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 biodiversity1,2. 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.

Correction: Plasmids manipulate bacterial behaviour through translational regulatory crosstalk.

[This corrects the article DOI: 10.1371/journal.pbio.3001988.].

Global and regional drivers of land-use emissions in 1961-2017.

Historically, human uses of land have transformed and fragmented ecosystems1,2, degraded biodiversity3,4, disrupted carbon and nitrogen cycles5,6 and added prodigious quantities of greenhouse gases (GHGs) to the atmosphere7,8. However, in contrast to fossil-fuel carbon dioxide (CO2) emissions, trends and drivers of GHG emissions from land management and land-use change (together referred to as 'land-use emissions') have not been as comprehensively and systematically assessed. Here we present country-, process-, GHG- and product-specific inventories of global land-use emissions from 1961 to 2017, we decompose key demographic, economic and technical drivers of emissions and we assess the uncertainties and the sensitivity of results to different accounting assumptions. Despite steady increases in population (+144 per cent) and agricultural production per capita (+58 per cent), as well as smaller increases in emissions per land area used (+8 per cent), decreases in land required per unit of agricultural production (-70 per cent) kept global annual land-use emissions relatively constant at about 11 gigatonnes CO2-equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO2-equivalent per decade to 14.6 gigatonnes CO2-equivalent in 2017 (about 25 per cent of total anthropogenic GHG emissions). Although emissions intensity decreased in all regions, large differences across regions persist over time. The three highest-emitting regions (Latin America, Southeast Asia and sub-Saharan Africa) dominate global emissions growth from 1961 to 2017, driven by rapid and extensive growth of agricultural production and related land-use change. In addition, disproportionate emissions are related to certain products: beef and a few other red meats supply only 1 per cent of calories worldwide, but account for 25 per cent of all land-use emissions. Even where land-use change emissions are negligible or negative, total per capita CO2-equivalent land-use emissions remain near 0.5 tonnes per capita, suggesting the current frontier of mitigation efforts. Our results are consistent with existing knowledge-for example, on the role of population and economic growth and dietary choice-but provide additional insight into regional and sectoral trends.

Plasmids manipulate bacterial behaviour through translational regulatory crosstalk.

Beyond their role in horizontal gene transfer, conjugative plasmids commonly encode homologues of bacterial regulators. Known plasmid regulator homologues have highly targeted effects upon the transcription of specific bacterial traits. Here, we characterise a plasmid translational regulator, RsmQ, capable of taking global regulatory control in Pseudomonas fluorescens and causing a behavioural switch from motile to sessile lifestyle. RsmQ acts as a global regulator, controlling the host proteome through direct interaction with host mRNAs and interference with the host's translational regulatory network. This mRNA interference leads to large-scale proteomic changes in metabolic genes, key regulators, and genes involved in chemotaxis, thus controlling bacterial metabolism and motility. Moreover, comparative analyses found RsmQ to be encoded on a large number of divergent plasmids isolated from multiple bacterial host taxa, suggesting the widespread importance of RsmQ for manipulating bacterial behaviour across clinical, environmental, and agricultural niches. RsmQ is a widespread plasmid global translational regulator primarily evolved for host chromosomal control to manipulate bacterial behaviour and lifestyle.

A comprehensive quantification of global nitrous oxide sources and sinks.

Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

Growth hormone-releasing hormone receptor antagonist MIA-602 attenuates cardiopulmonary injury induced by BSL-2 rVSV-SARS-CoV-2 in hACE2 mice.

