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1. Relative abundance data can misrepresent heritability of the microbiome

   https://doi.org/10.1186/s40168-023-01669-w  

   Bruijning, Marjolein ; Ayroles, Julien F. ; Henry, Lucas P. ; Koskella, Britt ; Meyer, Kyle M. ; Metcalf, C. Jessica E. ( October 2023 , Microbiome)

   Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h²) of the microbiome—the proportion of variance in the abundance in each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample.

   We derived an analytical approximation for the heritability that one obtains when using such relative, and not absolute, abundances, based on an underlying quantitative genetic model for absolute abundances. Based on this, we uncovered three problems that can arise when using relative abundances to estimate microbiome heritability: (1) the interdependency between taxa can lead to imprecise heritability estimates. This problem is most apparent for dominant taxa. (2) Large sample size leads to high false discovery rates. With enough statistical power, the result is a strong overestimation of the number of heritable taxa in a community. (3) Microbial co-abundances lead to biased heritability estimates.

   We discuss several potential solutions for advancing the field, focusing on technical and statistical developments, and conclude that caution must be taken when interpreting heritability estimates and comparing values across studies.

    

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2. Macroecological predictors of evolutionary and plastic potential do not apply at microgeographic scales for a freshwater cladoceran under climate change

   https://doi.org/10.1093/evlett/qrad042  

   Nadeau, Christopher P. ; Urban, Mark C. ( October 2023 , Evolution Letters)

   Rapid evolutionary adaptation could reduce the negative impacts of climate change if sufficient heritability of key traits exists under future climate conditions. Plastic responses to climate change could also reduce negative impacts. Understanding which populations are likely to respond via evolution or plasticity could therefore improve estimates of extinction risk. A large body of research suggests that the evolutionary and plastic potential of a population can be predicted by the degree of spatial and temporal climatic variation it experiences. However, we know little about the scale at which these relationships apply. Here, we test if spatial and temporal variation in temperature affects genetic variation and plasticity of fitness and a key thermal tolerance trait (critical thermal maximum; CTmax) at microgeographic scales using a metapopulation of Daphnia magna in freshwater rock pools. Specifically, we ask if (a) there is a microgeographic adaptation of CTmax and fitness to differences in temperature among the pools, (b) pools with greater temporal temperature variation have more genetic variation or plasticity in CTmax or fitness, and (c) increases in temperature affect the heritability of CTmax and fitness. Although we observed genetic variation and plasticity in CTmax and fitness, and differences in fitness among pools, we did not find support for the predicted relationships between temperature variation and genetic variation or plasticity. Furthermore, the genetic variation and plasticity we observed in CTmax are unlikely sufficient to reduce the impacts of climate change. CTmax plasticity was minimal and heritability was 72% lower when D. magna developed at the higher temperatures predicted under climate change. In contrast, the heritability of fitness increased by 53% under warmer temperatures, suggesting an increase in overall evolutionary potential unrelated to CTmax under climate change. More research is needed to understand the evolutionary and plastic potential under climate change and how that potential will be altered in future climates.

    

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3. Spatial and ontogenetic variance in local densities modify selection on demographic traits

   https://doi.org/10.1111/1365-2435.14335  

   Mutz, Jessie ; Inouye, Brian D. ( April 2023 , Functional Ecology)

   Local density can affect individual performance by altering the strength of species interactions. Within many populations, local densities vary spatially (individuals are patchily distributed) or change across life stages, which should influence the selection and eco‐evolutionary feedback because local density variance affects mean fitness and is affected by traits of individuals. However, most studies on the evolutionary consequences of density‐dependent interactions focus on populations where local densities are relatively constant through time and space.

   We investigated the influence of spatial and ontogenetic variance in local densities within an insect population by comparing a model integrating both types of local density variance with models including only spatial variance, only ontogenetic variance, or no variance. We parameterized the models with experimental data, then used elasticity and invasion analyses to characterize selection on traits that affect either the local density an individual experiences (mean clutch size) or individuals' sensitivity to density (effect of larval crowding on pupal mass).

   Spatial and ontogenetic variance reduced population elasticity to effects of local density by 76% and 34% on average, respectively.

   Spatial variance modified selection and adaptive dynamics by altering the tradeoff between density‐dependent and density‐independent vital rates. In models including spatial variance, strategies that maximized density‐dependent survival were favoured over fecundity‐maximizing strategies even at low population density, counter to predictions of density‐dependent selection theory. Furthermore, only models that included spatial variance, thus linking the scales of oviposition and density‐dependent larval survival, had an evolutionarily stable clutch size.

   Ontogenetic variance weakened selection on mean clutch size and sensitivity to larval crowding by disrupting the relationship between trait values and performance during critical life stages.

   We demonstrate that local density variance can strongly modify selection at empirically observed interaction strengths and identify mechanisms for the effects of spatial and ontogenetic variance. Our findings reveal the potential for local density variance to mediate eco‐evolutionary feedback by shaping selection on demographically important traits.

   Read the freePlain Language Summaryfor this article on the Journal blog.

    

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4. Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development

   https://doi.org/10.1523/JNEUROSCI.0735-23.2023  

   Busch, Erica L. ; Rapuano, Kristina M. ; Anderson, Kevin M. ; Rosenberg, Monica D. ; Watts, Richard ; Casey, B. J. ; Haxby, James V. ; Feilong, Ma ( December 2023 , The Journal of Neuroscience)

   The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9–10 years;n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.

    

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5. Vector demography, dispersal and the spread of disease: Experimental epidemics under elevated resource supply

   https://doi.org/10.1111/1365-2435.13672  

   Strauss, Alexander T. ; Henning, Jeremiah A. ; Porath‐Krause, Anita ; Asmus, Ashley L. ; Shaw, Allison K. ; Borer, Elizabeth T. ; Seabloom, Eric W. ; Biere, ed., Arjen ( September 2020 , Functional Ecology)

   The spread of many diseases depends on the demography and dispersal of arthropod vectors. Classic epidemiological theory typically ignores vector dynamics and instead makes the simplifying assumption of frequency‐dependent transmission. Yet, vector ecology may be critical for understanding the spread of disease over space and time and how disease dynamics respond to environmental change.

   Here, we ask how environmental change shapes vector demography and dispersal, and how these traits of vectors govern the spatiotemporal spread of disease.

   We developed disease models parameterised by traits of vectors and fit them to experimental epidemics. The experiment featured a viral pathogen (CYDV‐RPV) vectored by aphidsRhopalosiphum padiamong populations of grass hostsAvena sativaunder two rates of environmental resource supply (i.e. fertilisation of the host). We compared anon‐spatialmodel that ignores vector movement, alagged dispersalmodel that emphasises the delay between vector reproduction and dispersal, and atravelling wavemodel that generates waves of infections across space and time.

   Resource supply altered both vector demography and dispersal. Thelagged dispersalmodel fit best, indicating that vectors first reproduced locally and then dispersed globally among hosts in the experiment. Elevated resources decreased vector population growth rates, nearly doubled their carrying capacity per host, increased dispersal rates when vectors carried the virus, and homogenised disease risk across space.

   Together, the models and experiment show how environmental eutrophication can shape spatial disease dynamics—for example, homogenising disease risk across space—by altering the demography and behaviour of vectors.

   A freePlain Language Summarycan be found within the Supporting Information of this article.

    

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