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Selected Data Visualizations

NOAA Fisheries surveys off the west coast of the United States

I built this R Shiny App to visualize the timing (day of year, year) and spatial extent (latitude and longitude) of seven at-sea surveys that I've used to parameterize an end-to-end ecosystem model. This app has served a useful way to communicate the details of the surveys with collaborators and colleagues interested in our ecosystem model.

End-to-end ecosystem model results

I built this R Shiny App to visualize the effects of pyrosome blooms on other species. This app allows the user to select functional groups of interest and returns plots of end-to-end ecosystem model simulations.

Birds and bats avoid noise

These visualizations are from our 2021 paper in Nature Communications. A, B, and D depict raw data with conditional fitted lines from generalized linear mixed-effects models (with 95% CI). C depicts phylogenetically-controlled generalized least squares models. 

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Gomes et al. (2021) Nature Communications

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Arthropods respond to river noise

These Bayesian generalized linear mixed-effects model (GLMM) visualizations are from our 2021 paper in Oikos. The figure on the left are point estimates with 80% and 90% credible intervals for each arthropod order and trap type combination. The figure below shows raw data and conditional interaction effects (estimated by a GLMM) between sound pressure level and sound frequency on two aquatic insects.

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Gomes et al. (2021) Oikos

Orb-weaving spiders are more abundant in noise

These visualizations are from our 2021 paper in Functional Ecology. Figures (a)-(d) on the left depict point estimates and credible intervals from Bayesian generalized linear mixed-effects models. Silhouettes show direction of change. The figure on the right shows raw abundance data for two species of orb-weaving spiders and 100 posterior draws for the conditional effects of sound pressure level on abundance. 

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Gomes et al. (2021) Functional Ecology

Vertical stratification of bats in the neotropics

This visualization is from our 2020 paper in PeerJ. Here I show point estimates and credible intervals (80 and 90%), from a Bayesian generalized linear mixed-effects model, for the abundance of various bat species/groups in the canopy and understory. 

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Gomes et al. (2020) PeerJ

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