The long-term genetic stability and individual specificity of the human gut microbiome.

By following up the gut microbiome, 51 human phenotypes and plasma levels of 1,183 metabolites in 338 individuals after 4 years, we characterize microbial stability and variation in relation to host physiology. Using these individual-specific and temporally stable microbial profiles, including bacterial SNPs and structural variations, we develop a microbial fingerprinting method that shows up to 85% accuracy in classifying metagenomic samples taken 4 years apart. Application of our fingerprinting method to the independent HMP cohort results in 95% accuracy for samples taken 1 year apart. We further observe temporal changes in the abundance of multiple bacterial species, metabolic pathways, and structural variation, as well as strain replacement. We report 190 longitudinal microbial associations with host phenotypes and 519 associations with plasma metabolites. These associations are enriched for cardiometabolic traits, vitamin B, and uremic toxins. Finally, mediation analysis suggests that the gut microbiome may influence cardiometabolic health through its metabolites.

Motion state-dependent motor learning based on explicit visual feedback has limited spatiotemporal properties compared with adaptation to physical perturbations.

We recently showed that subjects can learn motion state-dependent changes to motor output (temporal force patterns) based on explicit visual feedback of the equivalent force field (i.e., without the physical perturbation). Here, we examined the spatiotemporal properties of this learning compared with learning based on physical perturbations. There were two human subject groups and two experimental paradigms. One group (n = 40) experienced physical perturbations (i.e., a velocity-dependent force field, vFF), whereas the second (n = 40) was given explicit visual feedback (EVF) of the force-velocity relationship. In the latter, subjects moved in force channels and we provided visual feedback of the lateral force exerted during the movement, as well as the required force pattern based on movement velocity. In the first paradigm (spatial generalization), following vFF or EVF training, generalization of learning was tested by requiring subjects to move to 14 untrained target locations (0° to ±135° around the trained location). In the second paradigm (temporal stability), following training, we examined the decay of learning over eight delay periods (0 to 90 s). Results showed that learning based on EVF did not generalize to untrained directions, whereas the generalization for the vFF was significant for targets ≤ 45° away. In addition, the decay of learning for the EVF group was significantly faster than the FF group (a time constant of 2.72 ± 1.74 s vs. 12.53 ± 11.83 s). Collectively, our results suggest that recalibrating motor output based on explicit motion state information, in contrast to physical disturbances, uses learning mechanisms with limited spatiotemporal properties.NEW & NOTEWORTHY Adjustment of motor output based on limb motion state information can be achieved based on explicit information or from physical perturbations. Here, we investigated the spatiotemporal characteristics of short-term motor learning to determine the properties of the respective learning mechanisms. Our results suggest that adjustments based on physical perturbations are more temporally stable and applied over a greater spatial range than the learning based on explicit visual feedback, suggesting largely separate learning mechanisms.

The relationships between structure and function of plant communities in the desert steppe.

BACKGROUND: Assessing the relationships between spatial and temporal structures and functions of plant communities is an effective way to understand the changing dynamics of plant communities in specific environments. In this study, we investigated the response of structural and functional stabilities of plant communities to stocking rate in the desert steppe over a 16-year grazing period as the research background. METHODS: We used classical statistical methods to investigate the quantitative characteristics of plant communities over time (2014-2019) and space (2017-2019) at four stocking rates (control, CK, 0 sheep·ha-1·month-1; light grazing, LG, 0.15 sheep·ha-1·month-1; moderate grazing, MG, 0.30 sheep·ha-1·month-1; heavy grazing, HG, 0.45 sheep·ha-1·month-1) in the Stipa breviflora desert steppe of Inner Mongolia. We then examined the relationship between structural and functional stability of plant communities. RESULTS: On the spatial scale, the structural stability of plant community was the highest in the LG treatment and the lowest in the MG treatment. The functional stability of plant community was the highest in the MG treatment and the lowest in the HG treatment. On the temporal scale, the structural stability of plant community was the highest in the MG treatment and the lowest in the LG treatment. The functional stability of plant community was the highest in the LG treatment and the lowest in the HG treatment. Affected by the stocking rate, the structural stability of plant community fluctuated more widely on the spatial scale and its functional stability varied more widely on the temporal scale. Nonetheless, the functional stability of the plant community is more responsive to the stocking rate. CONCLUSIONS: Our findings suggest that influenced by the disturbance of stocking rate, the structural stability of plant community is more significant than the functional stability in the desert grassland ecosystem, which lays a solid foundation for the study of ecosystem stability.

