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Emma E. Goldberg

Researcher at University of Minnesota

Publications -  50
Citations -  5125

Emma E. Goldberg is an academic researcher from University of Minnesota. The author has contributed to research in topics: Population & Macroevolution. The author has an hindex of 27, co-authored 48 publications receiving 3944 citations. Previous affiliations of Emma E. Goldberg include University of Illinois at Chicago & University of Maryland, College Park.

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TRY plant trait database : Enhanced coverage and open access

Jens Kattge, +754 more
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
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Species Selection Maintains Self-Incompatibility

TL;DR: It is shown that in the nightshade plant family (Solanaceae), species with functional self-incompatibility diversify at a significantly higher rate than those without it, and the apparent short-term advantages of potentially self-fertilizing individuals are offset by strong species selection, which favors obligate outcrossing.
Journal ArticleDOI

Model inadequacy and mistaken inferences of trait-dependent speciation

TL;DR: It is shown that for many empirical phylogenies, characters simulated in the absence of state-dependent diversification exhibit an even higher Type I error rate, indicating that the method is susceptible to additional, unknown model inadequacies.
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Model Inadequacy and Mistaken Inferences of Trait-Dependent Speciation

TL;DR: For example, this article showed that for many empirical phylogenies, characters simulated in the absence of state-dependent diversification exhibit an even higher Type I error rate, indicating that the method is susceptible to additional, unknown model inadequacies.
Journal ArticleDOI

Phylogenetic inference of reciprocal effects between geographic range evolution and diversification.

TL;DR: In this paper, the authors introduce a likelihood-based approach to estimate region-dependent rates of speciation, extinction, and range evolution from a phylogeny, using a new model in which these processes are interdependent.