Phosphorus resource partitioning underpins diversity patterns and assembly processes of microbial communities in plateau karst lakes

Eutrophication triggered by internal phosphorus (P) poses a substantial threat to the biodiversity of organisms in freshwater ecosystems. However, little is known about the linkages between P resource partitioning and microbial succession, especially in karst sediments. Here, we studied the diversity patterns and assembly processes of bacterial and archaeal communities in sediment cores from two historically hyper-eutrophicated karst lakes, Hongfeng Lake and Aha Lake, and investigated the relative contribution of P fractions to them. Our null and neutral models consistently indicated that bacterial and archaeal community assembly was judged to be deterministic rather than stochastic. We found a monotonically decreasing pattern for bacterial Shannon diversity toward deep sediments in Aha Lake, but U- or hump-shaped patterns for archaea in Hongfeng and Aha Lakes. Intriguingly, the community dissimilarity Bray-Curtis of bacteria and archaea consistently increased with increasing depth distance, with slopes of 0.0080 and 0.0069 in Hongfeng Lake and 0.0078 and 0.0087 in Aha Lake, respectively. Such cross-taxon congruence was well-supported by equivalent ecological processes (i.e., environmental selection). For bacteria and archaea, Shannon diversity was primarily affected by the total P (TP) fractions such as the loosely adsorbed TP or calcium-bound TP and sediment TP. Their community composition was significantly (P < 0.05) affected by calcium-bound inorganic P (Pi), loosely adsorbed Pi and reductant-soluble Pi. Although sediment properties were important, bacterial and archaeal diversity or community composition were well-explained by the Pi fractions, with high direct or indirect effects. In particular, Pi fractions exhibited stronger effects on bacterial and archaeal characteristics than organic P fractions. Taken together, our study provides novel insights into the ecological importance of P resource partitioning to microbial succession, which has crucial implications for disentangling the biogeochemical processes of P cycling in aquatic ecosystems.

The impact of anthropogenic pressures on microbial diversity and river multifunctionality relationships on a global scale

Conserving biodiversity is crucial for maintaining essential ecosystem functions, as indicated by the positive relationships between biodiversity and ecosystem functioning. However, the impacts of declining biodiversity on ecosystem functions in response to mounting human pressures remain uncertain. This uncertainty arises from the complexity of trade-offs among human activities, climate change, river properties, and biodiversity, which have not been comprehensively addressed collectively. Here, we provide evidence that river biodiversity was significantly and positively associated with multifunctionality and contributed to key ecosystem functions such as microbially driven water purification, leaf litter decomposition and pathogen control. However, human pressure led to abrupt changes in microbial diversity and river multifunctionality relationships at a human pressure value of 0.5. In approximately 30 % (N = 58) of countries globally, the ratio of area above this threshold exceeded the global average (∼11 %), especially in Europe. Results show that human pressure affected ecosystem functions through direct effects and interactive effects. We provide more direct evidence that the nonadditive effects triggered by prevailing human pressure impact the multifunctionality of rivers globally. Under high levels of human stress, the beneficial effects of biodiversity on nutrient cycling, carbon storage, gross primary productivity, leaf litter decomposition, and pathogen control tend to diminish. Our findings highlight that considering interactions between human pressure and local abiotic and biotic factors is key for understanding the fate of river ecosystems under climate change and increasing human pressure.

Incorporating biotic interactions to better model current and future vegetation of the maritime Antarctic

Maritime Antarctica's harsh abiotic conditions forged simple terrestrial ecosystems, mostly constituted of bryophytes, lichens, and vascular plants. Though biotic interactions are, together with abiotic factors, thought to help shape this ecosystem, influencing species' distribution and, indirectly, mediating their response to climate, the importance of these interactions is still fairly unknown. We modeled current and future abundance patterns of bryophytes, lichens, and vascular plants, accounting for biotic interactions and abiotic drivers, along a climatic gradient in maritime Antarctica. The influence of regional climate and other drivers was modeled using structural equation models, with and without biotic interactions. Models with biotic interactions performed better; the one offering higher ecological support was used to estimate current and future spatial distributions of vegetation. Results suggest that plants are confined to lower elevations, negatively impacting bryophytes and lichens, whereas at higher elevations both climate and other drivers influence bryophytes and lichens. Our findings strongly support the use of biotic interactions to predict the spatial distribution of Antarctic vegetation.

The structure of bacteria-fungi bipartite networks along elevational gradients in contrasting climates

Climate change is altering species distribution and modifying interactions in microbial communities. Understanding microbial community structure and their interactions is crucial to interpreting ecosystem responses to climate change. Here, we examined the assemblages of stream bacteria and fungi, and the associations between the two groups along elevational gradients in two regions with contrasting precipitation and temperature, that is the Galong and Qilian mountains of the Tibetan Plateau. In the wetter and warmer region, the species richness significantly increased and decreased with elevation for bacteria and fungi, respectively, while were nonsignificant in the drier and colder region. Their bipartite network structure was also different by showing significant increases in connectance and nestedness towards higher elevations only in the wetter and warmer region. In addition, these correlation network structure generally exhibited similar positive association with species richness in the wetter and warmer region and the drier and colder region. In the wetter and warmer region, climatic change along elevation was more important in determining connectance and nestedness, whereas microbial species richness exerted a stronger influence on network structure and robustness in the drier and colder region. These findings indicate substantial forthcoming changes in microbial diversity and network structure in warming climates, especially in wetter and warmer regions on Earth, advancing the understanding of microbial bipartite interactions' response to climate change.

Carbon and Nutrient Limitations of Microbial Metabolism in Xingkai Lake, China: Abiotic and Biotic Drivers

Microbial communities are crucial for water quality and biogeochemical cycling in freshwaters. Microbes secrete extracellular enzymes to decompose organic matter for their needs of nutrients and scarce elements. Yet, there is a lack of knowledge on microbial metabolic limitations in freshwaters, especially in lake sediments. Here, we examined the carbon, nitrogen, and phosphorus-acquiring extracellular enzyme activities and the bacterial and fungal communities of 30 sediments across Xingkai Lake, the largest freshwater lake in Northeast Asia. We further analyzed the microbial metabolic limitations via extracellular enzyme stoichiometry and explored the direct and indirect effects of abiotic and biotic factors on the limitations. We found that microbial metabolisms were primarily limited by phosphorus in Xingkai Lake. For instance, microbial carbon and phosphorus limitations were closely correlated to abiotic factors like water depth, total dissolved solids, sediment total carbon, and conductivity. The metabolic limitations were also affected by biotic factors, such as showing positive relationships with the alpha and beta diversity of bacteria, and with the beta diversity of fungi. In addition, community compositions of bacteria and fungi were mainly correlated to abiotic factors such as total carbon and dissolved organic carbon, respectively. Collectively, microbial metabolic limitations were affected directly or indirectly by abiotic factors and microbial communities. Our findings indicate that microbial metabolic limitations are not only driven by bacteria and fungi but also by abiotic factors such as water depth and total nitrogen, and thus provide empirical evidence for effective management of freshwater lakes under climate warming and intensified human activities.

Deciphering the key factors affecting pesticide residue risk in vegetable ecosystem

Soil contamination, particularly from pesticide residues, presents a significant challenge to the sustainable development of agricultural ecosystems. Identifying the key factors influencing soil pesticide residue risk and implementing effective measures to mitigate their risks at the source are essential. Here, we collected soil samples and conducted a comprehensive survey among local farmers in the Three Gorges Reserve Area, a major agricultural production region in Southwest China. Subsequently, employing a dual analytical approach combining structural equation modeling (SEM) and random forest modeling (RFM), we examined the effects of various factors on pesticide residue accumulation in vegetable ecosystems. Our SEM analysis revealed that soil characteristics (path coefficient 0.85) and cultivation factor (path coefficient 0.84) had the most significant effect on pesticide residue risk, while the farmer factors indirectly influenced pesticide residues by impacting both cultivation factors and soil characteristics. Further exploration using RFM identified the three most influential factors contributing to pesticide residue risk as cation exchange capacity (CEC) (account for 18.84%), cultivation area (account for 14.12%), and clay content (account for 13.01%). Based on these findings, we carried out experimental trials utilizing Integrated Pest Management (IPM) technology, resulting in a significant reduction in soil pesticide residues and notable improvements in crop yields. Therefore, it is recommended that governmental efforts should prioritize enhanced training for vegetable farmers, promotion of eco-friendly plant protection methods, and regulation of agricultural environments to ensure sustainable development.

