An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor

Disentangling the veil line for Brazilian biodiversity: An overview from two long-term research programs reveals huge gaps in ecological data reporting

The lack of synthesized information regarding biodiversity is a major problem among researchers, leading to a pervasive cycle where ecologists make field campaigns to collect information that already exists and yet has not been made available for a broader audience. This problem leads to long-lasting effects in public policies such as spending money multiple times to conduct similar studies in the same area. We aim to identify this knowledge gap by synthesizing information available regarding two Brazilian long-term biodiversity programs and the metadata generated by them. Using a unique dataset containing 1904 metadata, we identified patterns of metadata distribution and intensity of research conducted in Brazil, as well as where we should concentrate research efforts in the next decades. We found that the majority of metadata were about vertebrates, followed by plants, invertebrates, and fungi. Caatinga was the biome with least metadata, and that there's still a lack of information regarding all biomes in Brazil, with none of them being sufficiently sampled. We hope that these results will have implications for broader conservation and management guiding, as well as to funding allocation programs.

Mapping safe drinking water use in low- and middle-income countries

Safe drinking water access is a human right, but data on safely managed drinking water services (SMDWS) is lacking for more than half of the global population. We estimate SMDWS use in 135 low- and middle-income countries (LMICs) at subnational levels with a geospatial modeling approach, combining existing household survey data with available global geospatial datasets. We estimate that only one in three people used SMDWS in LMICs in 2020 and identified fecal contamination as the primary limiting factor affecting almost half of the population of LMICs. Our results are relevant for raising awareness about the challenges and limitations of current global monitoring approaches and demonstrating how globally available geospatial data can be leveraged to fill data gaps and identify priority areas in LMICs.

Quantifying the fluxes of carbon loss from an undrained tropical peatland ecosystem in Indonesia

Conservation of undrained tropical peatland ecosystems is critical for climate change mitigation as they store a tremendous amount of soil carbon that is preserved under anoxic water-logged conditions. Unfortunately, there are too few measurements of carbon fluxes from these ecosystems to estimate the climate change mitigation potential from such conservation efforts. Here, we measured carbon dioxide (CO2) and methane (CH4) fluxes as well as fluvial organic carbon export over the peat swamp forest within an undrained tropical peatland landscape in East Kalimantan, Indonesia. Our measurements throughout one year (Oct 2022-Sep 2023) showed that despite its water-logged condition, peat and water overlying the swamp forest on average emits 11.02 ± 0.49 MgCO2 ha-1 yr-1 of CO2 and 0.58 ± 0.04 MgCO2e ha-1 yr-1 of CH4. Further, the fluvial organic carbon export contributes to additional carbon loss of 1.68 ± 0.06 MgCO2e ha-1 yr-1. Our results help improve the accuracy of carbon accounting from undrained tropical peatlands, where we estimated a total carbon loss of 13.28 ± 0.50 MgCO2e ha-1 yr-1. Nevertheless, the total carbon loss reported from our sites is about half than what is reported from the drained peatland landscapes in the region and resulted in a larger onsite carbon sink potential estimate compared to other undrained peat swamp forests. Together, these findings indicate that conserving the remaining undrained peatland ecosystems in Indonesia from drainage and degradation is a promising natural climate solution strategy that avoids significant carbon emissions.

Tree species occurring in Amazonian wetland forests consistently show broader range sizes and niche breadths than trees in upland forests

Generally, species with broad niches also show large range sizes. We investigated the relationship between hydrological niche breadth and geographic range size for Amazonian tree species seeking to understand the role of habitat specialization to Amazonian wetlands and upland forests on the current distribution of tree species. We obtained 571,092 valid occurrence points from GBIF and SpeciesLink to estimate the range size and the niche breadth of 76% of all known Amazonian tree species (5150 tree species). Hydrological niche breadth was measured on different unidimensional axes defined by (1) total annual precipitation; (2) precipitation seasonality; (3) actual evapotranspiration; and (4) water table depth. Geographic range sizes were estimated using alpha-hull adjustments. General linear models were used to relate niche breadth to range size while contrasting tree species occurring and not occurring in wetlands. The hydrological niche breadth of Amazonian tree species varied mostly along the water table depth axis. The average range size for an Amazonian tree species was 751,000 km2 (median of 154,000 km2 and standard deviation of 1,550,000 km2). Niche breadth-range size relationships for Amazonian tree species were positive for all models, and the explanatory power of the models improved when including whether a species occurred in wetlands or in terrestrial uplands. Wetland species had steeper positive slopes for the niche breadth-range size relationship, and consistently larger range sizes for a given niche breadth. Amazonian tree species varied strongly in hydrological niche breadth and range size, but most species had narrow niche breadths and range sizes. Our results suggest that the South American riverscape may have been acting as a corridor for species dispersal in the Neotropical lowlands.

Spatial distribution of degradation and deforestation of palm swamp peatlands and associated carbon emissions in the Peruvian Amazon

The vast peat deposits in the Peruvian Amazon are crucial to the global climate. Palm swamp, the most extensive regional peatland ecosystem faces different threats, including deforestation and degradation due to felling of the dominant palm Mauritia flexuosa for fruit harvesting. While these activities convert this natural C sink into a source, the distribution of degradation and deforestation in this ecosystem and related C emissions remain unstudied. We used remote sensing data from Landsat, ALOS-PALSAR, and NASA's GEDI spaceborne LiDAR-derived products to map palm swamp degradation and deforestation within a 28 Mha area of the lowland Peruvian Amazon in 1990-2007 and 2007-2018. We combined this information with a regional peat map, C stock density data and peat emission factors to determine (1) peatland C stocks of peat-forming ecosystems (palm swamp, herbaceous swamp, pole forest), and (2) areas of palm swamp peatland degradation and deforestation and associated C emissions. In the 6.9 ± 0.1 Mha of predicted peat-forming ecosystems within the larger 28 Mha study area, 73% overlaid peat (5.1 ± 0.9 Mha) and stored 3.88 ± 0.12 Pg C. Degradation and deforestation in palm swamp peatlands totaled 535,423 ± 8,419 ha over 1990-2018, with a pronounced dominance for degradation (85%). The degradation rate increased 15% from 15,400 ha y-1 (1990-2007) to 17,650 ha y-1 (2007-2018) and the deforestation rate more than doubled from 1,900 ha y-1 to 4,200 ha y-1. Over 1990-2018, emissions from degradation amounted to 26.3 ± 3.5 Tg C and emissions from deforestation were 12.9 ± 0.5 Tg C. The 2007-2018 emission rate from both biomass and peat loss of 1.9 Tg C yr-1 is four times the average biomass loss rate due to gross deforestation in 2010-2019 reported for the hydromorphic Peruvian Amazon. The magnitude of emissions calls for the country to account for deforestation and degradation of peatlands in national reporting.

Wetland health assessment using DPSI framework: a case study in Kolkata Metropolitan Area

Wetlands are among the most valuable components of the ecosystem, playing an important role in preventing floods, maintaining the hydrological cycle, protecting against natural hazards, and controlling local weather conditions and ecological restoration. The Kolkata Metropolitan Area (KMA) is considered one of the most ecologically valuable regions in terms of wetland ecosystem, but due to haphazard development and human activities, the wetlands of the city are under constant threat of degradation. Therefore, this study aims to assess the factors responsible for wetland health and their dynamics using Driving Force-Pressure-State-Impact (DPSI) framework. To assess wetland health during 2011-2020, seventeen indicators and four sub-indicators were selected to calculate weights using the analytic hierarchy process (AHP). The results showed that most of the municipalities in the healthy category were in the pressure (P) section in 2011, while fluctuations were observed in the impact (I) section in several wards during 2011-20. The condition section (S) showed the overall change in the water, vegetation, and built-up categories from 2011 to 2020, so the most dominant category was "healthy," followed by "unhealthy" and "poor." The highly significant factors worsening wetland health were population density (B1), road density (B3), per capita wastewater generation (B5), per capita solid waste generation (B7), biological oxygen demand (D1a), dissolved oxygen (D1b), pH (D1c), and total coliform (D1d). The results of the study can help develop sustainable conservation and management of the wetland ecosystem in the KMA urban area and at the global level with similar geographical conditions.

