Volume 9, Number 2 (January 2022):3349-3358, doi:10.15243/jdmlm.2022.092.3349 ISSN: 2339-076X (p); 2502-2458 (e), www.jdmlm.ub.ac.id
Open Access 3349 Research Article
Assessing the distribution of total Fe, Cu, and Zn in tropical peat at an oil palm plantation and their relationship with several environmental factors
Heru Bagus Pulunggono1*, Lina Lathifah Nurazizah2, Moh Zulfajrin3, Syaiful Anwar1, Supiandi Sabiham1
1 Department of Soil Science and Land Resource, IPB University, Bogor 16680 Indonesia
2 Bachelor Program of Agronomy and Horticulture Department, IPB University, Bogor 16680 Indonesia
3 Bachelor Program of Soil Science and Land Resource Department, IPB University, Bogor 16680 Indonesia
*corresponding author: [email protected]
Abstract Article history:
Received 1 November 2021 Accepted 18 December 2021 Published 1 January 2022
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.
Keywords:
oil palm age peat micronutrients peat thickness season
tree and canal distances
To cite this article: Pulunggono, H.B., Nurazizah, L.L., Zulfajrin, M., Anwar, S. and Sabiham, S. 2022. Assessing the distribution of total Fe, Cu, and Zn in tropical peat at an oil palm plantation and their relationship with several environmental factors. Journal of Degraded and Mining Lands Management 9(2):3349-3358, doi:10.15243/jdmlm.2022.092.3349.
Introduction
Tropical peatlands occupy an area of about 13.4 million hectares (Mha) in Indonesia, contributing to about 7% of the national total land area and mostly distributed over the lowland area of Sumatera and Borneo Islands, whereas small parts are found
scattering in Papua and Sulawesi Islands (Anda et al., 2021). Peat is considered an important natural resource that has been allocated for future development in national and regional planning (Law et al., 2015; Sari et al., 2021). Due to the limited productive area of mineral soil, the large size of the peat area has been the
Open Access 3350 subject of extensive agricultural activities such as cash
crops cultivation (Könönen et al., 2015), rubber (Wakhid et al., 2017), and oil palm plantation (Miettinen et al., 2016; Dohong et al., 2017). However, despite the consideration as a fragile ecosystem (Saputra, 2019), tropical peatlands are linked to the global carbon cycle (Ribeiro et al., 2021). Peat comprises high organic material and contains lower micronutrients content, including Fe, Cu, and Zn (Abat et al., 2012). In order to achieve and maintain high productivity, as well as gain sustainable cultivation and mitigate land degradation, understanding the distributions of micronutrients in peat and their relationship with some environmental factors become an imminent necessity.
Iron (Fe), Copper (Cu), and Zinc (Zn) are the trace metal elements or micronutrients that play a broad role in the peatland system (Riedel et al., 2013;
Bhattacharyya et al., 2018; Zhang et al., 2020) and essential for higher plant including oil palm (Broeshart et al., 1957; Broadley et al., 2012; Corley and Tinker, 2016). Generally, micronutrient transformation and mobility in peat are mainly affected by organic acid, pH, Eh, temperature, and water content, which their values are governed by many environmental factors (Tipping et al., 2003; Jauhainen et al., 2014; Szajdak et al., 2020). Through these factors, several environmental factors such as oil palm age, site, depth, peat thickness, and seasonal change could indirectly influence the micronutrients distribution in peat (Könönen et al., 2015; Bhattacharyya et al., 2018;
Dhandapani et al., 2021).
Peat, especially on its surface, undergoes mineralization at a rapid rate after land clearing, planting, and drainage canal development (Kawahigashi and Sumida, 2006; Prananto et al., 2020). The release of available nutrients, including micronutrients of Fe, Cu, and Zn, to the peat solution was enhanced in the peat surface due to close contact with the atmosphere and lower water content, suggesting the possible variation of these nutrients at different depths. However, the mineralization rate becomes slower in the older oil palm plantation, reflecting the state of equilibria among peat compaction, groundwater table, and microclimate under dense canopy cover (Jauhainen et al., 2014), as well as the trade-off between dilution and enrichment process. The layer of organic matter in peat, which is thinner in the edge and oppositely thicker in the center at the peat dome, gave different effects for nutrient movement from mineral soil substratum (Watanabe et al. 2013). Rainfall change in each season affects the water table level in peat that governs the dilution process and nutrient transportation vertically and laterally (Marwanto et al., 2018). On the other hand, the bonding strength between Fe, Cu, and Zn with the organic matter was different, determining a more preferably complexed element over the other (Tipping and Hurley, 1992; Yonebayashi et al., 1994). Drainage canal development at oil palm plantation affects the
peat aeration (Othman et al., 2011; Miettinen et al., 2017), which leads to the transformation and mobilization of Fe, Cu, and Zn (Riedel et al., 2013;
Bhattacharyya et al., 2018; Zhao et al., 2019).
