Toward Robust Top-Bottom Paleolimnological Assessments: A Canada-Wide Sedimentation Map Evaluated with LakePulse Data

Toward Robust Top-Bottom Paleolimnological Assessments: A Canada-Wide Sedimentation Map Evaluated with LakePulse Data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Toward Robust Top-Bottom Paleolimnological Assessments: A Canada-Wide Sedimentation Map Evaluated with LakePulse Data Neal Michelutti, Alexandre Baud, Carsten Meyer-Jacob, Adam Jeziorski, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9359156/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract The “top–bottom” approach in paleolimnology provides a rapid means of assessing environmental change by comparing modern surface sediments with deeper intervals assumed to pre-date major anthropogenic disturbances (ca. pre-1880). However, spatial variability in sediment accumulation rates can undermine the assumption that a fixed depth will represent background conditions in all study lakes. The largest top-bottom study conducted to date was the Canadian LakePulse Network, which collected 664 sediment cores from 12 ecozones as part of a comprehensive program aimed at assessing the health of lakes across Canada. To estimate minimum depths corresponding to pre-industrial conditions for the LakePulse study sites, we compiled 357 published 210 Pb-dated sediment cores from across Canada and the northern United States. These data were used to generate a spatially interpolated sedimentation map, providing a national framework for Canadian lakes that can be used to inform future top-bottom studies. A representative subset of 212 LakePulse lakes was evaluated using excess 210 Pb measurements to test whether estimated bottom intervals reached pre-industrial age. Target bottom depths varied among ecozones, ranging from 22 cm in the northern regions of the Taiga Plains, Taiga Cordillera and Boreal Cordillera to 47 cm in the Boreal Plains, Semi-Arid Plateaux and Prairies. Target depths were strongly aligned with ecozone-level human impact indices, indicating that watershed land use is a dominant driver of recent sediment accumulation. Validation analyses, using the uncertainty of excess 210 Pb, showed that fewer than 9% of the study lakes failed to reach pre-industrial conditions at, or below, the target depths, although higher failure rates occurred in more impacted regions such as the Mixedwood Plains. These findings demonstrate that regionally calibrated depth targets can reliably support large-scale top-bottom assessments while highlighting the importance of accounting for watershed disturbance across diverse landscapes. Top-bottom paleolimnology NSERC Canadian LakePulse network Lake sediment accumulation Kriging interpolation 210Pb radioisotopes Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The “top-bottom” approach in paleolimnology is a comparative method that involves analyzing the surface (top) sediment layer, representing modern conditions, and a deeper (bottom) interval, representing reference conditions prior to major anthropogenic impacts, typically pre-1880s (Smol 2008 ). This approach is often used in large-scale or multi-lake studies where the goal is to provide a relatively rapid assessment of the magnitude and direction of limnological change across broad geographic areas, or regions with differing land-use histories (e.g., Charles and Smol 1990 ; Camarero et al. 2009 ; Rahman et al. 2025 ). The recovery of the most recently deposited sediments is easily confirmed by the presence of an intact sediment-water interface. However, in the absence of a dating profile, it is possible that the bottom layer may not actually represent pre-impact conditions. Lake sediment accumulation rates vary depending on several factors including ecoregions and watershed characteristics (Baud et al. 2021 ); therefore, a fixed sediment depth will not correspond to the same historical time across different lakes. While the top-bottom approach has clear advantages for rapidly assessing change in a large number of lakes, its reliance on assumed ages for bottom sediments can limit its interpretive strength. Typically, a top-bottom study will use a sub-set of fully dated sediment cores from within a particular region to approximate the depth corresponding to pre-impact conditions. However, the validity of the assumptions underlying the date estimations is rarely tested. The need for a Canada-wide contextualization of sedimentation rates was prompted by the creation of the Natural Sciences and Engineering Research Council of Canada (NSERC) Canadian LakePulse Network (hereafter LakePulse), which was launched in 2016 to provide the first national assessment of lake health (Huot et al. 2019 ). The LakePulse program was a coordinated effort that obtained detailed limnological data from 664 lakes and included a paleolimnological component that collected ~ 664 top-bottom sediment samples and ~ 120 full cores spanning 12 ecozones (Huot et al. 2019 ). This extensive sampling program, carried out by a coordinated and standardized effort consisting of several independent field teams, required a priori knowledge of the estimated background sediment depth across various Canadian ecoregions to ensure consistent interpretation of top-bottom sediment samples. Our study has two distinct, but interrelated, objectives. The first is the development of a spatially interpolated map showing minimum sediment core depths for pre-industrial times (ca. 1880s) from across the different ecoregions of Canada (including some nearby sites in northern USA) estimated using age-depth models from the published literature. This nationwide investigation of sedimentation rates was used to provide clear target depths for bottom intervals of cores collected during the LakePulse field sampling. In addition, this data synthesis provides important insights into the sedimentation rates among different Canadian ecozones and will help guide future top-bottom studies to select ecozone-dependent sediment depths corresponding to pre-industrial activities. The second objective centers on using the LakePulse data to determine how often the bottom depth targets failed on a large-scale (i.e., were the estimated pre-industrial bottom depths actually of pre-industrial age?) and, in doing so, identify regions where the assumptions of a standard top-bottom approach may be harder to meet. Knowledge of the approximate percentage of lakes in a top-bottom study that fail to reach target bottom depths (i.e., pre-industrial conditions) helps establish a threshold for when top-bottom results may reflect meaningful ecological change rather than being an artifact of varying sedimentation rates. Methods Development of a Canada-wide lake sedimentation rate map The Canadian sedimentation rate map was based on published literature from 357 dated lake sediment cores distributed across Canada and the Northern USA (Fig. 1 ). Figures and tables were digitized from the scientific literature using DigitizeIt software, following a methodology similar to Baud et al. ( 2021 ), which focused on global sedimentation rates. To address gaps in coverage, a supplemental literature search was conducted. This search targeted records with recent ²¹⁰Pb chronologies (post-1850 CE) and included studies beyond those published in the Journal of Paleolimnology , unlike Baud et al. ( 2021 ). Keywords related to geographic regions (e.g., “Prairies,” “NWT,” “Yukon”, “Alberta”, etc.) and names of researchers active in those areas were used to identify relevant studies. In