Effects of Micro-Topography and Vegetation on Soil Moisture on Fixed Sand Dunes in Tengger Desert, China

Soil moisture is a key factor in arid ecosystems, with local variations influenced by topography and vegetation. Understanding this relationship is crucial for combating desertification. Employing ANOVA, Mean Decrease Accuracy (MDA) analysis from random forest modeling and Structural Equation Modeling (SEM), this study investigates the distribution of soil moisture and its associations with topographic and vegetative factors across four micro-geomorphic units in the Tengger Desert, China. Significant heterogeneity in soil moisture across various layers and locations, including windward and leeward slopes and the tops and bottoms of dunes, was observed. Soil moisture generally increases from the surface down to 300 cm, with diminishing fluctuations at greater depths. Soil moisture peaks in the surface and middle layers on windward slopes and in deep layers at the bottom of dunes, exhibiting an initial rise and then a decline on windward slopes. Topographic (including slope direction and elevation difference) and vegetation (including shrub and herb coverage) factors significantly influence soil moisture across three depth layers. Topographic factors negatively affect soil moisture directly, whereas vegetation positively influences it indirectly, with shrub and herb abundance enhancing moisture levels. These insights inform ecological management and the formulation of soil moisture-conservation strategies in arid deserts. The study underscores customizing sand-binding vegetation to various micro-geomorphic dune units.

Dryland rock detention structures increase herbaceous vegetation cover and stabilize shrub cover over 10 years but do not directly affect soil fertility

Rock detention structures (RDS) such as check dams, gabions, and one rock dams are commonly used to mitigate erosion impacts in dryland ephemeral stream channels. RDS increase local water infiltration and floodplain connectivity, reduce sediment transport, and enhance vegetation growth and establishment. In addition to increasing overall vegetation cover, RDS may also buffer against a cycle of vegetation growth and collapse during years of extremely variable precipitation, helping to maintain stable cover. Although widely employed by land managers, success as reported in scientific literature varies, especially with regard to RDS effects on vegetation and soil fertility. We present the results of a 10-year field experiment in southeastern Arizona, USA, designed in collaboration with local land practitioners to measure local in-channel effects of RDS. Over 10 years, cover of herbaceous vegetation (forbs and grasses) doubled from 11 % to 22 % in channels treated with RDS, but did not significantly increase in untreated control channels. Shrub cover in treated channels was significantly less variable than in control channels over time. We analyzed the complex relationships between RDS, vegetation cover, and soil fertility using structural equation modeling (SEM), which represented conditions of the tenth year alone. SEM revealed that RDS did not directly affect soil fertility, as measured by total soil nitrogen, total soil carbon, soil organic matter, microbial richness, and potential nutrient cycling capacity. Notably, SEM did not yield the same trends as temporal monitoring, possibly because our structural equation models could not capture change over time. This discrepancy highlights the need for long-term, frequent monitoring of aboveground and belowground conditions to evaluate treatment success on a management scale. Overall, installing rock detention structures in ephemeral channels in arid and semiarid regions is a low-cost, feasible way to increase channel sediment aggradation, forb, and grass cover; stabilize shrub cover; and combat dryland degradation.

Bottom-up rather than top-down mechanisms determine mesocarnivore interactions in Norway

Interactions among coexisting mesocarnivores can be influenced by different factors such as the presence of large carnivores, land-use, environmental productivity, or human disturbance. Disentangling the relative importance of bottom-up and top-down processes can be challenging, but it is important for biodiversity conservation and wildlife management. The aim of this study was to assess how the interactions among mesocarnivores (red fox Vulpes vulpes, badger Meles meles, and pine marten Martes martes) were affected by large carnivores (Eurasian lynx Lynx lynx and wolf Canis lupus), land cover variables (proportion of agricultural land and primary productivity), and human disturbance, as well as how these top-down and bottom-up mechanisms were influenced by season. We analyzed 3 years (2018-2020) of camera trapping observations from Norway and used structural equation models to assess hypothesized networks of causal relationships. Our results showed that land cover variables were more strongly associated with mesocarnivore detection rates than large carnivores in Norway. This might be caused by a combination of low density of large carnivores in an unproductive ecosystem with strong seasonality. Additionally, detection rates of all mesocarnivores showed positive associations among each other, which were stronger in winter. The prevalence of positive interactions among predators might indicate a tendency to use the same areas and resources combined with weak interference competition. Alternatively, it might indicate some kind of facilitative relationship among species. Human disturbance had contrasting effects for different species, benefiting the larger mesocarnivores (red fox and badger) probably through food subsidization, but negatively affecting apex predators (wolf and lynx) and smaller mesocarnivores (pine marten). In a human-dominated world, this highlights the importance of including anthropogenic influences in the study of species interactions.

Using structural equation modeling to assess the genotoxic and mutagenic effects of heavy metal contamination in the freshwater ecosystems: A study involving Oreochromis niloticus in an urban river

Chemical pollutants represent a leading problem for aquatic ecosystems, as they can induce genetic, biochemical, and physiological changes in the species of these ecosystems, thus compromising their adaptability and survival. The Capibaribe River runs through the state of Pernambuco, located in Northeastern Brazil, and passes through areas of agricultural cultivation, densely populated cities, and industrial centers, primarily textiles. Despite its importance, few ecotoxicological studies have been conducted on its environment, and knowledge about pollution patterns and their effects on its biota is still being determined. The objective of this study was to evaluate the water quality and the damage supposed to be caused by pollutants on the DNA specimens of Nile tilapia (Oreochromis niloticus) obtained from seven strategic points of Capibaribe. Tilapia specimens and water were collected during the rainy and dry seasons from 2015 to 2017. The following characteristics were analyzed: physicochemical (six), metal concentration (seven), local pluviosity, micronuclei, and comet assay. The physicochemical and heavy metal analyses were exploratory, whereas the ecotoxicological analyses were hypothetical. To verify this hypothesis, we compared the groups of fish collected to the results of the micronuclei test and comet assay. We created a Structural Equation Model (SEM) to determine how each metal's micronuclei variables, damage index, pluviosity, and concentration were related. Our results demonstrated that the highest values for markers of genetic damage were detected at points with the highest heavy metal concentrations, especially iron, zinc, manganese, chromium, and cadmium. The SEM demonstrated that metals could explain the findings of the genotoxicity markers. Moreover, other pollutants, such as pesticides, should be considered, mainly where the river passes through rural areas. The results presented here demonstrate that the Capibaribe River has different degrees of contamination and confirm our hypothesis.

Chemodiversity of riverine dissolved organic matter: Effects of local environments and watershed characteristics

Riverine dissolved organic matter (DOM) is crucial to global carbon cycling and aquatic ecosystems. However, the geographical patterns and environmental drivers of DOM chemodiversity remain elusive especially in the waters and sediments of continental rivers. Here, we systematically analyzed DOM molecular diversity and composition in surface waters and sediments across 97 broadly distributed rivers using data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. We further examined the associations of molecular richness and composition with geographical, climatic, physicochemical variables, as well as the watershed characteristics. We found that molecular richness significantly decreased toward higher latitudes, but only in sediments (r = -0.24, p < 0.001). The environmental variables like precipitation and non-purgeable organic carbon showed strong associations with DOM molecular richness and composition. Interestingly, we identified that less-documented factors like watershed characteristics were also related to DOM molecular richness and composition. For instance, DOM molecular richness was positively correlated with the soil sand fraction for waters, while with the percentage of forest for sediments. Importantly, the effects of watershed characteristics on DOM molecular richness and composition were generally stronger in waters than sediments. This phenomenon was further supported by the fact that 11 out of 13 watershed characteristics (e.g., the percentages of impervious area and cropland) showed more positive than negative correlations with molecular abundance especially in waters. As the percentage of forest increased, there was a continuous accumulation of the compounds with higher molecular weight, aromaticity, and degree of unsaturation. In contrast, human activities accumulated the compounds with lower molecular weight and oxygenation, and higher bioavailability. Our findings imply that it may be possible to use a small set of broadly available data types to predict DOM molecular richness and composition across diverse river systems. Elucidation of mechanisms underlying these relationships will provide further enhancements to such predictions, especially when extrapolating to unsampled systems.

