Lasting signature of planting year weather on restored grasslands
Groves, Anna; Bauer, Jonathan; Brudvig, Lars (2020), Lasting signature of planting year weather on restored grasslands, Dryad, Dataset, https://doi.org/10.5061/dryad.6q573n5vt
Ecological restoration — the rebuilding of damaged or destroyed ecosystems — is a critical component of conservation efforts, but is hindered by inconsistent, unpredictable outcomes. We investigated a source of this variation that is anecdotally suggested by practitioners, but for which empirical evidence is rare: the weather conditions during the first growing season after planting. The idea of whether natural communities face long-term consequences from conditions even many years in the past, called historical contingency, is a debated idea in ecological research. Using a large dataset (83 sites) across a wide geographic distribution (three states), we find evidence that precipitation and temperatures in the planting year (2-19 years before present) affected the relative dominance of the sown (native target species) and non-sown (mostly non-native) species. We find strong support for lasting planting year weather effects in restored tallgrass prairies, thereby supporting the historically contingent model of community assembly in a real-world setting.
We surveyed 83 restored prairie sites in Illinois, Indiana, and Michigan between 18 July-16 September 2016. In each site, we established a 50 m transect in a random orientation. For Michigan and Illinois sites, transects were centered on the approximate centroid of the site; for Indiana sites, which were much larger, transects were placed inside the boundary of visible edge effects. At 5- or 10- m intervals (for Michigan and Illinois/Indiana sites, respectively), we placed a 1 m x 1 m quadrat frame on the ground and visually quantified the percent cover of each species present. We surveyed 5 plots per site in Indiana and Illinois, and 10 plots in Michigan (for compatibility with another project outside the scope of this manuscript). In addition, we systematically walked a 20 m x 50 m area centered on the transect and recorded additional species observed.
We collected two soil cores at 5 m intervals along each transect using an Oakfield soil probe (20 total per site, 2 cm × 20 cm soil cores). Soil cores were homogenized at each site. We determined soil water holding capacity by saturating field samples and then drying for 72 hours at 105°C and calculating the proportional difference in saturated wet weight and oven‐dried weight. Air-dried samples were also analyzed for a variety of soil properties including pH, percent organic matter, percent clay/silt/sand, and soil nutrients (S, P, Ca, Mg, K, Na, B, Fe, Mn, Cu, Zn, and Al) by Brookside Laboratories (New Knoxville, OH, USA). To reduce the potential number of predictor variables, we conducted a principal components analysis on the soils data using prcomp in R with each variable scaled due to large variation the concentrations of soil nutrients. For later analyses, we used the first principal component, which accounted for 40.5% of the variation in the soils data and was associated with higher percent organic matter, higher water holding capacity, higher clay content, higher silt content, higher nutrients (except Zn, Fe, and P), and less sand.
We worked with land managers at each site to compile information about the restored prairies, including the date of planting, prescribed fire history, and the relative abundance (by weight) of each species sown in the initial planting. We used 30-arcsec (approximately 800 m) spatially gridded PRISM Climate Data to compile interpolated information on the daily precipitation accumulation and minimum and maximum temperature in the first growing season for each site based on its latitude and longitude. We used these data to calculate cumulative growing degree days (base 10°C); this temperature-based unit is often used in agronomic systems to predict development of plants and other species. We calculated cumulative precipitation and averages related to temperature and precipitation at various stages throughout the growing season.
To characterize weather conditions at the time of planting we focused on eleven variables that we hypothesized would influence the germination and establishment of plant communities during the first growing season of prairie restoration: spring temperatures (degree day accumulation March 1 – June 1), spring precipitation accumulation (March 1 – June 1), summer temperatures (degree day accumulation June 1 – September 1), summer precipitation accumulation (June 1 – September 1), full growing season temperatures (degree day accumulation March 1 – September 1), full growing season precipitation accumulation (March 1 – September 1), the hottest month (maximum degree days accumulated in a 30-day period), the longest drought (maximum consecutive days without a precipitation event), the driest month (minimum precipitation in a 30-day period, in mm), average low temperature (March 1 – September 1, °C), and the average monthly precipitation (March 1 – September 1, mm). We focused on this set of variables owing to the reported roles of temperature and precipitation for plant establishment dynamics[28,71] and for year effects broadly. Because many of these variables were correlated, we conducted a Principal Components Analysis to determine composite metrics with which to test our hypotheses. We focused on the first three axes (out of eleven total) that together accounted for 74.2% of the variation in weather data.
