Biology subjects

Morrissey, M. B.

Publications and source records attributed to Morrissey, M. B..

6 recordsLinked to original sources

bioRxiv2023

The missing fraction problem as an episodes of selection problem

In evolutionary quantitative genetics, the missing fraction problem refers to the case where phenotypes seen later in life are biased because a non-random subset of those phenotypes are missing from the population due to prior viability selection on correlated traits. As any such missing fraction will bias our estimates of selection, and therefore, responses to selection, it is one potential explanation for the paradox of stasis seen in wild populations. The two components required for the missing fraction problem to arise are: (1) viability selection; and (2) correlation between later-life traits and those important for early-life survival. Although it is plausible that these conditions are widespread in wild populations, this problem has received very little attention since it was first discussed (Grafen 1988; Hadfield 2008). It is impossible to know what phenotypes would have been expressed later in life by individuals who died during an earlier episode of viability selection, which has probably put researchers off. Here we show that we can break the problem down into episodes of selection and recover either (a) true estimates of phenotypic selection for later-life traits, or (b) adjusted estimates of the response to selection, depending on the data available. Implementation of complex statistics should uncover how prevalent the problem may be across many existing datasets (the latter approach). Whereas overall, we hope that viewing the missing fraction problem as an episodes of selection problem increases motivation, and provides justification, for a shift in focus to directly studying early-life viability selection. "...what a correlation with [lifetime reproductive success] or its components tells you depends on the causes of the natural variation in the character. It will not always be easy to discover those causes." -- Grafen (1988) "It is surprising that the problem of missing data has received so little attention given that viability selection is central to evolutionary biology." -- Hadfield (2008)

evolutionary biology↗

bioRxiv2022

Phenotypic selection analysis and confounding environmental variables

When environmental variation contributes to relationships between traits and fitness, it can confound analyses of phenotypic selection and, ultimately, bias predictions of adaptive evolution. To date, discussions of how to combat this problem emphasise complex statistical analyses aimed at estimating the genetic basis of the relationship between traits and fitness (e.g., the secondary theorem of selection). This article presents a path analysisbased description of the environmental confounding problem, which clarifies the issue and motivates simpler analyses as potential solutions. We show how standard selection analyses can be expanded to explicitly include environmental variables that may confound trait-fitness relationships, potentially leading to dramatically improved predictions of the evolutionary response to selection relative to classical phenotype-based estimates. We provide both univariate and multivariate treatments of the decomposition of the selection differential into components that may cause evolution via direct and indirect selection and components representing evolutionarily inert, environmentally-induced covariance. The multivariate treatment also yields expressions for the decomposition of the selection differential based on extended selection gradients, which may be of wide general interest beyond the environmental problem. Our approach to the environmental confounding problem makes more plausible demands on data than previous, more involved, quantitative genetic approaches, and addresses the issue of environmental confounding in a more biologically informative way.

evolutionary biology↗

bioRxiv2021

A synthesis of senescence predictions for indeterminate growth, and support from multiple tests in wild lake trout

Senescence, or the deterioration of functionality with age, varies widely across taxa in pattern and rate. Insights into why and how this variation occurs are hindered by the predominance of lab-focused research on short-lived model species with determinate growth. We synthesize evolutionary theories of senescence, highlight key information gaps, and clarify predictions for species with low mortality and variable degrees of indeterminate growth. Lake trout are an ideal species to evaluate predictions in the wild. We monitored individual males from two populations (1976-2017) longitudinally for changes in adult mortality (actuarial senescence) and body condition (proxy for energy balance). A cross-sectional approach (2017) compared young (ages 4-10 years) and old (18-37 years) adults for (1) phenotypic performance in body condition, and semen quality - which is related to fertility under sperm competition (reproductive senescence), and (2) relative telomere length (potential proxy for cellular senescence). Adult growth in these particular populations is constrained by a simplified food web, and our data support predictions of negligible senescence when maximum size is only slightly larger than maturation size. Negative senescence (aka reverse senescence) may occur in other lake trout populations where diet shifts allow maximum sizes to be much larger than maturation size.

evolutionary biology↗

bioRxiv2020

Multivariate distributions of behavioural, morphological, and ontogenetic traits in hybrids bring new insights into the divergence of sympatric Arctic charr morphs.