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%-18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.

Mapping global non-floodplain wetlands

Non-floodplain wetlands - those located outside the floodplains - have emerged as integral components to watershed resilience, contributing hydrologic and biogeochemical functions affecting watershed-scale flooding extent, drought magnitude, and water-quality maintenance. However, the absence of a global dataset of non-floodplain wetlands limits their necessary incorporation into water quality and quantity management decisions and affects wetland-focused wildlife habitat conservation outcomes. We addressed this critical need by developing a publicly available "Global NFW" (Non-Floodplain Wetland) dataset, comprised of a global river-floodplain map at 90 m resolution coupled with a global ensemble wetland map incorporating multiple wetland-focused data layers. The floodplain, wetland, and non-floodplain wetland spatial data developed here were successfully validated within 21 large and heterogenous basins across the conterminous United States. We identified nearly 33 million potential non-floodplain wetlands with an estimated global extent of over 16×106 km2. Non-floodplain wetland pixels comprised 53% of globally identified wetland pixels, meaning the majority of the globe's wetlands likely occur external to river floodplains and coastal habitats. The identified global NFWs were typically small (median 0.039 km2), with a global median size ranging from 0.018-0.138 km2. This novel geospatial Global NFW static dataset advances wetland conservation and resource-management goals while providing a foundation for global non-floodplain wetland functional assessments, facilitating non-floodplain wetland inclusion in hydrological, biogeochemical, and biological model development. The data are freely available through the United States Environmental Protection Agency's Environmental Dataset Gateway (https://gaftp.epa.gov/EPADataCommons/ORD/Global_NonFloodplain_Wetlands/, last access: 24 May 2023) and through https://doi.org/10.23719/1528331 (Lane et al., 2023a).

A synthesis of hydroclimatic, ecological, and socioeconomic data for transdisciplinary research in the Mekong

The Mekong River basin (MRB) is a transboundary basin that supports livelihoods of over 70 million inhabitants and diverse terrestrial-aquatic ecosystems. This critical lifeline for people and ecosystems is under transformation due to climatic stressors and human activities (e.g., land use change and dam construction). Thus, there is an urgent need to better understand the changing hydrological and ecological systems in the MRB and develop improved adaptation strategies. This, however, is hampered partly by lack of sufficient, reliable, and accessible observational data across the basin. Here, we fill this long-standing gap for MRB by synthesizing climate, hydrological, ecological, and socioeconomic data from various disparate sources. The data- including groundwater records digitized from the literature-provide crucial insights into surface water systems, groundwater dynamics, land use patterns, and socioeconomic changes. The analyses presented also shed light on uncertainties associated with various datasets and the most appropriate choices. These datasets are expected to advance socio-hydrological research and inform science-based management decisions and policymaking for sustainable food-energy-water, livelihood, and ecological systems in the MRB.

The High-Elevation Peatlands of the Northern Andes, Colombia

Andean peatlands are important carbon reservoirs for countries in the northern Andes and have a unique diversity. Peatland plant diversity is generally related to hydrology and water chemistry, and the response of the vegetation in tropical high-elevation peatlands to changes in elevation, climate, and disturbance is poorly understood. Here, we address the questions of what the main vegetation types of peat-forming vegetation in the northern Andes are, and how the different vegetation types are related to water chemistry and pH. We measured plant diversity in 121 peatlands. We identified a total of 264 species, including 124 bryophytes and 140 vascular plants. We differentiated five main vegetation types: cushion plants, Sphagnum, true mosses, sedges, and grasses. Cushion-dominated peatlands are restricted to elevations above 4000 m. Variation in peatland vegetation is mostly driven be elevation and water chemistry. Encroachment of sedges and Sphagnum sancto-josephense in disturbed sites was associated with a reduction in soil carbon. We conclude that peatland variation is driven first by elevation and climate followed by water chemistry and human disturbances. Sites with higher human disturbances had lower carbon content. Peat-forming vegetation in the northern Andes was unique to each site bringing challenges on how to better conserve them and the ecosystem services they offer.

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

BACKGROUND

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well.

RESULTS

Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites.

CONCLUSIONS

Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

Soil CO2 and CH4 fluxes from different forest types in tropical peat swamp forest

Information on temporal and spatial variations in soil greenhouse gas (GHG) fluxes from tropical peat forests is essential to predict the influence of climate change and estimate the effects of land use on global warming and the carbon (C) cycle. To obtain such basic information, soil carbon dioxide (CO2) and methane (CH4) fluxes, together with soil physicochemical properties and environmental variables, were measured at three major forest types in the Maludam National Park, Sarawak, Malaysia, for eight years, and their relationships were analyzed. Annual soil CO2 fluxes ranged from 860 to 1450 g C m⁻2 yr⁻1 without overall significant differences between the three forest sites, while soil CH4 fluxes, 1.2-10.8 g C m⁻2 yr⁻1, differed. Differences in GHG fluxes between dry and rainy seasons were not necessarily significant, corresponding to the extent of seasonal variation in groundwater level (GWL). The lack of significant differences in soil CO2 fluxes between the three sites could be attributed to set-off between the negative and positive effects of the decomposability of soil organic matter as estimated by pyrophosphate solubility index (PSI) and GWL. The impact of El-Niño on annual CO2 flux also varied between the sites. The variation in soil CH4 fluxes from the three sites was enhanced by variations in temperature, GWL, PSI, and soil iron (Fe) content. A positive correlation was observed between the annual CH4 flux and GWL at only one site, and the influence of soil properties was more pronounced at the site with the lowest GWL and the highest PSI. Variation in annual CH4 fluxes was controlled more strongly by temperature where GWL was the highest and GWL and plant growth fluctuations were the least. Inter-annual variations in soil CO2 and CH4 fluxes confirmed the importance of long-term monitoring of these at multiple sites supporting different forest types.

Oil palm (Elaeis guineensis) plantation on tropical peatland in South East Asia: Photosynthetic response to soil drainage level for mitigation of soil carbon emissions

While existing moratoria in Indonesia and Malaysia should preclude continued large-scale expansion of palm oil production into new areas of South-East Asian tropical peatland, existing plantations in the region remain a globally significant source of atmospheric carbon due to drainage driven decomposition of peatland soils. Previous studies have made clear the direct link between drainage depth and peat carbon decomposition and significant reductions in the emission rate of CO₂ can be made by raising water tables nearer to the soil surface. However, the impact of such changes on palm fruit yield is not well understood and will be a critical consideration for plantation managers. Here we take advantage of very high frequency, long-term monitoring of canopy-scale carbon exchange at a mature oil palm plantation in Malaysian Borneo to investigate the relationship between drainage level and photosynthetic uptake and consider the confounding effects of light quality and atmospheric vapour pressure deficit. Canopy modelling from our dataset demonstrated that palms were exerting significantly greater stomatal control at deeper water table depths (WTD) and the optimum WTD for photosynthesis was found to be between 0.3 and 0.4 m below the soil surface. Raising WTD to this level, from the industry typical drainage level of 0.6 m, could increase photosynthetic uptake by 3.6 % and reduce soil surface emission of CO₂ by 11 %. Our study site further showed that despite being poorly drained compared to other planting blocks at the same plantation, monthly fruit bunch yield was, on average, 14 % greater. While these results are encouraging, and at least suggest that raising WTD closer to the soil surface to reduce emissions is unlikely to produce significant yield penalties, our results are limited to a single study site and more work is urgently needed to confirm these results at other plantations.

