Learn R Programming

cheddar (version 0.1-626)

NvMTriTrophicTable: N-versus-M tri-trophic statistics

Description

Tri-trophic statistics.

Usage

NvMTriTrophicTable(collection)

Arguments

collection
an object of class CommunityCollection.

Value

  • A data.frame with a column per community and the rows
  • Mean link length
  • Mean L upper
  • Mean L lower
  • 2 x mean link length
  • Mean 2-span
  • Mean L upper + L lower
  • 2 x mean link length / mean 2-span
  • Mean L upper + L lower/ mean 2-span
  • Mean count chain length
  • Mean count chain length x mean link length
  • Community span
  • Mean count chain length x mean link length / community span
  • Mean sum chain lengths
  • Mean chain span
  • Mean chain span / community span
  • Mean sum chain lengths / mean chain span
  • Mean sum chain lengths / community span
  • Lnumber of trophic links after removals.
  • S^2number of nodes squared after removals.
  • L/S^2directed connectance links after removals.
  • L/Slinkage density after removals.
  • Lnumber of trophic links before removals.
  • S^2number of nodes squared before removals.
  • L/S^2directed connectance links before removals.
  • L/Slinkage density before removals.

Details

Returns a data.frame that contains the same statistics presented in Table 1 on Cohen et al 2009 PNAS. The function removes nodes lacking body mass (M) and/or numerical abundance (N), cannibalistic links and isolated nodes from each community. The last eight rows of the table contain four network statistics both with and without these removals.

References

Cohen, J.E. and Schittler, D.N. and Raffaelli, D.G. and Reuman, D.C. (2009) Food webs are more than the sum of their tritrophic parts. Proceedings of the National Academy of Sciences of the United States of America 106, 52, 22335--22340.

See Also

NvMTriTrophicStatistics, CommunityCollection

Examples

Run this code
data(TL84, TL86, YthanEstuary)
collection <- CommunityCollection(list(TL84, TL86, YthanEstuary))
table <- NvMTriTrophicTable(collection)
print(round(table, 2))

Run the code above in your browser using DataLab