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Article

Assessment of Wet Inorganic Nitrogen Deposition in an Oil Palm Plantation-Forest Matrix Environment in Borneo

by
Giacomo Sellan
1,2,3,*,
Noreen Majalap
4,
Jill Thompson
3,
Nancy B. Dise
3,
Chris D. Field
2,
Salvatore E. Pappalardo
5,
Daniele Codato
5,
Rolando Robert
4 and
Francis Q. Brearley
2
1
CNRS—UMR LEEISA, Campus Agronomique, Kourou 97310, French Guiana
2
Department of Natural Sciences, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, UK
3
UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, UK
4
Forest Research Centre, Sabah Forestry Department, P.O. Box 1407, Sandakan 90715, Sabah, Malaysia
5
Department of Civil, Environmental and Architectural Engineering (ICEA), University of Padua, 35100 Padua, Italy
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(2), 297; https://doi.org/10.3390/atmos14020297
Submission received: 2 December 2022 / Revised: 27 January 2023 / Accepted: 29 January 2023 / Published: 2 February 2023
(This article belongs to the Special Issue Atmospheric Deposition and Its Effects on Terrestrial Ecosystems)
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Abstract

:
Nitrogen (N) deposition significantly affects forest dynamics, carbon stocks and biodiversity, and numerous assessments of N fluxes and impacts exist in temperate latitudes. In tropical latitudes, however, there are few such assessments. In this study, we measured the inorganic N concentration (wet deposition) deposited in rainfall and rainfall pH throughout one year at the boundary of a forest reserve in Malaysian Borneo. We considered that the N deposition may be either from forest and agricultural fires or derived from agricultural fertiliser. Therefore, we determined the wind trajectories using the HYSPLIT model provided by NOAA, the location of fires throughout the landscape throughout one year using NASA’s FIRM system, and obtained the land use cover map of Malaysia and Indonesia. We then correlated our monthly cumulative wet N deposition with the cumulative number of fires and the cumulative area of oil palm plantation that wind trajectories arriving at our study site passed over before reaching the rainfall sampling site. At 7.45 kg N ha−1 year−1, our study site had the highest annual wet inorganic N deposition recorded for a Malaysian forest environment. The fire season and the cumulative agricultural area crossed by the winds had no significant effect on N deposition, rainfall N concentration, or rainfall pH. We suggest that future research should use 15N isotopes in rainfall to provide further information on the sources of N deposition in tropical forests such as this.

1. Introduction

Forests in the tropics are composed of a matrix of different forests types. Whilst the widespread lowland evergreen rain forests are thought to be phosphorus (P) limited [1], other tropical forests such as heath and montane, are considered nitrogen (N) poor [2,3,4]. So, N poor forests may respond differently to increases in N inputs than lowland evergreen rain forests. The use of fertilisers, fossil fuel and biomass burning have been increasing the concentration of atmospheric reactive N (defined as oxide gases, anions and amine derivatives) since the mid-20th century in the industrialised northern hemisphere, with a consequent increase in N deposition [5,6]. The global dataset of [7] allows a comparison of worldwide N deposition rates ranging from 0.17 kg N ha−1 year−1 in Alaska to 27.1 kg N ha−1 year−1 in parts of China. Globally, more than 11% of non-agricultural vegetated land received an amount of wet and dry inorganic N deposition exceeding a critical load of 10 kg N ha−1 year−1 [8], above which a negative effect on vegetation is expected. Critical loads are set according to abiotic and biotic conditions affecting sensitivity. Acidic European coniferous forests, for example, are highly sensitive to N deposition and have a N critical load of 10–15 kg N ha−1 year−1 [9], whereas Chinese subtropical evergreen forests have a higher N critical load of 20–70 kg N ha−1 year−1 [10] because they are P limited. However, in the tropics, N deposition leads to a drop in soil pH [11] and decreases in plant biodiversity [12,13]. The rate of N deposition is predicted to increase in tropical areas [14]. The Sundaland biogeographic region that includes the island of Borneo, for example, is predicted to exceed a deposition rate of 10 kg N ha−1 year−1 on 15.6% of its area by 2050 [14]. Despite the importance of tropical regions as biodiversity hotspots and the potentially damaging effects of N deposition, few monitoring stations for N deposition and studies on N deposition exist in these zones [7].
South-east Asia seasonally undergoes a burning season, usually around September-October [15], where land is cleared and burned to establish small-scale agriculture or agro-industrial plantations [16]. The greatest fire density has been recorded in Kalimantan and Sumatra, Indonesia [17] and, to a lesser extent, in Malaysian Borneo and Brunei [18]. Biomass burning in tropical regions produces a haze that is an important input source of atmospheric N [19,20,21]. Another potential source of reactive N to forests is agriculture. Agro-industrial crops such as oil palm [22] drive the demand of tropical countries for N fertilisers that consume c. 70% of the global fertiliser production [23]. Few measurements of N deposition exist for Malaysian Borneo (but see [7]), where rain forests are enclosed in a mosaic of oil palm estates [24] and are likely to undergo seasonal haze pollution from fires and N deposition due to the fertilisation of plantations. Borneo has widespread N-limited forests such as heath forests (known as kerangas) and montane forests. Both of these forest types host a high plant endemism with species adapted to low soil nutrients [25]. These forests are, therefore, important to maintain the biodiversity of tropical areas overall and of the island of Borneo in particular. An increase in N deposition could thus lead to biodiversity losses in a similar way to temperate ecosystems. In this research, we hypothesised that, as our study site is near to an intensive agricultural area and receives wind from areas that suffer fires, it is subject to a high amount of N deposition. We tested this by collecting rainfall with a wet-only sampler throughout one year and measuring the concentrations of rainfall NH4+ and NO3−. Furthermore, we hypothesised that the monthly amount of wet N deposited at our study site from rainfall is correlated with fire occurrences or N fertilizer addition to nearby cultivated land that is brought to the site by the prevailing winds. We tested this second hypothesis by back-crossing the monthly wind trajectories arriving at our study site with the monthly fires map obtained by satellite and the land use map of the neighbouring area. In this way we obtained two indices that were then correlated with the monthly deposition of wet inorganic N to determine their relationship.

