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Indirect Energy Flows in Niche Model Food Webs: Effects of Size and Connectance

机译:生态位模型食物网中的间接能量流:尺寸和连接性的影响

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摘要

Indirect interactions between species have long been of interest to ecologists. One such interaction type takes place when energy or materials flow via one or more intermediate species between two species with a direct predator-prey relationship. Previous work has shown that, although each such flow is small, their great number makes them important in ecosystems. A new network analysis method, dynamic environ approximation, was used to quantify the fraction of energy flowing from prey to predator over paths of length greater than 1 (flow indirectness or FI) in a commonly studied food web model. Web structure was created using the niche model and dynamics followed the Yodzis-Innes model. The effect of food web size (10 to 40 species) and connectance (0.1 to 0.48) on FI was examined. For each of 250 model realizations run for each pair of size and connectance values, the FI of every predator-prey interaction in the model was computed and then averaged over the whole network. A classification and regression tree (CART) analysis was then used to find the best predictors of FI. The mean FI of the model food webs is 0.092, with a standard deviation of 0.0279. It tends to increase with system size but peaks at intermediate connectance levels. Of 27 potential predictor variables, only five (mean path length, dominant eigenvalue of the adjacency matrix, connectance, mean trophic level and fraction of species belonging to intermediate trophic levels) were selected by the CART algorithm as best accounting for variation in the data; mean path length and the dominant eigenvalue of the adjacency matrix were dominant.
机译:长期以来,生态学家一直关注物种之间的间接相互作用。当能量或物质通过两个物种之间具有直接捕食者-被捕食关系的一个或多个中间物种流动时,就会发生一种这样的相互作用类型。先前的工作表明,尽管每一个这样的流量都很小,但数量巨大,使其在生态系统中很重要。在通常研究的食物网模型中,使用了一种新的网络分析方法,即动态环境逼近,来量化在长度大于1(流动间接性或FI)的路径上从猎物流向掠食者的能量比例。 Web结构是使用利基模型创建的,动力学遵循Yodzis-Innes模型。研究了食物网尺寸(10至40种)和连接度(0.1至0.48)对FI的影响。对于针对每对大小和连通性值运行的250个模型实现中的每一个,计算模型中每个捕食者与被捕食者相互作用的FI,然后在整个网络中平均。然后,使用分类和回归树(CART)分析来找到FI的最佳预测因子。模型食物网的平均FI为0.092,标准偏差为0.0279。它倾向于随系统大小而增加,但在中间连接级别达到峰值。在27个潜在的预测变量中,CART算法仅选择了5个(平均路径长度,邻接矩阵的主要特征值,连通性,平均营养水平和属于中等营养水平的物种的分数)作为对数据变化的最佳解释;平均路径长度和邻接矩阵的主要特征值是主要的。

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    Jane Shevtsov; Rosalyn Rael;

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  • 年(卷),期 -1(10),10
  • 年度 -1
  • 页码 e0137829
  • 总页数 14
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