scholarly journals Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

2021 ◽  
Vol 17 (5) ◽  
pp. 2055-2071
Author(s):  
Paul D. Zander ◽  
Maurycy Żarczyński ◽  
Wojciech Tylmann ◽  
Shauna-kay Rainford ◽  
Martin Grosjean
Keyword(s):  
High Resolution ◽  
Meteorological Conditions ◽  
Additive Models ◽  
Formation Processes ◽  
Seasonal Climate ◽  
Climate Proxy ◽  
Climate Signals ◽  
Paleoclimate Reconstructions ◽  
Annual Resolution ◽  
Very High

Abstract. Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare, mainly because the climate–proxy relationships are complex and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (µXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore seasonal climate signals preserved in biochemical varves and, thus, assess the potential for annual-resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and µXRF-inferred elements at very high spatial resolution (60 µm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland, over the period 1966–2019 CE. We compare these data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperatures were predicted using Ti and total C (Radj2=0.55; cross-validated root mean square error (CV-RMSE) = 0.7 ∘C, 14.4 %). Windy days from March to December (mean daily wind speed > 7 m s−1) were predicted using mass accumulation rate (MAR) and Si (Radj2=0.48; CV-RMSE = 19.0 %). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate–proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual-resolution seasonal weather inference from varve biogeochemical data.

scholarly journals Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

2021 ◽  
Author(s):  
Paul D. Zander ◽  
Maurycy Żarczyński ◽  
Wojciech Tylmann ◽  
Shauna-kay Rainford ◽  
Martin Grosjean
Keyword(s):  
High Resolution ◽  
Meteorological Conditions ◽  
Additive Models ◽  
Formation Processes ◽  
Seasonal Climate ◽  
Climate Proxy ◽  
Climate Signals ◽  
Paleoclimate Reconstructions ◽  
Annual Resolution ◽  
Very High

Abstract. Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare mainly because the climate-proxy relationships are complex, and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (μXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore (seasonal) climate signals preserved in biochemical varves and, thus, assess the potential for annual resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and uXRF-inferred elements at very high spatial resolution (60 μm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland over the period 1966–2019 CE. We compare this data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperature were predicted using Ti and total C (R2adj = 0.55; cross-validated root mean square error (CV-RMSE) = 0.7 °C, 14.4%). Windy days from March to December (mean daily wind speed > 7 m/s) were predicted using mass accumulation rate (MAR) and Si (R2adj = 0.48; CV-RMSE = 19.0%). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate-proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual resolution seasonal weather inference from varve biogeochemical data.

Searching for weather in varves: use of ultra-high-resolution scanning techniques to reconstruct seasonal meteorological conditions

2021 ◽  
Author(s):  
Paul Zander ◽  
Maurycy Żarczyński ◽  
Wojciech Tylmann ◽  
Shauna-kay Rainford ◽  
Martin Grosjean
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Lake Sediments ◽  
Predictive Power ◽  
Accumulation Rate ◽  
Meteorological Data ◽  
Meteorological Conditions ◽  
Additive Models ◽  
Geochemical Data ◽  
Formation Processes

<p>Varved lake sediments are recognized as valuable archives of paleoclimatic information due to their precise chronological control. However, paleoclimate reconstructions based on the composition of biochemical varves are relatively rare (Zolitschka et al., 2015). We applied novel high-resolution scanning techniques to the varved sediments of Lake Żabińskie, Poland to obtain spatially resolved geochemical data at a resolution of 60 μm covering the period 1966-2019. Relative abundances of elements were measured in resin-embedded sediment slabs using a Bruker M4 Tornado micro-XRF scanner. Chloropigments-<em>a</em> and bacteriopheopigments-<em>a</em> were measured on a wet sediment core using a Specim Hyperspectral core scanner (Butz et al., 2015). The high resolution of the scanning data, and the relatively thick well-preserved varves (average thickness = 6.4 mm), enables a close examination of seasonal scale sediment composition and varve formation processes. Time series of geochemical variables within each varve year were classified into 4 varve type groups based on the dissimilarity measure ψ for multivariate time series (Benito and Birks, 2020; Gordon and Birks, 1974). Based on a Multivariate Analysis Of Variance test, these groups of years experienced significant (p<0.05) differences in seasonal meteorological conditions, particularly wind speed and temperature.  Additionally, a correlation analysis on mean annual geochemical values from the aforementioned scanning techniques and conventional CNS analysis, and seasonal meteorological data revealed significant (p<0.05) correlations with windiness and temperature. Based on these relationships, we applied generalized additive models to predict spring and summer (MAMJJA) temperature and number of windy days (spring through fall), yielding models with significant predictive power. Based on model selection, the variables with the most predictive power for spring and summer temperature were Ti (negative correlation) and total C. The variables with the most predictive power for windiness were Si, sediment accumulation rate, and varve type. This study highlights the usefulness of high-resolution scanning techniques to improve our understanding of varve formation processes and relationships between varve composition and climate variables in biochemical varves.</p><p> </p><p><strong>References</strong></p><p>Benito, B. M. and Birks, H. J. B.: distantia: an open‐source toolset to quantify dissimilarity between multivariate ecological time‐series, Ecography (Cop.)., 43(5), 660–667, doi:10.1111/ecog.04895, 2020.</p><p>Butz, C., Grosjean, M., Fischer, D., Wunderle, S., Tylmann, W. and Rein, B.: Hyperspectral imaging spectroscopy: a promising method for the biogeochemical analysis of lake sediments, J. Appl. Remote Sens., 9(1), 096031, doi:10.1117/1.jrs.9.096031, 2015.</p><p>Gordon, A. D. and Birks, H. J. B.: Numerical methods in Quaternary palaeoecology: II. Comparison of pollen diagrams, New Phytol., 73(1), 221–249, doi:10.1111/j.1469-8137.1974.tb04621.x, 1974.</p><p>Zolitschka, B., Francus, P., Ojala, A. E. K. and Schimmelmann, A.: Varves in lake sediments - a review, Quat. Sci. Rev., 117, 1–41, doi:10.1016/j.quascirev.2015.03.019, 2015.</p>

scholarly journals Tracking climate signals in varved lake sediments: research strategy and key sites for comprehensive process studies in the Masurian Lakeland