2. Materials and Methods

2.1. Study Area

Our collection site was located at the Sabah Forestry Department’s Forest Research Centre (FRC) in Sepilok, Sabah, Malaysia (Figure 1). The FRC building is surrounded by a matrix of residential dwellings, fruit orchards and oil palm estates, and there is an urban centre (Sandakan) about 10 km to the east. Further south from FRC (c. 1 km) and west (c. 0.5 km) extends a 44 km2 primary forest growing on alluvial, sandstone and heath forest soil [26], the Kabili-Sepilok Forest Reserve. The close proximity of the forest reserve to the matrix of urbanized and agricultural landscape is typical for northern Borneo, given the rapid expansion of agroindustry and human activities. The climate is equatorial with a mean temperature of c. 26 °C and an annual rainfall of c. 3000 mm [27,28]. Most of the rain falls between November and February due to the influence of the north-east monsoon, which brings winds from the Philippines. The driest month is usually April, when the rainfall is less than 100 mm month−1 [28]. From June to August, the south-west monsoon brings air masses from Indonesian Kalimantan, southern Borneo [27].

2.2. Sampling and Analysis

Nitrogen deposition comprises wet and dry depositions; in this study, we were only able to sample wet N deposition. We collected rainwater with a wet-only sampler placed on the highest point of the FRC building. The sampler was composed of two cylinders one inside the other; the two cylinders were connected by a funnel. This allowed even the lightest rain to be collected in the sampler and reduced the evaporation. Sampling was carried out twice per week over a period of 12 months from September 2016 to August 2017. We recorded rainwater volume using a rain gauge. Sub-samples of rainfall were then filtered with a 0.2 µm filter. After filtration, we recorded rainwater pH with a Corning 240 pH meter, then we acidified the samples to pH ~2 with two drops of 50% H2SO4. Samples were then stored in a −20 °C refrigerator until NH4+ and NO3− analyses could be carried out using a segmented flow analyser (Astoria-Pacific A2, Clackamas, OR, USA). We did not measure total dissolved N, so our results refer to wet-deposited inorganic N only. We calculated monthly deposition of N derived from NH4+ and NO3− (referred as NH4+-N and NO3−-N) as well as the monthly volume-weighted concentration of NH4+ and NO3−. Volume-weighted concentration is a routine measure that expresses the average concentration of ions in the total volume of precipitation that fell within a certain time period. Volume weighted concentration (Ci) was calculated as
Ci = ƩjPjCij/ƩjPj
where Pj is the amount of precipitation in sampling j (mm) and Cij is the concentration of constituent i for sampling j (µmol l−1) [29]. We then multiplied the volume-weighted N concentration by the total precipitation for each month to obtain the bulk wet deposition in kg ha−1 year−1.

2.3. Wind Trajectories, Fires, Land Use and the Correlation with N Deposition

We considered fires and agricultural activities as providing atmospheric N inputs and winds as N transporters. To investigate whether active fires or land use were a significant source of wet N deposition, we back-crossed wind trajectories with fire maps for the study area generated using the HYSPLIT model provided by NOAA (www.ready.noaa.gov, accessed on 20 October 2022; [31]) and with the land use map of year 2016 from the Nusantara Atlas (https://map.nusantara-atlas.org/ accessed on 19 December 2019; [32]) using ESRI ArcMap (version 10.3.1). To this aim we used the Quantun Geographic Information System QGIS [33]. Throughout the study period (September 2016 to August 2017), we generated twelve wind trajectories (width of 12 km) every two weeks at three different altitudes (50 m, 500 m and 1000 m), each running for 315 h. We chose these wind heights because the smoke released from fires in Borneo has been estimated to reach heights between 523 m and 993 m [34]. Nonetheless, smoke is concentrated at a lower height so we also added the 50 m trajectory. We obtained the fire maps from NASA’s FIRMS system, which provides data from active fires detected by MODIS C6 satellites (https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms accessed on 3 December 2018). Using these data, we counted how many fires the winds arriving at our study site passed over every two weeks. We used only fire points which had a detection confidence over 30%, as suggested by the MODIS website (https://www.earthdata.nasa.gov/faq/firms-faq#ed-confidence accessed on 22 December 2019). The smoke from each fire becomes less dense with increasing distance from the fire itself. This is of course a simplification and it depends on the meteorology at the time of the fire and on the air mass movements. We accounted for this by creating three buffer rings around each fire point. The rings had a radius of 5, 10 and 15 km from the fire point and we assigned a lower weighting to the largest 15 km ring, an intermediate weighting to the 10 km radius ring and the greatest weighting to the 5 km ring. We then used the ‘intersect’ command in QGIS to assign to each wind point the weight of the respective fire buffer ring that it passed over. To assess the type of land use that the winds arriving to our sampling point were passing over, we used the ‘join attributes by location’ function in QGIS. Among the wind points passing over oil palm plantations, we assigned a value of 1 to the wind points at 50 m height, a value of 0.6 to the wind points at 500 m height and a value of 0.3 to the wind points at 1000 m height. Finally, we calculated the cumulative monthly fire count (MFC) and the cumulative monthly land use count (MLUC) to assess if there was a relationship between changes in monthly total wet N deposition and concentration in rainfall with the potential air pollution derived from fires or from agricultural fertilisers. Given the normal distribution of our variables (Shapiro–Wilk’s test), we examined the correlations of MFC and MLUC with monthly rainfall, rainwater pH, NH4+-N and NO3−-N total monthly deposition, and NH4+ and NO3− concentration in rainfall, with Pearson correlation tests. All the p-values were adjusted using the Benjamini–Hochberg false discovery rate (fdr) procedure [35]. We also conducted a sensitivity analysis to make sure that assigning different weights to the buffer rings and the winds did not alter the significance of the Pearson tests. All the statistical analyses were performed with R version 3.5.1 [36].

