Stochastic processes drive divergence of bacterial and fungal communities in sympatric wild insect species despite sharing a common diet.

Arthropods harbor complex microbiota that play a pivotal role in host fitness. While multiple factors, like host species and diet, shape microbiota in arthropods, their impact on community assembly in wild insects remains largely unknown. In this study, we surveyed bacterial and fungal community assembly in nine sympatric wild insect species that share a common citrus fruit diet. Source tracking analysis suggested that these insects acquire some bacteria and fungi from the citrus fruit with varying degrees. Although sharing a common diet led to microbiota convergence, the diversity, composition, and network of both bacterial and fungal communities varied significantly among surveyed insect groups. Null model analysis indicated that stochastic processes, particularly dispersal limitation and drift, are primary drivers of structuring insect bacterial and fungal communities. Importantly, the influence of each community assembly process varied strongly depending on the host species. Thus, we proposed a speculative view that the host specificity of the microbiome and mycobiome assembly is widespread in wild insects despite sharing the same regional species pool. Overall, this research solidifies the importance of host species in shaping microbiomes and mycobiomes, providing novel insights into their assembly mechanisms in wild insects. IMPORTANCE: Since the microbiome has been shown to impact insect fitness, a mechanistic understanding of community assembly has potentially significant applications but remains largely unexplored. In this paper, we investigate bacterial and fungal community assembly in nine sympatric wild insect species that share a common diet. The main findings indicate that stochastic processes drive the divergence of microbiomes and mycobiomes in nine sympatric wild insect species. These findings offer novel insights into the assembly mechanisms of microbiomes and mycobiomes in wild insects.

Mechanisms of bacterial and fungal community assembly in leaf miners during transition from natural to laboratory environments.

Environmental heterogeneity partly drives microbial succession in arthropods, while the microbial assembly mechanisms during environmental changes remain largely unknown. Here, we explored the temporal dynamics and assembly mechanisms within both bacterial and fungal communities in Liriomyza huidobrensis (Blanchard) during the transition from field to laboratory conditions. We observed a decrease in bacterial diversity and complexity of bacterial-fungal co-occurrence networks in leaf miners transitioning from wild to captive environments. Both neutral and null models revealed that stochastic processes, particularly drift (contributing over 70%), play a crucial role in governing bacterial and fungal community assembly. The relative contribution of ecological processes such as dispersal, drift, and selection varied among leaf miners transitioning from wild to captive states. Furthermore, we propose a hypothetical scenario for the assembly and succession of microbial communities in the leaf miner during the short- and long-term transition from the wild to captivity. Our findings suggest that environmental heterogeneity determines the ecological processes governing bacterial and fungal community assembly in leaf miners, offering new insights into microbiome and mycobiome assembly mechanisms in invasive pests amidst environmental change.

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.

On null models for temporal small-worldness in brain dynamics.

Brain dynamics can be modeled as a temporal brain network starting from the activity of different brain regions in functional magnetic resonance imaging (fMRI) signals. When validating hypotheses about temporal networks, it is important to use an appropriate statistical null model that shares some features with the treated empirical data. The purpose of this work is to contribute to the theory of temporal null models for brain networks by introducing the random temporal hyperbolic (RTH) graph model, an extension of the random hyperbolic (RH) graph, known in the study of complex networks for its ability to reproduce crucial properties of real-world networks. We focus on temporal small-worldness which, in the static case, has been extensively studied in real-world complex networks and has been linked to the ability of brain networks to efficiently exchange information. We compare the RTH graph model with standard null models for temporal networks and show it is the null model that best reproduces the small-worldness of resting brain activity. This ability to reproduce fundamental features of real brain networks, while adding only a single parameter compared with classical models, suggests that the RTH graph model is a promising tool for validating hypotheses about temporal brain networks.

We show that the random temporal hyperbolic (RTH) graph is a suitable null model for testing hypotheses about brain dynamics, after comparing it with the current state of the art and two other geometric null models. The static version of this theoretical model captures properties of various real-world networks, and its temporal version exhibits the temporal small-world property, for which we propose a new proper temporal definition. In particular, we show that the model best reproduces the temporal small-worldness measured in the empirical temporal network extracted from fMRI signals.

