![]() Importantly, these relationships were robust to sampling spatial extent. Moreover, we showed that patch configuration at the landscape level can change the direction of these local-scale patch isolation effects on pollinator body-size distribution, functional diversity and plant-pollinator interactions. This complementarity occurred partly because larger pollinators interacted with more plant species. We observed higher pollinator functional diversity in less-isolated patches, which promoted plant reproduction via a relationship between functional diversity and interaction complementarity. ![]() ![]() body-size) diversity influence plant reproduction. We then evaluated how these changes in pollinator functional (i.e. We combined a field experiment with an agent-based model to assess how landscape structure and local flower patch isolation affect pollinator body-size distribution and plant-pollinator interactions, sampled at different spatial extents. The environmental filtering of species traits can influence the identity of their interaction partners and the contribution of species interactions to ecosystem functioning, but the extent to which this process is influenced by landscape composition and configuration remains unclear. Users of this package benefit from the fast and easy coding provided by the highly developed NetLogo framework, coupled with the versatility, power and massive resources of the R language. NetLogoR provides new R classes to define model agent objects and functions to implement spatially explicit agent‐based models in the R environment. Models built with NetLogoR are written in R language and are run on the R platform no other software or language has to be involved. Rather than a call function to use the NetLogo software, NetLogoR is a translation into the R language of the structure and functions of NetLogo. NetLogoR follows the same framework as the NetLogo software (Wilensky 1999). SE‐ABMs are models that simulate the fate of entities at the individual level within a spatial context and where patterns emerge at the population level. ![]() ![]() NetLogoR is an R package to build and run spatially explicit agent‐based models (SE‐ABMs) using the R language. ![]()
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