total, 357 lake sedimentation records were compiled, including 124 from Baud et al. ( 2021 ) and 233 newly identified sites through the supplemental search (full reference list given in ESM 1). These additions significantly improved the spatial coverage of sedimentation data across Canada. The target bottom depths for lakes in each ecozone were determined based on qualitative visual inspection of the distribution of core depths that dated to ~ 1880 CE (Fig. 2 ). From the 357 lakes compiled in the literature review, this number dropped to 223 lakes when only considering the ecozones sampled in the LakePulse dataset. Practical feasibility was also a factor in setting the target depths, as retrieving longer sediment cores becomes increasingly difficult when using gravity‑coring techniques. Kriging interpolation was used to develop a Canada-wide map showing minimum depths representing pre-industrial age (1880s; Fig. 1 ; ESM 2). In this analysis, ordinary kriging was carried out in ArcGIS using only empirical pre‑industrial sediment‑depth measurements compiled from published sources. No auxiliary environmental layers or secondary predictor variables were incorporated. The interpolation relied exclusively on ArcGIS’s default geostatistical procedures to characterize spatial autocorrelation and produce a continuous prediction surface. Table 1 Ecozone-specific target bottom depths (cm) estimated from a literature synthesis of 223 dated sediment cores, and their evaluation using the LakePulse (LP) subset (n = 212 lakes). For each ecozone, the table shows: (1) the minimum target depth estimated to reach pre-industrial (~ 1880s) sediments based on published age-depth models; (2) the number of lakes analyzed in the LP subset (n = 212); (3) the percentage of cores that were shorter than the estimated target depths for each ecozone; (4) the percentage of lakes in the LP subset in which the target bottom depth failed to reach pre-industrial conditions as indicated by excess 210 Pb above uncertainty; and (5) the mean Human Impact Index for lakes (max value = 1) in the LP subset within each ecozone. Ecozone Bottom sample target depth (cm) from lit review # lakes in LP subset % cores shorter than target depth % lakes with excess 210 Pb above uncertainty Mean Human Impact Index (± stdev) Taiga Cordillera 22 3 100 0 0.011 ± 0.190 Taiga Plains 22 14 100 0 0.026 ± 0.026 Boreal Cordillera 22 10 100 20 0.107 ± 0.225 Semi-Arid Plateaux 47 13 46 0 0.117 ± 0.104 Atlantic Highlands 32 20 50 0 0.121 ± 0.100 Montane Cordillera 32 26 15 4 0.124 ± 0.146 Boreal Shield 32 23 17 13 0.155 ± 0.169 Atlantic Maritime 32 23 39 9 0.194 ± 0.254 Prairies 47 12 33 8 0.272 ± 0.317 Pacific Maritime 32 17 18 0 0.299 ± 0.329 Boreal Plains 47 15 40 7 0.308 ± 0.257 Mixedwood Plains 32 36 28 22 0.315 ± 0.264 LakePulse field methods The selection strategy for the LakePulse study sites is detailed in Huot et al. ( 2019 ). Briefly, 664 lakes were sampled over three summers spanning 2017–2019. All potential study lakes within ⁓1 km of a road across the 12 focal ecozones were identified and then a subset were selected based on a stratified random sampling design that included lake size and a human impact index within each ecozone as the group stratifications. Sediment cores from ~ 664 lakes were collected during three summer field campaigns. The cores were retrieved from as close to the deepest point in each basin as possible to ensure sediments were representative of basin-wide conditions. The sediment cores were collected from each basin using a NLA gravity corer (Blomqvist, 1991 ) and sectioned on-site using a vertical extruder. Two top and two bottom intervals were collected from each lake: 0–1 cm, 1–2 cm and bottom intervals: (x-4)-(x-3) and (x-3)-(x-2), where x was the length of the core; the target length of x in each ecozone was established prior to the field campaign based on the literature review survey sites. We note that because the sediment cores all varied in length, some cores were either shorter or longer than the estimated target depth for each ecozone (Table 1 ; ESM 3). Due to the large number of lakes sampled during the LakePulse survey (664), we restricted the radiometric measurement of top-bottom sediments to a 212-lake subset (Fig. 3 ). Lakes from all 12 of the focal ecozones were included, although the total number in each ecozone varied due to sampling limitations (Table 1 ). Validation of bottom interval dates In the 212 LakePulse subset, unsupported 210 Pb activities of a top and bottom sediment interval from each site were measured (ESM 3) using gamma spectroscopy following the methods outlined in Schelske et al. ( 1994 ). Briefly, approximately 10 g of wet sediment was freeze-dried, placed into plastic tubes, and sealed with 2-ton epoxy. With only top and bottom sediment intervals collected per core, construction of full decay curves and generation of dates through an approach such as the constant rate of supply model (Appleby and Oldfield 1978 ) was not possible. The bottom samples were deemed to have reached background (i.e., pre 1880s) conditions if the uncertainty of excess 210 Pb was greater than the excess 210 Pb value. Excess 210 Pb was calculated by subtracting supported 210 Pb activities (i.e., Ra-226 activities (via its granddaughter isotope 214 Pb)) from total 210 Pb activities. For each bottom sample, the uncertainty of excess 210 Pb was calculated by: Uncertainty excess 210 Pb = sqrt (( 210 Pb error ^2) + ( 214 Pb error ^2)) Results & Discussion From the literature review survey (n = 223 sediment cores), the ecozones with the deepest threshold depths (i.e., highest sedimentation rates) estimated to reach pre-industrial conditions (ca. 1880s) were Boreal Plains, Prairies, and Semi-Arid Plains at 47 cm, followed by Atlantic Highlands, Atlantic Maritime, Boreal Shield, Mixedwood Plains, Montane Cordillera, and Pacific Maritime at 32 cm. The shallowest depths to pre-industrial conditions were lakes in the Boreal Cordillera, and Taiga Plains at 22 cm (Fig. 2 ; Table 1 ). Although the literature review survey contained no lakes from the Taiga Cordillera, the threshold depth for this ecozone was estimated using the sedimentation map (Fig. 1 ) at 22 cm, which is the same value as its nearest northern counterparts in the Taiga Plains and Boreal Cordillera (Fig. 1 ). From the 212 LakePulse subset, the estimated target depths were obtained for ⁓60% of sediment cores. In general, the majority of cores that fell short of the estimated target depths did so by less than ⁓3 cm (ESM 3) and given this closeness to the target depths, we found a much smaller percentage of lakes (⁓9%) did not extend to pre-Industrial conditions (discussed below). Several factors contribute to lake sedimentation rates including the watershed characteristics (geology, elevation, vegetation, size, basin morphometry) and climate variables (temperature, precipitation). However, in a study of lake sediment accumulation rates from ⁓500 lakes globally, Baud et al. ( 2021 ) showed that the strongest driver of modern accumulation rates was human activity in the catchments, notably cropland cover and population density. In the LakePulse study, a Human Impact Index (Huot et al. 2019 ) was calculated for each lake based on a mean, weighted estimation of land-use activities within that lakes’ catchment. For each land-use pixel within a study sites’ catchment, a value between 0 (least impacted) and 1 (most impacted) was assigned based on the following categories: urban, mines/oil, agriculture: 1; pasture, recent