Data from: Effects of plant and pollinator traits on the maintenance of a food deceptive species within a plant community
| Main Authors: | Qu, Hungchun, Seifan, Tal, Seifan, Merav, Qu, Hongchun |
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| Format: | info dataset Journal |
| Terbitan: |
, 2017
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4989562 |
Daftar Isi:
- Model-mimic plant systems are well known. However, the conditions promoting the existence of such systems are still an enigma. We suggest that by focusing on floral similarity between model and mimic, reward levels offered by models, and pollinators' ability to adjust foraging accordingly, the conditions can be better understood. Using spatially-explicit modelling, we examined trait combinations that lead to the survival of deceptive species under a large range of mimic strategies, from Batesian mimicry to general food deception. Unlike previous models studying such systems, we examined model-mimic interactions in the presence of a third, dissimilar species, thus generating a more realistic scenario where pollinators may avoid the model-mimic system altogether. Results showed that overall survival and abundance of species in food deceptive systems depend on the relative reward provided by the participating species and the potential alternatives available. Specifically, the success of a mimic in a Batesian mimicry system depends on high levels of reward provided by its model species relative to potential alternatives in the flower community. On the other hand, the success of a mimic in a general food deception system was higher when the reward offered was lower. Our study suggests that the ability of pollinators to utilize their experience as part of decision-making is highly relevant in promoting mimic survival, thus shedding light on the conditions under which food deception is expected.
- Coefficients for best survival modelCoeeficients and SE for the selected survival model for each of the plant species. The models were selected by forward selection process out of the set of Cox proportional hazard regressions constructed of all combinations of the model explanatory factors.TableA12.docxCoefficients for best abundance modelModel Coeefficients and SE for the selected abundance model for each of the plant species. The models were selected by forward selection process out of the GLMM of all combinations of the model explanatory factors.Table A14.docxCoefficients for best pollinator visit modelsModel coefficients and SE for the selected best model for each of the plant species. The models were selected by forward selection process out of the GLMM of all combinations of the model explanatory factors.Table A23.docxCoefficients for best pollinator choice modelModel coefficients and SE for best pollinator choice model. The models were selected by forward selection process out of the GLM of all combinations of the model explanatory factors.Table A25.docx