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The carbon (C) dynamics of boreal coniferous swamps are a largely understudied component of wetland carbon cycling. We investigated the above‐ and below‐ground carbon stocks and growing season carbon dioxide (CO2) and methane (CH4) fluxes from a representative boreal coniferous swamp in northern Alberta, Canada in 2022. Tree inventories, understory vegetation biomass and peat cores were collected across three sub‐sites within the broader swamp, with gas flux collars placed in the dominant plant communities present. Alongside the C flux measurements, environmental variables such as water table depth, soil temperature and growing season understory green leaf phenology were measured. Our results show that these boreal coniferous swamps store large volumes of organic C in their biomass and soil (134 kg C m−2), comparable with other wetland and forest types, although 95% of the total C stock at our site was within the soil organic carbon. We also found that understory CO2and CH4fluxes indicated that the ground layer of the site is a source of greenhouse gases (GHGs) to the atmosphere across the growing season. However, we did not measure litterfall input, tree GHG fluxes or net primary productivity of the overstory, therefore we are not able to say whether the site is an overall source of C to the atmosphere. This study provides a much‐needed insight into the C dynamics of these under‐valued wetland ecosystems, and we highlight the need for a coordinated effort across boreal regions to try to improve inventories of C stocks and fluxes. Compared to other wetland types across Canada, boreal conifer swamps do not receive the same level of scientific attention and therefore our understanding of how much carbon they potentially store and release is limited. To fill this knowledge gap, our study measured how much carbon was stored both in the trees and within the soil itself, alongside measurements of carbon uptake and release within a representative conifer swamp wetland in Western Canada. We found that although these wetlands may function similarly to other wetland types, by ignoring them, we are missing out on large amounts of carbon being stored in these systems. We also found that at the ground layer, these sites are a source of carbon, that is, releasing more carbon than is being taken up by the understory moss and plant layer. However, we cannot say if the site overall is a source of carbon to the atmosphere as we were unable to measure other key components of a wetland carbon cycle including litterfall input and the productivity of the trees themselves. Our findings indicate that by not including these wetlands in modeling of carbon dynamics, we are missing a substantial component of boreal carbon cycling processes. Boreal conifer swamp wetlands are an underrepresented wetland class within wetland C cycling measurements and modelingThese swamps store large volumes of organic C in their aboveground biomass but most importantly, in their soil organic carbon stockWe also found that the ground‐layer of this site is a net source of greenhouse gases during the growing season Boreal conifer swamp wetlands are an underrepresented wetland class within wetland C cycling measurements and modeling These swamps store large volumes of organic C in their aboveground biomass but most importantly, in their soil organic carbon stock We also found that the ground‐layer of this site is a net source of greenhouse gases during the growing season

Lakes process large volumes of organic carbon (OC), are important sources of methane (CH4), and contribute to climatic warming. However, there is a lack of data from large lakes >500 km2, which creates uncertainty in global budgets. In this data article, we present dissolved CH4, OC bioreactivity measurements, water chemistry, and algal biovolumes at 11 stations across Lake Mälaren, the third largest (1,074 km2) Swedish lake. Total phosphorus concentrations show that during the study period the lake was classed as mesotrophic/eutrophic. Overall mean CH4concentration from all stations, sampled five times to cover seasonal variation, was 2.51 μg l−1(0.98–5.39 μg l−1). There was no significant seasonal variation although ranges were greatest during summer. Concentrations of CH4were greatest in shallow waters close to anthropogenic nutrient sources, whilst deeper, central basins had lower concentrations. Methane correlated positively with measures of lake productivity (chlorophyll a, total phosphorus), and negatively to water depth and oxygen concentration, with oxygen emerging as the sole significant driver in a linear mixed effects model. We collated data from other lakes >500 km2(n= 21) and found a significant negative relationship between surface area and average CH4concentration. Large lakes remain an understudied contributor to the global CH4cycle and future research efforts should aim to quantify the spatial and temporal variation in their diffusive and ebullitive emissions, and associated drivers. Lakes contribute to climatic warming, because they emit large amounts of the powerful greenhouse gas methane into the atmosphere. This occurs because