Unfortunately, the research conducted in peat, combining the environmental factors described above and clarifying its relationship with total Fe, Cu, and Zn, were found scarce. Unlike in the mineral soils, the available fraction of Fe, Cu, and Zn in peat occurs at a very limited amount compared to their unavailable fraction due to strong complexation by organic matter (Tipping and Hurley, 1992; Yonebayashi et al., 1994;
Abat et al., 2012).
From this perspective, the research for total micronutrients in peat representing their major portion is still relevant. Therefore, this study aimed to capture the general distribution of total Fe, Cu, and Zn in peat at the oil palm plantation and assess their relationship with several environmental factors, including oil palm age, peat thickness, seasonal change, distance from canal, distance from the oil palm tree and depth of sample collection. This finding may help to construct a better understanding of agronomic management in oil palm plantations.
Materials and Methods Peat sampling
This study was conducted from October 2017 to February 2018. The research site was an oil palm plantation cultivated at peat soil in Pangkalan Pisang, Koto Gasib, Siak, Riau, Indonesia. Peat samples were taken inside the block using a combination of six environmental factors, namely: 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) (Table 1). Peat Sampling was conducted compositely of four subsamples. The peat decomposition stage is comprised of hemic-sapric, having the bulk density of 0.10–0.18 g cm-3 (Pulunggono et al., 2019).
Laboratory measurement
Peat chemical analysis was carried out at the Soil Chemistry and Fertility Laboratory, Soil and Land Resources Department, Faculty of Agriculture, IPB University. Total micronutrient (Fe, Cu, Zn) determination using wet digestion extracted by 98%
H2SO4 and H2O2 (USDA 2004). Furthermore, the samples were sieved and stirred. The final solution was then measured by AAS (Atomic Absorption Spectrophotometer) Shimadzu AA-6300.
Statistical analyses
Statistical analyses were performed using Microsoft Excel and Minitab.
Open Access 3351 Table 1. Transect location that represent oil palm age in different peat thickness.
Block Oil Palm Age (year) Peat Thickness (m) Coordinate
L7 – I Oil Palm < 6 <3 N 0.74025°, E 101.76818°
L7 – II Oil Palm < 6 >3 N 0.74069°, E 101.76787°
K19 Oil Palm 6 – 15 <3 N 0.73271°, E 101.76559°
K23 Oil Palm > 15 >3 N 0.72609°, E 101.75919°
K24 Oil Palm > 15 <3 N 0.77256°, E 101.75771°
K25 Oil Palm 6 - 15 >3 N 0.72581°, E 101.74564°
Figure 1. The layout of the sampling collection.
All environmental factors combination of Fe, Cu, and Zn datasets resulted in 864 data for each element.
Outliers were removed; moreover, the square root (sqrt) transformation was employed to the datasets until their distribution approached the normal curve, reducing the datasets to 582, 565, and 603 data, respectively. The differences of total Fe, Cu, and Zn were assessed using linear mixed effect models with restricted maximum likelihood (REML). Oil palm age, season, peat thickness, and distance from the canal were assigned as fixed effects. Meanwhile, distances from the oil palm tree and sampling depth were incorporated as random effects.
The relationship between total Fe, Cu, and Zn with five selected factors was assessed by applying Pearson correlation and backward elimination stepwise for multiple regression (BESR) analyses. We excluded categorical data (i.e., oil palm age, peat thickness, and season) in correlation analysis due to the limitation of mathematical calculation in the equation, which specified all parameters presented as numerical data types. To obtain regression equations based on all parameters in BESR, we incorporated entire data as categorical effects. Owing to high variability in our datasets, P-value selection becomes arbitrary. Based on that, we modified model selection criteria in BESR, which were included the R2, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) into consideration. The first only concerns the goodness of fits, whereas both the latter deal with the trade-off between model fit and complexity. Hence, we thoroughly selected the model
not only possessed a lower P-value, but also gained higher R2 and lower AICc-BIC.
In order to gather more information regarding the total Fe, Cu, and Zn in peat, we were tried to compare the multiple regression/BESR with the multivariate method. Principal component analysis (PCA) based on a correlation matrix was selected to assess which underlying environmental factor governing total Fe, Cu, and Zn and determine the grouping between the environmental factors that cannot be significantly separated by REML.
