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Central Asia is located at the confluence of large-scale atmospheric circulation systems. It is thus likely to be highly susceptible to changes in the dynamics of those systems; however, little is still known about the regional paleoclimate history. Here we present carbon and hydrogen isotopic compositions of n-alkanoic acids from a late Holocene sediment core from Lake Karakuli (eastern Pamir, Xinjiang Province, China). Instrumental evidence and isotopeenabled climate model experiments with the Laboratoire de Meteorologie Dynamique Zoom model version 4 (LMDZ4) demonstrate that delta D values of precipitation in the region are influenced by both temperature and precipitation amount. We find that these parameters are inversely correlated on an annual scale, i.e., the climate has varied between relatively cool and wet and more warm and dry over the last 50 years. Since the isotopic signals of these changes are in the same direction and therefore additive, isotopes in precipitation are sensitive recorders of climatic changes in the region. Additionally, we infer that plants use year-round precipitation (including snowmelt), and thus leaf wax delta D values must also respond to shifts in the proportion of moisture derived from westerly storms during late winter and early spring. Downcore results give evidence for a gradual shift to cooler and wetter climates between 3.5 and 2.5 cal kyr BP, interrupted by a warm and dry episode between 3.0 and 2.7 kyr BP. Further cool and wet episodes occur between 1.9 and 1.5 and between 0.6 and 0.1 kyr BP, the latter coeval with the Little Ice Age. Warm and dry episodes from 2.5 to 1.9 and 1.5 to 0.6 kyr BP coincide with the Roman Warm Period and Medieval Climate Anomaly, respectively. Finally, we find a drying tend in recent decades. Regional comparisons lead us to infer that the strength and position of the westerlies, and wider northern hemispheric climate dynamics, control climatic shifts in arid Central Asia, leading to complex local responses. Our new archive from Lake Karakuli provides a detailed record of the local signatures of these climate transitions in the eastern Pamir.
Organic geochemical proxy data from surface sediment samples and a sediment core from Lake Donggi Cona were used to infer environmental changes on the northeastern Tibetan Plateau spanning the last 18.4 kyr. Long-chain n-alkanes dominate the aliphatic hydrocarbon fraction of the sediment extract from most surface sediment samples and the sediment core. Unsaturated mid-chain n-alkanes (nC(23:1) and nC(25:1)) have high abundances in some samples, especially in core samples from the late glacial and early Holocene. TOC contents, organic biomarker and non-pollen-palynomorph concentrations and results from organic petrologic analysis on selected samples suggest three major episodes in the history of Lake Donggi Cona. Before ca. 12.6 cal ka BP samples contain low amounts of organic matter due to cold and arid conditions during the late glacial. After 12.6 cal ka BP, relatively high contents of TOC and concentrations of Botryococcus fossils, as well as enhanced concentrations of mid-chain n-alkanes and n-alkenes suggest a higher primary and macrophyte productivity than at present This is supported by high contents of palynomorphs derived from higher plants and algae and was possibly triggered by a decrease of salinity and amelioration of climate during the early Holocene. Since 6.8 cal ka BP Lake Donggi Cona has been an oligotrophic freshwater lake. Proxy data suggest that variations in insolation drive ecological changes in the lake, with increased aquatic productivity during the early Holocene summer insolation maximum. Short-term drops of TOC contents or biomarker concentrations (at 9.9 cal ka BP, after 8.0 and between 3.5 and 1.7 cal ka BP) can possibly be related to relatively cool and dry episodes reported from other sites on the north-eastern Tibetan Plateau, which are hypothesized to occur in phase with Northern Hemisphere cooling events.
Although the climate development over the Holocene in the Northern Hemisphere is well known, palaeolimnological climate reconstructions reveal spatiotemporal variability in northern Eurasia. Here we present a multi-proxy study from north-eastern Siberia combining sediment geochemistry, and diatom and pollen data from lake-sediment cores covering the last 38,000 cal. years. Our results show major changes in pyrite content and fragilarioid diatom species distributions, indicating prolonged seasonal lake-ice cover between similar to 13,500 and similar to 8900 cal. years BP and possibly during the 8200 cal. years BP cold event. A pollen-based climate reconstruction generated a mean July temperature of 17.8 degrees C during the Holocene Thermal Maximum (HTM) between similar to 8900 and similar to 4500 cal. years BP. Naviculoid diatoms appear in the late Holocene indicating a shortening of the seasonal ice cover that continues today. Our results reveal a strong correlation between the applied terrestrial and aquatic indicators and natural seasonal climate dynamics in the Holocene. Planktonic diatoms show a strong response to changes in the lake ecosystem due to recent climate warming in the Anthropocene. We assess other palaeolimnological studies to infer the spatiotemporal pattern of the HTM and affirm that the timing of its onset, a difference of up to 3000 years from north to south, can be well explained by climatic teleconnections. The westerlies brought cold air to this part of Siberia until the Laurentide ice sheet vanished 7000 years ago. The apparent delayed ending of the HTM in the central Siberian record can be ascribed to the exceedance of ecological thresholds trailing behind increases in winter temperatures and decreases in contrast in insolation between seasons during the mid to late Holocene as well as lacking differentiation between summer and winter trends in paleolimnological reconstructions. (C) 2015 Elsevier Ltd. All rights reserved.
Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
This study investigates the spatial and temporal distributions of 14 key arboreal taxa and their driving forces during the last 22,000 calendar years before ad 1950 (kyr BP) using a taxonomically harmonized and temporally standardized fossil pollen dataset with a 500-year resolution from the eastern part of continental Asia. Logistic regression was used to estimate pollen abundance thresholds for vegetation occurrence (presence or dominance), based on modern pollen data and present ranges of 14 taxa in China. Our investigation reveals marked changes in spatial and temporal distributions of the major arboreal taxa. The thermophilous (Castanea, Castanopsis, Cyclobalanopsis, Fagus, Pterocarya) and eurythermal (Juglans, Quercus, Tilia, Ulmus) broadleaved tree taxa were restricted to the current tropical or subtropical areas of China during the Last Glacial Maximum (LGM) and spread northward since c. 14.5kyr BP. Betula and conifer taxa (Abies, Picea, Pinus), in contrast, retained a wider distribution during the LGM and showed no distinct expansion direction during the Late Glacial. Since the late mid-Holocene, the abundance but not the spatial extent of most trees decreased. The changes in spatial and temporal distributions for the 14 taxa are a reflection of climate changes, in particular monsoonal moisture, and, in the late Holocene, human impact. The post-LGM expansion patterns in eastern continental China seem to be different from those reported for Europe and North America, for example, the westward spread for eurythermal broadleaved taxa.
A modern pollen dataset from China and Mongolia (18-52 degrees N, 74-132 degrees E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables - mean annual precipitation (P-ann): 35-2091 mm, mean annual temperature (T-ann): -12.1-25.8 degrees C, mean temperature in the coldest month (Mt(co).): -33.8-21.7 degrees C, and mean temperature in the warmest month (Mt(wa)): 03-29.8 degrees C. Modern pollen-climate relationships are assessed using canonical correspondence analysis (CCA), Huisman-Olff-Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that P-ann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r(2)) and root mean square error of prediction (RMSEP). Mt(co) and Mt(wa) may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power. (C) 2014 Elsevier B.V. All rights reserved.
A total of 271 pollen records were selected from a large collection of both raw and digitized pollen spectra from eastern continental Asia (70 degrees-135 degrees E and 18 degrees-55 degrees N). Following pollen percentage recalculations, taxonomic homogenization, and age-depth model revision, the pollen spectra were interpolated at a 500-year resolution and a taxonomically harmonized and temporally standardized fossil pollen dataset established with 226 pollen taxa, covering the last 22 cal lea. Of the 271 pollen records, 85% were published since 1990, with reliable chronologies and high temporal resolutions; of these, 50% have raw data with complete pollen assemblages, ensuring the quality of this dataset The pollen records available for each 500-year time slice are well distributed over all main vegetation types and climatic zones of the study area, making their pollen spectra suitable for paleovegetation and paleoclimate research. Such a dataset can be used as an example for the development of similar datasets for other regions of the world.
Ongoing and past biome transitions are generally assigned to climate and atmospheric changes (e.g. temperature, precipitation, CO2), but the major regional factors or factor combinations that drive vegetation change often remain unknown. Modelling studies applying ensemble runs can help to partition the effects of the different drivers. Such studies require careful validation with observational data. In this study, fossil pollen records from 741 sites in Europe, 728 sites in North America, and 418 sites in Asia (extracted from terrestrial archives including lake sediments) are used to reconstruct biomes at selected time slices between 40 cal ka BP (calibrated thousand years before present) and today. These results are used to validate Northern Hemisphere biome distributions (>30 degrees N) simulated by the biome model BIOME4 that has been forced with climate data simulated by a General Circulation model. Quantitative comparisons between pollen- and model-based results show a generally good fit at a broad spatial scale. Mismatches occur in central-arid Asia with a broader extent of grassland throughout the last 40 ka (likely due to the over-representation of Artemisia and Chenopodiaceae pollen) and in Europe with over-estimation of tundra at 0 cal ka BP (likely due to human impacts to some extent). Sensitivity analysis reveals that broad-scale biome changes follow the global signal of major postglacial temperature change, although the climatic variables vary in their regional and temporal importance. Temperature is the dominant variable in Europe and other rather maritime areas for biome changes between 21 and 14 ka, while precipitation is highly important in the arid inland regions of Asia and North America. The ecophysiological effect of changes in the atmospheric CO2-concentration has the highest impact during this transition than in other intervals. With respect to modern vegetation in the course of global warming, our findings imply that vegetation change in the Northern Hemisphere may be strongly limited by effective moisture changes, i.e. the combined effect of temperature and precipitation, particularly in inland areas. (C) 2019 Elsevier Ltd. All rights reserved.
Pollen-based quantitative land-cover reconstruction for northern Asia covering the last 40 ka cal BP
(2019)
We collected the available relative pollen productivity estimates (PPEs) for 27 major pollen taxa from Eurasia and applied them to estimate plant abundances during the last 40 ka cal BP (calibrated thousand years before present) using pollen counts from 203 fossil pollen records in northern Asia (north of 40 degrees N). These pollen records were organized into 42 site groups and regional mean plant abundances calculated using the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. Time-series clustering, constrained hierarchical clustering, and detrended canonical correspondence analysis were performed to investigate the regional pattern, time, and strength of vegetation changes, respectively. Reconstructed regional plant functional type (PFT) components for each site group are generally consistent with modern vegetation in that vegetation changes within the regions are characterized by minor changes in the abundance of PFTs rather than by an increase in new PFTs, particularly during the Holocene. We argue that pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, particularly when a high pollen producer invades areas dominated by low pollen producers. Comparisons with vegetation-independent climate records show that climate change is the primary factor driving land-cover changes at broad spatial and temporal scales. Vegetation changes in certain regions or periods, however, could not be explained by direct climate change, e.g. inland Siberia, where a sharp increase in evergreen conifer tree abundance occurred at ca. 7-8 ka cal BP despite an unchanging climate, potentially reflecting their response to complex climate-permafrost-fire-vegetation interactions and thus a possible long-term lagged climate response.