3. Results

Over the 12 months of monitoring (from July 2016 to August 2017), we recorded 4637 mm total rainfall, which was higher than the mean of around 3000 mm year−1 for this location ([27]; www.ncdc.noaa.gov/cdo-web/ accessed on 22 December 2019). During this time, the driest month was, unexpectedly, February, with 175 mm rainfall, and November was the wettest month (765 mm; Figure 2). The monthly mean volume- weighted concentration of NH4+ in rainfall was lowest in October 2016 (3.5 µmol L−1) and peaked in June 2017 (21.6 µmol L−1), declining again in the following two months (Table 1). June 2017 also had the greatest wet NH4+-N deposition (1.28 kg N ha−1); the lowest was in October 2016 (0.21 kg N ha−1). The volume-weighted concentration of NO3− remained constant through the year (1.1 µmol l−1 ± 0.09 SE; Figure 2). In total, we calculated a deposition rate of wet inorganic N of 7.45 kg N ha−1 year−1 which was dominated by NH4+ (90.4%), with NO3− making up the remainder (9.6%). Rainfall had an annual mean pH of 5.38 ± 0.02 SE, with the most acidic rain event in October 2016 (pH 4.71) and the least acidic in August 2017 (pH 5.82).
The winds coming from the Philippines are characteristic of the north-east monsoon, usually from November to February, although these winds were still active until April 2017 (Figure 3). The south-west monsoon usually appears around June and July but, according to our simulation, these months had quite weak winds; strong south-west monsoon winds arrived only in August. Throughout our study period, two major fire seasons occurred in the region. The first fire season was between September and October 2016 with high concentrations of fires in Kalimantan and Sarawak. The second was between March and May 2017, with fires in the western part of the Philippines (i.e., Palawan, Western Visayas and Negros island, as well as Zamboanga peninsula; Figure 3).
The winds arriving at our study site in September 2016 passed over the greatest number and intensity of fires; the winds arriving in December 2016 passed over the least number and intensity of fires. Winds from September and October 2016 arriving at our site intercepted fires from both Sarawak (at approximately 500 km distance) and Kalimantan (at approximately 450 km distance), whereas during the last two months of the north-east monsoon (March and April), winds intercepted the fires in the south-west Philippines, which had been detected by the satellites over a period of approximately nine months.
The winds that arrived at our study site in August 2017 passed through the greatest amount of oil palm cultivated areas (MLUC of 1492), whereas the winds arriving at our study site in February 2017 passed through the smallest extent of oil palm cultivated areas (MLUC of 101). We found no significant correlation between any N form or rainfall pH with MFC or and the MLUC, either with and without applying the fdr correction (Table 2; p > 0.05 in all cases).

