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Fishing for nutrients in heterogeneous landscapes: modelling plant growth trade-offs in monocultures and mixed communities

机译:捕捞异质景观中的养分:模拟单一栽培和混合社区中植物生长的权衡

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摘要

The problem of how best to find and exploit essential resources, the quality and locations of which are unknown, is common throughout biology. For plants, the need to grow an efficient root system so as to acquire patchily distributed soil nutrients is typically complicated by competition between plants, and by the costs of maintaining the root system. Simple mechanistic models for root growth can help elucidate these complications, and here we argue that these models can be usefully informed by models initially developed for foraging fish larvae. Both plant and fish need to efficiently search a spatio-temporally variable environment using simple algorithms involving only local information, and both must perform this task against a backdrop of intra- and inter-specific competition and background mortality. Here we develop these parallels by using simple stochastic models describing the growth and efficiency of four contrasting idealized root growth strategies. We show that plants which grow identically in isolation in homogeneous substrates will typically perform very differently when grown in monocultures, in heterogeneous nutrient landscapes and in mixed-species competition. In particular, our simulations show a consistent result that plants which trade-off rapid growth in favour of a more efficient and durable root system perform better, both on average and in terms of the best performing individuals, than more rapidly growing ephemeral root systems. Moreover, when such slower growing but more efficient plants are grown in competition, the overall community productivity can exceed that of the constituent monocultures. These findings help to disentangle many of the context-dependent behaviours seen in the experimental literature, and may form a basis for future studies at the level of complex population dynamics and life history evolution.
机译:在整个生物学中,如何最好地发现和利用必需资源的质量和位置未知的问题是很普遍的。对于植物而言,由于植物之间的竞争以及维持根系的成本,通常需要生长高效的根系以获取分布不均匀的土壤养分。简单的根部生长机理模型可以帮助阐明这些并发症,在这里我们认为,这些模型可以从最初为觅食鱼幼虫开发的模型中获得有用的信息。植物和鱼类都需要使用仅涉及本地信息的简单算法来有效地搜索时空变化的环境,并且两者都必须在种内和种间竞争和背景死亡率的背景下执行此任务。在这里,我们通过使用简单的随机模型来描述这些相似之处,该模型描述了四种对比的理想根生长策略的生长和效率。我们表明,在单一栽培,异质养分景观和混合物种竞争中生长时,在均质基质中独立生长的植物通常会表现出很大不同。尤其是,我们的模拟显示出一致的结果,即权衡快速增长以支持更高效和持久的根系的植物,比起较快生长的短暂根系,在平均水平和表现最佳的个体方面均表现更好。而且,当这种生长缓慢但效率更高的植物在竞争中生长时,整个社区的生产力可能会超过组成单一栽培的生产力。这些发现有助于弄清实验文献中许多与环境有关的行为,并可能为将来在复杂的人口动态和生活史演变水平上进行研究奠定基础。

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