clearcuts: 0.5; natural landscapes: 0. There was generally a good congruence between the mean Human Impact Indices calculated for LakePulse sites (n = 212; Fig. 3 ) in each ecozone and the target bottom depth calculated for each ecozone from the literature review (n = 233; Fig. 2 ). For example, the lowest mean human impact indices were from the Taiga Plains, Taiga Cordillera and Boreal Cordillera, all of which had the lowest estimated target bottom depths (22 cm) required to reach pre-industrial sediments (Table 1 ). Similarly, ecozones with the highest mean human impact indices such as Boreal Plains and Prairies were regions identified with requiring the deepest target bottom depths (47 cm) to reach pre-industrial sediments. With a few exceptions (e.g., Semi-Arid Plateaux lakes), these data indicate human activity within a watershed is a key driver of lake sedimentation rates. An important question in any top-bottom study is: How often do the target bottom depths fail to reach pre-industrial conditions? Across all ecozones in the LakePulse top-bottom subset, only 18 out of 212 (< 9%) study lakes did not reach pre-industrial conditions (determined here by excess 210 Pb above measurement uncertainty; Table 1 ; ESM 3) based on the designated minimum target bottom depths. Somewhat complicating this assessment is that many sediment cores (⁓39%) of the 212 LakePulse subset were shorter than the estimated target depths (Table 1 ; ESM 3). That said, only half of the 18 cores mentioned above that did not reach pre-industrial conditions were shorter than their estimated target depths. Given the differing number of study sites within each ecozone, it is difficult to make direct comparisons among ecozones about how often the bottom target depths were insufficient to reach pre-industrial conditions. The Mixedwood Plains had the highest number of study sites (n = 36) and also the highest number of lakes (n = 8; 22%) where bottom sediments did not extend to pre-industrial times (Table 1 ). In contrast, the bottom sediments in lakes from several ecozones, including Atlantic Highland, Pacific Maritime, Semi-Arid Plateaux, and Taiga Plains, were all sufficiently deep to reach pre-industrial sediments (Table 1 ). Surface sediment excess 210 Pb values in the LakePulse subset varied widely across ecozones with highest overall values recorded in the Boreal Shield, Boreal Cordillera, Pacific Maritime, and Mixedwood Plains ecozones (Figs. 3 , 4 ; ESM 3). The lowest surface sediment excess 210 Pb values were generally recorded in the Taiga Cordillera, Taiga Plains, Prairies, and Boreal Plains ecozones. The surface sediment values show a slight negative correlation (r = − 0.176; P = 0.0103) with the mean human impact index, indicating human activity within the catchments is not strongly governing excess 210 Pb values. Generally, precipitation is a key driver of atmospheric 210 Pb inputs, but certainly other factors including the bedrock geology, the presence of frozen ground, and sediment focussing in deep basins are important (Appleby 2001 ; Liu et al. 2024 ). Excess 210 Pb values in bottom sediments were generally uniformly low indicating most reached background conditions, with only a few lakes in the Boreal Cordillera and Boreal Shield recording some high values (Fig. 3 ). Our data suggest that ecozone-specific differences in sediment accumulation across Canada are influenced by the intensity of human activity within lake catchments, reinforcing global evidence that land use is a dominant driver of modern sedimentation rates (Baud et al. 2021 ). The close correspondence between the mean human impact indices and the estimated target depths required to reach pre-industrial sediments underscores the importance of accounting for watershed disturbances when designing top-bottom paleolimnological studies. Encouragingly, the designated target bottom depths were sufficient to capture pre-industrial conditions in more than 90% of the LakePulse subset of lakes, suggesting that regionally calibrated depth thresholds are broadly effective, though refinements may be warranted for lakes with a high degree of catchment alteration. Our data indicate that top-bottom studies recording significant changes in less than ⁓10% of study sites may be a result of pre-industrial sediments not being obtained and thus should be interpreted with care. The lack of a clear relationship between surface sediment excess 210 Pb and the human impact index further highlights the complexity of sediment dynamics and the influence of additional factors such as atmospheric deposition and basin morphometry. Collectively, these findings provide a practical framework for optimizing sediment core sampling strategies at national scales and emphasize that continued watershed disturbance will act to accelerate sediment accumulation rates. Declarations Funding. AB was funded by an FRQNT Scholarship and an FRQNT Team grant awarded to IGE and JPS (as well as D. Antoniades, P. del Giorgio and P. Francus). Author Contribution NM, AB, CM-J, AJ, IG-E, JPS wrote the main manuscript text; AB, IG-E conceptualization; AB, IG-E, CM-J, AJ data analyses. Acknowledgement We thank the NSERC Lake Pulse network for great assistance in coordination and sampling. AB was funded by an FRQNT Scholarship and an FRQNT Team grant awarded to IGE and JPS (as well as D. Antoniades, P. del Giorgio and P. Francus). We also acknowledge discussions across the entire FRQNT Team including the aforementioned individuals as well as D. Zilkey, H. Ghanbari and K. Griffiths. Data Availability We compiled published ²¹⁰Pb chronologies (post-1850 CE) searched using keywords related to geographic regions (e.g., “Prairies,” “NWT,” “Yukon”, “Alberta”, etc.) and names of researchers active in those areas. In total, 357 lake sedimentation lake sediment records were compiled, including 124 from Baud et al. (2021) and 233 newly identified sites through the supplemental search (full reference list given in ESM 1). References Appleby (2001) Chronostratigraphic techniques in recent sediments. In: Last WM, Smol JP (eds) Tracking Environmental Change Using Lake Sediments. Volume 1: Basin Analysis, Coring, and Chronological Techniques. Kluwer Academic Publishers, Dordrecht, The Netherlands. pp 171–203 Appleby P, Oldfield F (1978) The calculation of lead-210 dates assuming a constant rate of supply of unsupported 210 Pb to the sediment. Catena 5:1–8 Baud A (2022) Anthropogenic development over the last ~ 200 years leaves physical and geochemical imprints in lake sediment records. PhD thesis, McGill University. 316 p Baud A, Jenny J-P, Francus P, Gregory-Eaves I (2021) Global acceleration of lake sediment accumulation rates linked to human activities. J Paleolimnol 66:453–467 https://doi.org/10.1007/s10933-021-00217-6 Blomqvist S (1991) Quantitative sampling of soft bottom sediments: problems and solutions. Mar Ecol Prog Ser 72: 295–304 Camarero L, Botev I, Muri G, Psenner R, Rose N and Stuchlík E (2009) Trace elements in alpine and arctic lake sediments as a record of diffuse atmospheric contamination across Europe. Freshwater Biology, 54: 2518–2532 Charles DF, Smol JP (1990) The PIRLA II project: regional assessment of lake acidification trends. Internationale Vereinigung für theoretische und angewandte Limnologie: Verhandlungen, 24(1): 474–480 Huot Y, Brown CA, Potvin G, Antoniades D, Baulch HM, et al (2019). The NSERC Canadian Lake Pulse Network: A national assessment of lake health providing science for water management in a changing climate. Science of the Total Environment 695, 133668 Liu C, Chen J, Zhang W, Ungar K (2024) Outdoor Radon Dose Rate in Canada’s Arctic amid Climate Change. Environmental Science & Technology 58(26): 11309–11319 Rahman M, Vermaire JC, Sivarajah B (2025) Assessing shifts in diatom communities in eastern Ontario recreational lakes in relation to land-use and climatic changes over the past ~ 150 years using a top–bottom paleolimnological approach. Journal of Paleolimnology, 73: 517–535 Schelske CL, Peplow A, Brenner M, Spencer CN (1994) Low-background gamma counting: applications for 210 Pb dating of sediments. Journal of Paleolimnology 10: 115–128 Smol JP (2008) Pollution of lakes and rivers: A paleoenvironmental perspective, 2nd edn. Blackwell Publishing, Oxford, 383 pp Additional Declarations No competing interests reported. Supplementary Files ESM1BibliographyCanadaSAR.docx ESM2Litreviewsites.xlsx ESM3lakepulsesubset212.