CHELSEA N MILLER
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Chelsea N. Miller, Ph.D. 

NSF Postdoctoral Fellow

@ The Holden Arboretum, Kirtland, OH

  • Studying the effects of climate change-induced variation in the phenology of plant-insect interactions on herbaceous plant distributions 

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Using observational and experimental laboratory and field techniques, computational analyses, and ecological niche modeling, I address questions such as:

1. How does fine-scale variation in species interactions scale up to impact regional distributions of species? ​

2. How does climate change impact the timing of mutualistic and antagonistic insect-plant interactions across environmental gradients?

3. How do climate change-exacerbated natural disturbances impact composition of forest insect communities and interactions between host trees and phytophagous insects?

Links: 
  • cnmiller@holdenfg.org
  • CV
  • ​​Google Scholar
  • Research Gate

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NSF Postdoctoral Fellowship in Biology
June 2022 - May 2024
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PictureDr. Katie Stuble, Community Ecologist @ Holden Arboretum
INTEGRATING PHENOLOGY AND SPECIES INTERACTIONS INTO PREDICTIONS OF SPRING EPHEMERAL DISTRIBUTIONS

Using living collections of plants across a regional network of arboreta and botanical gardens, our team addresses whether phenological plasticity of plant traits (flowering, fruiting, senescence) and critical plant-animal interactions (pollination, dispersal, herbivory) can mitigate climate change-driven range shifts in spring ephemerals. In collaboration with citizen scientists, data collected across this common garden will be integrated into Trait-Based Distribution Models to incorporate species interactions, phenology, plasticity, and local adaptation into predictions of future plant distributions under climate change. Work conducted in collaboration with members of the Stuble Lab at The Holden Arboretum.

Past Postdoctoral research 
​2020 - 2022

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I was a postdoc in Dr. Kamal Gandhi's Forest Entomology Lab at the Warnell School of Forestry and Natural Resources at the University of Georgia from September 2020 - June 2022.

My work focused on the impacts of severe wind disturbances on populations and community assembly of subcortical insects (Cerambycids and Buprestids) in southeastern U.S. planted and natural pine forests. During this postdoc, I collaborated broadly with private foresters, USDA USFS employees, and students, faculty and staff at UGA and beyond. 
Featured research: 
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New publication out in Diversity and Distributions: Reproductive traits explain occupancy of predicted distributions in a genus of eastern North American understory herbs.

My coauthors and I determined whether reproductive traits relating to biotic and dispersal factors explain differences between estimated potential and occupied geographic distributions for 21 species of Trillium. We estimated fundamental niches and associated predicted suitable distributions using climate-calibrated ecological niche models and defined occupied distributions as the intersection between known ranges and predicted suitable areas (PSAs). We then calculated proportional occupancy of the predicted suitable distribution (PO) by dividing the area of the occupied distribution by the PSA. Reproductive traits (ovule number, seed set, number of seeds/plant, seed mass, adult biomass, flower type: sessile/pedicellate) were related to PO using beta regression models.
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Takeaways:

1. There was considerable variation in PO across species (1.1%–96%, mean = 51%). The majority of species that filled < 60% of their potential range had sessile flowers, whereas the majority of species that filled > 60% of their potential range had pedicellate flowers. (Fig. 2).
2. The best-fit model found significantly lower PO for sessile-flowered species. (Fig. 3). Ovule number and seed mass were also significant predictors of PO.
3. Variation in PO among Trillium species can be explained by flower type, ovule number and seed mass—biotic traits related to dispersal ability.

Variation in dispersal potential stemming from primary and long-distance dispersers is related to the ability to occupy the predicted suitable distribution in Trillium.
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