Abstract

Apple orchards constitute an important agro-ecosystem across Kashmir Himalayan Region (KHR), but estimates of their soil organic carbon (SOC) are unavailable. We investigated 174 apple orchards for estimating SOC spatial distribution across KHR at regional scale and evaluate accuracy of five interpolation methods. The selected orchards were representative of varied size, age, and management practices prevalent across KHR. Soil samples were collected from both tree rows and alleys between tree rows by digging pits at three depth intervals of 0–10; 10–20 and 20–30 cm. A total of 1044 soil samples were collected. The interpolation methods used included, ordinary kriging (OK), inverse distance weighing, empirical bayesian kriging, radial basis functions and local polynomial interpolation. Cross validation was used to assess the comparative performance of each method by measuring interpolation bias and accuracy. The soils were structurally less stony, with weak granular to moderate crumb at surface and sub-angular to angular blocky structure at sub-surface. The soils exhibited lowest co-efficient of variation for soil acidity and highest for soil electrical conductivity. With mean value of 12.33 ± 3.98 g kg⁻¹ on concentration basis and 48.45 Mg C ha⁻¹ on stock basis, the SOC declined with increasing soil depth, so much that near surface (0–10 cm) SOC content could explain well over 64% and 35% of second (20–30 cm) and third layer (20–30 cm) variation respectively. Exponential model best described SOC content across all depths. Semi-variograms of SOC at topsoil exhibited larger nugget effect while nugget sill ratios of 43% suggested moderate SOC spatial dependence. Cross validation exhibited better accuracy for OK in terms of indicating good match between observed and predicted SOC. This study exemplifies that apple orchards across KHR are significant carbon pool, improves our understanding of spatial distribution of SOC and help in evaluating soil health by providing site specific maps.

摘要

苹果园构成了克什米尔喜马拉雅地区 (KHR) 的重要农业生态系统，但无法对其土壤有机碳 (SOC) 进行估算。我们调查了 174 个苹果园，以估计区域尺度 KHR 的 SOC 空间分布，并评估五种插值方法的准确性。选定的果园代表了 KHR 中普遍存在的不同规模、年龄和管理实践。通过在 0-10 的三个深度间隔挖坑，从树行和树行之间的小巷收集土壤样品；10-20 和 20-30 厘米。共采集土壤样品 1044 个。使用的插值方法包括普通克里金法 (OK)、反距离加权、经验贝叶斯克里金法、径向基函数和局部多项式插值法。交叉验证用于通过测量插值偏差和准确性来评估每种方法的比较性能。土壤结构较少石质，表层为弱粒状至中等碎屑，次表层为亚角至角块状结构。土壤表现出最低的土壤酸度变异系数和最高的土壤电导率。平均值为 12.33 ± 3.98 g kg^-1基于浓度和 48.45 Mg C ha ^-1基于存量，SOC 随土壤深度的增加而下降，以至于近地表 (0-10 cm) SOC 含量可以很好地解释超过 64% 和 35% 的秒 (20 –30 cm) 和第三层 (20–30 cm) 分别变化。指数模型最好地描述了所有深度的 SOC 含量。表层土壤 SOC 的半变异函数表现出更大的金块效应，而 43% 的金块基台比率表明 SOC 空间依赖性中等。就指示观察到的和预测的 SOC 之间的良好匹配而言，交叉验证表现出更好的 OK 准确性。这项研究表明，KHR 的苹果园是重要的碳库，提高了我们对 SOC 空间分布的理解，并通过提供特定地点的地图帮助评估土壤健康。