Benefits of tropical peatland rewetting for subsidence reduction and forest regrowth: results from a large-scale restoration trial

Drainage and deforestation of tropical peat swamp forests (PSF) in Southeast Asia cause carbon emissions and biodiversity loss of global concern. Restoration efforts to mitigate these impacts usually involve peatland rewetting by blocking canals. However, there have been no studies to date of the optimal rewetting approach that will reduce carbon emission whilst also promoting PSF regeneration. Here we present results of a large-scale restoration trial in Sumatra (Indonesia), monitored for 7.5 years. Water levels in a former plantation were raised over an area of 4800 ha by constructing 257 compacted peat dams in canals. We find peat surface subsidence rates in the rewetted restoration area and adjoining PSF to be halved where water tables were raised from ~ - 0.6 m to ~ - 0.3 m, demonstrating the success of rewetting in reducing carbon emission. A total of 57 native PSF tree species were found to spontaneously grow in the most rewetted conditions and in high densities, indicating that forest regrowth is underway. Based on our findings we propose that an effective PSF restoration strategy should follow stepwise rewetting to achieve substantial carbon emission reduction alongside unassisted regrowth of PSF, thereby enabling the peat, forest and canal vegetation to establish a new nature-based ecosystem balance.

DeltaDTM: A global coastal digital terrain model

Coastal elevation data are essential for a wide variety of applications, such as coastal management, flood modelling, and adaptation planning. Low-lying coastal areas (found below 10 m +Mean Sea Level (MSL)) are at risk of future extreme water levels, subsidence and changing extreme weather patterns. However, current freely available elevation datasets are not sufficiently accurate to model these risks. We present DeltaDTM, a global coastal Digital Terrain Model (DTM) available in the public domain, with a horizontal spatial resolution of 1 arcsecond (∼30 m) and a vertical mean absolute error (MAE) of 0.45 m overall. DeltaDTM corrects CopernicusDEM with spaceborne lidar from the ICESat-2 and GEDI missions. Specifically, we correct the elevation bias in CopernicusDEM, apply filters to remove non-terrain cells, and fill the gaps using interpolation. Notably, our classification approach produces more accurate results than regression methods recently used by others to correct DEMs, that achieve an overall MAE of 0.72 m at best. We conclude that DeltaDTM will be a valuable resource for coastal flood impact modelling and other applications.

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.

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'.

Variable carbon losses from recurrent fires in drained tropical peatlands

Tropical peatland fires play a significant role in the context of global warming through emissions of substantial amounts of greenhouse gases. However, the state of knowledge on carbon loss from these fires is still poorly developed with few studies reporting the associated mass of peat consumed. Furthermore, spatial and temporal variations in burn depth have not been previously quantified. This study presents the first spatially explicit investigation of fire-driven tropical peat loss and its variability. An extensive airborne Light Detection and Ranging data set was used to develop a prefire peat surface modelling methodology, enabling the spatially differentiated quantification of burned area depth over the entire burned area. We observe a strong interdependence between burned area depth, fire frequency and distance to drainage canals. For the first time, we show that relative burned area depth decreases over the first four fire events and is constant thereafter. Based on our results, we revise existing peat and carbon loss estimates for recurrent fires in drained tropical peatlands. We suggest values for the dry mass of peat fuel consumed that are 206 t ha(-1) for initial fires, reducing to 115 t ha(-1) for second, 69 t ha(-1) for third and 23 t ha(-1) for successive fires, which are 58-7% of the current IPCC Tier 1 default value for all fires. In our study area, this results in carbon losses of 114, 64, 38 and 13 t C ha(-1) for first to fourth fires, respectively. Furthermore, we show that with increasing proximity to drainage canals both burned area depth and the probability of recurrent fires increase and present equations explaining burned area depth as a function of distance to drainage canal. This improved knowledge enables a more accurate approach to emissions accounting and will support IPCC Tier 2 reporting of fire emissions.

Autism and suicidality: Review of risk factors in literature

Introduction

There is emerging evidence that suicide and suicidal behavior frequently occur in people with autistic spectrum disorders (ASD), although this topic is largely understudied. We have little understanding of suicidal behavior among individuals with ASD and there are no empirical data to guide practitioners in the treatment of suicidality in persons with ASD. There is a need to investigate risk factors associated with suicidal behavior in persons with ASD, to improve prevention strategies and interventions.

Objectives

To get an overview from literature of risk factors for suicidality in individuals with ASD.

Methods

Review of the literature using Cochrane Collaboration Centre, Embase, Medline, PsychINFO, PubMed, and Web of Science.

Results

In the literature, we found that, among already known risk factors like comorbid depression, an underlying vulnerability in personality may be a risk factor for suicidal behavior. Several studies showed that a high score on the temperament factor ‘novelty seeking’ and ‘harm avoidance’ is associated with suicidality. In other studies, where suicidality was not an object of study, adults with ASD showed high scores on ‘harm avoidance’ and low scores on ‘novelty seeking’. This suggests that personality profiles may be of predictive value for suicidality in adults with ASD. A study proposal focused on this possible association be presented.

Disclosure of interest

The authors have not supplied their declaration of competing interest.