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 07 May, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 10 Apr, 2026 Submission checks completed at journal 10 Apr, 2026 First submitted to journal 08 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9359156","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623748805,"identity":"a610170b-c58c-4f1a-9271-b4186b456eaa","order_by":0,"name":"Neal Michelutti","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYFAC9uM/PpCohSdBcgap1hhI85Ck3lzsQIKxTdlhOX7p9mcSDDV2hLVYzk48kJxz7rCx5JwzZhIMx5KJcNXthITDuW2HEzfcyGGTYGxgJkqLYbNl2+H6/TfSnwG11BOlxZiZse1wgoFEghlQy2FitOSkMfacSzeccSPH2CLh2HFitKQfY/hRZi3PPyP94Y0PNdWEtUAAG5ROIFYDQssoGAWjYBSMAmwAANQcN0FvPz6cAAAAAElFTkSuQmCC","orcid":"","institution":"Queen's University","correspondingAuthor":true,"prefix":"","firstName":"Neal","middleName":"","lastName":"Michelutti","suffix":""},{"id":623748806,"identity":"4ff1018d-148e-4e58-90c1-0edb92e0f12c","order_by":1,"name":"Alexandre Baud","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Alexandre","middleName":"","lastName":"Baud","suffix":""},{"id":623748811,"identity":"330c780f-aae0-4c2b-ab46-829e42429636","order_by":2,"name":"Carsten Meyer-Jacob","email":"","orcid":"","institution":"Université du Québec","correspondingAuthor":false,"prefix":"","firstName":"Carsten","middleName":"","lastName":"Meyer-Jacob","suffix":""},{"id":623748814,"identity":"20c3bd94-69df-494e-a8f8-66d50bb8c61c","order_by":3,"name":"Adam Jeziorski","email":"","orcid":"","institution":"Queen's University","correspondingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Jeziorski","suffix":""},{"id":623748817,"identity":"c953b895-f016-4a54-993d-8ab5b8de1e70","order_by":4,"name":"Irene Gregory-Eaves","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Irene","middleName":"","lastName":"Gregory-Eaves","suffix":""},{"id":623748821,"identity":"fce17d5b-58ad-4dd8-a31d-1ed01bf6081a","order_by":5,"name":"John Paul Smol","email":"","orcid":"","institution":"Queen's University","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"Paul","lastName":"Smol","suffix":""}],"badges":[],"createdAt":"2026-04-08 15:53:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9359156/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9359156/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107489519,"identity":"d1769c83-2643-494a-a14c-1ae5c47c1f98","added_by":"auto","created_at":"2026-04-22 02:47:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":682807,"visible":true,"origin":"","legend":"\u003cp\u003eInterpolated spatial distribution of pre-industrial (1880 CE) sediment depth using kriging methods based on data collected from the literature (357 lakes; shown as white squares; adapted from Baud (2022)).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/77c54ede7a5ade031ca80c6f.png"},{"id":107704380,"identity":"37d0600a-9f09-45c1-96d1-14ec2a053d08","added_by":"auto","created_at":"2026-04-24 08:45:06","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":184107,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing the sediment depth at age 1880 based on \u003csup\u003e210\u003c/sup\u003ePb-dated cores from the literature review (n=223 sediment cores; ESM 2). Number of lakes in each ecozone indicated at bottom. The dotted lines correspond to the target depths used in the LakePulse top-bottom survey (see also Table 1). Boxplot colours indicate bottom target depth groupings: white = 22 cm (Boreal Cordillera, Taiga Plains); medium grey = 32 cm (Atlantic Highlands, Atlantic Maritime, Boreal Shield, Mixedwood Plains, Montane Cordillera, Pacific Maritime); dark grey = 47 cm (Boreal Plains, Prairies, Semi-Arid Plateaux).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/40913a4df14d6401159b4455.jpeg"},{"id":107704492,"identity":"034c7860-70b5-4141-b043-21148d8bffd5","added_by":"auto","created_at":"2026-04-24 08:45:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":123358,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of top-bottom samples (n=212) from the LakePulse network across 12 ecozones.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/13278be3b34e38ee0a75ba0a.png"},{"id":107463793,"identity":"856e80cc-8ffb-4570-8261-3d4301dc68a9","added_by":"auto","created_at":"2026-04-21 17:43:40","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":297453,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing excess \u003csup\u003e210\u003c/sup\u003ePb activities for 212 LakePulse top (upper panel) and bottom (lower panel) samples across 12 ecozones.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/327be5d05b70de702ebcea8a.jpeg"},{"id":108494354,"identity":"a3d9eb2f-aaa8-4a59-bef6-14d03c0d72e8","added_by":"auto","created_at":"2026-05-05 10:04:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1454280,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/d41d280d-3c87-4a07-b93c-7e91e788d495.pdf"},{"id":107463789,"identity":"14429694-f55d-47d3-bb95-535e9d09b4ea","added_by":"auto","created_at":"2026-04-21 17:43:40","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":30252,"visible":true,"origin":"","legend":"","description":"","filename":"ESM1BibliographyCanadaSAR.docx","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/fa9907f352ade64ffbf9948f.docx"},{"id":108180613,"identity":"f702283d-3ec5-497c-80ff-ff6de1ca0c8f","added_by":"auto","created_at":"2026-04-30 08:49:41","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23652,"visible":true,"origin":"","legend":"","description":"","filename":"ESM2Litreviewsites.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/b78addc7c621129dc4addfd4.xlsx"},{"id":107463791,"identity":"59823006-1982-4eeb-a2d0-434a8fbea982","added_by":"auto","created_at":"2026-04-21 17:43:40","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":68871,"visible":true,"origin":"","legend":"","description":"","filename":"ESM3lakepulsesubset212.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9359156/v1/3ddb4970dc4bc347412580b4.