Herbivore exclusion stabilizes alpine grassland biomass production across spatial scales.

There is growing evidence that land-use management practices such as livestock grazing can strongly impact the local diversity, functioning, and stability of grassland communities. However, whether these impacts depend on environmental condition and propagate to larger spatial scales remains unclear. Using an 8-year grassland exclosure experiment conducted at nine sites in the Tibetan Plateau covering a large precipitation gradient, we found that herbivore exclusion increased the temporal stability of alpine grassland biomass production at both the local and larger (site) spatial scales. Higher local community stability was attributed to greater stability of dominant species, whereas higher stability at the larger scale was linked to higher spatial asynchrony of productivity among local communities. Additionally, sites with higher mean annual precipitation had lower dominant species stability and lower grassland stability at both the spatial scales considered. Our study provides novel evidence that livestock grazing can impair grassland stability across spatial scales and climatic gradients.

Plant diversity and community age stabilize ecosystem multifunctionality.

It is well known that biodiversity positively affects ecosystem functioning, leading to enhanced ecosystem stability. However, this knowledge is mainly based on analyses using single ecosystem functions, while studies focusing on the stability of ecosystem multifunctionality (EMF) are rare. Taking advantage of a long-term grassland biodiversity experiment, we studied the effect of plant diversity (1-60 species) on EMF over 5 years, its temporal stability, as well as multifunctional resistance and resilience to a 2-year drought event. Using split-plot treatments, we further tested whether a shared history of plants and soil influences the studied relationships. We calculated EMF based on functions related to plants and higher-trophic levels. Plant diversity enhanced EMF in all studied years, and this effect strengthened over the study period. Moreover, plant diversity increased the temporal stability of EMF and fostered resistance to reoccurring drought events. Old plant communities with shared plant and soil history showed a stronger plant diversity-multifunctionality relationship and higher temporal stability of EMF than younger communities without shared histories. Our results highlight the importance of old and biodiverse plant communities for EMF and its stability to extreme climate events in a world increasingly threatened by global change.

Temporal asynchrony of plant and soil biota determines ecosystem multifunctional stability.

The role of plant biodiversity in stabilizing ecosystem multifunctionality has been extensively studied; however, the impact of soil biota biodiversity on ecosystem multifunctional stability, particularly under multiple environmental changes, remains unexplored. By conducting an experiment with environmental changes (adding water and nitrogen to a long-term grazing experiment) and an experiment without environmental changes (an undisturbed site) in semi-arid grasslands, our research revealed that environmental changes-induced changes in temporal stability of both above- and belowground multifunctionality were mainly impacted by plant and soil biota asynchrony, rather than by species diversity. Furthermore, changes in temporal stability of above- and belowground multifunctionality, under both experiments with and without environmental changes, were mainly associated with plant and soil biota asynchrony, respectively, suggesting that the temporal asynchrony of plant and soil biota has independent and non-substitutable effects on multifunctional stability. Our findings emphasize the importance of considering both above- and belowground biodiversity or functions when evaluating the stabilizing effects of biodiversity on ecosystem functions.

Does Intention Strength Moderate the Intention-Health Behavior Relationship for Covid-19 Protection Behaviors?

