Impact of climate zones and seasons on indoor airborne microbial communities: Insights from a comprehensive analysis.

Bacteria and fungi are ubiquitous throughout built environments and are suspended in the air, potentially affecting human health. However, the impacts of climate zones on the diversity, structure, and stochastic assembly of indoor airborne microbes remain unknown. This study comprehensively analyzed indoor airborne microbes across five climate zones in China during the summer and winter using high-throughput sequencing. The diversity and structure of indoor airborne communities vary across climatic zones. A random forest model was used to identify biomarkers in different climate zones. The results showed no relationship between the biomarkers and their rankings in mean relative abundance. The Sloan neutral model fitting results indicated that the impact of climate zones on the stochastic process in the assembly of indoor airborne microbes was considerably more important than that of seasons. Additionally, the influence of seasons on the diversity, structure, and stochastic assembly process of indoor airborne microbes differed among different climate zones. The diversity, structure, and stochastic assembly processes of bacteria present distinctive outcomes in climate zones and seasons compared with those of fungi. Overall, these findings indicate that customized strategies are necessary to manage indoor airborne microbial communities in each climate zone, season, and for specific microbial species.

Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes.

BACKGROUND: Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists' (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies-amplicon sequencing and whole-genome (shotgun sequencing)-respectively generate two contrastingly different categories of metagenomic reads (data)-OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes. RESULTS: The ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan's near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project. CONCLUSIONS: All of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.

Accounting for the microbial assembly of each process in wastewater treatment plants (WWTPs): study of four WWTPs receiving similar influent streams.

We evaluated a unique model in which four full-scale wastewater treatment plants (WWTPs) with the same treatment schematic and fed with similar influent wastewater were tracked over an 8-month period to determine whether the community assembly would differ in the activated sludge (AS) and sand filtration (SF) stages. For each WWTP, AS and SF achieved an average of 1-log10 (90%) and <0.02-log10 (5%) reduction of total cells, respectively. Despite the removal of cells, both AS and SF had a higher alpha and beta diversity compared to the influent microbial community. Using the Sloan neutral model, it was observed that AS and SF were individually dominated by different assembly processes. Specifically, microorganisms from influent to AS were predominantly determined by the selective niche process for all WWTPs, while the microbial community in the SF was relatively favored by a stochastic, random migration process, except two WWTPs. AS also contributed more to the final effluent microbial community compared with the SF. Given that each WWTP operates the AS independently and that there is a niche selection process driven mainly by the chemical oxygen demand concentration, operational taxonomic units unique to each of the WWTPs were also identified. The findings from this study indicate that each WWTP has its distinct microbial signature and could be used for source-tracking purposes.IMPORTANCEThis study provided a novel concept that microorganisms follow a niche assembly in the activated sludge (AS) tank and that the AS contributed more than the sand filtration process toward the final microbial signature that is unique to each treatment plant. This observation highlights the importance of understanding the microbial community selected by the AS stage, which could contribute toward source-tracking the effluent from different wastewater treatment plants.

Quantifying Stochastic Processes in Shaping Dissolved Organic Matter Pool with High-Resolution Mass Spectrometry.

Natural dissolved organic matter (DOM) represents a ubiquitous molecular mixture, progressively characterized by spatiotemporal resolution. However, an inadequate comprehension of DOM molecular dynamics, especially the stochastic processes involved, hinders carbon cycling predictions. This study employs ecological principles to introduce a neutral theory to elucidate the fundamental processes involving molecular generation, degradation, and migration. A neutral model is thus formulated to assess the probability distribution of DOM molecules, whose frequencies and abundances follow a ß-distribution relationship. The neutral model is subsequently validated with high-resolution mass spectrometry (HRMS) data from various waterbodies, including lakes, rivers, and seas. The model fitting highlights the prevalence of molecular neutral distribution and quantifies the stochasticity within DOM molecular dynamics. Furthermore, the model identifies deviations of HRMS observations from neutral expectations in photochemical and microbial experiments, revealing nonrandom molecular transformations. The ecological null model further validates the neutral modeling results, demonstrating that photodegradation reduces molecular stochastic dynamics at the surface of an acidic pit lake, while random distribution intensifies at the river surface compared with the porewater. Taken together, the DOM molecular neutral model emphasizes the significance of stochastic processes in shaping a natural DOM pool, offering a potential theoretical framework for DOM molecular dynamics in aquatic and other ecosystems.