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Toward Robust Top-Bottom Paleolimnological Assessments: A Canada-Wide Sedimentation Map Evaluated with LakePulse Data","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe \u0026ldquo;top-bottom\u0026rdquo; approach in paleolimnology is a comparative method that involves analyzing the surface (top) sediment layer, representing modern conditions, and a deeper (bottom) interval, representing reference conditions prior to major anthropogenic impacts, typically pre-1880s (Smol \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This approach is often used in large-scale or multi-lake studies where the goal is to provide a relatively rapid assessment of the magnitude and direction of limnological change across broad geographic areas, or regions with differing land-use histories (e.g., Charles and Smol \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Camarero et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Rahman et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The recovery of the most recently deposited sediments is easily confirmed by the presence of an intact sediment-water interface. However, in the absence of a dating profile, it is possible that the bottom layer may not actually represent pre-impact conditions. Lake sediment accumulation rates vary depending on several factors including ecoregions and watershed characteristics (Baud et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); therefore, a fixed sediment depth will not correspond to the same historical time across different lakes. While the top-bottom approach has clear advantages for rapidly assessing change in a large number of lakes, its reliance on assumed ages for bottom sediments can limit its interpretive strength.\u003c/p\u003e \u003cp\u003eTypically, a top-bottom study will use a sub-set of fully dated sediment cores from within a particular region to approximate the depth corresponding to pre-impact conditions. However, the validity of the assumptions underlying the date estimations is rarely tested. The need for a Canada-wide contextualization of sedimentation rates was prompted by the creation of the Natural Sciences and Engineering Research Council of Canada (NSERC) Canadian LakePulse Network (hereafter LakePulse), which was launched in 2016 to provide the first national assessment of lake health (Huot et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The LakePulse program was a coordinated effort that obtained detailed limnological data from 664 lakes and included a paleolimnological component that collected\u0026thinsp;~\u0026thinsp;664 top-bottom sediment samples and ~\u0026thinsp;120 full cores spanning 12 ecozones (Huot et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This extensive sampling program, carried out by a coordinated and standardized effort consisting of several independent field teams, required \u003cem\u003ea priori\u003c/em\u003e knowledge of the estimated background sediment depth across various Canadian ecoregions to ensure consistent interpretation of top-bottom sediment samples.\u003c/p\u003e \u003cp\u003eOur study has two distinct, but interrelated, objectives. The first is the development of a spatially interpolated map showing minimum sediment core depths for pre-industrial times (ca. 1880s) from across the different ecoregions of Canada (including some nearby sites in northern USA) estimated using age-depth models from the published literature. This nationwide investigation of sedimentation rates was used to provide clear target depths for bottom intervals of cores collected during the LakePulse field sampling. In addition, this data synthesis provides important insights into the sedimentation rates among different Canadian ecozones and will help guide future top-bottom studies to select ecozone-dependent sediment depths corresponding to pre-industrial activities. The second objective centers on using the LakePulse data to determine how often the bottom depth targets failed on a large-scale (i.e., were the estimated pre-industrial bottom depths actually of pre-industrial age?) and, in doing so, identify regions where the assumptions of a standard top-bottom approach may be harder to meet. Knowledge of the approximate percentage of lakes in a top-bottom study that fail to reach target bottom depths (i.e., pre-industrial conditions) helps establish a threshold for when top-bottom results may reflect meaningful ecological change rather than being an artifact of varying sedimentation rates.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eDevelopment of a Canada-wide lake sedimentation rate map\u003c/p\u003e \u003cp\u003eThe Canadian sedimentation rate map was based on published literature from 357 dated lake sediment cores distributed across Canada and the Northern USA (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Figures and tables were digitized from the scientific literature using DigitizeIt software, following a methodology similar to Baud et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), which focused on global sedimentation rates. To address gaps in coverage, a supplemental literature search was conducted. This search targeted records with recent ²¹⁰Pb chronologies (post-1850 CE) and included studies beyond those published in the \u003cem\u003eJournal of Paleolimnology\u003c/em\u003e, unlike Baud et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Keywords related to geographic regions (e.g., “Prairies,” “NWT,” “Yukon”, “Alberta”, etc.) and names of researchers active in those areas were used to identify relevant studies. In total, 357 lake sedimentation records were compiled, including 124 from Baud et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) and 233 newly identified sites through the supplemental search (full reference list given in ESM 1). These additions significantly improved the spatial coverage of sedimentation data across Canada.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe target bottom depths for lakes in each ecozone were determined based on qualitative visual inspection of the distribution of core depths that dated to ~ 1880 CE (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). From the 357 lakes compiled in the literature review, this number dropped to 223 lakes when only considering the ecozones sampled in the LakePulse dataset. Practical feasibility was also a factor in setting the target depths, as retrieving longer sediment cores becomes increasingly difficult when using gravity‑coring techniques. Kriging interpolation was used to develop a Canada-wide map showing minimum depths representing pre-industrial age (1880s; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; ESM 2). In this analysis, ordinary kriging was carried out in ArcGIS using only empirical pre‑industrial sediment‑depth measurements compiled from published sources. No auxiliary environmental layers or secondary predictor variables were incorporated. The interpolation relied exclusively on ArcGIS’s default geostatistical procedures to characterize spatial autocorrelation and produce a continuous prediction surface.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab1\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEcozone-specific target bottom depths (cm) estimated from a literature synthesis of 223 dated sediment cores, and their evaluation using the LakePulse (LP) subset (n = 212 lakes). For each ecozone, the table shows: (1) the minimum target depth estimated to reach pre-industrial (~ 1880s) sediments based on published age-depth models; (2) the number of lakes analyzed in the LP subset (n = 212); (3) the percentage of cores that were shorter than the estimated target depths for each ecozone; (4) the percentage of lakes in the LP subset in which the target bottom depth failed to reach pre-industrial conditions as indicated by excess \u003csup\u003e210\u003c/sup\u003ePb above uncertainty; and (5) the mean Human Impact Index for lakes (max value = 1) in the LP subset within each ecozone.