Abstract
The selective properties of fishing that influence behavioural traits have recently gained interest. Recent acoustic tracking experiments have revealed between-individual differences in the circadian behavioural traits of marine free-living fish; these differences are consistent across time and ecological contexts and generate different chronotypes. Here, we hypothesised that the directional selection resulting from fishing influences the wild circadian behavioural variation and affects differently to individuals in the same population differing in certain traits such as awakening time or rest onset time. We developed a spatially explicit social-ecological individual-based model (IBM) to test this hypothesis. The parametrisation of our IBM was fully based on empirical data; which represent a fishery formed by patchily distributed diurnal resident fish that are exploited by a fleet of mobile boats (mostly bottom fisheries). We ran our IBM with and without the observed circadian behavioural variation and estimated selection gradients as a quantitative measure of trait change. Our simulations revealed significant and strong selection gradients against early-riser chronotypes when compared with other behavioural and life-history traits. Significant selection gradients were consistent across a wide range of fishing effort scenarios. Our theoretical findings enhance our understanding of the selective properties of fishing by bridging the gaps among three traditionally separated fields: fisheries science, behavioural ecology and chronobiology. We derive some general predictions from our theoretical findings and outline a list of empirical research needs that are required to further understand the causes and consequences of circadian behavioural variation in marine fish.
Highlights
Humans have exploited fish populations through trait-selective harvesting since the origin of our species (Allendorf & Hard, 2009)
To explore whether fishing selection influences circadian behavioural traits, we developed a computational individual-based model (IBM) where a fish population spatially behaves in a 2-D landscape and is exploited by a fleet of fishing boats during a fishing session
For the purpose of this study, we focused on two descriptors of this biased random walk (BRW) movement model described in Alos et al (2016a): (i) the size of the circular home range (HR) radius that can be interpreted as a surrogate for the total foraging area and activity space, and (ii) the harmonic force (k, in min-1) that can be interpreted as the strength of the drift or attraction force towards the centre of the HR, which determines the slope of the curve describing the cumulative space used in a period of time
Summary
Humans have exploited fish populations through trait-selective harvesting since the origin of our species (Allendorf & Hard, 2009). With the recent development of aquatic telemetry, fisheries scientists have a powerful tool available to study behavioural types of free-living fishes (Hussey et al, 2015; Lennox et al, 2017a) and how fisheries may promote the selection of behavioural types in real-world fisheries (Alos et al, 2016b; Monk & Arlinghaus, 2018; Olsen et al, 2012) Together, these two developments have generated substantial empirical evidence demonstrating that bold and high-exploratory individuals (Alos, Palmer & Arlinghaus, 2012; Biro & Sampson, 2015; Harkonen et al, 2014; Klefoth, Kobler & Arlinghaus, 2011; Olsen et al, 2012) are more prone to harvest; this evidence supports the idea that timidity syndrome can give rise to exploited fish populations that are composed of shy, less active and less exploratory individuals (Arlinghaus et al, 2016, 2017)
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