Data from: Integrating vital rates explains optimal worker size for resource return by bumble bee workers
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https://datadryad.org/dataset/doi:10.5061/dryad.42gp897
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1. Size-number trade-offs in reproduction are commonly observed in nature.
Bumble bee (Bombus spp.) colonies produce workers that vary considerably
in size. This variation suggests that colonies face potential size-number
trade-offs when producing workers. 2. Here, we estimated size-based vital
rates of Bombus vosnesenskii workers using colonies reared from wild
caught queens. We conducted a mark-recapture study to estimate worker
survival as a function of body size. We also collected data on pollen and
nectar loads as well as foraging trips using a radio-frequency
identification system to estimate daily resource return as a function of
body size. We integrated survival and daily resource return to estimate
lifetime resource collection and offset these estimates by the size-based
worker production costs. 3. We found size-based trade-offs among workers
of different sizes. Smaller workers had higher survival, but larger
workers returned with more resources per day. The largest workers made
slightly fewer foraging trips per day. 4. Overall, larger workers made the
greatest lifetime contribution to both nectar and pollen collection.
However, once the benefits of larger workers are offset by their higher
production costs, intermediate-sized workers were the optimal for net
resource contribution according to our models. Many previous studies have
found that larger workers outperformed smaller workers with foraging and
in-nest tasks, yet these studies have not integrated multiple fitness
components or worker production costs to quantify net resource
contribution towards colony growth. 5. Accounting for tradeoffs between
costs and performance changed our conclusions about optimal body size from
being large to being near the observed average. Similar approaches of
integrating multiple vital rates may resolve apparently suboptimal life
histories in other taxa.
提供机构:
Dryad
创建时间:
2018-11-16



