Productivity and diversity of annually harvested reconstructed prairie communities database
datasetposted on 12.09.2018 by Farnaz Kordbacheh, Meghann Jarchow, Lydia English, Matt Liebman
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
This data supports an accepted article that will be published in Journal of Applied Ecology in Jan 2019.
Matt Liebman (email@example.com) is the corresponding author for the article.
Productivity and diversity of annually harvested reconstructed prairie communities database was compiled to test whether the long-term maintenance of biodiversity can be achieved alongside substantial productivity in fertilized mixed-species prairie. Using this database, we report how NPK fertilizer application, precipitation, and time affected the species composition and productivity of reconstructed prairie communities harvested annually as biofuel feedstocks over a nine-year period. Three main datasets were used for the analyses conducted, each encompassed a part of the full picture. First, we used prod_pre_div.csv to evaluate the relationship between productivity and precipitation. We also used this file to run the Analysis of Variance (ANOVA) on productivity, species richness, Simpson’s evenness and Simpson’s diversity. Results of this analysis are shown in Figure 1 and figure 2 of our article. Further, we used species _cover.csv for the ANOVA on the cover of individual plant species, cover of functional groups-i.e. C3 grasses, C4 grasses, the non-leguminous, the leguminous and cover of forbs partitioned by flowering time( see Table 2, Figure 3 and Figure 4). For creating a complementary picture from changes in species composition over time and treatment, we used species_proportional_cover.csv for multivariate analyses- i.e. non-metric multidimensional Scaling (NMDS), Multi Response-Permutation Procedure (MRPP), and the matching of ordination method (see Figure 5A and 5B). Usage of these datasets has no copyright or proprietary restrictions other than citation of the paper.