40 research outputs found

    Sediment accumulation rates in subarctic lakes: Insights into age-depth modeling from 22 dated lake records from the Northwest Territories, Canada

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    Age-depth modeling using Bayesian statistics requires well-informed prior information about the behavior of sediment accumulation. Here we present average sediment accumulation rates (represented as deposition times, DT, in yr/cm) for lakes in an Arctic setting, and we examine the variability across space (intra- and inter-lake) and time (late Holocene). The dataset includes over 100 radiocarbon dates, primarily on bulk sediment, from 22 sediment cores obtained from 18 lakes spanning the boreal to tundra ecotone gradients in subarctic Canada. There are four to twenty-five radiocarbon dates per core, depending on the length and character of the sediment records. Deposition times were calculated at 100-year intervals from age-depth models constructed using the 'classical' age-depth modeling software Clam. Lakes in boreal settings have the most rapid accumulation (mean DT 20±10 yr/cm), whereas lakes in tundra settings accumulate at moderate (mean DT 70±10 yr/cm) to very slow rates, (>100yr/cm). Many of the age-depth models demonstrate fluctuations in accumulation that coincide with lake evolution and post-glacial climate change. Ten of our sediment cores yielded sediments as old as c. 9000cal BP (BP=years before AD 1950). From between c. 9000cal BP and c. 6000cal BP, sediment accumulation was relatively rapid (DT of 20-60yr/cm). Accumulation slowed between c. 5500 and c. 4000cal BP as vegetation expanded northward in response to warming. A short period of rapid accumulation occurred near 1200cal BP at three lakes. Our research will help inform priors in Bayesian age modeling

    Climate change and the long-term viability of the World’s busiest heavy haul ice road

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    Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world’s busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR
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