Nutrient and trace element concentrations influence greenhouse gas emissions from Malaysian tropical peatlands

Abstract

Tropical peatlands are unique and globally important ecosystems for carbon storage that are generally considered nutrient poor. However, different nutrient and trace element concentrations in these complex ecosystems and their interactions with carbon emissions are largely unknown. The objective of this research was to explore the concentrations of macro‐ and micronutrients and othertrace elements in surface peats, and their relationship with greenhouse gas emissions in North Selangor peatlands subjected to different land use. All nutrient and trace element concentrations except chromium exhibited significant differences between sites. Most macronutrients and some micronutrients showed significant differences between seasons, typically with a reduction over time from wet to dry seasons, possibly due to leaching. CO2 emissions were positively related to organic matter content and manganese concentrations and negatively correlated with selenium. CH4 emissions were positively correlated with organic matter content, manganese, copper, barium, cobalt and aluminium, and negatively correlated with molybdenum, selenium, lithium and vanadium. This research has detected loss of essential nutrients over time, aiding to increase nutrient limitation in tropical peatlands due to drainage. The observed significant correlation between trace elements and greenhouse gas emissions strengthens the importance of including trace element analyses in understanding the biogeochemical functions of these understudied peatlands.

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

“…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.…”

“…Colloidal association of Fe, Al, and dissolved organic matter control other micronutrients (including Cu and Zn) and their transportation across peatdraining 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.…”

“…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).…”

Seasonal litter contribution to total peat respiration from drained tropical peat under mature oil palm plantation

“…In order to capture specific role between CO2 flux with environmental variables, many recurrent reports developed more sophisticated statistical models, e.g. hierarchical Bayesian regression (Ishikura et al, 2017), machine learning tree regression (Meiling et al, 2005), Gaussian linear mixed effect models (Manning et al, 2019), and backward elimination stepwise regression (Dhandapani et al, 2020) to predict CO2 flux in tropical peatland. Nevertheless, besides only focusing on describing Rt, Rp, and Rl, this paper preserves linear regression (LR and MLR) and correlation (Rp and Rs) to initially explain the general relationship between CO2 flux and other environmental variables.…”

Sustainable soil management and climate change mitigation

“…A study in the UK showed that grassland CO 2 emissions were positively correlated with clay content (Miller et al., 2020). Trace elements such as manganese and selenium were found to affect CO 2 and CH 4 emissions in tropical peatland (Dhandapani et al., 2021).…”