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.

Genes and genome-resolved metagenomics reveal the microbial functional make up of Amazon peatlands under geochemical gradients

The Pastaza-Marañón Foreland Basin (PMFB) holds the most extensive tropical peatland area in South America. PMFB peatlands store ~7.07 Gt of organic carbon interacting with multiple microbial heterotrophic, methanogenic, and other aerobic/anaerobic respirations. Little is understood about the contribution of distinct microbial community members inhabiting tropical peatlands. Here, we studied the metagenomes of three geochemically distinct peatlands spanning minerotrophic, mixed, and ombrotrophic conditions. Using gene- and genome-centric approaches, we evaluate the functional potential of the underlying microbial communities. Abundance analyses show significant differences in C, N, P, and S acquisition genes. Furthermore, community interactions mediated by toxin-antitoxin and CRISPR-Cas systems were enriched in oligotrophic soils, suggesting that non-metabolic interactions may exert additional controls in low-nutrient environments. Additionally, we reconstructed 519 metagenome-assembled genomes spanning 28 phyla. Our analyses detail key differences across the geochemical gradient in the predicted microbial populations involved in degradation of organic matter, and the cycling of N and S. Notably, we observed differences in the nitric oxide (NO) reduction strategies between sites with high and low N2 O fluxes and found phyla putatively capable of both NO and sulfate reduction. Our findings detail how gene abundances and microbial populations are influenced by geochemical differences in tropical peatlands.

Hotspots of geogenic arsenic and manganese contamination in groundwater of the floodplains in lowland Amazonia (South America)

Arsenic enrichment in groundwater resources in deltas and floodplains of large sediment-rich rivers is a worldwide natural hazard to human health. High spatial variability of arsenic concentrations in affected river basins limits cost-effective mitigation strategies. Linking the chemical composition of groundwater with the topography and fluvial geomorphology is a promising approach for predicting arsenic pollution on a regional scale. Here we correlate the distribution of arsenic contaminated wells with the fluvial dynamics in the Amazon basin. Groundwater was sampled from tube wells along the Amazon River and its main tributaries in three distinct regions in Peru and Brazil. For each sample, the major and trace element concentrations were analyzed, and the position of the well within the sedimentary structure was determined. The results show that aquifers in poorly weathered sediments deposited by sediment-rich rivers are prone to mobilization and accumulation of aqueous arsenic and manganese, both in sub-Andean foreland basins, and in floodplains downstream. Two zones at risk are distinguished: aquifers in the channel-dominated part of the floodplain (CDF) and aquifers in the overbank deposits on the less-dynamic part of the floodplain (LDF). Some 70 % of the wells located on the CDF and 20 % on the LDF tap groundwater at concentrations exceeding the WHO guideline of 10 μg/L arsenic (max. 430 μg/L), and 70 % (CDF) and 50 % (LDF) exceeded 0.4 mg/L manganese (max. 6.6 mg/L). None of the water samples located outside the actual floodplain of sediment-rich rivers, or on riverbanks of sediment-poor rivers exceed 5 μg/L As, and only 4 % exceeded 0.4 mg/L Mn. The areas of highest risk can be delineated using satellite imagery. We observe similar patterns as in affected river basins in South and Southeast Asia indicating a key role of sedimentation processes and fluvial geomorphology in priming arsenic and manganese contamination in aquifers.

Testing the Contribution of Multi-Source Remote Sensing Features for Random Forest Classification of the Greater Amanzule Tropical Peatland

Tropical peatlands such as Ghana's Greater Amanzule peatland are highly valuable ecosystems and under great pressure from anthropogenic land use activities. Accurate measurement of their occurrence and extent is required to facilitate sustainable management. A key challenge, however, is the high cloud cover in the tropics that limits optical remote sensing data acquisition. In this work we combine optical imagery with radar and elevation data to optimise land cover classification for the Greater Amanzule tropical peatland. Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission (SRTM) imagery were acquired and integrated to drive a machine learning land cover classification using a random forest classifier. Recursive feature elimination was used to optimize high-dimensional and correlated feature space and determine the optimal features for the classification. Six datasets were compared, comprising different combinations of optical, radar and elevation features. Results showed that the best overall accuracy (OA) was found for the integrated Sentinel-2, Sentinel-1 and SRTM dataset (S2+S1+DEM), significantly outperforming all the other classifications with an OA of 94%. Assessment of the sensitivity of land cover classes to image features indicated that elevation and the original Sentinel-1 bands contributed the most to separating tropical peatlands from other land cover types. The integration of more features and the removal of redundant features systematically increased classification accuracy. We estimate Ghana's Greater Amanzule peatland covers 60,187 ha. Our proposed methodological framework contributes a robust workflow for accurate and detailed landscape-scale monitoring of tropical peatlands, while our findings provide timely information critical for the sustainable management of the Greater Amanzule peatland.

