DOI: 10.5683/sp3/ly6d5q
title: Joint environmental and social benefits from diversified agriculture

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p&gt;Agricultural simplification continues to expand at the expense of more diverse forms of agriculture. This simplification in the form of, for example, intensively-managed monocultures, poses a risk to keeping the world within safe and just Earth system boundaries. Here, we estimate how agricultural diversification simultaneously affects social and environmental outcomes. Drawing from 24 studies in 11 countries across 2,655 farms, we show how five diversification strategies focusing on livestock, crops, soils, non-crop plantings, and water conservation benefit social (human well-being, yields, food security) and environmental (biodiversity, ecosystem services, reduced environmental externalities) outcomes. We find that applying multiple diversification strategies creates more positive outcomes than individual management strategies alone. To realize these benefits, well-designed policies are needed to incentivize the adoption of multiple diversification strategies in unison.&lt;/p&gt;
description: &lt;b&gt;Methods&lt;/b&gt;&lt;br /&gt;&lt;p class="MsoNormal" style="margin-bottom:6.0pt;text-align:justify;"&gt;&lt;span lang="EN-US"&gt;As a first step to identify relevant datasets, participants of the SESYNC working group ‘Can Enhancing Diversity Help Scale Up Agriculture's Benefits to People and the Environment?’ were identified who had studied farm sites with varying levels of diversification in different parts of the world. Our goal was to encompass a wide range of farming systems across geographic latitudes, from subsistence to commercial farming, while also considering the geophysical landscape context of agricultural diversification outcomes. As a second step to obtain a sufficient representation of various geographic regions as well as types of agricultural diversification strategies, the group identified additional data contributors with relevant datasets (done through a broader solicitation request for data) as potential collaborators.&lt;/span&gt;&lt;/p&gt;
&lt;p class="MsoNormal" style="margin-bottom:6.0pt;text-align:justify;"&gt;&lt;span lang="EN-US"&gt;We had three inclusion criteria for datasets. That is, datasets should have recorded at least:  1) one agricultural diversification practice, while also including control study sites without or with less diversification, 2) one environmental outcome variable, and 3) one social outcome variable. We compiled 24 datasets that cover 11 countries from 5 world regions: Brazil (5); Malawi (3); Costa Rica (2); Ethiopia (2); Germany (2); Bolivia (1); Canada (1); Colombia (1); USA (5); Ghana (1); and Indonesia (1).&lt;/span&gt;&lt;/p&gt;
description: &lt;b&gt;Usage notes&lt;/b&gt;&lt;br /&gt;&lt;p&gt;The raw data file is .xlsx and the compound variables and other constructed variables are in a CSV file.  All data processing and statistical analyses were performed using R software.&lt;/p&gt;
description: <b>Dryad version number:</b> 8
<b>Version status:</b> submitted
<b>Dryad curation status:</b> Published
<b>Sharing link:</b> http://datadryad.org/stash/dataset/doi:10.5061/dryad.1zcrjdfxw
<b>Storage size:</b> 1712876
<b>Visibility:</b> public