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New methods of spatial analysis in urban gardens inform future vegetation surveying

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Egerer, MH, Wagner, B, Lin, BB, Kendal, D ORCID: 0000-0003-2816-1722 and Zhu, K 2020 , 'New methods of spatial analysis in urban gardens inform future vegetation surveying' , Landscape Ecology, vol. 35, no. 3 , pp. 761-778 , doi: 10.1007/s10980-020-00974-1.

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Abstract

Context: Land use change requires measuring shifting patterns in biodiversity at various spatial scales to inform landscape management. Assessing vegetation change at different scales is challenging in urban ecosystems managed by many individuals. Thus, we do not know much about the structure and function of green spaces that support biodiversity. Objective: We aim to understand how vegetation structure and function indicators in urban community gardens vary with spatial scale, applying new and traditional methods in landscape ecology to inform future research and application. Methods: We performed two methods to assess garden vegetation structure (height) and function (species diversity, cover) at the garden- and garden plot scale. First, we used traditional field sampling to estimate garden vegetation at the garden scale (1 m2 quadrats along transects) and at the plot scale (estimated within entire plot) to measure height, diversity and cover. Second, we used UAV aerial imagery to derive measures of garden and plot vegetation using canopy height models (CHMs). We evaluated differences in CHMs at each scale across the gardens, and compared field and UAV-derived measures. Results: Garden vegetation characteristics vary with spatial scale. Plant species richness and vegetation cover, but not height, related to UAV-derived imagery. Conclusions: New technologies paired with traditional field methods can together inform how vegetation structure and function vary with spatial scale in urban landscapes. Spatial scale is key to accurate and meaningful urban vegetation analyses. New and traditional methods in urban ecology research should develop together to improve and streamline their future application.

Item Type: Article
Authors/Creators:Egerer, MH and Wagner, B and Lin, BB and Kendal, D and Zhu, K
Keywords: urban agriculture, plant diversity, garden, unmanned aerial vehicle, remote sensing, citizen science, community gardens, species identification
Journal or Publication Title: Landscape Ecology
Publisher: Kluwer Academic Publ
ISSN: 0921-2973
DOI / ID Number: 10.1007/s10980-020-00974-1
Copyright Information:

Copyright The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made

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