Effects of cultivation practice on floristic and flowering diversity of spontaneously growing plant species on arable fields
Data files
Jan 11, 2022 version files 166.51 KB
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Seg2019_korr.dbf
166.51 KB
Abstract
In the past, the floristic diversity of arable fields has been described in terms of species diversity (SD) and their degree of coverage (C), but never in combination with the recording of the actually flowered species (FS) and their flowering intensity (FI) to striking differences in the cultivation methods on arable land. In relation with SD and C, however, FS and FI may provide important additional information on the functional biodiversity of fields. The aim was therefore to investigate the effects of a) conventional, b) organic as well as c) smallholder (never application of herbicides) on the floristic diversity. Using a region in Germany, we investigated SD, C, FS and FI synchronously in a), b) and c), by 356 vegetation surveys (5x5m plots) conducted in spring and summer in 2019 in winter cereals. Statistical tests were used to analyse the differences between a), b) and c). The medians were used to compare the floristic diversity of a), b) and c) and finally relationships of FS and FI to SD were analysed in relation to the cultivation methods. Significant differences in SD, C, FS and FI were found between the a), b) and c) in spring and summer characterised by sharp declines from c) to b) to a). A drastic reduction in floristic diversity from c) 100 to b) 52 to a) 3 was determined. Plants in flower (FS, FI), were very poorly in a), moderately well to well in b) and well to very well represented in c). C) to a) was characterised by an sharp decline, and, from a) to b) by sharp increase in floristic diversity. With current acreage proportions of a) in mind, this would affect, about one-third of land area in Germany, associated with a drastic reduction in functional biodiversity for insects.
Collected: field investigations, vegetation surveys
Processed: statistical data analysis by the use of statistics software R (R Core Team, 2020)