A modern pollen–temperature calibration data set from Korea and quantitative temperature reconstructions for the Holocene

The Holocene ◽  
2011 ◽  
Vol 21 (7) ◽  
pp. 1125-1135 ◽  
Author(s):  
Jungjae Park
Keyword(s):  
Transfer Function ◽  
Correspondence Analysis ◽  
East Coast ◽  
Ice Age ◽  
Weighted Averaging ◽  
Calibration Data ◽  
Data Set ◽  
The Holocene ◽  
Modern Pollen ◽  
The Relationship

Modern surface pollen samples from the mountains along the east coast of Korea were used to derive pollen–temperature transfer functions. Detrended correspondence analysis (DCA) and detrended canonical correspondence analysis (DCCA) were performed to test the robustness of the relationship between the modern pollen assemblages and temperatures. The relationship exhibited a high correlation (DCA, r = −0.887; DCCA, r = −0.908). The performance of the best weighted averaging partial least squares (WA-PLS) transfer function was statistically good ([Formula: see text] = 0.74; RMSEP = 1.79°C). In order to quantitatively reconstruct the Holocene temperature changes, the best model was applied to five fossil pollen records produced from four coastal lagoons of the east coast and one high-altitude peat bog. Anomalies calculated from reconstructed paleotemperature data were combined to generate a synthesis temperature reconstruction for the east coast of Korea, in which the ‘Medieval Warm Period’, ‘Little Ice Age’, and ‘Migration Period’ were clearly shown. This study demonstrated the validity of the quantitative reconstruction of paleotemperature using the pollen–climate transfer function, even in heavily human-impacted areas such as the Korean Peninsula.

scholarly journals Quantifying late-Holocene climate in the Ecuadorian Andes using a chironomid-based temperature inference model

2016 ◽  
Author(s):  
Frazer Matthews-Bird ◽  
Stephen J. Brooks ◽  
Philip B. Holden ◽  
Encarni Montoya ◽  
William D . Gosling
Keyword(s):  
Late Holocene ◽  
Bayesian Method ◽  
Ice Age ◽  
Weighted Averaging ◽  
Mean Annual Temperature ◽  
Calibration Data ◽  
Tropical Andes ◽  
Data Set ◽  
Cold Temperatures ◽  
Inference Models

Abstract. Presented here is the first chironomid calibration dataset for tropical South America. Surface sediments were collected from 59 lakes across Bolivia (15 lakes), Peru (32 lakes) and Ecuador (12 lakes) between 2004 and 2013 over an altitudinal gradient from 150 m above sea level (a.s.l) to 4655 m a.s.l, between 0-­17°S and 64-­78°W. The study sites cover a mean annual temperature (MAT) gradient of 25°C. In total, 55 chironomid taxa were identified in the 59 calibration data-­set lakes. When used as a single explanatory variable, MAT explains 12.9% of the variance (λ1/λ2= 1.431). Two inference models were developed using weighted averaging and Bayesian methods. The best performing model using conventional statistical methods was a WA (inverse) model (R2jack= 0.890, RMSEPjack= 2.404, Mean biasjack= -­0.017, Max biasjack= 4.665). The Bayesian method produced a model with R2jack= 0.909, RMSEPjack= 2.373, Mean biasjack= 0.598, Max biasjack= 3.158. Both models were used to infer past temperatures from a c. 3000 yr record from the tropical Andes of Ecuador, Laguna Pindo. Inferred temperatures fluctuated around modern day conditions but showed significant departures at certain intervals (c. 1600 cal yr BP; c. 3000-­2500 cal yr BP). Both methods (WA/Bayesian) showed similar patterns of temperature variability; however, the magnitude of fluctuations differed. In general the WA method was more variable often inferring unrealistically cold temperatures (c. -­7±2.5°C relative to the modern). The Bayesian method provided temperature anomaly estimates for cool periods that lay within the expected range of the Holocene (c. -­3±3.4°C). The chironomid-­based MAT recon struction from the Laguna Pindo fossil record suggests that periods of low solar output not only affect the tropics through changes in precipitation, but also directly affect tropical temperatures. Inferred temperatures were 2-­3°C colder relative to the modern during the widely recognised 3500-­2500 cal yr BP cooling event. Long-­term cooling during the late-­Holocene culminating in the Little Ice Age (LIA) is not apparent in the Laguna Pindo record. A cooling by 1-­2°C relative to the modern during the LIA is recorded in a single fossil sa