Extensive global wetland loss over the past three centuries

Wetlands have long been drained for human use, thereby strongly affecting greenhouse gas fluxes, flood control, nutrient cycling and biodiversity^1,2. Nevertheless, the global extent of natural wetland loss remains remarkably uncertain³. Here, we reconstruct the spatial distribution and timing of wetland loss through conversion to seven human land uses between 1700 and 2020, by combining national and subnational records of drainage and conversion with land-use maps and simulated wetland extents. We estimate that 3.4 million km² (confidence interval 2.9-3.8) of inland wetlands have been lost since 1700, primarily for conversion to croplands. This net loss of 21% (confidence interval 16-23%) of global wetland area is lower than that suggested previously by extrapolations of data disproportionately from high-loss regions. Wetland loss has been concentrated in Europe, the United States and China, and rapidly expanded during the mid-twentieth century. Our reconstruction elucidates the timing and land-use drivers of global wetland losses, providing an improved historical baseline to guide assessment of wetland loss impact on Earth system processes, conservation planning to protect remaining wetlands and prioritization of sites for wetland restoration⁴.

Small Body, Large Chromosomes: Centric Fusions Shaped the Karyotype of the Amazonian Miniature Fish Nannostomus anduzei (Characiformes, Lebiasinidae)

Miniature refers to species with extraordinarily small adult body size when adult and can be found within all major metazoan groups. It is considered that miniature species have experienced severe alteration of numerous morphological traits during evolution. For a variety of reasons, including severe labor concerns during collecting, chromosomal acquisition, and taxonomic issues, miniature fishes are neglected and understudied. Since some available studies indicate possible relationship between diploid chromosome number (2n) and body size in fishes, we aimed to study one of the smallest Neotropical fish Nannostomus anduzei (Teleostei, Characiformes, Lebiasinidae), using both conventional (Giemsa staining, C-banding) and molecular cytogenetic methods (FISH mapping of rDNAs, microsatellites, and telomeric sequences). Our research revealed that N. anduzei possesses one of the lowest diploid chromosome numbers (2n = 22) among teleost fishes, and its karyotype is entirely composed of large metacentric chromosomes. All chromosomes, except for pair number 11, showed an 18S rDNA signal in the pericentromeric region. 5S rDNA signals were detected in the pericentromeric regions of chromosome pair number 1 and 6, displaying synteny to 18S rDNA signals. Interstitial telomeric sites (ITS) were identified in the centromeric region of pairs 6 and 8, indicating that centric fusions played a significant role in karyotype evolution of studied species. Our study provides further evidence supporting the trend of diploid chromosome number reduction along with miniaturization of adult body size in fishes.

Coupled abiotic-biotic cycling of nitrous oxide in tropical peatlands

Atmospheric nitrous oxide (N2O) is a potent greenhouse gas thought to be mainly derived from microbial metabolism as part of the denitrification pathway. Here we report that in unexplored peat soils of Central and South America, N2O production can be driven by abiotic reactions (≤98%) highly competitive to their enzymatic counterparts. Extracted soil iron positively correlated with in situ abiotic N2O production determined by isotopic tracers. Moreover, we found that microbial N2O reduction accompanied abiotic production, essentially closing a coupled abiotic-biotic N2O cycle. Anaerobic N2O consumption occurred ubiquitously (pH 6.4-3.7), with proportions of diverse clade II N2O reducers increasing with consumption rates. Our findings show that denitrification in tropical peat soils is not a purely biological process but rather a 'mosaic' of abiotic and biotic reduction reactions. We predict that hydrological and temperature fluctuations differentially affect abiotic and biotic drivers and further contribute to the high N2O flux variation in the region.

Preliminary biological data of Sahel wetland ecosystems in Burkina Faso: Implications for ecological health assessment

Birds, amphibians, fish, and macroinvertebrates are useful indicators of ecological conditions and ensure considerable conservation value and tools for decision making in management of wetland ecosystems. However, the use of these organisms to monitor wetland ecosystems has rarely been explored in Western Africa. Whereas, we are currently facing to growing multiple anthropogenic pressures and climate warming that impact negatively our wetlands and the biodiversity. Notably, there is an urgent need of cost-effective tools for wetland ecosystems health assessment in Burkina Faso. In this study, we examined the taxonomic composition of birds, amphibians, fish, and macroinvertebrates and explored their potential use for monitoring wetland ecosystems. From our findings, measures of taxa composition and diversity respond to the gradients of anthropogenic alterations. Our results revealed that the highest diversity of fish and macroinvertebrates taxa was recorded in protected sites, whereas the lowest diversity was obtained in degraded sites. Additionally, the findings showed a strong and positive correlation between macroinvertebrates taxa and key water variables, whereas fish taxa were strongly correlated to xylal (deadwood) substrates. Most of bird’s species were recorded in tree-shrubs, and amphibians of protected wetlands were distinguished by identifying indicator taxa through indicator value index. African wetland ecosystems and biodiversity may be sustainably preserved through responsive monitoring programs of wetlands by limnologists.

Variation in carbon and nitrogen concentrations among peatland categories at the global scale

Peatlands account for 15 to 30% of the world's soil carbon (C) stock and are important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10-20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446-532 g kg-1) and lowest in intermediate and extremely rich fens (375-414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.

Peatland Loss in Southeast Asia Contributing to U.S. Biofuel's Greenhouse Gas Emissions

Land use change (LUC) induced by biofuel production could lead to greenhouse gas (GHG) emissions, which potentially increase biofuel's carbon intensity. Among the sources of LUC-related emissions for soy biodiesel, the contribution from peatland loss to agricultural plantations in Southeast Asia remains uncertain. Here, we analyzed LUC in Malaysia and Indonesia and modeled its impacts on the GHG emissions of soy biodiesel produced in the United States. It shows that oil palm plantations have more than doubled over 2001-2016 and the area of palm-on-peatlands (PoP) has expanded 3.7 times. Over new palm plantations, the share of PoP is about 19% regardless of time and location and the emission factor (EF) for peatland-to-palm conversion is estimated to be 41.5 Mg CO₂ ha^-1 yr^-1. With these updates on PoP and EF, the contribution of peatland loss (0.7-5.1 g CO₂e MJ^-1) to biodiesel emissions is only 40-65% of previous estimates, which reduces discrepancies among model simulations used by different agencies. Based on emerging evidence on LUC and related carbon changes, our analysis reexamines regional peatland loss and its impacts on LUC emissions modeling and provides new insights into the estimation of LUC impacts on biofuels' carbon intensity.

How can process-based modeling improve peat CO2 and N2O emission factors for oil palm plantations?

