested the relative importance of species richness and cover of rooted aquatic vegetation, as well as cover of the loose-lying form of the macroalgae bladderwrack (Fucus vesiculosus), for ecosystem multifunctionality in shallow bays along the western Baltic Sea coast. We estimated multifunctionality based on four indicators of functions that support ecosystem services: recruitment of large predatory fish, grazer biomass, inverted ‘nuisance’ algal biomass, and water clarity. Piecewise path analysis showed that multifunctionality was driven by high cover of rooted aquatic vegetation and bladderwrack, particularly when the two co-occurred. This synergistic effect was nearly three times as strong as a negative effect of land-derived nitrogen loading. Species richness of aquatic vegetation indirectly benefitted multifunctionality by increasing vegetation cover. Meanwhile, high bladderwrack cover tended to decrease vegetation species richness, indicating that bladderwrack has both positive and negative effects on multifunctionality. We conclude that managing for dense and diverse vegetation assemblages may mitigate effects of anthropogenic pressures (for example, eutrophication) and support healthy coastal ecosystems that provide a range of benefits. To balance the exploitation of coastal ecosystems and maintain their multiple processes and services, management therefore needs to go beyond estimation of vegetation cover and consider the diversity and functional types of aquatic vegetation.

Reduced magnitude and shifted seasonality of CO2 sink by experimental warming in a coastal wetland

Coastal wetlands have the highest carbon sequestration rate per unit area among all unmanaged natural ecosystems. However, how the magnitude and seasonality of the CO₂ sink in coastal wetlands will respond to future climate warming remains unclear. Here, based on measurements of ecosystem CO₂ fluxes in a field experiment in the Yellow River Delta, we found that experimental warming (i.e., a 2.4°C increase in soil temperature) reduced net ecosystem productivity (NEP) by 23.7% across two growing seasons of 2017-2018. Such a reduction in NEP resulted from the greater decrease in gross primary productivity (GPP) than ecosystem respiration (ER) under warming. The negative warming effect on NEP mainly occurred in summer (-43.9%) but not in autumn (+61.3%), leading to a shifted NEP seasonality under warming. Further analyses showed that the warming effects on ecosystem CO₂ exchange were mainly controlled by soil salinity and its corresponding impacts on species composition. For example, warming increased soil salinity (+35.0%), reduced total aboveground biomass (-9.9%), and benefited the growth of plant species with high salt tolerance and late peak growth. To the best of our knowledge, this study provides the first experimental evidence on the reduced magnitude and shifted seasonality of CO₂ exchange under climate warming in coastal wetlands. These findings underscore the high vulnerability of wetland CO₂ sink in coastal regions under future climate change.

Introducing the Adverse Ecosystem Service Pathway as a Tool in Ecological Risk Assessment

Soils provide numerous ecosystem services (ESs) such as food production and water purification. These ESs result from soil organism interactions and activities, which are supported by the soil physicochemical properties. Risk assessment for this complex system requires understanding the relationships among its components, both in the presence and absence of stressors. To better understand the soil ecosystem and how exposure to potentially toxic elements impact ESs, we developed a quantitative technique, the adverse ecosystem service pathway (AESP) model. We sampled 47 soils across Canada and analyzed them for properties that included pH and cation exchange capacity. We spiked the soils with a metal mixture and measured 15 soil processes representing five ESs. Using a Pearson correlation, we confirmed that proxies of ESs are linked to soil properties. t test results showed that, apart from soil enzyme activities (p > 0.05), the processes underlying ES proxies are significantly reduced in metal-impacted soils. Using soil properties as predictors of ES proxies, we developed AESP models: one for spiked and another for control soils. These models showed adverse effects on ESs in spiked soils, depicted as changes in partial correlation coefficients. The AESP model, therefore, can be an important tool to understand complex ecosystems and improve risk assessment.

