Dataset Information

Use of auto-germ to model germination timing in the sagebrush-steppe.

ABSTRACT: Germination timing has a strong influence on direct seeding efforts, and therefore is a closely tracked demographic stage in a wide variety of wildland and agricultural settings. Predictive seed germination models, based on soil moisture and temperature data in the seed zone are an efficient method of estimating germination timing. We utilized Visual Basic for Applications (VBA) to create Auto-Germ, which is an Excel workbook that allows a user to estimate field germination timing based on wet-thermal accumulation models and field temperature and soil moisture data. To demonstrate the capabilities of Auto-Germ, we calculated various germination indices and modeled germination timing for 11 different species, across 6 years, and 10 Artemisia-steppe sites in the Great Basin of North America to identify the planting date required for 50% or more of the simulated population to germinate in spring (1 March or later), which is when conditions are predicted to be more conducive for plant establishment. Both between and within the species, germination models indicated that there was high temporal and spatial variability in the planting date required for spring germination to occur. However, some general trends were identified, with species falling roughly into three categories, where seeds could be planted on average in either fall (Artemisia tridentata ssp. wyomingensis and Leymus cinereus), early winter (Festuca idahoensis, Poa secunda, Elymus lanceolatus, Elymus elymoides, and Linum lewisii), or mid-winter (Achillea millefolium, Elymus wawawaiensis, and Pseudoroegneria spicata) and still not run the risk of germination during winter. These predictions made through Auto-Germ demonstrate that fall may not be an optimal time period for sowing seeds for most non-dormant species if the desired goal is to have seeds germinate in spring.

SUBMITTER: Richardson WC

PROVIDER: S-EPMC6303710 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Use of auto-germ to model germination timing in the sagebrush-steppe.

Richardson William C WC Whitaker Dallin R DR Sant Kyler P KP Barney Nicholas S NS Call Ryan S RS Roundy Bruce A BA Aanderud Zachary T ZT Madsen Matthew D MD

Ecology and evolution 20181114 23

Germination timing has a strong influence on direct seeding efforts, and therefore is a closely tracked demographic stage in a wide variety of wildland and agricultural settings. Predictive seed germination models, based on soil moisture and temperature data in the seed zone are an efficient method of estimating germination timing. We utilized Visual Basic for Applications (VBA) to create Auto-Germ, which is an Excel workbook that allows a user to estimate field germination timing based on wet-t ...[more]

PMID: 30598754

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Project description:Background:Precipitation is predicted to become more variable in the western United States, meaning years of above and below average precipitation will become more common. Periods of extreme precipitation are major drivers of interannual variability in ecosystem functioning in water limited communities, but how ecosystems respond to these extremes over the long-term may shift with precipitation means and variances. Long-term changes in ecosystem functional response could reflect compensatory changes in species composition or species reaching physiological thresholds at extreme precipitation levels. Methods:We conducted a five year precipitation manipulation experiment in a sagebrush steppe ecosystem in Idaho, United States. We used drought and irrigation treatments (approximately 50% decrease/increase) to investigate whether ecosystem functional response remains consistent under sustained high or low precipitation. We recorded data on aboveground net primary productivity (ANPP), species abundance, and soil moisture. We fit a generalized linear mixed effects model to determine if the relationship between ANPP and soil moisture differed among treatments. We used nonmetric multidimensional scaling to quantify community composition over the five years. Results:Ecosystem functional response, defined as the relationship between soil moisture and ANPP, was similar among irrigation and control treatments, but the drought treatment had a greater slope than the control treatment. However, all estimates for the effect of soil moisture on ANPP overlapped zero, indicating the relationship is weak and uncertain regardless of treatment. There was also large spatial variation in ANPP within-years, which contributes to the uncertainty of the soil moisture effect. Plant community composition was remarkably stable over the course of the experiment and did not differ among treatments. Discussion:Despite some evidence that ecosystem functional response became more sensitive under sustained drought conditions, the response of ANPP to soil moisture was consistently weak and community composition was stable. The similarity of ecosystem functional responses across treatments was not related to compensatory shifts at the plant community level, but instead may reflect the insensitivity of the dominant species to soil moisture. These species may be successful precisely because they have evolved life history strategies that buffer them against precipitation variability.

Project description:Sagebrush (Artemisia spp.) steppe is one of North America's most imperiled ecosystems, as the result of many factors including grazing, development, fire, and invasion of exotic plants. Threats to sagebrush steppe are expected to increase because of climate change and further human development. Many songbirds use sagebrush steppe opportunistically, but a few obligate species are dependent on it. To quantify the habitat associations of three sagebrush obligates, the Sage Thrasher (Oreoscoptes montanus), Sagebrush Sparrow (Artemisiospiza nevadensis), and Brewer's Sparrow (Spizella breweri), and nine other songbird species that use this habitat, we surveyed across a broad region of Idaho. At each of 104 sites, we selected three plots, one each in relatively poor, moderate, and good condition, defined qualitatively by the cover of native shrubs. We quantified bird abundance by point counts, described the habitat at these points by a line-intercept method, and at each plot calculated the fraction of a circle (radius 1 km) covered in shrubs or grassland. We compared two-scale occupancy models based on these data by the information-theoretic approach. According to the models, our qualitative assessment of habitat condition within a site distinguished birds' use of relatively good habitat from their use of poor habitats only, not from those in moderate condition. Thus the sagebrush-obligate species may tolerate some local habitat degradation, at least up to some unidentified threshold. Occurrence of all three sagebrush obligates correlated well with one or more characteristics of sagebrush such as its cover, height, or heterogeneity in height. They differed in the Sage Thrasher being most sensitive to sagebrush cover, the Sagebrush Sparrow being found more often at lower elevations, and the Brewer's Sparrow being less sensitive to ground cover. The nine other species evaluated were less or negatively associated with attributes of sagebrush. On the basis of these results, we suggest that the three sagebrush obligates are best conserved by promoting shrublands over a broad range of elevations, containing both sagebrush and other shrubs in patches of mixed height, and minimizing invasive annual grasses.

Dataset Information

Use of auto-germ to model germination timing in the sagebrush-steppe.

Publications

Use of auto-germ to model germination timing in the sagebrush-steppe.

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