Distribution and Prevalence of Wolbachia Infections in Native Populations of the Fire Ant Solenopsis invicta (Hymenoptera: Formicidae)

Wolbachia are endosymbiotic bacteria that commonly infect arthropods. These bacteria induce a number of phenotypes in their hosts, including cytoplasmic incompatibility, thelytokous parthenogenesis, feminization, and male killing. We surveyed native South American populations of the fire ant Solenopsis invicta Buren for Wolbachia infections by using a diagnostic polymerase chain reaction assay. In addition, we determined the fidelity of vertical transmission of the bacteria from mother to offspring in this species by assaying daughters in 24 simple-family (monogyne) colonies. Infections were common in many parts of the extensive native range of S. invicta. However, the proportion of individuals infected varied greatly among samples, ranging from zero in several populations from the northerly parts of the range to >90% in more southerly populations. Possible explanations for this variation in the prevalence of Wolbachia infections are discussed. A survey of the two social forms of S. invicta from four geographic areas showed that the prevalence of Wolbachia infections consistently was higher in the monogyne form (single queen per colony) than the sympatric polygyne form (multiple queens per colony). One likely explanation for this trend is that the selective regimes acting on Wolbachia in the two forms differ because of the dissimilar reproductive strategies used by each form. Finally, overall transmission efficiency was found to be very high (>99%), making it unlikely that imperfect transmission prevents the spread of the microbe to near fixation in native population

A new variance ratio metric to detect the timescale of compensatory dynamics

Understanding the mechanisms governing ecological stability—why a property such as primary productivity is stable in some communities and variable in others—has long been a focus of ecology. Compensatory dynamics, in which anti-synchronous fluctuations between populations buffer against fluctuations at the community level, are a key theoretical mechanism of stability. Classically, compensatory dynamics have been quantified using a variance ratio approach that compares the ratio between community variance and aggregate population variance, such that a lower ratio indicates compensation and a higher ratio indicates synchrony among species fluctuations. However, population dynamics may be influenced by different drivers that operate on different timescales, and evidence from aquatic systems indicates that communities can be compensatory on some timescales and synchronous on others. The variance ratio and related metrics cannot reflect this timescale specificity, yet have remained popular, especially in terrestrial systems. Here, we develop a timescale-specific variance ratio approach that formally decomposes the classical variance ratio according to the timescales of distinct contributions. The approach is implemented in a new R package, called tsvr, that accompanies this paper. We apply our approach to a long-term, multisite grassland community dataset. Our approach demonstrates that the degree of compensation vs. synchrony in community dynamics can vary by timescale. Across sites, population variability was typically greater over longer compared to shorter timescales. At some sites, minimal timescale specificity in compensatory dynamics translated this pattern of population variability into a similar pattern of greater community variability on longer compared to shorter timescales. But at other sites, differentially stronger compensatory dynamics at longer compared to shorter timescales produced lower-than-expected community variability on longer timescales. Within every site, there were plots that exhibited shifts in the strength of compensation between timescales. Our results highlight that compensatory vs. synchronous dynamics are intrinsically timescale-dependent concepts, and our timescale-specific variance ratio provides a metric to quantify timescale specificity and relate it back to the classic variance ratio

General statistical scaling laws for stability in ecological systems

Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance. These relationships can be calibrated using random or representative samples measured at individual scales, and projected to predict average stability at other scales across a wide range of contexts. Moreover deviations between observed vs. extrapolated scaling relationships can reveal information about unobserved heterogeneity across time, space, or species. We anticipate that these methods will be useful for cross-study synthesis of stability data, extrapolating measurements to unobserved scales, and identifying underlying causes and consequences of heterogeneity

Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

Multi-ethnic genome-wide association study for atrial fibrillation

Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF

Stabilizing and Equalizing Mechanisms Alter Community Coexistence and Macroevolutionary Diversity Patterns