Oil palm plantations on peat and associated drainage generate sizeable GHG emissions. Current IPCC default emission factors (EF) for oil palm on organic soil are based on a very limited number of observations from young plantations, thereby resulting in large uncertainties in emissions estimates. To explore the potential of process-based modeling to refine oil palm peat CO₂ and N₂O EFs, we simulated peat GHG emissions and biogeophysical variables over 30 years in plantations of Central Kalimantan, Indonesia. The DNDC model simulated well the magnitude of C inputs (litterfall and root mortality) and dynamics of annual heterotrophic respiration and peat decomposition N₂O fluxes. The modeled peat onsite CO₂-C EF was lower than the IPCC default (11 Mg C ha^-1 yr^-1) and decreased from 7.7 ± 0.4 Mg C ha^-1 yr^-1 in the first decade to 3.0 ± 0.2 and 1.8 ± 0.3 Mg C ha^-1 yr^-1 in the second and third decades of the rotation. The modeled N₂O-N EF from peat decomposition was higher than the IPCC default (1.2 kg N ha^-1 yr^-1) and increased from 3.5 ± 0.3 kg N ha^-1 yr^-1 in the first decade to 4.7-4.6 ± 0.5 kg N ha^-1 yr^-1 in the following ones. Modeled fertilizer-induced N₂O emissions were minimal and much less than 1.6% of N inputs recommended by the IPCC in wet climates regardless of soil type. Temporal variations in EFs were strongly linked to soil C:N ratio and soil mineral N content for CO₂ and fertilizer-induced N₂O emissions, and to precipitation, water table level and soil NH₄⁺ content for peat decomposition N₂O emissions. These results suggest that current IPCC EFs for oil palm on organic soil could over-estimate peat onsite CO₂ emissions and underestimate peat decomposition N₂O emissions and that temporal variation in emissions should be considered for further improvement of EFs.

Accelerated migration of mangroves indicate large-scale saltwater intrusion in Amazon coastal wetlands

Saltwater intrusion can dramatically transform coastal ecosystems, changing vegetation and impacting wildlife and human communities who rely on these natural resources. This phenomenon is difficult to measure over large and remote areas but can be inferred from changes in the distribution of salt-tolerant vegetation, such as mangroves, observable from satellite imagery. The northern coast of Brazil has the largest continuous mangrove forest in the world and very low human occupation. Even so, saltwater intrusion and changes to the coastline have been reported in this region, with potential consequences for mangrove carbon storage and for local livelihoods, but this has not been quantified due to the remoteness of the area. This study measured changes in mangrove distribution along the Northern Brazil coast in the state of Amapá, covering ca. 15,000 km², over the last 38 years using Landsat satellite imagery. We found that mangrove area in this region is highly dynamic, with significant gains and losses occurring over the study period, but with an overall net gain of 157 km². Mangroves have been systematically expanding inland and this growth has accelerated close to the shoreline and at the head of tidal channels in the last two decades, indicating rapid and large-scale saltwater intrusion in this region. This phenomenon is likely driven by sea level rise, which also accelerated in this region in recent decades, but anthropogenic impacts such as buffalo grazing may also play an important role.

Gridded maps of wetlands dynamics over mid-low latitudes for 1980–2020 based on TOPMODEL

Dynamics of global wetlands are closely linked to biodiversity conservation, hydrology, and greenhouse gas emissions. However, long-term time series of global wetland products are still lacking. Using a diagnostic model based on the TOPography-based hydrological MODEL (TOPMODEL), this study produced an ensemble of 28 gridded maps of monthly global/regional wetland extents (with more reliable estimates at mid-low latitudes) for 1980–2020 at 0.25° × 0.25° spatial resolution, calibrated with a combination of four observation-based wetland data and seven gridded soil moisture reanalysis datasets. The gridded dynamic maps of wetlands capture the spatial distributions, seasonal cycles, and interannual variabilities of observed wetland extent well, and also show a good agreement with independent satellite-based terrestrial water storage estimates over wetland areas. The long temporal coverage extending beyond the era of satellite datasets, the global coverage, and the opportunity to provide real-time updates from ongoing soil moisture data make these products helpful for various applications such as analyzing the wetland-related methane emission.

Measurement(s)	wetland area
Technology Type(s)	computational modeling technique
Factor Type(s)	geographic location • temporal interval
Sample Characteristic - Environment	land
Sample Characteristic - Location	global

Gains in biodiversity conservation and ecosystem services from the expansion of the planet's protected areas

Protected areas safeguard biodiversity, ensure ecosystem functioning, and deliver ecosystem services to communities. However, only ~16% of the world's land area is under some form of protection, prompting international calls to protect at least 30% by 2030. We modeled the outcomes of achieving this 30 × 30 target for terrestrial biodiversity conservation, climate change mitigation, and nutrient regulation. We find that the additional ~2.8 million ha of habitat that would be protected would benefit 1134 ± 175 vertebrate species whose habitats currently lack any form of protection, as well as contribute to either avoided carbon emissions or carbon dioxide sequestration, equivalent to 10.9 ± 3.6 GtCO₂ year^-1 (28.4 ± 9.4% of the global nature-based climate-change mitigation potential). Furthermore, expansion of the protected area network would increase its ability to regulate water quality and mitigate nutrient pollution by 142.5 ± 31.0 MtN year^-1 (28.5 ± 6.2% of the global nutrient regulation potential).

Rewetting Tropical Peatlands Reduced Net Greenhouse Gas Emissions in Riau Province, Indonesia

Draining deforested tropical peat swamp forests (PSFs) converts greenhouse gas (GHG) sinks to sources and increases the likelihood of fire hazards. Rewetting deforested and drained PSFs before revegetation is expected to reverse this outcome. This study aims to quantify the GHG emissions of deforested PSFs that have been (a) reforested, (b) converted into oil palm, or (c) replanted with rubber. Before rewetting, heterotrophic soil respiration in reforested, oil palm, and rubber plantation areas were 48.91 ± 4.75 Mg CO2 ha−1 yr−1, 54.98 ± 1.53 Mg CO2 ha−1 yr−1, and 67.67 ± 2.13 Mg CO2 ha−1 yr−1, respectively. After rewetting, this decreased substantially by 21%, 36%, and 39%. Conversely, rewetting drained landscapes that used to be methane (CH4) sinks converted them into CH4 sources; almost twice as much methane was emitted after rewetting. Nitrous oxide (N2O) emissions tended to decrease; in nitrogen-rich rubber plantations, N2O emissions halved; in nitrogen-poor reforested areas, emissions reduced by up to a quarter after rewetting. Overall, rewetting reduced the net emissions up to 15.41 Mg CO2-eq ha−1 yr−1 (25%) in reforested, 18.36 Mg CO2-eq ha−1 yr−1 (18%) in oil palm, and 28.87 Mg CO2-eq ha−1 yr−1 (17%) in rubber plantation areas.

Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSMTrop,Nat) and drained (PEATCLSMTrop,Drain) tropical peatlands. Simulations with PEATCLSMTrop,Nat were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSMNorth,Nat) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSMTrop,Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSMTrop,Drain outperformed CLSM, PEATCLSMNorth,Nat, and PEATCLSMTrop,Nat over drained sites. Despite the overall improvements of PEATCLSMTrop,Nat over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.

A needle in a haystack: Integrative taxonomy reveals the existence of a new small species of fossorial frog (Anura, Microhylidae, Synapturanus) from the vast lower Putumayo basin, Peru

We describe a new species of microhylid frog of the genus Synapturanus from the lower Putumayo basin in Loreto, Perú. Specimens inhabited the soils of stunted pole forests growing on peat. The new species is distinguished from other species of Synapturanus through morphology, genetics, and acoustic characteristics. This species differs from most nominal congeners by having a head flat in lateral view (vs convex in the rest of species), a characteristic only shared by S. rabus and S. salseri. The new species can be distinguished from S. rabus and S. salseri by a combination of morphological characters and by having an advertisement call with a note length of 0.05–0.06 seconds (vs 0.03 seconds in S. rabus) and a dominant frequency ranging from 1.73 to 1.81 kHz (vs 1.10–1.47 kHz in S. salseri). Principal component analyses of 12 morphological characters and three acoustic variables further support differences between the new species and its described and undescribed congeners.

