Variable carbon losses from recurrent fires in drained tropical peatlands

Refining greenhouse gas emission factors for Indonesian peatlands and mangroves to meet ambitious climate targets

For countries' emission-reduction efforts under the Paris Agreement to be effective, baseline emission/removals levels and reporting must be as transparent and accurate as possible. For Indonesia, which holds among the largest area of tropical peatlands and mangrove forest in the world, it is particularly important for these high-carbon ecosystems to produce high-accuracy greenhouse gas inventory and to improve national forest reference emissions level/forest reference level. Here, we highlight the opportunity for refining greenhouse gas emission factors (EF) of peatlands and mangroves and describe scientific challenges to support climate policy processes in Indonesia, where 55 to 59% of national emission reduction targets by 2030 depend on mitigation in Forestry and Other Land Use. Based on the stock-difference and flux change approaches, we examine higher-tier EF for drained and rewetted peatland, peatland fires, mangrove conversions, and mangrove on peatland to improve future greenhouse gas flux reporting in Indonesia. We suggest that these refinements will be essential to support Indonesia in achieving Forest and Other Land Use net sink by 2030 and net zero emissions targets by 2060 or earlier.

Simulating carbon accumulation and loss in the central Congo peatlands

Peatlands of the central Congo Basin have accumulated carbon over millennia. They currently store some 29 billion tonnes of carbon in peat. However, our understanding of the controls on peat carbon accumulation and loss and the vulnerability of this stored carbon to climate change is in its infancy. Here we present a new model of tropical peatland development, DigiBog_Congo, that we use to simulate peat carbon accumulation and loss in a rain-fed interfluvial peatland that began forming ~20,000 calendar years Before Present (cal. yr BP, where 'present' is 1950 CE). Overall, the simulated age-depth curve is in good agreement with palaeoenvironmental reconstructions derived from a peat core at the same location as our model simulation. We find two key controls on long-term peat accumulation: water at the peat surface (surface wetness) and the very slow anoxic decay of recalcitrant material. Our main simulation shows that between the Late Glacial and early Holocene there were several multidecadal periods where net peat and carbon gain alternated with net loss. Later, a climatic dry phase beginning ~5200 cal. yr BP caused the peatland to become a long-term carbon source from ~3975 to 900 cal. yr BP. Peat as old as ~7000 cal. yr BP was decomposed before the peatland's surface became wetter again, suggesting that changes in rainfall alone were sufficient to cause a catastrophic loss of peat carbon lasting thousands of years. During this time, 6.4 m of the column of peat was lost, resulting in 57% of the simulated carbon stock being released. Our study provides an approach to understanding the future impact of climate change and potential land-use change on this vulnerable store of carbon.

Building capacity for estimating fire emissions from tropical peatlands; a worked example from Indonesia

Tropical peatlands are globally significant in the terrestrial carbon cycle as they are comprised of a large forest carbon sink and a large peat carbon store-both of which can potentially be exchanged with the atmosphere on decadal time frames. Greenhouse gas emissions from fire-disturbance and development of tropical peatlands over the last few decades, and the potential for ongoing emissions, highlights the need for policy to slow or halt emissions and to activate mechanisms to sequester carbon through restoration of degraded peatlands. The UN REDD + scheme provides a means for developing countries to receive payments for avoided deforestation and forest degradation, but the steps to achieve REDD+ compliance are rigorous and the details required can be a barrier to activating benefits-especially for peatlands where repeated cycles of fire interrupt forest recovery and create a range of recovery classes. Therefore, to improve estimates of peat fire emissions and of carbon balance of tropical peatlands, the biomass and combustion factor parameters need to be developed and applied according to forest recovery stage. In this study we use published activity data from the extensive 1997 fires in the peatlands of Indonesian Borneo to detail a transparent and accountable way to estimate and report emissions from tropical peatland fires. This example for estimating and reporting emissions is provided to assist REDD+ countries to efficiently develop their capacity for improving emissions estimates from fire-impacted tropical peatlands.

Carbon dioxide emissions through land use change, fire, and oxidative peat decomposition in Borneo

Borneo has accumulated an abundance of woody carbon in its forests and peat. However, agricultural land conversion accompanied by plantation development, dead wood burning, and peat drying from drainage are major challenges to climate change mitigation. This study aimed to develop a method of estimating carbon dioxide (CO2) emissions from land use change, forest and peat fires, and oxidative peat decomposition, and CO2 uptake from biomass growth across Borneo using remote sensing data from 2001 to 2016. Although CO2 uptake by biomass growth in vast forests has shown a significant increasing trend, an annual net release of 461.10 ± 436.51 (average ± 1 standard deviation) Tg CO2 year-1 was observed. The estimated emissions were predominantly characterized by land use changes from 2001 to 2003, with the highest emissions in 2001. Land use change was evaluated from annual land use maps with an accuracy of 92.0 ± 1.0% (average ± 1 standard deviation). Forest and peat fires contributed higher emissions in 2002, 2006, 2009, 2014, and 2015 compared to other years and were strongly correlated with the Southern Oscillation Indexes. These results suggest that more CO2 may have been released into the atmosphere than previously thought.