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eEcozone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eBottom sample target depth (cm) from lit review\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003e# lakes in LP subset\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003e% cores shorter than target depth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003e% lakes with excess \u003csup\u003e210\u003c/sup\u003ePb above uncertainty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eMean Human Impact Index (± stdev)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTaiga Cordillera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.011 ± 0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTaiga Plains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.026 ± 0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBoreal Cordillera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.107 ± 0.225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSemi-Arid Plateaux\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.117 ± 0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAtlantic Highlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.121 ± 0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMontane Cordillera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.124 ± 0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBoreal Shield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.155 ± 0.169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAtlantic Maritime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.194 ± 0.254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePrairies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.272 ± 0.317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePacific Maritime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.299 ± 0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBoreal Plains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.308 ± 0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMixedwood Plains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.315 ± 0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eLakePulse field methods\u003c/p\u003e \u003cp\u003eThe selection strategy for the LakePulse study sites is detailed in Huot et al. (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Briefly, 664 lakes were sampled over three summers spanning 2017–2019. All potential study lakes within ⁓1 km of a road across the 12 focal ecozones were identified and then a subset were selected based on a stratified random sampling design that included lake size and a human impact index within each ecozone as the group stratifications.\u003c/p\u003e \u003cp\u003eSediment cores from ~ 664 lakes were collected during three summer field campaigns. The cores were retrieved from as close to the deepest point in each basin as possible to ensure sediments were representative of basin-wide conditions. The sediment cores were collected from each basin using a NLA gravity corer (Blomqvist, \u003cspan class=\"CitationRef\"\u003e1991\u003c/span\u003e) and sectioned on-site using a vertical extruder. Two top and two bottom intervals were collected from each lake: 0–1 cm, 1–2 cm and bottom intervals: (x-4)-(x-3) and (x-3)-(x-2), where x was the length of the core; the target length of x in each ecozone was established prior to the field campaign based on the literature review survey sites. We note that because the sediment cores all varied in length, some cores were either shorter or longer than the estimated target depth for each ecozone (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; ESM 3). Due to the large number of lakes sampled during the LakePulse survey (664), we restricted the radiometric measurement of top-bottom sediments to a 212-lake subset (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Lakes from all 12 of the focal ecozones were included, although the total number in each ecozone varied due to sampling limitations (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eValidation of bottom interval dates\u003c/p\u003e \u003cp\u003eIn the 212 LakePulse subset, unsupported \u003csup\u003e210\u003c/sup\u003ePb activities of a top and bottom sediment interval from each site were measured (ESM 3) using gamma spectroscopy following the methods outlined in Schelske et al. (\u003cspan class=\"CitationRef\"\u003e1994\u003c/span\u003e). Briefly, approximately 10 g of wet sediment was freeze-dried, placed into plastic tubes, and sealed with 2-ton epoxy. With only top and bottom sediment intervals collected per core, construction of full decay curves and generation of dates through an approach such as the constant rate of supply model (Appleby and Oldfield \u003cspan class=\"CitationRef\"\u003e1978\u003c/span\u003e) was not possible. The bottom samples were deemed to have reached background (i.e., pre 1880s) conditions if the uncertainty of excess \u003csup\u003e210\u003c/sup\u003ePb was greater than the excess \u003csup\u003e210\u003c/sup\u003ePb value. Excess \u003csup\u003e210\u003c/sup\u003ePb was calculated by subtracting supported \u003csup\u003e210\u003c/sup\u003ePb activities (i.e., Ra-226 activities (via its granddaughter isotope \u003csup\u003e214\u003c/sup\u003ePb)) from total \u003csup\u003e210\u003c/sup\u003ePb activities. For each bottom sample, the uncertainty of excess \u003csup\u003e210\u003c/sup\u003ePb was calculated by:\u003c/p\u003e \u003cp\u003eUncertainty excess \u003csup\u003e210\u003c/sup\u003ePb = sqrt ((\u003csup\u003e210\u003c/sup\u003ePb\u003csub\u003eerror\u003c/sub\u003e ^2) + (\u003csup\u003e214\u003c/sup\u003ePb\u003csub\u003eerror\u003c/sub\u003e ^2))\u003c/p\u003e "},{"header":"Results \u0026 Discussion","content":"\u003cp\u003eFrom the literature review survey (n = 223 sediment cores), the ecozones with the deepest threshold depths (i.e., highest sedimentation rates) estimated to reach pre-industrial conditions (ca. 1880s) were Boreal Plains, Prairies, and Semi-Arid Plains at 47 cm, followed by Atlantic Highlands, Atlantic Maritime, Boreal Shield, Mixedwood Plains, Montane Cordillera, and Pacific Maritime at 32 cm. The shallowest depths to pre-industrial conditions were lakes in the Boreal Cordillera, and Taiga Plains at 22 cm (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e; Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Although the literature review survey contained no lakes from the Taiga Cordillera, the threshold depth for this ecozone was estimated using the sedimentation map (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) at 22 cm, which is the same value as its nearest northern counterparts in the Taiga Plains and Boreal Cordillera (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). From the 212 LakePulse subset, the estimated target depths were obtained for ⁓60% of sediment cores. In general, the majority of cores that fell short of the estimated target depths did so by less than ⁓3 cm (ESM 3) and given this closeness to the target depths, we found a much smaller percentage of lakes (⁓9%) did not extend to pre-Industrial conditions (discussed below).\u003c/p\u003e\u003cp\u003eSeveral factors contribute to lake sedimentation rates including the watershed characteristics (geology, elevation, vegetation, size, basin morphometry) and climate variables (temperature, precipitation). However, in a study of lake sediment accumulation rates from ⁓500 lakes globally, Baud et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) showed that the strongest driver of modern accumulation rates was human activity in the catchments, notably cropland cover and population density. In the LakePulse study, a Human Impact Index (Huot et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e) was calculated for each lake based on a mean, weighted estimation of land-use activities within that lakes’ catchment. For each land-use pixel within a study sites’ catchment, a value between 0 (least impacted) and 1 (most impacted) was assigned based on the following categories: urban, mines/oil, agriculture: 1; pasture, recent clearcuts: 0.5; natural landscapes: 0.