Data · dataset · 2022
Local plant richness predicts bee abundance and diversity in a study of urban residential yards
Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp3/vl6j53
Description
Abstract
Understanding the drivers of biodiversity in cities is a central goal of urban ecology. There is currently intense scientific and public interest in the factors that influence pollinator diversity in cities and their surroundings. Existing studies point to a variety of landscape and local factors as potentially important, including urbanization (often defined as impervious surface cover in the surrounding lands), tree canopy cover and the diversity and abundance of locally flowering plants.
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However, few studies have sought to weigh the relative importance of these predictors of bee community metrics. Using a set of 27 residential yards chosen to represent a gradient of both urbanization and tree canopy cover at a landscape scale, we used pan trapping and netting to assess the abundance and diversity of local bee communities across the City of Ottawa, Ontario, Canada. Surprisingly, the landscape factors (urbanization and tree cover) described only a tiny fraction (< 1%) of the total variance in bee abundance and diversity across sites.
This was true regardless of the scale of analysis at which the landscape factors were measured. Instead, a yard's floral richness, and, to a somewhat lesser extent, its floral abundance, emerged as the most important predictors of a yard's bee community abundance and diversity. Our study offers an important counterpoint to a growing body of work emphasizing the impacts of landscape factors on bee communities.
Instead, our research suggests that improving bee floral resources by increasing the plant species richness and abundance locally is a powerful tool to support bee conservation, regardless of the level of urbanization or tree cover in the surrounding landscape. Our work highlights that the practice of promoting ‘bee-friendly’ plantings in private yards, currently being undertaken by a number of non-profits around the world, can play an important role in restoring and maintaining urban pollinator communities.
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP3%2FVL6J53 ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp3/vl6j53 ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP3%2… ↗
metadata API · from borealisdata ca
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Crop and pasture production 74%
Provenance · 2 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP3/VL6J53 | 13 d ago | JSON v1 |
| Agri-environmental Research Data Dataverse | doi:10.5683/SP3/VL6J53 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3004 | enrichment · borealisdata ca | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].dataverse_subject:other | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].dataverse_subject:other | source · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |