Ecological Modeling for Pesticide Risk Assessment for Honey Bees and Other Pollinators

Grimm, Volker; Becher, Melissa; Thorbek, Pernille; Osborne, Juliet L.

doi:10.1002/9781118852408.ch11

Cited by 3 publications

(3 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, agent‐based models are fundamentally designed to track state variables on an individual basis, enabling the distributional modeling of exposure levels experienced by individual bees. The development of an agent‐based modeling, though, is typically a long and demanding process, especially when the model is intended to support regulatory decision‐making . A simpler, though minimally mechanistic, approach would be to simulate in‐hive pesticide distribution by Monte Carlo sampling.…”

Section: Secondary Exposurementioning

confidence: 99%

Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology

Sponsler

Johnson

2016

Enviro Toxic and Chemistry

View full text Add to dashboard Cite

Abstract:The role of pesticides in recent honey bee losses is controversial, partly because field studies often fail to detect effects predicted by laboratory studies. This dissonance highlights a critical gap in the field of honey bee toxicology: there exists little mechanistic understanding of the patterns and processes of exposure that link honey bees to pesticides in their environment. The authors submit that 2 key processes underlie honey bee pesticide exposure: 1) the acquisition of pesticide by foraging bees, and 2) the in-hive distribution of pesticide returned by foragers. The acquisition of pesticide by foraging bees must be understood as the spatiotemporal intersection between environmental contamination and honey bee foraging activity. This implies that exposure is distributional, not discrete, and that a subset of foragers may acquire harmful doses of pesticide while the mean colony exposure would appear safe. The inhive distribution of pesticide is a complex process driven principally by food transfer interactions between colony members, and this process differs importantly between pollen and nectar. High priority should be placed on applying the extensive literature on honey bee biology to the development of more rigorously mechanistic models of honey bee pesticide exposure. In combination with mechanistic effects modeling, mechanistic exposure modeling has the potential to integrate the field of honey bee toxicology, advancing both risk assessment and basic research. Environ Toxicol Chem 2017;36:871-881. # 2016 SETAC

show abstract

Section: Secondary Exposurementioning

confidence: 99%

Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology

Sponsler

Johnson

2016

Enviro Toxic and Chemistry

View full text Add to dashboard Cite

show abstract

“…To understand the role that each of the factors pesticides, parasites and lack of floral resources, may play in honeybee colony failure, multi-stress models are needed that deal with hive dynamics, parasitic infections as well as contaminants (Grimm et al 2014). The BEEHAVE model is an example of such a model (Becher et al 2014;Rumkee et al 2015) that can be exploited to disentangle the multi-stress interactions.…”

Section: Introductionmentioning

confidence: 99%

An energetics-based honeybee nectar-foraging model used to assess the potential for landscape-level pesticide exposure dilution

Baveco

Focks

Belgers

et al. 2015

Preprint

View full text Add to dashboard Cite

Estimating the exposure of honeybees to pesticides on a landscape scale requires models of their spatial foraging behaviour. For this purpose, we developed a mechanistic, energetics-based model for a single day of nectar foraging in complex landscape mosaics. The hive population was assumed to select the resource patch with highest net energetic efficiency in perfect knowledge of its environment. During the day the optimal patch could change, due to resource depletion or related to the characteristics of the resource (i.e., the period flowers were open and provided nectar). By quantifying foraging costs and yield in terms of energy, we accounted for the impact of field distance and size, the occurrence of resource depletion and the characteristics of the resource type (crops and wild flowers), like seasonal and diurnal patterns in availability.From the model we derived simple rules for resource patch selection, e.g., for landscapes with mass-flowering crops, the net energetic efficiency would be proportional to the ratio of the energetic content of the nectar of the crop divided by distance of crop field to the hive. Also, we determined maximum distances at which resources like oilseed rape and clover could still be energetically attractive.We used the model to assess the potential for pesticide exposure dilution in landscapes of different composition and complexity. Dilution implied a lower average concentration in nectar arriving at the hive, resulting from foraging effort being diverted away from treated fields. Applying the model for all possible hive locations in a landscape, landscape-specific distributions of dilution values were obtained.For a case study area for which detailed spatial data were available, we tested three scenarios that were expected to lead to exposure dilution: the presence of i) equally attractive crop fields in the neighbourhood of a treated field, ii) highly attractive flowers strips of different widths at the edges of treated fields (off-crop in-field resources), and iii) highly attractive resources on off-field (semi-natural) habitats. The results indicated significant dilution at landscape scale only from flowers strips of more than 5 m wide and off-field habitats. On an area-base, flowers strips were approximately 10 times as effective as off-field habitats, the main reason being that the flowers strips had an optimal location, always at the edges of treated fields.

show abstract

“…Their dependence on cropland for nectar and pollen 9 acquisition, however, leads to high potential exposure to pesticides (Krupke et al 2012). 10 To understand the role that each of the factors pesticides, parasites and lack of floral resources, 11 may play in honeybee colony failure, multi-stress models are needed that deal with hive 12 dynamics, parasitic infections as well as contaminants (Grimm et al 2014). The BEEHAVE nearby, most foraging will take place within a few kilometres.…”

Section: Introductionmentioning

confidence: 99%

Untitled

Supplemental Information 1: Supplemental Figures Baveco Et Al

View full text Add to dashboard Cite

Ecological Modeling for Pesticide Risk Assessment for Honey Bees and Other Pollinators

Cited by 3 publications

References 38 publications

Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology

Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology

An energetics-based honeybee nectar-foraging model used to assess the potential for landscape-level pesticide exposure dilution

Untitled

Contact Info

Product

Resources

About