Abstract

Agroforestry systems play an important role in sustainable agroecosystems. However, accurately and adequately quantifying the relationships between environmental factors and tree growth in these systems are still lacking. Objectives of this study were to quantify environmental factors affecting growth of four tree species and to develop functional soil maps (FSM) for each species in an agroforestry site. The diameter at breast height, absolute growth rate (AGR), and neighborhood competition index of 259 trees from four species (northern red oak [Quercus rubra], pecan [Carya illinoinensis], cottonwood [Populus deltoides], and sycamore [Platanus occidentalis]) were determined. A total of 51 topsoil samples were collected and analyzed, and 12 terrain attributes were derived from the digital elevation model. The relationships between AGR, soil, topography, and tree size were analyzed using Spearman correlation. Based on correlation analysis, FSM for each species were generated using the k-means cluster method by overlaying correlated soil and terrain attribute maps. Results showed tree size and terrain attributes were driving factors affecting tree growth rate relative to soil properties. The spatial variations in AGR among functional units were statistically compared within tree species and the areas with larger AGR were identified by the FSM. This study demonstrated that FSM could delineate areas with different AGR for the oak, cottonwood, and sycamore trees. The AGR of pecan trees did not vary among functional units. The generated FSM may allow land managers to more precisely establish and manage agroforestry systems.

Highlights

  • Agroforestry systems are being increasingly adopted in North America because of their advantages in improving economic incomes, wildlife diversity, carbon storage, and mitigation of regional climate change (Jose et al 2019)

  • This study demonstrated that functional soil maps (FSM) could delineate areas with different absolute growth rate (AGR) for the oak, cottonwood, and sycamore trees

  • The study area could be classified into the convergence flat bottom area, the middle steep slope area, and the upper flat area per the spatial distribution of indices of slope, multi-resolution ridge top fatness (MRRTF), and multi-resolution valley bottom flatness index (MRVBF)

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Summary

Introduction

Agroforestry systems are being increasingly adopted in North America because of their advantages in improving economic incomes, wildlife diversity, carbon storage, and mitigation of regional climate change (Jose et al 2019). The tree growth rate in any agroforestry system may be highly variable within the same species and among different species due to variability of multiple biotic and abiotic factors (Chamagne et al 2017; Stephenson et al 2014). Influences and interactions of biotic and abiotic factors may differ among soil type, tree species, and management. In small-scale areas where single or a limited number of tree species are planted, micro-topography variation has been found to strongly affect soil nutrient distribution, water distribution, and biological processes, which may influence variations in individual tree growth rates (Bassett 1964; Cavelier et al 2000; Kubler et al 2020; Rhoades 1996). Quantification of relationships among tree genetics, tree growth, soil variability, and soil-landscape features are needed to maximize efficiency in agroforestry systems

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