\u003c/p\u003e\u003cp\u003eThere was generally a good congruence between the mean Human Impact Indices calculated for LakePulse sites (n = 212; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e) in each ecozone and the target bottom depth calculated for each ecozone from the literature review (n = 233; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). For example, the lowest mean human impact indices were from the Taiga Plains, Taiga Cordillera and Boreal Cordillera, all of which had the lowest estimated target bottom depths (22 cm) required to reach pre-industrial sediments (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Similarly, ecozones with the highest mean human impact indices such as Boreal Plains and Prairies were regions identified with requiring the deepest target bottom depths (47 cm) to reach pre-industrial sediments. With a few exceptions (e.g., Semi-Arid Plateaux lakes), these data indicate human activity within a watershed is a key driver of lake sedimentation rates.\u003c/p\u003e\u003cp\u003eAn important question in any top-bottom study is: How often do the target bottom depths fail to reach pre-industrial conditions? Across all ecozones in the LakePulse top-bottom subset, only 18 out of 212 (\u0026lt; 9%) study lakes did not reach pre-industrial conditions (determined here by excess \u003csup\u003e210\u003c/sup\u003ePb above measurement uncertainty; Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; ESM 3) based on the designated minimum target bottom depths. Somewhat complicating this assessment is that many sediment cores (⁓39%) of the 212 LakePulse subset were shorter than the estimated target depths (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; ESM 3). That said, only half of the 18 cores mentioned above that did not reach pre-industrial conditions were shorter than their estimated target depths.\u003c/p\u003e\u003cp\u003eGiven the differing number of study sites within each ecozone, it is difficult to make direct comparisons among ecozones about how often the bottom target depths were insufficient to reach pre-industrial conditions. The Mixedwood Plains had the highest number of study sites (n = 36) and also the highest number of lakes (n = 8; 22%) where bottom sediments did not extend to pre-industrial times (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, the bottom sediments in lakes from several ecozones, including Atlantic Highland, Pacific Maritime, Semi-Arid Plateaux, and Taiga Plains, were all sufficiently deep to reach pre-industrial sediments (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSurface sediment excess \u003csup\u003e210\u003c/sup\u003ePb values in the LakePulse subset varied widely across ecozones with highest overall values recorded in the Boreal Shield, Boreal Cordillera, Pacific Maritime, and Mixedwood Plains ecozones (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e; ESM 3). The lowest surface sediment excess \u003csup\u003e210\u003c/sup\u003ePb values were generally recorded in the Taiga Cordillera, Taiga Plains, Prairies, and Boreal Plains ecozones. The surface sediment values show a slight negative correlation (r = − 0.176; P = 0.0103) with the mean human impact index, indicating human activity within the catchments is not strongly governing excess \u003csup\u003e210\u003c/sup\u003ePb values. Generally, precipitation is a key driver of atmospheric \u003csup\u003e210\u003c/sup\u003ePb inputs, but certainly other factors including the bedrock geology, the presence of frozen ground, and sediment focussing in deep basins are important (Appleby \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e; Liu et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Excess \u003csup\u003e210\u003c/sup\u003ePb values in bottom sediments were generally uniformly low indicating most reached background conditions, with only a few lakes in the Boreal Cordillera and Boreal Shield recording some high values (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur data suggest that ecozone-specific differences in sediment accumulation across Canada are influenced by the intensity of human activity within lake catchments, reinforcing global evidence that land use is a dominant driver of modern sedimentation rates (Baud et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The close correspondence between the mean human impact indices and the estimated target depths required to reach pre-industrial sediments underscores the importance of accounting for watershed disturbances when designing top-bottom paleolimnological studies. Encouragingly, the designated target bottom depths were sufficient to capture pre-industrial conditions in more than 90% of the LakePulse subset of lakes, suggesting that regionally calibrated depth thresholds are broadly effective, though refinements may be warranted for lakes with a high degree of catchment alteration. Our data indicate that top-bottom studies recording significant changes in less than ⁓10% of study sites may be a result of pre-industrial sediments not being obtained and thus should be interpreted with care. The lack of a clear relationship between surface sediment excess \u003csup\u003e210\u003c/sup\u003ePb and the human impact index further highlights the complexity of sediment dynamics and the influence of additional factors such as atmospheric deposition and basin morphometry. Collectively, these findings provide a practical framework for optimizing sediment core sampling strategies at national scales and emphasize that continued watershed disturbance will act to accelerate sediment accumulation rates.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding.\u003c/h2\u003e \u003cp\u003eAB was funded by an FRQNT Scholarship and an FRQNT Team grant awarded to IGE and JPS (as well as D. Antoniades, P. del Giorgio and P. Francus).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNM, AB, CM-J, AJ, IG-E, JPS wrote the main manuscript text; AB, IG-E conceptualization; AB, IG-E, CM-J, AJ data analyses.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the NSERC Lake Pulse network for great assistance in coordination and sampling. AB was funded by an FRQNT Scholarship and an FRQNT Team grant awarded to IGE and JPS (as well as D. Antoniades, P. del Giorgio and P. Francus). We also acknowledge discussions across the entire FRQNT Team including the aforementioned individuals as well as D. Zilkey, H. Ghanbari and K. Griffiths.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eWe compiled published \u0026sup2;\u0026sup1;⁰Pb chronologies (post-1850 CE) searched using keywords related to geographic regions (e.g., \u0026ldquo;Prairies,\u0026rdquo; \u0026ldquo;NWT,\u0026rdquo; \u0026ldquo;Yukon\u0026rdquo;, \u0026ldquo;Alberta\u0026rdquo;, etc.) and names of researchers active in those areas. In total, 357 lake sedimentation lake sediment records were compiled, including 124 from Baud et al. (2021) and 233 newly identified sites through the supplemental search (full reference list given in ESM 1).