Ecological variability, both across space and through time, plays a critical role in maintaining the incredible range of biodiversity observed in nature and is foundational to coexistence theory. Using a combination of analytical techniques, simulation models, and novel paleobiology databases, I examine how ecological variability contributes to coexistence, or how competing species are able to persist in a given environment. I quantify the strength of coexistence in spatially structured communities and the relative importance of species similarities (equalizing mechanisms) and species differences (stabilizing mechanisms) in maintaining biodiversity across space and time. I find that trait-tradeoffs among species, abiotic heterogeneity, stochasticity, and dispersal limitation within spatially structured communities all have unique signatures of coexistence mechanisms. I additionally show that coexistence theory allows us to analyze more complex communities with multiple assembly mechanisms. While coexistence theory exhibits robust, unique signatures across assembly mechanisms, other, more commonly used methods, such as the beta-null deviation measure, are unable to infer community assembly processes from patterns in beta-diversity. This is especially evident for the presence-absence based measure when compared to the abundance-based measure. Finally, I extend the stabilizing and equalizing framework of coexistence theory beyond its use in community ecology to examine macroecological patterns in mammalian diversity. I show that body mass diversity and its evolution can be well-approximated using primarily equalizing mechanisms. This trend holds across terrestrial mammals, a mammalian sub-clade (Equidae), and even across vastly different environments. Both marine (cetaceans) and terrestrial mammals exhibit similar body mass distributions and evolution, where environmental constraints determine the minimum size above which equalizing processes interact in a predictable way to create a right-skewed body mass distribution. Across this work, I find that stabilizing mechanisms are critical for coexistence in spatially structured communities, but equalizing mechanisms effectively predict patterns in mammalian body mass diversity across evolutionary time scales. Generally, the equalizing and stabilizing framework of coexistence theory provides a mechanistic understanding of patterns in biodiversity, both at the community and macroecological scale

The Long and the Short of It: Mechanisms of Synchronous and Compensatory Dynamics Across Temporal Scales

Synchronous dynamics (fluctuations that occur in unison) are universal phenomena with widespread implications for ecological stability. Synchronous dynamics can amplify the destabilizing effect of environmental variability on ecosystem functions such as productivity, whereas the inverse, compensatory dynamics, can stabilize function. Here we combine simulation and empirical analyses to elucidate mechanisms that underlie patterns of synchronous versus compensatory dynamics. In both simulated and empirical communities, we show that synchronous and compensatory dynamics are not mutually exclusive but instead can vary by timescale. Our simulations identify multiple mechanisms that can generate timescale-specific patterns, including different environmental drivers, diverse life histories, dispersal, and non-stationary dynamics. We find that traditional metrics for quantifying synchronous dynamics are often biased toward long-term drivers and may miss the importance of short-term drivers. Our findings indicate key mechanisms to consider when assessing synchronous versus compensatory dynamics and our approach provides a pathway for disentangling these dynamics in natural systems

Quantifying the Relative Importance of Variation in Predation and the Environment for Species Coexistence

Coexistence and food web theory are two cornerstones of the long‐standing effort to understand how species coexist. Although competition and predation are known to act simultaneously in communities, theory and empirical study of these processes continue to be developed largely independently. Here, we integrate modern coexistence theory and food web theory to simultaneously quantify the relative importance of predation and environmental fluctuations for species coexistence. We first examine coexistence in a theoretical, multitrophic model, adding complexity to the food web using machine learning approaches. We then apply our framework to a stochastic model of the rocky intertidal food web, partitioning empirical coexistence dynamics. We find the main effects of both environmental fluctuations and variation in predator abundances contribute substantially to species coexistence. Unexpectedly, their interaction tends to destabilise coexistence, leading to new insights about the role of bottom‐up vs. top‐down forces in both theory and the rocky intertidal ecosystem

Data from: Cross-scale dynamics in community and disease ecology: relative timescales shape the community ecology of pathogens

Communities of free-living organisms are shaped by processes operating within and among patches of habitat, while pathogen communities are shaped by analogous processes operating within and among hosts. Resource competition (R) theory can describe dynamics within patches or hosts, while metacommunity dynamics describe competition-colonization tradeoffs, extinction debts, and superinfection. However, models at this broader scale often assume instantaneous competitive exclusion in co-inhabited patches or coinfected hosts. Impacts of more gradual competitive exclusion on the abundance, distribution, and diversity of species are less clear. Here, we nest a general resource competition model within a metacommunity framework and manipulate the relative timescales for processes operating within and among patches/hosts. We focus on superinfection in pathogen communities. We compare cases where transmission depends on infection prevalence versus the abundance of pathogens within hosts. Surprisingly, slowing the relative pace of competitive exclusion within hosts can decrease infection prevalence of the inferior competitor and increase prevalence of the superior competitor, depending on transmission and virulence. Slower dynamics reduce the abundance of both pathogens within hosts and promote diversity at multiple scales: coinfections within individual hosts and co-occurrence in the host population. These results highlight surprising feedbacks that can emerge across scales and reinforce the rich cross-scale connections between community and disease ecology