COVID-19 pneumonia causes acute lung injury and acute respiratory distress syndrome (ALI/ARDS) characterized by early pulmonary endothelial and epithelial injuries with altered pulmonary diffusing capacity and obstructive or restrictive physiology. Growth hormone-releasing hormone receptor (GHRH-R) is expressed in the lung and heart. GHRH-R antagonist, MIA-602, has been reported to modulate immune responses to bleomycin lung injury and inflammation in granulomatous sarcoidosis. We hypothesized that MIA-602 would attenuate rVSV-SARS-CoV-2-induced pulmonary dysfunction and heart injury in a BSL-2 mouse model. Male and female K18-hACE2tg mice were inoculated with SARS-CoV-2/USA-WA1/2020, BSL-2-compliant recombinant VSV-eGFP-SARS-CoV-2-Spike (rVSV-SARS-CoV-2), or PBS, and lung viral load, weight loss, histopathology, and gene expression were compared. K18-hACE2tg mice infected with rVSV-SARS-CoV-2 were treated daily with subcutaneous MIA-602 or vehicle and conscious, unrestrained plethysmography performed on days 0, 3, and 5 (n = 7 to 8). Five days after infection mice were killed, and blood and tissues collected for histopathology and protein/gene expression. Both native SARS-CoV-2 and rVSV-SARS-CoV-2 presented similar patterns of weight loss, infectivity (~60%), and histopathologic changes. Daily treatment with MIA-602 conferred weight recovery, reduced lung perivascular inflammation/pneumonia, and decreased lung/heart ICAM-1 expression compared to vehicle. MIA-602 rescued altered respiratory rate, increased expiratory parameters (Te, PEF, EEP), and normalized airflow parameters (Penh and Rpef) compared to vehicle, consistent with decreased airway inflammation. RNASeq followed by protein analysis revealed heightened levels of inflammation and end-stage necroptosis markers, including ZBP1 and pMLKL induced by rVSV-SARS-CoV-2, that were normalized by MIA-602 treatment, consistent with an anti-inflammatory and pro-survival mechanism of action in this preclinical model of COVID-19 pneumonia.

Multiple toxins and a protease contribute to the aphid-killing ability of Pseudomonas fluorescens PpR24.

Aphids are globally important pests causing damage to a broad range of crops. Due to insecticide resistance, there is an urgent need to develop alternative control strategies. In our previous work, we found Pseudomonas fluorescens PpR24 can orally infect and kill the insecticide-resistant green-peach aphid (Myzus persicae). However, the genetic basis of the insecticidal capability of PpR24 remains unclear. Genome sequencing of PpR24 confirmed the presence of various insecticidal toxins such as Tc (toxin complexes), Rhs (rearrangement hotspot) elements, and other insect-killing proteases. Upon aphids infection with PpR24, RNA-Seq analysis revealed 193 aphid genes were differentially expressed with down-regulation of 16 detoxification genes. In addition, 1325 PpR24 genes (542 were upregulated and 783 downregulated) were subject to differential expression, including genes responsible for secondary metabolite biosynthesis, the iron-restriction response, oxidative stress resistance, and virulence factors. Single and double deletion of candidate virulence genes encoding a secreted protease (AprX) and four toxin components (two TcA-like; one TcB-like; one TcC-like insecticidal toxins) showed that all five genes contribute significantly to aphid killing, particularly AprX. This comprehensive host-pathogen transcriptomic analysis provides novel insight into the molecular basis of bacteria-mediated aphid mortality and the potential of PpR24 as an effective biocontrol agent.

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems.

Climate warming is expected to increase global methane (CH4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH4 remain uncertain. Here, we use established drivers to hindcast changes in CH4 fluxes (FCH4 ) since the early 1980s. We trained a machine learning (ML) model on CH4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH4 , with increases in FCH4 of ca. 10% or higher found in the fall from 1981-1989 to 2010-2018. The annual trends were driven by increases during summer and fall, particularly at high-CH4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH4 (defined according to the 95th percentile of the daily FCH4 values over a reference period) have become more frequent during the last four decades and currently account for 10-40% of the total seasonal fluxes. The share of extreme FCH4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH4 emission seasons and boosting extreme emissions.

A new winter wheat genetic resource harbors untapped diversity from synthetic hexaploid wheat.

