Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass-loss rate and stabilization.

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.

Nonlinear life table response experiment analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers.

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second-order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second-order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second-order LTRE analyses could improve our understanding of population responses to changing environments.

Global increase of lianas in tropical forests.

Lianas profoundly affect tropical forests dynamics, reducing productivity and carbon storage, which underscores the importance of monitoring change in their abundance in projecting the future of the global terrestrial carbon store. While increasing liana populations are documented within the Neotropics, the global consistency of these patterns is questioned, and remains to be determined. To evaluate pantropical trends in liana abundance comprehensively and quantitatively, we conducted a systematic literature review and meta-analysis. This approach allowed us to synthesize data from published longitudinal studies examining liana trends across the tropics. We calculated standardized effect sizes and standard errors, and applied a Bayesian hierarchical meta-analytic model to adjust for publication bias. Our analysis reveals an overall pan-tropical increase in lianas abundance, occurring at an average rate of 1.7 ± 0.7 SE% per year (~10% to 24% per decade). This upward trend, confirmed to be robust against publication bias, extends beyond Neotropical regions, indicating a widespread phenomenon. Although a global trend of increasing liana abundance is evident, significant local variation exist, attributable to differences in life cycle stages, abundance metrics, forest successional stages, and biogeographical realms. Notably, increases in stem density of saplings and biomass of canopy lianas, especially in old-growth forests, point to global climatic drivers and heightened turnover rates in tropical forests as factors promoting sustained liana growth in the canopy and clonal colonization in the understory. These trends suggest that the rise in liana abundance may not only persist but could also intensify under climate change. Considering both previous and current research on lianas, our findings confirm growing concerns about lianas' expanding impact on pan-tropical carbon storage, highlighting their significant potential effect on global carbon dynamics.

Testing for concordance between predicted species richness, past prioritization, and marine protected area designations in the western Indian Ocean.

Scientific advances in environmental data coverage and machine learning algorithms have improved the ability to make large-scale predictions where data are missing. These advances allowed us to develop a spatially resolved proxy for predicting numbers of tropical nearshore marine taxa. A diverse marine environmental spatial database was used to model numbers of taxa from ∼1000 field sites, and the predictions were applied to all 7039 6.25-km2 reef cells in 9 ecoregions and 11 nations of the western Indian Ocean. Our proxy for total numbers of taxa was based on the positive correlation (r2 = 0.24) of numbers of taxa of hard corals and 5 highly diverse reef fish families. Environmental relationships indicated that the number of fish species was largely influenced by biomass, nearness to people, governance, connectivity, and productivity and that coral taxa were influenced mostly by physicochemical environmental variability. At spatial delineations of province, ecoregion, nation, and strength of spatial clustering, we compared areas of conservation priority based on our total species proxy with those identified in 3 previous priority-setting reports and with the protected area database. Our method identified 119 locations that fit 3 numbers of taxa (hard coral, fish, and their combination) and 4 spatial delineations (nation, ecoregion, province, and reef clustering) criteria. Previous publications on priority setting identified 91 priority locations of which 6 were identified by all reports. We identified 12 locations that fit our 12 criteria and corresponded with 3 previously identified locations, 65 that aligned with at least 1 past report, and 28 that were new locations. Only 34% of the 208 marine protected areas in this province overlapped with identified locations with high numbers of predicted taxa. Differences occurred because past priorities were frequently based on unquantified perceptions of remoteness and preselected priority taxa. Our environment-species proxy and modeling approach can be considered among other important criteria for making conservation decisions.