4. Discussion

Nitrogen deposition is known to decrease plant diversity in terrestrial N-limited ecosystems [37,38]. This evidence mainly comes from studies of temperate sites and tropical forests are underrepresented. Here, we assessed the amount of N deposition over one year for a single location in Sabah, Malaysian Borneo, where forests are in close proximity to N-emitting sources such as fires and agro-industrial cultivation. We also assessed the relationship of N deposition with the trajectory of winds passing over fires and oil palm cultivation, as both are known to emit N. At 7.45 N ha−1 year−1, our study site received the highest wet inorganic N deposition measured for a forest environment in Malaysia (Table 3). Previous measurements have been carried out in lowland pristine forest (1.1 to 2.2 kg N ha−1 year−1, [7,39]), forest surrounded by oil palm and rubber cultivation (the highest measurement of 6.2 kg N ha−1 year−1, [40,41]) and montane forest (3.0 to 3.7 kg N ha−1 year−1 [7,42]). As we measured only wet inorganic N deposition and were unable to consider organic N and dry deposition (which can be equal to or exceed wet N deposition), it is likely that the total N deposition in our study site exceeds the critical load of 10–15 kg N ha−1 year−1, that is proposed as potentially damaging to temperate forests [38]. This is relevant because heath forest, a forest typology widespread throughout the tropics, is possibly limited by soil N, similar to temperate forests [43,44]. Heath forest, thus, could have a critical load similar to temperate forests. Mean rainfall pH was mainly high and characteristic of an environment with low emissions of oxidised N, although pH sometimes fell below 5.3, indicating acidic deposition [7]. Given the low and stable oxidised N concentration recorded during our monitoring, this pH variation might be driven by fluctuations in sulphur concentration [45], which we did not measure. We acknowledge that the use of only one rain gauge collector and the limited sampling of only 12 months poses a limitation to the statistical power of our study. The rainfall pattern during the 12 months of sampling (from July 2016 to August 2017) was not typical for the year as it had c. 1600 mm of rain more than the average year. Nonetheless, our study site, being between a forest edge and a matrix of agro-industrial cultivation and human settlements, is representative of a large share of tropical rainforests, given that 20% of tropical forests lies within 100 m of a forest edge [46].
The pattern of NH4+-N concentration in rainfall suggested seasonal wet N deposition variation, but we were not able to pinpoint the origin of this seasonal variation. The seasonal pattern of fires we detected is typical for Borneo, with most active fires in September [47]. The large number of fires in south-west Philippines is concomitant with the dry season for the area (Philippine Atmospheric, Geophysical and Astronomical Services Administration, http://bagong.pagasa.dost.gov.ph/ accessed on 22 December 2019), suggesting a seasonal fire regime. However, despite the known emission of oxidised and reduced N from fires [48], we did not find any correlation between monthly wet inorganic N deposition or concentration in rainwater and the number of fires that winds coming to our study site intercepted. The winds from the month with the highest rainwater NH4+ concentration (June 2017) intercepted the least number of fires. Biomass combustion generally produces oxidised N [19,49], which was low in our rainfall samples (9% of the total N deposition) and stable throughout the year. We thus consider it unlikely that fires and haze affected N deposition at our study site. We also suggest that the most reactive N deposited on these forests originates from nearby sources, a reasonable hypothesis in many tropical forests due to the heavy rainfall and high interception area by dense leafy canopies [50].
Table
Table 3. Comparison of annual wet inorganic N deposition rates in some Malaysian and Singaporean sites.
Table 3. Comparison of annual wet inorganic N deposition rates in some Malaysian and Singaporean sites.
Site NH4+-NNO3−-NpHRainfallReference
kg ha−1 year−1 mm year−1
ForestForest type
Sepilok (East Malaysia)Lowland6.70.75.44637This study
Danum (East Malaysia)Lowland0.70.45.12996Vet et al., 2014 [7]
Pasoh (West Malaysia)Lowland2.33.95.82381Manokaran 1980 [40]
Berembun (West Malaysia)Montane1.41.65.91979Yusop and Nik 1989 [42]
Tanah Rata (West Malaysia)Montane1.42.14.92879Vet et al., 2014 [7]
City
Singapore 11.513.4-2554Karthikeyan et al., 2009 [51]
We suggest that the main source of NH4+ in rainwater in these forests is agro-industrial fertilisation. Oil palms are regularly fertilised. We hypothesised that this fertilisation produces large amounts of ammonia (NH3) and other reduced N compounds (collectively, NHx) that are hydrolysed to ammonium (NH4+) in the lower atmosphere and deposited in rainfall and dry deposition to downwind forests. Nonetheless, we found no correlation between any form of wet N deposition with the amount of oil palm plantations that the winds arriving at our study site intercepted. We speculate that the amount of N emitted by plantations, and thus the amount of N deposited by rain, is highest immediately after the fertilisation. It would then be necessary to know the seasonality of N fertilisation in oil palm plantations. There are, to our knowledge, no studies of NHx emission and deposition from oil palm plantations, although it is known that these compounds are, in general, produced in abundance after crop fertilisation [38,52]. In addition, one study found that nitrous oxide (N2O) emissions, also presumably from fertilisation, can increase about 160 times from natural forests to oil palm plantations [53]. We hypothesise that the relatively still air throughout May and June could have led to an accumulation of fertiliser-derived NH4+ in the air mass that was then deposited in rainwater. In order to better understand the origins and the consequences of N deposition on Bornean forests, further work should investigate the seasonality of oil palm fertilisation.

5. Conclusions

Excess N deposition poses hazards to N-limited forest ecosystems such as the heath and montane forests in Borneo, potentially causing soil acidification, eutrophication, damage to roots, foliage, and mycorrhizas, species composition change, and biodiversity loss [38]. Here, we assessed the magnitude of wet inorganic N deposition over one year (2016–2017) at a site close to a pristine forest reserve. The site is also next to oil palm plantations and might be affected by volatilised N fertiliser from the plantation. It may also be impacted by the reactive N in seasonal haze from forest fires.
Our site received an amount of wet inorganic N deposition higher than any previously recorded from Malaysian forests. The deposition was mainly composed of NH4+ that increased substantially from April through June 2017. We did not find evidence that forest fires nor the passage of winds over oil palm plantations influenced the concentration or the total deposition of inorganic N. We consider that changes in rainwater NH4+ concentration were due to NH4+ accumulation sourced from the surrounding fertilised oil palm estates, rather than from forest fires. To further test this, we can compare the isotopic N signature of fertilisers used in the area to determine the source of N deposited on the forest. Furthermore, it should be clearly defined in which months the fertiliser is applied to the oil palm sites. Should we discover that fertiliser is the main contributor, then policy makers and local authorities should consider limiting the amount of fertiliser used in plantations near threatened forest sites.

Author Contributions

Conceptualisation, G.S., F.Q.B., J.T., N.B.D. and C.D.F.; methodology, G.S., N.M. and R.R.; formal analysis, G.S., S.E.P. and D.C.; resources, N.M. and R.R.; writing—original draft preparation, G.S., F.Q.B. and J.T.; writing—review and editing, All authors. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Manchester Metropolitan University’s Environmental Science Research Centre. J.T. and N.B.D. were supported by UKCEH.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data on wet N deposition is available from the corresponding author.

