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Empirical models for describing recent sedimentation rates in lakes distributed across broad spatial scales

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Abstract

Over the last 20 years there has been a surge of interest in paleolimnology and as a result a large accumulation of lake sedimentation records. This emerging archive has allowed us to develop empirical models to describe which variables explain significant variation in sedimentation rates over the past ∼150 years across large spatial scales. We hypothesized that latitude would be a significant explanatory variable of profundal zone lake sedimentation rates across a temperate to polar gradient. We further hypothesized that along a more longitudinally-constrained dataset (i.e. east coast of North America), latitude would explain a greater proportion of the variance. To test these hypotheses, we collated data from 125 natural, average-sized lakes (with surface area <500 km2) by recording authors’ estimates of sedimentation rates (measured as mm/year) or by digitizing recent sediment profiles and calculating sedimentation rates over the past ∼150 years. We found that, at both scales, latitude was the strongest predictor of lake sedimentation rates (full dataset: r 2 = 0.28, P = 0.001, n = 125; east coast dataset: r 2 = 0.58, P < 0.001, n = 43). By conducting a multiple linear regression analysis, we found that 70% of the variance in sedimentation rates from the east coast transect was explained by latitude and elevation alone. This latter model is of sufficient strength that it is a robust predictive tool. Given that climate and land-use strongly co-vary with latitude and that both of these factors have previously been shown to influence lake sedimentation rates, it appears that latitude is a surrogate measure for climate and land-use changes. We also show support for land-use as an important variable influencing sedimentation rates by demonstrating large increases in recent versus Holocene accumulation rates. These results indicate that it is possible to make generalizations about sedimentation rates across broad spatial scales with even limited geographic data.

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Acknowledgements

Funding for this project was provided by le Fonds québécois de recherche sur la nature et les technologies (FQRNT) and McGill University. We would like to thank all the original authors whose data we have synthesized here, especially those who responded to our emails and dug through their files for data that we could not find in their papers. We would also like to acknowledge the assistance provided by Erika Brown in synthesizing the climate data and developing our map. Comments provided by three anonymous reviewers, Jacob Kalff, Émilie Saulnier-Talbot and Daniel Selbie also improved this paper. This manuscript represents a contribution by members of le Groupe de Recherche Interuniversitaire en Limnologie (GRIL).

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  1. Department of Biology, McGill University, 1205 Docteur Penfield, Montreal, QC, Canada, H3A 1B1

    Soren Brothers, Jesse C. Vermaire & Irene Gregory-Eaves

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  1. Soren Brothers
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  2. Jesse C. Vermaire
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  3. Irene Gregory-Eaves
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Correspondence to Irene Gregory-Eaves.

 

 

Appendix A The database of all lakes used in our analyses. Below are the geographic, morphometric, sedimentation rates and dating data that we compiled. The type of dating techniques used are listed using the following notation: 1 = 210Pb, 2 = 137Cs, 3 = pollen, 4 = stable lead or other geochemical markers)
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Brothers, S., Vermaire, J.C. & Gregory-Eaves, I. Empirical models for describing recent sedimentation rates in lakes distributed across broad spatial scales. J Paleolimnol 40, 1003–1019 (2008). https://doi.org/10.1007/s10933-008-9212-8

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