Using machine learning algorithms to predict groundwater levels in Indonesian tropical peatlands

Tropical peatlands play a vital role in the global carbon cycle as large carbon reservoirs and substantial carbon sinks. Indonesia possesses the largest share (65 %) of tropical peat carbon, equal to 57.4 Gt C. Human perturbations such as extensive logging, deforestation and canalization exacerbate water losses, especially during dry seasons, when low precipitation and high evapotranspiration rates combine with the increased drainage to lower groundwater levels. Drying and increasing temperatures of the surface peat exacerbate ignition and wildfire risks within the peat soils. As such, it is critically important to know how groundwater levels in peatlands are changing over space and time. In this study, a multilinear regression model as well as two machine learning algorithms, random forest and extreme gradient boosting, were used to model groundwater level over the study period (2010-12) within a peat dome impacted by drainage canals and multiple wildfires in Central Kalimantan, Indonesia. Although all three models performed well, based on overall fit, spatial modeling of groundwater level results revealed that extreme gradient boosting (R² = 0.998, RMSE = 0.048 m) outperformed random forest (R² = 0.997, RMSE = 0.054 m) and multilinear regression (R² = 0.970, RMSE = 0.221 m) near drainage canals, which are key fire ignition risk locations in the peatlands. Our study also shows that, on average, elevation and precipitation are the most important parameters influencing groundwater level spatiotemporally.

Peat moisture dataset of Sumatra peatlands

Peatland is a unique ecosystem that is key in regulating global carbon cycle, climate, hydrology, and biodiversity. Peat moisture content is a key variable in ecohydrological and biogeochemical cycles known to control peatland's greenhouse gas emissions and fire vulnerability. Peat moisture is also an indicator of the success of peat restoration projects. Here we present datasets of peat moisture dynamic and retention capacity of degraded tropical peatlands. The data were collected from automatic daily monitoring and field campaigns. The peat moisture content data consists of daily data from 21 stations across three peatland provinces in Sumatra Island, Indonesia, from 2018 to 2019. In addition, peat water retention data were collected from field campaigns in Riau province. This dataset represents human modified peatlands which can be used as a benchmark for hydrological and biogeochemical models.

Detecting tropical peatland degradation: Combining remote sensing and organic geochemistry

Tropical peatlands are important carbon stores that are vulnerable to drainage and conversion to agriculture. Protection and restoration of peatlands are increasingly recognised as key nature based solutions that can be implemented as part of climate change mitigation. Identification of peatland areas that are important for protection and restauration with regards to the state of their carbon stocks, are therefore vital for policy makers. In this paper we combined organic geochemical analysis by Rock-Eval (6) pyrolysis of peat collected from sites with different land management history and optical remote sensing products to assess if remotely sensed data could be used to predict peat conditions and carbon storage. The study used the North Selangor Peat Swamp forest, Malaysia, as the model system. Across the sampling sites the carbon stocks in the below ground peat was ca 12 times higher than the forest (median carbon stock held in ground vegetation 114.70 Mg ha-1 and peat soil 1401.51 Mg ha-1). Peat core sub-samples and litter collected from Fire Affected, Disturbed Forest, and Managed Recovery locations (i.e. disturbed sites) had different decomposition profiles than Central Forest sites. The Rock-Eval pyrolysis of the upper peat profiles showed that surface peat layers at Fire Affected, Disturbed Forest, and Managed Recovery locations had lower immature organic matter index (I-index) values (average I-index range in upper section 0.15 to -0.06) and higher refractory organic matter index (R -index) (average R-index range in upper section 0.51 to 0.65) compared to Central Forest sites indicating enhanced decomposition of the surface peat. In the top 50 cm section of the peat profile, carbon stocks were negatively related to the normalised burns ratio (NBR) (a satellite derived parameter) (Spearman's rho = -0.664, S = 366, p-value = <0.05) while there was a positive relationship between the hydrogen index and the normalised burns ratio profile (Spearman's rho = 0.7, S = 66, p-value = <0.05) suggesting that this remotely sensed product is able to detect degradation of peat in the upper peat profile. We conclude that the NBR can be used to identify degraded peatland areas and to support identification of areas for conversation and restoration.

Assessing costs of Indonesian fires and the benefits of restoring peatland

Deforestation and drainage has made Indonesian peatlands susceptible to burning. Large fires occur regularly, destroying agricultural crops and forest, emitting large amounts of CO₂ and air pollutants, resulting in adverse health effects. In order to reduce fire, the Indonesian government has committed to restore 2.49 Mha of degraded peatland, with an estimated cost of US$3.2-7 billion. Here we combine fire emissions and land cover data to estimate the 2015 fires, the largest in recent years, resulted in economic losses totalling US$28 billion, whilst the six largest fire events between 2004 and 2015 caused a total of US$93.9 billion in economic losses. We estimate that if restoration had already been completed, the area burned in 2015 would have been reduced by 6%, reducing CO₂ emissions by 18%, and PM_2.5 emissions by 24%, preventing 12,000 premature mortalities. Peatland restoration could have resulted in economic savings of US$8.4 billion for 2004-2015, making it a cost-effective strategy for reducing the impacts of peatland fires to the environment, climate and human health.

