Path dependencies in US agriculture: Regional factors of diversification

Path dependencies in US agriculture: Regional factors of diversification
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美国农业的路径依赖:多样化的区域因素

DOI:
10.1016/j.agee.2022.107957
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发表时间:
2022
期刊:
Ecosystems & Environment
影响因子:
--
通讯作者:
Burchfield, Emily K.
Burchfield, Emily K.
中科院分区:
--
文献类型:
--
作者:
Spangler, Kaitlyn;Schumacher, Britta L.;Bean, Brennan;Burchfield, Emily K.

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对美国农业中农业生物多样性下降和不断扩大的社会经济不平等的关切突出了系统变革的迫切需要。尽管越来越多的证据表明农业系统多样化的田野和景观规模的好处,但美国农业的路径依赖对这种多样化路径构成了障碍。这项研究旨在通过两个主要的研究问题来阐明农业景观的路径依赖关系,这些因素通过两个主要的研究问题在区域范围内激励作物多样化:1)什么是最能预测美国农业多样性的生物物理和社会生态因素;2)这些因素在地区上是如何变化的?使用由几个开源数据库构建的一个新的面板数据集,我们使用随机森林(RF)排列变量重要性度量来识别和比较美国九个地区最能预测县级作物多样性的因素。我们的结果表明,气候、土地利用标准和农业投入一直是预测区域间农业多样性的最重要类别;然而,这些类别中变量的相对区域重要性存在变异性。因此,最强烈地预测美国各地农业多样性的因素在地区层面上起着明显的作用,强调需要考虑多个影响尺度。这些不同的区域关系造成了路径依赖,阻碍了加强农业多样性。通过更恰当地解决制约农业多样化的美国农业景观的区域因素,着眼于未来的作物景观,我们可以将目前的路径依赖转向更具弹性和适应性的美国农业未来。
Concerns of declining agrobiodiversity and widening socioeconomic inequities in United States (US) agriculture highlight the critical need for systemic change. Despite surmounting evidence of the field and landscape scale benefits of diversifying agricultural systems, path dependencies of US agriculture present barriers to such diversification pathways. This study aims to elucidate path dependencies of agricultural landscapes that (dis)incentivize crop diversification at the regional scale through two main research questions: 1) what are the biophysical and socioecological factors most predictive of agricultural diversity across the US; and 2) how do these factors vary regionally? Using a novel panel dataset constructed from several open-source databases, we use random forest (RF) permutation variable importance measures to identify and compare the factors most predictive of county-level crop diversity across nine US regions. Our results show that climate, land use norms, and farm inputs are consistently the most important categories for predicting agricultural diversity across regions; however, variability exists in the relative regional importance of variables within these categories. Thus, factors most strongly predictive of agricultural diversity across US landscapes operate distinctly at a regional level, emphasizing the need to consider multiple scales of influence. These distinct regional relationships contribute to path dependencies that present resistance to enhancing agricultural diversity. By more appropriately addressing the regional factors of US agricultural landscapes the constrain agricultural diversification, with an eye towards future cropscapes, we can shift current path dependencies toward a more resilient and adaptive US agricultural future.
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