Evaluación de la concordancia entre la riqueza de especies pronosticada, priorizaciones pasadas y la designación de áreas marinas protegidas en el oeste del Océano Índico Resumen Los avances científicos en la cobertura de datos ambientales y los algoritmos de aprendizaje automatizado han mejorado la capacidad de predecir a gran escala cuando hacen falta datos. Estos avances nos permiten desarrollar un representante con resolución espacial para predecir la cantidad de taxones marinos en las costas tropicales. Usamos una base de datos espaciales de diversos ambientes marinos para modelar la cantidad de taxones a partir de ∼1000 sitios de campo y aplicamos las predicciones a las 7039 celdas arrecifales de 6.25­km2 en nueve ecorregiones y once países del oeste del Océano Índico. Nuestro representante para la cantidad total de taxones se basó en la correlación positiva (r2=0.24) de la cantidad de taxones de corales duros y cinco familias de peces arrecifales con diversidad alta. Las relaciones ambientales indicaron que el número de especies de peces estuvo influenciado principalmente por la biomasa, la cercanía a las personas, la gestión, la conectividad y la productividad y que los taxones de coral estuvieron influenciados principalmente por la variabilidad ambiental fisicoquímica. Comparamos la prioridad de las áreas de conservación a nivel de las delimitaciones espaciales de provincia, ecorregión, nación y fuerza del agrupamiento espacial basado en nuestro total de especies representantes con aquellas especies identificadas en tres reportes previos de establecimiento de prioridades y con la base de datos de áreas protegidas. Con nuestro método identificamos 119 localidades aptas para tres cantidades de taxones (corales duros, peces y su combinación) y cuatro criterios de delimitación espacial (nación, ecorregión, provincia y grupo de arrecifes). Las publicaciones previas sobre el establecimiento de prioridades identificaron 91 localidades prioritarias de las cuales seis fueron identificadas por todos los reportes. Identificamos doce localidades que se ajustan a nuestros doce criterios y se correspondieron con tres localidades identificadas previamente, 65 que se alinearon con al menos un reporte anterior y 28 que eran nuevas localidades. Sólo 34% de las 208 áreas marinas protegidas en esta provincia se traslaparon con localidades identificadas con un gran número de taxones pronosticados. Hubo diferencias porque en el pasado se priorizaba frecuentemente con base en las percepciones no cuantificadas de lo remoto y prioritario de los taxones preseleccionados. Nuestra especie representante del ambiente y nuestra estrategia de modelo pueden considerarse entre otros criterios importantes para tomar decisiones de conservación.

High-Resolution Estimates of N2O Emissions from Inland Waters and Wetlands in China.

Inland waters (rivers, lakes, and reservoirs) and wetlands (marshes and coastal wetlands) represent large and continuous sources of nitrous oxide (N2O) emissions, in view of adequate biomass and anaerobic conditions. Considerable uncertainties remain in quantifying spatially explicit N2O emissions from aquatic systems, attributable to the limitations of models and a lack of comprehensive data sets. Herein, we conducted a synthesis of 1659 observations of N2O emission rates to determine the major environmental drivers across five aquatic systems. A framework for spatially explicit estimates of N2O emissions in China was established, employing a data-driven approach that upscaled from site-specific N2O fluxes to robust multiple-regression models. Results revealed the effectiveness of models incorporating soil organic carbon and water content for marshes and coastal wetlands, as well as water nitrate concentration and dissolved organic carbon for lakes, rivers, and reservoirs for predicting emissions. Total national N2O emissions from inland waters and wetlands were 1.02 × 105 t N2O yr-1, with contributions from marshes (36.33%), rivers (27.77%), lakes (25.27%), reservoirs (6.47%), and coastal wetlands (4.16%). Spatially, larger emissions occurred in the Songliao River Basin and Continental River Basin, primarily due to their substantial terrestrial biomass. This study offers a vital national inventory of N2O emissions from inland waters and wetlands in China, providing paradigms for the inventorying work in other countries and insights to formulate effective mitigation strategies for climate change.

Global Atlas of Methane Metabolism Marker Genes in Soil.

Methane, a greenhouse gas, plays a pivotal role in the global carbon cycle, influencing the Earth's climate. Only a limited number of microorganisms control the flux of biologically produced methane in nature, including methane-oxidizing bacteria, anaerobic methanotrophic archaea, and methanogenic archaea. Although previous studies have revealed the spatial and temporal distribution characteristics of methane-metabolizing microorganisms in local regions by using the marker genes pmoA or mcrA, their biogeographical patterns and environmental drivers remain largely unknown at a global scale. Here, we used 3419 metagenomes generated from georeferenced soil samples to examine the global patterns of methane metabolism marker gene abundances in soil, which generally represent the global distribution of methane-metabolizing microorganisms. The resulting maps revealed notable latitudinal trends in the abundances of methane-metabolizing microorganisms across global soils, with higher abundances in the sub-Arctic, sub-Antarctic, and tropical rainforest regions than in temperate regions. The variations in global abundances of methane-metabolizing microorganisms were primarily governed by vegetation cover. Our high-resolution global maps of methane-metabolizing microorganisms will provide valuable information for the prediction of biogenic methane emissions under current and future climate scenarios.

Unraveling Spatially Diverse and Interactive Regulatory Mechanisms of Wetland Methane Fluxes to Improve Emission Estimation.