A global overview of studies about land management, land-use change, and climate change effects on soil organic carbon

Major drivers of gains or losses in soil organic carbon (SOC) include land management, land-use change, and climate change. Thousands of original studies have focused on these drivers of SOC change and are now compiled in a growing number of meta-analyses. To critically assess the research efforts in this domain, we retrieved and characterized 192 meta-analyses of SOC stocks or concentrations. These meta-analyses comprise more than 13,200 original studies conducted from 1910 to 2020 in 150 countries. First, we show that, despite a growing number of studies over time, the geographical coverage of studies is limited. For example, the effect of land management, land-use change, and climate change on SOC has been only occasionally studied in North and Central Africa, and in the Middle East and Central Asia. Second, the meta-analyses investigated a limited number of land management practices, mostly mineral fertilization, organic amendments, and tillage. Third, the meta-analyses demonstrated relatively low quality and transparency. Lastly, we discuss the mismatch between the increasing number of studies and the need for more local, reusable, and diversified knowledge on how to preserve high SOC stocks or restore depleted SOC stocks.

Phenology is the dominant control of methane emissions in a tropical non-forested wetland

Tropical wetlands are a significant source of atmospheric methane (CH₄), but their importance to the global CH₄ budget is uncertain due to a paucity of direct observations. Net wetland emissions result from complex interactions and co-variation between microbial production and oxidation in the soil, and transport to the atmosphere. Here we show that phenology is the overarching control of net CH₄ emissions to the atmosphere from a permanent, vegetated tropical swamp in the Okavango Delta, Botswana, and we find that vegetative processes modulate net CH₄ emissions at sub-daily to inter-annual timescales. Without considering the role played by papyrus on regulating the efflux of CH₄ to the atmosphere, the annual budget for the entire Okavango Delta, would be under- or over-estimated by a factor of two. Our measurements demonstrate the importance of including vegetative processes such as phenological cycles into wetlands emission budgets of CH₄.

Tropical wetlands are a significant but understudied source of methane. Here, methane emissions were measured over three years in a perennial tropical swamp in the Okavango Delta, Botswana, finding phenology was the overarching control of emissions.

An Overview of Remote Sensing Data Applications in Peatland Research Based on Works from the Period 2010–2021

In the 21st century, remote sensing (RS) has become increasingly employed in many environmental studies. This paper constitutes an overview of works utilising RS methods in studies on peatlands and investigates publications from the period 2010–2021. Based on fifty-nine case studies from different climatic zones (from subarctic to subtropical), we can indicate an increase in the use of RS methods in peatland research during the last decade, which is likely a result of the greater availability of new remote sensing data sets (Sentinel 1 and 2; Landsat 8; SPOT 6 and 7) paired with the rapid development of open-source software (ESA SNAP; QGIS and SAGA GIS). In the studied works, satellite data analyses typically encompassed the following elements: land classification/identification of peatlands, changes in water conditions in peatlands, monitoring of peatland state, peatland vegetation mapping, Gross Primary Productivity (GPP), and the estimation of carbon resources in peatlands. The most frequently employed research methods, on the other hand, included: vegetation indices, soil moisture indices, water indices, supervised classification and machine learning. Remote sensing data combined with field research is deemed helpful for peatland monitoring and multi-proxy studies, and they may offer new perspectives on research at a regional level.

Identifying Key Drivers of Peatland Fires Across Kalimantan's Ex-Mega Rice Project Using Machine Learning

Throughout Indonesia ecological degradation, agricultural expansion, and the digging of drainage canals has compromised the integrity and functioning of peatland forests. Fragmented landscapes of scrubland, cultivation, degraded forest, and newly established plantations are then susceptible to extensive fires that recur each year. However, a comprehensive understanding of all the drivers of fire distribution and the conditions of initiation is still absent. Here we show the first analysis in the region that encompasses a wide range of driving factors within a single model that captures the inter-annual variation, as well as the spatial distribution of peatland fires. We developed a fire susceptibility model using machine learning (XGBoost random forest) that characterizes the relationships between key predictor variables and the distribution of historic fire locations. We then determined the relative importance of each predictor variable in controlling the initiation and spread of fires. The model included land-cover classifications, a forest clearance index, vegetation indices, drought indices, distances to infrastructure, topography, and peat depth, as well as the Oceanic Niño Index (ONI). The model performance consistently scores highly in both accuracy and precision across all years (>75% and >67.5% respectively), though recall metrics are much lower (>25%). Our results confirm the anthropogenic dependence of extreme fires in the region, with distance to settlements and distance to canals consistently weighted the most important driving factors within the model structure. Our results may help target the root causes of fire initiation and propagation to better construct regulation and rehabilitation efforts to mitigate future fires.

Comparing GHG Emissions from Drained Oil Palm and Recovering Tropical Peatland Forests in Malaysia

For agricultural purposes, the drainage and deforestation of Southeast Asian peatland resulted in high greenhouse gases’ (GHGs, e.g., CO2, N2O and CH4) emission. A peatland regenerating initiative, by rewetting and vegetation restoration, reflects evidence of subsequent forest recovery. In this study, we compared GHG emissions from three Malaysian tropical peatland systems under the following different land-use conditions: (i) drained oil palm plantation (OP), (ii) rewetting-restored forest (RF) and (iii) undrained natural forest (NF). Biweekly temporal measurements of CO2, CH4 and N2O fluxes were conducted using a closed-chamber method from July 2017 to December 2018, along with the continuous measurement of environmental variables and a one-time measurement of the soil physicochemical properties. The biweekly emission data were integrated to provide cumulative fluxes using the trapezoidal rule. Our results indicated that the changes in environmental conditions resulting from draining (OP) or rewetting historically drained peatland (RF) affected CH4 and N2O emissions more than CO2 emissions. The cumulative CH4 emission was significantly higher in the forested sites (RF and NF), which was linked to their significantly higher water table (WT) level (p < 0.05). Similarly, the high cumulative CO2 emission trends at the RF and OP sites indicated that the RF rewetting-restored peatland system continued to have high decomposition rates despite having a significantly higher WT than the OP (p < 0.05). The highest cumulative N2O emission at the drained-fertilized OP and rewetting-restored RF sites was linked to the available substrates for high decomposition (low C/N ratio) together with soil organic matter mineralization that provided inorganic nitrogen (N), enabling ideal conditions for microbial mediated N2O emissions. Overall, the measured peat properties did not vary significantly among the different land uses. However, the lower C/N ratio at the OP and the RF sites indicated higher decomposition rates in the drained and historically drained peat than the undrained natural peat (NF), which was associated with high cumulative CO2 and N2O emissions in our study.

Degradation-driven changes in fine root carbon stocks, productivity, mortality, and decomposition rates in a palm swamp peat forest of the Peruvian Amazon

BACKGROUND

Amazon palm swamp peatlands are major carbon (C) sinks and reservoirs. In Peru, this ecosystem is widely threatened owing to the recurrent practice of cutting Mauritia flexuosa palms for fruit harvesting. Such degradation could significantly damage peat deposits by altering C fluxes through fine root productivity, mortality, and decomposition rates which contribute to and regulate peat accumulation. Along a same peat formation, we studied an undegraded site (Intact), a moderately degraded site (mDeg) and a heavily degraded site (hDeg) over 11 months. Fine root C stocks and fluxes were monthly sampled by sequential coring. Concomitantly, fine root decomposition was investigated using litter bags. In the experimental design, fine root stocks and dynamics were assessed separately according to vegetation type (M. flexuosa palm and other tree species) and M. flexuosa age class. Furthermore, results obtained from individual palms and trees were site-scaled by using forest composition and structure.