Seasonal assembly of skin microbiota driven by neutral and selective processes in the greater horseshoe bat.

Skin microbiota play an important role in protecting bat hosts from the fungal pathogen Pseudogymnoascus destructans, which has caused dramatic bat population declines and extinctions. Recent studies have provided insights into the bacterial communities of bat skin, but variation in skin bacterial community structure in the context of the seasonal dynamics of fungal invasion, as well as the processes that drive such variation, remain largely unexplored. In this study, we characterized bat skin microbiota over the course of the bat hibernation and active season stages and used a neutral model of community ecology to determine the relative roles of neutral and selective processes in driving microbial community variation. Our results showed significant seasonal shifts in skin community structure, as well as less diverse microbiota in hibernation than in the active season. Skin microbiota were influenced by the environmental bacterial reservoir. During both the hibernation and active season stages, more than 78% of ASVs in bat skin microbiota were consistent with neutral distribution, implying that neutral processes, that is, dispersal or ecological drift contributing the most to shifts in skin microbiota. In addition, the neutral model showed that some ASVs were actively selected by the bats from the environmental bacterial reservoir, accounting for approximately 20% and 31% of the total community during hibernation and active season stages, respectively. Overall, this research provides insights into the assemblage of bat-associated bacterial communities and will aid in the development of conservation strategies against fungal disease.

Biofilm thickness controls the relative importance of stochastic and deterministic processes in microbial community assembly in moving bed biofilm reactors.

Deterministic and stochastic processes are believed to play a combined role in microbial community assembly, though little is known about the factors determining their relative importance. We investigated the effect of biofilm thickness on community assembly in nitrifying moving bed biofilm reactors using biofilm carriers where maximum biofilm thickness is controlled. We examined the contribution of stochastic and deterministic processes to biofilm assembly in a steady state system using neutral community modelling and community diversity analysis with a null-modelling approach. Our results indicate that the formation of biofilms results in habitat filtration, causing selection for phylogenetically closely related community members, resulting in a substantial enrichment of Nitrospira spp. in the biofilm communities. Stochastic assembly processes were more prevalent in biofilms of 200 µm and thicker, while stronger selection in thinner (50 µm) biofilms could be driven by hydrodynamic and shear forces at the biofilm surface. Thicker biofilms exhibited greater phylogenetic beta-diversity, which may be driven by a variable selection regime caused by variation in environmental conditions between replicate carrier communities, or by drift combined with low migration rates resulting in stochastic historical contingency during community establishment. Our results indicate that assembly processes vary with biofilm thickness, contributing to our understanding of biofilm ecology and potentially paving the way towards strategies for microbial community management in biofilm systems.

Wastewater treatment plant effluent discharge decreases bacterial community diversity and network complexity in urbanized coastal sediment.

The wastewater treatment plant (WWTP) effluent discharge affects the microorganisms in the receiving water bodies. Despite the ecological significance of microbial communities in pollutant degradation and element cycling, how the community diversity is affected by effluent remains obscure. Here, we compared the sediment bacterial communities exposed to different intensities of WWTP effluent discharge in Hangzhou Bay, China: i) a severely polluted area that receives effluent from an industrial WWTP, ii) a moderately polluted area that receives effluent from a municipal WWTP, and iii) less affected area that inner the bay. We found that the sediment bacterial diversity decreased dramatically with pollution levels of inorganic nutrients, heavy metals, and organic halogens. Microbial community assembly model analysis revealed increased environmental selection and decreased species migration rate in the severely polluted area, resulting in high phylogenetic clustering of the bacterial communities. The ecological networks were less complex in the two WWTP effluent receiving areas than in the inner bay area, as suggested by the smaller network size and lower modularity. Fewer negative network associations were detected in the severely (6.7%) and moderately (8.3%) polluted areas than in the less affected area (16.7%), indicating more collaborative inter-species behaviors are required under stressful environmental conditions. Overall, our results reveal the fundamental impacts of WWTP effluents on the ecological processes shaping coastal microbial communities and point to the potential adverse effects of diversity loss on ecosystem functions.

