Land use change is a major pressure on pollinator abundance, diversity, and plant-pollinator interactions. Far less is known about how land use alters the structure of plant-pollinator networks and their robustness to plant-pollinator coextinctions.

We analyzed the structure of plant-pollinator networks sampled in 12 landscapes along an urbanisation and agricultural intensity gradient, from early spring to late summer 2021, and used a stochastic coextinction model to correlate plant-pollinator coextinction risk with network structure (species and network-level metrics) and landscape context.

Networks in intensively managed (i.e. agricultural and urban) landscapes had a lower risk of initiating a coextinction cascade, while networks in less-intensively managed landscapes may be less robust. Network structure modulated the frequency and severity of coextinctions and species loss, while the strength of species interactions increased robustness.

Urban networks were more species-rich and symmetrical due to the high diversity of ornamental plants, while intensively managed agricultural landscapes had smaller, more tightly connected, and nested networks.

Network structure modulated the frequency of extinctions, which was decreased by greater linkage density, interaction asymmetry, and interaction dependence in the networks, while once an extinction occurred, nestedness and linkage density propagated the degree of the coextinction cascade and species loss. At the species level, species strength was inversely correlated with extinction risk, implying that generalist species with a high number of interactions with specialists had the lowest extinction risk.

The dataset describes plant-pollinator networks in 12 landscapes in Bourgogne (eastern France), collected in three different seasons. Per sampling site and sampling period, all pollinators on flowers were caught on a 1 km transect with 2 hours of catching time. The landscape was 1 km in radius and landscape metrics were calculated based on this distance. Pollinators were caught within the inner 500 m radius of this landscape. Network metrics were calculated using the bipartite package in R. Z-score standardization was done using 10,000 random networks created by the vaznull function in bipartite.

A Stochastic Coextinction Model (SCM) was run on the data to test network robustness. The R code for this is given. For further details, we refer to the metadata files.