Developing a modern pollen-climate calibration data set for Norway

Boreas ◽  
2010 ◽  
Vol 39 (4) ◽  
pp. 674-688 ◽  
Author(s):  
ANNE E. BJUNE ◽  
H. JOHN B. BIRKS ◽  
SYLVIA M. PEGLAR ◽  
ARVID ODLAND
Keyword(s):  
Calibration Data ◽  
Data Set ◽  
Modern Pollen ◽  
Calibration Data Set

scholarly journals Inferring late-Holocene climate in the Ecuadorian Andes using a chironomid-based temperature inference model

2016 ◽  
Vol 12 (5) ◽  
pp. 1263-1280 ◽  
Author(s):  
Frazer Matthews-Bird ◽  
Stephen J. Brooks ◽  
Philip B. Holden ◽  
Encarni Montoya ◽  
William D. Gosling
Keyword(s):  
Bayesian Method ◽  
Mean Squared Error ◽  
Weighted Averaging ◽  
Mean Annual Temperature ◽  
Calibration Data ◽  
Tropical Andes ◽  
Data Set ◽  
Inference Models ◽  
Calibration Data Set ◽  
Study Sites

Abstract. Presented here is the first chironomid calibration data set for tropical South America. Surface sediments were collected from 59 lakes across Bolivia (15 lakes), Peru (32 lakes), and Ecuador (12 lakes) between 2004 and 2013 over an altitudinal gradient from 150 m above sea level (a.s.l) to 4655 m a.s.l, between 0–17° S and 64–78° W. The study sites cover a mean annual temperature (MAT) gradient of 25 °C. In total, 55 chironomid taxa were identified in the 59 calibration data set lakes. When used as a single explanatory variable, MAT explains 12.9 % of the variance (λ1/λ2 =  1.431). Two inference models were developed using weighted averaging (WA) and Bayesian methods. The best-performing model using conventional statistical methods was a WA (inverse) model (R2jack =  0.890; RMSEPjack =  2.404 °C, RMSEP – root mean squared error of prediction; mean biasjack =  −0.017 °C; max biasjack =  4.665 °C). The Bayesian method produced a model with R2jack =  0.909, RMSEPjack =  2.373 °C, mean biasjack =  0.598 °C, and max biasjack =  3.158 °C. Both models were used to infer past temperatures from a ca. 3000-year record from the tropical Andes of Ecuador, Laguna Pindo. Inferred temperatures fluctuated around modern-day conditions but showed significant departures at certain intervals (ca. 1600 cal yr BP; ca. 3000–2500 cal yr BP). Both methods (WA and Bayesian) showed similar patterns of temperature variability; however, the magnitude of fluctuations differed. In general the WA method was more variable and often underestimated Holocene temperatures (by ca. −7 ± 2.5 °C relative to the modern period). The Bayesian method provided temperature anomaly estimates for cool periods that lay within the expected range of the Holocene (ca. −3 ± 3.4 °C). The error associated with both reconstructions is consistent with a constant temperature of 20 °C for the past 3000 years. We would caution, however, against an over-interpretation at this stage. The reconstruction can only currently be deemed qualitative and requires more research before quantitative estimates can be generated with confidence. Increasing the number, and spread, of lakes in the calibration data set would enable the detection of smaller climate signals.

scholarly journals 14C Record and Wiggle-Match Placement for the Anatolian (Gordion Area) Juniper Tree-Ring Chronology ~1729 to 751 Cal BC, and Typical Aegean/Anatolian (Growing Season Related) Regional 14C Offset Assessment

Radiocarbon ◽  
2010 ◽  
Vol 52 (4) ◽  
pp. 1571-1597 ◽  
Author(s):  
Sturt W Manning ◽  
Bernd Kromer ◽  
Christopher Bronk Ramsey ◽  
Charlotte L Pearson ◽  
Sahra Talamo ◽  
...  
Keyword(s):  
Tree Ring ◽  
High Precision ◽  
Growing Season ◽  
Central Anatolia ◽  
Calibration Data ◽  
Tree Ring Chronology ◽  
Data Set ◽  
Multiple Measurements ◽  
Relationship Of ◽  
The Relationship