Results and Discussion
Spatiotemporal micronutrient distribution
The concentration of total micronutrients in peat according to oil palm age, peat thickness, season, distances from drainage canal, distances from the oil palm tree, and the depth of sample collection is presented in Figure 1. Total Fe had the highest concentration in peat compared to other micronutrients analyzed in this study, which accounted for 20 times of total Zn and 90 times of total Cu. The total Fe, Cu, and Zn recorded in this study were in the common range of peat soil reported by previous researchers (i.e., Lucas 1982; Ambak et al., 1991; Abat et al., 2012;
Dhandapani et al., 2018; Nelvia 2018; Hashim et al., 2019; Dhandapani et al., 2021). Total Fe, Cu, and Zn distribution were strongly influenced by their age, peat thickness, and distance from the canal. Meanwhile, total Cu and Zn were also governed by seasonal change. The entire total micronutrients exhibited no
Open Access 3352 significant differences within the depth of sample
collection and distance from the oil palm tree. A clearly high amount of total Fe and Cu were found in
>3 m thickness; meanwhile, the total Zn showed an opposite trend. These contrasting findings with previous studies (Watanabe et al., 2013) are caused
possibly by the inclusion of mineral soil contaminant from harvest path and collection road, lateral mobilization from decomposed pruned frond, or micro-site accumulation from inorganic fertilizer and amendment (Mermut et al., 1996; McBride and Spiers, 2001; Yusuyin et al., 2016).
Figure 2. The distribution of total Fe, Cu and Zn in peat according to six selected factors. (a) oil palm age, (b) peat thickness, (c) season, (d) distance from canal, (e) distance from oil palm tree, and
(f) depth of sample collection.
It has been recognized that the nutrient requirement of the oil palm tree is increasing since the increase of its flowering and fruiting capability (Corley and Tinker, 2016). This study found a statistically higher amount of total Fe and Zn in peat cultivated by the younger oil palm tree (<6 years old) compared to the older. This partially indicated that the oil palm tree constantly
absorbs a considerable amount of Fe and Zn after it reaches its productive age.
We marked higher content of total Zn in peat collected during the dry season than the rainy season.
Total Fe exhibited a similar pattern with Zn; however, no statistical difference was found (P>0.05). As stated before, total Fe, Cu, and Zn showed no significant 0
50 100 150 200 250
5 12 16
Concentration (ppm)
Oil Palm Age (Year)
Fe x7 Cu
0 50 100 150 200 250
<3 >3
Peat Thickness (m)
Concentration (ppm) Fe x7 Cu Zn
0 50 100 150 200
1 2 3 4
Concentration (ppm)
Distance from Oil Palm Tree (m)
Fe x7 Cu Zn
-80 -65 -50 -35 -20 -5
0 50 100 150 200
Depth of sample collection (cm)
Concentration (ppm)
Fe x7 Cu Zn
0 50 100 150 200 250
Rainy Dry
Season
Concentration (ppm)
Fe x7 Cu
0 50 100 150 200
10 25 50 75 100 150
Concentration (ppm)
Distance from Canal (m)
Fe x7 Cu Zn
(a) (b)
(c) (d)
(e) (f)
Open Access 3353 differences within the random effects. The depth of
sample collection also had negligible effects on the difference of all micronutrients. This suggests the trade-off between dilution against enrichment process due to excessive water during the rainy season, particularly for Fe and Zn, highlighting the dominance of the dilution process over the latter. Through the column experiment, Miyamoto et al. (2013) found that Fe, Cu, and Zn can be leached out from the peat with varying availability states, both in the dry and rainy seasons. Furthermore, strong dilution evidence was found by Gandois et al. (2020), quantifying higher micronutrients in blackwater and drainage canals originating from drained (and some cultivated) peatland areas compared to whitewater. This indicates that continuous leaching within an extended period (6–
15 and >15 years) also contributes to significant
micronutrients losses (Table 2; oil palm age; P<0.001) in our study site.
Relationship between total Fe, Cu, and Zn with the six selected factors
The Pearson correlation among distance from canal, distance from the oil palm tree, and the depth of sample collection with total Fe, Cu, and Zn, shown in Table 3.
All factors exhibited no significant relationships with Fe. Total Cu was significantly increased along with the distance from the canal and deepening of sample collection. However, the increase of the distance from oil palm trees significantly decreased total Zn. The significance of the weak correlation between total Fe, Cu, and Zn with the entire factors recorded in this study is possibly due to the high variance of the large datasets included in the correlation.
Table 2. Linear mixed models with restricted maximum likelihood (REML) showing statistically significant (bold value:P<0.05) differences of total Fe, Cu, and Zn among many environmental factors.
