Preferred Name

Christine Verdream

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Date of Graduation

5-7-2020

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Department of Biology

Advisor(s)

Christine May

Abstract

The James spinymussel (Parvaspina collina) is Critically Endangered and endemic to Virginia’s James River basin. P. collina was listed as Endangered in 1988 and more than 90% of the species has been lost over the last 30 years (USFWS 1990). Despite the development of a recovery plan in 1990, there has not been a comprehensive reassessment of P. collina in over 30 years. This study explored the relationship between flooding and P. collina population dynamics in a flood prone stream and further explained habitat occupancy. Study sites included Swift Run and Little Oregon Creek, both of which still support viable populations of P. collina. Swift Run was the focus of the effects of flooding on population trends, while habitat occupancy utilized both sites. The best fit generalized linear model to explain the relationship between emigration/immigration and discharge (cfs) was simple linear regression. Discharge was able to explain 57% of the variation in emigration and 42% in immigration. Additionally, emigration and immigration were both significantly greater following floods (≥ 3,500 cfs) compared to low flows (p < 0.01 & p =0.015). The best fit Cormack – Jolly – Seber model was used to estimate survival (φ) and recapture (p) probabilities after floods and low flow events for each year. All survival estimates were > 90%, while recapture estimates ranged from 41% to 79%. Habitat occupancy analysis examined the probability of habitat patch occupancy and stability with logistic regression models. The best-fit occupancy model incorporated depth as a significant predictor of occupancy and was able to predict the occupancy of 60% of patches in Swift Run and 85% in Little Oregon Creek. The best fit stability model incorporated depth and grain size as significant predictors of stability and was able to accurately predict the stability of 83% of occupied patches at Swift Run. Additionally, Swift Run had significantly higher valve lengths for P. collina and Villosa constricta (p < 0.001). These results are intended to aid agency officials when determining locations to release propagated mussels and to understand the impacts flooding can have on mussel communities.

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