Summarising and synthesising regression coefficients through systematic review and meta-analysis for improving hypertension prediction using metamodelling: protocol

INTRODUCTION

Hypertension is one of the most common medical conditions and represents a major risk factor for heart attack, stroke, kidney disease and mortality. The risk of progression to hypertension depends on several factors, and combining these risk factors into a multivariable model for risk stratification would help to identify high-risk individuals who should be targeted for healthy behavioural changes and/or medical treatment to prevent the development of hypertension. The risk prediction models can be further improved in terms of accuracy by using a metamodel updating technique where existing hypertension prediction models can be updated by combining information available in existing models with new data. A systematic review and meta-analysis will be performed of hypertension prediction models in order to identify known risk factors for high blood pressure and to summarise the magnitude of their association with hypertension.

METHODS AND ANALYSIS

MEDLINE, Embase, Web of Science, Scopus and grey literature will be systematically searched for studies predicting the risk of hypertension among the general population. The search will be based on two key concepts: hypertension and risk prediction. The summary statistics from the individual studies will be the regression coefficients of the hypertension risk prediction models, and random-effect meta-analysis will be used to obtain pooled estimates. Heterogeneity and publication bias will be assessed, along with study quality, which will be assessed using the Prediction Model Risk of Bias Assessment Tool checklist.

ETHICS AND DISSEMINATION

Ethics approval is not required for this systematic review and meta-analysis. We plan to disseminate the results of our review through journal publications and presentations at applicable platforms.

Frequent or scarce? Damage to flight-enabling body parts in bats (Chiroptera)

Bat wings are characterized by high endurance, and these mammals have developed a number of adaptations that protect them from falling into obstacles and potential injuries. However, in bat populations, there are individuals with visible fresh or healed injuries to the flight-enabling body parts. The aim of this research was to determine the differences in the occurrence of wing membrane damages among species of bats that differ in ecology and behavior. The study was conducted in southern and western Poland in the years 2000-2016 and included 3,525 individuals of six species: lesser horseshoe bat Rhinolopus hipposideros, Daubenton's bat Myotis daubentonii, Natterer's bat Myotis nattereri, greater mouse-eared bat Myotis myotis, western barbastelle Barbastella barbastellus, and brown long-eared bat Plecotus auritus. In all, 2.9% of the bats studied showed damage to the flight-enabling body parts. Natterer's bat was the species with the highest number of injured individuals (21.74%). The lowest number of injured individuals (0.3%) was found in the brown long-eared bat. The most frequently observed type of damage was loss of an edge of the wing membrane (29.3%). The bat species studied differed significantly in the occurrence and location of flight enabling body parts damages. Certain behavioral and ecological factors like foraging mode, foraging habitats and habitat types of bat species determine the number of wing and tail membrane damages.

Climate and plant controls on soil organic matter in coastal wetlands

Coastal wetlands are among the most productive and carbon-rich ecosystems on Earth. Long-term carbon storage in coastal wetlands occurs primarily belowground as soil organic matter (SOM). In addition to serving as a carbon sink, SOM influences wetland ecosystem structure, function, and stability. To anticipate and mitigate the effects of climate change, there is a need to advance understanding of environmental controls on wetland SOM. Here, we investigated the influence of four soil formation factors: climate, biota, parent materials, and topography. Along the northern Gulf of Mexico, we collected wetland plant and soil data across elevation and zonation gradients within 10 estuaries that span broad temperature and precipitation gradients. Our results highlight the importance of climate-plant controls and indicate that the influence of elevation is scale and location dependent. Coastal wetland plants are sensitive to climate change; small changes in temperature or precipitation can transform coastal wetland plant communities. Across the region, SOM was greatest in mangrove forests and in salt marshes dominated by graminoid plants. SOM was lower in salt flats that lacked vascular plants and in salt marshes dominated by succulent plants. We quantified strong relationships between precipitation, salinity, plant productivity, and SOM. Low precipitation leads to high salinity, which limits plant productivity and appears to constrain SOM accumulation. Our analyses use data from the Gulf of Mexico, but our results can be related to coastal wetlands across the globe and provide a foundation for predicting the ecological effects of future reductions in precipitation and freshwater availability. Coastal wetlands provide many ecosystem services that are SOM dependent and highly vulnerable to climate change. Collectively, our results indicate that future changes in SOM and plant productivity, regulated by cascading effects of precipitation on freshwater availability and salinity, could impact wetland stability and affect the supply of some wetland ecosystem services.