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Application of Discrete Choice Models to Predict White Crappie Temperature Selection in Two Missouri Impoundments

机译:离散选择模型在预测两个密苏里州蓄水库中白饼温度选择中的应用

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Temperature selection by white crappie Pomoxis annularis over 24 h was determined in two Missouri impoundments, Little Dixie Lake and Rocky Fork Lake, on six and five dates, respectively, during June-August 2001 using temperature-sensitive radio transmitters. Temperature and dissolved oxygen (DO) profiles showed that the habitable portions of the upper water columns associated with fish locations varied by as much as 6 deg C in temperature. The habitable portions of water columns were subdivided intothree strata (warm, moderate, and cool) such that each stratum covered an equivalent temperature range (<=2 deg C). Discrete choice models (DCMs) were developed for each impoundment to predict the relative probabilities of white crappies selecting the different strata in response to stratum height, DO concentration, average temperature throughout the habitable water column (AVG), and fish weight. For each impoundment, a distinct DCM containing AVG as the sole predictor variable was most supported by the data. Cross-verification indicated that the DCMs accurately predicted white crappie thermal strata selection within the impoundments for which they were developed but that they were inaccurate when applied across the impoundments. The DCM for Little Dixie Lake predicted that white crappies mostly select warm strata at AVGs less than 27 deg C and mostly select cool strata at AVGs of 27 deg C or more. In contrast, the DCM for Rocky Fork Lake predicted that white crappies continue to select warm strata until AVGs reach 30 deg C, select moderate strata at AVGs of 30-32 deg C, and select cool strata only when AVGs exceed 32 deg C. The predicted mean daily thermal experiences of the white crappies in each impoundment, obtained by multiplying the relative selection probabilities for the different strata by the average temperatures in those strata, remained within 0.5 deg C of the mean of observed temperatures experienced by white crappies. These findings indicate that discrete choice modeling provides a novel and effective approach for predicting the daily thermal experiences of fish.
机译:在2001年6月至8月的六个密苏里州小迪克西湖和落基福克湖两个密苏里州蓄水库中,使用温度敏感的无线电发射器分别确定了白色小app在24小时内的温度选择。温度和溶解氧(DO)曲线表明,与鱼类位置相关的上部水柱的可居住部分温度变化高达6摄氏度。将水柱的可居住部分细分为三个层(温暖,中等和凉爽),以使每个层都覆盖等效的温度范围(<= 2摄氏度)。针对每个蓄水池开发了离散选择模型(DCM),以预测白cr根据层高,DO浓度,整个可居住水柱(AVG)的平均温度和鱼的重量选择不同层的相对概率。对于每个蓄积,数据最支持包含AVG作为唯一预测变量的不同DCM。交叉验证表明,DCM可准确预测在为其开发的水库内白碎屑热层的选择,但在整个水库中应用时,它们是不准确的。小迪克西湖(DCM)的预测表明,白cr大多在27摄氏度以下的AVG处选择温暖的地层,而大多数在27摄氏度或以上的AVG处选择凉的地层。相反,洛基福克湖(Rocky Fork Lake)的DCM预测,白cr继续选择温暖的地层直到AVG达到30摄氏度,在AVG达到30-32摄氏度时选择中等的地层,仅当AVG超过32摄氏度时才选择凉爽的地层。通过将不同层的相对选择概率乘以这些层的平均温度获得的每个蓄积层中白cr的预计平均每日热经验,仍保持在白cr所观察到的平均温度的0.5摄氏度以内。这些发现表明,离散选择建模提供了一种新颖有效的方法来预测鱼的日常热经验。

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