Plant invasion and naturalization are influenced by genome size, ecology and economic use globally

Human factors and plant characteristics are important drivers of plant invasions, which threaten ecosystem integrity, biodiversity and human well-being. However, while previous studies often examined a limited number of factors or focused on a specific invasion stage (e.g., naturalization) for specific regions, a multi-factor and multi-stage analysis at the global scale is lacking. Here, we employ a multi-level framework to investigate the interplay between plant characteristics (genome size, Grime's adaptive CSR-strategies and native range size) and economic use and how these factors collectively affect plant naturalization and invasion success worldwide. While our findings derived from structural equation models highlight the substantial contribution of human assistance in both the naturalization and spread of invasive plants, we also uncovered the pivotal role of species' adaptive strategies among the factors studied, and the significantly varying influence of these factors across invasion stages. We further revealed that the effects of genome size on plant invasions were partially mediated by species adaptive strategies and native range size. Our study provides insights into the complex and dynamic process of plant invasions and identifies its key drivers worldwide.

Decoupling the effects of air temperature change on soil erosion in Northeast China

Changes in the air temperature tend to indirectly affect soil erosion by influencing rainfall, vegetation growth, economic development, and agricultural activities. In this study, the partial least squares-structural equation model (PLS-SEM) was used to decouple the impacts of temperature change on soil erosion in Northeast China from 2001 to 2019, and the indirect effect of temperature change on the pathways of natural and socioeconomic factors was analyzed. The results showed that temperature increase in Northeast China caused an increase in soil erosion by increasing rainfall and promoting economic development. Under the pathway of natural factors, in spring, the promoting effect on soil erosion under the influence of temperature change on rainfall was greater than the inhibiting effect on soil erosion under by the influence of temperature change on vegetation. In summer, the opposite effect was observed. Under the pathway of natural factors, over time, the promoting effect of temperature increase on soil erosion increased by 22.7%. Under the pathway of socioeconomic factors, temperature change not only aggravated soil erosion by promoting economic development, but also indirectly increased investments in agriculture and water conservation by improving the economy, thus inhibiting soil erosion to a certain extent. Over time, the contribution of temperature change to soil erosion through socioeconomic pathway was reduced by 44.4%. When the pathway of natural factors is compared with that of socioeconomics factors, temperature change imposed a more notable effect on the change in soil erosion through the socioeconomic pathway, indicating that human activities are the driving factors with a greater effect on soil erosion. Based on this, reasonable human intervention is an important means to alleviate soil erosion aggravation caused by rising temperatures.

Movement ecology of an endangered mesopredator in a mining landscape

BACKGROUND

Efficient movement and energy expenditure are vital for animal survival. Human disturbance can alter animal movement due to changes in resource availability and threats. Some animals can exploit anthropogenic disturbances for more efficient movement, while others face restricted or inefficient movement due to fragmentation of high-resource habitats, and risks associated with disturbed habitats. Mining, a major anthropogenic disturbance, removes natural habitats, introduces new landscape features, and alters resource distribution in the landscape. This study investigates the effect of mining on the movement of an endangered mesopredator, the northern quoll (Dasyurus hallucatus). Using GPS collars and accelerometers, we investigate their habitat selection and energy expenditure in an active mining landscape, to determine the effects of this disturbance on northern quolls.

METHODS

We fit northern quolls with GPS collars and accelerometers during breeding and non-breeding season at an active mine site in the Pilbara region of Western Australia. We investigated broad-scale movement by calculating the movement ranges of quolls using utilisation distributions at the 95% isopleth, and compared habitat types and environmental characteristics within observed movement ranges to the available landscape. We investigated fine-scale movement by quolls with integrated step selection functions, assessing the relative selection strength for each habitat covariate. Finally, we used piecewise structural equation modelling to analyse the influence of each habitat covariate on northern quoll energy expenditure.

RESULTS

At the broad scale, northern quolls predominantly used rugged, rocky habitats, and used mining habitats in proportion to their availability. However, at the fine scale, habitat use varied between breeding and non-breeding seasons. During the breeding season, quolls notably avoided mining habitats, whereas in the non-breeding season, they frequented mining habitats equally to rocky and riparian habitats, albeit at a higher energetic cost.

CONCLUSION

Mining impacts northern quolls by fragmenting favoured rocky habitats, increasing energy expenditure, and potentially impacting breeding dispersal. While mining habitats might offer limited resource opportunities in the non-breeding season, conservation efforts during active mining, including the creation of movement corridors and progressive habitat restoration would likely be useful. However, prioritising the preservation of natural rocky and riparian habitats in mining landscapes is vital for northern quoll conservation.

Climatic zone effects of non-native plant invasion on CH4 and N2O emissions from natural wetland ecosystems

Plant invasion can significantly alter the carbon and nitrogen cycles of wetlands, which potentially affects the emission of greenhouse gases (GHGs). The extent of these effects can vary depending on several factors, including the species of invasive plants, their growth patterns, and the climatic conditions prevailing in the wetland. Understanding the global effects of plant invasion on the emission of methane (CH4) and nitrous oxide (N2O) is crucial for the climate-smart management of wetlands. Here, we performed a global meta-analysis of 207 paired case studies that quantified the effect of non-native plant invasion on CH4 and N2O emissions in tropical/sub-tropical (TS) and temperate (TE) wetlands. The average emission rate of CH4 from the TS wetlands increased significantly from 337 to 577 kg CH4 ha-1 yr-1 in areas where native plants had been displaced by invasive plants. Similarly, in TE wetlands, the emission rates increased from 211 to 299 kg CH4 ha-1 yr-1 following the invasion of alien plant species. The increase in CH4 emissions at invaded sites was attributed to the increase in plant biomass, soil organic carbon (SOC), and soil moisture (SM). The effects of plant invasion on N2O emissions differed between TS and TE wetlands in that there was no significant effect in TS wetlands, whereas the N2O emissions reduced in TE wetlands. This difference in N2O emissions between climate zones was attributed to the depletion of NH4+ and NO3- in soils and the lower soil temperature in temperate regions. Overall, plant invasion increased the global net CH4 emissions from natural wetlands by 10.54 Tg CH4 yr-1. However, there were variations in CH4 emissions across different climatic zones, indicated by a net increase in CH4 emissions, of 9.97 and 0.57 Tg CH4 yr-1 in TS and TE wetlands, respectively. These findings highlight that plant invasion not only strongly stimulates the emission of CH4 from TS wetlands, but also suppresses N2O emissions from TE wetlands. These novel insights immensely improve our current understanding of the effects of climatic zones on biogeochemical controlling factors that influence the production of greenhouse gases (GHGs) from wetlands following plant invasion. By analyzing the specific mechanisms by which invasive plants affect GHG emissions in different climatic zones, effective strategies can be devised to reduce GHG emissions and preserve wetland ecosystems.

Plant litter loss exacerbates drought influences on grasslands

Plant litter is known to affect soil, community, and ecosystem properties. However, we know little about the capacity of litter to modulate grassland responses to climate change. Using a 7-yr litter removal experiment in a semiarid grassland, here we examined how litter removal interacts with a 2-yr drought to affect soil environments, plant community composition, and ecosystem function. Litter loss exacerbates the negative impacts of drought on grasslands. Litter removal increased soil temperature but reduced soil moisture and nitrogen mineralization, which substantially increased the negative impacts of drought on primary productivity and the abundance of perennial rhizomatous graminoids. Moreover, complete litter removal shifted plant community composition from grass-dominated to forb-dominated and reduced species and functional group asynchrony, resulting in lower ecosystem temporal stability. Our results suggest that ecological processes that lead to reduction in litter, such as burning, grazing, and haying, may render ecosystems more vulnerable and impair the capacity of grasslands to withstand drought events.