KEY MESSAGE: The NIAB_WW_SHW_NAM population, a large nested association mapping panel, is a useful resource for mapping QTL from synthetic hexaploid wheat that can improve modern elite wheat cultivars. The allelic richness harbored in progenitors of hexaploid bread wheat (Triticum aestivum L.) is a useful resource for addressing the genetic diversity bottleneck in modern cultivars. Synthetic hexaploid wheat (SHW) is created through resynthesis of the hybridisation events between the tetraploid (Triticum turgidum subsp. durum Desf.) and diploid (Aegilops tauschii Coss.) bread wheat progenitors. We developed a large and diverse winter wheat nested association mapping (NAM) population (termed the NIAB_WW_SHW_NAM) consisting of 3241 genotypes derived from 54 nested back-cross 1 (BC1) populations, each formed via back-crossing a different primary SHW into the UK winter wheat cultivar 'Robigus'. The primary SHW lines were created using 15 T. durum donors and 47 Ae. tauschii accessions that spanned the lineages and geographical range of the species. Primary SHW parents were typically earlier flowering, taller and showed better resistance to yellow rust infection (Yr) than 'Robigus'. The NIAB_WW_SHW_NAM population was genotyped using a single nucleotide polymorphism (SNP) array and 27 quantitative trait loci (QTLs) were detected for flowering time, plant height and Yr resistance. Across multiple field trials, a QTL for Yr resistance was found on chromosome 4D that corresponded to the Yr28 resistance gene previously reported in other SHW lines. These results demonstrate the value of the NIAB_WW_SHW_NAM population for genetic mapping and provide the first evidence of Yr28 working in current UK environments and genetic backgrounds. These examples, coupled with the evidence of commercial wheat breeders selecting promising genotypes, highlight the potential value of the NIAB_WW_SHW_NAM to variety improvement.

Fire frequency drives decadal changes in soil carbon and nitrogen and ecosystem productivity.

Fire frequency is changing globally and is projected to affect the global carbon cycle and climate. However, uncertainty about how ecosystems respond to decadal changes in fire frequency makes it difficult to predict the effects of altered fire regimes on the carbon cycle; for instance, we do not fully understand the long-term effects of fire on soil carbon and nutrient storage, or whether fire-driven nutrient losses limit plant productivity. Here we analyse data from 48 sites in savanna grasslands, broadleaf forests and needleleaf forests spanning up to 65 years, during which time the frequency of fires was altered at each site. We find that frequently burned plots experienced a decline in surface soil carbon and nitrogen that was non-saturating through time, having 36 per cent (±13 per cent) less carbon and 38 per cent (±16 per cent) less nitrogen after 64 years than plots that were protected from fire. Fire-driven carbon and nitrogen losses were substantial in savanna grasslands and broadleaf forests, but not in temperate and boreal needleleaf forests. We also observe comparable soil carbon and nitrogen losses in an independent field dataset and in dynamic model simulations of global vegetation. The model study predicts that the long-term losses of soil nitrogen that result from more frequent burning may in turn decrease the carbon that is sequestered by net primary productivity by about 20 per cent of the total carbon that is emitted from burning biomass over the same period. Furthermore, we estimate that the effects of changes in fire frequency on ecosystem carbon storage may be 30 per cent too low if they do not include multidecadal changes in soil carbon, especially in drier savanna grasslands. Future changes in fire frequency may shift ecosystem carbon storage by changing soil carbon pools and nitrogen limitations on plant growth, altering the carbon sink capacity of frequently burning savanna grasslands and broadleaf forests.

Multiple constraints cause positive and negative feedbacks limiting grassland soil CO2 efflux under CO2 enrichment.

Terrestrial ecosystems are increasingly enriched with resources such as atmospheric CO2 that limit ecosystem processes. The consequences for ecosystem carbon cycling depend on the feedbacks from other limiting resources and plant community change, which remain poorly understood for soil CO2 efflux, JCO2, a primary carbon flux from the biosphere to the atmosphere. We applied a unique CO2 enrichment gradient (250 to 500 µL L-1) for eight years to grassland plant communities on soils from different landscape positions. We identified the trajectory of JCO2 responses and feedbacks from other resources, plant diversity [effective species richness, exp(H)], and community change (plant species turnover). We found linear increases in JCO2 on an alluvial sandy loam and a lowland clay soil, and an asymptotic increase on an upland silty clay soil. Structural equation modeling identified CO2 as the dominant limitation on JCO2 on the clay soil. In contrast with theory predicting limitation from a single limiting factor, the linear JCO2 response on the sandy loam was reinforced by positive feedbacks from aboveground net primary productivity and exp(H), while the asymptotic JCO2 response on the silty clay arose from a net negative feedback among exp(H), species turnover, and soil water potential. These findings support a multiple resource limitation view of the effects of global change drivers on grassland ecosystem carbon cycling and highlight a crucial role for positive or negative feedbacks between limiting resources and plant community structure. Incorporating these feedbacks will improve models of terrestrial carbon sequestration and ecosystem services.

Pseudomonas syringae isolated in lichens for the first time: Unveiling Peltigera genus as the exclusive host.