The East Mediterranean Radiocarbon (inter-)Comparison Project (EMRCP) has measured the 14C ages of a number of sets of tree rings from the Gordion Area dendrochronology from central Anatolia at the Heidelberg Radiocarbon Laboratory. In several cases, multiple measurements were made over a period from the 1980s to 2009. This paper presents the final data set from this work (128 high-precision measurements), and considers (i) the relationship of these data against the standard Northern Hemisphere 14C calibration data set (IntCal09), and (ii) the optimum calendar dating of this floating tree-ring record on the basis of the final set of high-precision 14C data. It finds good agreement between the Anatolian data and IntCal09 in some important intervals (e.g. ∼1729 to 1350 cal BC) and observes one period (9th–8th centuries BC) where there appears to be some indication of a regional/growing season signal, and another period (later 14th–13th centuries BC) where IntCal09 may not best reflect the real 14C record. The scale of the typical growing-season-related regional 14C offset (ΔR) between the Aegean/Anatolian region and IntCal09 is also assessed (for the mid-2nd millennium BC and mid-2nd millennium AD), and found to be usually minor (at times where there are no major additional forcing factors and/or issues with the IntCal09 data set): of the order of 2–4 ± 2–4 yr.

scholarly journals OPTiMAL: A new machine learning approach for GDGT-based palaeothermometry

2019 ◽  
Author(s):  
Yvette L. Eley ◽  
William Thompson ◽  
Sarah E. Greene ◽  
Ilya Mandel ◽  
Kirsty Edgar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Sea Surface ◽  
Calibration Data ◽  
Data Set ◽  
Calibration Dataset ◽  
Surface Temperatures ◽  
Calibration Data Set ◽  
Relative Abundances ◽  
The Relationship

Abstract. In the modern oceans, the relative abundances of Glycerol dialkyl glycerol tetraether (GDGTs) compounds produced by marine archaeal communities show a significant dependence on the local sea surface temperature at the site of formation. When preserved in ancient marine sediments, the measured abundances of these fossil lipid biomarkers thus have the potential to provide a geological record of long-term variability in planetary surface temperatures. Several empirical calibrations have been made between observed GDGT relative abundances in late Holocene core top sediments and modern upper ocean temperatures. These calibrations form the basis of the widely used TEX86 palaeothermometer. There are, however, two outstanding problems with this approach, first the appropriate assignment of uncertainty to estimates of ancient sea surface temperatures based on the relationship of the ancient GDGT assemblage to the modern calibration data set; and second, the problem of making temperature estimates beyond the range of the modern empirical calibrations (> 30 ºC). Here we apply modern machine-learning tools, including Gaussian Process Emulators and forward modelling, to develop a new mathematical approach we call OPTiMAL (Optimised Palaeothermometry from Tetraethers via MAchine Learning) to improve temperature estimation and the representation of uncertainty based on the relationship between ancient GDGT assemblage data and the structure of the modern calibration data set. We reduce the root mean square uncertainty on temperature predictions (validated using the modern data set) from ~ ±6 ºC using TEX86 based estimators to ±3.6 ºC using Gaussian Process estimators for temperatures below 30 ºC. We also provide a new but simple quantitative measure of the distance between an ancient GDGT assemblage and the nearest neighbour within the modern calibration dataset, as a test for significant non-analogue behaviour. Finally, we advocate against the use of temperature estimates beyond the range of the modern empirical calibration dataset, given the absence – to date – of a robust predictive biological model or extensive and reproducible mesocosm experimental data in this elevated temperature range.

Distribution of freshwater diatoms in 64 Labrador (Canada) lakes: species–environment relationships along latitudinal gradients and reconstruction models for water colour and alkalinity

2002 ◽  
Vol 59 (2) ◽  
pp. 329-349 ◽  
Author(s):  
Marie-Andrée Fallu ◽  
Nancie Allaire ◽  
Reinhard Pienitz
Keyword(s):  
Transfer Functions ◽  
Latitudinal Gradients ◽  
Weighted Averaging ◽  
Calibration Data ◽  
Paleoenvironmental Reconstruction ◽  
Vegetation Types ◽  
Forest Zone ◽  
Data Set ◽  
Water Colour ◽  
Lichen Woodland

