Plant composition and weather data during tallgrass prairie restoration

Tallgrass prairie communities were restored using the same live seed mix
every other year from 2010-2020 to test the hypothesis that dissimilarity
in planting-year climate statistically predicts dissimilarity in
developing plant community composition, and planting-year precipitation
and temperature variables explain cover of species and major compositional
underlying community dissimilarity. This dataset contains percent cover of
plant species establishing over time in six restored prairies established
in six different years at the Konza Prairie Biological Station in Kansas
(USA) and corresponding precipitation and temperature data for each year a
prairie was restored. The experiment is referred to as the “Sequential
Restoration Plots” and contains seven prairie communities (sequences)
restored in an agricultural field over time. Plant species, the absolute
cover of each species, and cover of compositional groups (all sown
species, all volunteer species, all forb species, all grass species, sown
C4 grasses, sown C3 species, and sown forb species) over the first three
years of community establishment in each plot and subplot of the six
sequences corresponding to planting years 2010, 2012, 2014, 2016, 2018,
and 2020 (sequences I-VI) are provided in this dataset. Weather data
contained in this dataset correspond the years each prairie sequence was
restored. Annual precipitation and temperature summary variables were
calculated to relate cover of species and compositional groups to planting
year climate. Climate vectors (capturing intra-annual variability and
extremes) were also created for each planting year to perform multiple
regression on distance matrices to examine the relationship between
dissimilarity in planting year precipitation and temperature conditions
and dissimilarity in communities that developed over the first three years
of restoration.