Author
CLINE, NATHAN - Brigham Young University | |
ROUNDY, BRUCE - Brigham Young University | |
Hardegree, Stuart |
Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only Publication Acceptance Date: 9/1/2010 Publication Date: 2/6/2011 Citation: Cline, N., Roundy, B., Hardegree, S.P. 2011. Germination prediction from soil moisture and temperature data across the Great Basin. In: Abstracts of the 64th Annual Meeting, Society for Range Management, Billings, MT, Feb 6-10, 2011 (CD-ROM Abstract). Interpretive Summary: Technical Abstract: Preventing cheatgrass (Bromus tectorum) dominance associated with frequent wildfires depends, in part, on successful establishment of desirable species sown in fire rehabilitation and fuel control projects. We tested the effects of fire, herbicide applications, and mechanical treatments on predicted germination of five cheatgrass collections, six bunchgrasses, and three forb species using near surface (1-3 cm) soil moisture potential and temperature at 28 sites in the Great Basin. Sites included grasslands (Elymus spp. and Agropyron spp.) and sagebrush stands (Artemisia spp.) either invaded or not invaded by woodland species (Juniperus spp. and Pinus spp.). Potential germination was estimated using wet thermal accumulation models developed in the laboratory for each seed collection. These models were constructed in previous studies by exposing seeds to a range of constant temperatures and calculating the degree hours above a base temperature threshold required to germinate 50% of germinable seeds. Thermal accumulation and progress toward germination in field seedbeds was calculated from field soil temperatures when soil was wetter than – 1.5 MPa as measured by thermocouples and gypsum blocks. Treatments had much less effect on surface soil moisture and temperature and predicted germination than did site or year. Successful germination for most species was predicted on many sites in spring. Seedling establishment may be more limited by seedling survival than germination. This approach to modeling germination could be used for ranking potential species success and developing more performance-based selection of revegetation species for rangelands. |