Yen Jian D L, Cabral Reniel B, Cantor Mauricio, Hatton Ian, Kortsch Susanne, Patrício Joana, Yamamichi Masato
School of Physics and Astronomy, Monash University, Melbourne, VIC, 3800, Australia.
National Institute of Physics, University of the Philippines Diliman, Quezon City, 1101, Philippines.
J Anim Ecol. 2016 Mar;85(2):537-47. doi: 10.1111/1365-2656.12484. Epub 2016 Feb 8.
Trophic interactions are central to ecosystem functioning, but the link between food web structure and ecosystem functioning remains obscure. Regularities (i.e. consistent patterns) in food web structure suggest the possibility of regularities in ecosystem functioning, which might be used to relate structure to function. We introduce a novel, genetic algorithm approach to simulate food webs with maximized throughput (a proxy for ecosystem functioning) and compare the structure of these simulated food webs to real empirical food webs using common metrics of food web structure. We repeat this analysis using robustness to secondary extinctions (a proxy for ecosystem resilience) instead of throughput to determine the relative contributions of ecosystem functioning and ecosystem resilience to food web structure. Simulated food webs that maximized robustness were similar to real food webs when connectance (i.e. levels of interaction across the food web) was high, but this result did not extend to food webs with low connectance. Simulated food webs that maximized throughput or a combination of throughput and robustness were not similar to any real food webs. Simulated maximum-throughput food webs differed markedly from maximum-robustness food webs, which suggests that maximizing different ecological functions can generate distinct food web structures. Based on our results, food web structure would appear to have a stronger relationship with ecosystem resilience than with ecosystem throughput. Our genetic algorithm approach is general and is well suited to large, realistically complex food webs. Genetic algorithms can incorporate constraints on structure and can generate outputs that can be compared directly to empirical data. Our method can be used to explore a range of maximization or minimization hypotheses, providing new perspectives on the links between structure and function in ecological systems.
营养相互作用是生态系统功能的核心，但食物网结构与生态系统功能之间的联系仍不明确。食物网结构中的规律（即一致的模式）表明生态系统功能存在规律的可能性，这或许可用于将结构与功能联系起来。我们引入一种新颖的遗传算法方法来模拟具有最大通量（生态系统功能的一个指标）的食物网，并使用食物网结构的常用指标将这些模拟食物网的结构与实际经验食物网进行比较。我们用对次生灭绝的稳健性（生态系统恢复力的一个指标）代替通量重复此分析，以确定生态系统功能和生态系统恢复力对食物网结构的相对贡献。当连通性（即整个食物网的相互作用水平）较高时，使稳健性最大化的模拟食物网与实际食物网相似，但这一结果并未扩展到连通性低的食物网。使通量最大化或通量与稳健性组合最大化的模拟食物网与任何实际食物网都不相似。模拟的最大通量食物网与最大稳健性食物网明显不同，这表明最大化不同的生态功能可产生不同的食物网结构。基于我们的结果，食物网结构与生态系统恢复力的关系似乎比与生态系统通量的关系更强。我们的遗传算法方法具有通用性，非常适合大型、实际复杂的食物网。遗传算法可纳入对结构的约束，并能生成可直接与经验数据比较的输出。我们的方法可用于探索一系列最大化或最小化假设，为生态系统中结构与功能的联系提供新视角。
