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Multiple metrics provide context for the distribution of a highly mobile fish predator, the blue catfish
Author(s) -
Gerber Kayla M.,
Mather Martha E.,
Smith Joseph M.,
Peterson Zachary J.
Publication year - 2019
Publication title -
ecology of freshwater fish
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.667
H-Index - 55
eISSN - 1600-0633
pISSN - 0906-6691
DOI - 10.1111/eff.12438
Subject(s) - context (archaeology) , population , fish <actinopterygii> , ecology , flathead , diel vertical migration , fidelity , fishery , geography , biology , computer science , demography , archaeology , sociology , telecommunications
Data sets with increased spatial and temporal resolution can help researchers and resource managers quantify representative distributional patterns of mobile sportfish. In this research, first, we illustrate patterns of sportfish distribution using individual ( percent of population, residence time, number of movements ) and combined distributional metrics. Second, we apply these metrics to one highly mobile fish species, the blue catfish ( Ictalurus furcatus ), across a range of spatial (whole reservoir, region, site) and temporal (year, month, diel period) scales. Specifically, we tracked 123 acoustically tagged blue catfish with a 20‐receiver array in Milford Reservoir, KS , USA . When we integrated metrics, four site‐specific distributional patterns emerged: (a) a large, active multi‐site fish aggregation, (b) localised site fidelity, (c) transitional sites and (d) rarely used locations. These patterns would not have been detected using a single metric as each measurement revealed a different piece of the distribution story. For example, if we had only quantified percent of population, we could identify fish location, but not whether individual fish spent time at a location or were just passing through. Our examination of multiple scales also provided a novel context for interpreting site‐specific patterns. As an illustration of this insight, using conventional approaches, we would have observed heterogeneity, but we would not have detected fish aggregations, in which individual fish either remained or repeatedly returned to a site. In summary, our results show the advantage of setting the entire ecosystem as the study boundary to integrate multiple responses using a spatially and temporally extensive data set.

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