Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands

Author:

Ylagan Shane1,Brye Kristofor R.1,Ashworth Amanda J.2,Owens Phillip R.2,Smith Harrison1,Poncet Aurelie M.1,Sauer Tom J.2,Thomas Andrew L.3

Affiliation:

1. University of Arkansas

2. USDA-ARS

3. University of Missouri

Abstract

Abstract Minimal research has been conducted relating apparent electrical conductivity (ECa) surveys to plant and terrain properties in agroforestry systems. Objectives were to identify i) ECa survey relationships with forage yield, tree growth, and terrain attribute within ECa-derived soil management zones (SMZs) and ii) terrain attributes that drive ECa variability within a 20-year-old, 4.25-ha, agroforestry system in the Ozark Highlands of northwest Arkansas. The average of 12 monthly perpendicular (PRP) and horizontal coplanar (HCP) ECa surveys (August 2020 to July 2021) and 14 terrain attributes were obtained. Tree diameter at breast height (DBH) and height (TH) measurements were made in December 2020 and March 2021, respectively, and forage yield samples were collected during Summer 2018 and 2019. Apparent EC-tree property relationships were generally stronger within the whole site (averaged across tree property and ECa configuration, |r| = 0.38) than within the SMZs (averaged across tree property, ECa configuration, and SMZ, |r| = 0.27). The strength of the SMZs’ terrain-attribute-PRP-ECa relationships were 9 to 205% greater than that for the whole site. In whole-site, multi-linear regressions, Slope Length and Steepness Factor (10.5%), Mid-slope (9.4%), and Valley Depth (7.2%) had the greatest influence (i.e., percent of total sum of squares) on PRP ECa variability, whereas Valley Depth (15.3%), Wetness Index (11.9%), and Mid-slope (11.2%) had the greatest influence on HCP ECa variability. Results show how ECa relates to plant (i.e., DBH, TH, and forage yield) and terrain data within SMZs in agroforestry systems with varying topography and could be used to precisely manage agroforestry systems.

Publisher

Research Square Platform LLC

Reference35 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3