RESULTS

At the scale of individuals, fine root C biomass in M. flexuosa adults was higher at the mDeg site than at the Intact and hDeg sites, while in trees it was lowest at the hDeg site. Site-scale fine root biomass (Mg C ha-1) was higher at the mDeg site (0.58 ± 0.05) than at the Intact (0.48 ± 0.05) and hDeg sites (0.32 ± 0.03). Site-scale annual fine root mortality rate was not significantly different between sites (3.4 ± 1.3, 2.0 ± 0.8, 1.5 ± 0.7 Mg C ha-1 yr-1 at the Intact, mDeg, and hDeg sites) while productivity (same unit) was lower at the hDeg site (1.5 ± 0.8) than at the Intact site (3.7 ± 1.2), the mDeg site being intermediate (2.3 ± 0.9). Decomposition was slow with 63.5-74.4% of mass remaining after 300 days and it was similar among sites and vegetation types.

CONCLUSIONS

The significant lower fine root C stock and annual productivity rate at the hDeg site than at the Intact site suggests a potential for strong degradation to disrupt peat accretion. These results stress the need for a sustainable management of these forests to maintain their C sink function.

The current burden of Japanese encephalitis and the estimated impacts of vaccination: Combining estimates of the spatial distribution and transmission intensity of a zoonotic pathogen

Japanese encephalitis virus (JEV) is a major cause of neurological disability in Asia and causes thousands of severe encephalitis cases and deaths each year. Although Japanese encephalitis (JE) is a WHO reportable disease, cases and deaths are significantly underreported and the true burden of the disease is not well understood in most endemic countries. Here, we first conducted a spatial analysis of the risk factors associated with JE to identify the areas suitable for sustained JEV transmission and the size of the population living in at-risk areas. We then estimated the force of infection (FOI) for JE-endemic countries from age-specific incidence data. Estimates of the susceptible population size and the current FOI were then used to estimate the JE burden from 2010 to 2019, as well as the impact of vaccination. Overall, 1,543.1 million (range: 1,292.6-2,019.9 million) people were estimated to live in areas suitable for endemic JEV transmission, which represents only 37.7% (range: 31.6-53.5%) of the over four billion people living in countries with endemic JEV transmission. Based on the baseline number of people at risk of infection, there were an estimated 56,847 (95% CI: 18,003-184,525) JE cases and 20,642 (95% CI: 2,252-77,204) deaths in 2019. Estimated incidence declined from 81,258 (95% CI: 25,437-273,640) cases and 29,520 (95% CI: 3,334-112,498) deaths in 2010, largely due to increases in vaccination coverage which have prevented an estimated 314,793 (95% CI: 94,566-1,049,645) cases and 114,946 (95% CI: 11,421-431,224) deaths over the past decade. India had the largest estimated JE burden in 2019, followed by Bangladesh and China. From 2010-2019, we estimate that vaccination had the largest absolute impact in China, with 204,734 (95% CI: 74,419-664,871) cases and 74,893 (95% CI: 8,989-286,239) deaths prevented, while Taiwan (91.2%) and Malaysia (80.1%) had the largest percent reductions in JE burden due to vaccination. Our estimates of the size of at-risk populations and current JE incidence highlight countries where increasing vaccination coverage could have the largest impact on reducing their JE burden.

Japanese encephalitis is a vector-transmitted, zoonotic disease that is endemic throughout a large portion of Asia. Vaccination has significantly reduced the JE burden in several formerly high-burden countries, but vaccination coverage remains limited in several other countries with high JE burdens. A better understanding of both the spatial distribution and the magnitude of the burden in endemic countries is critical for future disease prevention efforts. To estimate the number of people living in areas within Asia suitable for JEV transmission we conducted a spatial analysis of the risk factors associated with JE. We estimate that over one billion people live in areas suitable for local JEV transmission. We then combined these population-at-risk estimates with estimates of the force of infection (FOI) to model the national-level burden of JE (annual cases and deaths) over the past decade. Increases in vaccination coverage have reduced JE incidence from over 80,000 cases in 2010 to fewer than 57,000 cases in 2019. We estimate that vaccination has prevented almost 315,000 cases and 115,000 deaths in the past decade. Our results also call attention to the countries, and high-risk areas within countries, where increases in vaccination coverage are most needed.

Improving Forest Baseline Maps in Tropical Wetlands Using GEDI-Based Forest Height Information and Sentinel-1

Remote Sensing-based global Forest/Non-Forest (FNF) masks have shown large inaccuracies in tropical wetland areas. This limits their applications for deforestation monitoring and alerting in which they are used as a baseline for mapping new deforestation. In radar-based deforestation monitoring, for example, moisture dynamics in unmasked non-forest areas can lead to false detections. We combined a GEDI Forest Height product and Sentinel-1 radar data to improve FNF masks in wetland areas in Gabon using a Random Forest model. The GEDI Forest Height, together with texture metrics derived from Sentinel-1 mean backscatter values, were the most important contributors to the classification. Quantitatively, our mask outperformed existing global FNF masks by increasing the Producer’s Accuracy for the non-forest class by 14%. The GEDI Forest Height product by itself also showed high accuracies but contained Landsat artifacts. Qualitatively, our model was best able to cleanly uncover non-forest areas and mitigate the impact of Landsat artifacts in the GEDI Forest Height product. An advantage of the methodology presented here is that it can be adapted for different application needs by varying the probability threshold of the Random Forest output. This study stresses that, in any application of the suggested methodology, it is important to consider the UA/PA trade-off and the effect it has on the classification. The targeted improvements for wetland forest mapping presented in this paper can help raise the accuracy of tropical deforestation monitoring.

Microbial Communities and Interactions of Nitrogen Oxides With Methanogenesis in Diverse Peatlands of the Amazon Basin

Tropical peatlands are hotspots of methane (CH₄) production but present high variation and emission uncertainties in the Amazon region. This is because the controlling factors of methane production in tropical peats are not yet well documented. Although inhibitory effects of nitrogen oxides (NO_x) on methanogenic activity are known from pure culture studies, the role of NO_x in the methane cycling of peatlands remains unexplored. Here, we investigated the CH₄ content, soil geochemistry and microbial communities along 1-m-soil profiles and assessed the effects of soil NO_x and nitrous oxide (N₂O) on methanogenic abundance and activity in three peatlands of the Pastaza-Marañón foreland basin. The peatlands were distinct in pH, DOC, nitrate pore water concentrations, C/N ratios of shallow soils, redox potential, and ¹³C enrichment in dissolved inorganic carbon and CH₄ pools, which are primarily contingent on H₂-dependent methanogenesis. Molecular 16S rRNA and mcrA gene data revealed diverse and novel methanogens varying across sites. Importantly, we also observed a strong stratification in relative abundances of microbial groups involved in NO_x cycling, along with a concordant stratification of methanogens. The higher relative abundance of ammonia-oxidizing archaea (Thaumarchaeota) in acidic oligotrophic peat than ammonia-oxidizing bacteria (Nitrospira) is noteworthy as putative sources of NO_x. Experiments testing the interaction of NO_x species and methanogenesis found that the latter showed differential sensitivity to nitrite (up to 85% reduction) and N₂O (complete inhibition), which would act as an unaccounted CH₄ control in these ecosystems. Overall, we present evidence of diverse peatlands likely differently affected by inhibitory effects of nitrogen species on methanogens as another contributor to variable CH₄ fluxes.