Diversity and ecological assembly process of aerobic anoxygenic phototrophic bacteria in a low irradiation area, Three Gorges Reservoir.

Aerobic anoxygenic phototrophic bacteria (AAPB) are significant bacterial groups in aquatic ecosystems, known for their rapid growth and photoheterotrophic characteristics. However, the distribution and ecological assembly process of AAPB in low irradiation freshwater basins remain unclear, warranting further investigation. In this study, we present the diversity, abundance, spatial variations, ecological process, and community interaction of AAPB in sediment of Three Gorges Reservoir (TGR) under low irradiation. Our findings demonstrate the dominant genera of AAPB community that exist in the TGR area also are appeared in different waters, with some regional preference. Moreover, the concentration of pufM gene, an indicator for AAPB, maintains a consistently high numerical level ranging from (2.21 ± 0.44) × 104 to (9.98 ± 0.30) × 107 gene copies/g. Although solar irradiation is suggested as the major factor affecting AAPB, it remains unclear whether and how AAPB differ between regions due to varying solar irradiation levels. Our results show spatial differences between total bacteria and AAPB communities, with significant differences observed only in AAPB. Geographical and environmental factor contributed less than 10% to the spatial difference of community, with sediment type and environmental factors being the key factors influencing microbial community structure. The stochastic process plays a dominant role in the aggregation and replacement of AAPB communities, among which the most contribution is dispersal limitation. For AAPB network, Yoonia and Gemmobacter are the hubs for modules. Those results valuable insights into the AAPB communities in TGR with low irradiation.

The siren song of so-called evidence: Why the evidence for social ecology models is not as strong as we think.

Ecological competition models from biology have been adopted for the study of a wide variety of social entities, including workplace organizations and voluntary associations.Despite their popularity, a number of fundamental challenges to these models have not been sufficiently recognized or addressed. As a result, it's possible that some apparently supportive evidence for ecological competition is in fact the outcome of chance or other processes. We propose a permutation test to compare observed evidence for ecological competition against an appropriate counterfactual population. To demonstrate our approach and validate our concern about the quality of evidence for ecological competition models, we apply the permutation test to one specific case. The results indicate that K-correlation values that have been taken as evidence for a well-established model, the Ecology of Affiliation, are quite common even in the absence of ecological competition. We conclude that the existing evidence for social ecology models may not be as reliable as commonly believed due to the disconnect between theory and empirical testing.

Soil microbial subcommunity assembly mechanisms are highly variable and intimately linked to their ecological and functional traits.

Revealing the mechanisms underlying soil microbial community assembly is a fundamental objective in molecular ecology. However, despite increasing body of research on overall microbial community assembly mechanisms, our understanding of subcommunity assembly mechanisms for different prokaryotic and fungal taxa remains limited. Here, soils were collected from more than 100 sites across southwestern China. Based on amplicon high-throughput sequencing and iCAMP analysis, we determined the subcommunity assembly mechanisms for various microbial taxa. The results showed that dispersal limitation and homogenous selection were the primary drivers of soil microbial community assembly in this region. However, the subcommunity assembly mechanisms of different soil microbial taxa were highly variable. For instance, the contribution of homogenous selection to Crenarchaeota subcommunity assembly was 70%, but it was only around 10% for the subcommunity assembly of Actinomycetes, Gemmatimonadetes and Planctomycetes. The assembly of subcommunities including microbial taxa with higher occurrence frequencies, average relative abundance and network degrees, as well as wider niches tended to be more influenced by homogenizing dispersal and drift, but less affected by heterogeneous selection and dispersal limitation. The subcommunity assembly mechanisms also varied substantially among different functional guilds. Notably, the subcommunity assembly of diazotrophs, nitrifiers, saprotrophs and some pathogens were predominantly controlled by homogenous selection, while that of denitrifiers and fungal pathogens were mainly affected by stochastic processes such as drift. These findings provide novel insights into understanding soil microbial diversity maintenance mechanisms, and the analysis pipeline holds significant value for future research.

