Precipitation and invasive winter annual grass data for the Great Plains
Data files
Aug 25, 2024 version files 11.45 KB
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dryad_data.csv
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README.md
Abstract
Aim: Climate change is predicted to increase spatial extent and equilibrium abundance of many invasive species, and there is evidence this may already be happening. In North American grasslands, the most concerning invaders are winter annuals. Understanding winter annual responses to climate change is challenging because these species are regulated by weather during multiple seasons, unlike perennials that are overwhelmingly regulated by growing season precipitation. We quantified downy brome (Bromus tectorum L. (ITIS)) and Japanese brome (Bromus japonicus Thunb.) responses to precipitation and temperature. These functionally similar invasive winter annual grasses are destroying wildlife habitat, reducing livestock production, and increasing wildfire risks across vast portions of the western U.S.
Location: Great Plains, U.S.A.
Methods: Using Bayesian methods to integrate experimental and long-term (30 yr) monitoring data, we estimated the effects of precipitation and temperature on biomass production of bromes and native species.
Results: Unsurprisingly, brome biomass increased with the current growing season (spring) precipitation. Alternatively, brome biomass declined with previous growing season precipitation, perhaps because previously wet conditions strengthened perennial competitors of bromes. These positive and negative effects of growing season precipitation largely cancelled out and left mean brome biomass unchanged. This suggests bromes will be insensitive to changes in growing season precipitation. Conversely, bromes proved highly sensitive to fall precipitation. Fall precipitation is necessary for germination, and brome biomass in the current growing season increased with precipitation the previous fall (p<0.0001), two falls ago (p<0.001), and likely even three falls ago (p=0.09).
Conclusions: Fall precipitation is projected to increase in much of the western U.S., and a mere 5% (3.0 mm) increase would cause an 11% (7%, 14%) [mean(95% confidence interval)] increase in brome biomass. These results should urge increased focus on fall weather to understand winter annual plant responses to climate change.
README: Precipitation and invasive winter annual grass data for the Great Plains
https://doi.org/10.5061/dryad.jh9w0vthk
Description of the data and file structure
Files and variables
Data fields, which are named in the first row of the file, indicate:
1) Site. This is a number identifying the research site. To determine which number corresponds with which site, see Appendix A1.
2) Year of vegetation sampling
3) Julian day of vegetation sampling
4) Precipitation in millimeters from September 1 to November 15 three years before vegetation measurement
5) Precipitation in millimeters from September 1 to November 15 two years before vegetation measurement
6) Precipitation in millimeters from September 1 to November 15 the year before vegetation measurement
7) Precipitation in millimeters from March 1 to June 15 the year before vegetation measurement
8) Precipitation in millimeters from March 1 to June 15 the year of vegetation measurement
9) Biomass in grams per meter squared of the invasive winter annual grasses downy brome (Bromus tectorum L.) and Japanese brome (Bromus japonicus Thunb.)
10) Biomass in grams per meter squared of all herbaceous plants except downy brome and Japanese brome
Methods
We studied ten sites separated by ≤13 km on the 22,250-ha Fort Keogh Livestock and Range Research Laboratory (46°22’53”N 105°53’03”W). Soils were deep, well-drained loams (Pinehill, Eapa, Sonnett, Yamacall, Glendive) or silty loams (Kobase). In addition to bromes, vegetation included native perennial cool-season grasses (e.g. Pascopyrum smithii (Rydb.) A. Love and Hesperostipa comata [Trin. & Rupr.] Barkworth), native perennial warm season grasses (e.g Bouteloua gracilis (Willd. ex Kunth) Lag. ex Griffiths), native and nonnative forbs (e.g. Achillea millefolium L.), cactus (Opuntia polyacantha Haw.), and shrubs (e.g. Artemisia tridentata Nutt. and Artemisia cana Pursh).
One site was used for long-term fire research (Vermeire and Russell 2018, Vermeire et al. 2020), and from this site we used data from nine non-burned control plots (15 × 20 m) (Appendix A1: Table S1). This site was not grazed since 2001. Near peak standing crop from 2008 to 2020, four randomly placed 2500-cm2 circular quadrats were clipped to ground level within each plot, except three of the plots were burned in 2012 and therefore not included 2012-2020. Current-year biomass was sorted into functionally similar plant groups, dried to constant weight (60 °C), then weighed.
Another site had 12 plots (5 × 10 m) that were used for precipitation and grazing research. Some plots received precipitation reduction/addition treatments in 1994, 1998, 1999, and 2004-2007, and the site was not grazed since 1992, except some plots were intensely grazed in 1994, 1995, and 1998-2000 (Heitschmidt et al. 1999, Heitschmidt et al. 2005, Heitschmidt and Vermeire 2006, Vermeire and Rinella 2020). Biomass was measured1993-2023, except 2003, and data from plots that received grazing or water treatments were omitted from analysis for the treatment year and the following two years. Ten randomly placed 250-cm2 circular quadrats were clipped to ground level within each plot near the peak standing crop. Biomass was sorted into functionally similar plant groups, dried (60 °C, 48 h), and then weighed. From 2019-2023, we also sorted current-year biomass from old biomass produced the previous year. In the analysis section, we explain how we used regressions of old biomass on total biomass from the previous year to adjust data to reflect current-year biomass.
The other eight sites were pairs of grazed and adjacent not-grazed (since 1993) areas (Vermeire et al. 2018, Reinhart et al. 2021). Biomass was measured at each site in 1994-2008 and every two years from 2010 to 2022, except when spring grazing prior to measurement prevented accurate biomass estimation. This grazing occurred four years in two grazed sites, ten years in two grazed sites, and one year in two not-grazed sites that were unintentionally grazed in 2020. Twenty randomly placed 2500-cm2 square quadrats were clipped to ground level within each plot near the peak standing crop. Current-year biomass was sorted by species, dried (60 °C, 48 h), and weighed.
Literature cited
Heitschmidt, R. K., M. R. Haferkamp, M. G. Karl, and A. L. Hild. 1999. Drought and grazing: 1. Effects on quantity of forage produced. Journal of Range Management 52:440-446.
Heitschmidt, R. K., K. D. Klement, and M. R. Haferkamp. 2005. Interactive effects of drought and grazing on Northern Great Plains rangelands. Rangeland Ecology and Management 58:11-19.
Heitschmidt, R. K., and L. T. Vermeire. 2006. Can abundant summer precipitation counter losses in herbage production caused by spring drought. Rangeland Ecology and Management 59:392-399.
Reinhart, K. O., H. S. Sanni Worogo, M. J. Rinella, and L. T. Vermeire. 2021. Livestock increase soil organic carbon in the Northern Great Plains. Rangeland Ecology & Management 79:22-27.
Vermeire, L. T., and M. J. Rinella. 2020. Fall water effects on growing season soil water content and plant productivity. Rangeland Ecology & Management 73:252-258.
Vermeire, L. T., and M. L. Russell. 2018. Seasonal timing of fire alters biomass and species composition of northern mixed prairie. Rangeland Ecology & Management 71:714-720.
Vermeire, L. T., D. J. Strong, E. A. Gates, C. B. Marlow, and R. C. Waterman. 2020. Can mowing substitute for fire in semiarid grassland? Rangeland Ecology & Management 73:97-2020.
Vermeire, L. T., D. J. Strong, and R. C. Waterman. 2018. Grazing history effects on rangeland biomass, cover and diversity responses to fire and grazing utilization. Rangeland Ecology & Management 71:770-775.