Factors Sqrt Fe (N=582) Sqrt Cu (N=565) Sqrt Zn (N=603)
Fixed Effects
Oil Palm Age F=25.33; P<0.001 F=32.35; P<0.001 F=9.15; P<0.001
Season F=0.00; P=0.961 F=6.57; P=0.011 F=5.20; P=0.023
Peat Thickness F=25.43; P<0.001 F=115.79; P<0.001 F=13.65; P<0.001
Distance from Canal F=2.39; P=0.036 F=3.30; P=0.006 F=2.54; P=0.027
Random Effects
Depth of Sample Collection Z=0.08; P=0.469 Z=0.89; P=0.186 Z=0.86; P=0.196 Distance From Oil Palm Tree Z=0.44; P=0.329 Z=0.69; P=0.245 Z=1.15; P=0.125 Accuracies
R2 14.29% 31.27% 16.16%
AICc 3988.05 1494.12 2338.22
BIC 4001.06 1507.04 2351.34
Table 3. Pearson correlation (Rp) between distance from canal, distance from the oil palm tree, and depth of sample collection with total Fe, Cu, and Zn; supplemented with a coefficient of variation for the corresponding variable
Factors Total Fe Total Cu Total Zn
Rp cv Rp cv Rp cv
Distance From Canal -0.06
71.86
0.15
78.28
-0.07
59.96
Distance From Oil Palm Tree 0.02 0.06 -0.26
Depth of Sample Collection -0.01 0.21 0.13
Note: bold values indicate statistically significance.
Modified backward elimination stepwise for multiple regression/BESR (Table 4) showed that the oil palm age, peat thickness, and distance from canal were the common factors governing total Fe, Cu, and Zn in peat significantly. Moreover, total Cu and Zn were also dictated by the season and depth of sample collection.
Fe and Cu tended to increase along with the increase of the distance from the oil palm tree (P>0.05), whereas Zn exhibited an oppositely notable relationship (P<0.001). Due to the dilution and
concentration processes (Marwanto et al., 2018), there is an opportunity for micronutrient leaching in the rainy season. Adequate amounts of H+ from humic substances (Husni et al., 1995) coupled with root’s originates (Hinsinger et al., 2003) generate an acidic condition in peat. This condition thereby increased micronutrients availability (Abat et al., 2012), albeit the process was reduced by strong chelation of soil organic complexes (Tipping and Hurley, 1992;
Yonebayashi et al., 1994). Gandois et al. (2020)
Open Access 3354 suggested that weathering of mineral soil material
during peat accumulation processes enriched Fe in peat. Colloidal association of Fe, Al, and dissolved organic matter control other micronutrients (including Cu and Zn) and their transportation across peat- draining water. Dhandapani et al. (2021) found that total Zn was affected significantly by seasonal
differences; meanwhile, the interaction between season and site showed remarkable influence on total Cu. We did not find any interaction between predictors (included different micro-site in oil palm plantation and season) in REML; however, by analyzing BESR (Figure 3), our study agreed with the first of their results not only total Zn but also in total Cu.
Table 4. Modified backward elimination stepwise for multiple regression (BESR) of Fe, Cu, and Zn.
Sqrt Fe Sqrt Cu Sqrt Zn
Coeficients P Coeficients P Coeficients P
Constant 25.27 1.045 6.251
Determinants
Age -5.541 <0.001 0.7012 <0.001 -0.733 <0.001
Thick 3.145 <0.001 0.7977 <0.001 -0.501 <0.001
Season 0.1867 0.012 -0.304 0.023
Canal -3.110 0.037 0.3870 0.006 -0.399 0.025
Tree 1.061 0.199 0.1610 0.076 -1.256 <0.001
Depth 0.3806 <0.001 0.569 0.001
Accuracies
R2 14.52%
4007.52 4063.64
31.45% 16.23%
AICc 1469.65 2320.27
BIC 1538.04 2389.78
Note: Age represents oil palm age (year), Thick represents peat thickness (m), Canal represents the distance to drainage canal (m), Tree represents the distance to the oil palm tree (m), and depth represents sampling depth (cm).
Table 5. The PCA variance and correlation matrix for Fe, Cu, and Zn datasets.