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.

Wide-Area Near-Real-Time Monitoring of Tropical Forest Degradation and Deforestation Using Sentinel-1

The use of Sentinel-1 (S1) radar for wide-area, near-real-time (NRT) tropical-forest-change monitoring is discussed, with particular attention to forest degradation and deforestation. Since forest change can relate to processes ranging from high-impact, large-scale conversion to low-impact, selective logging, and can occur in sites having variable topographic and environmental properties such as mountain slopes and wetlands, a single approach is insufficient. The system introduced here combines time-series analysis of small objects identified in S1 data, i.e., segments containing linear features and apparent small-scale disturbances. A physical model is introduced for quantifying the size of small (upper-) canopy gaps. Deforestation detection was evaluated for several forest landscapes in the Amazon and Borneo. Using the default system settings, the false alarm rate (FAR) is very low (less than 1%), and the missed detection rate (MDR) varies between 1.9% ± 1.1% and 18.6% ± 1.0% (90% confidence level). For peatland landscapes, short radar detection delays up to several weeks due to high levels of soil moisture may occur, while, in comparison, for optical systems, detection delays up to 10 months were found due to cloud cover. In peat swamp forests, narrow linear canopy gaps (road and canal systems) could be detected with an overall accuracy of 85.5%, including many gaps barely visible on hi-res SPOT-6/7 images, which were used for validation. Compared to optical data, subtle degradation signals are easier to detect and are not quickly lost over time due to fast re-vegetation. Although it is possible to estimate an effective forest-cover loss, for example, due to selective logging, and results are spatiotemporally consistent with Sentinel-2 and TerraSAR-X reference data, quantitative validation without extensive field data and/or large hi-res radar datasets, such as TerraSAR-X, remains a challenge.

First Evidence of Peat Domes in the Congo Basin using LiDAR from a Fixed-Wing Drone

The world’s most extensive tropical peatlands occur in the Cuvette Centrale depression in the Congo Basin, which stores 30.6 petagrams of carbon (95% CI, 6.3–46.8). Improving our understanding of the genesis, development and functioning of these under-studied peatlands requires knowledge of their topography and, in particular, whether the peat surface is domed, as this implies a rain-fed system. Here we use a laser altimeter mounted on an unmanned airborne vehicle (UAV) to measure peat surface elevation along two transects at the edges of a peatland, in the northern Republic of Congo, to centimetre accuracy and compare the results with an analysis of nearby satellite LiDAR data (ICESat and ICESat-2). The LiDAR elevations on both transects show an upward slope from the peatland edge, suggesting a surface elevation peak of around 1.8 m over ~20 km. While modest, this domed shape is consistent with the peatland being rainfed. In-situ peat depth measurements and our LiDAR results indicate that this peatland likely formed at least 10,000 years BP in a large shallow basin ~40 km wide and ~3 m deep.

Methanogens and Methanotrophs Show Nutrient-Dependent Community Assemblage Patterns Across Tropical Peatlands of the Pastaza-Marañón Basin, Peruvian Amazonia

Tropical peatlands are globally important carbon reservoirs that play a crucial role in fluxes of atmospheric greenhouse gases. Amazon peatlands are expected to be large source of atmospheric methane (CH₄) emissions, however little is understood about the rates of CH₄ flux or the microorganisms that mediate it in these environments. Here we studied a mineral nutrient gradient across peatlands in the Pastaza-Marañón Basin, the largest tropical peatland in South America, to describe CH₄ fluxes and environmental factors that regulate species assemblages of methanogenic and methanotrophic microorganisms. Peatlands were grouped as minerotrophic, mixed and ombrotrophic categories by their general water source leading to different mineral nutrient content (rich, mixed and poor) quantified by trace elements abundance. Microbial communities clustered dependent on nutrient content (ANOSIM p < 0.001). Higher CH₄ flux was associated with minerotrophic communities compared to the other categories. The most dominant methanogens and methanotrophs were represented by Methanobacteriaceae, and Methylocystaceae, respectively. Weighted network analysis demonstrated tight clustering of most methanogen families with minerotrophic-associated microbial families. Populations of Methylocystaceae were present across all peatlands. Null model testing for species assemblage patterns and species rank distributions confirmed non-random aggregations of Methylococcacae methanotroph and methanogen families (p < 0.05). We conclude that in studied amazon peatlands increasing mineral nutrient content provides favorable habitats for Methanobacteriaceae, while Methylocystaceae populations seem to broadly distribute independent of nutrient content.

