Assessing social and biophysical drivers of spontaneous plant diversity and structure in urban vacant lots.

Clicks: 353
ID: 12749
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #96 of 637 articles by views in The Science of the total environment

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 637 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Vacant lots are typically viewed as urban blight but are also green spaces that provide wildlife habitat and ecosystem services in urban landscapes. Vacant lot vegetation results from interacting biophysical and social forces, and studying vacant lot ecology is an opportunity to examine urban socio-environmental intersections. Here, we assess vegetation patterns in vacant lots across Chicago, IL (USA), and ask two questions: 1) How does diversity and structure vary, and 2) how do social and biophysical drivers contribute to this variation? We conducted vegetation surveys in 35 vacant lots in the summer of 2015. In each lot, we identified all herbaceous plants (excluding turf grasses) and woody seedlings and measured species richness, evenness, vegetation height, and total vegetated area. We used field sampled data about human activities and land use in vacant lots (e.g., presence of a path, trash and turf), coupled with sociodemographic data (e.g., income, ethnicity), and fine-scale land cover to construct two models for each vegetation measure: a best-fit biophysical model and a best-fit social model. We then used variation partitioning to compare the relative strength of these models and any overlap between them. In total, we identified 109 plant species. Species evenness was high, suggesting that there are few rare species in this system. Species richness and vegetation height were better explained by social models, while vegetated area and evenness were better explained by biophysical models. We saw evidence of overlapping explanatory power between the social and biophysical domains. The amount of trash in a lot was the most significant variable, explaining three of our vegetation measures. Lots with higher amounts of trash had higher richness and evenness, and lower vegetated area. This assessment of patterns of vegetation in Chicago's vacant lots provides insight into how habitat differs across the city and informs urban conservation paradigms.
Reference Key
anderson2019assessingthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Anderson, Elsa C;Minor, Emily S;
Journal The Science of the total environment
Year 2019
DOI
S0048-9697(18)34351-1
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.