Land Cover and Land Use Change Decreases Net Ecosystem Production in Tropical Peatlands of West Kalimantan, Indonesia

Deforested and converted tropical peat swamp forests are susceptible to fires and are a major source of greenhouse gas (GHG) emissions. However, information on the influence of land-use change (LUC) on the carbon dynamics in these disturbed peat forests is limited. This study aimed to quantify soil respiration (heterotrophic and autotrophic), net primary production (NPP), and net ecosystem production (NEP) in peat swamp forests, partially logged forests, early seral grasslands (deforested peat), and smallholder-oil palm estates (converted peat). Peat swamp forests (PSF) showed similar soil respiration with logged forests (LPSF) and oil palm (OP) estates (37.7 Mg CO2 ha−1 yr−1, 40.7 Mg CO2 ha−1 yr−1, and 38.7 Mg CO2 ha−1 yr−1, respectively), but higher than early seral (ES) grassland sites (30.7 Mg CO2 ha−1 yr−1). NPP of intact peat forests (13.2 Mg C ha−1 yr−1) was significantly greater than LPSF (11.1 Mg C ha−1 yr−1), ES (10.8 Mg C ha−1 yr−1), and OP (3.7 Mg C ha−1 yr−1). Peat swamp forests and seral grasslands were net carbon sinks (10.8 Mg CO2 ha−1 yr−1 and 9.1 CO2 ha−1 yr−1, respectively). In contrast, logged forests and oil palm estates were net carbon sources; they had negative mean Net Ecosystem Production (NEP) values (−0.1 Mg CO2 ha−1 yr−1 and −25.1 Mg CO2 ha−1 yr−1, respectively). The shift from carbon sinks to sources associated with land-use change was principally due to a decreased Net Primary Production (NPP) rather than increased soil respiration. Conservation of the remaining peat swamp forests and rehabilitation of deforested peatlands are crucial in GHG emission reduction programs.

Carbon balance of tropical peat forests at different fire history and implications for carbon emissions

Accurate assessment of tropical peat forest carbon stocks and impact of fires on carbon pools is required to determine the magnitude of emissions to the atmosphere and to support emissions reduction policies. We assessed total aboveground carbon (AGC) in biomass pools including trees, shrubs, deadwood, litter and char, and peat carbon to develop empirical estimates of peat swamp forest carbon stocks in response to fire and disturbance. In contrast to the common assumption that peat fires combust all AGC, we observed that about half of undisturbed forest AGC, equivalent to about 70 Mg C ha^-1, remains after one or two recent fires - mainly in dead trees, woody debris and pyrogenic carbon. Both recently burnt and repeatedly burnt peat forests store similar amounts of carbon in the top 10 cm of peat when compared with undisturbed forests (70 Mg C ha^-1), mainly due to increased peat bulk density after fires that compensates for their lower peat C%. The proportion of fuel mass consumed in fire, or combustion factor (CF), is required to make accurate estimates of peat fire emissions for both AGC and peat carbon. This study estimated a CF for AGC (CF_AGC) of 0.56, comparable to the default value of the Intergovernmental Panel on Climate Change (IPCC). This study estimated a varying CF for peat (CF_PEAT) that ranged from 0.4 to 0.68 as depth of burn increased. This revised CF_PEAT is one third to one half of the IPCC default value of 1.0. The current assumption of complete combustion of peat (CF = 1.0) is widely acknowledged in the literature as oversimplification and is not supported by our field observations or data. This study provides novel empirical data to improve estimates of peat forests carbon stocks and emissions from tropical peat fires.

The Use of Subsidence to Estimate Carbon Loss from Deforested and Drained Tropical Peatlands in Indonesia

Drainage is a major means of the conversion of tropical peat forests into agriculture. Accordingly, drained peat becomes a large source of carbon. However, the amount of carbon (C) loss from drained peats is not simply measured. The current C loss estimate is usually based on a single proxy of the groundwater table, spatially and temporarily dynamic. The relation between groundwater table and C emission is commonly not linear because of the complex natures of heterotrophic carbon emission. Peatland drainage or lowering groundwater table provides plenty of oxygen into the upper layer of peat above the water table, where microbial activity becomes active. Consequently, lowering the water table escalates subsidence that causes physical changes of organic matter (OM) and carbon emission due to microbial oxidation. This paper reviews peat bulk density (BD), total organic carbon (TOC) content, and subsidence rate of tropical peat forest and drained peat. Data of BD, TOC, and subsidence were derived from published and unpublished sources. We found that BD is generally higher in the top surface layer in drained peat than in the undrained peat. TOC values in both drained and undrained are lower in the top and higher in the bottom layer. To estimate carbon emission from the top layer (0–50 cm) in drained peats, we use BD value 0.12 to 0.15 g cm−3, TOC value of 50%, and a 60% conservatively oxidative correction factor. The average peat subsidence is 3.9 cm yr−1. The range of subsidence rate per year is between 2 and 6 cm, which results in estimated emission between 30 and 90 t CO2e ha−1 yr−1. This estimate is comparable to those of other studies and Tier 1 emission factor of the 2013 IPCC GHG Inventory on Wetlands. We argue that subsidence is a practical approach to estimate carbon emission from drained tropical peat is more applicable than the use of groundwater table.

