Effects of sampling completeness on the structure of plant-pollinator networks.

Plant-animal interaction networks provide important information on community organization. One of the most critical assumptions of network analysis is that the observed interaction patterns constitute an adequate sample of the set of interactions present in plant-animal communities. In spite of its importance, few studies have evaluated this assumption, and in consequence, there is no consensus on the sensitivity of network metrics to sampling methodological shortcomings. In this study we examined how variation in sampling completeness influences the estimation of six network metrics frequently used in the literature (connectance, nestedness, modularity, robustness to species loss, path length, and centralization). We analyzed data of 186 flowering plants and 336 pollinator species in 10 networks from a forest-fragmented system in central Chile. Using species-based accumulation curves, we estimated the deviation of network metrics in undersampled communities with respect to exhaustively sampled communities and the effect of network size and sampling evenness on network metrics. Our results indicate that: (1) most metrics were affected by sampling completeness but differed in their sensitivity to sampling effort; (2) nestedness, modularity, and robustness to species loss were less influenced by insufficient sampling than connectance, path length, and centralization; (3) robustness was mildly influenced by sampling evenness. These results caution studies that summarize information from databases with high, or unknown, heterogeneity in sampling effort per species and should stimulate researchers to report sampling intensity to standardize its effects in the search for broad patterns in plant-pollinator networks.