lake bottom sediments and lake waters are home to microbes that produce methane, which then travels diffusively in a dissolved form, or as bubbles, through the lake water and into the air. There is large uncertainty about how much methane is released by lakes on a global scale, and more measurements are required to reduce this uncertainty, particularly from very large lakes. In our study, we measured dissolved methane from 11 sampling locations across a very large Swedish lake, and repeated this five times over a year. Levels of methane within the lake were generally low, but they varied over space and time. Higher methane levels occurred in shallower waters near large towns and cities, and were associated with greater concentrations of nutrients such as phosphorus, which act as food for the methane‐producing microbes. Lakes are globally important sources of atmospheric methane but there is a lack of data from large lakes >500 km2We measured methane concentrations across a large (1,074 km2) Swedish lake on five occasions over an annual periodMethane varied seasonally and spatially, and higher concentrations were associated with nutrient inputs, lower dissolved oxygen, and shallower waters Lakes are globally important sources of atmospheric methane but there is a lack of data from large lakes >500 km2 We measured methane concentrations across a large (1,074 km2) Swedish lake on five occasions over an annual period Methane varied seasonally and spatially, and higher concentrations were associated with nutrient inputs, lower dissolved oxygen, and shallower waters

The Alaska Arctic Vegetation Archive (AVA-AK, GIVD-ID: NA-US-014) is a free, publically available database archive of vegetation-plot data from the Arctic tundra region of northern Alaska. The archive currently contains 24 datasets with 3,026 non-overlapping plots. Of these, 74% have geolocation data with 25-m or better precision. Species cover data and header data are stored in a Turboveg database. A standardized Pan Arctic Species List provides a consistent nomenclature for vascular plants, bryophytes, and lichens in the archive. A web-based online Alaska Arctic Geoecological Atlas (AGA-AK) allows viewing and downloading the species data in a variety of formats, and provides access to a wide variety of ancillary data. We conducted a preliminary cluster analysis of the first 16 datasets (1,613 plots) to examine how the spectrum of derived clusters is related to the suite of datasets, habitat types, and environmental gradients. We present the contents of the archive, assess its strengths and weaknesses, and provide three supplementary files that include the data dictionary, a list of habitat types, an overview of the datasets, and details of the cluster analysis.

Observing the environment in the vast regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest inaccessible terrestrial biomes on Earth, requires remote sensing across multiple spatial and temporal scales, from towers to satellites, particularly those equipped for imaging spectroscopy (IS). We describe a rationale for using IS derived from advances in our understanding of Arctic tundra vegetation communities and their interaction with the environment. To best leverage ongoing and forthcoming IS resources, including National Aeronautics and Space Administration’s Surface Biology and Geology mission, we identify a series of opportunities and challenges based on intrinsic spectral dimensionality analysis and a review of current data and literature that illustrates the unique attributes of the Arctic tundra biome. These opportunities and challenges include thematic vegetation mapping, complicated by low‐stature plants and very fine‐scale surface composition heterogeneity; development of scalable algorithms for retrieval of canopy and leaf traits; nuanced variation in vegetation growth and composition that complicates detection of long‐term trends; and rapid phenological changes across brief growing seasons that may go undetected due to low revisit frequency or be obscured by snow cover and clouds. We recommend improvements to future field campaigns and satellite missions, advocating for research that combines multi‐scale spectroscopy, from lab studies to satellites that enable frequent and continuous long‐term monitoring, to inform statistical and biophysical approaches to model vegetation dynamics. Remote sensing has a long history of characterizing the distribution and dynamics of vegetation in a wide variety of biomes, including the Arctic tundra which is experiencing warming more rapidly than the global average. Imaging spectroscopy (IS)—a rapidly advancing field of remote sensing that measures reflected light in narrow, contiguous “colors” from satellites, aircraft, or towers—has demonstrated great promise to “watch” how key land surface properties vary across space and over time. Because they are vast, remote, and have relatively little infrastructure, currently available IS data from the Arctic tundra are sporadic and intermittent. Hence, it has been challenging to study and characterize these ecosystems across broad spatial scales and through time. Furthermore, the climate and ecology of these