Biology subjects

Wolkovich, E. M.

Publications and source records attributed to Wolkovich, E. M..

3 recordsLinked to original sources

bioRxiv2023

How to define, use, and interpret Pagel's lambda (lambda) in ecology and evolution

1Pagels {lambda} (lambda) is a critical tool in ecology and evolution for describing trait evolution, imputing missing species data, and generalising ecological relationships beyond their study system. Yet the interpretation of {lambda} depends on context, and there are many misconceptions about metrics that are similar but not identical to {lambda}. As an index of phylogenetic signal applied to continuous traits, {lambda} typically (but not always) ranges between 0 and 1, and is a rate-independent measure of the degree to which closely-related species resemble one-another relative to a Brownian motion expectation. But this measure is biased by non-random species sampling--a common characteristic of ecological data--which also makes phylogenetic imputation of missing traits challenging. The {lambda} estimated in regression models has little to do with the phylogenetic signal of measured traits and is better considered as either a statistical correction or a measure of the impact of unmeasured (latent) traits in the model. In other contexts, such as hierarchical models including intra-specific variation, {lambda} is frequently confused with distinct metrics such as h2. We show how confusion in defining and using {lambda} can mislead our interpretation of ecological and evolutionary processes. Open research statementNo data were used or collected as part of this work.

evolutionary biology↗

bioRxiv2021

A simple explanation for declining temperature sensitivity with warming

Temperature sensitivity--the magnitude of a biological response per {degrees}C--is a fundamental concept across scientific disciplines, especially biology, where temperature determines the rate of many plant, animal and ecosystem processes. Recently, a growing body of literature in global change biology has found temperature sensitivities decline as temperatures rise (Fuet al., 2015; Gusewell et al., 2017; Piao et al., 2017; Chen et al., 2019; Dai et al., 2019). Such observations have been used to suggest climate change is reshaping biological processes, with major implications for forecasts of future change. Here we present a simple alternative explanation for observed declining sensitivities: the use of linear models to estimate non-linear temperature responses. We show how linear estimates of sensitivities will appear to decline with warming for events that occur after a cumulative thermal threshold is met--a common model for many biological events. Corrections for the non-linearity of temperature response in simulated data and long-term phenological data from Europe remove the apparent decline. Our results show that rising temperatures combined with linear estimates based on calendar time produce observations of declining sensitivity--without any shift in the underlying biology. Current methods may thus undermine efforts to identify when and how warming will reshape biological processes. Significance statementRecently a growing body of literature has observed declining temperature sensitivities of plant leafout and other events with higher temperatures. Such results suggest that climate change is already reshaping fundamental biological processes. These temperature sensitivities are often estimated as the magnitude of a biological response per {degrees}C from linear regression. The underlying model for many events--that a critical threshold of warmth must be reached to trigger the event--however, is non-linear. We show that this mismatch between the statistical and biological models can produce the illusion of declining sensitivities with warming using current methods. We suggest simple alternative approaches that can better identify when and how warming will reshape biological processes.

plant biology↗

bioRxiv2018

On the importance of accounting for intraspecific genomic relatedness in multi-species studies

1. Analyses in many fields of ecology are increasingly considering multiple species and multiple individuals per species. Premises of statistical tests are often violated with such datasets because of the non-independence of residuals due to phylogenetic relationships or intraspecific population structure. Comparative approaches that account for the phylogenetic relationship of species--for which the benefits are demonstrated--are well developed. However, the importance of accounting for the intraspecific genetic structure, especially with the phylogenetic structure, is rarely addressed in the ecological literature.\n\n2. We investigated whether it is beneficial to account for intraspecific genomic relatedness in multi-species studies. For this, we used a Phylogenetic Mixed Model to analyze simulated data and results from a budburst experiment where clippings of 10 tree and shrub species were subjected to different treatments in terms of temperature and photoperiod.\n\n3. We found that accounting for intraspecific genomic relatedness yields more accurate and precise fixed effects as well as increased statistical power, but more so when the relative importance of the intraspecific to the phylogenetic genetic structure is greater. Analysis of the budburst experiment further showed that accounting for intraspecific and phylogenetic structures yields improved estimates of warming and photoperiod effects and their interactions in explaining the time to budburst.\n\n4. Our results show that important statistical gains can be made by incorporating information on the intraspecific genomic relatedness of individuals in multi-species studies. This is relevant for investigations that are interested in intraspecific variation and that plan to include such observations in statistical tests.

ecology↗