Peat-forest burning smoke in Maritime Continent: Impacts on receptor PM2.5 and implications at emission sources

This study characterizes the impacts of transported peat-forest (PF) burning smoke on an urban environment and evaluates associated source burning conditions based on carbon properties of PM_2.5 at the receptor site. We developed and validated a three-step classification that enables systematic and more rapid identification of PF smoke impacts on a tropical urban environment with diverse emissions and complex atmospheric processes. This approach was used to characterize over 300 daily PM_2.5 data collected during 2011-2013, 2015 and 2019 in Singapore. A levoglucosan concentration of ≥0.1 μg/m³ criterion indicates dominant impacts of transported PF smoke on urban fine aerosols. This approach can be used in other ambient environments for practical and location-dependent applications. Organic carbon (OC) concentrations (as OC indicator) can be an alternate to levoglucosan for assessing smoke impacts on urban environments. Applying the OC concentration indicator identifies smoke impacts on ∼80% of daily samples in 2019 and shows an accuracy of 51-86% for hourly evaluation. Following the systematic identification of urban PM_2.5 predominantly affected by PF smoke in 2011-2013, 2015 and 2019, we assessed the concentration ratio of char-EC/soot-EC as an indicator of smoldering- or flaming-dominated burning emissions. When under the influence of transported PF smoke, the mean concentration ratio of char-EC to soot-EC in urban PM_2.5 decreased by >70% from 8.2 in 2011 to 2.3 in 2015 but increased to 3.8 in 2019 (p < 0.05). The reversed trend with a 65% increase from 2015 to 2019 shows stronger smoldering relative to flaming, indicating a higher level of soil moisture at smoke origins, possibly associated with rewetting and revegetating peatlands since 2016.

Identifying and addressing knowledge gaps for improving greenhouse gas emissions estimates from tropical peat forest fires

Tropical peatlands are areas of high carbon density that are important in biosphere-atmosphere interactions. Drainage and burning of tropical peatlands releases about 5% of global greenhouse gas (GHG) emissions, yet there is great uncertainty in these estimates. Our comprehensive literature review of parameters required to calculate GHG emissions from burnt peat forests, following the international guidelines, revealed many gaps in knowledge of carbon pools and few recent supporting studies. To improve future estimates of the total ecosystem carbon balance and peatfire emissions this study aimed to account for all carbon pools: aboveground, deadwood, pyrogenic carbon (PyC) and peat of single and repeatedly burnt peat forests. A further aim was to identify the minimum sampling intensity required to detect with 80% power significant differences in these carbon pools among long unburnt, recently burnt and repeatedly burnt peat swamp forests. About 90 Mg C ha^-1 remains aboveground as deadwood after a single fire and half of this remains after a second fire. One fire produces 4.5 ± 0.6 Mg C ha^-1 of PyC, with a second fire increasing this to 7.1 ± 0.8 Mg C ha^-1. For peat swamp forests these aboveground carbon pools are rarely accounted in estimates of emissions following multiple fires, while PyC has not been included in the total peat carbon mass balance. Peat bulk density and peat carbon content change with fire frequency, yet these parameters often remain constant in the published emission estimates following a single and multiple fires. Our power analysis indicated that as few as 12 plots are required to detect meaningful differences between fire treatments for the major carbon pools. Further field studies directed at improving the parameters for calculating carbon balance of disturbed peat forest ecosystems are required to better constrain peatfire GHG emission estimates.

Nutrient Balance as a Tool for Maintaining Yield and Mitigating Environmental Impacts of Acacia Plantation in Drained Tropical Peatland—Description of Plantation Simulator

Responsible management of Acacia plantations requires an improved understanding of trade-offs between maintaining stand production whilst reducing environmental impacts. Intensive drainage and the resulting low water tables (WT) increase carbon emissions, peat subsidence, fire risk and nutrient export to water courses, whilst increasing nutrient availability for plant uptake from peat mineralization. In the plantations, hydrology, stand growth, carbon and nutrient balance, and peat subsidence are connected forming a complex dynamic system, which can be thoroughly understood by dynamic process models. We developed the Plantation Simulator to describe the effect of drainage, silviculture, fertilization, and weed control on the above-mentioned processes and to find production schemes that are environmentally and economically viable. The model successfully predicted measured peat subsidence, which was used as a proxy for stand total mass balance. Computed nutrient balances indicated that the main growth-limiting factor was phosphorus (P) supply, and the P balance was affected by site index, mortality rate and WT. In a scenario assessment, where WT was raised from −0.80 m to −0.40 m the subsidence rate decreased from 4.4 to 3.3 cm yr−1, and carbon loss from 17 to 9 Mg ha−1 yr−1. P balance shifted from marginally positive to negative suggesting that additional P fertilization is needed to maintain stand productivity as a trade-off for reducing C emissions.