BACKGROUND AND PURPOSE: The present research tests whether intention strength moderates intention-health behavior relations and the extent to which this is accounted for by the moderating effects of intention stability, goal priority, and goal conflict. METHODS: In a prospective multi-behavior study, a representative sample of UK adults (N = 503) completed measures of past behavior, intention, intention strength, goal priority, and goal conflict in relation to eight Covid-19 protection behaviors at time 1. Intention and self-reported behavior were assessed at time 2 (2 months later). Intention stability was assessed over 2 months. RESULTS: Intention strength was a significant moderator of the intention-behavior relationship (controlling for past behavior). Controlling for the moderating effects of intention stability attenuated the moderating effect of intention strength, while also controlling for the moderating effects of goal priority and goal conflict reduced the moderating effects of intention strength to nonsignificance. CONCLUSIONS: The present findings indicate that intention strength is a significant moderator of the intention-health behavior relationship. They also suggest that the moderating effect of intention strength is explained by effects on intention stability, goal priority, and goal conflict. Tests of interventions to manipulate intention strength as a means to strengthen intention stability and intention-behavior relations are warranted.

Predictors of engaging in eight Covid-19 protection behaviors (e.g., wearing face coverings, social distancing) were examined in a representative sample of adults in the UK in November 2021. Intentions to engage in these behaviors (e.g., "I will try to wear a face covering in public places in the next two months") were a strong predictor of self-reported engagement 2 months later, even when taking account of people's past behavior. Importantly, people's intentions were more predictive of behavior when intentions were judged to be strong (e.g., important, based on a lot of thought). Further analyses revealed that the enhanced effect of strong intentions on behavior was due to strong intentions being more stable over time, and being given greater priority over, and not conflicting with, other goals. Increasing the strength of people's intentions may be a useful and novel way to increase performance of health-protection behaviors.

Mowing increased community stability in semiarid grasslands more than either fencing or grazing.

A substantial body of empirical evidence suggests that anthropogenic disturbance can affect the structure and function of grassland ecosystems. Despite this, few studies have elucidated the mechanisms through which grazing and mowing, the two most widespread land management practices, affect the stability of natural grassland communities. In this study, we draw upon 9 years of field data from natural grasslands in northern China to investigate the effects of gazing and mowing on community stability, specifically focusing on community aboveground net primary productivity (ANPP) and dominance, which are two major biodiversity mechanisms known to characterize community fluctuations. We found that both grazing and mowing reduced ANPP in comparison to areas enclosed by fencing. Grazing reduced community stability by increasing the likelihood of single-species dominance and decreasing the relative proportion of nondominant species. In contrast, mowing reduced the productivity of the dominant species but increased the productivity of nondominant species. As a consequence, mowing improved the overall community stability by increasing the stability of nondominant species. Our study provides novel insight into understanding of the relationship between community species fluctuation-stability, with implications for ecological research and ecosystem management in natural grasslands.

Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan.

Temporally stable patterns of neural coordination among distributed brain regions are crucial for survival. Recently, many studies highlight association between healthy aging and modifications in organization of functional brain networks, across various time-scales. Nonetheless, quantitative characterization of temporal stability of functional brain networks across healthy aging remains unexplored. This study introduces a data-driven unsupervised approach to capture high-dimensional dynamic functional connectivity (dFC) via low-dimensional patterns and subsequent estimation of temporal stability using quantitative metrics. Healthy aging related changes in temporal stability of dFC were characterized across resting-state, movie-viewing, and sensorimotor tasks (SMT) on a large (n = 645) healthy aging dataset (18-88 years). Prominent results reveal that (1) whole-brain temporal dynamics of dFC movie-watching task is closer to resting-state than to SMT with an overall trend of highest temporal stability observed during SMT followed by movie-watching and resting-state, invariant across lifespan aging, (2) in both tasks conditions stability of neurocognitive networks in young adults is higher than older adults, and (3) temporal stability of whole brain resting-state follows a U-shaped curve along lifespan-a pattern shared by sensorimotor network stability indicating their deeper relationship. Overall, the results can be applied generally for studying cohorts of neurological disorders using neuroimaging tools.

The temporal profile of self-prioritization.