Acknowledgments

We would like to thank the Sabah Biodiversity Council, the Soil Chemistry section, Ecology section and Herbarium staff from Sabah Forest Research Centre and in particular the research assistants Spincer Sitim, Lioba Sawadon and Yun Len Lee. We are indebted Marijn Bauters for valuable suggestions, David Gaveau and Erik Meijaard for the help in obtaining the land use map and Pierre Gloaguen for the assistance with R coding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Cunha, H.F.V.; Andersen, K.M.; Lugli, L.F.; Santana, F.D.; Aleixo, I.F.; Moraes, A.M.; Garcia, S.; Di Ponzio, R.; Mendoza, E.O.; Brum, B.; et al. Direct evidence for phosphorus limitation on Amazon forest productivity. Nature 2022, 608, 558–562. [Google Scholar] [CrossRef]
  2. Benner, J.W.; Vitousek, P.M.; Ostertag, R. Nutrient cycling and nutrient limitation in tropical montane cloud forests. In Tropical Montane Cloud Forests: Science for Conservation and Management; Bruijnzeel, L., Scatena, F., Hamilton, L., Eds.; Cambridge University Press: Cambridge, UK, 2011; pp. 90–100. [Google Scholar]
  3. Moran, J.A.; Barker, M.G.; Moran, A.J.; Becker, P.; Ross, S.M. A comparison of the soil water, nutrient status, and litterfall characteristics of tropical heath and mixed-dipterocarp forest sites in Brunei. Biotropica 2000, 32, 2–13. [Google Scholar] [CrossRef]
  4. Tanner, E.V.J.; Kapos, V.; Franco, W. Nitrogen and phosphorus fertilization effects on Venezuelan montane forest trunk growth and litterfall. Ecology 1992, 73, 78–86. [Google Scholar] [CrossRef]
  5. Galloway, J.N.; Aber, J.D.; Erisman, J.W.; Seitzinger, S.P.; Howarth, R.W.; Cowling, E.B.; Cosby, B.J. The nitrogen cascade. Bioscience 2003, 53, 341–356. [Google Scholar] [CrossRef]
  6. Galloway, J.N.; Dentener, F.J.; Capone, D.G.; Boyer, E.W.; Howarth, R.W.; Seitzinger, S.P.; Asner, G.P.; Cleveland, C.C.; Green, P.A.; Holland, E.A.; et al. Nitrogen cycles: Past, present, and future. Biogeochemistry 2004, 70, 153–226. [Google Scholar] [CrossRef]
  7. Vet, R.; Artz, R.S.; Carou, S.; Shaw, M.; Ro, C.U.; Aas, W.; Baker, A.; Bowersox, V.C.; Dentener, F.J.; Galy-Lacaux, C.; et al. A global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus. Atmos. Environ. 2014, 93, 3–100. [Google Scholar] [CrossRef]
  8. Dentener, F.J.; Drevet, J.; Lamarque, J.F.; Bey, I.; Eickhout, B.; Fiore, A.M.; Hauglustaine, D.; Horowitz, L.W.; Krol, M.; Kulshrestha, U.C.; et al. Nitrogen and sulfur deposition on regional and global scales: A multimodel evaluation. Glob. Biogeochem. Cycles 2006, 20, GB4003. [Google Scholar] [CrossRef]
  9. Bobbink, R.; Loran, C.; Tomassen, H. (Eds.) Review and Revision of Empirical Critical Loads of Nitrogen for Europe; Umweltbundesamt/German Environment Agency: Dessau-Roßlau, Germany, 2022. [Google Scholar]
  10. Liu, X.; Duan, L.; Mo, J.; Du, E.; Shen, J.; Lu, X.; Zhang, Y.; Zhou, X.; He, C.; Zhang, F. Nitrogen deposition and its ecological impact in China: An overview. Environ. Pollut. 2011, 159, 2251–2264. [Google Scholar] [CrossRef]
  11. Lu, X.; Mao, Q.; Gilliam, F.S.; Luo, Y.; Mo, J. Nitrogen deposition contributes to soil acidification in tropical ecosystems. Glob. Chang. Biol. 2014, 20, 3790–3801. [Google Scholar] [CrossRef]
  12. Lu, X.; Mo, J.; Gilliam, F.S.; Zhou, G.; Fang, Y. Effects of experimental nitrogen additions on plant diversity in an old-growth tropical forest. Glob. Chang. Biol. 2010, 16, 2688–2700. [Google Scholar] [CrossRef] [Green Version]
  13. Midolo, G.; Alkemade, R.; Schipper, A.M.; Benítez-López, A.; Perring, M.P.; De Vries, W. Impacts of nitrogen addition on plant species richness and abundance: A global meta-analysis. Glob. Ecol. Biogeogr. 2018, 28, 398–413. [Google Scholar] [CrossRef]
  14. Phoenix, G.K.; Hicks, W.K.; Cinderby, S.; Kuylenstierna, J.C.I.; Stock, W.D.; Dentener, F.J.; Giller, K.E.; Austin, A.T.; Lefroy, R.D.B.; Gimeno, B.S.; et al. Atmospheric nitrogen deposition in world biodiversity hotspots: The need for a greater global perspective in assessing N deposition impacts. Glob. Chang. Biol. 2006, 12, 470–476. [Google Scholar] [CrossRef]
  15. Jones, D.S. ASEAN and transboundary haze pollution in Southeast Asia. Asia Eur. J. 2006, 4, 431–446. [Google Scholar] [CrossRef]
  16. Barber, C.V.; Schweithelm, J. Trial by Fire: Forest Fire and Forestry Policy in Indonesia’s Era of Crisis and Reform; World Resources Institute: Washington, DC, USA, 2000. [Google Scholar]
  17. Lohman, D.J.; Bickford, D.; Sodhi, N.S. The burning issue. Science 2007, 316, 376. [Google Scholar] [CrossRef] [PubMed]
  18. Aiken, S.R. Runaway fires, smoke-haze pollution, and unnatural disasters in Indonesia. Geogr. Rev. 2004, 94, 55–79. [Google Scholar] [CrossRef]