Potential shift from a carbon sink to a source in Amazonian peatlands under a changing climate

Amazonian peatlands store a large amount of soil organic carbon (SOC), and its fate under a future changing climate is unknown. Here, we use a process-based peatland biogeochemistry model to quantify the carbon accumulation for peatland and nonpeatland ecosystems in the Pastaza-Marañon foreland basin (PMFB) in the Peruvian Amazon from 12,000 y before present to AD 2100. Model simulations indicate that warming accelerates peat SOC loss, while increasing precipitation accelerates peat SOC accumulation at millennial time scales. The uncertain parameters and spatial variation of climate are significant sources of uncertainty to modeled peat carbon accumulation. Under warmer and presumably wetter conditions over the 21st century, SOC accumulation rate in the PMFB slows down to 7.9 (4.3-12.2) g⋅C⋅m-2⋅y-1 from the current rate of 16.1 (9.1-23.7) g⋅C⋅m-2⋅y-1, and the region may turn into a carbon source to the atmosphere at -53.3 (-66.8 to -41.2) g⋅C⋅m-2⋅y-1 (negative indicates source), depending on the level of warming. Peatland ecosystems show a higher vulnerability than nonpeatland ecosystems, as indicated by the ratio of their soil carbon density changes (ranging from 3.9 to 5.8). This is primarily due to larger peatlands carbon stocks and more dramatic responses of their aerobic and anaerobic decompositions in comparison with nonpeatland ecosystems under future climate conditions. Peatland and nonpeatland soils in the PMFB may lose up to 0.4 (0.32-0.52) Pg⋅C by AD 2100 with the largest loss from palm swamp. The carbon-dense Amazonian peatland may switch from a current carbon sink into a source in the 21st century.

Ecosystem state shifts during long-term development of an Amazonian peatland

The most carbon (C)-dense ecosystems of Amazonia are areas characterized by the presence of peatlands. However, Amazonian peatland ecosystems are poorly understood and are threatened by human activities. Here, we present an investigation into long-term ecohydrological controls on C accumulation in an Amazonian peat dome. This site is the oldest peatland yet discovered in Amazonia (peat initiation ca. 8.9 ka BP), and developed in three stages: (i) peat initiated in an abandoned river channel with open water and aquatic plants; (ii) inundated forest swamp; and (iii) raised peat dome (since ca. 3.9 ka BP). Local burning occurred at least three times in the past 4,500 years. Two phases of particularly rapid C accumulation (ca. 6.6-6.1 and ca. 4.9-3.9 ka BP), potentially resulting from increased net primary productivity, were seemingly driven by drier conditions associated with widespread drought events. The association of drought phases with major ecosystem state shifts (open water wetland-forest swamp-peat dome) suggests a potential climatic control on the developmental trajectory of this tropical peatland. A third drought phase centred on ca. 1.8-1.1 ka BP led to markedly reduced C accumulation and potentially a hiatus during the peat dome stage. Our results suggest that future droughts may lead to phases of rapid C accumulation in some inundated tropical peat swamps, although this can lead ultimately to a shift to ombrotrophy and a subsequent return to slower C accumulation. Conversely, in ombrotrophic peat domes, droughts may lead to reduced C accumulation or even net loss of peat. Increased surface wetness at our site in recent decades may reflect a shift towards a wetter climate in western Amazonia. Amazonian peatlands represent important carbon stores and habitats, and are important archives of past climatic and ecological information. They should form key foci for conservation efforts.

Age, extent and carbon storage of the central Congo Basin peatland complex

Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 10¹⁵ grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation.

