Assessing the distribution of total Fe, Cu, and Zn in tropical peat at an oil palm plantation and their relationship with several environmental factors

Abstract

Extensive utilization of fragile tropical peatlands ecosystem encourages a better understanding of spatiotemporal micronutrients distribution. The distribution of total Fe, Cu, and Zn in peat and their relationship with environmental factors were studied under oil palm plantation, Pangkalan Pisang, Koto Gasib, Riau, Indonesia. Peat samples were taken compositely inside the block using a combination of six factors, including a) the oil palm age (<6, 6-15, >15 years old), b) the peat thickness (< 3 and >3 m), c) season (rainy and dry), d) the distances from the secondary canal (10, 25, 50, 75, 100, and 150 m), e) the distances from an oil palm tree (1, 2, 3, and 4 m), and f) the depth of sample collection (0-20, 20-40, and 40-70 cm from the peat surface). Total Fe, Cu, and Zn were determined by the wet digestion method. These micronutrients observed in this study possessed high variability; however, they were within the expected range in tropical peatland. The entire micronutrients were statistically different by oil palm age, peat thickness, and distance from canal. Meanwhile, total Cu and Zn were also significantly different at each season. The oil palm age, peat thickness, and distance from the canal were the common factors controlling total Fe, Cu, and Zn in peat significantly. Moreover, total Cu and Zn were also dictated by season, distance from the oil palm tree, and depth of sample collection. Based on visual interpretation in PCA (principal component analysis), all micronutrients were categorized into two groups, separated by 2 m distance from the oil palm tree and 20 cm depth from the soil surface. Our study also highlights the dominance of the dilution over the enrichment process in peat, which requires further research to formulate micronutrients fertilization, especially for an extended cultivation time.

Prediction and Interpretation of Total N and Its Key Drivers in Cultivated Tropical Peat using Machine Learning and Game Theory

“…The results of the peat chemical analyses were summarized in Figure 3, distinguishing between the training and validation datasets. The figures revealed that the chemical variables in both datasets fell within the typical range observed in tropical peat, as reported by previous researchers (e.g., Adeolu et al 2018;Dhandapani et al 2021;Harianti et al 2018;Hashim et al 2019;Pulunggono et al 2022b;Sangok et al 2017). However, the recorded total Fe in this study was three times lower than that observed by Dhandapani et al (2020) in similar land use.…”

“…A single block (around 30 hectares) is usually established as the smallest sampling unit for OPP management. Nevertheless, previous research highlighted the spatiotemporal variability of peat nutrients at sub-block scales, along with the gradients of the distance from the oil palm tree, canal and mineral soil border, peat thickness, sampling depth, oil palm age, season, and land use (Pulunggono et al 2016;Pulunggono 2019;Pulunggono 2020;Pulunggono 2021;Pulunggono 2022a;Pulunggono 2022b). Soil samples must be collected enormously to satisfy the sampling design for this detailed approach, especially for large-scale OPP.…”

Identifying the Underlying Factors and Variables Governing Macronutrients in Cultivated Tropical Peatland Using Regression Tree Approach

“…The complexity of the problems of the linear approach was also exacerbated by the variability of nutrient concentrations and characteristics in the spatial perspective, both laterally and vertically, as affected by management zonation at the block level (Nelson et al, 2015;Pulunggono et al, 2022a). Specific zone or microsite occurs on OP plantation following best management practices/BMP (RSPO, 2012).…”