Pseudomonas syringae is a bacterial complex that is widespread through a range of environments, typically associated with plants where it can be pathogenic, but also found in non-plant environments such as clouds, precipitation, and surface waters. Understanding its distribution within the environment, and the habitats it occupies, is important for examining its evolution and understanding behaviours. After a recent study found P. syringae living among a range of vascular plant species in Iceland, we questioned whether lichens could harbour P. syringae. Sixteen different species of lichens were sampled all over Iceland, but only one lichen genus, Peltigera, was found to consistently harbour P. syringae. Phylogenetic analyses of P. syringae from 10 sampling points where lichen, tracheophyte, and/or moss were simultaneously collected showed significant differences between sampling points, but not between different plants and lichens from the same point. Furthermore, while there were similarities in the P. syringae population in tracheophytes and Peltigera, the densities in Peltigera thalli were lower than in moss and tracheophyte samples. This discovery suggests P. syringae strains can localize and survive in organisms beyond higher plants, and thus reveals opportunities for studying their influence on P. syringae evolution.

Genomic and functional analysis of phage-mediated horizontal gene transfer in Pseudomonas syringae on the plant surface.

Many strains of Pseudomonas colonise plant surfaces, including the cherry canker pathogens, Pseudomonas syringae pathovars syringae and morsprunorum. We have examined the genomic diversity of P. syringae in the cherry phyllosphere and focused on the role of prophages in transfer of genes encoding Type 3 secreted effector (T3SE) proteins contributing to the evolution of virulence. Phylogenomic analysis was carried out on epiphytic pseudomonads in the UK orchards. Significant differences in epiphytic populations occurred between regions. Nonpathogenic strains were found to contain reservoirs of T3SE genes. Members of P. syringae phylogroups 4 and 10 were identified for the first time from Prunus. Using bioinformatics, we explored the presence of the gene encoding T3SE HopAR1 within related prophage sequences in diverse P. syringae strains including cherry epiphytes and pathogens. Results indicated that horizontal gene transfer (HGT) of this effector between phylogroups may have involved phage. Prophages containing hopAR1 were demonstrated to excise, circularise and transfer the gene on the leaf surface. The phyllosphere provides a dynamic environment for prophage-mediated gene exchange and the potential for the emergence of new more virulent pathotypes. Our results suggest that genome-based epidemiological surveillance of environmental populations will allow the timely application of control measures to prevent damaging diseases.

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions.

Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Gas and Propane Combustion from Stoves Emits Benzene and Increases Indoor Air Pollution.

Exposure pathways to the carcinogen benzene are well-established from tobacco smoke, oil and gas development, refining, gasoline pumping, and gasoline and diesel combustion. Combustion has also been linked to the formation of nitrogen dioxide, carbon monoxide, and formaldehyde indoors from gas stoves. To our knowledge, however, no research has quantified the formation of benzene indoors from gas combustion by stoves. Across 87 homes in California and Colorado, natural gas and propane combustion emitted detectable and repeatable levels of benzene that in some homes raised indoor benzene concentrations above well-established health benchmarks. Mean benzene emissions from gas and propane burners on high and ovens set to 350 °F ranged from 2.8 to 6.5 µg min-1, 10 to 25 times higher than emissions from electric coil and radiant alternatives; neither induction stoves nor the food being cooked emitted detectable benzene. Benzene produced by gas and propane stoves also migrated throughout homes, in some cases elevating bedroom benzene concentrations above chronic health benchmarks for hours after the stove was turned off. Combustion of gas and propane from stoves may be a substantial benzene exposure pathway and can reduce indoor air quality.

Alveolar epithelial cell growth hormone releasing hormone receptor in alveolar epithelial inflammation.

