Palynological and AVHRR observations of modern vegetational gradients in eastern
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Both fossil pollen records and satellite-based instruments are remote sensors of Earth' s vegetation with complementary properties. Satellites supply spatially continuous and highly resolved images for the past several decades, whereas pollen records include local and regional signals of vegetation composition, spanning millennia. Together, pollen and satellite-based observations measure vegetation change across a broad range of temporal scales. Here, we compare pollen percentages of needleleaved and broadleaved plant taxa to AVHRR estimates of percent tree cover, for two regions in eastern North America with well-dee ned physiognomic gradients. The linear e t between the pollen percentages and percent tree cover is strongest for search window half-widths of 25- 75 km and unweighted or inverse-distance weightings, consistent with previous taxon-based studies of regional pollen source area and transport. Variance not explained by the linear model arises primarily from differential properties of the AVHRR and pollen sensors, particularly site-specie c variability in the pollen data and intertaxonomic differences in pollen representation. These sources of variance can be minimized by regionally smoothing the pollen data and multivariate analogue approaches. A strong e t between observed tree-cover percentages and best-analogue estimates (r 2 = 0.70 to 0.78) suggests that analogue-based methods can be applied to infer past tree-cover proportions from fossil pollen records. Linking pollen and AVHRR observations in this manner effectively extrapolates satellite-derived variables beyond the few decades of direct observation, enabling study of longer-term variations in land cover and impacts upon climate and the terrestrial carbon cycle.Keywords:
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Records from terrestrial ecosystems play a key role in the understanding of the history and the mechanisms of the past global changes.Pollen analysis is one of the best proxies for past changes in the environment.However,due to the complicated relationship between pollen dispersal process and their final accumulation in the sediment,the relationship between fossil pollen assemblages,vegetation reconstructions and climate is not linear.This is why research on surface pollen assemblages and their relationships with modern vegetation and climate provide a foundation for reconstructing paleoenvironments based on fossil pollen.In order to investigate the relationship between the surface pollen and modern vegetation,the authors analyzed a total of 54 surface pollen samples from Dalianhai Lake catchment,a typical small basin in the transition area from arid to semi-arid region,northwest China.The pollen spectra from this region serve as the direct source contributed by wind,and the corresponding relationship between the pollen assemblages of surface samples and main vegetation types is better.Hierarchical Cluster Analysis(HCA) and the RDA ordination analysis of the main herbs and shrubs pollen assemblages stored in surface samples indicate a good correspondance relationship between pollen in the sediment and main vegetation from the region.Temperature and moisture are the main factors identified to influence plant distribution.Pollen response surfaces are non-linear function describing the way in which the abundances of taxa depend on the joint effects of two or more environmental variables,which has been broadly used for studying all kinds of palaeoclimatic projects such as COHMAP.In this paper the authors also used this non-linear method to generate pollen climate-response surface models from 54 surface-pollen samples from Dalianhai Lake catchment and associated climatic parameters at sites;Four different kinds of herbs were selected by the Principle Components Analysis(PCA) with high Eigenvalue and clear indicative significance,which abundance and mean July temperature and annual precipitation were used to obtain second or third degree multiple regressions by various non-linear variable transformations to allow flexibility shapes.The abundance of each species is represented by the height(Z) of surface coordinates(X,Y) corresponding to the values of precipitation(Y) and mean July temperature(X).The results indicate that the response surface pollen typically has at least one peak,and each fitted surface is unique for estimating past climate.In this study,Artemisia- Chenopodiaceae assemblage reflects the relative wetness,while Chenopodiaceae-Artemisia reflects relatively dry conditions,Increases Cyperaceae indicates cold-wet weather,and in Poaceae reflects either cold-wet and/or warm-wet conditions,which is consistent with other research work from North China.This is the first trial to use the pollen climate response surface model to quantitative reconstruct palaeoclimate in the northeastern Tibetan Plateau.Because of the insufficient pollen data of the surface earth samples,this research work is only considered as an attempt for a quantitative reconstruction of the palaeoclimate and palaeoenvironmen.
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The Landscape Reconstruction Algorithm (LRA) with the two models REVEALS and LOVE is developed to transform pollen percentage data to vegetation cover. This paper presents the first study to evaluate LRA in a region with large topographic variations within a short distances. The REVEALS model estimates regional vegetation abundance based on pollen assemblages from large lakes (100–500 ha). Pollen surface samples from one large and 28 small lakes are used together with a combination of regionally derived pollen productivity estimates and available estimates from other regions of Europe. The results show a good relationship between REVEALS-estimated forest cover and vegetation abundance based on the CORINE land-cover data. The REVEALS results using various sets of pollen assemblages from small lakes were comparable to those using one large lake. Local vegetation abundance using the LOVE model was estimated around 26 lakes. For common taxa, such as Pinus and Poaceae, the LOVE-based estimates of plant abundance match well with the distance-weighted plant abundances based on vegetation maps. Our results indicate that the LRA approach is effective for reconstruction of long-term vegetation changes in western Norway and other regions with high topographic relief when no major gradients exist in the pollen data.