EMDR for symptoms of depression, stress and burnout in health care workers exposed to COVID-19 (HARD): A study protocol for a trial within a cohort study

Background: Stressful events during a pandemic are a major cause of serious health problems, such as burnout, depression and posttraumatic stress disorder (PTSD) among health care workers (HCWs). During three years, HCWs, on the frontline to fight the COVID-19 pandemic, have been at an increased risk of high levels of stress, anxiety, depression, burnout and PTSD. Regarding potential psychological interventions, Eye Movement Desensitization & Reprocessing (EMDR) is a structured, strongly recommended therapy based on its well-known efficacy in reducing PTSD symptoms and anxiety.Objectives: This study, designed as a trial within a cohort (TwiC), aims to 1) estimate the prevalence of depression, burnout and PTSD in a sample of HCWs after experiencing the COVID-19 emergency (cohort part) and 2) assess the efficacy and acceptability of 'EMDR + usual care' for HCWs from the cohort who report significant psychological symptoms (trial part).Methods: The study, designed as a TwiC, consists of a prospective cohort study (n = 3000) with an embedded, pragmatic, randomized open-label superiority trial with two groups (n = 900). Participants included in the trial part are HCWs recruited for the cohort with significant symptoms on at least one psychological dimension (depression, burnout, PTSD) at baseline, 3 months or 6 months, determined by using the Patient Health Questionnaire (PHQ-9), Professional Quality of Life (ProQOL) scale, and PTSD Checklist for the DSM-5 (PCL-5). The intervention consists of 12 separate EMDR sessions with a certified therapist. The control group receives usual care. The trial has three primary outcomes: changes in depression, burnout and PTSD scores from randomization to 6 months. All participants are followed up for 12 months.Conclusions: This study provides empirical evidence about the impact of the COVID-19 pandemic and the mental health burden it places on HCWs and assesses the effectiveness of EMDR as a psychological intervention.Trial registration NCT04570202.

Untangling the impact of plantation type and functional traits on ecosystem nutrient stocks in an experimentally restored forest ecosystem

The primary objective of ecological restoration is recovering biodiversity and ecosystem functioning. While a functional trait-based approach can help understand community assembly and ecosystem function recovery during ecological restoration, there still exists a knowledge gap in assessing how functional traits indicate the mediating roles of the plant community in response to forest restoration effects on ecosystem functions. This study applied the "response-effect trait" framework to investigate experimentally whether the treatment of plantation type has an impact on community trait compositions, which in turn could affect forest ecosystem nutrient stocks - here, carbon (C) and nitrogen (N) and phosphorus (P) stocks in tree, understory, litter and soil pools at an experimental station in subtropical China. We used structural equation models (SEMs) to examine the relationships among plantation type, community weighted mean of traits, and nutrient stocks in each pool. Our results show that most of the tree and understory traits studied were response traits to plantation type. Moreover, certain traits played a significant role in mediating plantation-type effects on C, N and P stocks for understory pool (e.g., understory stem specific density and specific leaf area, tree leaf phosphorus content), and for litter and soil pools (e.g., tree leaf carbon or phosphorus content, understory specific leaf area, leaf nitrogen or phosphorus content), known as "response-effect traits". For the tree pool, only effect traits, and no "response-effect" tree traits, were found for the N stock. Total effects of SEMs indicated that, understory or tree traits can have a greater impact than plantation type on understory or litter C, N or P stocks. After approximately 35 years of natural restoration, exotic plantations exhibited a different community trait characteristic from native plantations. The important roles of traits in mediating the effects of plantation type on non-tree pool C, N and P stocks were highlighted.

Water-energy-vegetation nexus explain global geographical variation in surface urban heat island intensity

Surface urban heat island (SUHI) is a key climate risk associated with urbanization. Previous case studies have suggested that precipitation (water), radiation (energy), and vegetation have important effects on urban warming, but there is a lack of research that combines these factors to explain the global geographic variation in SUHI intensity (SUHII). Here, we utilize remotely sensed and gridded datasets to propose a new water-energy-vegetation nexus concept that explains the global geographic variation of SUHII across four climate zones and seven major regions. We found that SUHII and its frequency increase from arid zones (0.36 ± 0.15 °C) to humid zones (2.28 ± 0.10 °C), but become weaker in the extreme humid zones (2.18 ± 0.15 °C). We revealed that from semi-arid/humid to humid zones, high precipitation is often coupled with high incoming solar radiation. The increased solar radiation can directly enhance the energy in the area, leading to higher SUHII and its frequency. Although solar radiation is high in arid zones (mainly in West, Central, and South Asia), water limitation leads to sparse natural vegetation, suppressing the cooling effect in rural areas and resulting in lower SUHII. In extreme humid regions (mainly in tropical areas), incoming solar radiation tends to flatten out, which, coupled with increased vegetation as hydrothermal conditions become more favorable, leads to more latent heat and reduces the intensity of SUHI. Overall, this study offers empirical evidence that the water-energy-vegetation nexus highly explains the global geographic variation of SUHII. The results can be used by urban planners seeking optimal SUHI mitigation strategies and for climate change modeling work.

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.

Seagrass production around artificial reefs is resistant to human stressors

Primary production underpins most ecosystem services, including carbon sequestration and fisheries. Artificial reefs (ARs) are widely used for fisheries management. Research has shown that a mechanism by which ARs in seagrass beds can support fisheries and carbon sequestration is through increasing primary production via fertilization from aggregating fish excretion. Seagrass beds are heavily affected by anthropogenic nutrient input and fishing that reduces nutrient input by consumers. The effect of these stressors is difficult to predict because impacts of simultaneous stressors are typically non-additive. We used a long-term experiment to identify the mechanisms by which simultaneous impacts of sewage enrichment and fishing alter seagrass production around ARs across non-orthogonal gradients in human-dominated and relatively unimpacted regions in Haiti and The Bahamas. Merging trait-based measures of seagrass and seagrass ecosystem processes, we found that ARs consistently enhanced per capita seagrass production and maintained ecosystem-scale production despite drastic shifts in controls on production from human stressors. Importantly, we also show that coupled human stressors on seagrass production around ARs were additive, contrasting expectations. These findings are encouraging for conservation because they indicate that seagrass ecosystems are highly resistant to coupled human stressors and that ARs promote ecosystem services even in human-dominated ecosystems.

Spring arrival of the common cuckoo at breeding grounds is strongly determined by environmental conditions in tropical Africa

Failure to adapt migration timing to changes in environmental conditions along migration routes and at breeding locations can result in mismatches across trophic levels, as occurs between the brood parasitic common cuckoo Cuculus canorus and its hosts. Using satellite tracking data from 87 male cuckoos across 11 years, we evaluate why the cuckoo has not advanced its arrival to the UK. Across years, breeding ground arrival was primarily determined by timing of departure from stopover in West Africa before northward crossing of the Sahara. Together with high population synchrony and low apparent endogenous control of this event, this suggests that a seasonal ecological constraint operating here limits overall variation in breeding grounds arrival, although this event was itself influenced by carry-over from timing of arrival into tropical Africa. Between-year variation within individuals was, in contrast, mostly determined by northward migration through Europe, probably due to weather conditions. We find evidence of increased mortality risk for (a) early birds following migration periods positively impacting breeding grounds arrival, and (b) late birds, possibly suffering energy limitation, after departure from the breeding grounds. These results help identify areas where demands of responding to global change can potentially be alleviated by improving stopover quality.

