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Recent global warming is pronounced in high-latitude regions (e.g. northern Asia), and will cause the vegetation to change. Future vegetation trends (e.g. the "arctic greening") will feed back into atmospheric circulation and the global climate system. Understanding the nature and causes of past vegetation changes is important for predicting the composition and distribution of future vegetation communities. Fossil pollen records from 468 sites in northern and eastern Asia were biomised at selected times between 40 cal ka bp and today. Biomes were also simulated using a climate-driven biome model and results from the two approaches compared in order to help understand the mechanisms behind the observed vegetation changes. The consistent biome results inferred by both approaches reveal that long-term and broad-scale vegetation patterns reflect global- to hemispheric-scale climate changes. Forest biomes increase around the beginning of the late deglaciation, become more widespread during the early and middle Holocene, and decrease in the late Holocene in fringe areas of the Asian Summer Monsoon. At the southern and southwestern margins of the taiga, forest increases in the early Holocene and shows notable species succession, which may have been caused by winter warming at ca. 7 cal ka bp. At the northeastern taiga margin (central Yakutia and northeastern Siberia), shrub expansion during the last deglaciation appears to prevent the permafrost from thawing and hinders the northward expansion of evergreen needle-leaved species until ca. 7 cal ka bp. The vegetation-climate disequilibrium during the early Holocene in the taiga-tundra transition zone suggests that projected climate warming will not cause a northward expansion of evergreen needle-leaved species.
A comprehensive understanding of the regional vegetation responses to long-term climate change will help to forecast Earth system dynamics. Based on a new well-dated pollen data set from Kanas Lake and a review on the published pollen records in and around the Altai Mountains, the regional vegetation dynamics and forcing mechanisms are discussed. In the Altai Mountains, the forest optimum occurred during 10-7ka for the upper forest zone and the tree line decline and/or ecological shifts were caused by climatic cooling from around 7ka. In the lower forest zone, the forest reached an optimum in the middle Holocene, and then increased openness of the forest, possibly caused by both climate cooling and human activities, took place in the late Holocene. In the lower basins or plains around the Altai Mountains, the development of protograssland or forest benefited from increasing humidity in the middle to late Holocene. Plain Language Summary In the Altai Mountains and surrounding area of central Asia, the previous studies of the Holocene paleovegetation and paleoclimate studies did not discuss the different ecological limiting factors for the vegetation in high mountains and low-elevation areas due to limited data. With accumulating fossil pollen data and surface pollen data, it is possible to understand better the geomorphological effect on the vegetation and discrepancies of vegetation/forest responses to large-scale climate forcing, and it is also possible to get reliable quantitative reconstructions of climate. Here our new pollen data and review on the published fossil pollen data will help us to look into the past climate change and vertical evolution of vegetation in this important area of the Northern Hemisphere. Based on our study, it can be concluded that the growth of taiga forest in the wetter areas may be promoted under a future warmer climate, while the forest in the relatively dry areas is liable to decline, and the different vegetation dynamics will contribute to future high-resolution coupled vegetation-climate model for Earth system modelling.
The climate conditions during Marine Isotope Stage (MIS) 3 were similar to present-day conditions, but whether humidity then exceeded present levels is debated, and the driving mechanisms of palaeoclimate evolution since MIS 3 remain unclear. Here, we use pollen data from Wulagai Lake, Inner Mongolia, to reconstruct vegetation and climate changes since the middle MIS 3. The steppe biome is reconstructed as the first dominant biome and the desert biome as the second, and the results show that the vegetation was steppe over the last 43,800 years. Poaceae, Artemisia, Caryophyllaceae and Humulus were abundant from middle to late MIS 3, indicating humid climate conditions. As drought-tolerant species such as Hippophae, Nitraria and Chenopodiaceae spread during MIS 2, the climate became arid. The Holocene is characterized by the dominance of steppe with mixed coniferous-broadleaved forests in the Greater Hinggan Range, and the desert biome retains high affinity scores, indicating that the climate was semi-arid. The climate from middle to late MIS 3 was wetter than in the Holocene; this shift was related to changes in the Northern Hemisphere's solar insolation and ice volume. The humid conditions during MIS 3 were attributed to strong ice–albedo feedback, which led to evaporation that was less than the precipitation. The enhanced evaporation caused by increased solar insolation and decreased ice volume might have exceeded the precipitation during the Holocene and resulted in low effective humidity in the Wulagai Lake basin.
The goal of China's sloping land conversion programme (SLCP) is to combat soil erosion and to reduce rural poverty. An ex-ante assessment of possible SLCP impacts was conducted with a focus on rural sustainability, taking the drought-prone region of Guyuan in Western China as an example. The Framework for Participatory Impact Assessment (FoPIA) was used to conduct two complementary impact assessments, one assessing SLCP impacts at regional level and a second one assessing alternative forest management options, to explore possible trade-offs among the economic, social and environmental dimensions of sustainability. Regional stakeholders assessed the SLCP to be capable of reducing soil erosion but felt it negatively affected rural employment, and a further continuation of the Programme was advocated. Assessment of three forest management scenarios by scientists showed that an orientation towards energy forests is potentially beneficial to all three sustainability dimensions. Ecological forests had disproportionate positive impacts on environmental functions and adverse impact on the other two sustainability dimensions. Economic forests were assessed to serve primarily the economic and social sustainability dimensions, while environmental impacts were still tolerable. The FoPIA results were evaluated against the available literature on the SLCP. Overall, the assessment results appeared to be reasonable, but the results of the regional stakeholders appeared to be too optimistic compared with the more critical assessment of the scientists. The SLCP seems to have the potential to tackle soil erosion but requires integrated forest management to minimize the risk of water stress while contributing to economic and social benefits in Guyuan. Copyright (C) 2012 John Wiley & Sons, Ltd.