Personal relevance exerts a powerful influence on decisional processing, such that arbitrary stimuli associated with the self are classified more rapidly than identical material linked with other people. Notwithstanding numerous demonstrations of this facilitatory effect, it remains unclear whether self-prioritization is a temporally stable outcome of decision-making. Accordingly, using a shape-label matching task in combination with computational modeling, the current experiment investigated this matter. The results were informative. First, regardless of the target of comparison (i.e., friend or stranger), self-prioritization was a persistent product of decision-making across the testing session. Second, a variant of the standard drift diffusion model in which decisional boundaries collapsed gradually over the course of the task best fit the observed data. Third, whereas the efficiency of stimulus processing increased for other-related stimuli during the task, it decreased for self-related material. Collectively, these findings advance understanding of the temporal profile of self-prioritization.

The temporal stability of maternal parenting style and child feeding practices: A six-wave longitudinal study.

Although parenting styles and child feeding practices are conceptualized as distal, static predictors of child eating and weight outcomes, few studies have examined the temporal stability (i.e., change over time) of these parenting measures. Also, parental characteristics, such as mental health or socio-demographics, may make it more or less difficult to sustain consistent parenting behavior. This study examined the temporal stability of parenting styles and child feeding practices and the association between temporal stability indices with maternal sociodemographic and mental health characteristics. The analytic sample included 161 ethnically diverse mothers enrolled in a six-wave bi-annual longitudinal study. During each wave, mothers reported on their parenting styles and child feeding practices using validated self-report questionnaires. Temporal stability indices for parenting styles were moderate for authoritative (ICC = 0.57) and authoritarian (ICC = 0.70) styles, yet high for permissive (ICC = 0.78) styles. Temporal stability scores for child feeding practices were low for discipline (ICC = 0.33), limit setting (ICC = 0.33), monitoring (ICC = 0.36), and pressure to eat (ICC = 0.34); however, restriction (ICC = 0.53) and role modeling of healthy eating were moderate (ICC = 0.73). Greater income and education status were positively associated with stability in authoritative, authoritarian, and permissive parenting styles, as well as with limit setting, monitoring, role modeling of healthy eating, and pressure to eat feeding practices. Higher anxiety and depressive symptoms and lower self-esteem were negatively associated with permissive parenting styles and role modeling of healthy eating. Findings show that maternal parenting styles and child feeding practices fluctuate over time, and sociodemographic and mental health characteristics are related to stability of some of these parenting styles and behaviors.

Determinants of tree population temporal stability in a temperate mixed forest over a gradient of nitrogen addition.

Nitrogen (N) deposition is a significant threat to the functioning of forests and negatively impacts the delivery of forest goods and services. Contemporary management approaches seek to adapt forests to such N-deposition stressors, but to date how plant populations in natural forests respond to N deposition and what factors determine the contrasting responses among populations are still unclear. Here, we investigated the impact of N-addition (control: 0 kg ha-1 yr-1; low: 25 kg ha-1 yr-1; medium: 50 kg ha-1 yr-1; high: 75 kg ha-1 ha yr-1) on tree population temporal stability and how initial tree size, mycorrhizal type, and leaf N content (LNC; as a surrogate for functional trait composition) mediate tree population responses to N-addition in a Korean pine and mixed broadleaved dominated temperate forest in northern China. We quantified tree species population temporal stability as the ratio of mean to standard deviation of the year-by-year stem increments recorded in individual trees from 2015 to 2022 experimental period. The results showed different temporal stabilities of tree species among four N-addition levels, with the highest population stability observed within the high N-addition plots. Furthermore, initial tree size had significantly (p < 0.001) positive effects on population temporal stability. The effect of LNC and initial tree size were also contingent on the level of N applied. Specifically, increase in tree population LNC reduced population temporal stability in all plots where N was added. Our results imply that retention of large-sized trees and species with resource-conservative strategies (e.g., low LNC) could enhance forest stability under N deposition.

Identifying patients with cognitive motor dissociation using resting-state temporal stability.