Identifying historical and future global change drivers that place species recovery at risk

Ecosystem management in the face of global change requires understanding how co-occurring threats affect species and communities. Such an understanding allows for effective management strategies to be identified and implemented. An important component of this is differentiating between factors that are within (e.g. invasive predators) or outside (e.g. drought, large wildfires) of a local manager's control. In the global biodiversity hotspot of south-western Australia, small- and medium-sized mammal species are severely affected by anthropogenic threats and environmental disturbances, including invasive predators, fire, and declining rainfall. However, the relative importance of different drivers has not been quantified. We used data from a long-term monitoring program to fit Bayesian state-space models that estimated spatial and temporal changes in the relative abundance of four threatened mammal species: the woylie (Bettongia penicillata), chuditch (Dasyurus geoffroii), koomal (Trichosurus vulpecula) and quenda (Isoodon fusciventor). We then use Bayesian structural equation modelling to identify the direct and indirect drivers of population changes, and scenario analysis to forecast population responses to future environmental change. We found that habitat loss or conversion and reduced primary productivity (caused by rainfall declines) had greater effects on species' spatial and temporal population change than the range of fire and invasive predator (the red fox Vulpes vulpes) management actions observed in the study area. Scenario analysis revealed that a greater extent of severe fire and further rainfall declines predicted under climate change, operating in concert are likely to further reduce the abundance of these species, but may be mitigated partially by invasive predator control. Considering both historical and future drivers of population change is necessary to identify the factors that risk species recovery. Given that both anthropogenic pressures and environmental disturbances can undermine conservation efforts, managers must consider how the relative benefit of conservation actions will be shaped by ongoing global change.

Distinguishing the impact of tourism development on ecosystem service trade-offs in ecological functional zone

Tourism in ecological functional zones (EFZs) is rapidly becoming an increasing trend; however, its impact on ecosystem services remains poorly understood owing to the absence of a consistent quantification framework. This study uses the Taihang Mountains (THM), an EFZ in China, as an example to develop a framework for evaluating the direct and indirect impact pathways of scenic spots on the trade-offs between multiple ecosystem services by identifying the linkages between scenic spot development, socioeconomic change, land use transitions, and ecosystem services. The results show that the continued conversion of agricultural land, grassland, and forest to constructed land around scenic spots in 2000-2020 was accompanied by a decline in water yield (WY) and habitat quality (HQ); while food production (FP), carbon storage (CS), and soil retention (SR) increased. Land use and ecosystem service changes around scenic spots in the THM also exhibited significant spatial gradient effects. In particular, a 10-km buffer area was identified as a distinct "influence zone" where the ecosystem services trade-offs and land use changes were the most pronounced. In 2010, scenic spot revenue was the dominant factor that increased the trade-offs between SR with FP and CS via direct pathways. However, in 2020, the dominant factor was scenic spot level, which shifted the impact toward the relationship between CS and WY and HQ by intensifying the trade-offs to facilitating synergies. This was accomplished in an indirect manner, such as the facilitation of local population growth, industrial restructuring, and infrastructure development. This study reveals the varying effects of scenic spot development via different pathways, thereby providing useful insights for global EFZs to more precisely design policies that can adequately balance human activities with ecosystem services.

Social determinants of health and disease in companion dogs: a cohort study from the Dog Aging Project

Exposure to social environmental adversity is associated with health and survival across many social species, including humans. However, little is known about how these health and mortality effects vary across the lifespan and may be differentially impacted by various components of the environment. Here, we leveraged a relatively new and powerful model for human aging, the companion dog, to investigate which components of the social environment are associated with dog health and how these associations vary across the lifespan. We drew on comprehensive survey data collected on 21,410 dogs from the Dog Aging Project and identified five factors that together explained 33.7% of the variation in a dog's social environment. Factors capturing financial and household adversity were associated with poorer health and lower physical mobility in companion dogs, while factors that captured social support, such as living with other dogs, were associated with better health when controlling for dog age and weight. Notably, the effects of each environmental component were not equal: the effect of social support was 5× stronger than financial factors. The strength of these associations depended on the age of the dog, including a stronger relationship between the owner's age and the dog's health in younger as compared to older dogs. Taken together, these findings suggest the importance of income, stability and owner's age on owner-reported health outcomes in companion dogs and point to potential behavioral and/or environmental modifiers that can be used to promote healthy aging across species.

Ecosystem services in connected catchment to coast ecosystems: Monitoring to detect emerging trends

There is an increasing need for long-term monitoring of ecosystems and their services to inform on-ground management. The supply of many ecosystem services relies on connections that span multiple ecosystems. Monitoring the underlying condition of interconnected ecosystems is therefore required to track effectiveness of past interventions and identify impending change. Here we test the performance of indicators of ecosystem services with the aim of identifying the time-scales over which indicators of ecosystem services responded to change. We chose a case-study of a catchment in Northern Australia, where water resource development is a threat to the river flows that support vegetation growth and the life-cycle of coastal fishery species. We developed a novel approach to performance testing that drew on state-space modelling to capture ecological dynamics, and structural equation modelling to capture covariation in indicator time series. We first quantified covariation among three ecological indicators that had time-series data: pasture biomass, vegetation greenness and barramundi catch per unit effort. Higher values of all indicators occurred in years with greater river flow. We then predicted the emergence times for each indicator, as the time taken for a trend in an indicator to emerge from the background of natural variation. Emergence times were > 10 years in all cases, quantified at 80 % and higher confidence levels. Past trends and current status of ecosystem service flows are often used by decision makers to directly inform near-term actions, particularly for provisioning services (such as barramundi catch) due to their important contribution to regional economies. We found that ecological indicators could be used to assess historical performance over decadal timespans, but not as short-term indicators of recent change. More generally, we offer an approach to performance testing of indicators. This approach could be useful for quantifying timescales of ecosystem response in systems where cross-ecosystem connections are important.

Addressing controversies in the xylem embolism resistance-vessel diameter relationship

Although xylem embolism is a key process during drought-induced tree mortality, its relationship to wood anatomy remains debated. While the functional link between bordered pits and embolism resistance is known, there is no direct, mechanistic explanation for the traditional assumption that wider vessels are more vulnerable than narrow ones. We used data from 20 temperate broad-leaved tree species to study the inter- and intraspecific relationship of water potential at 50% loss of conductivity (P₅₀ ) with hydraulically weighted vessel diameter (D_h ) and tested its link to pit membrane thickness (T_PM ) and specific conductivity (K_s ) on species level. Embolism-resistant species had thick pit membranes and narrow vessels. While D_h was weakly associated with T_PM , the P₅₀ -D_h relationship remained highly significant after accounting for T_PM . The interspecific pattern between P₅₀ and D_h was mirrored by a link between P₅₀ and K_s , but there was no evidence for an intraspecific relationship. Our results provide robust evidence for an interspecific P₅₀ -D_h relationship across our species. As a potential cause for the inconsistencies in published P₅₀ -D_h relationships, our analysis suggests differences in the range of trait values covered, and the level of data aggregation (species, tree or sample level) studied.

Estimating direct and indirect effects of habitat structure on nesting field sparrows (Spizella pusilla) using structural equation models

Due to consistent population declines across the continent, grassland birds have become a guild of high conservation and management interest. Despite a large number of studies investigating grassland bird habitat associations, we know relatively little about the mechanisms through which habitat characteristics may impact grassland birds, as these mechanisms are often assumed rather than directly tested. For this study, we estimated whether the effects of habitat structure on breeding Field Sparrows are mediated through changes in predator (snake and raccoon) abundance, alternative prey availability, or arthropod biomass using structural equation models. We found no evidence of nest survival or nest density of Field Sparrows being directly influenced by nest predator abundance, alternative prey, or arthropod biomass, although habitat characteristics associated with increased nest survival were also associated with greater arthropod biomass and reduced predator abundance. We suggest that habitat structure in our study area primarily impacts breeding Field Sparrows through direct means, such as influencing nest concealment or foraging efficiency. Our results also suggest that nest success and nest density are decoupled in our study area, so Field Sparrows may be preferentially selecting nest sites with structural characteristics that do not increase nest survival. Ultimately, our findings from this study indicate that while predator avoidance and food provisioning likely play an important role in determining nest survival for grassland birds, predator abundance and arthropod biomass may not necessarily predict predation risk and foraging efficiency to the extent that is often assumed.

