Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Abstract

Seasonal turnover in plant and floral visitor communities changes the structure of the network of interactions they are involved in. Despite the dynamic nature of plant–visitor networks, a usual procedure is to pool year‐round interaction data into a single network which may result in a biased depiction of the real structure of the interaction network. The annual temporal dynamics and the effect of merging monthly data have previously been described for qualitative data (i.e. describing the occurrence of interactions) alone, while its quantitative aspect (i.e. the actual frequency with which interactions occur) remain little explored. For this, we built a set of 12 monthly networks describing year‐round plant–floral visitor interactions in a 30‐hectare planted forest and its adjacent agricultural landscape at Bahauddin Zakariya University Multan, Pakistan. A total of 80 plant and 162 insect species, which engaged in 1573 unique interactions, were recorded. Most network properties (particularly the number of plants, visitors and unique interactions) varied markedly during the year. Data aggregation showed that while animal species, plant species, unique interaction, weighted nestedness, interaction diversity and robustness increased, connectance and specialization decreased. The only metric which seemed relatively unaffected by data pooling was interaction evenness. In general, quantitative metrics were relatively less affected by temporal data aggregation than qualitative ones. Avoiding data aggregation not only gives a more realistic depiction of the dynamic nature of plant–visitor community networks, but also avoids biasing network metrics and, consequently, their expected response to disturbances such as the loss of species.

Seasonal variation of plant-pollinator networks on oceanic island: lower specialization when resources are more abundant

“…Meanwhile, the winter season had two additional distinct features: specialized visitor groups (Lepidoptera) were more species-rich, and more specialized plants were blooming during this period. In this study, all network qualitative properties showed significant seasonal variations of a single network through its annual cycle which were consistent with previous studies [42,49,50]. The seasonal changes in nestedness, network-level specialization and modularity suggest that species exhibited more specialized interactions during the season when the number of species and interactions were at a minimum.…”

“…The seasonal changes in nestedness, network-level specialization and modularity suggest that species exhibited more specialized interactions during the season when the number of species and interactions were at a minimum. The similar results were also found in subtropical climate areas [50]. Since specialization is not affected by system size and sampling intensity [32]; our findings regarding seasonal variations in specialization seem robust.…”

“…For example, Apidae concentrated their collection activities on a limited group of sources when many types of resources were available, whereas more plant species were exploited during periods of lower number of flowering plants [51]. The variability of the abundance of species that interact in four seasons, the phenological changes in flowering and pollinator appearances, and importantly, the opposite results of network-level specialization between two seasons (dry and rainy) networks and among seven networks suggested that simple cumulative networks were a limited tool for the deep analysis of a pollination system, even though the qualitative metrics were more affected by temporal data aggregation than quantitative ones [50]. The present study thus strengthens the viewpoint that a proper description of the interactions in a plant-pollinator community with year-round activity should include all months and not just the few months of dry and rainy seasons.…”

Core-periphery structure in mutualistic networks: an epitaph for nestedness?

“…Network mesoscale structures derive from node degree distributions, which in mutualistic networks are highly skewed, with few highly generalized species and a long tail of specialists Jonhson et al, 2013;Sajjad et al, 2017). Numerous studies suggest that observed degree distributions result from neutral processes, such as highly skewed abundances or sampling-related issues, which ultimately result in large differences in species' detection probabilities (Ollerton et al, 2003;Vázquez & Aizen, 2004;Vázquez et al, 2005Vázquez et al, , 2009Kallimanis et al, 2009;Araujo et al, 2010).…”

“…For instance, current practices involve the quantification of network properties on data that is aggregated temporally, disregarding temporal dynamics despite these communities show high turnovers of species and interactions, with a highly skewed distribution of species' phenophases, and a network structure that evolves seasonally (Ollerton et al, 2003;Vázquez et al, 2005Vázquez et al, , 2009Olesen et al, 2008;Petanidou et al, 2008;Kallimanis et al, 2009;Araujo et al, 2010;Zhang et al, 2011;Falcão et al, 2016;Sajjad et al, 2017;Kantsa et al, 2018). In addition to skewed degree distributions, mutualistic networks tend to have a high degree of disassortativity, that is, specialist species tend to interact with generalists (Vázquez & Aizen, 2004;Jonhson et al, 2013).…”