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Standard oil palm management
In this paper, we consider predominant management practices in large industrial plantations, as they are generally related with highest environmental impacts (Lee et al., 2014a). Moreover, practices in independent smallholders’ plantations may be more variable and are less characterised in the literature (Lee et al., 2014b). However, a large part of smallholders’ plantations in Asia and South America are supervised by industrial plantations in the young age of the palms, and their practices are hence partly comparable to the industrial plantations. In industrial plantations, practices also vary, as for the choice of the planting material, the rate and placement of mineral and organic fertilisers, the weeding practices, etc. But some practices have a relatively lower variability, such as planting density, duration of the growth cycle, and sowing of a legume cover. Therefore, we considered the management practices being the most spread, which we referred to as standard management practices in this paper.
N cycling in oil palm plantations must be considered in the context of management systems, which we briefly summarise here. This summary is derived from (Corley and Tinker, 2015), and we refer readers to that book for more detailed insights. Palm plantations are generally grown on a cycle of approximately 25 years. Clearing and preparation practices may differ depending on the landform and previous land cover. Important variations for N cycling concern the amount of residues from the previous vegetation left to decompose in the field, as well as anti-erosion measures and drain density. One-year-old palms from a nursery are planted in equilateral triangular spacing with a planting density usually in the range of 120– 160 palm ha-1. A legume cover, e.g., Pueraria phaseoloides or Mucuna bracteata, is generally sown in order to provide quick ground cover and fix N from the atmosphere. The legume rapidly covers the whole area and is controlled with manual weeding around palms. It declines as the oil palm canopy grows and is at least partially replaced by more shade-tolerant vegetation around the sixth year when the palm canopy closes.
During the first 2–3 years of plantation, i.e., the immature phase, fruit bunches are not harvested and female inflorescences may be removed to improve growth and subsequent production at the beginning of the third year after planting. During the following 22 years, i.e., the mature phase, the plantation is harvested two to four times per month. For each fresh fruit bunch harvested, one or two palm fronds are pruned and left in the field, mostly in windrows in every second interrow. The alternate inter-row is used for the harvest pathway. The natural vegetation cover in the harvest path and in the circle around the palms is controlled three to four times a year with selective chemical or mechanical weeding. In the remaining area, vegetation is left to grow, except for woody weeds to avoid critical competition with the oil palms.
Fertiliser management varies greatly between plantations and through the life cycle. It generally consists of the application of various forms of mineral fertilisers containing N, P, K, Mg, S, B, Cl, but can be also complemented or substituted by organic fertilisers. Organic fertilisers come mainly from the palm oil mill. After oil extraction, the empty fruit bunches and the palm oil mill effluent may be returned, either fresh or after co-composting, to parts of the plantation, especially on poor soils or in the vicinity of the mill. Around 25 years after planting, the productivity of the palms declines due to higher fruit lost and higher harvesting cost, depending on the palms’ height and stand per hectare. The old palms are felled and sometimes chipped and left in the field to decompose, and new seedlings are planted between them.
Based on this standard management, we identified three main peculiarities in N dynamics to be accounted for in the oil palm N budget. These characteristics are related both to the lifespan of the crop and the management practices. First, as a perennial crop, the palm grows continuously for around 25 years and develops a wide root network, whose extent and turnover will impact nutrient uptake efficiency. Practices are adapted to the plants’ evolving needs and may vary from year to year. Thus, N dynamics may be impacted differently each year and may be influenced by both short- and long-term processes. Second, management practices are spatially differentiated and generate marked spatial heterogeneity across the plantation. For instance, mineral and organic fertilisers may be unevenly distributed and weeds are controlled in specific areas. Thus, the practices generate three main visible zones on the ground: the weeded circle, the harvest pathway, and the pruned frond windrows. These zones differ in terms of ground cover, soil organic matter content, bulk density, and soil biodiversity (Carron et al., 2015; Nelson et al., 2015), and the differences become more pronounced over the crop cycle. N dynamics must also be related to the distribution of fertiliser, which may or may not be associated with the visible zones. N fertiliser may be applied manually or mechanically usually as a band around the outside of the weeded circle. Empty fruit bunches are usually applied in piles adjacent to the harvest path. Temporal and spatial heterogeneity may both influence N dynamics and may also affect the measurement accuracy of N fluxes and stocks (Nelson et al., 2014). Third, internal fluxes of N within the plantation may be important. For instance, as a tropical perennial crop, oil palm produces a large amount of biomass that is returned to the soil, with large associated N fluxes such as pruned fronds, empty fruit bunches, and felled palm. There are also internal fluxes within the palm tree itself, notably from old to new fronds.