Increasing diversity and biotic homogenization of lake plankton during recovery from acidification

Determining biodiversity responses to environmental change, such as acidification, is critical for ecosystem projections under future global change scenarios. Here, we analyzed three plankton communities of phytoplankton, crustaceans and rotifers in 28 lakes in the Adirondack Park, USA, during 1994-2012, and examined the spatiotemporal trends in their alpha and beta diversity during recovery from acidification. For all plankton assemblages, Shannon diversity increased towards recent years and high lake pH, and there was an increasing community dissimilarity with pH changes. The spatial mean Bray-Curtis dissimilarities across all lakes decreased over time for phytoplankton and rotifers leading to an increase in spatial homogenization. Such a homogenization cooccurred however with the overall increasing diversity in this region, which contrasts with the previous classic view that homogenization is mainly driven by loss of species and results in biodiversity loss. We further observed lower temporal mean beta diversity in low-pH lakes for crustaceans and rotifers, but not for phytoplankton. Generally, spatial and temporal mean beta diversity of the three taxonomic groups were primarily driven by lake-water ion variables, and rotifers were also constrained by nutrients and climate. Collectively, our results show how and why plankton community compositions vary over space along with acidification recovery, and further highlight the importance of spatiotemporal studies combined with long-term monitoring programs in assessing biodiversity change during the recovery of disturbed ecosystems.

Community assembly history alters relationships between biodiversity and ecosystem functions during restoration

Relationships between biodiversity and ecosystem functioning depend on the processes structuring community assembly. However, predicting biodiversity-ecosystem functioning (BEF) relationships based on community assembly remains challenging because assembly outcomes are often contingent on history and the consequences of history for ecosystem functions are poorly understood. In a grassland restoration experiment, we isolated the role of history for the relationships between plant biodiversity and multiple ecosystem functions by initiating assembly in three different years, while controlling for all other aspects of community assembly. We found that two aspects of assembly history-establishment year and succession-altered species and trait community trajectories, which in turn altered net primary productivity, decomposition rates, and floral resources. Moreover, history altered BEF relationships (which ranged from positive to negative), both within and across functions, by modifying the causal pathways linking species identity, traits, diversity, and ecosystem functions. Our results show that the interplay of deterministic succession and environmental stochasticity during establishment mediate historical contingencies that cause variation in biodiversity and ecosystem functions, even under otherwise identical assembly conditions. An explicit attention to history is needed to understand why biodiversity-ecosystem function relationships vary in natural ecosystems: a critical question at the intersection of fundamental theory and applications to environmental change biology and ecosystem restoration.

The spatial patterns of diversity and their relationships with environments in rhizosphere microorganisms and host plants differ along elevational gradients

Introduction

Identifying spatial patterns of biodiversity along elevational gradients provides a unified framework for understanding these patterns and predicting ecological responses to climate change. Moreover, microorganisms and plants are closely interconnected (e.g., via the rhizosphere) and thus may share spatial patterns of diversity and show similar relationships with environments.

Methods

This study compared diversity patterns and relationships with environments in host plants and rhizosphere microorganisms (including various functional groups) along elevational gradients across three climatic zones.

Results

We found that above-and belowground diversity decreased monotonically or showed a hump-shaped or U-shaped pattern along elevation gradients. However, the diversity patterns of plants, bacteria, and fungi varied depending on the taxon and climatic zone. Temperature and humidity strongly contribute to above-and belowground diversity patterns and community composition along elevational gradients. Nonetheless, soil factors might be important regulators of diversity patterns and the community composition of plants and microorganisms along these gradients. Structural equation modeling revealed that environmental factors had a stronger direct effect on rhizosphere microbial diversity than host plant diversity.

Discussion

In sum, spatial patterns of diversity and their relationships with environments in rhizosphere microorganisms and their host plants differed at the regional scale. Different functional groups (e.g., pathogen, mycorrhiza and nitrifier) of soil microorganisms may have divergent elevational patterns and environmental responses. These data improve our understanding of elevational diversity patterns, and provide new insights into the conservation of biodiversity and ecosystem management, especially under climate change.

Investigating speed-safety association: Considering the unobserved heterogeneity and human factors mediation effects

The relationship between mean speed and crash likelihood is unclear in the literature. The contradictory findings can be attributed to the masking effects of the confounding variables in this association. Moreover, the unobserved heterogeneity has almost been criticized as a reason behind the current inconclusive results. This research provides an effort to develop a model that analyzes the mean speed-crash frequency relationship by crash severity and type. Also, the confounding and mediation effects of the environment, driver, and traffic-related attributes have been considered. To this end, the loop detector and crash data were aggregated daily for rural multilane highways of Tehran province, Iran, covering two years, 2020-2021. The partial least squares path modeling (PLS-PM) was employed for crash causal analysis along with the finite mixture partial least squares (FIMIX-PLS) segmentation to account for potential unobserved heterogeneity between observations. The mean speed was negatively and positively associated with the frequency of property damage-only (PDO) and severe accidents, respectively. Moreover, driver-related variables, including tailgating, distracted driving, and speeding, played key mediation roles in associating traffic and environmental factors with the crash risk. The higher the mean speed and the lower the traffic volume, the higher odds of distracted driving. Distracted driving was, in turn, associated with the higher vulnerable road users (VRU) accidents and single-vehicle accidents, triggering a higher frequency of severe accidents. Moreover, lower mean speed and higher traffic volume were positively correlated with the percentage of tailgating violations, which, in turn, predicted multi-vehicle accidents as the main predictor of PDO crash frequency. In conclusion, the mean speed effects on the crash risk are entirely different for each crash type through distinct crash mechanisms. Hence, the distinct distribution of crash types in different datasets might have led to current inconsistent results in the literature.

Salinity reduces site quality and mangrove forest functions. From monitoring to understanding

Mangroves continue to be threatened across their range by a mix of anthropogenic and climate change-related stress. Climate change-induced salinity is likely to alter the structure and functions of highly productive mangrove systems. However, we still lack a comprehensive understanding of how rising salinity affects forest structure and functions because of the limited availability of mangrove field data. Therefore, based on extensive spatiotemporal mangrove data covering a large-scale salinity gradient, collected from the world's largest single tract mangrove ecosystem - the Bangladesh Sundarbans, we, aimed to examine (QI) how rising salinity influences forest structure (e.g., stand density, diversity, leaf area index (LAI), etc.), functions (e.g., carbon stocks, forest growth), nutrients availability, and functional traits (e.g., specific leaf area, wood density). We also wanted to know (QII) how forest functions interact (direct vs. indirect) with biotic (i.e., stand structure, species richness, etc.) and abiotic factors (salinity, nutrients, light availability, etc.). We also asked (QIII) whether the functional variable decreases disproportionately with salinity and applied the power-law (i.e., Y = a X^b) to the salinity and functional variable relationships. In this study, we found that rises in salinity significantly impede forest growth and produce less productive ecosystems dominated by dwarf species while reducing stand structural properties (i.e., tree height, basal area, dominant tree height, LAI), soil carbon (organic and root carbon), and macronutrient availability in the soil (e.g., NH4+, P, and K). Besides, species-specific leaf area (related to resource acquisition) also decreased with salinity, whereas wood density (related to resource conservation) increased. We observed a declining abundance of the salt-intolerant climax species (Heritiera fomes) and dominance of the salt-tolerant species (Excoecaria agallocha, Ceriops decandra) in the high saline areas. In the case of biotic and abiotic factors, salinity and salinity-driven gap fraction (high transmission of light) had a strong negative impact on functional variables, while nutrients and LAI had a positive impact. In addition, the power-law explained the consistent decline of functional variables with salinity. Our study disentangles the negative effects of salinity on site quality in the Sundarbans mangrove ecosystem, and we recognize that nutrient availability and LAI are likely to buffer the less salt-tolerant species to maintain the ability to sequester carbon with sea-level rise. These novel findings advance our understanding of how a single stressor-salinity-can shape mangrove structure, functions, and productivity and offer decision makers a much-needed scientific basis for developing pragmatic ecosystem management and conservation plans in highly stressed coastal ecosystems across the globe.