  19. Andreae, M.O.; Browell, E.V.; Garstang, M.; Gregory, G.L.; Harriss, R.C.; Hill, G.F.; Jacob, D.J.; Pereira, M.C.; Sachse, G.W.; Setzer, A.W.; et al. Biomass-burning emissions and associated haze layers over Amazonia. J. Geophys. Res. 1988, 93, 1509–1527. [Google Scholar] [CrossRef]
  20. Crutzen, P.J.; Andreae, M.O. Biomass burning in the tropics: Impact on atmospheric chemistry and biogeochemical cycles. Science 1990, 250, 1669–1678. [Google Scholar] [CrossRef]
  21. Lobert, J.M.; Schaffe, D.H.; Hao, W.M.; Crutzen, P.J. Importance of biomass burning in the atmospheric budgets of nitrogen-containing gases. Nature 1990, 346, 552–554. [Google Scholar] [CrossRef]
  22. Carrasco, L.R.; Larrosa, C.; Edwards, D.P. A double-edged sword for tropical forests. Science 2014, 346, 38–41. [Google Scholar] [CrossRef]
  23. Albanito, F.; Lebender, U.; Cornulier, T.; Sapkota, T.B.; Brentrup, F.; Stirling, C.; Hillier, J. Direct nitrous oxide emissions from tropical and sub-tropical agricultural systems—A review and modelling of emission factors. Sci. Rep. 2017, 7, 44235. [Google Scholar] [CrossRef] [Green Version]
  24. Abram, N.K.; Xofis, P.; Tzanopoulos, J.; MacMillan, D.C.; Ancrenaz, M.; Chung, R.; Peter, L.; Ong, R.C.; Lackman, I.; Goossens, B.; et al. Synergies for improving oil palm production and forest conservation in floodplain landscapes. PLoS ONE 2014, 9, e95388. [Google Scholar] [CrossRef]
  25. Ashton, P.S. Conservation of Borneo biodiversity: Do small lowland parks have a role, or are big inland sanctuaries sufficient? Brunei as an example. Biodivers. Conserv. 2010, 19, 343–356. [Google Scholar] [CrossRef]
  26. Sellan, G.; Brearley, F.Q.; Nilus, R.; Titin, J.; Majalap, N. Differences in soil properties among contrasting soil types in Northern Borneo. J. Trop. For. Sci. 2021, 33, 191–202. [Google Scholar] [CrossRef]
  27. Fox, J.E.D. A Handbook to Kabili-Sepilok Forest Reserve. Sabah Forest Record No. 9; Borneo Literature Bureau: Kuching, Malaysia, 1973. [Google Scholar]
  28. Nilus, R. Effect of Edaphic Variation on Forest Structure, Dynamics and Regeneration in a Lowland Tropical Rainforest in Borneo. Ph.D. Thesis, University of Aberdeen, Aberdeen, UK, 2003. [Google Scholar]
  29. EPA Quality Assurance Handbook for Air Pollution Measurement Systems: Volume V. Manual for Precipitation Measuremnt Systems Part 1. Quality Assurance Manual; EPA: Washington, DC, USA, 1983.
  30. Hansen, M.C.; Potapov, P.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-resolution global maps of 21st-century forest cover change. Science 2013, 342, 850–853. [Google Scholar] [CrossRef] [PubMed]
  31. Draxler, R.R.; Rolph, G.D. HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model Access via NOAA ARL READY Website (College Park, MD:NOAAAir Resources Laboratory). Available online: http://arl.noaa.gov/HYSPLIT.php (accessed on 22 December 2019).
  32. Gaveau, D.L.A.; Sheil, D.; Husnayaen; Salim, M.A.; Arjasakusuma, S.; Ancrenaz, M.; Pacheco, P.; Meijaard, E. Rapid conversions and avoided deforestation: Examining four decades of industrial plantation expansion in Borneo. Sci. Rep. 2016, 6, 32017. [Google Scholar] [CrossRef] [PubMed]
  33. QGIS Development Team. QGIS Geographic Information System. Version 3.8-Zanzibar. Open Source Geospatial Foundation Project. 2019. Available online: https://www.scirp.org/(S(351jmbntvnsjt1aadkozje))/reference/referencespapers.aspx?referenceid=2631129 (accessed on 22 October 2022).
  34. Zender, C.S.; Krolewski, A.G.; Tosca, M.G.; Randerson, J.T. Tropical biomass burning smoke plume size, shape, reflectance, and age based on 2001–2009 MISR imagery of Borneo. Atmos. Chem. Phys. 2012, 12, 3437–3454. [Google Scholar] [CrossRef]
  35. Benjamini, Y.; Krieger, A.M.; Yekutieli, D. Adaptive linear step-up procedures that control the false discovery rate. Biometrika 2006, 93, 491–507. [Google Scholar] [CrossRef]
  36. R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2021. [Google Scholar]
  37. Anderson-Teixeira, K.J.; Davies, S.J.; Bennett, A.C.; Gonzalez-Akre, E.B.; Muller-Landau, H.C.; Wright, S.J.; Abu Salim, K.; Almeyda Zambrano, A.M.; Alonso, A.; Baltzer, J.L.; et al. CTFS-ForestGEO: A worldwide network monitoring forests in an era of global change. Glob. Chang. Biol. 2015, 21, 528–549. [Google Scholar] [CrossRef]
  38. Bobbink, R.; Hicks, K.; Galloway, J.N.; Spranger, T.; Alkemade, R.; Ashmore, M.; Bustamante, M.; Cindereby, S.; Davidson, E.; Dentener, F.J.; et al. Global assessment of nitrogen deposition effects on terrestrial plant diversity: A synthesis. Ecol. Appl. 2010, 20, 30–59. [Google Scholar] [CrossRef]