Use of trophic ecology of omnivorous fish and abiotic factors as supporting tools for assessing environmental impacts in a neotropical river.

The study of diet is one of the mechanisms by which competition for resources between species that cohabit in the same ecosystem can be inferred. Therefore, the relationships of the indices that measure specialization in the diet of fish species are necessary to characterize the nutritional quality of these populations and the ecosystem's environmental health. Three species of catfish were selected: one invasive (Clarias gariepinus) and two natives (Trachelyopterus striatulus and Rhamdia quelen), with similar distribution along the Guapi-Macacu River, in the Guapimirim Protection Area (Rio de Janeiro). Fifty-nine catfish of the three species were collected in total, along 32 collection points in the Guapi-Macacu River in two periods (dry and rainy) in 2018. Non-parametric statistics showed the partition of resources between species and the influence of abiotic factors (temperature, pH, transparency, and dissolved oxygen) contributing to the selection of available resources in the environment. Diet-related indices-repletion index (RI), condition factor (K), niche width, and trophic position (TP) of the specimens collected-contributed to measuring the nutritional status of each of these catfish species, showing that R. quelen has a relationship between RI and K, tending to absorb and metabolize nutrients faster than other species. In addition, the invasive species occupies a wide range of TPs compared to native species, confirming its feeding plasticity. On the contrary, T. striatulus needs large amounts of terrestrial insects to maintain its poor condition factor. Also, the RI showed direct influences of abiotic variables, with the temperature being the most prominent. Our results suggest that the invasive species can benefit from this environment that shows signs of environmental degradation.

Economic impact disharmony in global biological invasions.

A dominant syndrome of the Anthropocene is the rapid worldwide spread of invasive species with devastating environmental and socio-economic impacts. However, the dynamics underlying the impacts of biological invasions remain contested. A hypothesis posits that the richness of impactful invasive species increases proportionally with the richness of non-native species more generally. A competing hypothesis suggests that certain species features disproportionately enhance the chances of non-native species becoming impactful, causing invasive species to arise disproportionately relative to the numbers of non-native species. We test whether invasive species with reported monetary costs reflect global numbers of established non-native species among phyla, classes, and families. Our results reveal that numbers of invasive species with economic costs largely reflect non-native species richness among taxa (i.e., in 96 % of families). However, a few costly taxa were over- and under-represented, and their composition differed among environments and regions. Chordates, nematodes, and pathogenic groups tended to be the most over-represented phyla with reported monetary costs, with mammals, insects, fungi, roundworms, and medically-important microorganisms being over-represented classes. Numbers of costly invasive species increased significantly with non-native richness per taxon, while monetary cost magnitudes at the family level were also significantly related to costly invasive species richness. Costs were biased towards a few 'hyper-costly' taxa (such as termites, mosquitoes, cats, weevils, rodents, ants, and asters). Ordination analysis revealed significant dissimilarity between non-native and costly invasive taxon assemblages. These results highlight taxonomic groups which harbour disproportionately high numbers of costly invasive species and monetary cost magnitudes. Collectively, our findings support prevention of arrival and containment of spread of non-native species as a whole through effective strategies for mitigation of the rapidly amplifying impacts of invasive species. Yet, the hyper- costly taxa identified here should receive greater focus from managers to reduce impacts of current invasive species.

Soil salinity is the main factor influencing the soil bacterial community assembly process under long-term drip irrigation in Xinjiang, China.

Identifying the potential factors associated with the impact of long-term drip irrigation (DI) on soil ecosystems is essential for responding to the environmental changes induced by extensive application of DI technology in arid regions. Herein, we examined the effects of the length of time that DI lasts in years (NDI) on soil bacterial diversity as well as the soil bacterial community assembly process and the factors influencing it. The results showed that long-term DI substantially reduced soil salinity and increased soil bacterial diversity while affecting the soil bacterial community structure distinctly. Null model results showed that the soil bacterial community assembly transitioned from stochastic processes to deterministic processes, as NDI increased. Homogeneous selection, a deterministic process, emerged as the dominant process when NDI exceeded 15 years. Both random forest and structural equation models showed that soil salinity was the primary factor affecting the bacterial community assembly process. In summary, this study suggested that soil bacteria respond differently to long-term DI and depends on the NDI, influencing the soil bacterial community assembly process under long-term DI.