Grazing and ecosystem service delivery in global drylands

Grazing represents the most extensive use of land worldwide. Yet its impacts on ecosystem services remain uncertain because pervasive interactions between grazing pressure, climate, soil properties, and biodiversity may occur but have never been addressed simultaneously. Using a standardized survey at 98 sites across six continents, we show that interactions between grazing pressure, climate, soil, and biodiversity are critical to explain the delivery of fundamental ecosystem services across drylands worldwide. Increasing grazing pressure reduced ecosystem service delivery in warmer and species-poor drylands, whereas positive effects of grazing were observed in colder and species-rich areas. Considering interactions between grazing and local abiotic and biotic factors is key for understanding the fate of dryland ecosystems under climate change and increasing human pressure.

Soil moisture-atmosphere feedback dominates land N2 O nitrification emissions and denitrification reduction

Soil moisture (SM) is essential to microbial nitrogen (N)-cycling networks in terrestrial ecosystems. Studies have found that SM-atmosphere feedbacks dominate the changes in land carbon fluxes. However, the influence of SM-atmosphere feedbacks on the N fluxes changes, and the underlying mechanisms remain highly unsure, leading to uncertainties in climate projections. To fill this gap, we used in situ observation coupled with gridded and remote sensing data to analyze N₂ O fluxes emissions globally. Here, we investigated the synergistic effects of temperature, hydroclimate on global N₂ O fluxes, as the result of SM-atmosphere feedback impact on N fluxes. We found that SM-temperature feedback dominates land N₂ O emissions by controlling the balance between nitrifier and denitrifier genes. The mechanism is that atmospheric water demand increases with temperature and thereby reduces SM, which increases the dominant N₂ O production nitrifier (containing amoA AOB gene) and decreases the N₂ O consumption denitrifier (containing the nosZ gene), consequently will potential increasing N₂ O emissions. However, we find that the spatial variations of soil-water availability as a result of the nonlinear response of SM to vapor pressure deficit caused by temperature are some of the greatest challenges in predicting future N₂ O emissions. Our data-driven assessment deepens the understanding of the impact of SM-atmosphere interactions on the soil N cycle, which remains uncertain in earth system models. We suggest that the model needs to account for feedback between SM and atmospheric temperature when estimating the response of the N₂ O emissions to climatic change globally, as well as when conducting field-scale investigations of the response of the ecosystem to warming.

Data synthesis for environmental management: A case study of Chesapeake Bay

Synthesizing large, complex data sets to inform resource managers towards effective environmental stewardship is a universal challenge. In Chesapeake Bay, a well-studied and intensively monitored estuary in North America, the challenge of synthesizing data on water quality and land use as factors related to a key habitat, submerged aquatic vegetation, was tackled by a team of scientists and resource managers operating at multiple levels of governance (state, federal). The synthesis effort took place over a two-year period (2016-2018), and the results were communicated widely to a) scientists via peer review publications and conference presentations; b) resource managers via web materials and workshop presentations; and c) the public through newspaper articles, radio interviews, and podcasts. The synthesis effort was initiated by resource managers at the United States Environmental Protection Agencys' Chesapeake Bay Program and 16 scientist participants were recruited from a diversity of organizations. Multiple short, immersive workshops were conducted regularly to conceptualize the problem, followed by data analysis and interpretation that supported the preparation of the synthetic products that were communicated widely. Reflections on the process indicate that there are a variety of structural and functional requirements, as well as enabling conditions, that need to be considered to achieve successful outcomes from synthesis efforts.

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.

Extracellular enzyme stoichiometry reveals carbon and nitrogen limitations closely linked to bacterial communities in China’s largest saline lake

Saline lakes possess substantial carbon storage and play essential roles in global carbon cycling. Benthic microorganisms mine and decompose sediment organic matter via extracellular enzymes to acquire limiting nutrients and thus meet their element budgets, which ultimately causes variations in sediment carbon storage. However, current knowledge about microbial nutrient limitation and the associated organic carbon changes especially in saline lake remains elusive. Therefore, we took Qinghai Lake, the largest saline lake of China, as an example to identify the patterns and drivers of microbial metabolic limitations quantified by the vector analyses of extracellular enzyme stoichiometry. Benthic microorganisms were dominantly colimited by carbon (C) and nitrogen (N). Such microbial C limitation was aggravated upon the increases in water salinity and sediment total phosphorus, which suggests that sediment C loss would be elevated when the lake water is concentrated (increasing salinity) and phosphorus becomes enriched under climate change and nutrient pollution, respectively. Microbial N limitation was predominantly intensified by water total nitrogen and inhibited by C limitation. Among the microbial drivers of extracellular enzyme investments, bacterial community structure consistently exerted significant effects on the C, N, and P cycles and microbial C and N limitations, while fungi only altered the P cycle through species richness. These findings advance our knowledge of microbial metabolic limitation in saline lakes, which will provide insights towards a better understanding of global sediment C storage dynamics under climate warming and intensified human activity.

The evolution of insular woodiness

Insular woodiness (IW)-the evolutionary transition from herbaceousness toward woodiness on islands-is one of the most iconic features of island floras. Since pioneering work by Darwin and Wallace, a number of drivers of IW have been proposed, such as 1) competition for sunlight requiring plants with taller and stronger woody stems and 2) drought favoring woodiness to safeguard root-to-shoot water transport. Alternatively, IW may be the indirect result of increased lifespan related to 3) a favorable aseasonal climate and/or 4) a lack of large native herbivores. However, information on the occurrence of IW is fragmented, hampering tests of these potential drivers. Here, we identify 1,097 insular woody species on 375 islands and infer at least 175 evolutionary transitions on 31 archipelagos, concentrated in six angiosperm families. Structural equation models reveal that the insular woody species richness on oceanic islands correlates with a favorable aseasonal climate, followed by increased drought and island isolation (approximating competition). When continental islands are also included, reduced herbivory pressure by large native mammals, increased drought, and island isolation are most relevant. Our results illustrate different trajectories leading to rampant convergent evolution toward IW and further emphasize archipelagos as natural laboratories of evolution, where similar abiotic or biotic conditions replicated evolution of similar traits.

Illuminating biodiversity changes in the ‘Black Box’

Soil is often described as a ‘black box’, as surprisingly little is known about the high levels of biodiversity that reside there. For aboveground organisms, we have good knowledge of the distribution of the species and how they might change under future human impacts. Yet despite the fact that soil organisms provide a wide variety of ecosystem functions, we have very limited knowledge of their distribution and how their diversity might change in the future. In order to create accurate and generalisable models of biodiversity, the underlying data need to be representative of the entire globe. Yet even with our recently compiled global earthworm dataset of over 11000 sites, there are gaps across large regions. These gaps are consistent across many other datasets of both above- and belowground diversity. In order to fill the gaps we propose a sampling network (SoilFaUNa), to create a comprehensive database of soil macrofauna diversity and soil functions (e.g. decomposition rates). Building on the existing dataset of earthworm diversity and early data from the SoilFaUNa project, we will investigate changes in earthworm diversity. From our current work, we know that both climate and land use are main drivers in predicting earthworm diversity, but both will change under future scenarios and may alter ecosystem functions. We will, using space-for-time substitution models, estimate how earthworm diversity and their functions might change in the future, modelling earthworm diversity as a function of climate, land use and soil properties and predicting based on future scenarios. Previous studies of aboveground diversity changes over time using time-series analysis have found no-net-loss in richness, but analyses have criticisms. We aim to use time-series data on earthworms to move this debate forward, by using data and statistical methods that would address the criticisms, whilst increasing our knowledge on this understudied soil group. Field experiments and micro-/mesocosm experiments have been used to investigate the link between a number of soil organisms and ecosystem functions under few environmental conditions. Meta-analyses, which can produce generalisable results can only answer questions for which there are data. Thus, we have been lacking on information on the link between the entire community of soil fauna and ecosystem functions and impact of changes to the soil fauna community across environmental contexts. Using data collected from the SoilFaUNa project, we will, for the first time, synthesise globally distributed specifically-sampled data to model how changes in the community composition of soil macrofauna (due to changes in land use, climate or soil properties) impact the ecosystem functions in the soil.

