DOI: 10.5061/dryad.2bvq83c31
title: Data from: Complementing urban agriculture and green spaces is important for ecosystem functions and biodiversity in cities: A systematic review and meta-analysis

description: As cities expand, they encroach on agricultural land, impacting food
 production and natural habitats. While urban agriculture could help
 address these issues, the impact of increased food production on ecosystem
 functions—particularly with regards to soil conservation, climate
 regulation, and biodiversity—remains poorly understood. To fill this
 knowledge gap, we conducted a meta-analysis to quantify the effects of
 urban agriculture on ecosystem functions (i.e., soil quality and climate
 regulation) and biodiversity (i.e., plants, birds, mammals, arthropods,
 and insect pollinators). We estimated ecosystem functions and biodiversity
 in urban agriculture by comparing them with other urban green spaces
 (e.g., parks, residential gardens, green roofs) and conventional rural
 farms. Our results overall showed that urban agriculture is in an
 intermediate state between the other urban green spaces and conventional
 rural farms in terms of environmental impacts. Urban agriculture had a
 positive effect on the studied ecosystem functions relative to
 conventional rural farms (+25%, CI95: +12% to +39%), but was equivalent in
 its provision of these functions to other green spaces. Urban agriculture
 also had a positive effect on biodiversity compared to conventional rural
 farms (+38%, CI95: -10 to +111%), but a negative effect compared to green
 spaces (-12%, CI95: -29 to +8%). Specifically, urban agriculture had 39%
 (CI95: -59 to -10%) lower plant diversity and abundance than that seen in
 other green spaces. Practical implications: Our results suggest that urban
 agriculture's contribution to urban sustainability requires
 complementarity with other green spaces to effectively support ecosystem
 functions and biodiversity in cities. We also detected substantial issues
 with the classification and characterisation of urban agriculture plots.
 Improving conceptual and methodological consistency will continue to be a
 crucial challenge for urban agriculture research.
description: # Data from: Complementing urban agriculture and green spaces is important
 for ecosystem functions and biodiversity in cities: A systematic review
 and meta-analysis Dataset DOI:
 [10.5061/dryad.2bvq83c31](10.5061/dryad.2bvq83c31) ## Description of the
 data and file structure We followed PRISMA guidelines to screen articles
 (2000–2024) on urban agriculture’s effects on biodiversity and ecosystem
 functions. Studies were selected if they: (1) involved
 soil/substrate-based urban farms/gardens (including hydroponics), (2)
 cultivated crops (excluding livestock-only systems), and (3) compared
 urban agriculture to green infrastructure or rural farms. We searched
 Scopus and Web of Science using terms like “Urban agriculture,”
 “Biodiversity,” and taxonomic groups (e.g., “Birds,” “Insects”). After
 removing duplicates, 1288 studies were screened; 21 met our criteria,
 providing 243 effect sizes for meta-analysis. ### Files and variables ####
 File: UABioDataset.csv **Description:** This dataset compiles effect sizes
 from 21 studies (2000–2024) comparing biodiversity (e.g., arthropods,
 birds, plants) and ecosystem functions (e.g., climate regulation, soil
 conservation) in urban agriculture systems (e.g., collective gardens,
 individual plots) against two controls: *green infrastructure* (e.g.,
 parks, urban greenspaces) and *conventional rural farms*. Data were
 extracted following PRISMA guidelines and include geographic coordinates,
 taxonomic groups, measured outcomes (means, standard deviations, sample
 sizes), and effect directions (positive/negative). The dataset supports
 meta-analyses on how urban agriculture influences ecological communities
 and services globally. ##### Variables * Code: Unique identifier for each
 study. * Study_ID: Author-year reference code (e.g., `6_Wo` = Wo et al.,
 2022). * Reference: Full citation for the study. * Year: Publication year.
 * Lat, Long: Geographic coordinates of the study site. * Continent: Study
 location (e.g., Asia, Europe). * Topic: Focus on *Biodiversity* or
 *Ecosystem functions*. * Cat1: Specific category (e.g., *Arthropods*,
 *Climate Regulation*). * UAT: Urban agriculture type (e.g., *Collective
 Gardens*, *Commercial Farms*). * CWS: Control system: *Green
 Infrastructure* or *Conventional Farms*. * Ind_Effect: Direction of
 effect: `+` (positive), `-` (negative), or blank (neutral). * Mean_Exp:
 Mean values for experimental (urban agriculture) groups. * SD_Exp:
 Standard deviations for experimental groups. * SE_Exp: Standard errors for
 experimental groups (if SD not available). * SD2_Exp: SD for experimental
 groups computed using SE when SDs were not available in the original
 studies. * N_Exp: Sample sizes for experimental groups. * Mean_Control:
 Mean values for control groups. * SD_Control: Standard deviations for
 control groups. * SE_Control: Standard errors for control groups (if SD
 not available). * SD2_Control: SD for control groups computed using SE
 when SDs were not available in the original studies. * N_Control: Sample
 sizes for control groups. * ES_ID: Unique identifier for each effect size
 entry. **Explanation of NA Values in the Dataset** This dataset comes from
 a meta-analysis where: * Some studies reported **Standard Deviation
 (SD)**, which we converted to Standard Error (SE). * Other studies
 directly reported **SE** (when SD was unavailable). As a result: * The
 **SD column** has NA values where only SE was originally reported. * The
 **SE column** has NA values where only SD was originally reported (and
 later converted to SE). * These NA values are expected and reflect
 differences in how the source studies reported their data. ##
 Code/software All the analyses were performed in R statistical environment
 (r-project.org/; R version 4.3.0). Main packages used were metafor
 (v4.4-0) and emmeans (v1.10.2),