Antczak-Orlewska, Olga; Święta-Musznicka, Joanna; Trębska, Gabriela; Janik, Ewa; Rzodkiewicz, Monika; Pawłowski, Dominik; Okupny, Daniel; Nazarova, Larisa B; Kuliński, Karol; Koziorowska, Katarzyna; Kittel, Piotr; Kotrys, Bartosz; Płóciennik, Mateusz (2026): Chironomidae-inferred late Holocene water level reconstruction from the alas lake (AL1 profile) in the Yana-Indigirka Lowland, NE Yakutia [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.987967
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Published: 2026-01-05 • DOI registered: 2026-02-03
Abstract:
This data set presents the reconstructed water level for AL1 sediment core based on subfossil Chironomidae data. The core was collected in July 2019 from from the lower alas level, approximately 1.5 km north of the Berelekh River (70.84057° N, 147.48369° E). It was taken from the active layer as a monolith using a Russian auger and was subsequently cut into 1-cm slices in the laboratory of the Chokurdakh Scientific Tundra Station. Water depth was reconstructed using the East-Siberian chironomid-based inference model (WA-PLS, 1 component; r2 boot = 0.62; RMSEP = 0.35) based on a modern calibration dataset of 150 lakes from Yakutia (Nazarova et al., 2011). To determine whether the modern calibration model had adequate analogues for the fossil assemblages, the modern analogue technique (MAT) was performed using C2 version 1.7.7 (Juggins, 2007) on percentage, square-root-transformed data. The distance between each fossil sample and its most similar modern assemblage was compared, and the 5th percentile of all squared-chord distances of the modern data was used to define the cut-off for a good analogue (Plikk et al., 2019).
Keyword(s):
References:
Juggins, Stephen (2007): C2 Version 1.5 User Guide. Software for Ecological and Palaeoecological Data Analysis and Visualisation [software]. Newcastle University, Newcastle upon Tyne
Nazarova, Larisa B; Herzschuh, Ulrike; Wetterich, Sebastian; Kumke, Thomas; Pestryakova, Luidmila A (2011): Chironomid-based inference models for estimating mean July air temperature and water depth from lakes in Yakutia, northeastern Russia. Journal of Paleolimnology, 45(1), 57-71, https://doi.org/10.1007/s10933-010-9479-4
Plikk, Anna; Engels, Stefan; Luoto, Tomi P; Nazarova, Larisa B; Salonen, J Sakari; Helmens, Karin F (2019): Chironomid-based temperature reconstruction for the Eemian Interglacial (MIS 5e) at Sokli, northeast Finland. Journal of Paleolimnology, 61(3), 355-371, https://doi.org/10.1007/s10933-018-00064-y
Funding:
Horizon 2020 (H2020), grant/award no. HOLARCLIM: The Late Holocene climate change inferred from the wetland ecosystems in the lower Indigirka River basin
Ministerstwo Nauki i Szkolnictwa Wyższego, grant/award no. RID/SP/0045/2024/01: Regional Excellence Initiative
National Science Centre Poland (NCN), grant/award no. 2023/07/X/NZ8/00294: Holocene climatic fluctuations in the Yana-Indigirka Lowland (north-eastern Yakutia, Republic of Sakha) in the light of paleoecological research (MINIATURA-7)
Coverage:
Latitude: 70.840583 * Longitude: 147.483694
Date/Time Start: 2019-07-09T00:00:00 * Date/Time End: 2019-07-09T00:00:00
Minimum DEPTH, sediment/rock: 0.010 m * Maximum DEPTH, sediment/rock: 0.235 m
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | DEPTH, sediment/rock | Depth sed | m | Antczak-Orlewska, Olga | Geocode | |
| 2 | Lake, water depth, reconstructed | Lake water depth reconstr | m | Antczak-Orlewska, Olga | Transfer function; weighted averaging partial least squares (WA-PLS) | |
| 3 | Bootstrapping cross validation, standard error | SEB | ± | Antczak-Orlewska, Olga | Transfer function; weighted averaging partial least squares (WA-PLS) | |
| 4 | Dissimilarity, minimum | DC min | Antczak-Orlewska, Olga | Transfer function; weighted averaging partial least squares (WA-PLS) | ||
| 5 | Standard deviation | Std dev | ± | Antczak-Orlewska, Olga | Transfer function; weighted averaging partial least squares (WA-PLS) |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Size:
92 data points
Data
| 1 Depth sed [m] | 2 Lake water depth reconstr [m] | 3 SEB [±] | 4 DC min | 5 Std dev [±] |
|---|---|---|---|---|
| 0.010 | 1.953909013820420 | 0.713769554627578 | 97.1114542924311 | 1.070467187726930 |
| 0.025 | 1.371268137106850 | 0.846372477972281 | 101.5068153050040 | 0.364005494464026 |
| 0.035 | 1.098469932721130 | 0.236071655296202 | 91.6631225920068 | 0.378318648760539 |
| 0.045 | 1.651583510584190 | 0.373458491933335 | 108.3242413755950 | 0.889325587172662 |
| 0.055 | 1.550258967684180 | 0.370231971623559 | 97.4111444737698 | 0.995809218675947 |
| 0.065 | 1.370919306428060 | 0.214136300677560 | 95.4629469627496 | 0.412935830365930 |
| 0.075 | 0.663265052415144 | 0.172144448595737 | 85.2108010017677 | 0.360728429708555 |
| 0.085 | 1.750586158089710 | 0.357650814675731 | 99.5472278311608 | 0.478147466792411 |
| 0.095 | 1.077466433174000 | 0.211718420265047 | 94.3306567050435 | 0.975205106631420 |
| 0.105 | 1.238730241793310 | 0.310939518847366 | 99.7622075454043 | 0.540855803333939 |
| 0.115 | 1.576649002497000 | 0.352276540711861 | 97.7489823951878 | 1.073702007076450 |
| 0.125 | 1.022412810597670 | 0.235988001162642 | 90.7385905773835 | 0.999787977523235 |
| 0.135 | 1.629717036560290 | 0.460886708920945 | 91.9979167149918 | 0.405488594167580 |
| 0.145 | 0.951467175528816 | 0.164716168101179 | 97.3209990343653 | 0.892762566419538 |
| 0.155 | 1.067753686597120 | 0.324680705757572 | 87.8887089546459 | 0.286181760425084 |
| 0.165 | 2.366328958513330 | 0.457437160334086 | 109.6716491440910 | 2.204109797628060 |
| 0.175 | 3.318657723570140 | 0.666061630013291 | 81.4916876962961 | 2.186526926429220 |
| 0.185 | 3.905727566891000 | 0.483024518655151 | 109.2200024932170 | 2.660305433592170 |
| 0.195 | 3.906956109172080 | 0.833740333663186 | 113.2644288974500 | 2.507508723813340 |
| 0.205 | 4.126989496207410 | 0.576316791446481 | 97.9403197421470 | 2.679594185693050 |
| 0.215 | 4.216795738226010 | 0.561142572915344 | 118.6038531472020 | 2.325704194432300 |
| 0.225 | 3.843053096596030 | 0.691304710763503 | 116.7563717195520 | 2.139369065869650 |
| 0.235 | 3.557388062722960 | 0.476843059196133 | 94.7359109611305 | 2.036786684952550 |