The Potential of ICESat-2 to Identify Carbon-Rich Peatlands in Indonesia

Peatlands in Indonesia are one of the primary global storages for terrestrial organic carbon. Poor land management, drainage, and recurrent fires lead to the release of huge amounts of carbon dioxide. Accurate information about the extent of the peatlands and its 3D surface topography is crucial for assessing and quantifying this globally relevant carbon store. To identify the most carbon-rich peatlands—dome-shaped ombrogenous peat—by collecting GPS-based terrain data is almost impossible, as these peatlands are often located in remote areas, frequently flooded, and usually covered by dense tropical forest vegetation. The detection by airborne LiDAR or spaceborne remote sensing in Indonesia is costly and laborious. This study investigated the potential of the ICESat-2/ATLAS LiDAR satellite data to identify and map carbon-rich peatlands. The spaceborne ICESat-2 LiDAR data were compared and correlated with highly accurate field validated digital terrain models (DTM) generated from airborne LiDAR as well as the commercial global WorldDEM DTM dataset. Compared to the airborne DTM, the ICESat-2 LiDAR data produced an R2 of 0.89 and an RMSE of 0.83 m. For the comparison with the WorldDEM DTM, the resulting R2 lay at 0.94 and the RMSE at 0.86 m. We model the peat dome surface from individual peat hydrological units by performing ordinary kriging on ICESat-2 DTM-footprint data. These ICESat-2 based peatland models, compared to a WorldDEM DTM and airborne DTM, produced an R2 of 0.78, 0.84, and 0.94 in Kalimantan and an R2 of 0.69, 0.72, and 0.85 in Sumatra. The RMSE ranged from 0.68 m to 2.68 m. These results demonstrate the potential of ICESat-2 in assessing peat surface topography. Since ICESat-2 will collect more data worldwide in the years to come, it can be used to survey and map carbon-rich tropical peatlands globally and free of charge.

Drainage increases CO2 and N2 O emissions from tropical peat soils

Tropical peatlands are vital ecosystems that play an important role in global carbon storage and cycles. Current estimates of greenhouse gases from these peatlands are uncertain as emissions vary with environmental conditions. This study provides the first comprehensive analysis of managed and natural tropical peatland GHG fluxes: heterotrophic (i.e. soil respiration without roots), total CO₂ respiration rates, CH₄ and N₂ O fluxes. The study documents studies that measure GHG fluxes from the soil (n = 372) from various land uses, groundwater levels and environmental conditions. We found that total soil respiration was larger in managed peat ecosystems (median = 52.3 Mg CO₂  ha^-1  year^-1 ) than in natural forest (median = 35.9 Mg CO₂  ha^-1  year^-1 ). Groundwater level had a stronger effect on soil CO₂ emission than land use. Every 100 mm drop of groundwater level caused an increase of 5.1 and 3.7 Mg CO₂  ha^-1  year^-1 for plantation and cropping land use, respectively. Where groundwater is deep (≥0.5 m), heterotrophic respiration constituted 84% of the total emissions. N₂ O emissions were significantly larger at deeper groundwater levels, where every drop in 100 mm of groundwater level resulted in an exponential emission increase (exp(0.7) kg N ha^-1  year^-1 ). Deeper groundwater levels induced high N₂ O emissions, which constitute about 15% of total GHG emissions. CH₄ emissions were large where groundwater is shallow; however, they were substantially smaller than other GHG emissions. When compared to temperate and boreal peatland soils, tropical peatlands had, on average, double the CO₂ emissions. Surprisingly, the CO₂ emission rates in tropical peatlands were in the same magnitude as tropical mineral soils. This comprehensive analysis provides a great understanding of the GHG dynamics within tropical peat soils that can be used as a guide for policymakers to create suitable programmes to manage the sustainability of peatlands effectively.

Mapping deep peat carbon stock from a LiDAR based DTM and field measurements, with application to eastern Sumatra

BACKGROUND

Reduction of carbon emissions from peatlands is recognized as an important factor in global climate change mitigation. Within the SE Asia region, areas of deeper peat present the greatest carbon stocks, and therefore the greatest potential for future carbon emissions from degradation and fire. They also support most of the remaining lowland swamp forest and its associated biodiversity. Accurate maps of deep peat are central to providing correct estimates of peat carbon stocks and to facilitating appropriate management interventions. We present a rapid and cost-effective approach to peat thickness mapping in raised peat bogs that applies a model of peat bottom elevation based on field measurements subtracted from a surface elevation model created from airborne LiDAR data.