Methane fluxes (FCH4) vary significantly across wetland ecosystems due to complex mechanisms, challenging accurate estimations. The interactions among environmental drivers, while crucial in regulating FCH4, have not been well understood. Here, the interactive effects of six environmental drivers on FCH4 were first analyzed using 396,322 half-hourly measurements from 22 sites across various wetland types and climate zones. Results reveal that soil temperature, latent heat turbulent flux, and ecosystem respiration primarily exerted direct effects on FCH4, while air temperature and gross primary productivity mainly exerted indirect effects by interacting with other drivers. Significant spatial variability in FCH4 regulatory mechanisms was highlighted, with different drivers demonstrated varying direct, indirect, and total effects among sites. This spatial variability was then linked to site-specific annual-average air temperature (17.7%) and water table (9.0%) conditions, allowing the categorization of CH4 sources into four groups with identified critical drivers. An improved estimation approach using a random forest model with three critical drivers was consequently proposed, offering accurate FCH4 predictions with fewer input requirements. By explicitly accounting for environmental interactions and interpreting spatial variability, this study enhances our understanding of the mechanisms regulating CH4 emissions, contributing to more efficient modeling and estimation of wetland FCH4.

Environmental drivers of biogeography and community structure in a Mid-Atlantic estuary.

Estuaries include some of the most productive yet anthropogenically impacted marine ecosystems on the planet, and provide critical habitat to many ecologically and economically important marine species. In order to elucidate ecological function in estuaries, we must understand what factors drive community dynamics. Delaware Bay is the third largest estuary in the United States and hosts over 200 species of migrant and resident fishes and invertebrates. The Delaware Division of Fish and Wildlife has conducted two long-term trawl surveys at monthly intervals in Delaware Bay since 1966. The two surveys collect data on environmental conditions, species composition, and number of fishes and macroinvertebrates across different size classes and life histories. Using a suite of multivariate approaches including hierarchical cluster analysis, canonical correlation analysis, and permutational multivariate analysis of variance, we characterized the fish and macroinvertebrate community in Delaware Bay and found that community composition and environmental conditions varied across spatial and seasonal scales. We identified four distinct biogeographic regions, based on environmental conditions and community composition, which were consistent across surveys. We found that the community was driven primarily by gradients in temperature and salinity and that abundant, frequently occurring species in the Bay have well-defined environmental associations. Our work represents the first attempt to use an existing historical survey to better understand how environmental parameters influence diversity and distribution of macrofauna within Delaware Bay, providing insight into how abiotic variables, influenced by climate, may impact the Delaware Bay ecosystem and similar estuarine ecosystems worldwide.

Geographic distribution of bacterial communities of inland waters in China.

Microorganisms are integral to freshwater ecological functions and, reciprocally, their activity and diversity are shaped by the ecosystem state. Yet, the diversity of bacterial community and its driving factors at a large scale remain elusive. To bridge this knowledge gap, we delved into an analysis of 16S RNA gene sequences extracted from 929 water samples across China. Our analyses revealed that inland water bacterial communities showed a weak latitudinal diversity gradient. We found 530 bacterial genera with high relative abundance of hgcI clade. Among them, 29 core bacterial genera were identified, that is strongly linked to mean annual temperature and nutrient loadings. We also detected a non-linear response of bacterial network complexity to the increasing of human pressure. Mantel analysis suggested that MAT, HPI and P loading were the major factors driving bacterial communities in inland waters. The map of taxa abundance showed that the abundant CL500-29 marine group in eastern and southern China indicated high eutrophication risk. Our findings enhance our understanding of the diversity and large-scale biogeographic pattern of bacterial communities of inland waters and have important implications for microbial ecology.

Exploring the environmental influences and community assembly processes of bacterioplankton in a subtropical coastal system: Insights from the Beibu Gulf in China.

Due to rapid urbanization, the Beibu Gulf, a semi-closed gulf in the northwestern South China Sea, faces escalating ecological and environmental threats. Understanding the assembly mechanisms and driving factors of bacterioplankton in the Beibu Gulf is crucial for preserving its ecological functions and services. In the present study, we investigated the spatiotemporal dynamics of bacterioplankton communities and their assembly mechanisms in the Beibu Gulf based on the high-throughput sequencing of the bacterial 16 S rRNA gene. Results showed significantly higher bacterioplankton diversity during the wet season compared to the dry season. Additionally, distinct seasonal variations in bacterioplankton composition were observed, characterized by an increase in Cyanobacteria and Thermoplasmatota and a decrease in Proteobacteria and Bacteroidota during the wet season. Null model analysis revealed that stochastic processes governed bacterioplankton community assembly in the Beibu Gulf, with drift and homogenizing dispersal dominating during the dry and wet seasons, respectively. Enhanced deterministic assembly of bacterioplankton was also observed during the wet season. Redundancy and random forest model analyses identified the physical properties (e.g., temperature) and nutrient content (e.g., nitrate) of water as primary environmental drivers influencing bacterioplankton dynamics. Moreover, variation partitioning and distance-decay of similarity revealed that environmental filtering played a significant role in shaping bacterioplankton variations in this rapidly developed coastal ecosystem. These findings advance our understanding of bacterioplankton assembly in coastal ecosystems and establish a theoretical basis for effective ecological health management amidst ongoing global changes.

