A global database to catalogue the impacts of agricultural management practices on terrestrial biodiversity.
Abundance
Agriculture
Biomass
Land-management practices
Meta-analysis
Richness
Taxonomic groups
Journal
Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
03
02
2023
revised:
04
09
2023
accepted:
04
09
2023
medline:
27
9
2023
pubmed:
27
9
2023
entrez:
27
9
2023
Statut:
epublish
Résumé
Habitat loss and degradation due to global agriculture land use is a major threat to biodiversity. Identifying agricultural management practices that mitigate these impacts is urgently needed. Thousands of experiments have been conducted worldwide in the last decades to compare the impacts of various agricultural management practices on biodiversity. The magnitudes of difference in biodiversity responses between pairs of agricultural practices, i.e. effect sizes, have now been synthesised in a growing number of meta-analyses. Yet, each meta-analysis generally focuses on a specific type of farming practice and on specific taxonomic groups, or a single region. Meta-analyses could furthermore yield different or sometimes opposite results for the similar research questions. Gathering all the effect sizes in one single dataset helps to critically assess and weigh the available evidence across all studied practices, taxonomic groups and geographical areas, and provide stakeholders a solid base to better inform their decisions. Here, we present a comprehensive dataset of 200 published meta-analyses gathering 1885 effect sizes based on more than 14 000 primary studies. We detail the effect of 8 main individual field practices (e.g. pest and disease management, amendment and fertilisation), 3 agricultural systems (e.g. organic farming, conservation agriculture) and 2 landscape level interventions (i.e. landscape complexity, land-use change). Our dataset covers numerous taxonomic groups over 14 phyla, including animals (e.g. birds, insects), microorganisms (e.g. fungi, bacteria), plants (e.g. trees, weeds). The dataset presented provides a resource to support decision-makers, farmers, and conservation ecologists alike for managing agricultural land for biodiversity.
Identifiants
pubmed: 37753256
doi: 10.1016/j.dib.2023.109555
pii: S2352-3409(23)00655-8
pmc: PMC10518681
doi:
Types de publication
Journal Article
Langues
eng
Pagination
109555Informations de copyright
© 2023 Published by Elsevier Inc.
Références
Biochem Med (Zagreb). 2012;22(3):276-82
pubmed: 23092060
BMJ. 2021 Mar 29;372:n71
pubmed: 33782057
Methods Protoc. 2021 Jan 14;4(1):
pubmed: 33466759
Glob Chang Biol. 2021 Oct;27(19):4697-4710
pubmed: 34114719
ACP J Club. 1995 Nov-Dec;123(3):A12-3
pubmed: 7582737
Sci Data. 2022 May 24;9(1):228
pubmed: 35610235
PLoS One. 2015 Sep 17;10(9):e0138237
pubmed: 26379270
Res Synth Methods. 2019 Dec;10(4):606-614
pubmed: 31355546