2017 ◽  
Vol 17 (3) ◽  
pp. 159-166 ◽  
Author(s):  
Wojciech Tylmann ◽  
Paulina Głowacka ◽  
Agnieszka Szczerba
Keyword(s):  
High Resolution ◽  
Lake Sediments ◽  
Sediment Cores ◽  
Monitoring Program ◽  
Sediment Traps ◽  
Research Strategy ◽  
Meteorological Conditions ◽  
Lake Basin ◽  
Climate Signals ◽  
Process Studies

AbstractLake sediments are excellent archives of environmental and climate change. Especially important are varved sediments which can provide high-resolution (annual) records of those changes. Process studies including limnological measurements, particle flux monitoring and analyses of sediment structures give an opportunity to explain relationships between meteorological conditions, in-lake processes and varve formation. In our study, three lakes were selected in the Masurian Lakeland: Lake Żabińskie, Łazduny and Rzęśniki. These relatively small and deep lakes contain well preserved biogenic varves. The lakes are influenced by the same meteorological conditions but differ in terms of their catchment size, land use, hydrology, lake basin morphology and trophic status. To explore the relationships between different parameters and preservation/transformation of climate signals in the sediments we started systematic limnological measurements in the water column of these lakes, water sampling for hydrochemical analyses, monitoring of modern sedimentation using sediment traps and analysis of topmost varves from short sediment cores. With this comprehensive and high-resolution monitoring program scheduled for at least four years we are going to verify the potential of varves to track short-term meteorological phenomena in lake sediments.

Seasonal climate signals (1990–2008) in a modern Soreq Cave stalagmite as revealed by high-resolution geochemical analysis

2014 ◽  
Vol 363 ◽  
pp. 322-333 ◽  
Author(s):  
Ian J. Orland ◽  
Yuval Burstyn ◽  
Miryam Bar-Matthews ◽  
Reinhard Kozdon ◽  
Avner Ayalon ◽  
...  
Keyword(s):  
High Resolution ◽  
Geochemical Analysis ◽  
Seasonal Climate ◽  
Climate Signals

Very High Resolution Analysis of the Dynamics of a Coronal Plasmoid

1994 ◽  
Vol 144 ◽  
pp. 593-596
Author(s):  
O. Bouchard ◽  
S. Koutchmy ◽  
L. November ◽  
J.-C. Vial ◽  
J. B. Zirker
Keyword(s):  
High Resolution ◽  
Solar Eclipse ◽  
Total Solar Eclipse ◽  
Field Of View ◽  
Small Field ◽  
High Resolution Analysis ◽  
Ccd Observations ◽  
Resolution Analysis ◽  
Very High ◽  
Small Field Of View

AbstractWe present the results of the analysis of a movie taken over a small field of view in the intermediate corona at a spatial resolution of 0.5“, a temporal resolution of 1 s and a spectral passband of 7 nm. These CCD observations were made at the prime focus of the 3.6 m aperture CFHT telescope during the 1991 total solar eclipse.

Three-dimensional fault geometry and kinematics of the 2008 M 7.1 Yutian earthquake revealed by very-high resolution satellite stereo imagery

2019 ◽  
Vol 232 ◽  
pp. 111300
Author(s):  
Xiaogang Song ◽  
Nana Han ◽  
Xinjian Shan ◽  
Chisheng Wang ◽  
Yingfeng Zhang ◽  
...  
Keyword(s):  
High Resolution ◽  
Three Dimensional ◽  
Fault Geometry ◽  
Stereo Imagery ◽  
Very High ◽  
Geometry And Kinematics

scholarly journals Object Oriented Classification for Mapping Mixed and Pure Forest Stands Using Very-High Resolution Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2508
Author(s):  
Loredana Oreti ◽  
Diego Giuliarelli ◽  
Antonio Tomao ◽  
Anna Barbati
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
Parametric Method ◽  
Mixed Forest ◽  
Mixed Stands ◽  
Mapping Unit ◽  
Mixed Forests ◽  
High Resolution Imagery ◽  
Very High Resolution Imagery ◽  
Very High

The importance of mixed forests is increasingly recognized on a scientific level, due to their greater productivity and efficiency in resource use, compared to pure stands. However, a reliable quantification of the actual spatial extent of mixed stands on a fine spatial scale is still lacking. Indeed, classification and mapping of mixed populations, especially with semi-automatic procedures, has been a challenging issue up to date. The main objective of this study is to evaluate the potential of Object-Based Image Analysis (OBIA) and Very-High-Resolution imagery (VHR) to detect and map mixed forests of broadleaves and coniferous trees with a Minimum Mapping Unit (MMU) of 500 m2. This study evaluates segmentation-based classification paired with non-parametric method K- nearest-neighbors (K-NN), trained with a dataset independent from the validation one. The forest area mapped as mixed forest canopies in the study area amounts to 11%, with an overall accuracy being equal to 85% and K of 0.78. Better levels of user and producer accuracies (85–93%) are reached in conifer and broadleaved dominated stands. The study findings demonstrate that the very high resolution images (0.20 m of spatial resolutions) can be reliably used to detect the fine-grained pattern of rare mixed forests, thus supporting the monitoring and management of forest resources also on fine spatial scales.

Sign in / Sign up

Export Citation Format

Share Document