Application of N budgets to fertiliser management
N budgets or balances are based on the principle of mass conservation (Meisinger and Randall, 1991; O Legg and J Meisinger, 1982). In agroecosystems, this principle can be represented as follows: N inputs=N outputs +ΔN storage. This simple principle can lead to various approaches, whose complexity increases with the number of considered fluxes and the accuracy of the calculation (Figure 1.1). (Oenema et al., 2003; Watson and Atkinson, 1999) proposed a distinction between three basic approaches in nutrient budget studies: (1) farm-gate budgets, which record only the fluxes of purchased nutrients entering and fluxes of harvested nutrients leaving the system; (2) system budgets, which also include natural fluxes of nutrients entering and leaving the system such as biological N fixation or N leaching, but without looking at potential internal dynamics; (3) cycling models, which take into account all fluxes entering and leaving the system and also quantify internal fluxes and stocks, e.g., immobilisation in plants and mineralisation of residues.
N from plant residues to the litter
Another major internal flux is the N contained in plant residues, which goes from the plants to the litter (flux no. 6 in Figure 1.2). Residues come from the palms, legume cover crops, and other vegetation. For plants other than palms and legumes, to our knowledge no data is available. For legume cover, Agamuthu and Broughton (1985) estimated an amount of 123 kg N ha−1 yr−1 going from the living plants to the litter over the first 3 years under oil palm and Pushparajah (1981) estimated an amount of about 120–160 kg N ha−1 yr−1 over the first to the third years and less than 40 kg N ha−1 yr−1 over the fourth to the seventh years under rubber trees. In both cases, root turnover was not taken into account. For palms, several residues are distinguished: those produced throughout the crop cycle, mostly in the mature phase such as pruned fronds, removed inflorescences, frond bases, root exudates, and dead roots and those produced only once before replanting, i.e., the whole palm when it is felled.
For pruned fronds, the flux of N depends on the quantity of fronds pruned and their N content. Frond production rate stabilizes after 8–12 years at about 20–24 fronds yr−1 (Corley and Tinker, 2015). Several publications estimated the annual flux of N going to the litter, with values ranging from 67 to 131 kg N ha−1 yr−1 (Carcasses, 2004, unpublished data; Redshaw, 2003; Schmidt, 2007; Turner and Gillbanks, 2003). Therefore, this flux is uncertain and the reasons for the variability are not well defined; they may depend on the soil, climate, and planting material which influence frond production and frond weight and on the methods of measurement of N content. For male inflorescences, the flux of N going to the litter has been ignored in most N cycling studies. We found only two estimates, being 6 and 11.2 kg N ha−1 yr−1 (Carcasses, 2004, unpublished data; Turner and Gillbanks, 2003, respectively). These estimates suggest that this flux is lower than the uncertainty of the concomitant N flux via pruned fronds. For frond bases, which rot and fall naturally from the trunk, the only estimate we found was of 3 kg N ha−1 yr−1 going to the litter (Carcasses, 2004, unpublished data).
For root exudates and transfers into the soil via Mycorrhizae, no estimate of N flux is available to our knowledge. Roots themselves are continuously dying and being replaced by new ones. This death of roots constitutes a flux of N going from the palm to the litter pool and depends on the rate of root turnover and on the N content of roots when they die. Root turnover is very difficult to measure. Corley and Tinker (2003) reviewed several methods to estimate it such as deduction from measurements of soil carbon balance or measurements of the growth of roots after extracting soil cores and refilling the holes with root-free soil. Estimates of average turnover ranged from 1.03 to 11.5 t of dry matter ha−1 yr−1 for adult palms (Dufrêne, 1989; Henson and Chai, 1997; Jourdan et al., 2003; Lamade et al., 1996), and turnover was reported to be zero for 3–4-year-old palms (Henson and Chai, 1997). Thus, with an average root N content of 0.32 % of dry matter measured by Ng et al. (1968) in 8–15-year-old palms in Malaysia, the average N flux from root turnover would range from 3.3 to 36.8 kg N ha−1 yr−1. Carcasses (2004, unpublished data) also proposed the value of 7.5 kg N ha−1 yr−1 based on data from Henson and Chai (1997). Therefore, this flux is highly uncertain. Moreover, Corley and Tinker (2003) noted that root turnover measured in Malaysia was much lower than that in Africa, which could be explained by the death of a larger part of the root system in Africa during the annual dry season (Forde, 1972).