The Memory Problem for Neutral Mutational Models of Evolution.

Models for the evolution of various phenotypes are sometimes constructed with an assumption that mutational effects will be symmetrically distributed about a static mean. This model produces a memory effect that over long evolutionary times results in an expectation that randomized sequences underlying the genetic architecture of the trait will on average retain the ancestral phenotype. This expectation is unrealistic and also inconsistent with our current understanding of processes of molecular evolution.

Improving the realism of neutral ecological models by incorporating transient dynamics with temporal changes in community size.

Neutral models in ecology assume that all species are demographically equivalent, such that their abundances differ ultimately because of demographic stochasticity rather than selection. In spite of their simplicity, neutral models have been found to accurately reproduce static patterns of biodiversity for diverse communities. However, the same neutral models have been found to exhibit species abundance dynamics that are far too slow compared to reality, resulting in poor fits to temporally dynamic patterns of biodiversity. Here, we show that one of the root causes of these slow dynamics is the additional assumption that a community has reached an equilibrium with a fixed community size, with species that have a net growth rate close to zero. We removed this additional assumption by constructing and analyzing a neutral model with an expected community size that can change over time and is not necessarily at equilibrium, which thus allows the historical formation of a community to be represented explicitly. Our analysis demonstrated that for the general scenario where a small community rapidly grows in size to a carrying capacity, representing recovery from ecological disturbance or assembly of a new community, the model produced much larger changes in species abundances and much shorter species ages than a neutral model at an equilibrium with fixed community size. In addition, the species abundance distribution was biphasic with a subset of abundant species arising from a founder effect. We confirmed these new results in applications of the new model to the specific scenario of recovery of the Amazon tree community after the end-Cretaceous bolide impact, which involved periods of increasing and decreasing community size. We conclude that incorporating transient dynamics in neutral models improves realism by allowing explicit consideration of how a community is formed over realistic time-scales.

Assessing mechanisms for microbial taxa and community dynamics using process models.

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer-resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer-resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

Further Quantifying the Niche-Neutral Continuum of Human Digestive Tract Microbiomes with Near Neutral Model and Stochasticity Analysis.

It is postulated that the human digestive tract (DT) from mouth to intestine is differentiated into diverse niches. For example, Segata et al. discovered that the microbiomes of diverse habitats along the DT could be distinguished as 4 types (niches) including (i) stool; (ii) sub-gingival plaques (SubP) and supra-gingival plaques (SupP); (iii) tongue dorsum (TD), throat (TH), palatine tonsils (PT), and saliva (Sal); and (iv) hard palate (HP) and buccal mucosa (BM), and keratinized gingiva (KG). These niches are different not only in composition, but also in metabolic potentials. In a previous study, we applied Harris et al's multi-site neutral and Tang and Zhou's niche-neutral hybrid models to characterize the DT niches discovered by Segata et al. Here, we complement the previous study by applying Sloan's near-neural model and Ning et al's stochasticity analysis framework to quantify the niche-neutral continuum of the DT microbiome distribution to shed light on the possible ecological/evolutionary mechanism that shapes the continuum. Overall but excluding the stool site, the proportion of neutral OTUs (46%) is slightly higher than that of the positive selection (38%), but significantly higher than negative selection (15%). The gut (stool) exhibited 3 to 12 times lower neutrality than other DT sites. The analysis also cross-verified our previous hypothesis that the KG (keratinized gingiva) is of distinct assembly dynamics in the DT microbiome, should be treated as a fifth niche. Our findings offer new insight on the long-standing debate concerning whether a minimum of 2-mm of KG width is necessary for marginal periodontal health.