First discovery of Holocene cryptotephra in Amazonia

The use of volcanic ash layers for dating and correlation (tephrochronology) is widely applied in the study of past environmental changes. We describe the first cryptotephra (non-visible volcanic ash horizon) to be identified in the Amazon basin, which is tentatively attributed to a source in the Ecuadorian Eastern Cordillera (0-1°S, 78-79°W), some 500-600 km away from our field site in the Peruvian Amazon. Our discovery 1) indicates that the Amazon basin has been subject to volcanic ash fallout during the recent past; 2) highlights the opportunities for using cryptotephras to date palaeoenvironmental records in the Amazon basin and 3) indicates that cryptotephra layers are preserved in a dynamic Amazonian peatland, suggesting that similar layers are likely to be present in other peat sequences that are important for palaeoenvironmental reconstruction. The discovery of cryptotephra in an Amazonian peatland provides a baseline for further investigation of Amazonian tephrochronology and the potential impacts of volcanism on vegetation.

Tropical wetlands: A missing link in the global carbon cycle?

Tropical wetlands are not included in Earth system models, despite being an important source of methane (CH₄) and contributing a large fraction of carbon dioxide (CO₂) emissions from land use, land use change, and forestry in the tropics. This review identifies a remarkable lack of data on the carbon balance and gas fluxes from undisturbed tropical wetlands, which limits the ability of global change models to make accurate predictions about future climate. We show that the available data on in situ carbon gas fluxes in undisturbed forested tropical wetlands indicate marked spatial and temporal variability in CO₂ and CH₄ emissions, with exceptionally large fluxes in Southeast Asia and the Neotropics. By upscaling short-term measurements, we calculate that approximately 90 ± 77 Tg CH₄ year^-1 and 4540 ± 1480 Tg CO₂ year^-1 are released from tropical wetlands globally. CH₄ fluxes are greater from mineral than organic soils, whereas CO₂ fluxes do not differ between soil types. The high CO₂ and CH₄ emissions are mirrored by high rates of net primary productivity and litter decay. Net ecosystem productivity was estimated to be greater in peat-forming wetlands than on mineral soils, but the available data are insufficient to construct reliable carbon balances or estimate gas fluxes at regional scales. We conclude that there is an urgent need for systematic data on carbon dynamics in tropical wetlands to provide a robust understanding of how they differ from well-studied northern wetlands and allow incorporation of tropical wetlands into global climate change models.

Ecology of testate amoebae in an Amazonian peatland and development of a transfer function for palaeohydrological reconstruction

Tropical peatlands represent globally important carbon sinks with a unique biodiversity and are currently threatened by climate change and human activities. It is now imperative that proxy methods are developed to understand the ecohydrological dynamics of these systems and for testing peatland development models. Testate amoebae have been used as environmental indicators in ecological and palaeoecological studies of peatlands, primarily in ombrotrophic Sphagnum-dominated peatlands in the mid- and high-latitudes. We present the first ecological analysis of testate amoebae in a tropical peatland, a nutrient-poor domed bog in western (Peruvian) Amazonia. Litter samples were collected from different hydrological microforms (hummock to pool) along a transect from the edge to the interior of the peatland. We recorded 47 taxa from 21 genera. The most common taxa are Cryptodifflugia oviformis, Euglypha rotunda type, Phryganella acropodia, Pseudodifflugia fulva type and Trinema lineare. One species found only in the southern hemisphere, Argynnia spicata, is present. Arcella spp., Centropyxis aculeata and Lesqueresia spiralis are indicators of pools containing standing water. Canonical correspondence analysis and non-metric multidimensional scaling illustrate that water table depth is a significant control on the distribution of testate amoebae, similar to the results from mid- and high-latitude peatlands. A transfer function model for water table based on weighted averaging partial least-squares (WAPLS) regression is presented and performs well under cross-validation (r(2)(apparent)= 0.76, RMSE = 4.29; r(2)(jack)= 0.68, RMSEP =5.18). The transfer function was applied to a 1-m peat core, and sample-specific reconstruction errors were generated using bootstrapping. The reconstruction generally suggests near-surface water tables over the last 3,000 years, with a shift to drier conditions at c. cal. 1218-1273 AD.

Global patterns of groundwater table depth

Shallow groundwater affects terrestrial ecosystems by sustaining river base-flow and root-zone soil water in the absence of rain, but little is known about the global patterns of water table depth and where it provides vital support for land ecosystems. We present global observations of water table depth compiled from government archives and literature, and fill in data gaps and infer patterns and processes using a groundwater model forced by modern climate, terrain, and sea level. Patterns in water table depth explain patterns in wetlands at the global scale and vegetation gradients at regional and local scales. Overall, shallow groundwater influences 22 to 32% of global land area, including ~15% as groundwater-fed surface water features and 7 to 17% with the water table or its capillary fringe within plant rooting depths.