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The positive Arctic–methane (CH 4 ) feedback forms when more CH 4 is released from the Arctic tundra to warm the climate, further stimulating the Arctic to emit CH 4 . This study utilized the CLM-Microbe model to project CH 4 emissions across five distinct Arctic tundra ecosystems on the Alaska North Slope, considering three Shared Socioeconomic Pathway (SSP) scenarios using climate data from three climate models from 2016 to 2100. Employing a hyper-resolution of 5 m × 5 m within 40,000 m 2 domains accounted for the Arctic tundra’s high spatial heterogeneity; three sites were near Utqiaġvik (US-Beo, US-Bes, and US-Brw), with one each in Atqasuk (US-Atq) and Ivotuk (US-Ivo). Simulated CH 4 emissions substantially increased by a factor of 5.3 to 7.5 under the SSP5–8.5 scenario compared to the SSP1–2.6 and SSP2–4.5 scenarios. The projected CH 4 emissions exhibited a stronger response to rising temperature under the SSP5–8.5 scenario than under the SSP1–2.6 and SSP2–4.5 scenarios, primarily due to strong temperature dependence and the enhanced precipitation-induced expansion of anoxic conditions that promoted methanogenesis. The CH 4 transport via ebullition and plant-mediated transport is projected to increase under all three SSP scenarios, and ebullition dominated CH 4 transport by 2100 across five sites. Projected CH 4 emissions varied in temperature sensitivity, with a Q 10 range of 2.7 to 60.9 under SSP1–2.6, 3.8 to 17.6 under SSP2–4.5, and 5.7 to 17.2 under SSP5–8.5. Compared with the other three sites, US-Atq and US-Ivo were estimated to have greater increases in CH 4 emissions due to warmer temperatures and higher precipitation. The fact that warmer sites and warmer climate scenarios had higher CH 4 emissions suggests an intensified positive Arctic–CH 4 feedback in the 21st century. Microbial physiology and substrate availability dominated the enhanced CH 4 production. The simulated intensified positive feedback underscores the urgent need for a more mechanistic understanding of CH 4 dynamics and the development of strategies to mitigate CH 4 across the Arctic.

Arctic tundra soils store a globally significant amount of mercury (Hg), which could be transformed to the neurotoxic methylmercury (MeHg) upon warming and thus poses serious threats to the Arctic ecosystem. However, our knowledge of the biogeochemical drivers of MeHg production is limited in these soils. Using substrate addition (acetate and sulfate) and selective microbial inhibition approaches, we investigated the geochemical drivers and dominant microbial methylators in 60-day microcosm incubations with two tundra soils: a circumneutral fen soil and an acidic bog soil, collected near Nome, Alaska, United States. Results showed that increasing acetate concentration had negligible influences on MeHg production in both soils. However, inhibition of sulfate-reducing bacteria (SRB) completely stalled MeHg production in the fen soil in the first 15 days, whereas addition of sulfate in the low-sulfate bog soil increased MeHg production by 5-fold, suggesting prominent roles of SRB in Hg(II) methylation. Without the addition of sulfate in the bog soil or when sulfate was depleted in the fen soil (after 15 days), both SRB and methanogens contributed to MeHg production. Analysis of microbial community composition confirmed the presence of several phyla known to harbor microorganisms associated with Hg(II) methylation in the soils. The observations suggest that SRB and methanogens were mainly responsible for Hg(II) methylation in these tundra soils, although their relative contributions depended on the availability of sulfate and possibly syntrophic metabolisms between SRB and methanogens.

The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017-2019; g1/4g2.5gkm2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (>g22g000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86g% of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.