Differential Oral Microbial Input Determines Two Microbiota Pneumo-Types Associated with Health Status.

The oral and upper respiratory tracts are closely linked anatomically and physiologically with the lower respiratory tract and lungs, and the influence of oral and upper respiratory microbes on the lung microbiota is increasingly being recognized. However, the ecological process and individual heterogeneity of the oral and upper respiratory tract microbes shaping the lung microbiota remain unclear owing to the lack of controlled analyses with sufficient sample sizes. Here, the microbiomes of saliva, nasal cavity, oropharyngeal area, and bronchoalveolar lavage samples are profiled and the shaping process of multisource microbes on the lung microbiota is measured. It is found that oral and nasal microbial inputs jointly shape the lung microbiota by occupying different ecological niches. It is also observed that the spread of oral microbes to the lungs is heterogeneous, with more oral microbes entering the lungs being associated with decreased lung function and increased lung proinflammatory cytokines. These results depict the external shaping process of lung microbiota and indicate the great value of oral samples, such as saliva, in monitoring and assessing lung microbiota status in clinical settings.

Niche-Neutral Continuum Seems to Explain the Global Niche Differentiation and Local Drift of the Human Digestive Tract Microbiome.

The human digestive tract (DT) is differentiated into diverse niches and harbors the greatest microbiome diversity of our bodies. Segata et al. (2012) found that the microbiome of diverse habitats along the DT may be classified as four categories or niches with different microbial compositions and metabolic potentials. Nonetheless, few studies have offered theoretical interpretations of the observed patterns, not to mention quantitative mechanistic parameters. Such parameters should capture the essence of the fundamental processes that shape the microbiome distribution, beyond simple ecological metrics such as diversity or composition descriptors, which only capture the manifestations of the mechanisms. Here, we aim to get educated guesses for such parameters by adopting an integrated approach with multisite neutral (MSN) and niche-neutral hybrid (NNH) modeling, via reanalyzing Segata's 16s-rRNA samples covering 10 DT-sites from over 200 healthy individuals. We evaluate the relative importance of the four essential processes (drift, dispersal, speciation, and selection) in shaping the microbiome distribution and dynamics along DT, which are assumed to form a niche-neutral continuum. Furthermore, the continuum seems to be hierarchical: the selection or niche differentiations seem to play a predominant role (> 90% based on NNH) at the global (the DT metacommunity) level, but the neutral drifts seem to be prevalent (> 90% based on MSN/NNH) at the local sites except for the gut site. An additional finding is that the DT appears to have a fifth niche for the DT microbiome, namely, Keratinized gingival (KG), while in Segata's original study, only four niches were identified. Specifically, in Segata's study, KG was classified into the same niche type including buccal mucosa (BM), hard palate (HP), and KG. However, it should be emphasized that the proposal of the fifth niche of KG requires additional verification in the future studies.

Diversity patterns and speciation processes in a two-island system with continuous migration.

Geographic isolation is a central mechanism of speciation, but perfect isolation of populations is rare. Although speciation can be hindered if gene flow is large, intermediate levels of migration can enhance speciation by introducing genetic novelty in the semi-isolated populations or founding small communities of migrants. Here, we consider a two-island neutral model of speciation with continuous migration and study diversity patterns as a function of the migration probability, population size, and number of genes involved in reproductive isolation (dubbed as genome size). For small genomes, low levels of migration induce speciation on the islands that otherwise would not occur. Diversity, however, drops sharply to a single species inhabiting both islands as the migration probability increases. For large genomes, sympatric speciation occurs even when the islands are strictly isolated. Then species richness per island increases with the probability of migration, but the total number of species decreases as they become cosmopolitan. For each genome size, there is an optimal migration intensity for each population size that maximizes the number of species. We discuss the observed modes of speciation induced by migration and how they increase species richness in the insular system while promoting asymmetry between the islands and hindering endemism.

The Seasonal Patterns, Ecological Function and Assembly Processes of Bacterioplankton Communities in the Danjiangkou Reservoir, China.