RESULTS

In two raised peat bog test areas in Indonesia, we find that field peat thickness measurements correlate well with surface elevation derived from airborne LiDAR based DTMs (R² 0.83-0.88), confirming that the peat bottom is often relatively flat. On this basis, we created a map of extent and depth of deep peat (> 3 m) from a new DTM that covers two-thirds of Sumatran peatlands, applying a flat peat bottom of 0.61 m +MSL determined from the average of 2446 field measurements. A deep peat area coverage of 2.6 Mha or 60.1% of the total peat area in eastern Sumatra is mapped, suggesting that deep peat in this region is more common than shallow peat and its extent was underestimated in earlier maps. The associated deep peat carbon stock range is 9.0-11.5 Pg C in eastern Sumatra alone.

CONCLUSION

We discuss how the deep peat map may be used to identify priority areas for peat and forest conservation and thereby help prevent major potential future carbon emissions and support the safeguarding of the remaining forest and biodiversity. We propose rapid application of this method to other coastal raised bog peatland areas in SE Asia in support of improved peatland zoning and management. We demonstrate that the upcoming global ICESat-2 and GEDI satellite LiDAR coverage will likely result in a global DTM that, within a few years, will be sufficiently accurate for this application.

Effects of distance from canal and degradation history on peat bulk density in a degraded tropical peatland

Over recent decades, the combination of deforestation, peat drainage and fires have resulted in widespread degradation of Southeast Asia's tropical peatlands. These disturbances are generally thought to increase peat soil bulk density through peat drying and shrinkage, compaction, and consolidation. Biological oxidation and fires burning across these landscapes also consume surface peat, exposing older peat strata. The prevalence and severity of deforestation, peat drainage and fire are typically greater closer to canals, built to drain peatlands and provide access routes for people. We compared bulk densities of 240cm peat profiles from intact forests and degraded peatlands broadly, and also assessed differences between degraded peatlands near-to-canals (50-200m from the nearest canal) and far-from-canals (300+ m from the nearest canal). The effects of vegetation type and fire frequency on bulk density, irrespective of the distance from canal, were also investigated. Mean bulk density values ranged between 0.08 and 0.16gcm^-3 throughout the 240cm peat profiles. Drainage of peat near-to-canals increased bulk density of peat above the minimum water table depth. Degradation by deforestation and fire also increased bulk densities of upper peat strata, albeit with greater variability. Peat sampled further from canals experienced less intense water table drawdowns, buffering them from drainage effects. These areas were also more commonly forested and burnt less frequently. Differences in bulk densities below minimum water table levels are less clear, but may reflect lowering of the current peat surface in degraded peatlands broadly. These results clearly show that important differences in bulk density exist across degraded peatlands that are spatially dependent on distance from canals and disturbance history. These landscape features should be taken into account when designing future bulk density sampling efforts and peatland restoration programs, or when extrapolating from existing sources in order to make accurate inferences from them.

Fire Frequency and Related Land-Use and Land-Cover Changes in Indonesia’s Peatlands

Indonesia’s converted peatland areas have a well-established fire problem, but limited studies have examined the frequency with which they are burning. Here, we quantify fire frequency in Indonesia’s two largest peatland regions, Sumatra and Kalimantan, during 2001–2018. We report, annual areas burned, total peatland area affected by fires, amount of recurrent burning and associations with land-use and land-cover (LULC) change. We based these analyses on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua combined burned area and three Landsat-derived LULC maps (1990, 2007, and 2015) and explored relationships between burning and land-cover types. Cumulative areas burned amounted nearly half of the surface areas of Sumatra and Kalimantan but were concentrated in only ~25% of the land areas. Although peatlands cover only 13% of Sumatra and Kalimantan, annual percentage of area burning in these areas was almost five times greater than in non-peatlands (2.8% vs. 0.6%) from 2001 to 2018. Recurrent burning was more prominent in Kalimantan than Sumatra. Average fire-return intervals (FRI) in peatlands of both regions were short, 28 and 45 years for Kalimantan and Sumatra, respectively. On average, forest FRI were less than 50 years. In non-forest areas, Kalimantan had shorter average FRI than Sumatra (13 years vs. 40 years), with ferns/low shrub areas burning most frequently. Our findings highlight the significant influence of LULC change in altering fire regimes. If prevalent rates of burning in Indonesia’s peatlands are not greatly reduced, peat swamp forest will disappear from Sumatra and Kalimantan in the coming decades.

Fires, Smoke Exposure, and Public Health: An Integrative Framework to Maximize Health Benefits From Peatland Restoration

Emissions of particulate matter from fires associated with land management practices in Indonesia contribute to regional air pollution and mortality. We assess the public health benefits in Indonesia, Malaysia, and Singapore from policies to reduce fires by integrating information on fire emissions, atmospheric transport patterns, and population exposure to fine particulate matter (PM2.5). We use adjoint sensitivities to relate fire emissions to PM2.5 for a range of meteorological conditions and find that a Business-As-Usual scenario of land use change leads, on average, to 36,000 excess deaths per year into the foreseeable future (the next several decades) across the region. These deaths are largely preventable with fire reduction strategies, such as blocking fires in peatlands, industrial concessions, or protected areas, which reduce the health burden by 66, 45, and 14%, respectively. The effectiveness of these different strategies in mitigating human health impacts depends on the location of fires relative to the population distribution. For example, protecting peatlands through eliminating all fires on such lands would prevent on average 24,000 excess deaths per year into the foreseeable future across the region because, in addition to storing large amounts of fuel, many peatlands are located directly upwind of densely populated areas. We also demonstrate how this framework can be used to prioritize restoration locations for the Indonesian Peatland Restoration Agency based on their ability to reduce pollution exposure and health burden. This scientific framework is publicly available through an online decision support tool that allows stakeholders to readily determine the public health benefits of different land management strategies.