The large-scale expansion of rubber plantations in southern India: major impacts and the changing nature of drivers.

This study investigates the major environmental and socio-economic impacts of an increase in the area of rubber plantations and the changing patterns of drivers of land use changes. Using a combination of geospatial techniques and socio-economic methods, we mainly analyzed the rate of increase in area under rubber plantations, the major impacts of land use changes, and the changing drivers of land use changes. Our results show that the area under rubber plantations has increased significantly within the study area, with the area under rubber plantations increasing from 30 to 74% of the total area within five decades. Impact assessment of land use changes based on household surveys showed significant improvement in the socio-economic conditions of the farmers, however, at the expense of severe environmental degradation. Our results also indicate that while areas under rubber plantations continue to increase, the drivers of land use changes have changed over time. Furthermore, it has been observed that in the past, many interventions prioritized social and economic development and placed less emphasis on the ecological stability of the region. Perceptions of farmers revealed that the effects of ecological fragility already affected the economic robustness of the whole area. Therefore, we conclude that government interventions to support additional rubber cultivation should also focus on ecosystem stabilization in order to minimize the risk of an ecological catastrophe that would significantly affect the economic prosperity of the region.

Towards a mechanistic understanding of variation in aquatic food chain length.

Ecologists have long sought to understand variation in food chain length (FCL) among natural ecosystems. Various drivers of FCL, including ecosystem size, resource productivity and disturbance, have been hypothesised. However, when results are aggregated across existing empirical studies from aquatic ecosystems, we observe mixed FCL responses to these drivers. To understand this variability, we develop a unified competition-colonisation framework for complex food webs incorporating all of these drivers. With competition-colonisation tradeoffs among basal species, our model predicts that increasing ecosystem size generally results in a monotonic increase in FCL, while FCL displays non-linear, oscillatory responses to resource productivity or disturbance in large ecosystems featuring little disturbance or high productivity. Interestingly, such complex responses mirror patterns in empirical data. Therefore, this study offers a novel mechanistic explanation for observed variations in aquatic FCL driven by multiple environmental factors.

Influence of upwelling on coral reef benthic communities: a systematic review and meta-analysis.

Highly competitive coral reef benthic communities are acutely sensitive to changes in environmental parameters such as temperature and nutrient concentrations. Physical oceanographic processes that induce upwelling therefore act as drivers of community structure on tropical reefs. How upwelling impacts coral communities, however, is not fully understood; upwelling may provide a natural buffer against climate impacts and could potentially enhance the efficacy of spatial management and reef conservation efforts. This study employed a systematic review to assess existing literature linking upwelling with reef community structure, and a meta-analysis to quantify upwelling impact on the percentage cover of coral reef benthic groups. We show that upwelling has context-dependant effects on the cover of hard coral and fleshy macroalgae, with effect size and direction varying with depth, region and remoteness. Fleshy macroalgae were found to increase by 110% on inhabited reefs yet decrease by 56% around one well-studied remote island in response to upwelling. Hard coral cover was not significantly impacted by upwelling on inhabited reefs but increased by 150% when direct local human pressures were absent. By synthesizing existing evidence, this review facilitates adaptive and nuanced reef management which considers the influence of upwelling on reef assemblages.

Modeling the enigma of complex disease etiology.

