Mass ratio effects underlie ecosystem responses to environmental change
Data files
Nov 27, 2019 version files 6.06 MB
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BGPF_v5.xlsx
47.98 KB
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BGPN_v5.xlsx
80.34 KB
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CEE.xls
2.20 MB
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CO2.xls
44.54 KB
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D_R.xlsx
94.09 KB
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Dom_Silletti.xls
107.01 KB
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F_B_Press.xlsx
82.66 KB
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F_H_Pulse.xlsx
28.30 KB
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F_K_Press.xlsx
92.45 KB
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F_K_Pulse.xlsx
58.40 KB
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F_Sp_Press_v2.xlsx
215.46 KB
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F_Sp_Pulse.xlsx
456.47 KB
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gibson.xls
212.48 KB
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Grazing_ME.xls
330.75 KB
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Irrigation.xlsx
581.35 KB
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nutnet.xls
466.94 KB
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PPLOTS.xls
575.49 KB
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ramps.xlsx
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vi.xls
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Abstract
1. Random species loss has been shown experimentally to reduce ecosystem function, sometimes more than other anthropogenic environmental changes. Yet, controversy surrounds the importance of this finding for natural systems where species loss is non-random.
2. We compiled data from 16 multi-year experiments located at a single site in native tallgrass prairie. These experiments included responses to 11 anthropogenic environmental changes, as well as non-random biodiversity loss - either the removal of uncommon/rare plant species or the most common (dominant) species.
3. As predicted by the mass ratio hypothesis, loss of a dominant species had large impacts on productivity that were comparable to other anthropogenic drivers. In contrast, the loss of uncommon/rare species had small effects on productivity despite having the largest effects on species richness.
4. The anthropogenic drivers that had the largest effects on productivity – nitrogen, irrigation, and fire – experienced not only loss of species but also significant changes in the abundance and identity of dominant species.
5. Synthesis. These results suggest that mass ratio effects rather than species loss per se is an important determinant of ecosystem function with environmental change.
Methods
Data were downloaded from the Konza Prairie LTER website (http://lter.konza.ksu.edu) or obtained directly from investigators.
Usage notes
Files contain metadata, aboveground net primary productivity data, and plant species composition data for 16 experiments.