Box 25. Estimating trophic levels from individual food items.
As documented in Box 23, trophic levels (‘trophs’) are typically estimated from diet composition data, covering the whole range of food items consumed by a given species at a given locality and season (see the DIET COMPOSITION table). A troph (and its s.e.) can then be estimated, from the mean trophic level of the preys, plus one.
It is also possible to obtain rough estimates of the troph and its s.e. based on individual prey items (rather than a complete diet composition), as recorded in the FOOD ITEMS table, granted that enough food items have been entered for a given species, and that one is willing to accept certain assumptions on the relative importance of these food items in the overall diet of the species.
Examination of diet compositions entered until mid-1999 (n = > 1,800) showed that typically, the relative contribution of different food items to the overall diet composition follows a pattern described by the empirical model:
log10P = 2 – 1.9log10R – 0.161og10G …1)
where P is the contribution of an item to the total diet in percent;
R is the rank of the food item (in terms of its relative contribution to the total diet); and
G is the number of food items (in the DIET table, we always have 1 < G < 10).
In the following, a description of the resampling routine is provided which is used in FishBase to estimate trophs and their s.e. from individual food items. This routine involves three cases:
Case 1: all food items are plants or detritus
Then: troph = 2.0 and s.e. = 0;
Case 2: there is only one food item, and it is neither a plant nor detritus.
Then: troph = 1 + troph of food item & s.e. = s.e. of food item (see FOOD ITEMS table for trophic levels and s.e. of food items; use Food III if possible, or else Food II or else Food I).
Case 3: There are several food items, and at least one is not a plant or detritus.
Then: run Routine A.
Routine A
Count the food items, and call their number G;
Select at random one of these food items, and give it the rank 1 (R = 1);
Given G, and R, solve equation (1) for P;
Select at random one of the remaining food items, give it a rank of 2 (R = 2) and again solve equation (1) for P;
Repeat (2) – (4) until all items have been selected (R = 3, 4 . . . . G);
From the P values, and the trophs specific to each items, estimate a mean troph from:
… 2)
Compute s.e. of Troph from Sachs (1984)
… 3)
Save troph and s.e.; repeat (2) – (8), using different random numbers to select first, second, etc. item; stop after 100 loops.
Take grand mean of computed trophs and of their standard errors, output these and stop.
The key point of this routine is that the grand mean s.e. that is estimated considers all possible permutations of the food items in terms of the relative abundance they could have had in a real diet composition. Note that the standard errors and corresponding troph estimates obtained from this routine are tentative, and should be replaced by estimates from diet compositions whenever possible.
Reference
Sachs, L. 1984. Applied statistics. A handbook of techniques. 2nd ed. 707 p. Springer-Verlag, Inc., New York.
Daniel Pauly and Pascualita Sa-a
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