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Predicting germination in semi-arid wildland seedbeds II. Field validation of wet thermal-time models
Institution:1. Department of Cardiology, Azerbaijan Medical University, Baku, Azerbaijan;2. Department of Anesthesiology, Azerbaijan Medical University, Baku, Azerbaijan;3. Heart Rhythm Service, Department of Cardiology, Istanbul Medicine Hospital, Istanbul, Turkey;4. Department of Nephrology, Azerbaijan Medical University, Baku, Azerbaijan;1. L''Université Nantes Angers Le Mans, Oniris, Nantes F-44322, cedex 3, France;2. Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece;3. Institut National de la Recherche Agronomique, UMR1014 Sécurité des Aliments Microbiologie, Nantes F-44307, France
Abstract:Accurate prediction of germination for species used for semi-arid land revegetation would support selection of plant materials for specific climatic conditions and sites. Wet thermal-time models predict germination time by summing progress toward germination subpopulation percentages as a function of temperature across intermittent wet periods or within singular wet periods. Wet periods may be defined by any reasonable seedbed water potential above which seeds are expected to imbibe sufficiently to germinate. These models may be especially applicable to the Artemisia steppe of the western U.S.A. where water availability limits germination in summer and early fall while cool temperatures limit germination in late fall, winter, and spring when soil water is available. To test accuracy of wet thermal-time models we placed seedbags with seeds of five species commonly used in wildland revegetation, as well as two collections of the invasive annual grass, Bromus tectorum L. into Artemisia tridentata Nutt. ssp. wyomingensis Beetle and Young zone seedbeds for 19 field incubation periods over four seasons. Hourly surface (1–3 cm) soil temperatures and soil water potentials were measured near the seedbags. These data were input into thermal-time models which predicted time to germination for each seedbag retrieval date. Binomial data representing agreement (1) or lack of agreement (0) of predicted and actual germination for each retrieval date were analyzed using logistic regression. Thermal summation method, season, water potential threshold, and species most affected accuracy of predictions (P < 0.0002). A model which defined a wet period as ≥?1.5 MPa soil water potential and summed progress toward germination across intermittent wet periods was most accurate in predicting actual germination by a retrieval date. Across all species, this model correctly predicted that germination would occur in seedbags 75–95% of the time over the latewinter to mid-spring seasons, but only 50–71% of the time for the fall-early winter season when time of soil water availability was least. Although the wet thermal-time model overestimated time to germination for some species and seasons, its accuracy should be high enough to evaluate germination potential by mid-spring for different species, sites, and climatic conditions.
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