Geographic Setting and Groundwater Table Control Carbon Emission from Indonesian Peatland: A Meta-Analysis

Peat restoration is a key climate mitigation action for achieving Indonesia’s Nationally Determined Contribution (NDC) emission reduction target. The level of carbon reduction resulting from peat restoration is uncertain, owing in part to diverse methodologies and land covers. In this study, a meta-analysis was conducted to assess the impact of rewetting on reduction of total CO2 in soil and heterotrophic emissions at the country level. The tier 2 emission factor associated with the land cover category in Indonesia was also calculated. The analysis included a total of 32 studies with 112 observations (data points) for total CO2 emissions and 31 observations for heterotrophic emissions in Indonesia. The results show that the land cover category is not a significant predictor of heterotrophic and total soil emissions, but the highest observed soil emissions were found in the plantation forest. Using the random-effects model, our results suggest that an increase in the water table depth of 10 cm would result in an increase in total CO2 emissions of 2.7 Mg CO2 ha−1 year−1 and an increase in heterotrophic emissions of 2.3 Mg CO2 ha−1 year−1. Our findings show that managing water table depth in degraded peatlands in various land cover types is important to achieve Indonesia’s emission reduction target by 2030.

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.

Tropical peatlands and their contribution to the global carbon cycle and climate change

Peatlands are carbon-rich ecosystems that cover 185-423 million hectares (Mha) of the earth's surface. The majority of the world's peatlands are in temperate and boreal zones, whereas tropical ones cover only a total area of 90-170 Mha. However, there are still considerable uncertainties in C stock estimates as well as a lack of information about depth, bulk density and carbon accumulation rates. The incomplete data are notable especially in tropical peatlands located in South America, which are estimated to have the largest area of peatlands in the tropical zone. This paper displays the current state of knowledge surrounding tropical peatlands and their biophysical characteristics, distribution and carbon stock, role in the global climate, the impacts of direct human disturbances on carbon accumulation rates and greenhouse gas (GHG) emissions. Based on the new peat extension and depth data, we estimate that tropical peatlands store 152-288 Gt C, or about half of the global peatland emitted carbon. We discuss the knowledge gaps in research on distribution, depth, C stock and fluxes in these ecosystems which play an important role in the global carbon cycle and risk releasing large quantities of GHGs into the atmosphere (CO₂ and CH₄ ) when subjected to anthropogenic interferences (e.g., drainage and deforestation). Recent studies show that although climate change has an impact on the carbon fluxes of these ecosystems, the direct anthropogenic disturbance may play a greater role. The future of these systems as carbon sinks will depend on advancing current scientific knowledge and incorporating local understanding to support policies geared toward managing and conserving peatlands in vulnerable regions, such as the Amazon where recent records show increased forest fires and deforestation.

Paludiculture as a sustainable land use alternative for tropical peatlands: A review

Peatlands cover approximately 4.2 million km² of terrestrial land surface and store up to 700 Pg of terrestrial carbon. Preserving the carbon stocks in peatland is therefore crucial for climate change mitigation. Under natural conditions, peatland carbon storage is maintained by moist peat conditions, which decreases decomposition and encourages peat formation. However, conversion of peatlands to drainage-based agriculture in the form of industrial plantations and smallholder farming has resulted in globally significant greenhouse gas emissions. Paludiculture, loosely conceptualized as biomass production on wet peatlands with the potential to maintain carbon storage, is proposed as a sustainable, non-drainage-based agriculture alternative for peatland use. However, while the concept of paludiculture was developed in temperate ecoregions, its application in the tropics is poorly understood. In this review, we examine common definitions of paludiculture used in literature to derive key themes and future directions. We found three common themes: ecosystem services benefits of paludiculture, hydrological conditions of peatlands, and vegetation selection for planting. Ambiguities surrounding these themes have led to questions on whether paludiculture applications are sustainable in the context of carbon sequestration in peat soil. This review aims to evaluate and advance current understanding of paludiculture in the context of tropical peatlands, which is especially pertinent given expanding agriculture development into Central Africa and South America, where large reserves of peatlands were recently discovered.

Spatial and temporal variability of soil N2 O and CH4 fluxes along a degradation gradient in a palm swamp peat forest in the Peruvian Amazon

Mauritia flexuosa palm swamp, the prevailing Peruvian Amazon peatland ecosystem, is extensively threatened by degradation. The unsustainable practice of cutting whole palms for fruit extraction modifies forest's structure and composition and eventually alters peat-derived greenhouse gas (GHG) emissions. We evaluated the spatiotemporal variability of soil N₂ O and CH₄ fluxes and environmental controls along a palm swamp degradation gradient formed by one undegraded site (Intact), one moderately degraded site (mDeg) and one heavily degraded site (hDeg). Microscale variability differentiated hummocks supporting live or cut palms from surrounding hollows. Macroscale analysis considered structural changes in vegetation and soil microtopography as impacted by degradation. Variables were monitored monthly over 3 years to evaluate intra- and inter-annual variability. Degradation induced microscale changes in N₂ O and CH₄ emission trends and controls. Site-scale average annual CH₄ emissions were similar along the degradation gradient (225.6 ± 50.7, 160.5 ± 65.9 and 169.4 ± 20.7 kg C ha^-1  year^-1 at the Intact, mDeg and hDeg sites, respectively). Site-scale average annual N₂ O emissions (kg N ha^-1  year^-1 ) were lower at the mDeg site (0.5 ± 0.1) than at the Intact (1.3 ± 0.6) and hDeg sites (1.1 ± 0.4), but the difference seemed linked to heterogeneous fluctuations in soil water-filled pore space (WFPS) along the forest complex rather than to degradation. Monthly and annual emissions were mainly controlled by variations in WFPS, water table level (WT) and net nitrification for N₂ O; WT, air temperature and net nitrification for CH₄ . Site-scale N₂ O emissions remained steady over years, whereas CH₄ emissions rose exponentially with increased precipitation. While the minor impact of degradation on palm swamp peatland N₂ O and CH₄ fluxes should be tested elsewhere, the evidenced large and variable CH₄ emissions and significant N₂ O emissions call for improved modeling of GHG dynamics in tropical peatlands to test their response to climate changes.

A Bornean peat swamp forest is a net source of carbon dioxide to the atmosphere

Tropical peat forests are a globally important reservoir of carbon, but little is known about CO₂ exchange on an annual basis. We measured CO₂ exchange between the atmosphere and tropical peat swamp forest in Sarawak, Malaysia using the eddy covariance technique over 4 years from 2011 to 2014. The CO₂ fluxes varied between seasons and years. A small carbon uptake took place during the rainy season at the beginning of 2011, while a substantial net efflux of >600 g C/m² occurred over a 2 month period in the middle of the dry season. Conversely, the peat ecosystem was a source of carbon during both the dry and rainy seasons in subsequent years and more carbon was lost during the rainy season relative to the dry season. Our results demonstrate that the forest was a net source of CO₂ to the atmosphere during every year of measurement with annual efflux ranging from 183 to 632 g C m^-2  year^-1 , noting that annual flux values were sensitive to gap filling methodology. This is in contrast to the typical view of tropical peat forests which must have acted as net C sinks over time scales of centuries to millennia to create the peat deposits. Path analyses revealed that the gross primary productivity (GPP) and ecosystem respiration (RE) were primarily affected by vapour pressure deficit (VPD). Results suggest that future increases in VPD could further reduce the C sink strength and result in additional net CO₂ losses from this tropical peat swamp forest in the absence of plant acclimation to such changes in atmospheric dryness.

