Search

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 km(2), 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 Malaren, the third largest (1,074 km(2)) Swedish lake. Total phosphorus concentrations show that during the study period the lake was classed as mesotrophic/eutrophic. Overall mean CH4 concentration from all stations, sampled five times to cover seasonal variation, was 2.51 mu g l(-1) (0.98-5.39 mu g l(-1)). There was no significant seasonal variation although ranges were greatest during summer. Concentrations of CH4 were 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 km(2) (n = 21) and found a significant negative relationship between surface area and average CH4 concentration. Large lakes remain an understudied contributor to the global CH4 cycle and future research efforts should aim to quantify the spatial and temporal variation in their diffusive and ebullitive emissions, and associated drivers. Plain Language Summary 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 s

Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100–1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales.

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.