The availability of labile carbon (C) compounds in Arctic wetland soils is expected to increase due to thawing permafrost and increased fermentation as a result of decomposition of organic matter with warming. How microbial communities respond to this change will affect the balance of CO2 and CH4 emitted during anaerobic organic matter decomposition, and ultimately the net radiative forcing of greenhouse gas emissions from these soils. While soil water content limits aerobic respiration, the factors controlling methanogenesis and anaerobic respiration are poorly defined in suboxic Arctic soils. We conducted incubation experiments on two tundra soils from field sites on the Seward Peninsula, Alaska, with contrasting pH and geochemistry to determine the pathways of anaerobic microbial respiration and changes with increasing substrate availability upon warming. In incubation of soils from the circumneutral Teller site, the ratio of CO2 to CH4 dropped from 10 to

We investigated rates and controls on greenhouse gas (CO2 and CH4) production in two contrasting water-saturated tundra soils within a permafrost-affected watershed near Nome, Alaska, United States. Three years of field sample analysis have shown that soil from a fen-like area in the toeslope of the watershed had higher pH and higher porewater ion concentrations than soil collected from a bog-like peat plateau at the top of the hillslope. The influence of these contrasting geochemical and topographic environments on CO2 and CH4 production was tested in soil microcosms by incubating both the organic- and mineral-layer soils anaerobically for 55 days. Nitrogen (as NH4Cl) was added to half of the microcosms to test potential effects of N limitation on microbial greenhouse gas production. We found that the organic toeslope soils produced more CO2 and CH4, fueled by higher pH and higher concentrations of water-extractable organic C (WEOC). Our results also indicate N limitation on CO2 production in the peat plateau soils but not the toeslope soils. Together these results suggest that the weathering and leaching of ions and nutrients from tundra hillslopes can increase the rate of anaerobic soil organic matter decomposition in downslope soils by (1) increasing the pH of soil porewater; (2) providing bioavailable WEOC and fermentation products such as acetate; and (3) relieving microbial N limitation through nutrient runoff. We conclude that the soil geochemistry as mediated by landscape position is an important factor influencing the rate and magnitude of greenhouse gas production in tundra soils.

Ice-wedge polygons are common Arctic landforms. The future of these landforms in a warming climate depends on the bidirectional feedback between the rate of ice-wedge degradation and changes in hydrological characteristics. This work aims to better understand the relative roles of vertical and horizontal water fluxes in the subsurface of polygonal landscapes, providing new insights and data to test and calibrate hydrological models. Field-scale investigations were conducted at an intensively instrumented location on the Barrow Environmental Observatory (BEO) near Utqiagvik, AK, USA. Using a conservative tracer, we examined controls of microtopography and the frost table on subsurface flow and transport within a low-centered and a high-centered polygon. Bromide tracer was applied at both polygons in July 2015 and transport was monitored through two thaw seasons. Sampler arrays placed in polygon centers, rims, and troughs were used to monitor tracer concentrations. In both polygons, the tracer first infiltrated vertically until encountering the frost table and was then transported horizontally. Horizontal flow occurred in more locations and at higher velocities in the low-centered polygon than in the high-centered polygon. Preferential flow, influenced by frost table topography, was significant between polygon centers and troughs. Estimates of horizontal hydraulic conductivity were within the range of previous estimates of vertical conductivity, highlighting the importance of horizontal flow in these systems. This work forms a basis for understanding complexity of flow in polygonal landscapes.

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

Following publication of the original article.

Abstract. Ice-wedge polygons are common Arctic landforms. The future of these landforms in a warming climate depends on the bidirectional feedback between the rate of ice-wedge degradation and changes in hydrological characteristics. This work aims to better understand the relative roles of vertical and horizontal water fluxes in the subsurface of polygonal landscapes, providing new insights and data to test and calibrate hydrology models. Field-scale investigations were conducted at an intensively-instrumented location on the Barrow Environmental Observatory (BEO) near Utqiaġvik, AK, USA. Using a conservative tracer, we examined controls of microtopography and the frost table on subsurface flow and transport within a low-centered and a high-centered polygon. Bromide tracer was applied at both polygons in July 2015 and transport was monitored through two thaw seasons. Samplers arrays placed in polygon centers, rims, and troughs were used to monitor tracer concentrations. In both polygons, the tracer first infiltrated vertically until encountering the frost table, then was transported horizontally. Horizontal flow occurred in more locations and at higher velocities of fluxes in the low-centered polygon than in the high-centered polygon. Preferential flow, influenced by frost table topography, was significant between polygon centers and troughs. Estimates of horizontal hydraulic conductivity were within the range of previous estimates of vertical conductivity, highlighting the importance of horizontal flow in these systems. This work forms a basis for understanding complexity of flow in polygonal landscapes.

