Abstract
While a suite of approaches have been developed to describe the scale, rate and spatial structure of exchange among populations, a lack of mechanistic understanding will invariably compromise predictions of population-level responses to ecosystem modification. In this study, we measured the energetics and sustained swimming capacity of giant Australian cuttlefish Sepia apama and combined these data with information on the life-history strategy, behaviour and circulation patterns experienced by the species to predict scales of connectivity throughout parts of their range. The swimming capacity of adult and juvenile S. apama was poor compared to most other cephalopods, with most individuals incapable of maintaining swimming above 15 cm s−1. Our estimate of optimal swimming speed (6–7 cm s−1) and dispersal potential were consistent with the observed fine-scale population structure of the species. By comparing observed and predicted population connectivity, we identified several mechanisms that are likely to have driven fine-scale population structure in this species, which will assist in the interpretation of future population declines.
Highlights
Defining the scale of exchange among populations and the factors driving this exchange underpin our understanding of the dynamics, genetic structure, and biogeography of aquatic animals [1]
V.O2 increased in an exponential manner from resting (40.8 6 2.2 ml kg21 h21) up to 15–16 cm s21 (97.1 6 5.0 ml kg21 h21), which appeared to represent the maximum aerobic speed for S. apama
Swimming energetics of Sepia apama Our estimate of the speed that minimises aerobic cost of transport is approximately one third of that estimated for several squid and cuttlefish species, with both predicted speeds and those measured in the field more similar to those of the other buoyancy-regulating group of cephalopods, the chambered nautilus ([18] Fig. 2)
Summary
Defining the scale of exchange among populations and the factors driving this exchange underpin our understanding of the dynamics, genetic structure, and biogeography of aquatic animals [1]. The life-histories of most marine species include at least one widely dispersive stage, and the scale of this dispersal is one of the primary determinants of population structure [2]. Identifying the mechanisms that drive population structuring is exceedingly difficult, and a poor understanding of factors driving differentiation hinders the accurate prediction of a population’s response to environmental change. A comparison can be made between observed population connectivity and that which is predicted (based upon known life-history strategies, potential for dispersal, and oceanography experienced by a species, etc.), mechanisms driving structure can be better understood, and this will increase the ability to predict a population’s response to change
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