Using task-dependent neuroimaging techniques, recent studies discovered a fraction of patients with disorders of consciousness (DOC) who had no command-following behaviors but showed a clear sign of awareness as healthy controls, which was defined as cognitive motor dissociation (CMD). However, existing task-dependent approaches might fail when CMD patients have cognitive function (e.g., attention, memory) impairments, in which patients with covert awareness cannot perform a specific task accurately and are thus wrongly considered unconscious, which leads to false-negative findings. Recent studies have suggested that sustaining a stable functional organization over time, i.e., high temporal stability, is crucial for supporting consciousness. Thus, temporal stability could be a powerful tool to detect the patient's cognitive functions (e.g., consciousness), while its alteration in the DOC and its capacity for identifying CMD were unclear. The resting-state fMRI (rs-fMRI) study included 119 participants from three independent research sites. A sliding-window approach was used to investigate global and regional temporal stability, which measured how stable the brain's functional architecture was across time. The temporal stability was compared in the first dataset (36/16 DOC/controls), and then a Support Vector Machine (SVM) classifier was built to discriminate DOC from controls. Furthermore, the generalizability of the SVM classifier was tested in the second independent dataset (35/21 DOC/controls). Finally, the SVM classifier was applied to the third independent dataset, where patients underwent rs-fMRI and brain-computer interface assessment (4/7 CMD/potential non-CMD), to test its performance in identifying CMD. Our results showed that global and regional temporal stability was impaired in DOC patients, especially in regions of the cingulo-opercular task control network, default-mode network, fronto-parietal task control network, and salience network. Using temporal stability as the feature, the SVM model not only showed good performance in the first dataset (accuracy = 90%), but also good generalizability in the second dataset (accuracy = 84%). Most importantly, the SVM model generalized well in identifying CMD in the third dataset (accuracy = 91%). Our preliminary findings suggested that temporal stability could be a potential tool to assist in diagnosing CMD. Furthermore, the temporal stability investigated in this study also contributed to a deeper understanding of the neural mechanism of consciousness.

Soil biota diversity and plant diversity both contributed to ecosystem stability in grasslands.

Understanding the effects of diversity on ecosystem stability in the context of global change has become an important goal of recent ecological research. However, the effects of diversity at multiple scales and trophic levels on ecosystem stability across environmental gradients remain unclear. Here, we conducted a field survey of α-, ß-, and γ-diversity of plants and soil biota (bacteria, fungi, and nematodes) and estimated the temporal ecosystem stability of normalized difference vegetation index (NDVI) in 132 plots on the Mongolian Plateau. After climate and soil environmental variables were controlled for, both the α- and ß-diversity of plants and soil biota (mainly via nematodes) together with precipitation explained most variation in ecosystem stability. These findings evidence that the diversity of both soil biota and plants contributes to ecosystem stability. Model predictions of the future effects of global changes on terrestrial ecosystem stability will require field observations of diversity of both plants and soil biota.

Latitudinal patterns of forest ecosystem stability across spatial scales as affected by biodiversity and environmental heterogeneity.

Our planet is facing a variety of serious threats from climate change that are unfolding unevenly across the globe. Uncovering the spatial patterns of ecosystem stability is important for predicting the responses of ecological processes and biodiversity patterns to climate change. However, the understanding of the latitudinal pattern of ecosystem stability across scales and of the underlying ecological drivers is still very limited. Accordingly, this study examines the latitudinal patterns of ecosystem stability at the local and regional spatial scale using a natural assembly of forest metacommunities that are distributed over a large temperate forest region, considering a range of potential environmental drivers. We found that the stability of regional communities (regional stability) and asynchronous dynamics among local communities (spatial asynchrony) both decreased with increasing latitude, whereas the stability of local communities (local stability) did not. We tested a series of hypotheses that potentially drive the spatial patterns of ecosystem stability, and found that although the ecological drivers of biodiversity, climatic history, resource conditions, climatic stability, and environmental heterogeneity varied with latitude, latitudinal patterns of ecosystem stability at multiple scales were affected by biodiversity and environmental heterogeneity. In particular, α diversity is positively associated with local stability, while ß diversity is positively associated with spatial asynchrony, although both relationships are weak. Our study provides the first evidence that latitudinal patterns of the temporal stability of naturally assembled forest metacommunities across scales are driven by biodiversity and environmental heterogeneity. Our findings suggest that the preservation of plant biodiversity within and between forest communities and the maintenance of heterogeneous landscapes can be crucial to buffer forest ecosystems at higher latitudes from the faster and more intense negative impacts of climate change in the future.

