Abstract

Identifying genetically appropriate plant materials for seed based restoration relies on the principle of local adaptation where the objective is to match adaptive genetic characteristics to variation in ecological clines pertinent to plant establishment and persistence. In this study, basin wildrye (Leymus cinereus (Scribn. & Merr.) Á. Löve) sources from 25 wild populations and 4 commercial varieties were planted at 4 test sites. We assessed initial establishment and short term persistance. Plantings failed at 2 sites in both 2013 and 2014, with too few plants to quantify differences. At the remaining 2 sites, local sources had higher initial establishment in just 1 of 10 comparisons. Among commercial sources, the cultivars Magnar and Trailhead initially outperformed local pooled materials at Fountain Green but not at Nephi. Initial establishment under row cover was dramatically better than uncovered controls at both sites, but only persisted for 4 years after planting at the Fountain Green site. The native forb study evaluated the effects of species, sowing depth and row cover on field emergence of 20 forbs. Overall, emergence was very low ranging between 0.2% and 1.0% for 16 of the 20 species. Four species exceeded 1% emergence. Depth effects were species, site and year dependent. The odds of emergence decreased with increasing depth for four species, increased for three species and were mixed between sites and years for the remaining species. The odds of emergence were better under row cover than for uncovered control plots. Depths evaluated were deeper than recommended for most species and likely hindered emergence for some species. Site and year had much more effect on observed emergence than depth or treatment. Developing simple diagnostics to identify subspecies is key in the restoration of sagebrush ecosystems. We evaluated the SoilWeb app as a tool to identify sagebrush in the field. We evaluated the accuracy of the Richardson et.al. (2015) technique to classify sagebrush stands and evaluated data modeling strategies to improve classification accuracy. We found the SoilWeb app to be an accurate and informative tool to identify native-wild sagebrush populations. The Richardson et.al. (2015) seed weight criteria correctly classified just 19% of our sample populations to the correct subspecies. To improve upon this, we evaluated multifactor modeling using recursive partitioning and classification trees. Our most accurate classification tree correctly classified 80% of 2x tridentata sites but just 45% of wyomingensis sites.

Degree

PhD

College and Department

Plant and Wildlife Sciences

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2020-03-16

Document Type

Dissertation

Handle

http://hdl.lib.byu.edu/1877/etd11701

Keywords

local adaptation, basin wildrye, sowing depth, big sagebrush, seed weight

Language

english

Included in

Life Sciences Commons

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