BACKGROUND: Complex diseases often present as a diagnosis riddle, further complicated by the combination of multiple phenotypes and diseases as features of other diseases. With the aim of enhancing the determination of key etiological factors, we developed and tested a complex disease model that encompasses diverse factors that in combination result in complex diseases. This model was developed to address the challenges of classifying complex diseases given the evolving nature of understanding of disease and interaction and contributions of genetic, environmental, and social factors. METHODS: Here we present a new approach for modeling complex diseases that integrates the multiple contributing genetic, epigenetic, environmental, host and social pathogenic effects causing disease. The model was developed to provide a guide for capturing diverse mechanisms of complex diseases. Assessment of disease drivers for asthma, diabetes and fetal alcohol syndrome tested the model. RESULTS: We provide a detailed rationale for a model representing the classification of complex disease using three test conditions of asthma, diabetes and fetal alcohol syndrome. Model assessment resulted in the reassessment of the three complex disease classifications and identified driving factors, thus improving the model. The model is robust and flexible to capture new information as the understanding of complex disease improves. CONCLUSIONS: The Human Disease Ontology's Complex Disease model offers a mechanism for defining more accurate disease classification as a tool for more precise clinical diagnosis. This broader representation of complex disease, therefore, has implications for clinicians and researchers who are tasked with creating evidence-based and consensus-based recommendations and for public health tracking of complex disease. The new model facilitates the comparison of etiological factors between complex, common and rare diseases and is available at the Human Disease Ontology website.

Browning, nutrient inputs, and fast vertical mixing from simulated extreme rainfall and wind stress alter estuarine phytoplankton productivity.

Browning and nutrient inputs from extreme rainfall, together with increased vertical mixing due to strong winds, are more frequent in coastal ecosystems; however, their interactive effects on phytoplankton are poorly understood. We conducted experiments to quantify how browning, together with different mixing speeds (fluctuating radiation), and a nutrient pulse alter primary productivity and photosynthetic efficiency in estuarine phytoplankton communities. Phytoplankton communities (grazers excluded) were exposed simultaneously to these drivers, and key photosynthetic targets were quantified: oxygen production, electron transport rates (ETRs), and carbon fixation immediately following collection and after a 2-d acclimation/adaptation period. Increasing mixing speeds in a turbid water column (e.g. browning) significantly decreased ETRs and carbon fixation in the short term. Acclimation/adaptation to this condition for 2 d resulted in an increase in nanoplanktonic diatoms and a community that was photosynthetically more efficient; however, this did not revert the decreasing trend in carbon fixation with increased mixing speed. The observed interactive effects (resulting from extreme rainfall and strong winds) may have profound implications in the trophodynamics of highly productive system such as the Southwest Atlantic Ocean due to changes in the size structure of the community and reduced productivity.

Ecosystem type drives soil eukaryotic diversity and composition in Europe.

Soil eukaryotes play a crucial role in maintaining ecosystem functions and services, yet the factors driving their diversity and distribution remain poorly understood. While many studies focus on some eukaryotic groups (mostly fungi), they are limited in their spatial scale. Here, we analyzed an unprecedented amount of observational data of soil eukaryomes at continental scale (787 sites across Europe) to gain further insights into the impact of a wide range of environmental conditions (climatic and edaphic) on their community composition and structure. We found that the diversity of fungi, protists, rotifers, tardigrades, nematodes, arthropods, and annelids was predominantly shaped by ecosystem type (annual and permanent croplands, managed and unmanaged grasslands, coniferous and broadleaved woodlands), and higher diversity of fungi, protists, nematodes, arthropods, and annelids was observed in croplands than in less intensively managed systems, such as coniferous and broadleaved woodlands. Also in croplands, we found more specialized eukaryotes, while the composition between croplands was more homogeneous compared to the composition of other ecosystems. The observed high proportion of overlapping taxa between ecosystems also indicates that DNA has accumulated from previous land uses, hence mimicking the land transformations occurring in Europe in the last decades. This strong ecosystem-type influence was linked to soil properties, and particularly, soil pH was driving the richness of fungi, rotifers, and annelids, while plant-available phosphorus drove the richness of protists, tardigrades, and nematodes. Furthermore, the soil organic carbon to total nitrogen ratio crucially explained the richness of fungi, protists, nematodes, and arthropods, possibly linked to decades of agricultural inputs. Our results highlighted the importance of long-term environmental variables rather than variables measured at the time of the sampling in shaping soil eukaryotic communities, which reinforces the need to include those variables in addition to ecosystem type in future monitoring programs and conservation efforts.

Soils in warmer and less developed countries have less micronutrients globally.