Temporal stability of productivity is associated with complementarity and competitive intensities in intercropping.

Year-to-year stability in crop production is a crucial aspect of feeding a growing global population. Evidence from natural ecosystems shows that increasing plant diversity generally increases the temporal stability of productivity; however, we have little knowledge of the mechanisms by which diversity affects stability. In fact, understanding the drivers of stability is a major knowledge gap in our understanding of biodiversity and ecosystem function in general. We varied resource inputs into crop monocultures and intercropping of maize/pea and maize/rapeseed for 3 years in field experiments to create a wide range of values for temporal stability, complementarity effects, selection effects, competition, and facilitation. We correlated whole-system temporal stability in productivity with these values and the stability of competitively subordinate species and competitively dominant species in the intercrops. We then used structural equation modeling (SEM), which combines complex path models with latent variables, to estimate how interspecific interactions for water, nitrogen, and phosphorus affected the relationships between stability and these values. Intercropping treatments did not increase stability, but the wide range of stability created by our experiments allowed us to explore the relationship of many factors with stability. Complementarity correlated positively with the temporal stability of grain yield and aboveground biomass, suggesting that either facilitative interactions or niche partitioning shifted over time in ways that promoted stability. Furthermore, the temporal stability of total productivity of intercropping relied most on the stability of more productive species. However, facilitation tested by relative interaction index independently did not correlate with stability, but the temporal stability of the whole system increased as the competitive effects of competitively dominant species (pea and rapeseed) on competitively subordinate species (maize) decreased and was highest when these competitive effects were virtually zero. SEM indicated that as competition for soil nitrogen from competitively dominant species on competitively subordinate species decreased, the overall temporal stability of whole-system aboveground biomass increased. This stability then led to greater stability in grain production. Our findings indicate that complex shifts in complementarity and competitive intensities are likely to be key mechanisms that maintain temporal stability in species-diverse agriculture and, potentially, in natural systems.

Isolation and characterization of 21 microsatellite loci for the sea cucumber Holothuria (Halodeima) atra (Echinodermata, Holothuroidea) reveal low asexual propagation through time in Reunion Island (southwestern Indian Ocean).

BACKGROUND: Holothuria (Halodeima) atra Jaeger, 1833 is a tropical sea cucumber usually harvested for the "bêche-de-mer" trade market. It has been reported to reproduce both sexually, through gamete spawning, or asexually, through fission. To date, no study has ever investigated clonality, nor genetic connectivity, among its populations, using microsatellite markers. METHODS AND RESULTS: We isolated the first 21 microsatellite loci specific for H. atra, which were then used to investigate clonal diversity, genetic structure and diversity among 44 H. atra individuals sampled in Reunion Island (southwestern Indian Ocean), over two seasons. All 21 loci were polymorphic, with number of alleles per locus ranging from 2 to 10. No repetitive multi-locus genotype (MLG) and few clonal lineages (MLL) were found. Observed heterozygosities per locus and season ranged from 0.000 to 0.909, while expected heterozygosities ranged from 0.290 to 0.882. Four loci were at Hardy-Weinberg equilibrium for both seasons, all others presenting a deficit of heterozygotes in one or both seasons. Meanwhile, no genetic differentiation was detected between seasons, according to assignment tests and global FST. CONCLUSIONS: These results suggest low asexual propagation in this population. These loci represent useful tools to better understand reproductive strategies and population connectivity of H. atra, and thus provide relevant knowledge for efficient management.

Decoupled responses of above- and below-ground stability of productivity to nitrogen addition at the local and larger spatial scale.