Resolving inter-regional communication capacity in the human connectome.

Applications of graph theory to the connectome have inspired several models of how neural signaling unfolds atop its structure. Analytic measures derived from these communication models have mainly been used to extract global characteristics of brain networks, obscuring potentially informative inter-regional relationships. Here we develop a simple standardization method to investigate polysynaptic communication pathways between pairs of cortical regions. This procedure allows us to determine which pairs of nodes are topologically closer and which are further than expected on the basis of their degree. We find that communication pathways delineate canonical functional systems. Relating nodal communication capacity to meta-analytic probabilistic patterns of functional specialization, we also show that areas that are most closely integrated within the network are associated with higher order cognitive functions. We find that these regions' proclivity towards functional integration could naturally arise from the brain's anatomical configuration through evenly distributed connections among multiple specialized communities. Throughout, we consider two increasingly constrained null models to disentangle the effects of the network's topology from those passively endowed by spatial embedding. Altogether, the present findings uncover relationships between polysynaptic communication pathways and the brain's functional organization across multiple topological levels of analysis and demonstrate that network integration facilitates cognitive integration.

Resistance of aerobic granular sludge microbiomes to periodic loss of biomass.

Granular sludge is a biofilm process used for wastewater treatment which is currently being implemented worldwide. It is important to understand how disturbances affect the microbial community and performance of reactors. Here, two acetate-fed replicate reactors were inoculated with acclimatized sludge and the reactor performance, and the granular sludge microbial community succession were studied for 149 days. During this time, the microbial community was challenged by periodically removing half of the reactor biomass, subsequently increasing the food-to-microorganism (F/M) ratio. Diversity analysis together with null models show that overall, the microbial communities were resistant to the disturbances, observing some minor effects on polyphosphate-accumulating and denitrifying microbial communities and their associated reactor functions. Community turnover was driven by drift and random granule loss, and stochasticity was the governing ecological process for community assembly. These results evidence the aerobic granular sludge process as a robust system for wastewater treatment.

Deterministic processes dominate archaeal community assembly from the Pearl River to the northern South China Sea.

Archaea play a significant role in the biogeochemical cycling of nutrients in estuaries. However, comprehensive researches about their assembly processes remain notably insufficient. In this study, we systematically examined archaeal community dynamics distinguished between low-salinity and high-salinity groups in water and surface sediments over a 600-kilometer range from the upper Pearl River (PR) to the northern South China Sea (NSCS). Neutral community model analysis together with null model analysis showed that their C-score values were greater than 2, suggesting that deterministic processes could dominate the assembly of those planktonic or benthic archaeal communities at both the low-salinity and high-salinity sites. And deterministic processes contributed more in the low-salinity than high-salinity environments from the PR to the NSCS. Furthermore, through the co-occurrence network analysis, we found that the archaeal communities in the low-salinity groups possessed closer interactions and higher proportions of negative interactions than those in the high-salinity groups, which might be due to the larger environmental heterogeneities reflected by the nutrient concentrations of those low-salinity samples. Collectively, our work systematically investigated the composition and co-occurrence networks of archaeal communities in water as well as sediments from the PR to the NSCS, yielding new insights into the estuary's archaeal community assembly mechanisms.

Inferring microbial community assembly in an urban river basin through geo-multi-omics and phylogenetic bin-based null-model analysis of surface water.