  39. Yamashita, N.; Sase, H.; Kobayashi, R.; Leong, K.; Hanapi, J.M.; Uchiyama, S.; Urban, S.; Toh, Y.Y.; Muhamad, M.; Gidiman, J.; et al. Atmospheric deposition versus rock weathering in the control of streamwater chemistry in a tropical rain-forest catchment in Malaysian Borneo. J. Trop. Ecol. 2014, 30, 481–492. [Google Scholar] [CrossRef] [Green Version]
  40. Manokaran, N. The nutrient contents of precipitation, through fall and stem flow in a lowland tropical rain forest in Peninsular Malaysia. Malay. For. 1980, 34, 266–289. [Google Scholar]
  41. Okuda, T.; Suzuki, M.; Adachi, N.; Yoshida, K.; Niiyama, K.; Noor, N.S.; Hussein, N.A.; Manokaran, N.; Hashim, M. Logging history and its impact on forest structure and species composition in the Pasoh Forest Reserve—Implications for the sustainable management of natural resources and landscapes. In Pasoh: Ecology of a Lowland Rain Forest in Southeast Asia; Okuda, T., Manokaran, N., Matsumoto, Y., Niiyama, K., Thomas, S.C., Ashton, P.S., Eds.; Springer: Tokyo, Japan, 2003; pp. 15–34. [Google Scholar]
  42. Yusop, Z.; Nik, A.R. Rainfall chemistry and nutrient loading in a peninsular Malaysia forest site. J. Trop. For. Sci. 1989, 1, 201–214. [Google Scholar]
  43. Sellan, G. Ecological Responses of a Bornean Heath Forest (Kerangas) to Experimental Lime and Nitrogen. Ph.D. Thesis, Manchester Metropolitan University, Manchester, UK, 2019. [Google Scholar]
  44. Sellan, G.; Thompson, J.; Majalap, N.; Robert, R.; Brearley, F.Q. Impact of soil nitrogen availability and pH on tropical heath forest organic matter decomposition and decomposer activity. Pedobiologia J. Soil Ecol. 2020, 80, 150645. [Google Scholar] [CrossRef]
  45. Charlson, R.J.; Rodhe, H. Factors controlling the acidity of natural rainwater. Nature 1982, 295, 683–685. [Google Scholar] [CrossRef]
  46. Brinck, K.; Fischer, R.; Groeneveld, J.; Lehmann, S.; De Paula, M.D.; Putz, S.; Sexton, J.O.; Song, D.; Huth, A. High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle. Nat. Commun. 2017, 8, 14855. [Google Scholar] [CrossRef] [PubMed]
  47. Giglio, L.; Csiszar, I.; Justice, C.O. Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. J. Geophys. Res. Biogeosci. 2006, 111, 02016. [Google Scholar] [CrossRef]
  48. Bauters, M.; Drake, T.W.; Verbeeck, H.; Bodé, S.; Hervé-Fernández, P.; Zito, P.; Podgorski, D.C.; Boyemba, F.; Makelele, I.; Cizungu Ntaboba, L.; et al. High fire-derived nitrogen deposition on central African forests. Proc. Natl. Acad. Sci. USA 2018, 115, 549–554. [Google Scholar] [CrossRef]
  49. Radojevic, M. Chemistry of forest fires and regional haze with emphasis on Southeast Asia. Pure Appl. Geophys. 2003, 160, 157–187. [Google Scholar] [CrossRef]
  50. Ayers, G.P.; Peng, L.C.; Fook, L.S.; Kong, C.W.; Gillett, R.W.; Manins, P.C. Atmospheric concentrations and deposition of oxidised sulfur and nitrogen species at Petaling Jaya, Malaysia, 1993–1998. Tellus Ser. B Chem. Phys. Meteorol. 2000, 52, 60–73. [Google Scholar] [CrossRef]
  51. Karthikeyan, S.; He, J.; Palani, S.; Balasubramanian, R.; Burger, D. Determination of total nitrogen in atmospheric wet and dry deposition samples. Talanta 2009, 77, 979–984. [Google Scholar] [CrossRef]
  52. Bouwman, A.F.; Lee, D.S.; Asman, W.A.H.; Dentener, F.J.; Van Der Hoek, K.W.; Olivier, J.G.J. A global high-resolution emission inventory for ammonia. Glob. Biogeochem. Cycles 1997, 11, 561–587. [Google Scholar] [CrossRef]
  53. Fowler, D.; Nemitz, E.; Misztal, P.; di Marco, C.; Skiba, U.M.; Ryder, J.; Helfter, C.; Neil Cape, J.; Owen, S.; Dorsey, J.; et al. Effects of land use on surface-atmosphere exchanges of trace gases and energy in Borneo: Comparing fluxes over oil palm plantations and a rainforest. Philos. Trans. R. Soc. B Biol. Sci. 2011, 366, 3196–3209. [Google Scholar] [CrossRef] [PubMed]
Atmosphere 14 00297 g001 550
Figure 1. Location of the study site. (A) The island of Borneo with the approximate position of the Kabili-Sepilok Forest Reserve (Sabah, Malaysia) highlighted in red. (B) The Kabili-Sepilok Forest Reserve with the location of the Forest Research Centre (red star) highlighted. Panel B shows forested areas in white and non-forest areas in black (data from [30]).
Figure 1. Location of the study site. (A) The island of Borneo with the approximate position of the Kabili-Sepilok Forest Reserve (Sabah, Malaysia) highlighted in red. (B) The Kabili-Sepilok Forest Reserve with the location of the Forest Research Centre (red star) highlighted. Panel B shows forested areas in white and non-forest areas in black (data from [30]).
Atmosphere 14 00297 g001
Atmosphere 14 00297 g002 550
Figure 2. Total monthly rainfall at our study site in Sepilok, Sabah, Malaysia (blue bars) and volume-weighted mean concentration of rainfall NH4+ and NO3−.