As the water source for the Middle Route Project of the South-to-North Water Diversion Project (MR-SNWD) of China, the Danjiangkou Reservoir (DJR) is in the process of ecosystem reassembly, but the composition, function, and assembly mechanisms of bacterioplankton communities are not yet clear. In this study, the composition, distribution characteristics and influencing factors of bacterioplankton communities were analyzed by high-throughput sequencing (HTS); PICRUSt2 was used to predict community function; a molecular ecological network was used to analyze bacterioplankton interactions; and the assembly process of bacterioplankton communities was estimated with a neutral model. The results indicated that the communities, function and interaction of bacterioplankton in the DJR had significant annual and seasonal variations and that the seasonal differences were greater than that the annual differences. Excessive nitrogen (N) and phosphorus (P) nutrients in the DJR are the most important factors affecting water quality in the reservoir, N and P nutrients are the main factors affecting bacterial communities. Season is the most important factor affecting bacterioplankton N and P cycle functions. Ecological network analysis indicated that the average clustering coefficient and average connectivity of the spring samples were lower than those of the autumn samples, while the number of modules for the spring samples was higher than that for the autumn samples. The neutral model explained 66.3%, 63.0%, 63.0%, and 70.9% of the bacterioplankton community variations in samples in the spring of 2018, the autumn of 2018, the spring of 2019, and the autumn of 2019, respectively. Stochastic processes dominate bacterioplankton community assembly in the DJR. This study revealed the composition, function, interaction, and assembly of bacterioplankton communities in the DJR, providing a reference for the protection of water quality and the ecological functions of DJR bacterioplankton.

Stochastic neutral drifts seem prevalent in driving human virome assembly: Neutral, near-neutral and non-neutral theoretic analyses.

It is estimated that human body is inhabited by approximately 380 trillions of viruses, which exist in the form of viral communities and are collectively termed as human virome. How virome is assembled and what kind of forces maintain the composition and diversity of viral communities is still an open question. The question is of obvious importance because of its implications to human health and diseases. Here we address the question by harnessing the power of Hubbell's unified neutral theory of biodiversity (UNTB) in terms of three neutral models including standard Hubbell's neutral model (HNM), Sloan's near-neutral model (SNM) and Harris et al. (2017) multi-site neutral model (MSN), further augmented by Ning et al. (2019) normalized stochasticity ratio (NSR) and Hammal et al. (2015) power analysis for the neutral test (PNT). With the five models applied to 179 virome samples, we aim to obtain robust findings given both Type-I and Type-II errors are addressed and possible alternative, non-neutral processes are detected. It was found that stochastic neutral drifts seem prevalent: approximately 65-92% at metacommunity/landscape scales and 67-80% at virus species scale. The non-neutral selection is approximately 26-28% at community scale and 23% at species scale. The false negative rate is about 2-3%, which suggested rather limited confounding effects of non-neutral process on neutrality tests. We postulate that prevalence of neutrality in human virome is likely due to extremely simple structure of viruses (stands of DNA/RNA) and their inter-species homogeneities, forming the foundation of species equivalence-the hallmark of neutral theory.

Intertidal macroinvertebrate community structure in a subtropical channel is driven by sediment properties across different land-use types.

Macroinvertebrate community in the intertidal setup plays an important role in coastal ecosystem functions and biogeochemical cycle. However, different land use pattern may influence on their community structure, diversity, and composition in the coastal ecosystems. Using Van-Veen grab sampler, 60 sediment samples were seasonally collected from mangroves-dominated, aquaculture-dominated, and anthropogenically affected area in the lower intertidal zone of the Kohelia channel of Bangladesh, the Northern Bay of Bengal. We have tasted the variation in sediment properties across three land-use types in this intertidal habitat. To understand the patterns of benthic macroinvertebrate distribution, a neutral community model was applied. Our results showed that community composition and biodiversity of the benthic macroinvertebrate communities varied significantly between mangrove-dominated area with anthropogenically affected areas among the four seasons. The neutral community model revealed that community assembly of benthic macroinvertebrates in the lower intertidal habitats is structured by stochastic processes while sediment properties have significant influence on species distribution and interactions. Results suggested that land-use changes altered sediment properties and could change the diversity and distribution of the macroinvertebrate communities in the lower intertidal habitats.

