Consumer-plant interaction strength: importance of body size, density and metabolic biomass

Consumer-plant interaction strength: importance of body size, density and metabolic biomass
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DOI:
10.1111/oik.01966
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发表时间:
2015-10-01
期刊:
影响因子:
3.4
通讯作者:
Silliman, Brian R.
Silliman, Brian R.
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Atkins, Rebecca L.;Griffin, John N.;Silliman, Brian R.

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解释初级消费者和植物之间营养相互作用的强度和迹象的变化是一个长期存在的研究挑战。消费者密度和身体大小在空间和时间上变化很大,预计消费者-植物相互作用具有交互作用。在美国南部的盐沼,我们使用复制字段外壳正交操纵的身体大小(质量)和密度的一个占主导地位的消费者(蜗牛)。我们调查的影响(叶损伤和生物量)单一栽培的大米草,基础物种,超过三个月。增加消费者密度和身体的大小增加叶损害的添加剂,并预测,成倍减少植物生物量。值得注意的是,大小和密度决定了消费者对植物的影响的迹象:低至中等密度的小消费者增强,而高密度的大消费者强烈抑制,植物生物量。最后,总消费者代谢生物量(质量(0.75))在一个封闭的简约解释植物生物量的反应,支持理论预测,并表明,倍增效应的密度和身体大小导致其对总代谢生物量的影响。因此,可以根据代谢生物量预测人为扰动引起的消费者密度和体型变化的后果。
Explaining variability in the strength and sign of trophic interactions between primary consumers and plants is a long-standing research challenge. Consumer density and body size vary widely in space and time and are predicted to have interactive effects on consumer-plant interactions. In a southern US salt marsh, we used replicate field enclosures to orthogonally manipulate the body size (mass) and density of a dominant consumer (a snail). We investigated impacts (leaf damage and biomass) on monocultures of cordgrass, the foundation species, over three months. Increasing consumer density and body size increased leaf damage additively and, as predicted, multiplicatively reduced plant biomass. Notably, size and density determined the sign of consumer impact on plants: low to medium densities of small consumers enhanced, while high densities of large consumers strongly suppressed, plant biomass. Finally, total consumer metabolic biomass (mass(0.75)) within an enclosure parsimoniously explained plant biomass response, supporting theoretical predictions and suggesting that multiplicative effects of density and body size resulted from their effects on total metabolic biomass. The consequences of changes in consumer density and body size resulting from anthropogenic perturbations may therefore be predicted based on metabolic biomass.