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAppleby (2001) Chronostratigraphic techniques in recent sediments. In: Last WM, Smol JP (eds) Tracking Environmental Change Using Lake Sediments. Volume 1: Basin Analysis, Coring, and Chronological Techniques. Kluwer Academic Publishers, Dordrecht, The Netherlands. pp 171\u0026ndash;203\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAppleby P, Oldfield F (1978) The calculation of lead-210 dates assuming a constant rate of supply of unsupported \u003csup\u003e210\u003c/sup\u003ePb to the sediment. Catena 5:1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaud A (2022) Anthropogenic development over the last\u0026thinsp;~\u0026thinsp;200 years leaves physical and geochemical imprints in lake sediment records. PhD thesis, McGill University. 316 p\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaud A, Jenny J-P, Francus P, Gregory-Eaves I (2021) Global acceleration of lake sediment accumulation rates linked to human activities. J Paleolimnol 66:453\u0026ndash;467\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10933-021-00217-6\u003c/span\u003e\u003cspan address=\"10.1007/s10933-021-00217-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlomqvist S (1991) Quantitative sampling of soft bottom sediments: problems and solutions. Mar Ecol Prog Ser 72: 295\u0026ndash;304\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCamarero L, Botev I, Muri G, Psenner R, Rose N and Stuchl\u0026iacute;k E (2009) Trace elements in alpine and arctic lake sediments as a record of diffuse atmospheric contamination across Europe. Freshwater Biology, 54: 2518\u0026ndash;2532\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharles DF, Smol JP (1990) The PIRLA II project: regional assessment of lake acidification trends. Internationale Vereinigung f\u0026uuml;r theoretische und angewandte Limnologie: Verhandlungen, 24(1): 474\u0026ndash;480\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuot Y, Brown CA, Potvin G, Antoniades D, Baulch HM, et al (2019). The NSERC Canadian Lake Pulse Network: A national assessment of lake health providing science for water management in a changing climate. Science of the Total Environment 695, 133668\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu C, Chen J, Zhang W, Ungar K (2024) Outdoor Radon Dose Rate in Canada\u0026rsquo;s Arctic amid Climate Change. Environmental Science \u0026amp; Technology 58(26): 11309\u0026ndash;11319\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahman M, Vermaire JC, Sivarajah B (2025) Assessing shifts in diatom communities in eastern Ontario recreational lakes in relation to land-use and climatic changes over the past ~\u0026thinsp;150 years using a top\u0026ndash;bottom paleolimnological approach. Journal of Paleolimnology, 73: 517\u0026ndash;535\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchelske CL, Peplow A, Brenner M, Spencer CN (1994) Low-background gamma counting: applications for \u003csup\u003e210\u003c/sup\u003ePb dating of sediments. Journal of Paleolimnology 10: 115\u0026ndash;128\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmol JP (2008) Pollution of lakes and rivers: A paleoenvironmental perspective, 2nd edn. Blackwell Publishing, Oxford, 383 pp\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-paleolimnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jopl","sideBox":"Learn more about [Journal of Paleolimnology](http://link.springer.com/journal/10933)","snPcode":"10933","submissionUrl":"https://submission.nature.com/new-submission/10933/3","title":"Journal of Paleolimnology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Top-bottom paleolimnology, NSERC Canadian LakePulse network, Lake sediment accumulation, Kriging interpolation, 210Pb radioisotopes","lastPublishedDoi":"10.21203/rs.3.rs-9359156/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9359156/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe \u0026ldquo;top\u0026ndash;bottom\u0026rdquo; approach in paleolimnology provides a rapid means of assessing environmental change by comparing modern surface sediments with deeper intervals assumed to pre-date major anthropogenic disturbances (ca. pre-1880). However, spatial variability in sediment accumulation rates can undermine the assumption that a fixed depth will represent background conditions in all study lakes. The largest top-bottom study conducted to date was the Canadian LakePulse Network, which collected 664 sediment cores from 12 ecozones as part of a comprehensive program aimed at assessing the health of lakes across Canada. To estimate minimum depths corresponding to pre-industrial conditions for the LakePulse study sites, we compiled 357 published \u003csup\u003e210\u003c/sup\u003ePb-dated sediment cores from across Canada and the northern United States. These data were used to generate a spatially interpolated sedimentation map, providing a national framework for Canadian lakes that can be used to inform future top-bottom studies. A representative subset of 212 LakePulse lakes was evaluated using excess \u003csup\u003e210\u003c/sup\u003ePb measurements to test whether estimated bottom intervals reached pre-industrial age. Target bottom depths varied among ecozones, ranging from 22 cm in the northern regions of the Taiga Plains, Taiga Cordillera and Boreal Cordillera to 47 cm in the Boreal Plains, Semi-Arid Plateaux and Prairies. Target depths were strongly aligned with ecozone-level human impact indices, indicating that watershed land use is a dominant driver of recent sediment accumulation. Validation analyses, using the uncertainty of excess \u003csup\u003e210\u003c/sup\u003ePb, showed that fewer than 9% of the study lakes failed to reach pre-industrial conditions at, or below, the target depths, although higher failure rates occurred in more impacted regions such as the Mixedwood Plains. These findings demonstrate that regionally calibrated depth targets can reliably support large-scale top-bottom assessments while highlighting the importance of accounting for watershed disturbance across diverse landscapes.\u003c/p\u003e","manuscriptTitle":"Toward Robust Top-Bottom Paleolimnological Assessments: A Canada-Wide Sedimentation Map Evaluated with LakePulse Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-21 17:43:31","doi":"10.21203/rs.3.rs-9359156/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-07T13:34:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"220605565730146251496570311013215868240","date":"2026-04-15T15:08:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-14T11:44:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-10T14:25:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-10T14:25:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Paleolimnology","date":"2026-04-08T15:47:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-paleolimnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jopl","sideBox":"Learn more about [Journal of Paleolimnology](http://link.springer.com/journal/10933)","snPcode":"10933","submissionUrl":"https://submission.nature.com/new-submission/10933/3","title":"Journal of Paleolimnology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3784a409-4cbe-41d0-aeb8-7347abd85666","owner":[],"postedDate":"April 21st, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-07T13:34:28+00:00","index":16,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T17:43:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-21 17:43:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9359156","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9359156","identity":"rs-9359156","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}