Neutral Processes Provide an Insight Into the Structure and Function of Gut Microbiota in the Cotton Bollworm.

Gut-associated microbes can influence insect health and fitness. Understanding the structure of bacterial communities provides valuable insights on how different species may be selected and their functional characteristics in their hosts. The neutral model is powerful in predicting the structure of microbial communities, but its application in insects remains rare. Here, we examined the contribution of neutral processes to the gut-associated bacterial communities in Helicoverpa armigera caterpillars collected from different maize varieties at four locations. The gut-associated bacteria can be assigned to 37 Phyla, 119 orders, and 515 genera, with each individual gut containing 17-75% of the OTUs and 19-79% of the genera in the pooled samples of each population. The distribution patterns of most (75.59-83.74%) bacterial taxa were in good agreement with the neutral expectations. Of the remaining OTUs, some were detected in more individual hosts than would be predicted by the neutral model (i.e., above-partition), and others were detected in fewer individual hosts than predicted by the neutral model (i.e., below-partition). The bacterial taxa in the above-partitions were potentially selected by the caterpillar hosts, while the bacteria in the below-partitions may be preferentially eliminated by the hosts. Moreover, the gut-associated microbiota seemed to vary between maize varieties and locations, so ecological parameters outside hosts can affect the bacterial communities. Therefore, the structure of gut microbiota in the H. armigera caterpillar was mainly determined by stochastic processes, and the bacteria in the above-partition warrant further investigation for their potential roles in the caterpillar host.

Testing macroecological theories in cryptocurrency market: neutral models cannot describe diversity patterns and their variation.

We develop an analysis of the cryptocurrency market borrowing methods and concepts from ecology. This approach makes it possible to identify specific diversity patterns and their variation, in close analogy with ecological systems, and to characterize the cryptocurrency market in an effective way. At the same time, it shows how non-biological systems can have an important role in contrasting different ecological theories and in testing the use of neutral models. The study of the cryptocurrencies abundance distribution and the evolution of the community structure strongly indicates that these statistical patterns are not consistent with neutrality. In particular, the necessity to increase the temporal change in community composition when the number of cryptocurrencies grows, suggests that their interactions are not necessarily weak. The analysis of the intraspecific and interspecific interdependency supports this fact and demonstrates the presence of a market sector influenced by mutualistic relations. These latest findings challenge the hypothesis of weakly interacting symmetric species, the postulate at the heart of neutral models.

Non-zero-sum neutrality test for the tropical rain forest community using long-term between-census data.

For community ecologists, "neutral or not?" is a fundamental question, and thus, rejecting neutrality is an important first step before investigating the deterministic processes underlying community dynamics. Hubbell's neutral model is an important contribution to the exploration of community dynamics, both technically and philosophically. However, the neutrality tests for this model are limited by a lack of statistical power, partly because the zero-sum assumption of the model is unrealistic. In this study, we developed a neutrality test for local communities that implements non-zero-sum community dynamics and determines the number of new species (N sp) between observations. For the non-zero-sum neutrality test, the model distributed the expected N sp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed N sp with distributions of the expected N sp derived from the simulations. For this comparison, we developed a new "non-zero-sum N sp test," which we validated by running multiple neutral simulations using different parameter settings. We found that the non-zero-sum N sp test rejected neutrality at a near-significance level, which justified the validity of our approach. For an empirical test, the non-zero-sum N sp test was applied to real tropical tree communities in Panama and Malaysia. The non-zero-sum N sp test rejected neutrality in both communities when the observation interval was long and N sp was large. Hence, the non-zero-sum N sp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed N sp is large. This unique and simple approach is statistically powerful, even though it only employs two temporal sequences of community data. Thus, this test can be easily applied to existing datasets. In addition, application of the test will provide significant benefits for detecting changing biodiversity under climate change and anthropogenic disturbance.