Creating a Lowland and Peatland Landscape Digital Terrain Model (DTM) from Interpolated Partial Coverage LiDAR Data for Central Kalimantan and East Sumatra, Indonesia

Coastal lowland areas support much of the world population on only a small part of its terrestrial surface. Yet these areas face rapidly increasing land surface subsidence and flooding, and are most vulnerable to future sea level rise. The accurate and up to date digital terrain models (DTMs) that are required to predict and manage such risks are absent in many of the areas affected, especially in regions where populations are least developed economically and may be least resilient to such changes. Airborne LiDAR is widely seen as the most accurate data type for elevation mapping but can be prohibitively expensive, as are detailed field surveys across a broad geographic scale. We present an economical method that utilizes airborne LiDAR data along parallel flight lines (‘strips’) covering between 10% and 35% of the land depending on terrain characteristics, and manual interpolation. We present results for lowland areas in Central Kalimantan and East Sumatra (Indonesia), for which no accurate DTM currently exists. The study areas are covered with forest, plantations and agricultural land, on mineral soils and peatlands. The method is shown to yield DTM differences within 0.5 m, relative to full coverage LiDAR data, for 87.7–96.4% of the land surface in a range of conditions in 15 validation areas, and within 1.0 m for 99.3% of the area overall. After testing, the method was then applied to the entire eastern coastal zone of Sumatra, yielding a DTM at 100 m spatial resolution covering 7.1 Mha of lowland area from 1.45 Mha of effective LiDAR coverage. The DTM shows that 36.3%, or 2.6 Mha, of this area is below 2 m +MSL and, therefore, at risk of flooding in the near future as sea level rise continues. This DTM product is available for use in flood risk mapping, peatland mapping and other applications.

Increased fire hazard in human-modified wetlands in Southeast Asia

Vast areas of wetlands in Southeast Asia are undergoing a transformation process to human-modified ecosystems. Expansion of agricultural cropland and forest plantations changes the landscape of wetlands. Here we present observation-based modelling evidence of increased fire hazard due to canalization in tropical wetland ecosystems. Two wetland conditions were tested in South Sumatra, Indonesia, natural drainage and canal drainage, using a hydrological model and a drought-fire index (modified Keetch-Byram index). Our results show that canalization has amplified fire susceptibility by 4.5 times. Canal drainage triggers the fire season to start earlier than under natural wetland conditions, indicating that the canal water level regime is a key variable controlling fire hazard. Furthermore, the findings derived from the modelling experiment have practical relevance for public and private sectors, as well as for water managers and policy makers, who deal with canalization of tropical wetlands, and suggest that improved water management can reduce fire susceptibility.

Smoke radiocarbon measurements from Indonesian fires provide evidence for burning of millennia-aged peat

In response to a strong El Niño, fires in Indonesia during September and October 2015 released a large amount of carbon dioxide and created a massive regional smoke cloud that severely degraded air quality in many urban centers across Southeast Asia. Although several lines of evidence indicate that peat burning was a dominant contributor to emissions in the region, El Niño-induced drought is also known to increase deforestation fires and agricultural waste burning in plantations. As a result, uncertainties remain with respect to partitioning emissions among different ecosystem and fire types. Here we measured the radiocarbon content (¹⁴C) of carbonaceous aerosol samples collected in Singapore from September 2014 through October 2015, with the aim of identifying the age and origin of fire-emitted fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm). The Δ¹⁴C of fire-emitted aerosol was -76 ± 51‰, corresponding to a carbon pool of combusted organic matter with a mean turnover time of 800 ± 420 y. Our observations indicated that smoke plumes reaching Singapore originated primarily from peat burning (∼85%), and not from deforestation fires or waste burning. Atmospheric transport modeling confirmed that fires in Sumatra and Borneo were dominant contributors to elevated PM_2.5 in Singapore during the fire season. The mean age of the carbonaceous aerosol, which predates the Industrial Revolution, highlights the importance of improving peatland fire management during future El Niño events for meeting climate mitigation and air quality commitments.