Studying the development of fitness related traits in hybrids from populations diverging in sympatry is a fundamental approach to understand the processes of speciation. However, such traits are often affected by covariance structures that complicate the comprehension of these processes, especially because the interactive relationships between traits of different nature (e.g. morphology, behaviour, life-history) remain largely unknown in this context. In a common garden setup, we conducted an extensive examination of phenotypic traits suspected to be involved in the divergence of two recently evolved morphs of Arctic charr (Salvelinus alpinus), and investigated the consequences of potential patterns of trait covariance on the phenotype of their hybrids. We observed differences among morphs in overall phenotypic variance and in trait correlations. Phenotypic contrainsts also tended to be reduced in the hybrids, which corroborates the narrative of hybridization facilitating adaptive divergence by relaxing trait covariance. However, the hybrids were associated with reduced phenotypic variance at different scales (i.e. at the scale of the entire P matrix and in different parts of the multivariate space), and we identified stronger correlations between several ontogenetic and morphological traits in the hybrids than in both morphs. These findings suggest a limited potential for hybridization to generate phenotypic novelty, and emphasise the need for multivariate approaches conciliating ontogenetic, morphological and behavioural processes to study the processes of adaptive divergence and speciation.

evolutionary biology↗

bioRxiv2020

Selection of lamb size and early pregnancy in Soay sheep (Ovies aries)

The paradox of stasis - the unexpectedly slow evolution of heritable traits under direct selection - has been widely documented in the last few decades. This paradox is often particularly acute for body size, which is often heritable and where positive associations of size and fitness are frequently identified, but constraints to the evolution of larger body sizes are often not obvious. Here, we identify a trade-off between survival and size-dependent reproduction in Soay sheep (Ovis aries), contributes to selection against large body size. Using recently developed theory on non-linear developmental systems, then decompose total selection of ewe lamb mass along different causal paths to fitness. Larger lambs are more likely to become pregnant, which has a large viability cost. After controlling for this pathway, however, the association between lamb mass and subsequent lifetime fitness is positive. Thus this trade-off does not fully explain stasis of size in tis population, but it does substantially reduce the strength of positive directional selection of size that would otherwise occur. While selection currently favours reduced probability of early pregnancy, largely irrespective of body size, it is likely that the occurrence of early pregnancy could result from adaptation to conditions during a recent period during which population density was much lower.

evolutionary biology↗

bioRxiv2017

Fixed effect variance and the estimation of the heritability: Issues and solutions

Linear mixed effects models are frequently used for estimating quantitative genetic parameters, including the heritability, of traits of interest. Heritability is an important metric, because it acts as a filter that determines how efficiently phenotypic selection translates into evolutionary change. As a quantity of biological interest, it is important that the denominator, the phenotypic variance, actually reflects the amount of phenotypic variance in the relevant ecological stetting. The current practice of quantifying heritability from mixed effects models frequently deprives the heritability of variance explained by fixed effects (often leading to upward-bias) and it has been suggested to omit fixed effects when estimating heritabilities. We advocate an alternative option of fitting complex models incorporating all relevant effects, while including the variance explained by fixed effects into the estimation of heritabilities. The approach is easily implemented (an example is provided) and allows corrections for the estimation of heritability, such as the exclusion of variance arising from experimental design effects while still including all biologically relevant sources of variation. We explore the complications arising depending on the nature of the covariates included as fixed effects (e.g. biological or experimental origin, characteristics of biological covariates). Furthermore, we discuss fixed effects in non-linear and generalized linear models when fixed effects. In these cases, the variance parameters depend on the location of the intercept and hence on the scaling of the fixed effects. Integration over the biologically relevant range of fixed effects offers a preferred solution in those situations.

evolutionary biology↗