García-Algarra Javier, Pastor Juan Manuel, Iriondo José María, Galeano Javier
Centro Universitario U-TAD, Las Rozas, Spain.
Complex Systems Group, Universidad Politécnica de Madrid, Madrid, Spain.
PeerJ. 2017 May 18;5:e3321. doi: 10.7717/peerj.3321. eCollection 2017.
Network analysis has become a relevant approach to analyze cascading species extinctions resulting from perturbations on mutualistic interactions as a result of environmental change. In this context, it is essential to be able to point out key species, whose stability would prevent cascading extinctions, and the consequent loss of ecosystem function. In this study, we aim to explain how the -core decomposition sheds light on the understanding the robustness of bipartite mutualistic networks.
We defined three -magnitudes based on the -core decomposition: -radius, -degree, and -risk. The first one, -radius, quantifies the distance from a node to the innermost shell of the partner guild, while -degree provides a measure of centrality in the -shell based decomposition. -risk is a way to measure the vulnerability of a network to the loss of a particular species. Using these magnitudes we analyzed 89 mutualistic networks involving plant pollinators or seed dispersers. Two static extinction procedures were implemented in which -degree and -risk were compared against other commonly used ranking indexes, as for example MusRank, explained in detail in Material and Methods.
When extinctions take place in both guilds, -risk is the best ranking index if the goal is to identify the key species to preserve the giant component. When species are removed only in the primary class and cascading extinctions are measured in the secondary class, the most effective ranking index to identify the key species to preserve the giant component is -degree. However, MusRank index was more effective when the goal is to identify the key species to preserve the greatest species richness in the second class.
The -core decomposition offers a new topological view of the structure of mutualistic networks. The new -radius, -degree and -risk magnitudes take advantage of its properties and provide new insight into the structure of mutualistic networks. The -risk and -degree ranking indexes are especially effective approaches to identify key species to preserve when conservation practitioners focus on the preservation of ecosystem functionality over species richness.
网络分析已成为一种重要方法，用于分析因环境变化导致互利共生相互作用受到干扰而引发的级联物种灭绝。在此背景下，能够指出关键物种至关重要，这些物种的稳定性可防止级联灭绝以及随之而来的生态系统功能丧失。在本研究中，我们旨在解释核心分解如何有助于理解二分互利共生网络的稳健性。
我们基于核心分解定义了三个量：半径、度和风险。第一个量，半径，量化了一个节点到其伙伴群落最内层壳的距离，而度则提供了基于壳分解的中心性度量。风险是衡量网络对特定物种丧失的脆弱性的一种方式。利用这些量，我们分析了89个涉及植物传粉者或种子传播者的互利共生网络。实施了两种静态灭绝程序，其中将度和风险与其他常用的排名指标进行比较，例如材料与方法中详细解释的MusRank。
当两个群落都发生灭绝时，如果目标是识别出能保护巨型组件的关键物种，风险是最佳的排名指标。当仅在初级类中移除物种并在次级类中测量级联灭绝时，识别出能保护巨型组件的关键物种的最有效排名指标是度。然而，当目标是识别出能保护次级类中最大物种丰富度的关键物种时，MusRank指标更有效。
核心分解为互利共生网络的结构提供了一种新的拓扑视角。新的半径、度和风险量利用了其特性，并为互利共生网络的结构提供了新的见解。当保护从业者关注生态系统功能而非物种丰富度的保护时，风险和度排名指标是识别关键保护物种的特别有效方法。