N from the litter to the soil
Another important internal flux is the mineralisation or incorporation of N from the litter to the soil (flux no. 7 in Figure 1.2). The litter is composed mostly of plant residues but also contains active microorganisms and fauna. To our knowledge, no data is available regarding the decomposition of residues from plants other than oil palm or legumes in the oil palm system.
For legume litter decomposition, Chiu (2004) measured losses of about 70 % of dry matter after about 2–3 months in leaves and stems of P. phaseoloides and M. bracteata. But the net N release follows a slower dynamic due to the immobilisation of the N by the microbial fauna and flora involved in decomposition and the partial uptake of the N released by growing legumes. For instance, Vesterager et al. (1995) measured in a pot experiment with P. phaseoloides a net release of about 25 % of the N of the legume litter after 2 months, using a 15N labelling technique. In an oil palm field, Turner and Gillbanks (2003) reported that net N release from legume litter occurred between the 24th and the 30th months after planting.
For palm residues, no data was found for frond bases. For pruned fronds and felled and chipped trunks, Khalid et al. (2000) observed a loss of 50 % of dry matter after 6–8 months and a total decomposition after 12–18 months. For roots, Khalid et al. (2000) observed a loss of 50 % of dry matter after 10 months and a total decomposition after about 25 months. These decomposition rates were considered as approximately linear by Khalid et al. (2000), but Moradi et al. (2014) observed an exponential decrease with a faster decomposition over the first 5 months. Khalid et al. (2000) identified rainfall distribution as the main climatic factor controlling the rate of decomposition and observed that shredded residues decompose faster than un-shredded residues. For empty fruit bunches, when mineral N fertiliser was also added, losses of 50 % of dry matter were reported after 2–3 months (Lim and Zaharah, 2000; Rosenani and Hoe, 1996; Turner and Gillbanks, 2003), and total decomposition occurred within 6 to 12 months (Caliman et al., 2001b; Henson, 2004; Rosenani and Hoe, 1996). The decrease followed an exponential dynamic (Lim and Zaharah, 2000); the decomposition was faster when empty fruit bunches were applied in one layer than in two layers (Lim and Zaharah, 2000) and was slower without addition of mineral N (Caliman et al., 2001b). However, for all of these palm residues, the dynamics of N release is more complex than the dynamics of decomposition due to immobilisation by the microbial fauna and flora involved in decomposition. For instance, for trunks, Kee (2004) observed that the net release of N occurred only 12 months after felling. For empty fruit bunches, Zaharah and Lim (2000) observed a complete N immobilisation over their experimental period of about 8 months, and Caliman et al. (2001b) reported a N release of only 50 % at about 6 months, without adding mineral N.
The last internal flux considered is the mineralisation of soil organic N (flux no. 8 in Figure 1.2). Only few data are available, and they involve various soil depths, which hampers comparison. Schroth et al. (2000) estimated the net mineralisation in the top 10 cm of a central Amazonian upland soil at approximately 157 kg N ha−1 yr−1 after 15 years of oil palm production without any N fertiliser inputs. Khalid et al. (1999c) estimated the N mineralisation after replanting in Malaysia at about 312 kg N ha−1 yr−1 in fields without residues from the previous cycle except dead roots and at about 421 kg N ha−1 yr−1 in fields where the palm residues from the previous cycle were left on the soil. Finally, Allen et al. (2015) estimated the N mineralisation in the top 5 cm of soil in Sumatra at about 920 kg N ha−1 yr−1 in loam Acrisol and up to 1528 kg N ha−1 yr−1 in clay Acrisol. However, those measurements were done under more than 7-year-old oil palms established after logging, clearing, and burning of either forest or jungle rubber.
