Albecker Molly

No Thumbnail Available
Last Name
Albecker
First Name
Molly
ORCID

Filters

2022 3
3
3
Reset filters

Settings

Search Results

Now showing 1 - 3 of 3
  • Dataset
    Metadata for studies from meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2022-10-14) Albecker, Molly ; Trussell, Geoffrey ; Lotterhos, Katie
    Covariance can exist between the genetic and environmental influences on phenotype (CovGE) and can have an important role in ecological and evolutionary processes in nature and population responses to environmental change. CovGE is commonly called countergradient variation (CnGV; negative CovGE)or cogradient variation (CoGV; positive CovGE)and has been recognized in classic studies that have established several long-standing hypotheses about CnGV and CoGV. For instance, it is hypothesized that CnGV is more prevalent in nature than CoGV, that CnGV is more prevalent in fish, amphibian, and invertebrate taxa, across latitudinal or altitudinal environmental gradients, and more frequently occurs in metabolic compensation traits, including development, growth, feeding, metabolism, and activity, while CoGV is more commonly observed in morphological traits. The recent development of a standardized method to measure CovGE allows for the first rigorous quantitative exploration of these hypotheses. We use meta-analysis and apply the novel quantitative method to test whether the above hypotheses are supported in the literature. We found no differences in frequency of CnGV and CoGV, and no systematic patterns relative to taxa, environmental gradient, or trait type. However, our analyses suggest that CovGE may be as common as gene by environment (GxE) interactions. Given that CovGE is likely to have a strong impact on future outcomes for organisms experiencing environmental change, that significant CovGE occurred frequently, and the lack of systematic patterns in the occurrence of CovGE, we encourage a more widespread application of measuring CovGE. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/877414
  • Dataset
    Results using simulated data used to conduct power analyses
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2022-10-15) Albecker, Molly ; Trussell, Geoffrey ; Lotterhos, Katie
    Spatial covariance between genotypic and environmental influences on phenotypes (CovGE) can result in the nonrandom distribution of genotypes across environmental gradients and is a potentially important factor driving local adaptation. However, a framework to quantify the magnitude and significance of CovGE has been lacking. We develop a novel quantitative/analytical approach to estimate and test the significance of CovGE from reciprocal transplant or common garden experiments, which we validate using simulated data. We demonstrate how power to detect CovGE changes over a range of experimental designs. We confirm an inverse relationship between gene-by-environment interactions (GxE) and CovGE, as predicted by first principles, but show how phenotypes can be influenced by both. The metric provides a way to measure how phenotypic plasticity covaries with genetic differentiation and highlights the importance of understanding the dual influences of CovGE and GxE on phenotypes in studies of local adaptation and species’ responses to environmental change. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/877456
  • Dataset
    Results from a meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results in published literature
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2022-10-14) Albecker, Molly ; Trussell, Geoffrey ; Lotterhos, Katie
    Covariance can exist between the genetic and environmental influences on phenotype (CovGE) and can have an important role in ecological and evolutionary processes in nature and population responses to environmental change. CovGE is commonly called countergradient variation (CnGV; negative CovGE)or cogradient variation (CoGV; positive CovGE)and has been recognized in classic studies that have established several long-standing hypotheses about CnGV and CoGV. For instance, it is hypothesized that CnGV is more prevalent in nature than CoGV, that CnGV is more prevalent in fish, amphibian, and invertebrate taxa, across latitudinal or altitudinal environmental gradients, and more frequently occurs in metabolic compensation traits, including development, growth, feeding, metabolism, and activity, while CoGV is more commonly observed in morphological traits. The recent development of a standardized method to measure CovGE allows for the first rigorous quantitative exploration of these hypotheses. We use meta-analysis and apply the novel quantitative method to test whether the above hypotheses are supported in the literature. We found no differences in frequency of CnGV and CoGV, and no systematic patterns relative to taxa, environmental gradient, or trait type. However, our analyses suggest that CovGE may be as common as gene by environment (GxE) interactions. Given that CovGE is likely to have a strong impact on future outcomes for organisms experiencing environmental change, that significant CovGE occurred frequently, and the lack of systematic patterns in the occurrence of CovGE, we encourage a more widespread application of measuring CovGE. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/877425