skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Search for: All records

Creators/Authors contains: "Voje, Kjetil L"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract Models based on the Ornstein–Uhlenbeck process have become standard for the comparative study of adaptation. Cooper et al. (2016) have cast doubt on this practice by claiming statistical problems with fitting Ornstein–Uhlenbeck models to comparative data. Specifically, they claim that statistical tests of Brownian motion may have too high Type I error rates and that such error rates are exacerbated by measurement error. In this note, we argue that these results have little relevance to the estimation of adaptation with Ornstein–Uhlenbeck models for three reasons. First, we point out that Cooper et al. (2016) did not consider the detection of distinct optima (e.g. for different environments), and therefore did not evaluate the standard test for adaptation. Second, we show that consideration of parameter estimates, and not just statistical significance, will usually lead to correct inferences about evolutionary dynamics. Third, we show that bias due to measurement error can be corrected for by standard methods. We conclude that Cooper et al. (2016) have not identified any statistical problems specific to Ornstein–Uhlenbeck models, and that their cautions against their use in comparative analyses are unfounded and misleading. [adaptation, Ornstein–Uhlenbeck model, phylogenetic comparative method.] 
    more » « less
  2. Abstract Allometric scaling describes the relationship of trait size to body size within and among taxa. The slope of the population‐level regression of trait size against body size (i.e. static allometry) is typically invariant among closely related populations and species. Such invariance is commonly interpreted to reflect a combination of developmental and selective constraints that delimit a phenotypic space into which evolution could proceed most easily. Thus, understanding how allometric relationships do eventually evolve is important to understanding phenotypic diversification. In a lineage of fossil Threespine Stickleback (Gasterosteus doryssus), we investigated the evolvability of static allometric slopes for nine traits (five armour and four non‐armour) that evolved significant trait differences across 10 samples over 8500 years. The armour traits showed weak static allometric relationships and a mismatch between those slopes and observed evolution. This suggests that observed evolution in these traits was not constrained by relationships with body size, perhaps because prior, repeated adaptation to freshwater habitats by Threespine Stickleback had generated strong selection to break constraint. In contrast, for non‐armour traits, we found stronger allometric relationships. Those allometric slopes did evolve on short time scales. However, those changes were small and fluctuating and the slopes remained strong predictors of the evolutionary trajectory of trait means over time (i.e. evolutionary allometry), supporting the hypothesis of allometry as constraint. 
    more » « less
  3. The origins of cheilostome bryozoans and parental care in this group are substantially older than previously thought. 
    more » « less