N losses through runoff and erosion
N can also be lost through runoff (flux no. 11 in Figure 1.2) and erosion (flux no. 12 in Figure 1.2) as a solute (NO3− and NH4+) or as eroded particles of soil containing N. Corley and Tinker (2003) and Comte et al. (2012) reviewed measurements of N losses through runoff and erosion from oil palm plantations. Research was done in Malaysia from the 1970s to the 1990s (Kee and Chew, 1996; Maena et al., 1979) and more recently in Papua New Guinea (Banabas et al. 2008) and Sumatra (Sionita et al., 2014). The main variables studied were the effect of soil type, slope, and spatial heterogeneity resulting from management practices, such as soil cover management. The variability of reported values is less than for leaching, ranging from 2 to 15.6 % of N applied lost through runoff, and from 0.5 to 6.2 % of N applied lost through erosion (Kee and Chew, 1996; Maena et al., 1979). Spatial heterogeneity of soil cover seems to have an important effect on losses. Maena et al. (1979) reported losses through runoff of 2 % of N applied in frond piles, but 16 % of that applied in the harvest pathway. Sionita et al. (2014) showed that 10 to 37 t of soil ha−1 yr−1 were lost through erosion of bare soil, depending on slope, but this reduced to 2 to 4 t of soil ha−1 yr−1 with a standard vegetation cover and the same slopes.
These results indicated that soil cover has a significant effect on both runoff and erosion under oil palm. However, data is lacking concerning the transition between the felling of palms and the early development of young palms when the soil is not yet covered by the legume. Finally, it can be noted that in a given situation, there is a balance between runoff/erosion losses and leaching losses, in which soil permeability plays an important role. For instance, in Papua New Guinea, Banabas et al. 2008 estimated losses through leaching at about 37–103 kg N ha−1 yr−1 and negligible runoff, even with a high rainfall of 3000 mm yr−1. The authors suggested that the high permeability of volcanic ash soils could favour leaching over runoff.
N gaseous losses
A potentially important gaseous output is the volatilisation of NH3 (flux no. 13 in Figure 1.2), which can occur directly from the leaves and from soil after fertiliser application, especially urea. Regarding emissions from palm fronds and other vegetation in the system, to our knowledge, no measurements have been reported. For emissions from soil following fertiliser application, several studies were done into urea efficiency under oil palm (e.g. Tarmizi et al., 1993) but only a few measured NH3 volatilisation. Most of them were done in Malaysia between the 1960s and the 1980s, and they often compared urea and ammonium sulphate, the most commonly used fertilisers in oil palm plantations. Two studies were done in Malaysia using different fertiliser rates (125 and 250 kg N ha−1 yr−1) and on different soil types. Reported volatilisation rates from urea ranged from 11.2 to 42 % of N applied (14 to 105 kg N ha−1 yr−1), and volatilisation from ammonium sulphate ranged from 0.1 to 0.4 % of N applied (0.1 to 0.5 kg N ha−1 yr−1) (Chan and Chew, 1984; Sinasamy et al., 1982). Another experiment was carried out in Peru by Bouchet (2003, unpublished data) with a lower fertilisation rate (85 kg N ha−1 yr−1). The study found that 4 to 16 % of N applied in urea was volatilised (3.4 to 13.6 kg N ha−1 yr−1), with higher volatilisation under vegetation cover and no volatilisation from ammonium sulphate. Therefore, given the few studies done and the high variability of the results, the magnitude of losses and the reasons for variations are uncertain. For urea, the highest values were in sandy loam soils with high application rates, and for ammonium sulphate the highest values were in clay soils with high application rates, but they did not exceed 1 % of N applied.
Gaseous emissions of N2O, NOx, and N2 are produced by soil microorganisms, principally through nitrification and denitrification (flux no. 14 in Figure 1.2). Tropical soils are considered as important sources of N2O due to rapid N cycling (Duxbury and Mosier, 1993). As N2O and NOx emissions are difficult to measure and have a very high variability, very few measurements were carried out in oil palm (Corley and Tinker 2003; Banabas et al. 2008; Nelson et al., 2010). Maybe due to the recent growing concern about greenhouse gases emissions, most of the measurements available were done in the 2000s and most of them involved peatlands (e.g. Melling et al., 2007). To our knowledge, only two trials were carried out under oil palm on mineral soils. They focused on N2O emissions and showed very variable results whose average values ranged from 0.01 to 7.3 kg N ha−1 yr−1. Emissions tended to decrease with the age of palms and to be higher in poorly drained soils. Potential N2O emissions are high in poorly drained soils due to limited N uptake by plants and conditions that are conducive for denitrification.