Also included in this upload are:
"Groves-Bauer-Brudvig-2020-Seeds-Density.csv", which includes the seed mix data for the sites, that we collected from pracitioners, and our R script, "R.SCRIPT-Groves-Bauer-Brudvig-2020.R" used for data analyses and to produce figures for the paper.
The variables included in the "MASTER-DATA" dataset, and any additional notes about their origins, are as follows:
Site: A unique descriptor for each restored prairie site.
Landscape: Refers to whether the site was part of our Illinois (McHenry County Conservation District), Indiana (The Nature Conservancy's Kankakee Sands), or Michigan (private prairies restored by Native Connections, Three Rivers, MI); labeled as "MCCD", "KSands", or "MI", respectively.
First_Growing_Season: The first growing season after the prairie was planted.
Age_2016: The number of growing seasons that had passed since planting, as of 2016 when plant surveys were conducted.
Biomass: Total (dried) biomass collected from 5 1x1m plots. Plots with missing values ("NA") were mowed after plant community surveys but before biomass collection was able to take place.
Last.Burn: The number of years since the prairie last had a prescribed fire. If a site had never burned, was set to equal "Age_2016".
Rolling planting-year weather metrics, based on either degree day accumulation, or precipitation accumulation, starting March 1: Apr1.dd.accum, Apr1.precip.accum, May1.dd.accum, May1.precip.accum, Jun1.dd.accum, Jun1.precip.accum, Jul1.dd.accum, Jul1.precip.accum, Aug1.dd.accum, Aug1.precip.accum, Sep1.dd.accum, Sep1.precip.accum, summer.dd.accum, summer.precip.accum, Oct1.dd.accum, Oct1.precip.accum: For example, Apr1.dd.accum is the number of planting degree days by April 1 of the first growing season. "summer.dd.accum" is Jul 1 - Oct 1.
Additional metrics include: max.month.dd.accum, max.mean.month.precip, max.tot.month.precip, min.month.precip, high.temp, avg.high.temp, low.temp, avg.low.temp, avg.mon.rain.days, max.days.no.precip, avg.temp, spring.temp, summer.temp
Mix.Richness: The species richness of the seed mix sown to restore the site.
Based on the plant community surveys, we tallied the species richness (of all species, sown species only, and non-sown species only) for both the 1x1 m plots ("Richness.Plots") as well as for the larger site walkthrough ("Richness.Walkthru"). These two added together (without repeating species) is "Richness.Total.": Site.Richness.Walkthru, Site.Richness.Plots, Site.Richness.Total, Sown.Richness.Plots, Sown.Richness.Total, Nonsown.Richness.Plots, Nonsown.Richness.Total
Percent.of.Mix.Sp.Present: Percentage of species in the seed mix (Mix.Richness) present at the site.
Mean.Plot.Richness: Instead of total plot richness, the average across all plots.
Num.Plots: The number of plots surveyed at each site, should be 10 for Michigan and 5 for Illinois and Indiana sites.
Mean.Sown.Cover, Mean.Nonsown.Cover: Percent cover of sown and non-sown species at the 1x1m plot level. Can equal >100% because of overlapping plants.
Mix-Veg.BCdissim: Bray-Curtis dissimilarity between the composition of the seed mix and the standing plant community.
Mean.ANDGER.Cover, Mean.SOLCAN.Cover, Mean.SCHSCO.Cover, Mean.SORNUT.Cover, Mean.POAPRA.Cover, Mean.Rubus.Cover, Mean.RATPIN.Cover, Mean.DESCAN.Cover, Mean.ELYCAN.Cover, Mean.MONFIS.Cover: Percent cover of the most common sown and non-sown species, Andropogon gerardii, Solidago canadensis, Schizachyrium scoparium, Sorghastrum nutans, Poa pratensis, Rubus sp. Ratibida pinnata, Desmodium canadense, Elymus canadensis, and Mondarda fistulosa.
pH, Organic.Matter.percent, S.ppm, P.mg.per.kg, Ca.mg.per.kg, Mg.mg.per.kg, K.mg.per.kg, Na.mg.per.kg, B.half.detection, Fe.mg.per.kg, Mn.mg.per.kg, Cu.half.detection, Zn.mg.per.kg, Al.mg.kg, Clay.percent, Silt.percent, Sand.percent, Water.Holding.Capacity: Soils data.
U.S. Department of Agriculture, Award: 2016-67012-24680
National Science Foundation, Award: DEB-1552197
National Science Foundation, Award: DGE-1424871