Temperature Effect Investigation toward Peat Surface CO2 Emissions by Planting Leguminous Cover Crops in Oil Palm Plantations in West Kalimantan

Arifin, Arifin; Suntoro, Suntoro; Wongso,; Atmojo,; Prabang,; Setyono,; Widyatmani,; Sih,; Dewi,

doi:10.17265/2161-6264/2015.03b.002

Cited by 5 publications

(7 citation statements)

References 21 publications

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“…In contrast, in Sabaju the harvest path had significantly higher R tot than the frond pile and cover plants. These differences in R tot among microforms are noteworthy because few other studies consider the effects of surface management practices on R tot , with the exception of work by Arifin et al (2015), who also found that R tot was significantly lower when measured from beneath cover plants than from the harvest path. These differences in R tot among microforms are significant because they have direct bearing not only predicting and upscaling land-atmosphere fluxes, but also because they provide insight into how soil surface management practices are affecting soil CO 2 and CH 4 dynamics.…”

Section: Carbon Fluxes Vary Spatially In Managed Tropical Peatlandsmentioning

confidence: 89%

Carbon Emissions From Oil Palm Plantations on Peat Soil

Manning

Kho

Hill

et al. 2019

Front. For. Glob. Change

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Southeast Asian peatlands have undergone recent land use change with an increase in industrial agricultural plantations, including oil palm. Cultivating peatlands requires creating drainage ditches and other surface microforms (i.e., harvest paths, frond piles, cover plants, and next to the palm). However, it is currently unclear how these management actions affect rates of carbon losses from the peat. Here we report carbon fluxes from each of the different surface microforms measured monthly (soil CO 2 [total soil respiration-R tot ] and stem CH 4) and bimonthly (soil CH 4 , drain CO 2 and drain CH 4). We calculated annual carbon fluxes and partitioned heterotrophic (R h) and root-rhizosphere respiration by sampling rhizosphere and root-free soil. Linear mixed effect models were used to determine which environmental factors best-predicted carbon fluxes, and to develop recommendations for management solutions that could reduce carbon losses. Carbon fluxes varied significantly between the different microforms; the greatest CO 2 fluxes were measured next to the palm and the greatest CH 4 fluxes were measured from the drainage ditches. Annual estimates of R tot , R h and drain CO 2 were 22.08 ± 0.50, 17.75 ± 1.54, and 1.5 ± 0.10 Mg CO 2-C ha −1 yr −1 , respectively. R h varied between the two plantations: Sebungan averaged 11.43 ± 1.37 Mg CO 2-C ha −1 yr −1 and Sabaju averaged 24.08 ± 1.42 Mg CO 2-C ha −1 yr −1. Net ecosystem CH 4 fluxes averaged 61.02 ± 17.78 kg CH 4-C ha −1 yr −1-similar to unmanaged swamp forests. The two plantations did not vary in overall CH 4 flux, but did vary in transport pathway. CH 4 fluxes from the soil, drains and stems followed a ratio of 50:50:0 from Sabaju (water table depth [WTD]: −0.49 ± 0.004 m) and 11:98:0 from Sebungan (WTD: −0.77 ± 0.007 m). R h dominated the peat carbon losses. WTD controlled variation in R h from Sebungan where the WTD was deeper. Air and soil temperature controlled variation in Sabaju, with greater fluxes from the harvest path, attributed to the absence of shade. These results suggest that shading the soil (e.g., through addition of frond piles) and raising the water table may be the most effective ways to reduce peat carbon loss from drained peat soils.

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Section: Carbon Fluxes Vary Spatially In Managed Tropical Peatlandsmentioning

confidence: 89%

Carbon Emissions From Oil Palm Plantations on Peat Soil

Manning

Kho

Hill

et al. 2019

Front. For. Glob. Change

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“…Presence of understory vegetation, including cover crops such as nitrogen-fixing Mucuna bracteata which are commonly planted in young plantations, can help reduce soil erosion, and increase soil fertility and water-holding capacity (Corley and Tinker, 2003a;Baligar and Fageria, 2007;Anderson, 2008). Cover crops can help to reduce soil temperature which, particularly in peat soils, can help to reduce the rate of microbial oxidation, thereby reducing CO 2 emissions (Arifin et al, 2015). Cover crops can also help to reduce access of rhinoceros beetles (Oryctes rhinoceros, a pest species of young palms) to rotting logs that they use for breeding (Bedford, 1980).…”