Distinct rhizosphere soil responses to nitrogen in relation to microbial biomass and community composition at initial flowering stages of alfalfa cultivars

In the long-term growth process, alfalfa rhizosphere forms specific microbiome to provide nutrition for its growth and development. However, the effects of different perennial alfalfa cultivars on changes in the rhizosphere soil characteristics and microbiome are not well understood. In this study, 12 perennial alfalfa cultivars were grown continuously for eight years. Rhizosphere samples were tested using Illumina sequencing of the 16S rRNA gene coupled with co-occurrence network analysis to explore the relationship between alfalfa (biomass and crude protein content), soil properties, and the microbial composition and diversity. Redundancy analysis showed SOC and pH had the greatest impact on the composition of the rhizosphere microbial community. Moreover, microbial diversity also contributes to microbial composition. Soil properties (AP, EC, SOC and pH) exhibited a significant positive correlation with soil bacterial communities, which was attributed to the differences between plant cultivars. Partial least squares path modeling (PLS-PM) revealed that microbial biomass and community composition rather than diversity, are the dominant determinants in the rhizosphere soil nitrogen content of perennial alfalfa. Our findings demonstrate that the soil microbial biomass and composition of rhizosphere bacterial communities are strongly affected by cultivar, driving the changes in soil nitrogen content, and variances in the selective capacities of plants.

Interactive influences of meteorological and socioeconomic factors on ecosystem service values in a river basin with different geomorphic features

Ecosystem service value (ESV) is influenced by land use and land cover (LULC), and is closely related to natural conditions and human activities. However, the interactions between human and natural systems and ESV remain unclear, especially concerning widely discussed meteorological and socioeconomic factors. In this study, three periods of LULC patterns (2000, 2010, and 2020) in the Haihe River Basin, northern China, were collected to determine the relationship between changes in LULC and ESV over time. Natural and socioeconomic data associated with ESV were obtained and the structural equation model was used to decouple interactions between these factors. Results showed that the total value of regional ecosystem services has decreased as cultivated land shrunk and artificial surfaces increased over the past two decades. The ESV was significantly decreased in the middle of the basin. The direct effects of meteorological factors and socioeconomic factors on ESV were positive (0.094) and negative (-0.203), respectively. The indirect effect of socioeconomic factors on ESV through meteorological and LULC factors was 0.149. Structural equation modeling demonstrated that under the dominance of LULC, interactions between natural and socioeconomic factors affected ESV in a complex manner. These results implied that identifying the direct and indirect effects of economic development and human activities on ESV could guide and implement effective land management policies.

Ecological networks of dissolved organic matter and microorganisms under global change

Microbes regulate the composition and turnover of organic matter. Here we developed a framework called Energy-Diversity-Trait integrative Analysis to quantify how dissolved organic matter and microbes interact along global change drivers of temperature and nutrient enrichment. Negative and positive interactions suggest decomposition and production processes of organic matter, respectively. We applied this framework to manipulative field experiments on mountainsides in subarctic and subtropical climates. In both climates, negative interactions of bipartite networks were more specialized than positive interactions, showing fewer interactions between chemical molecules and bacterial taxa. Nutrient enrichment promoted specialization of positive interactions, but decreased specialization of negative interactions, indicating that organic matter was more vulnerable to decomposition by a greater range of bacteria, particularly at warmer temperatures in the subtropical climate. These two global change drivers influenced specialization of negative interactions most strongly via molecular traits, while molecular traits and bacterial diversity similarly affected specialization of positive interactions.

Microbes are intimately linked with the fate of organic matter. Here the authors develop an ecological network framework and show how microbes and dissolved organic matter interact along global change drivers of temperature and nutrient enrichment via manipulative field experiments on mountains.

Increase in rainfall intensity promotes soil nematode diversity but offset by nitrogen addition in a temperate grassland

Precipitation regime in arid and semi-arid regions is exhibiting a trend of increase in rainfall intensity but reduction in frequency under global climate change. In addition, nitrogen (N) deposition occurs simultaneously in the same regions. Nematodes are the dominant soil biota in terrestrial ecosystems and are involved in various underground processes. How the diversity of nematode communities responds to changing precipitation regime and how N deposition regulates the responses remain unclear. Here, we performed a field experiment initiated in 2012 to examine the effect of changes in the precipitation regime (2 mm precipitation intensity, 5 mm precipitation intensity, 10 mm precipitation intensity, 20 mm precipitation intensity, and 40 mm precipitation intensity) and N addition (10 g N m^-2 yr^-1) on soil nematode community in a semi-arid grassland in Inner Mongolia of China. We found that the abundance and diversity of nematodes increased under the treatments with fewer but stronger precipitation events (the largest abundance of total nematodes was 1458.37 individuals/100 g dry soil occurred under 40 mm intensity treatment). However, N addition reduced nematode diversity under these treatments, which largely offset the positive effects of increased rainfall intensity alone. Soil pH and plant belowground biomass were the main factors affecting nematode diversity. Our results imply that, as a consequence of global climate change, an increase in the intensity of rainfall events in the coming decades may favor the nematode communities within arid and semi-arid ecosystems. However, this positive effect may be largely offset by soil acidification in the regions experiencing heavy N deposition.

Causation inference in complicated atmospheric environment

Reliable attribution is crucial for understanding various climate change issues. However, complicated inner-interactions between various factors make causation inference in atmospheric environment highly challenging. Taking PM_2.5-Meteorology causation, which involves a large number of non-Linear and uncertain interactions between many meteorological factors and PM_2.5, as a case, we examined the performance of a series of mainstream statistical models, including Correlation Analysis (CA), Partial Correlation Analysis (PCA), Structural Equation Model (SEM), Convergent Cross Mapping (CCM), Partial Cross Mapping (PCM) and Geographical Detector (GD). From a coarse perspective, the Top 3 major meteorological factors for PM_2.5 in 190 cities across China extracted using different models were generally consistent. From a strict perspective, the extracted dominant meteorological factor for PM_2.5 demonstrated large model variations and shared a limited consistence. Such models as SEM and PCM, which are capable of further separating direct and indirect causation in simple systems, performed poorly to identify the direct and indirect PM_2.5-Meteorology causation. The notable inconsistence denied the feasibility of employing multiple models for better causation inference in atmospheric environment. Instead, the sole use of CCM, which is advantageous in dealing with non-linear causation and removing disturbing factors, is a preferable strategy for causation inference in complicated ecosystems. Meanwhile, given the multi-direction, uncertain interactions between many variables, we should be more cautious and less ambitious on the separation of direct and indirect causation. For better causation inference in the complicated atmospheric environment, the combination of statistical models and atmospheric models, and the further exploration of Deep Neural Network can be promising strategies.

Phosphorus is the key soil indicator controlling productivity in planted Masson pine forests across subtropical China

Soil physiochemical properties are critical to understanding forest productivity and carbon (C) finance schemes in terrestrial ecosystems. However, few studies have focused on the effects of the soil physiochemical properties on the productivity in planted forests. This study was therefore conducted at 113 sampling plots located in planted Masson pine forests across subtropical China to test what and how the aboveground net primary productivity (ANPP) would be explained by the soil physiochemical properties, stand attributes, and functional traits using regression analysis and structural equation modelling (SEM). Across subtropical China, the ANPP ranged from 1.79 to 14.04 Mg ha^-1 year^-1 among the plots, with an average value of 6.05 Mg ha^-1 year^-1. The variations in ANPP were positively related to the stand density, root phosphorus (P) content and soil total P content but were negatively related to the stand age, root C:P and N:P ratios. Among these factors, the combined effects of stand density, stand age and soil total P content explained 35% of the ANPP variations. The SEM results showed the indirect effect of the soil total P content via the root P content and C:P ratio on the ANPP and indirect effects of other soil properties (e.g., pH, clay, and bulk density) via the soil total P content and root functional traits (e.g., root P, C:P, and N:P) on the ANPP. By considering all possible variables and paths, the best-fitting SEM explained only 11-13% of the ANPP variations, which suggested that other factors may be more important in determining the productivity in planted forests. Overall, this study highlights that soil total P content should be used as a key soil indicator for determining the ANPP in planted Masson pine forests across subtropical China, and suggests that the root functional traits mediate the effects of soil properties on the ANPP.