Understanding the community assembly process is a central issue in microbial ecology. In this study, we analyzed the community assembly of particle-associated (PA) and free-living (FL) surface water microbiomes in 54 sites from the headstream to the river mouth of an urban river in Japan, the river basin of which has the highest human population density in the country. Analyses were conducted from two perspectives: (1) analysis of deterministic processes considering only environmental factors using a geo-multi-omics dataset and (2) analysis of deterministic and stochastic processes to estimate the contributions of heterogeneous selection (HeS), homogeneous selection (HoS), dispersal limitation (DL), homogenizing dispersal (HD), and drift (DR) as community assembly processes using a phylogenetic bin-based null model. The variation in microbiomes was successfully explained from a deterministic perspective by environmental factors, such as organic matter-related, nitrogen metabolism, and salinity-related parameters, using multivariate statistical analysis, network analysis, and habitat prediction. In addition, we demonstrated the dominance of stochastic processes (DL, HD, and DR) over deterministic processes (HeS and HoS) in community assembly from both deterministic and stochastic perspectives. Our analysis revealed that as the distance between two sites increased, the effect of HoS sharply decreased while the effect of HeS increased, particularly between upstream and estuary sites, indicating that the salinity gradient could potentially enhance the contribution of HeS to community assembly. Our study highlights the importance of both stochastic and deterministic processes in community assembly of PA and FL surface water microbiomes in urban riverine ecosystems.

Taxon-dependent effects of dispersal limitation versus environmental filters on bryophyte assemblages-Multiple perspective studies in land-bridge islands.

To explore the taxon-dependent contribution of dispersal limitation versus environmental filters to bryophyte assemblages. We investigated bryophytes and six environmental variables on 168 islands in the Thousand Island Lake,China. We compared the observed beta diversity with the expected values based on six null models (EE, EF, FE, FF, PE, and PF), detected the partial correlation of beta diversity with geographical distances. We quantified the contributions of spatial versus environmental variables and island isolation per se to species composition (SC) using variance partitioning. We modeled the species-area relationships (SARs) for bryophytes and the other eight biotas. To explore the taxon-dependent effects of spatial versus environmental filters on bryophytes, 16 taxa including five categories (total bryophytes, total mosses, liverworts, acrocarpous, and pleurocarpous mosses) and 11 species-richest families were included in the analyses. The observed beta diversity values were significantly different from the predicted values for all 16 taxa. For all five categories, the observed partial correlations between beta diversity and geographical distance after controlling environmental effects were not only positive, but also significantly different from the predicted values based on the null models. Spatial eigenvectors are more important in shaping SC than environmental variables for all 16 taxa except Brachytheciaceae and Anomodontaceae. Spatial eigenvectors contributed more to SC variation in liverworts than in mosses and in pleurocarpous mosses than in acrocarpous mosses. The effects of island isolation on SC were significant for all five categories, highly varied at the family level. The z values of the SARs for the five bryophyte categories were all larger than those of the other eight biotas. In subtropical fragmented forests, dispersal limitation exerted significant, taxon-dependent effects on bryophyte assemblages. It was dispersal limitation rather than environmental filtering that predominantly regulated the SC patterns of bryophytes.

Factors at multiple scales drive parasite community structure.

Understanding how ecological communities are assembled remains a key goal of ecosystem ecology. Because communities are hierarchical, factors acting at multiple scales can contribute to patterns of community structure. Parasites provide a natural system to explore this idea, as they exist as discrete communities within host individuals, which are themselves part of a community and metacommunity. We aimed to understand the relative contribution of multi-scale drivers in parasite community assembly and assess how patterns at one level may mask those occurring at another. Specifically, we wanted to disentangle patterns caused by passive sampling from those determined by ecological drivers, and how these vary with scale. We applied a Markov Random Fields model and assessed measures of ß-diversity and nestedness for 420 replicate parasite infracommunities (parasite assemblages in host individuals) across two freshwater mussel host species, three sites and two time periods, comparing our results to simulations from four different ecologically relevant null models. We showed that ß-diversity between sites (explaining 25% of variation in parasite distribution) and host species (41%) is greater than expected, and ß-diversity between individual hosts is smaller than expected, even after accounting for parasite prevalence and characteristics of host individuals. Furthermore, parasite communities were significantly less nested than expected once parasite prevalence and host characteristics were both accounted for, but more nested than expected otherwise, suggesting a degree of modularity at the within-host level that is masked if underlying host and parasite characteristics are not taken into account. The Markov Random Fields model provided evidence for possible competitive within-host parasite interactions, providing a mechanism for the observed infracommunity modularity. An integrative approach that examines factors at multiple scales is necessary to understand the composition of ecological communities. Furthermore, patterns at one level can alter the interpretation of ecologically important drivers at another if variation at higher scales is not accounted for.