Section: Introductionmentioning

confidence: 99%

Effects of Understory Vegetation Management on Plant Communities in Oil Palm Plantations in Sumatra, Indonesia

Luke

Purnomo

Advento

et al. 2019

Front. For. Glob. Change

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Oil palm plantations have expanded rapidly in recent decades, and are causing substantial impacts on tropical habitats and biodiversity. However, owing to its long lifespan (25-30 years), oil palm forms a much more varied and structurally-complex habitat than many other crops. This can include abundant understory vegetation and also epiphytes on palm trunks. However, the diversity of this plantation vegetation has been poorly studied, and there has been little consideration of the impacts of common plantation vegetation management practices on plant communities. We conducted a long-term vegetation management experiment that forms part of the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Programme in Riau, Indonesia. We manipulated herbicide and manual cutting regimes within mature oil palm plantations to create three different understory complexity treatments (Reduced, Normal, and Enhanced vegetation) across replicated sets of plots. Plant communities were surveyed before and after experimental understory vegetation treatments began in three different microhabitats: within the middle of the plantation block (core), on the road edge (edge) and on oil palm trunks (trunk). Part of the sampling was also conducted during a drought event. We recorded 120 plant species, which comprised a mixture of native, non-native, "beneficial," and "problem" species. We found substantial variation in plant communities between edge, core, and trunk microhabitats, indicating high levels of heterogeneity within the plantation. There were significant effects of varying understory treatment within both core and edge microhabitats, but no spillover of impacts into the trunk microhabitat. We also observed substantial impacts of drought on plant communities, with declines in either biomass, percentage cover, or richness seen across core, edge, and trunk microhabitats during low-rainfall periods. Our findings highlight the diversity of plant communities that can be supported within oil palm plantations, and the substantial impacts that management decisions, and also drought, can have on them. Given the Luke et al. Plant Communities in Oil Palm Plantations role that diverse plant communities can have in supporting species in other groups, this is likely to have a significant impact on the wider plantation biodiversity. We suggest that plantation management strategies give greater consideration to within-plantation understory plant communities and choose more wildlife-friendly options where possible.

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“…Similar marginal effects were shown by the distance from the oil palm tree on N prediction in the OP site (Figures 6 and 7). The BMP management allowed the fast-growing weeds (Ashton-Butt et al, 2018;Luke et al, 2019;Rahman et al, 2021) or leguminous plants (Arifin et al, 2015;Agus et al, 2019) to occupy the interrow and frond stack as understory cover crops/UCC. N mineralization derived from UCC's litter decomposition could enhance N in peat outside of the fertilization circle, hence, minimizing the effect of distance.…”

Section: Discussionmentioning

confidence: 99%

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

Pulunggono¹,

Madani²,

Zulfajrin³

2022

CELEBES Agricultural

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The capability of machine learning/ML algorithms to analyze the effect of human and environmental factors and variables in controlling soil nutrients has been profoundly studied over the last decades. Unfortunately, ML utilization to estimate macronutrients and their governing factors in cultivated tropical peat soil are extremely scarce. In this study, we trained regression tree/RT, ML-based pedotransfer models to predict total N, P, and K in peat soils based on oil palm/OP and OP+bush datasets. Our results indicated that the dataset might contain outliers, non-linear relationships, and heteroscedasticity, allowing RT-based models to perform better compared to multiple linear regression/MLR models (as a benchmark) in estimating total N and P in both datasets, contrastingly, not in K. The difference of important variables in each RT-based model partially showed the vital role of land use in nutrient modeling in peat. The depth of sample collection, organic C, and ash content became the prominent factor and variables in regulating the entire predicted nutrients. Meanwhile, the distance from the oil palm tree and pH were the salient features of total P prediction models in OP and OP+bush sites, respectively. This study proposed employing ML-based pedotransfer models in analyzing and interpreting complex tropical peat data as an alternative to linear-based regression. Our initial study also shed more light on the development possibility of the pedotransfer models that agricultural practician, researchers, companies, and farmers can use to predict macronutrients, both in tabular and spatial terms, in cultivated tropical peatlands

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Temperature Effect Investigation toward Peat Surface CO2 Emissions by Planting Leguminous Cover Crops in Oil Palm Plantations in West Kalimantan

Cited by 5 publications

References 21 publications

Carbon Emissions From Oil Palm Plantations on Peat Soil

Carbon Emissions From Oil Palm Plantations on Peat Soil

Effects of Understory Vegetation Management on Plant Communities in Oil Palm Plantations in Sumatra, Indonesia

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

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