Fine Particle Emissions From Tropical Peat Fires Decrease Rapidly With Time Since Ignition

Southeast Asia experiences frequent fires in fuel-rich tropical peatlands, leading to extreme episodes of regional haze with high concentrations of fine particulate matter (PM_2.5) impacting human health. In a study published recently, the first field measurements of PM_2.5 emission factors for tropical peat fires showed larger emissions than from other fuel types. Here we report even higher PM_2.5 emission factors, measured at newly ignited peat fires in Malaysia, suggesting that current estimates of fine particulate emissions from peat fires may be underestimated by a factor of 3 or more. In addition, we use both field and laboratory measurements of burning peat to provide the first mechanistic explanation for the high variability in PM_2.5 emission factors, demonstrating that buildup of a surface ash layer causes the emissions of PM_2.5 to decrease as the peat fire progresses. This finding implies that peat fires are more hazardous (in terms of aerosol emissions) when first ignited than when still burning many days later. Varying emission factors for PM_2.5 also have implications for our ability to correctly model the climate and air quality impacts downwind of the peat fires. For modelers able to implement a time-varying emission factor, we recommend an emission factor for PM_2.5 from newly ignited tropical peat fires of 58 g of PM_2.5 per kilogram of dry fuel consumed (g/kg), reducing exponentially at a rate of 9%/day. If the age of the fire is unknown or only a single value may be used, we recommend an average value of 24 g/kg.

Spatial evaluation of Indonesia's 2015 fire-affected area and estimated carbon emissions using Sentinel-1

Fires raged once again across Indonesia in the latter half of 2015, creating a state of emergency due to poisonous smoke and haze across Southeast Asia as well as incurring great financial costs to the government. A strong El Niño-Southern Oscillation (ENSO) led to drought in many parts of Indonesia, resulting in elevated fire occurrence comparable with the previous catastrophic event in 1997/1998. Synthetic Aperture Radar (SAR) data promise to provide improved detection of land use and land cover changes in the tropics as compared to methodologies dependent upon cloud- and haze-free images. This study presents the first spatially explicit estimates of burned area across Sumatra, Kalimantan, and West Papua based on high-resolution Sentinel-1A SAR imagery. Here, we show that 4,604,569 hectares (ha) were burned during the 2015 fire season (overall accuracy 84%), and compare this with other existing operational burned area products (MCD64, GFED4.0, GFED4.1s). Intersection of burned area with fine-scale land cover and peat layer maps indicates that 0.89 gigatons carbon dioxide equivalents (Gt CO₂ e) were released through the fire event. This result is compared to other estimates based on nonspatially explicit thermal anomaly measurements or atmospheric monitoring. Using freely available SAR C-band data from the Sentinel mission, we argue that the presented methodology is able to quickly and precisely detect burned areas, supporting improvement in fire control management as well as enhancing accuracy of emissions estimation.

In the line of fire: the peatlands of Southeast Asia

Peatlands are a significant component of the global carbon (C) cycle, yet despite their role as a long-term C sink throughout the Holocene, they are increasingly vulnerable to destabilization. Nowhere is this shift from sink to source happening more rapidly than in Southeast Asia, and nowhere else are the combined pressures of land-use change and fire on peatland ecosystem C dynamics more evident nor the consequences more apparent. This review focuses on the peatlands of this region, tracing the link between deforestation and drainage and accelerating C emissions arising from peat mineralization and fire. It focuses on the implications of the recent increase in fire occurrence for air quality, human health, ecosystem resilience and the global C cycle. The scale and controls on peat-driven C emissions are addressed, noting that although fires cause large, temporary peaks in C flux to the atmosphere, year-round emissions from peat mineralization are of a similar magnitude. The review concludes by advocating land management options to reduce future fire risk as part of wider peatland management strategies, while also proposing that this region's peat fire dynamic could become increasingly relevant to northern peatlands in a warming world.This article is part of the themed issue 'The interaction of fire and mankind'.

Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird)

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.

Indonesian fire activity and smoke pollution in 2015 show persistent nonlinear sensitivity to El Niño-induced drought

The 2015 fire season and related smoke pollution in Indonesia was more severe than the major 2006 episode, making it the most severe season observed by the NASA Earth Observing System satellites that go back to the early 2000s, namely active fire detections from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS), MODIS aerosol optical depth, Terra Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO), Aqua Atmospheric Infrared Sounder (AIRS) CO, Aura Ozone Monitoring Instrument (OMI) aerosol index, and Aura Microwave Limb Sounder (MLS) CO. The MLS CO in the upper troposphere showed a plume of pollution stretching from East Africa to the western Pacific Ocean that persisted for 2 mo. Longer-term records of airport visibility in Sumatra and Kalimantan show that 2015 ranked after 1997 and alongside 1991 and 1994 as among the worst episodes on record. Analysis of yearly dry season rainfall from the Tropical Rainfall Measurement Mission (TRMM) and rain gauges shows that, due to the continued use of fire to clear and prepare land on degraded peat, the Indonesian fire environment continues to have nonlinear sensitivity to dry conditions during prolonged periods with less than 4 mm/d of precipitation, and this sensitivity appears to have increased over Kalimantan. Without significant reforms in land use and the adoption of early warning triggers tied to precipitation forecasts, these intense fire episodes will reoccur during future droughts, usually associated with El Niño events.