Component PC1 PC2 PC3 PC4
Total Fe Datasets
Eigenvalue 1.066 1.013 0.987 0.934
Proportion 0.267 0.253 0.247 0.233
Cumulative 0.267 0.520 0.767 1.000
Eigenvectors Variable/Component Loadings Correlation
Canal 0.535 -0.536 -0.322 -0.568
Tree -0.147 -0.778 0.535 0.293
Depth 0.446 0.324 0.770 -0.321
sqrt Fe -0.702 -0.040 0.132 -0.699
Total Cu Datasets
Eigenvalue 1.233 1.024 0.982 0.761
Proportion 0.308 0.256 0.246 0.190
Cumulative 0.308 0.564 0.810 1.000
Eigenvectors Variable/Component Loadings Correlation
Canal 0.386 -0.707 -0.411 0.428
Tree 0.153 0.608 -0.768 0.128
Depth 0.567 0.360 0.491 0.555
sqrt Cu 0.711 -0.035 -0.003 -0.702
Total Zn Datasets
Eigenvalue 1.276 1.025 0.999 0.701
Proportion 0.319 0.256 0.250 0.175
Cumulative 0.319 0.575 0.825 1.000
Eigenvectors Variable/Component Loadings Correlation
Canal -0.134 -0.673 -0.691 -0.227
Tree -0.632 0.450 -0.111 -0.621
Depth 0.254 0.583 -0.714 0.292
sqrt Zn 0.719 0.064 0.026 -0.691
Open Access 3355 The result of principal component analysis (PCA) for
total Fe, Cu, and Zn were presented in Figure 3 and Table 5. The PCA revealed two main gradients; both possess eigenvalue more than 1 and explain the total variation of around 52 to 57 % of these micronutrients.
All of the micronutrients observed in this study correlated with PC1. PC2 was significantly correlated with the distance from the oil palm tree in the total Fe dataset, whereas having strong correlations with the distance from canal both in Cu and Zn datasets. PC3 was highly correlated with the depth of sample collection in Fe and Zn datasets. Meanwhile, similar PC’ was chiefly correlated with the distance from the oil palm tree in the Cu dataset. Based on PC1 and PC2 (plotted as X and Y axis, respectively), total Fe had a strong negative correlation with the depth of sample
collection. However, a contrary result was observed on total Cu. Total Zn showed a significant correlation with the distance from oil palm tree; meanwhile, relatively low relationships were observed to other variables. Score plots in Figures 3a, 3c, and 3e demonstrated the examples of possible grouping based on the distance from the oil palm tree. Our visual interpretation denoted that the entire total micronutrients can be determined into two groups.
PC2 separated most of the total Fe and Cu collected at 2 m from the oil palm tree from a farther distance.
Meanwhile, similar distance separation in total Zn was done diagonally. These categorizations were probably due to the density of feeding roots concentrated within 1 to 2 meters from the oil palm tree (Harianti et al., 2017).
Figure 3. Score plots showing relatively regular patterns and grouping (red circles) of total Fe (above: a, b), Cu (middle: c, d), and Zn (bottom: e, f) based on visual interpretation; separating the distance from the oil palm tree
(left: a, c, and e) and depth of sample collection (right: b, d, and f).
(a) (b)
(c) (d)
(e) (f)
Open Access 3356 The abundance of feeding root (considered as
quarternary root) was also different along with the depth from the peat surface, accumulating primarily at 0–15 cm depth (Sabiham et al., 2014). Yonebayashi et al. (1994) found that all of the micronutrients observed in this study were concentrated at peat surface (0 – 30 cm). The previous reports are in agreement with the visual separation shown in Figures 3b, 3d, and 3f. All total micronutrients were categorized diagonally into two groups, separating the observation in 0–20 cm from the deeper depth. The categorization based on PCA’s visual separation can become the solution after the REML (Table 2) or BESR (Table 4) tests were gained poor performance. From an agronomic perspective, both groupings among the distance from the oil palm tree and the depth of sample collection indicated the possible fertilization site. Micronutrient fertilization can be done inside a 2 m circle and inserted at 0-20 cm.
Conclusion
This research demonstrated the importance of studying soil micronutrients distribution and its relation with several environmental factors in oil palm plantations cultivated at tropical peatland. A statistically different total Fe, Cu, and Zn were determined by oil palm age, peat thickness, and distance from the canal. Total Cu and Zn were also significantly different at each season.
The age of the oil palm, peat thickness, and distance from the canal were the common factors controlling total Fe, Cu, and Zn in peat. Moreover, total Cu and Zn were also dictated by season, distance from the oil palm tree, and depth of sample collection. All micronutrients were categorized into two groups based on PCA, separated by 2 m distance from oil palm tree and 20 cm depth from the soil surface. Despite the strong chelation by soil organic complexes, there is an opportunity for micronutrients dilution and leaching process, particularly under an extended cultivation time. Further research is needed to formulate micronutrients fertilization, especially for matured oil palm plantations.
Acknowledgements
The authors would like to thank GAPKI (Indonesian Palm Oil Association) for their financial and technical support during the research.
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