Purpose: Growth hormone-releasing hormone (GHRH) is a 44-amino acid peptide that regulates growth hormone (GH) secretion. We hypothesized that GHRH receptor (GHRH-R) in alveolar type 2 (AT2) cells could modulate pro-inflammatory and possibly subsequent pro-fibrotic effects of lipopolysaccharide (LPS) or cytokines, such that AT2 cells could participate in lung inflammation and fibrosis. Methods: We used human alveolar type 2 (iAT2) epithelial cells derived from induced pluripotent stem cells (iPSC) to investigate how GHRH-R modulates gene and protein expression. We tested iAT2 cells' gene expression in response to LPS or cytokines, seeking whether these mechanisms caused endogenous production of pro-inflammatory molecules or mesenchymal markers. Quantitative real-time PCR (RT-PCR) and Western blotting were used to investigate differential expression of epithelial and mesenchymal markers. Result: Incubation of iAT2 cells with LPS increased expression of IL1-ß and TNF-α in addition to mesenchymal genes, including ACTA2, FN1 and COL1A1. Alveolar epithelial cell gene expression due to LPS was significantly inhibited by GHRH-R peptide antagonist MIA-602. Incubation of iAT2 cells with cytokines like those in fibrotic lungs similarly increased expression of genes for IL1-ß, TNF-α, TGFß-1, Wnt5a, smooth muscle actin, fibronectin and collagen. Expression of mesenchymal proteins, such as N-cadherin and vimentin, were also elevated after prolonged exposure to cytokines, confirming epithelial production of pro-inflammatory molecules as an important mechanism that might lead to subsequent fibrosis. Conclusion: iAT2 cells clearly expressed the GHRH-R. Exposure to LPS or cytokines increased iAT2 cell production of pro-inflammatory factors. GHRH-R antagonist MIA-602 inhibited pro-inflammatory gene expression, implicating iAT2 cell GHRH-R signaling in lung inflammation and potentially in fibrosis.

Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw.

Northern peatlands have accumulated large stocks of organic carbon (C) and nitrogen (N), but their spatial distribution and vulnerability to climate warming remain uncertain. Here, we used machine-learning techniques with extensive peat core data (n > 7,000) to create observation-based maps of northern peatland C and N stocks, and to assess their response to warming and permafrost thaw. We estimate that northern peatlands cover 3.7 ± 0.5 million km2 and store 415 ± 150 Pg C and 10 ± 7 Pg N. Nearly half of the peatland area and peat C stocks are permafrost affected. Using modeled global warming stabilization scenarios (from 1.5 to 6 °C warming), we project that the current sink of atmospheric C (0.10 ± 0.02 Pg C⋅y-1) in northern peatlands will shift to a C source as 0.8 to 1.9 million km2 of permafrost-affected peatlands thaw. The projected thaw would cause peatland greenhouse gas emissions equal to ∼1% of anthropogenic radiative forcing in this century. The main forcing is from methane emissions (0.7 to 3 Pg cumulative CH4-C) with smaller carbon dioxide forcing (1 to 2 Pg CO2-C) and minor nitrous oxide losses. We project that initial CO2-C losses reverse after ∼200 y, as warming strengthens peatland C-sinks. We project substantial, but highly uncertain, additional losses of peat into fluvial systems of 10 to 30 Pg C and 0.4 to 0.9 Pg N. The combined gaseous and fluvial peatland C loss estimated here adds 30 to 50% onto previous estimates of permafrost-thaw C losses, with southern permafrost regions being the most vulnerable.

Peak grain forecasts for the US High Plains amid withering waters.

Irrigated agriculture contributes 40% of total global food production. In the US High Plains, which produces more than 50 million tons per year of grain, as much as 90% of irrigation originates from groundwater resources, including the Ogallala aquifer. In parts of the High Plains, groundwater resources are being depleted so rapidly that they are considered nonrenewable, compromising food security. When groundwater becomes scarce, groundwater withdrawals peak, causing a subsequent peak in crop production. Previous descriptions of finite natural resource depletion have utilized the Hubbert curve. By coupling the dynamics of groundwater pumping, recharge, and crop production, Hubbert-like curves emerge, responding to the linked variations in groundwater pumping and grain production. On a state level, this approach predicted when groundwater withdrawal and grain production peaked and the lag between them. The lags increased with the adoption of efficient irrigation practices and higher recharge rates. Results indicate that, in Texas, withdrawals peaked in 1966, followed by a peak in grain production 9 y later. After better irrigation technologies were adopted, the lag increased to 15 y from 1997 to 2012. In Kansas, where these technologies were employed concurrently with the rise of irrigated grain production, this lag was predicted to be 24 y starting in 1994. In Nebraska, grain production is projected to continue rising through 2050 because of high recharge rates. While Texas and Nebraska had equal irrigated output in 1975, by 2050, it is projected that Nebraska will have almost 10 times the groundwater-based production of Texas.