Eastern Washington University
Measuring variation in body morphology and life history traits in Brook Stickleback (Culaea inconstans), Eastern Washington, USA
Abstract
dc:description.abstract<p>For freshwater ecosystems, invasive species are considered a major threat to biodiversity, and pose a challenge to those attempting to advance management strategies aimed at conserving natural populations. An invasive species’ ability to successfully invade a new ecosystem may be influenced by phenotypic plasticity, flexibility of life history traits, and the ability to migrate/disperse, among other factors. Brook stickleback (Culaea inconstans) have been a concern in eastern Washington since 1999 when they were discovered in water bodies on Turnbull National Wildlife Refuge. The purpose of this project was to describe potential variation in body morphology traits between systems that differed in environmental factors. BSB were collected at sites throughout the Rock Creek drainage along with environmental measures. Brook stickleback showed variation for all morphology measures between sites (p< 0.0001). Lentic and lotic systems expressed difference in a variety of traits (head depth, eye diameter, pelvic spine length, and anal spine length (p< 0.00455). Permanent and non-permanent systems expressed differences in weight, standard length, body depth, head length, head depth, eye diameter, gape width, and dorsal spine length (p< 0.00455). These results may lay the groundwork for future studies that may determine with more certainty how traits are changing and how quickly.</p>
Degree
thesis:*- Name thesis:degree_name
- Master of Science (MS) in Biology
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Biology
- Year
- 2020
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Crytser, Lily
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- Access is available to all users
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://dc.ewu.edu/theses/650
- OAI identifier oai:identifier
- oai:dc.ewu.edu:theses-1650