Foraging decisions

Large, generalist marine grazers such as fishes and urchins attempt to choose foods that maximize nutritional input (e.g., protein, lipids, and carbohydrate) (Mattson 1980 Choat and Clements 1998) and minimize intake of secondary metabolites (Hay 1991). The untested assumption underlying these optimal foraging decisions is that detoxification and excretion rates are a constraint on toxin intake and thus drive feeding choice (Freeland and Janzen 1974). However, we have virtually no information on such constraints in marine herbivores, because it requires an understanding of the metabolic fate of secondary metabolites. 

Biesmeijer, J.C, van Nieuwstadt, M.G.L., Lukacs, S. and Sommeijer, M.J. (1998). The role of internal and external information in foraging decisions of Melipona workers (Hymenoptera Meliponinae). Behav. Ecol. Sociobiol., 42,107-116. 

Higginson, A.D. and Barnard, C.J. (2004) Accumulating wing damage affects foraging decisions in honeybees Apis mellifera L.). Ecological Entomology, 29 52-59. 

Intake may be negatively correlated with residues due to repellency or avoidance positive relation between insect abundance and decision to use insecticide negative relation between use of insecticide and subsequent insect abundance positive relation between insect abundance and bird foraging behavior... 

Decisions (i) and (ii), and to some extent (iv), may be similar, but each of them considers foraging strategies at a different level of resource distribution. It is important to consider that resource patches exist at different hierarchical levels (e.g., forest, tree, limb, leaf, etc.) and that each patch level and each patch boundary can be defined by the behavior of the foraging insect. Whatever the patch level, the problem the forager faces is as follows individuals that remain too long in resource-poor areas accumulate resources at lower rates... 

The method of calibration equation selection developed by the NIRS Forage Network follows in an abbreviated form. Note that the terminology used is that of the Forage Network and it is not consistent with all NIR users or statisticians. Each term and abbreviation will soon be standardized by ASTM Task Group on NIR E-13.03.03. For each constituent, the standard error of calibration (SEC) and coefficient of determination (R ) for each calibration equation are important criteria for decision making with respect to equation selection. As wavelength (independent terms) are added to the equation, SEC will decrease and will increase. 

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