Changes in plant community assembly from patchy degradation of grasslands and grazing by different-sized herbivores.

Grassland degradation caused by increases in livestock grazing threatens a variety of ecosystem services. Understanding changes in plant community assembly during the process of grassland degradation in the presence of grazing is important to help restore degraded grasslands worldwide but has received little attention thus far. The grassland degradation process is typified by heterogeneous degradation, that is, gradual formation of degraded patches (hereafter "patchy degradation"). Here, we experimentally examined the effects of herbivore grazing and patchy degradation on plant community assembly using nine pairs of non-degraded (intact) and patch-degraded (fragmented) grasslands subject to grazing by different-sized herbivores (i.e., NG, no grazing; SG, sheep grazing; CG, cattle grazing) over 4 years. Using a null-model approach, we estimated the relative magnitude of deterministic processes of community assembly by comparing the observed and expected ß-diversity. We found that in the absence of herbivore grazing, deterministic processes played a greater role in community assembly, regardless of whether patchy degradation had occurred. However, the deterministic processes resulted in plant communities being more spatially similar in non-degraded grasslands while being more dissimilar in patchy degraded grasslands. Compared with non-degraded grasslands, species with strong competitive abilities (i.e., Leymus chinensis) were less dominant in patchy degraded grasslands, indicating relaxed competition and a reduced role of species interactions over plant communities. Instead, patchy degradation added the role of environmental variables over plant communities. SG consistently promoted more stochastic plant community assembly in both non-degraded and patch-degraded grasslands, while CG promoted more stochastic plant community assembly only in the non-degraded state, having no effect in the patch-degraded state. Our study offers important insights into changes in plant community assembly during ongoing patch-degradation of grasslands, indicating the role of increased environmental filtering of soil and reduced species interactions in driving plant community dynamics with increasing grassland patchy degradation. We also uncovered an herbivore species-specific effect on plant community assembly during the process of grassland degradation, which will better inform and improve future grassland restoration planning efforts.

Local stressors mask the effects of warming in freshwater ecosystems.

Climate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this knowledge gap by testing the ability of three contrasting null models to predict the joint impacts of warming and a range of other aquatic stressors using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were usually best explained by the effect of the stronger stressor alone (the dominance null model), especially if this stressor was a local disturbance associated with human land use. Prediction accuracy depended on stressor identity and how asymmetric stressors were in the magnitude of their effects. These findings suggest we can effectively predict the impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration, nutrients and contamination often override the biological consequences of higher temperatures in freshwater ecosystems.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Diversity and Selection of Surface Marine Microbiomes in the Atlantic-Influenced Arctic.

Arctic marine environments are experiencing rapid changes due to the polar amplification of global warming. These changes impact the habitat of the cold-adapted microbial communities, which underpin biogeochemical cycles and marine food webs. We comparatively investigated the differences in prokaryotic and microeukaryotic taxa between summer surface water microbiomes sampled along a latitudinal transect from the ice-free southern Barents Sea and into the sea-ice-covered Nansen Basin to disentangle the dominating community (ecological) selection processes driving phylogenetic diversity. The community structure and richness of each site-specific microbiome were assessed in relation to the physical and biogeochemical conditions of the environment. A strong homogeneous deterministic selection process was inferred across the entire sampling transect via a phylogenetic null modeling approach. The microbial species richness and diversity were not negatively influenced by northward decreasing temperature and salinity. The results also suggest that regional phytoplankton blooms are a major prevalent factor in governing the bacterial community structure. This study supports the consideration that strong homogeneous selection is imposed across these cold-water marine environments uniformly, regardless of geographic assignments within either the Nansen Basin or the Barents Sea.