The distribution of modern diatom assemblages in surficial sediments of 64 Labrador (Canada) lakes across broad vegetational biomes was studied in order to explore species–environment relationships and to develop transfer functions for paleoenvironmental reconstruction. The study sites were situated along a latitudinal gradient (51°27' to 57°37' N) and classified according to six catchment vegetation types: wetland (peatland) forest, spruce/fir forest, lichen woodland, forest–tundra, coastal tundra, and tundra. Canonical correspondence analysis revealed that among 28 environmental variables determined for each site, water colour and alkalinity accounted for most of the variance in the diatom data. Using weighted-averaging partial least squares techniques, we developed transfer functions for inference of water colour (CLR) (r2jack= 0.85, root mean square error of prediction (RMSEP) = 0.18log(CLR + 1) or 1.51 Pt units) and alkalinity (ALK) (r2jack= 0.63, RMSEP = 0.25log(ALK + 1) or 1.78 µeq·L–1) from the percent abundance of the 132 most abundant diatom taxa. By determining diatom distribution in relation to more detailed vegetation types within the boreal forest zone (wetland forest, spruce/fir forest, and lichen woodland), this calibration data set demonstrated the potential of these assemblages for revealing more subtle changes in lake catchment vegetation over time.

Holocene vegetation, climate and human impact in steppes around Lake Sevan (Armenia) based on a multiproxy approach: Pollen, NPPs and brGDGTs

2021 ◽  
Author(s):  
Mary Robles ◽  
Odile Peyron ◽  
Elisabetta Brugiapaglia ◽  
Guillemette Ménot ◽  
Lucas Dugerdil ◽  
...  
Keyword(s):  
Human Impact ◽  
Weighted Averaging ◽  
Lake Sevan ◽  
The Holocene ◽  
Modern Pollen ◽  
Climate Reconstructions ◽  
Multi Method Approach ◽  
The Impact ◽  
Multiproxy Approach ◽  
Method Approach

<p>In the Caucasus Mountains, the role of human influences and climate changes on steppes expansion over the Holocene is still discussed because this region is poorly documented. This study investigates (1) modern pollen-vegetation relationships in Armenia and (2) changes in vegetation, human activity and climate in the Holocene record of Vanevan peat (south-eastern shore of Lake Sevan) located in Armenia. The last 9700 years are recorded in the Vanevan core. We used a multiproxy approach including XRF, Pollen, Non-Pollen Palynomorphs (NPPs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs) to reconstruct changes in vegetation, human impact and climate. The combination of these proxies is innovative and aims to distinguish the impact of human activities and climate change on vegetation. Modern pollen assemblages from semi-desert/steppe regions of Armenia show an abundance of Chenopodiaceae while meadows steppes, subalpine and alpine meadows are dominated by Poaceae. The Holocene vegetation at Vanevan is characterized by steppes dominated by Poaceae, <em>Artemisia</em> and Chenopodiaceae. However, several arboreal taxa, such as <em>Quercus, Betula, Carpinus betulus</em> and <em>Ulmus</em>, are more developed on slopes between 8600 and 5100 cal BP. Regarding the human impact, the presence of agriculture is attested since 5200 cal BP, largely increases during the last 2000 years cal BP (high percentages of <em>Cerealia</em>-type pollen) and correlates with the occupation periods reported in archeological studies. Palaeoclimate changes at Vanevan are estimated from (1) water level changes (2) temperature reconstructions based on brGDGTs (3) climate reconstructions based on pollen (through a multi-method approach: Modern Analogue Technique, Weighted Averaging Partial Least Squares regression, Random Forest, and Boosted Regression Trees). Climate reconstructions based on pollen and brGDGTs are rare and the multi-method approach using pollen data is innovative in the region. The results of Vanevan give evidence of high temperatures from 7900 to 5100 cal BP and arid events at 6000, 5000-4500 and 4200 cal BP, in agreement with other regional records.</p>

scholarly journals Development of coccolithophore-based transfer functions in the western Mediterranean sea: a sea surface salinity reconstruction for the last 15.5 kyr

2015 ◽  
Vol 11 (12) ◽  
pp. 1635-1651 ◽  
Author(s):  
B. Ausín ◽  
I. Hernández-Almeida ◽  
J.-A. Flores ◽  
F.-J. Sierro ◽  
M. Grosjean ◽  
...  
Keyword(s):  
Transfer Function ◽  
Mediterranean Sea ◽  
Western Mediterranean ◽  
Partial Least Square ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Weighted Averaging ◽  
Surface Salinity ◽  
Data Set ◽  
Western Mediterranean Sea