ecosystems pose unique challenges for employing and interpreting IS data. Inspired by a forthcoming National Aeronautics and Space Administration satellite‐based IS mission, we present an overview of the current opportunities and challenges for the use of spectroscopy to study Arctic tundra, informed by novel measurements across a range of spatial and temporal scales. We share recommendations for how researchers could leverage IS to resolve pressing ecological questions and advance the design and sampling scheme of future instruments and campaigns. Imaging spectroscopy (IS) can help to measure the critical Arctic tundra properties, physiological function, and temporal dynamicsUpcoming IS satellite missions including National Aeronautics and Space Administration’s Surface Biology and Geology will make IS data widely available for Arctic tundra regionsTo properly interpret IS data users must consider spectral complexity of tundra driven by composition, sensitivity to climate, and phenology Imaging spectroscopy (IS) can help to measure the critical Arctic tundra properties, physiological function, and temporal dynamics Upcoming IS satellite missions including National Aeronautics and Space Administration’s Surface Biology and Geology will make IS data widely available for Arctic tundra regions To properly interpret IS data users must consider spectral complexity of tundra driven by composition, sensitivity to climate, and phenology

Vast areas of boreal peatlands are impacted by linear disturbances known as seismic lines. Tree removal and ground disturbance alter vegetation communities and are expected to change ecosystem functioning. As boreal landscapes continue to be disturbed by linear disturbances, understanding the magnitude and mechanisms of vegetation and phenology changes is the first step toward predicting carbon cycling changes across broad spatial scales. We investigate seismic line disturbances on peatland plant community composition and phenological patterns using readily available digital photography at a bog and a fen in Alberta, Canada. Our objectives were to: (a) compare the understory peatland vegetation on seismic lines with those in adjacent undisturbed areas using two phenological metrics (green and red chromatic coordinates); (b) evaluate if vegetation greenness is directly related to vegetation community composition, and (c) determine whether plot‐scale greenness predicts plant productivity. We found that areas of peatlands intersected by seismic lines have an earlier seasonal peak (maximum greenness) compared to undisturbed areas, and vegetation communities had a stronger relationship to greenness and gross primary production (GPP) at disturbed areas relative to undisturbed areas. This change in understory vegetation results in greater CO2uptake in disturbed areas. We demonstrate an easy‐to‐use application of digital photography that successfully quantifies phenological changes in boreal peatland vegetation. This nondestructive method for understanding vegetation phenology eliminated the need for fixed infrastructure and allowed us to expand our sampling capacity and study sites while allowing for repeated measures in the future. Industrial activities for oil and gas mining across boreal North America can result in a vast network of linear disturbances called seismic lines. These are narrow clearings cut across peatlands and forests, resulting in the removal of trees and compaction to the soil, leading to changes in both the vegetation communities and how these ecosystems function. One such impact is how the ground‐layer vegetation communities green up over the course of the growing season and how this affects how productive they are. In this study, we investigated the greenness patterns of vegetation communities at two different peatland types impacted by seismic lines. To do this, we collect photographs using smartphones, alongside vegetation surveys and carbon exchange measurements. We found that these disturbances significantly impact the greenness of these communities, with disturbed areas becoming more productive faster. Using smartphones to collect photographs provided a quick and easy method to collect greenness data without the need for expensive equipment or fixed infrastructure. As boreal peatlands continue to be under threat from increased disturbances, this study provides a first step in understanding how greenness and productivity may change in the future. Seismic lines cause a shift in vegetation communities and changes in green leaf phenology and greenness metricsReadily available smartphone photography successfully captured the phenological characteristics of these vegetation typesThe change in vegetation causes greater CO2uptake in the disturbed areas and greenness metrics were good predictors of these CO2changes Seismic lines cause a shift in vegetation communities and changes in green leaf phenology and greenness metrics Readily available smartphone photography successfully captured the phenological characteristics of these vegetation types The change in vegetation causes greater CO2uptake in the disturbed areas and greenness metrics were good predictors of these CO2changes