The first study showed N2O emissions ranging from 0.01 to 2.5 kg N ha−1 yr−1 in Indonesia (Ishizuka et al., 2005). The highest values were reported for young palms while the lowest were reported for old palms. Ishizuka suggested that the high emissions under young palms could result from the low uptake of young palms being concomitant with the application of fertiliser and the fixation of N by the legume cover. Conversely, the low emissions under old palms could result from the higher N uptake by palms and the absence of legume cover. The results also indicated that in this area, the N2O emissions were mainly determined by soil moisture. The second study showed emissions ranging from 1.36 to 7.3 kg N ha−1 yr−1 on two different soil types in Papua New Guinea (Banabas 2007). Banabas explained the highest emissions as being related to poor drainage of the soil.
Table of contents :
General introduction
1. Key unknowns in nitrogen budget for oil palm plantations: A review
1.1. Introduction
1.2. N budget within oil palm management
1.2.1. Standard oil palm management
1.2.2. Application of N budgets to fertiliser management
1.2.3. System boundaries and accounted fluxes
1.3. N fluxes and variability in plantations: state-of-the-art
1.3.1. Inputs
1.3.2. Internal fluxes
1.3.3. Outputs
1.4. Important fluxes and critical conditions for N losses
1.4.1. The most important and most uncertain fluxes
1.4.2. Critical conditions for N losses
1.5. Discussion and key research needs
1.6. Conclusions
Acknowledgments
2. Quantifying nitrogen losses in oil palm plantation: models and challenges
2.1. Introduction
2.2. Material and methods
2.2.1. Model selection and description
2.2.2. Description of comprehensive models
2.2.3. Description of sub-models
2.2.4. Model runs and sensitivity analysis
2.3. Results
2.3.1. Comparison of the 11 comprehensive models
2.3.2. Comparison of the 29 sub-models
2.3.3. Sensitivity analysis
2.4. Discussion
2.4.1. Relevance of model comparisons and flux estimates
2.4.2. Challenges for modelling the N budget in oil palm plantations
2.4.3. Implications for management
2.5. Conclusions
Acknowledgements
3. Yield and nitrogen losses in oil palm plantations: main drivers and management tradeoffs determined using simulation
3.1. Introduction
3.2. Material & methods
3.2.1. Study sites and datasets
3.2.2. Inputs, outputs and parameters
3.2.3. Morris sensitivity analysis
3.3. Results
3.3.1. Outputs of the simulations
3.3.2. Influential parameters
3.3.3. Trade-off between yield and N losses
3.4. Discussion
3.4.1. Relevance of the simulation built-up and outputs
3.4.2. Study limitations
3.4.3. Implications for managers, experimentalists, and modellers
3.5. Conclusions
4. IN-Palm: an agri-environmental indicator to assess potential nitrogen losses in oil palm plantations
4.1. Introduction
4.2. Materials and methods
4.2.1. INDIGO® method and fuzzy decision tree modelling approach
4.2.2. Modelled processes
4.2.3. Data used for design, calibration, reference values and validation
4.2.4. Validation of the R-leaching module
4.2.5. Scenario testing
4.3. Results and discussion
4.3.1. General structure and outputs
4.3.2. Calculation of the 17 modules
4.3.3. Validation of the R-Leaching module against field data
4.3.4. Scenario testing and management for N loss reduction
4.4. Conclusion
Acknowledgements
General discussion
6.1. Potential management options to reduce N losses in oil palm
6.2. Future use and development of IN-Palm
6.3. Future field measurements to reduce knowledge gaps in N loss estimates
6.4. INDIGO® framework and life cycle assessment
General conclusion
Appendices
Appendix 1. Permissions of reproduction of published journal articles in this thesis
Appendix 2. Parameter ranges for the Morris’ sensitivity analysis of chapter 2
Appendix 3. IN-Palm technical report
1. User instructions
2. Advantages and computation of fuzzy decision tree models
3. Structure of the 17 modules
Appendix 4. Pictures of fields to help the user in IN-Palm
Appendix 5. Summary of all parameters of IN-Palm
References