Abstract. A new data set of 88 marine surface sediment samples and related oceanic environmental variables (temperature, salinity, chlorophyll a, oxygen, etc.) was studied to quantify the relationship between assemblages of coccolithophore species and modern environmental conditions in the western Mediterranean Sea and the Atlantic Ocean, west of the Strait of Gibraltar. Multivariate statistical analyses revealed that coccolithophore species were primarily related to sea surface salinity (SSS), explaining an independent and significant proportion of variance in the coccolithophore data. A quantitative coccolithophore-based transfer function to estimate SSS was developed using the modern analog technique (MAT) and weighted-averaging partial least square regression (WA-PLS). The bootstrapped regression coefficient (R2boot) was 0.85MAT and 0.80WA-PLS, with a root-mean-square error of prediction (RMSEP) of 0.29MAT and 0.30WA-PLS (psu). The resulting transfer function was applied to fossil coccolithophore assemblages in the highly resolved (~ 65 years) sediment core CEUTA10PC08 from the Alboran Sea (western Mediterranean) in order to reconstruct SSS for the last 25 kyr. The reliability of the reconstruction was evaluated by assessing the degree of similarity between fossil and modern coccolithophore assemblages and by a comparison of reconstructions with fossil ordination scores. Analogs were poor for the stadials associated with Heinrich events 2 and 1 and part of the Last Glacial Maximum. Good analogs indicate a more reliable reconstruction of the SSS for the last 15.5 kyr. During this period, several millennial and centennial SSS changes were observed and associated with sea-level oscillations and variations in the Atlantic Water entering the Alboran.

Comparing Interpoint Distances in Correspondence Analysis: A Clarification

1987 ◽  
Vol 24 (4) ◽  
pp. 445-450 ◽  
Author(s):  
J. Douglas Carroll ◽  
Paul E. Green ◽  
Catherine M. Schaffer
Keyword(s):  
Correspondence Analysis ◽  
Singular Values ◽  
Diagonal Matrix ◽  
Data Set ◽  
French School ◽  
The Relationship

In a recent JMR article, the authors described and illustrated a correspondence analysis scaling that permitted both within-set and between-set squared distance comparisons. This note clarifies the relationship between the proposed scaling and another scaling (popular among the “French school” of data analysts) in which the diagonal matrix of singular values is applied to both X and Y coordinates. Using a data set from Greenacre, the authors examine conceptual and empirical contrasts among three alternative scalings.

scholarly journals Pollen-based temperature and precipitation inferences for the montane forest of Mt. Kilimanjaro during the last Glacial and the Holocene

2014 ◽  
Vol 10 (1) ◽  
pp. 195-234 ◽  
Author(s):  
L. Schüler ◽  
A. Hemp ◽  
H. Behling
Keyword(s):  
East Africa ◽  
Transfer Functions ◽  
Montane Forest ◽  
Weighted Averaging ◽  
Pollen Record ◽  
Climate Variables ◽  
The Holocene ◽  
Modern Pollen ◽  
Temperature And Precipitation ◽  
Pollen Rain

Abstract. The relationship between modern pollen-rain taxa and measured climate variables was explored along the elevational gradient of the southern slope of Mt. Kilimanjaro, Tanzania. Pollen assemblages in 28 pollen traps positioned on 14 montane forest vegetation plots were identified and their relationship with climate variables was examined using multivariate statistical methods. Canonical correspondence analysis revealed that the mean annual temperature, mean annual precipitation and minimum temperature each account for significant fractions of the variation in pollen taxa. A training set of 107 modern pollen taxa was used to derive temperature and precipitation transfer functions based on pollen subsets using weighted-averaging-partial-least-squares (WA-PLS) techniques. The transfer functions were then applied to a fossil pollen record from the montane forest of Mt. Kilimanjaro and the climate parameter estimates for the Late Glacial and the Holocene on Mt. Kilimanjaro were inferred. Our results present the first quantitatively reconstructed temperature and precipitation estimates for Mt Kilimanjaro and give highly interesting insights into the past 45 000 yr of climate dynamics in tropical East Africa. The climate reconstructions are consistent with the interpretation of pollen data in terms of vegetation and climate history of afro-montane forest in East Africa. Minimum temperatures above the frostline as well as increased precipitation turn out to be crucial for the development and expansion of montane forest during the Holocene. In contrast, consistently low minimum temperatures as well as about 25% drier climate conditions prevailed during the pre LGM, which kept the montane vegetation composition in a stable state. In prospective studies, the quantitative climate reconstruction will be improved by additional modern pollen rain data, especially from lower elevations with submontane dry forests and colline savanna vegetation in order to extend the reference climate gradient.

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