Soil micronutrients are capital for the delivery of ecosystem functioning and food provision worldwide. Yet, despite their importance, the global biogeography and ecological drivers of soil micronutrients remain virtually unknown, limiting our capacity to anticipate abrupt unexpected changes in soil micronutrients in the face of climate change. Here, we analyzed >1300 topsoil samples to examine the global distribution of six metallic micronutrients (Cu, Fe, Mn, Zn, Co and Ni) across all continents, climates and vegetation types. We found that warmer arid and tropical ecosystems, present in the least developed countries, sustain the lowest contents of multiple soil micronutrients. We further provide evidence that temperature increases may potentially result in abrupt and simultaneous reductions in the content of multiple soil micronutrients when a temperature threshold of 12-14°C is crossed, which may be occurring on 3% of the planet over the next century. Altogether, our findings provide fundamental understanding of the global distribution of soil micronutrients, with direct implications for the maintenance of ecosystem functioning, rangeland management and food production in the warmest and poorest regions of the planet.

Aging varies greatly within a single genus: A demographic study of Rhododendron spp. in botanic gardens.

PREMISE: There is mounting evidence that age matters in plant demography, but also indications that relationships between age and demographic rates may vary significantly among species. Age-based plant demographic data, however, are time-consuming to collect and still lacking for most species, and little is known about general patterns across species or what may drive differences. METHODS: We used individual birth and death records for 12 Rhododendron species from botanic gardens and conducted Bayesian survival trajectory analyses to assess how mortality changed with age. We calculated the demographic measures of aging rate, life-span equality, and life expectancy for each species, and assessed their relationships with the climatic conditions at species' sites of ancestral origin and with taxonomic group (subgenus). RESULTS: We found substantial among-species variation in survival trajectories, with mortality increasing, decreasing, or remaining constant with advancing age. Moreover, we found no relationships between demographic measures and ancestral climatic conditions but there were statistically significant differences among taxonomic groups in the rate of change in mortality with age (aging rate). CONCLUSIONS: We conclude that demographic consequences of aging can differ qualitatively, even among species in the same genus. In addition, taxonomic trends in aging rates indicate they may be genetically determined, though evolutionary drivers are still unclear. Furthermore, we suggest there is untapped potential in using botanic garden records in future studies on plant life history.

Copper and temperature shaped abundant and rare community assembly respectively in the Yellow River.

Untangling assembly and microbial interaction of abundant and rare microbiota in aquatic ecosystem is pivotal for understanding how community assembly respond to environmental variables and co-occurrence patterns. Here, we explored the assembly mechanisms, their drivers, and species co-occurrence of abundant and rare microbiomes in the Yellow River using 16S rRNA gene sequencing in Lanzhou, China. Here, abundant community was ubiquitous across all sites, whereas rare community was uneven distributed. The richness and community dissimilarity of rare taxa were significantly greater than those of abundant ones. Stochastic processes structured the rare community assembly in spring and winter, while deterministic processes shaped the abundant and rare community assembly in other seasons and all sites. Copper and water temperature mediated the balance between deterministic and stochastic processes of abundant and rare community, respectively. A few abundant taxa with closer relationships frequently occupied central positions and had a great effect on other co-occurrences in the network, while the majority of keystone microbiota were rare microbiome and played a considerable part in maintaining the network structure. Our study provides some ecological proposals for water quality management and ecological stability of the Yellow River. KEY POINTS: • Deterministic process dominated abundant and rare community assembly. • Cu and TW mediated the balance of abundant and rare community assembly respectively. • Abundant taxa had a greater effect on other co-occurrences in the network.

Twenty-year record of white pox disease in the Florida Keys: importance of environmental risk factors as drivers of coral health.

Declining coral populations worldwide place a special premium on identifying risks and drivers that precipitate these declines. Understanding the relationship between disease outbreaks and their drivers can help to anticipate when the risk of a disease pandemic is high. Populations of the iconic branching Caribbean elkhorn coral Acropora palmata have collapsed in recent decades, in part due to white pox disease (WPX). To assess the role that biotic and abiotic factors play in modulating coral disease, we present a predictive model for WPX in A. palmata using 20 yr of disease surveys from the Florida Keys plus environmental information collected simultaneously in situ and via satellite. We found that colony size was the most influential predictor for WPX occurrence, with larger colonies being at higher risk. Water quality parameters of dissolved oxygen saturation, total organic carbon, dissolved inorganic nitrogen, and salinity were implicated in WPX likelihood. Both low and high wind speeds were identified as important environmental drivers of WPX. While high temperature has been identified as an important cause of coral mortality in both bleaching and disease scenarios, our model indicates that the relative influence of HotSpot (positive summertime temperature anomaly) was low and actually inversely related to WPX risk. The predictive model developed here can contribute to enabling targeted strategic management actions and disease surveillance, enabling managers to treat the disease or mitigate disease drivers, thereby suppressing the disease and supporting the persistence of corals in an era of myriad threats.