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Successes, failures, and opportunities in the practical application of drift-foraging models

机译:漂移觅食模型的实际应用中的成功,失败和机会

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Accurately measuring productive capacity in streams is challenging, and field methods have generally focused on the limiting role of physical habitat attributes (e.g. channel gradient, depth, velocity, substrate). Because drift-foraging models uniquely integrate the effects of both physical habitat (velocity and depth) and prey abundance (invertebrate drift) on energy intake for drift-feeding fishes, they provide a coherent and transferable framework for modelling individual growth that includes the effects of both physical habitat and biological production. Despite this, drift-foraging models have been slow to realize their potential in an applied context. Practical applications have been hampered by difficulties in predicting growth (rather than habitat choice), and scaling predictions of individual growth to reach scale habitat capacity, which requires modelling the partitioning of resources among individuals and depletion of drift through predation. There has also been a general failure of stream ecologists to adequately characterize spatial and temporal variation in invertebrate drift within and among streams, so that sources of variation in this key component of drift-foraging models remain poorly understood. Validation of predictions of habitat capacity have been patchy or lacking, until recent studies demonstrating strong relationships between drift flux, modeled Net Energy Intake, and fish biomass. Further advances in the practical application of drift-foraging models will require i) a better understanding of the factors that cause variation in drift, better approaches for modelling drift, and more standardized methods for characterizing it; ii) identification of simple diagnostic metrics that correlate strongly with more precise but time-consuming bioenergetic assessments of habitat quality; and iii) a better understanding of how variation in drift-foraging strategies are associated with other suites of co-evolved traits that ecologically differentiate taxa of drift-feeding salmonids.
机译:准确测量河流的生产能力具有挑战性,田间方法通常集中在物理栖息地属性(例如河道梯度,深度,速度,底物)的有限作用上。由于漂流觅食模型独特地综合了物理栖息地(速度和深度)和猎物丰富度(无脊椎动物漂流)对漂流捕食鱼的能量摄入的影响,因此它们为建模单个生长提供了一个连贯且可转移的框架,其中包括物理栖息地和生物生产。尽管如此,漂移觅食模型在应用环境中实现其潜力的速度仍然很慢。由于难以预测生长(而不是选择栖息地)以及对个体生长进行规模预测以达到规模的生境能力,实际应用受到了阻碍,这需要对个体之间的资源分配和捕食造成的流失进行建模。流域生态学家普遍未能充分描述流域内和流域之间无脊椎动物漂移的时空变化特征,因此对漂移觅食模型这一关键组成部分的变化源仍然知之甚少。直到最近的研究表明漂移通量,模型化的净能量摄入量和鱼类生物量之间有很强的关系之前,对栖息地容量预测的验证一直很少或缺乏。漂移觅食模型的实际应用的进一步发展将需要:i)更好地理解引起漂移变化的因素,更好的漂移建模方法以及表征它的更标准化方法; ii)确定简单的诊断指标,这些指标与栖息地质量的更精确但耗时的生物能评估高度相关; iii)更好地了解漂流觅食策略的变化如何与其他系列共同进化的性状相关联,这些特征在生态上区分了以漂流为食的鲑鱼类群。

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