Reproductive Traits of Brown Trout in Two Contrasting Streams of Southeast Minnesota

Abstract

AbstractBrown Trout Salmo trutta are widely distributed fish that display substantial interpopulation variation in fundamental reproductive traits due to differences in local environmental conditions. This wide variation necessitates regional determination of key traits to aid local management efforts. In addition, several populations demonstrate a trade‐off between fecundity and egg size, often as a function of growth history in response to environmental conditions. To determine these traits in the Driftless Area of the Upper Midwest, we identified two streams with contrasting environmental conditions and quantified reproductive traits just prior to the fall‐spawning period in 2012. Reproductive traits included growth, length‐ and age‐at‐maturity, gonadosomatic index, and female fecundity and egg size. Environmental conditions were considered harsher at one site based on warmer water temperatures, more sand substrate, less adult fish cover, and presence of more potential interspecific competitors than at the other site. At both sites, Brown Trout of both sexes were short‐lived; few Brown Trout older than age 3 were collected, and both sexes matured at age 2. Length‐at‐maturity ranged from 226 to 230 mm TL for males and from 214 to 238 mm TL for females. Fecundity and egg size were both positively related to female size, and females produced up to about 800 eggs. Ovaries represented a maximum of about 15% of female body weight. Female Brown Trout growth differed between the two sites, but most reproductive traits and growth of males did not. There was no evidence of a trade‐off between fecundity and egg size, but length‐adjusted egg sizes were significantly larger at the site with harsher environmental conditions. Differences in egg size probably were not due to the presence of competitors but may have been due to warmer water temperatures. Collectively, these fundamental reproductive data will prove useful for future population modeling efforts to support evaluation of several management strategies.Received August 10, 2015; accepted December 16, 2015 Published online May 16, 2016