BACKGROUND Network analyses of plant-animal interactions hold valuable biological information. They are often used to quantify the degree of specialization between partners, but usually based on qualitative indices such as 'connectance' or number of links. These measures ignore interaction frequencies or sampling intensity, and strongly depend on network size. RESULTS Here we introduce two quantitative indices using interaction frequencies to describe the degree of specialization, based on information theory. The first measure (d') describes the degree of interaction specialization at the species level, while the second measure (H2') characterizes the degree of specialization or partitioning among two parties in the entire network. Both indices are mathematically related and derived from Shannon entropy. The species-level index d' can be used to analyze variation within networks, while H2' as a network-level index is useful for comparisons across different interaction webs. Analyses of two published pollinator networks identified differences and features that have not been detected with previous approaches. For instance, plants and pollinators within a network differed in their average degree of specialization (weighted mean d'), and the correlation between specialization of pollinators and their relative abundance also differed between the webs. Rarefied sampling effort in both networks and null model simulations suggest that H2' is not affected by network size or sampling intensity. CONCLUSION Quantitative analyses reflect properties of interaction networks more appropriately than previous qualitative attempts, and are robust against variation in sampling intensity, network size and symmetry. These measures will improve our understanding of patterns of specialization within and across networks from a broad spectrum of biological interactions.

中文翻译：

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衡量物种相互作用网络的专业化。


背景技术植物-动物相互作用的网络分析持有有价值的生物信息。它们通常用于量化合作伙伴之间的专业化程度，但通常基于“连接”或链接数量等定性指数。这些措施忽略了交互频率或采样强度，并且很大程度上取决于网络规模。结果在这里，我们基于信息论引入了两个使用交互频率来描述专业化程度的定量指标。第一个度量 (d') 描述了物种级别的交互专业化程度，而第二个度量 (H2') 则描述了整个网络中双方之间的专业化或划分程度。这两个指数在数学上都是相关的，并且源自香农熵。物种级指数 d' 可用于分析网络内的变化，而 H2' 作为网络级指数可用于不同交互网络之间的比较。对两个已发表的传粉媒介网络的分析发现了以前的方法未检测到的差异和特征。例如，网络内的植物和传粉媒介的平均专业化程度（加权平均值d'）不同，并且传粉媒介的专业化与其相对丰度之间的相关性在网络之间也不同。网络和零模型模拟中的稀疏采样工作表明 H2' 不受网络规模或采样强度的影响。结论 定量分析比以前的定性尝试更恰当地反映了交互网络的特性，并且对于采样强度、网络大小和对称性的变化具有鲁棒性。 这些措施将提高我们对广泛的生物相互作用中网络内部和网络之间的专业化模式的理解。