The Relative Pollen Productivities (RPPs) of common steppe species are estimated using Extended R-value (ERV) model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of northern China. Artemisia, Chenopodiaceae, Poaceae, Cyperaceae, and Asteraceae are the dominant pollen types in pollen assemblages, reflecting the typical steppe communities well. The five dominant pollen types and six common types (Thalictrum, Iridaceae, Potentilla, Ephedra, Brassicaceae, and Ulmus) have strong wind transport abilities; the estimated Relevant Source Area of Pollen (RSAP) is ca. 1000 m when the sediment basin radius is set at 0.5 m. Ulmus, Artemisia, Brassicaceae, Chenopodiaceae, and Thalictrum have relative high RPPs; Poaceae, Cyperaceae, Potentilla, and Ephedra pollen have moderate RPPs; Asteraceae and Iridaceae have low RPPs. The reliability test of RPPs revealed that most of the RPPs are reliable in past vegetation reconstruction. However, the RPPs of Asteraceae and Iridaceae are obviously underestimated, and those of Poaceae, Chenopodiaceae, and Ephedra are either slightly underestimated or slightly overestimated, suggesting that those RPPs should be considered with caution. These RPPs were applied to estimating plant abundances for two fossil pollen spectra (from the Lake Bayanchagan and Lake Haoluku) covering the Holocene in typical steppe area, using the "Regional Estimates of Vegetation Abundance from Large Sites" (REVEALS) model. The RPPs-based vegetation reconstruction revealed that meadow-steppe dominated by Poaceae, Cyperaceae, and Artemisia plants flourished in this area before 6500-5600 cal yr BP, and then was replaced by present typical steppe.
Pollen influx (number of pollen grains cm−2 year−1) can objectively reflect the dispersal and deposition features of pollen within a certain time and space, and is often used as a basis for the quantitative reconstruction of palaeovegetation; however, little is known about the features and mechanisms of vertical dispersal of pollen. Here we present the results from a 5 year (2006–2010) monitoring program using pollen traps placed at different heights from ground level up to 60 m and surface soil samples in a mixed coniferous and deciduous broad-leaved woodland in the Changbai mountains, northeastern China. The pollen percentages and pollen influx from the traps have very similar characteristics to the highest values for Betula, Fraxinus, Quercus and Pinus, among the tree taxa and Artemisia, Chenopodiaceae and Asteraceae among the herb taxa. Pollen influx values vary significantly with height and show major differences between three distinct layers, above-canopy (≥32 m), within the trunk layer (8 ≤ 32 m) and on the ground (0 m). These differences in pollen influx are explained by differences in (i) the air flows in each of these layers and (ii) the fall speed of pollen of the various taxa. We found that the pollen recorded on the ground surface is a good representation of the major part of the pollen transported in the trunk space of the woodland. Comparison of the pollen influx values with the theoretical, calculated “characteristic pollen source area” (CPSA) of 12 selected taxa indicates that the pollen deposited on the ground surface of the woodland is a fair representation with 85–90 % of the total pollen deposited at a wind speed of 2.4 m s−1 coming from within ca. 1–5 km for Pinus and Quercus, ca. 5–10 km for Ulmus, Tilia, Oleaceae and Betula, ca. 20–40 km for Fraxinus, Poaceae, Chenopodiaceae, Populus and Salix, and ca. 30–60 km for Artemisia; it is also a good representation with 90–98 % of the total pollen deposited coming from within 60 km at a wind speed of 2.4 m s−1, or 100 km at a wind speed: 6 m s−1, for the 12 selected taxa used in the CPSA calculation. Furthermore, comparison with the vegetation map of the area around the sampling site shows that the pollen deposited on the ground represents all plant communities which grow in the study area within 70 km radius of the sampling site. In this study, the pollen percentages obtained from the soil surface samples are significantly biased towards pollen taxa with good preservation due to thick and robust pollen walls. Therefore, if mosses are available instead, soil samples should be avoided for pollen studies, in particular for the study of pollen-vegetation relationships, the estimation of pollen productivities and quantitative reconstruction of past vegetation. The results also indicate that the existing model of pollen dispersal and deposition, Prentice’s model, provides a fair description of the actual pollen dispersal and deposition in this kind of woodland, which suggests that the application of the landscape reconstruction algorithm would be relevant for reconstruction of this type of woodland in the past.
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.
As the recent permafrost thawing of northern Asia proceeds due to anthropogenic climate change, precise and detailed palaeoecological records from past warm periods are essential to anticipate the extent of future permafrost variations. Here, based on the modern relationship between permafrost and vegetation (represented by pollen assemblages), we trained a Random Forest model using pollen and permafrost data and verified its reliability to reconstruct the history of permafrost in northern Asia during the Holocene. An early Holocene (12-8 cal ka BP) strong thawing trend, a middle-to-late Holocene (8-2 cal ka BP) relatively slow thawing trend, and a late Holocene freezing trend of permafrost in northern Asia are consistent with climatic proxies such as summer solar radiation and Northern Hemisphere temperature. The extensive distribution of permafrost in northern Asia inhibited the spread of evergreen coniferous trees during the early Holocene warming and might have decelerated the enhancement of the East Asian summer monsoon (EASM) by altering hydrological processes and albedo. Based on these findings, we suggest that studies of the EASM should consider more the state of permafrost and vegetation in northern Asia, which are often overlooked and may have a profound impact on climate change in this region.
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.