The calc_ef2() function is used to calculate the energy flow of a nematode
community. For detailed calculation method, see Wan et al. (2022): Step 1, the
fresh biomass of each nematode individuals was calculated based on the measurement
of body size or using publicly available data. Step 2, nematode metabolism (F) was
then calculated according to Ferris (2010) and van den Hoogen et al. (2019),
where Nt, Wt and mt are the number of individuals, the fresh weight and the cp class
of taxon t, respectively. Step 3, a five-node food web topology was constructed and
the feeding preferences of omnivores-carnivores on other trophic groups was assumed according
to community density. Step 4, the metabolism of each node was summed by all individual
metabolism of the respective trophic group. Step 5, we used assimilation efficiencies
(ea) of 0.25 for herbivores, 0.60 for bacterivores, 0.38 for fungivores and 0.5
for omnivores-carnivores according to Barnes et al. (2014) and De Ruiter et al. (1993).
Step 6, energy fluxes between nodes was calculated as follows: Fi = (F + L)/ea,
where L is the energy loss to higher trophic levels.
calc_ef2(data, .group1, .group2)An ef2-class object that stores the desired visualization results.
OF, Energy flow metabolism of omnivorous predatory nematodes.
OM, Fresh biomass (ug / 100g dry soil) of omnivorous predatory nematodes.
BF, Energy flow metabolism of bacteria-feeding nematodes.
BM, Fresh biomass (ug / 100g dry soil) of omnivorous predatory nematodes.
HF, Energy flow metabolism of herbivorous nematodes.
HM, Fresh biomass (ug / 100g dry soil) of herbivorous nematodes.
FF, Energy flow metabolism of fungus-feeding nematodes.
FM, Fresh biomass (ug / 100g dry soil) of fungus-feeding nematodes.
bp, Feeding preference of predatory nematodes over bacteria-feeding nematodes.
hp, Feeding preference of predatory nematodes over herbivorous nematodes.
fp, Feeding preferences of predatory nematodes over fungivorous nematodes.
fbo, Energy flow (ug C / 100g dry soil / day) between bacteria-feeding nematodes and omnivorous predatory nematodes.
fho, Energy flow (ug C / 100g dry soil / day) between herbivorous nematodes and omnivorous predatory nematodes.
ffo, Energy flow (ug C / 100g dry soil / day) between fungus-feeding nematodes and omnivorous predatory nematodes.
frb, Energy flow (ug C / 100g dry soil / day) between basal resources and bacteria-feeding nematodes.
frh, Energy flow (ug C / 100g dry soil / day) between basal resources and herbivorous nematodes.
frf, Energy flow (ug C / 100g dry soil / day) between basal resources and fungivorous nematodes.
U, Uniformity (U) of soil nematode energetic structure (unitless, mean ± standard error) was calculated as the
ratio of the mean of summed energy flux through each energy channel to the standard deviation of these mean values.
An nemindex-class object.
The group variable factor 1.
The group variable factor 2.
To facilitate code interpretation, it is recommended to use the pipe symbol
|> to connect functions:
nem_ter <- nem |> nem_index() |> calc_ef2(con_crop, season)
Wan, Bingbing, et al. "Organic amendments increase the flow uniformity of energy across nematode food webs." Soil Biology and Biochemistry 170 (2022): 108695.
Ferris, H., 2010. Form and function: metabolic footprints of nematodes in the soil food web. European Journal of Soil Biology 46, 97–104.
Van Den Hoogen, Johan, et al. "Soil nematode abundance and functional group composition at a global scale." Nature 572.7768 (2019): 194-198.
Barnes, A.D., Jochum, M., Mumme, S., Haneda, N.F., Farajallah, A., Widarto, T.H., Brose, U., 2014. Consequences of tropical land use for multitrophic biodiversity and ecosystem functioning. Nature Communications 5, 1–7.
De Ruiter, P.C., Van Veen, J.A., Moore, J.C., Brussaard, L., Hunt, H.W., 1993. Calculation of nitrogen mineralization in soil food webs. Plant and Soil 157, 263–273.
Other functions in this R package for data calculations:
calc_beta2, calc_compare, calc_compare2,
calc_beta, calc_alpha, calc_nemindex,
calc_funguild, calc_funguild2, calc_mf2,
calc_mf, calc_ter2, calc_ter,
calc_ef.
nem <- read_nem(tab = easynem_example("nemtab1.csv"),
tax = easynem_example("nemtax1.csv"),
meta = easynem_example("nemmeta1.csv"))
nem_index <- nem |> calc_nemindex() |> calc_ef2(con_crop, season)
nem_index
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