Pollinator population size and pollination ecosystem service responses to enhancing floral and nesting resources

Abstract

Modeling pollination ecosystem services requires a spatially explicit, process‐based approach because they depend on both the behavioral responses of pollinators to the amount and spatial arrangement of habitat and on the within‐ and between‐season dynamics of pollinator populations in response to land use. We describe a novel pollinator model predicting flower visitation rates by wild central‐place foragers (e.g., nesting bees) in spatially explicit landscapes. The model goes beyond existing approaches by: (1) integrating preferential use of more rewarding floral and nesting resources; (2) considering population growth over time; (3) allowing different dispersal distances for workers and reproductives; (4) providing visitation rates for use in crop pollination models. We use the model to estimate the effect of establishing grassy field margins offering nesting resources and a low quantity of flower resources, and/or late‐flowering flower strips offering no nesting resources but abundant flowers, on bumble bee populations and visitation rates to flowers in landscapes that differ in amounts of linear seminatural habitats and early mass‐flowering crops. Flower strips were three times more effective in increasing pollinator populations and visitation rates than field margins, and this effect increased over time. Late‐blooming flower strips increased early‐season visitation rates, but decreased visitation rates in other late‐season flowers. Increases in population size over time in response to flower strips and amounts of linear seminatural habitats reduced this apparent competition for pollinators. Our spatially explicit, process‐based model generates emergent patterns reflecting empirical observations, such that adding flower resources may have contrasting short‐ and long‐term effects due to apparent competition for pollinators and pollinator population size increase. It allows exploring these effects and comparing effect sizes in ways not possible with other existing models. Future applications include species comparisons, analysis of the sensitivity of predictions to life‐history traits, as well as large‐scale management intervention and policy assessment.

Flowering resources distract pollinators from crops: Model predictions from landscape simulations

“…Additional floral resources are most likely to benefit pollinators during periods of low availability, within and across years (Häussler, Sahlin, Baey, Smith, & Clough, 2017;. coexistence, and this work is underway (Bolin, Smith, Lonsdorf, & Olsson, 2018).…”

Bombus terrestris in a mass‐flowering pollinator‐dependent crop: A mutualistic relationship?

“…Since accurately studying bumblebee colony development in a field setting can be difficult (Westphal, Steffan-Dewenter, & Tscharntke, 2009;Wood, Holland, Hughes, & Goulson, 2015), this study uses an in-silico approach to simulate the population dynamics of Bombus terrestris L. in landscapes with and without courgette fields using the agent-based model Bumble-BEEHAVE (Becher et al, 2018). Although other bumblebee models exist (Crone & Williams, 2016;Häussler, Sahlin, Baey, Smith, & Clough, 2017;Olsson, Bolin, Smith, & Lonsdorf, 2015), Bumble-BEEHAVE is uniquely able to simulate the effects of multifactorial stressors on bumblebee survival at individual, colony and population levels on a daily basis, based on nectar and pollen sources which are approximated from real landscape maps of study sites.…”

Bumble‐BEEHAVE: A systems model for exploring multifactorial causes of bumblebee decline at individual, colony, population and community level

“…Six contrasting bumblebee models have recently been published (Banks et al., ; Bryden, Gill, Mitton, Raine, & Jansen, ; Cresswell, ; Crone & Williams, ; Häussler, Sahlin, Baey, Smith, & Clough, ; Olsson, Bolin, Smith, & Lonsdorf, ). However, while useful in exploring the impact of individual stressors, such as food availability (Crone & Williams, ) or pesticides (Bryden et al., ; Cresswell, ), none as yet have the structural realism to incorporate multiple stressors or competition, operating at different organisational levels (individual or colony or population).…”

“…Six contrasting bumblebee models have recently been published (Banks et al, 2017;Bryden, Gill, Mitton, Raine, & Jansen, 2013;Cresswell, 2017;Crone & Williams, 2016;Häussler, Sahlin, Baey, Smith, & Clough, 2017;Olsson, Bolin, Smith, & Lonsdorf, 2015).…”

“…This mechanistic richness is essential for deep and broad understanding of risk (EFSA, 2015)-indeed Crone and Williams (2016) and Banks et al (2017) noted that further processes and stage structure need incorporation. Most existing studies do not model multiple colonies (Bryden et al, 2013;Cresswell, 2017;Häussler et al, 2017; although see Banks et al, 2017) or capture the spatio-temporal dynamics of resource availability (although see Häussler et al, 2017;Olsson et al, 2015;Polce et al, 2013) which are essential to make accurate predictions in real landscapes. Table 1 summarises the approach and capability of each model in contrast to the Bumble-BEEHAVE model presented here.…”