A global map of terrestrial habitat types

We provide a global, spatially explicit characterization of 47 terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for quantifying species' Area of Habitat. We produced this novel habitat map for the year 2015 by creating a global decision tree that intersects the best currently available global data on land cover, climate and land use. We independently validated the map using occurrence data for 828 species of vertebrates (35152 point plus 8181 polygonal occurrences) and 6026 sampling sites. Across datasets and mapped classes we found on average a balanced accuracy of 0.77 ([Formula: see text]0.14 SD) at Level 1 and 0.71 ([Formula: see text]0.15 SD) at Level 2, while noting potential issues of using occurrence records for validation. The maps broaden our understanding of habitats globally, assist in constructing area of habitat refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments. Periodic updates are planned as better or more recent data becomes available.

Impact of forest plantation on methane emissions from tropical peatland

Tropical peatlands are a known source of methane (CH4 ) to the atmosphere, but their contribution to atmospheric CH4 is poorly constrained. Since the 1980s, extensive areas of the peatlands in Southeast Asia have experienced land-cover change to smallholder agriculture and forest plantations. This land-cover change generally involves lowering of groundwater level (GWL), as well as modification of vegetation type, both of which potentially influence CH4 emissions. We measured CH4 exchanges at the landscape scale using eddy covariance towers over two land-cover types in tropical peatland in Sumatra, Indonesia: (a) a natural forest and (b) an Acacia crassicarpa plantation. Annual CH4 exchanges over the natural forest (9.1 ± 0.9 g CH4  m-2  year-1 ) were around twice as high as those of the Acacia plantation (4.7 ± 1.5 g CH4  m-2  year-1 ). Results highlight that tropical peatlands are significant CH4 sources, and probably have a greater impact on global atmospheric CH4 concentrations than previously thought. Observations showed a clear diurnal variation in CH4 exchange over the natural forest where the GWL was higher than 40 cm below the ground surface. The diurnal variation in CH4 exchanges was strongly correlated with associated changes in the canopy conductance to water vapor, photosynthetic photon flux density, vapor pressure deficit, and air temperature. The absence of a comparable diurnal pattern in CH4 exchange over the Acacia plantation may be the result of the GWL being consistently below the root zone. Our results, which are among the first eddy covariance CH4 exchange data reported for any tropical peatland, should help to reduce the uncertainty in the estimation of CH4 emissions from a globally important ecosystem, provide a more complete estimate of the impact of land-cover change on tropical peat, and develop science-based peatland management practices that help to minimize greenhouse gas emissions.

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.

Peatland Governance: The Problem of Depicting in Sustainability Governance, Regulatory Law, and Economic Instruments

Limiting global warming to well below 2 degrees Celsius and better even to 1.5 degrees Celsius, according to Article 2 paragraph 1 of the Paris Agreement requires global zero emissions in a very short time. These targets imply that not only emissions from degraded peatlands have to be avoided, but conservation and rewetting of peatlands are also necessary to figure as sinks to compensate for unavoidable residual emissions. However, with regard to instruments for meeting these targets, measuring, depicting, and baseline definition are difficult for greenhouse gas emissions from peatlands. In the absence of an easily comprehensible control variable (such as fossil fuels), economic instruments reach their limits. This is remarkable in so far as economic instruments can otherwise handle governance problems and react to various behavioral motivational factors very well. Still, peatlands can be subject to certain regulations and prohibitions under command-and-control law even without precise knowledge of the emissions from peatland use, which will be shown using the example of the European Union (EU) and German legislation. This paper is a contribution to governance research and illustrates that even comprehensive quantity-control instruments for fossil fuels and livestock farming—which would address various environmental problems and reflect findings from behavioral research regarding motivation towards sustainability—require complementary fine-tuning through command-and-control law, e.g., for integrating peatland governance.

Emerging challenges for sustainable development and forest conservation in Sarawak, Borneo

The forests of Borneo-the third largest island on the planet-sustain some of the highest biodiversity and carbon storage in the world. The forests also provide vital ecosystem services and livelihood support for millions of people in the region, including many indigenous communities. The Pan-Borneo Highway and several hydroelectric dams are planned or already under construction in Sarawak, a Malaysian state comprising part of the Borneo. This development seeks to enhance economic growth and regional connectivity, support community access to services, and promote industrial development. However, the implications of the development of highway and dams for forest integrity, biodiversity and ecosystem services remained largely unreported. We assessed these development projects using fine-scale biophysical and environmental data and found several environmental and socioeconomic risks associated with the projects. The highway and hydroelectric dam projects will impact 32 protected areas including numerous key habitats of threatened species such as the proboscis monkey (Nasalis larvatus), Sarawak surili (Presbytis chrysomelas), Bornean orangutans (Pongo pygmaeus) and tufted ground squirrel (Rheithrosciurus macrotis). Under its slated development trajectory, the local and trans-national forest connectivity between Malaysian Borneo and Indonesian Borneo would also be substantially diminished. Nearly ~161 km of the Pan-Borneo Highway in Sarawak will traverse forested landscapes and ~55 km will traverse carbon-rich peatlands. The 13 hydroelectric dam projects will collectively impact ~1.7 million ha of forest in Sarawak. The consequences of planned highway and hydroelectric dams construction will increase the carbon footprint of development in the region. Moreover, many new road segments and hydroelectric dams would be built on steep slopes in high-rainfall zones and forested areas, increasing both construction and ongoing maintenance costs. The projects would also alter livelihood activities of downstream communities, risking their long-term sustainability. Overall, our findings identify major economic, social and environmental risks for several planned road segments in Sarawak-such as those between Telok Melano and Kuching; Sibu and Bintulu; and in the Lambir, Limbang and Lawas regions-and dam projects-such as Tutoh, Limbang, Lawas, Baram, Linau, Ulu Air and Baleh dams. Such projects need to be reviewed to ensure they reflect Borneo's unique environmental and forest ecosystem values, the aspirations of local communities and long-term sustainability of the projects rather than being assessed solely on their short-term economic returns.

Characteristics, Main Impacts, and Stewardship of Natural and Artificial Freshwater Environments: Consequences for Biodiversity Conservation

In this overview (introductory article to a special issue including 14 papers), we consider all main types of natural and artificial inland freshwater habitas (fwh). For each type, we identify the main biodiversity patterns and ecological features, human impacts on the system and environmental issues, and discuss ways to use this information to improve stewardship. Examples of selected key biodiversity/ecological features (habitat type): narrow endemics, sensitive (groundwater and GDEs); crenobionts, LIHRes (springs); unidirectional flow, nutrient spiraling (streams); naturally turbid, floodplains, large-bodied species (large rivers); depth-variation in benthic communities (lakes); endemism and diversity (ancient lakes); threatened, sensitive species (oxbow lakes, SWE); diverse, reduced littoral (reservoirs); cold-adapted species (Boreal and Arctic fwh); endemism, depauperate (Antarctic fwh); flood pulse, intermittent wetlands, biggest river basins (tropical fwh); variable hydrologic regime—periods of drying, flash floods (arid-climate fwh). Selected impacts: eutrophication and other pollution, hydrologic modifications, overexploitation, habitat destruction, invasive species, salinization. Climate change is a threat multiplier, and it is important to quantify resistance, resilience, and recovery to assess the strategic role of the different types of freshwater ecosystems and their value for biodiversity conservation. Effective conservation solutions are dependent on an understanding of connectivity between different freshwater ecosystems (including related terrestrial, coastal and marine systems).