The Southern Rocky Mountain Interactive Flora (SRMIF) and factors correlated with recognition of plants and mammals

This dissertation has two components: The Southern Rocky Mountain Interactive Flora (SRMIF) and the Species Identification Survey (SIS): Factors correlated with recognition of plants and mammals. A taxonomic informatics tool in progress, the SRMIF is an online interactive identification key. It employs Lucid software and will be a synthesis of the vascular plants of the Southern Rocky Mountain Region (Colorado, plus counties from New Mexico and Wyoming), with approximately 3750 taxa. Conceptual and logistical challenges are being overcome. One is the formulation of plant characters and character states; the master SRMIF data matrix includes 2,088 character states. Combined Lucid data matrices initiated by the author, at various stages of completion, include 3,920,946 boxes. Phases of the SRMIF are being released successively. Phase 1 is an available online key to families. Phase 2, nearly complete, is for genera. Phase 3, species, will follow. Phase 4 will provide text, photographs, a specimen database, and hyperlinks. Completed groundwork for the key includes a species checklist and updates to plant family acronyms. Lucid files are included on CD-ROM.; The SIS assesses plant and mammal recognition knowledge (RK) among UNC students and employees, and tests correlations between RK and demographic variables. Pilot participants viewed 30 PowerPoint slides of common, distinctive Colorado plant genera and wrote names. Main study participants viewed 24 "randomly" ordered slides of "well-known" plants, and animals "at large," 6 from each of 4 groups: plants of Colorado, plants of the world, mammals of Colorado, and mammals of the world. Participants selected common names from five-answer multiple-choice questions. For both surveys participants answered demographic and experience-related questions.; The pilot study demonstrated low levels of Colorado plant RK, whereas in the main study overall mammal recognition surpassed plant recognition. Variables significantly correlated with higher RK included learning experiences, years in region, and rural residence. Factor analysis loaded learning experiences questions into two components.; Tools such as the SRMIF can help counter effects of urbanization, increasing awareness of biodiversity.