Temporal stability of net primary productivity (NPP) is important for predicting the reliable provisioning of ecosystem services under global changes. Although nitrogen (N) addition is known to affect the temporal stability of aboveground net primary productivity (ANPP), it is unclear how it impacts that of belowground net primary productivity (BNPP) and NPP, and whether such effects are scale dependent. Here, using experimental N addition in a grassland, we found different responses of ANPP and BNPP stability to N addition at the local scale and that these responses propagated to the larger spatial scale. That is, N addition significantly decreased the stability of ANPP but did not affect the stability of BNPP and NPP at the two scales investigated. Additionally, spatial asynchrony of both ANPP and BNPP among communities provided greater stability at the larger scale and was not affected by N addition. Our findings challenge the traditional view that N addition would reduce ecosystem stability based on results from aboveground dynamics, thus highlighting the importance of viewing ecosystem stability from a whole system perspective.

Power law analysis of the human milk microbiome.

The human breast milk microbiome (HMM) has far reached health implications for both mothers and infants, and understanding the structure and dynamics of milk microbial communities is therefore of critical biomedical importance. Community heterogeneity, which has certain commonalities with familiar diversity but also with certain fundamental differences, is an important aspect of community structure and dynamics. Taylor's (1961) power law (TPL) (Nature, 1961) was discovered to govern the mean-variance power function relationship of population abundances and can be used to characterize population spatial aggregation (heterogeneity) and/or temporal stability. TPL was further extended to the community level to measure community spatial heterogeneity and/or temporal stability (Ma 2015, Molecular Ecology). Here, we applied TPL extensions (TPLE) to analyze the heterogeneity of the human milk microbiome by reanalyzing 12 datasets (2115 samples) of the healthy human milk microbiome. Our analysis revealed that the TPLE heterogeneity parameter (b) is rather stable across the 12 datasets, and there were approximately no statistically significant differences among ¾ of the datasets, which is consistent with the hypothesis that the heterogeneity scaling (i.e., change across individuals) of the human microbiome, including HMM, is rather stable or even constant. For this, we built a TPLE model for the pooled 12 datasets (b = 1.906), which can therefore represent the scaling rate of community-level spatial heterogeneity of HMM across individuals. Similarly, we also analyzed mixed-species ("averaged virtual species") level heterogeneity of HMM, and it was found that the mixed-species level heterogeneity was smaller than the heterogeneity at the previously mentioned community level (1.620 vs. 1.906).

Soil microbial community structures are shaped by agricultural systems revealing little temporal variation.

Many studies in soil microbial ecology are undertaken with a single sampling event, with the influence of temporal progression rarely being considered. Under field conditions, soil samples were taken from different agricultural systems; a sown grassland to maize rotation (MC), an intensively managed permanent grassland (INT), as well as extensively managed permanent grasslands with high (EXT_HP), low to sufficient (EXT_LP) and deficient available P (EXT_DP), six times throughout the 2017 growing season. Thus, this study aimed to determine if any differences in soil microbiome structures between both sharply contrasting (MC - INT - EXT), slightly differing (EXT_HP - EXT_DP) and quite similar (EXT_HP - EXT_LP and EXT_LP - EXT_DP) agricultural systems persist through changing growth conditions within the growing season. For both fungal and bacterial community structure, the influence of agricultural system (CV = 0.256, P < 0.001 and CV = 0.145, P < 0.01, respectively) was much greater than that of temporal progression (√CV = 0.065 and 0.042, respectively, both P < 0.001). Importantly, nearly all agricultural systems persistently harbored significantly distinct fungal community structures across each of the six sampling events (all at least P < 0.05). There were not as many pairwise differences in bacterial community structure between the agricultural systems, but some did persist (MC and EXT_HP âˆ¼ EXT_DP, all P < 0.001). Additionally, persistent indicator fungal OTUs (IndVal >0.7, P ≤ 0.05) associated to each agricultural system (except EXT_LP) were found in each of the six sampling events. These results highlight the temporal stability of pairwise differences in soil microbiome structures between established agricultural systems through changing plant growth conditions, even between those with a comparable management regime. This is a highly relevant finding in informing the sampling strategy of studies in soil microbial ecology as well as for designing efficient soil biodiversity monitoring systems.