BackgroundCrassulacean acid metabolism (CAM) enhances plant water-use efficiency through an inverse day/night pattern of stomatal closure/opening that facilitates nocturnal CO2 uptake. CAM has evolved independently in over 35 plant lineages, accounting for ~ 6% of all higher plants. Agave species are highly heat- and drought-tolerant, and have been domesticated as model CAM crops for beverage, fiber, and biofuel production in semi-arid and arid regions. However, the genomic basis of evolutionary innovation of CAM in genus Agave is largely unknown.ResultsUsing an approach that integrated genomics, gene co-expression networks, comparative genomics and protein structure analyses, we investigated the molecular evolution of CAM as exemplified in Agave. Comparative genomics analyses among C3, C4 and CAM species revealed that core metabolic components required for CAM have ancient genomic origins traceable to non-vascular plants while regulatory proteins required for diel re-programming of metabolism have a more recent origin shared among C3, C4 and CAM species. We showed that accelerated evolution of key functional domains in proteins responsible for primary metabolism and signaling, together with a diel re-programming of the transcription of genes involved in carbon fixation, carbohydrate processing, redox homeostasis, and circadian control is required for the evolution of CAM in Agave. Furthermore, we highlighted the potential candidates contributing to the adaptation of CAM functional modules.ConclusionsThis work provides evidence of adaptive evolution of CAM related pathways. We showed that the core metabolic components required for CAM are shared by non-vascular plants, but regulatory proteins involved in re-reprogramming of carbon fixation and metabolite transportation appeared more recently. We propose that the accelerated evolution of key proteins together with a diel re-programming of gene expression were required for CAM evolution from C3 ancestors in Agave.

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

The dynamics of evapotranspiration (ET), such as the partitioning to evaporation and transpiration, of polygonal ground on the Arctic Coastal Plain are not well understood. We assessed ET dynamics, including evaporation and transpiration partitioning, created by microtopographic features associated with high- and low-centered polygons. Chamber ET and leaf-level transpiration measurements were conducted in one-week field campaigns in two growing seasons with contrasting weather conditions. We found that ET was greater in the drier and warmer sampling period (2013) compared to the colder and wetter one (2014). Evaporation dominated ET, particularly in the wetter and colder sampling period (>90% in 2014 vs. 80% in 2013). In the 2013 sampling period, wetter and warmer conditions increased ET and the contribution of transpiration to ET. If the soils warm with degrading permafrost, ET and the fraction contributed by transpiration may increase to a certain threshold, when moisture must increase with rising temperatures to further increase these fluxes. While the fraction of transpiration may rise with warmer soils, it is unlikely that transpiration will completely dominate ET. This work highlights the complexities of understanding ET in this dynamic environment and the importance of understanding differences across polygonal ground.

Coastal tundra ecosystems are relatively flat, and yet display large spatial variability in ecosystem traits. The microtopographical differences in polygonal geomorphology produce heterogeneity in permafrost depth, soil temperature, soil moisture, soil geochemistry, and plant distribution. Few measurements have been made, however, of how water fluxes vary across polygonal tundra plant types, limiting our ability to understand and model these ecosystems. Our objective was to investigate how plant distribution and geomorphological location affect actual evapotranspiration (ET). These effects are especially critical in light of the rapid change polygonal tundra systems are experiencing with Arctic warming. At a field site near Barrow, Alaska, USA, we investigated the relationships between ET and plant cover in 2014 and 2015. ET was measured at a range of spatial and temporal scales using: (1) An eddy covariance flux tower for continuous landscape-scale monitoring; (2) An automated clear surface chamber over dry vegetation in a fixed location for continuous plot-scale monitoring; and (3) Manual measurements with a clear portable chamber in approximately 60 locations across the landscape. We found that variation in environmental conditions and plant community composition, driven by microtopographical features, has significant influence on ET. Among plant types, ET from moss-covered and inundated areas was more than twice that from other plant types. ET from troughs and low polygonal centers was significantly higher than from high polygonal centers. ET varied seasonally, with peak fluxes of 0.14 mm h−1 in July. Despite 24 hours of daylight in summer, diurnal fluctuations in incoming solar radiation and plant processes produced a diurnal cycle in ET. Combining the patterns we observed with projections for the impact of permafrost degradation on polygonal structure suggests that microtopographic changes associated with permafrost thaw have the potential to alter tundra ecosystem ET.

