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Importance of Temperature and Streamf low Variables for Explaining Variation in Relative Abundance of Age-0 Smallmouth Bass inSouthwestern Wisconsin Streams

机译:温度和流流变量的重要性,以解释威斯康星州西南部 - 0年龄-0时代小鲈鱼相对丰富的变化

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Identifying abiotic variables that influence fish recruitment patterns is crucial to understanding, assessing, and managing populations. Smallmouth Bass Micropterus dolomieu have been sampled from five streams in southwestern Wisconsin since 1989 withthe goals of explaining variation and describing patterns of annual age-0 relative abundance. Summer water temperature and stream stage data have been collected annually since 2010 and United States Geological Survey modeled stream temperature and stagedata were acquired from 1990-2009. Catch-per-unit-effort (CPUE) of age-0 fish was highly variable within and among streams and ranged from 0 to 48.54 fish/100 m across all streams. Random forest models with stepwise variable selection processes were used to determine the relative importance of stream temperature and stream stage variables in describing variation in CPUE from 2010-2016. July mean water temperature and maximum summer temperature explained 69.7% of the variation in CPUE of age-0 Smallmouth Bass. July mean temperature and maximum summer temperature were positively related with CPUE of age-0 fish from 2010-2016; however, modeled July mean water temperatures and modeled maximum summer temperatures were not significantly correlated with CPUEfrom 1990-2008. We conclude that caution must be taken when using models to predict CPUE of age-0 Smallmouth Bass from temperature or flow variables, as variability in both recruitment patterns and climatic conditions may reduce model application over longer time frames.
机译:识别影响鱼类招聘模式的非生物变量对于了解,评估和管理人口至关重要。自1989年以来,Smallmouth Bass MicroPterus Dolomieu自1989年以来,从西南威斯康星州西南部的五股溪流中取样,其目标是解释变化和描述年龄龄-0相对丰富的模式。自2010年以来,每年收集夏季水温和流阶段数据,从1990 - 2009年收购了美国地质调查建模的流程温度和Stagesata。 Age-0鱼的每单位努力(CPUE)在溪流内部和溪流中的高度变化,并且在所有溪流中的0到48.54条鱼/ 100米。具有逐步变量选择过程的随机森林模型用于确定流温和流阶段变量在2010 - 2016年描述CPUE的变化时的相对重要性。 7月的平均水温和最大夏季温度解释了4岁的CPUES-0小汤贝斯CPUE变化的69.7%。 7月均平均温度和最大夏季温度与2010-2016的Age-0鱼CPUE呈正相关;然而,建模的7月平均水温和建模的最大夏季温度与1990-2008的CPue没有显着相关。我们得出结论,必须在使用模型以从温度或流量变量预测年龄-0的CPUE时,必须采取谨慎,因为招聘模式和气候条件的可变性可能会降低模型应用在较长的时间范围内。

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