Figure 2. Total monthly rainfall at our study site in Sepilok, Sabah, Malaysia (blue bars) and volume-weighted mean concentration of rainfall NH4+ and NO3−.
Atmosphere 14 00297 g002
Atmosphere 14 00297 g003 550
Figure 3. Intersection of the fire map (where the fires are represented by the red dots) obtained for Borneo and surrounding regions (MODIS C6 satellites https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms accessed on 3 December 2018) with the backward wind trajectories (grey dotted lines) generated with the HYSPLIT model provided by NOAA. Backward wind trajectories were generated every two weeks at three different altitudes (50 m, 500 m and 1000 m) each running for 315 h. The backward wind trajectories end at our sample collection site in Sepilok, Sabah, Malaysia.
Figure 3. Intersection of the fire map (where the fires are represented by the red dots) obtained for Borneo and surrounding regions (MODIS C6 satellites https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms accessed on 3 December 2018) with the backward wind trajectories (grey dotted lines) generated with the HYSPLIT model provided by NOAA. Backward wind trajectories were generated every two weeks at three different altitudes (50 m, 500 m and 1000 m) each running for 315 h. The backward wind trajectories end at our sample collection site in Sepilok, Sabah, Malaysia.
Atmosphere 14 00297 g003
Table
Table 1. Monthly mean pH and the cumulative amount of wet NH4+-N and NO3−-N (kg ha−1) in rainfall collected in our study site at Sepilok, Sabah, Malaysia.
Table 1. Monthly mean pH and the cumulative amount of wet NH4+-N and NO3−-N (kg ha−1) in rainfall collected in our study site at Sepilok, Sabah, Malaysia.
DatepHNH4+-NNO3−-N
2016September5.370.350.08
October5.170.210.07
November5.380.990.09
December5.300.410.05
2017January5.440.720.09
February5.450.270.05
March5.340.510.06
April5.440.640.05
May5.460.730.04
June5.391.280.04
July5.320.330.04
August5.470.290.04
Total -6.740.71
Table
Table 2. Pearson correlation coefficients between the amount of fires that winds arriving at our sampling site passed over in the month before rainfall (MFC), the amount of oil palm cultivated area that winds arriving at our sampling site passed over in the month before rainfall (MLUC) and different monthly rainfall characteristics (total NH4+-N and NO3−-N deposition, NH4+ and NO3− mean concentration in rainfall, mean rainwater pH and rainfall amount). Rainfall samples were collected throughout one year at the Forest Research Centre, Sepilok, Sabah, Malaysia. The p- values (adjusted using the Benjamini–Hochberg false discovery rate are noted in superscript and were all non-significant.
Table 2. Pearson correlation coefficients between the amount of fires that winds arriving at our sampling site passed over in the month before rainfall (MFC), the amount of oil palm cultivated area that winds arriving at our sampling site passed over in the month before rainfall (MLUC) and different monthly rainfall characteristics (total NH4+-N and NO3−-N deposition, NH4+ and NO3− mean concentration in rainfall, mean rainwater pH and rainfall amount). Rainfall samples were collected throughout one year at the Forest Research Centre, Sepilok, Sabah, Malaysia. The p- values (adjusted using the Benjamini–Hochberg false discovery rate are noted in superscript and were all non-significant.
NH4+
kg ha−1		NO3−
kg ha−1		NH4+
µmol L−1		NO3−
µmol L−1		Rainwater
pH		Rainfall (mm)
MFC−0.300.340.270.42−0.220.480.250.380.040.90−0.370.24
MLUC−0.040.900.210.35−0.090.78−0.300.51−0.190.55−0.310.32
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MDPI and ACS Style

Sellan, G.; Majalap, N.; Thompson, J.; Dise, N.B.; Field, C.D.; Pappalardo, S.E.; Codato, D.; Robert, R.; Brearley, F.Q. Assessment of Wet Inorganic Nitrogen Deposition in an Oil Palm Plantation-Forest Matrix Environment in Borneo. Atmosphere 2023, 14, 297. https://doi.org/10.3390/atmos14020297

AMA Style

Sellan G, Majalap N, Thompson J, Dise NB, Field CD, Pappalardo SE, Codato D, Robert R, Brearley FQ. Assessment of Wet Inorganic Nitrogen Deposition in an Oil Palm Plantation-Forest Matrix Environment in Borneo. Atmosphere. 2023; 14(2):297. https://doi.org/10.3390/atmos14020297

Chicago/Turabian Style

Sellan, Giacomo, Noreen Majalap, Jill Thompson, Nancy B. Dise, Chris D. Field, Salvatore E. Pappalardo, Daniele Codato, Rolando Robert, and Francis Q. Brearley. 2023. "Assessment of Wet Inorganic Nitrogen Deposition in an Oil Palm Plantation-Forest Matrix Environment in Borneo" Atmosphere 14, no. 2: 297. https://doi.org/10.3390/atmos14020297

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