DOI: 10.5061/dryad.g4q05
title: Data from: Integrating lipid storage into general representations of fish energetics

description: Fish, even of the same species, can exhibit substantial variation in
 energy density (energy per unit wet weight). Most of this variation is due
 to differences in the amount of storage lipids. In addition to their
 importance as energy reserves for reproduction and for survival during
 unfavourable conditions, the accumulation of lipids represents a large
 energetic flux for many species, so figuring out how this energy flux is
 integrated with other major energy fluxes (growth, reproduction) is
 critical for any general theory of organismal energetics. Here, we
 synthesize data from a wide range of fish species and identify patterns of
 intraspecific variation in energy storage, and use these patterns to
 formulate a general model of energy allocation between growth, lipid
 storage and reproduction in fishes. From the compiled data we identified
 two patterns: (1) energy density increases with body size during the
 juvenile period, but is invariant with body size within the adult size
 range for most species, and (2) energy density changes across seasons,
 with depletion over winter, but increases fastest in periods of transition
 between favourable and unfavourable conditions for growth (i.e. fall).
 Based on these patterns we propose DEBlipid, a simple, general model of
 energy allocation that is closely related to a simplified version of
 Dynamic Energy Budget theory, DEBkiss. The crux of the model is that
 assimilated energy is partitioned, with κ fraction of energy allocated to
 pay maintenance costs first, and the surplus allocated to growth, and 1 −
 κ fraction of assimilated energy is allocated to accumulating storage
 lipids during the juvenile phase, and later to reproduction as adults.
 This mechanism, in addition to capturing the two patterns that motivated
 the model, was able to predict lipid dynamics in a novel context, the
 migration of anadromous fish from low-food freshwater to high-food marine
 environments. Furthermore, the model was used to explain intra and
 interspecific variation in reproductive output based on patterns of lipid
 accumulation as juveniles. Our results suggest that many seemingly
 complex, adaptive energy allocation strategies in response to ontogeny,
 seasonality and habitat quality can emerge from a simple physiological
 heuristic.
description: EnergyDensityDatebaseDryadDatabase of intraspecific variation in proximate composition and energy density data for 55 species of fish. Variables: Species; Ref (original reference for data); Median.Latitude (approximate median latitude of sample collection); Median.Longitude (approximate median longitude of sample collection) Capture.Year (year of sample collection); Julian.Median (median julian day (1-365) of sample collection); Julian.Range (length in days of the period over which samples were collected;) N.sample (number of fish per sample, if N &gt; 1 data are composite sample); Length.mm.TL (Fish Total Length (mm); p.Water (% water); p.Protein (% protein); p.Lipid (% lipid); p.Ash (% ash); EnergyDensity.kJ/g (Energy density of fish [kJ per g wet weight]); L_calc (0 if fish length taken from paper, 1 if calculated from weight using weight length relationship); EDtype ("paper" = energy density taken from paper, "ProLip" = calculated from proximate composition data on % protien and % lipid, "LipOnly" = estimated from % lipid data alone)annualized GSI dataData on annualized gonadosomatic Index (aGSI) for fish species compiled from the literature. For species that reproduce once annually, aGSI is equivalent to the GSI (gonad weight/somatic weight) of mature fish immediately preceding spawning. For species spawning biannually, aGSI is GSI divided by 2, and for species spawning multiple times per year, aGSI was calculated by multiplying ovary weight by the number of batches spawned per year.GSI_JAE_dryad.csv