The few prethaw observations of tundra carbon fluxes suggest that there may be large spring releases, but little is known about the scale and underlying mechanisms of this phenomenon. To address these questions, we combined ecosystem eddy flux measurements from two towers near Barrow, Alaska, with mechanistic soil-core thawing experiment. During a 2 week period prior to snowmelt in 2014, large fluxes were measured, reducing net summer uptake of CO2 by 46% and adding 6% to cumulative CH4 emissions. Emission pulses were linked to unique rain-on-snow events enhancing soil cracking. Controlled laboratory experiment revealed that as surface ice thaws, an immediate, large pulse of trapped gases is emitted. These results suggest that the Arctic CO2 and CH4 spring pulse is a delayed release of biogenic gas production from the previous fall and that the pulse can be large enough to offset a significant fraction of the moderate Arctic tundra carbon sink.

Microbial decomposition of soil organic carbon (SOC) in thawing Arctic permafrost is important in determining greenhouse gas feedbacks of tundra ecosystems to climate. However, the changes in microbial community structure during SOC decomposition are poorly known. Here we examine these changes using frozen soils from Barrow, Alaska, USA, in anoxic microcosm incubation at -2 and 8°C for 122 days. The functional gene array GeoChip was used to determine microbial community structure and the functional genes associated with SOC degradation, methanogenesis, and Fe(III) reduction. Results show that soil incubation after 122 days at 8°C significantly decreased functional gene abundance (P < 0.05) associated with SOC degradation, fermentation, methanogenesis, and iron cycling, particularly in organic-rich soil. These observations correspond well with decreases in labile SOC content (e.g., reducing sugar and ethanol), methane and CO2 production, and Fe(III) reduction. In contrast, the community functional structure was largely unchanged in the -2°C incubation. Soil type (i.e., organic vs. mineral) and the availability of labile SOC were among the most significant factors impacting microbial community structure. These results demonstrate the important roles of microbial community in SOC degradation and support previous findings that SOC in organic-rich Arctic tundra is highly vulnerable to microbial degradation under warming.

Already a proven mechanism for drought resilience, crassulacean acid metabolism (CAM) is a specialized type of photosynthesis that maximizes water-use efficiency by means of an inverse (compared to C3 and C4 photosynthesis) day/night pattern of stomatal closure/opening to shift CO2 uptake to the night, when evapotranspiration rates are low. A systems-level understanding of temporal molecular and metabolic controls is needed to define the cellular behaviour underpinning CAM. Here, we report high-resolution temporal behaviours of transcript, protein and metabolite abundances across a CAM diel cycle and, where applicable, compare the observations to the well-established C3 model plant Arabidopsis. A mechanistic finding that emerged is that CAM operates with a diel redox poise that is shifted relative to that in Arabidopsis. Moreover, we identify widespread rescheduled expression of genes associated with signal transduction mechanisms that regulate stomatal opening/closing. Controlled production and degradation of transcripts and proteins represents a timing mechanism by which to regulate cellular function, yet knowledge of how this molecular timekeeping regulates CAM is unknown. Here, we provide new insights into complex post-transcriptional and -translational hierarchies that govern CAM in Agave. These data sets provide a resource to inform efforts to engineer more efficient CAM traits into economically valuable C3 crops.

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data-model and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land-atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

Photosynthetic capacity, determined by light harvesting and carboxylation reactions, is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models (ESMs) at a reference temperature, it is either a fixed value for a given plant functional type or derived from a linear function of leaf nitrogen content. In this study, we conducted a comprehensive analysis that considered correlations of environmental factors with photosynthetic capacity as determined by maximum carboxylation (V(cm)) rate scaled to 25 degrees C (i.e., V(c),25; μmol CO2 x m(-2)x s(-1)) and maximum electron transport rate (J(max)) scaled to 25 degrees C (i.e., J25; μmol electron x m(-2) x s(-1)) at the global scale. Our results showed that the percentage of variation in observed V(c),25 and J25 explained jointly by the environmental factors (i.e., day length, radiation, temperature, and humidity) were 2-2.5 times and 6-9 times of that explained by area-based leaf nitrogen content, respectively. Environmental factors influenced photosynthetic capacity mainly through photosynthetic nitrogen use efficiency, rather than through leaf nitrogen content. The combination of leaf nitrogen content and environmental factors was able to explain -56% and -66% of the variation in V(c),25 and J25 at the global scale, respectively. Our analyses suggest that model projections of plant photosynthetic capacity and hence land-atmosphere exchange under changing climatic conditions could be substantially improved if environmental factors are incorporated into algorithms used to parameterize photosynthetic capacity in ESMs.

Arctic soils contain a large pool of terrestrial C and are of interest due to their potential for releasing significant carbon dioxide (CO2) and methane (CH4) to the atmosphere. Due to substantial landscape heterogeneity, predicting ecosystem-scale CH4 and CO2 production is challenging. This study assessed dissolved inorganic carbon (DIC = Σ (total) dissolved CO2) and CH4 in watershed drainages in Barrow, Alaska as critical convergent zones of regional geochemistry, substrates, and nutrients. In July and September of 2013, surface waters and saturated subsurface pore waters were collected from 17 drainages. Based on simultaneous DIC and CH4 cycling, we synthesized isotopic and geochemical methods to develop a subsurface CH4 and DIC balance by estimating mechanisms of CH4 and DIC production and transport pathways and oxidation of subsurface CH4. We observed a shift from acetoclastic (July) toward hydrogenotropic (September) methanogenesis at sites located toward the end of major freshwater drainages, adjacent to salty estuarine waters, suggesting an interesting landscape-scale effect on CH4 production mechanism. The majority of subsurface CH4 was transported upward by plant-mediated transport and ebullition, predominantly bypassing the potential for CH4 oxidation. Thus, surprisingly, CH4 oxidation only consumed approximately 2.51 ± 0.82% (July) and 0.79 ± 0.79% (September) of CH4 produced at the frost table, contributing to

Peatlands harbour more than one-third of terrestrial carbon leading to the argument that the bryophytes, as major components of peatland ecosystems, store more organic carbon in soils than any other collective plant taxa. Plants of the genus Sphagnum are important components of peatland ecosystems and are potentially vulnerable to changing climatic conditions. However, the response of Sphagnum to rising temperatures, elevated CO2 and shifts in local hydrology have yet to be fully characterized. In this review, we examine Sphagnum biology and ecology and explore the role of this group of keystone species and its associated microbiome in carbon and nitrogen cycling using literature review and model simulations. Several issues are highlighted including the consequences of a variable environment on plant-microbiome interactions, uncertainty associated with CO2 diffusion resistances and the relationship between fixed N and that partitioned to the photosynthetic apparatus. We note that the Sphagnum fallax genome is currently being sequenced and outline potential applications of population-level genomics and corresponding plant photosynthesis and microbial metabolic modelling techniques. We highlight Sphagnum as a model organism to explore ecosystem response to a changing climate and to define the role that Sphagnum can play at the intersection of physiology, genetics and functional genomics.

Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.

Climate change affects agricultural productivity worldwide. Increased prices of food commodities are the initial indication of drastic edible yield loss, which is expected to increase further due to global warming. This situation has compelled plant scientists to develop climate change-resilient crops, which can withstand broad-spectrum stresses such as drought, heat, cold, salinity, flood, submergence and pests, thus helping to deliver increased productivity. Genomics appears to be a promising tool for deciphering the stress responsiveness of crop species with adaptation traits or in wild relatives toward identifying underlying genes, alleles or quantitative trait loci. Molecular breeding approaches have proven helpful in enhancing the stress adaptation of crop plants, and recent advances in high-throughput sequencing and phenotyping platforms have transformed molecular breeding to genomics-assisted breeding (GAB). In view of this, the present review elaborates the progress and prospects of GAB for improving climate change resilience in crops, which is likely to play an ever increasing role in the effort to ensure global food security.