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Aim The boreal tree line is a prominent biogeographic feature, the position of which reflects climatic conditions. Pollen is the key sensor used to reconstruct past tree line patterns. Our aims in this study were to investigate pollen–vegetation relationships at the boreal tree line and to assess the success of a modified version of the biomization method that incorporates pollen productivity and dispersal in distinguishing the tree line. Location Northern Canada (307 sites) and Alaska (316 sites). Methods The REVEALS method for estimating regional vegetation composition from pollen data was simplified to provide correction factors to account for differential production and dispersal of pollen among taxa. The REVEALS-based correction factors were used to adapt the biomization method and applied as a set of experiments to pollen data from lake sediments and moss polsters from the boreal tree line. Proportions of forest and tundra predicted from modern pollen samples along two longitudinal transects were compared with those derived from a vegetation map by: (1) a tally of 'correct' versus 'incorrect' assignments using vegetation in the relevant map pixels, and (2) a comparison of the shape and position of north–south forest-cover curves generated from all transect pixels and from pollen data. Possible causes of bias in the misclassifications were assessed. Results Correcting for pollen productivity alone gave fewest misclassifications and the closest estimate of the modern mapped tree line position (Canada, + 300 km; Alaska, + 10 km). In Canada success rates were c. 40–70% and all experiments over-predicted forest cover. Most corrections improved results over uncorrected biomization; using only lakes improved success rates to c. 80%. In Alaska success rates were 70–80% and classification errors were more evenly distributed; there was little improvement over uncorrected biomization. Main conclusions Corrected biomization should improve broad-scale reconstructions of spatial patterns in forest/non-forest vegetation mosaics and across climate-sensitive ecotones. The Canadian example shows this is particularly the case in regions affected by taxa with extremely high pollen productivity (such as Pinus). Improved representation of actual vegetation distribution is most likely if pollen data from lake sediments are used because the REVEALS algorithm is based on the pollen dynamics of lake-based systems.
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Both fossil pollen records and satellite-based instruments are remote sensors of Earth's vegetation with complementary properties. Satellites supply spatially continuous and highly resolved images for the past several decades, whereas pollen records include local and regional signals of vegetation composition, spanning millennia. Together, pollen and satellite-based observations measure vegetation change across a broad range of temporal scales. Here, we compare pollen percentages of needleleaved and broadleaved plant taxa to AVHRR estimates of percent tree cover, for two regions in eastern North America with well-defined physiognomic gradients. The linear fit between the pollen percentages and percent tree cover is strongest for search window half-widths of 25–75 km and unweighted or inverse-distance weightings, consistent with previous taxon-based studies of regional pollen source area and transport. Variance not explained by the linear model arises primarily from differential properties of the AVHRR and pollen sensors, particularly site-specific variability in the pollen data and intertaxonomic differences in pollen representation. These sources of variance can be minimized by regionally smoothing the pollen data and multivariate analogue approaches. A strong fit between observed tree-cover percentages and best-analogue estimates (r 2 = 0.70 to 0.78) suggests that analogue-based methods can be applied to infer past tree-cover proportions from fossil pollen records. Linking pollen and AVHRR observations in this manner effectively extrapolates satellite-derived variables beyond the few decades of direct observation, enabling study of longer-term variations in land cover and impacts upon climate and the terrestrial carbon cycle.
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Dissimilarity coefficients measure the difference between multivariate samples and provide a quantitative aid to the identification of modern analogs for fossil pollen samples. How eight coefficients responded to differences among modern pollen samples from eastern North America was tested. These coefficients represent three different classes: (1) unweighted coefficients that are most strongly influenced by large-valued pollen types, (2) equal-weight coefficients that weight all pollen types equally but can be too sensitive to variations among rare types, and (3) signal-to-noise coefficients that are intermediate in their weighting of pollen types. The studies with modern pollen allowed definition of critical values for each coefficient, which, when not exceeded, indicate that two pollen samples originate from the same vegetation region. Dissimilarity coefficients were used to compare modern and fossil pollen samples, and modern samples so similar to fossil samples were found that most of three late Quaternary pollen diagrams could be “reconstructed” by substituting modern samples for fossil samples. When the coefficients indicated that the fossil spectra had no modern analogs, then the reconstructed diagrams did not match all aspects of the originals. No modern analogs existed for samples from before 9300 yr B.P. at Kirchner Marsh, Minnesota, and from before 11,000 yr B.P. at Wintergreen Lake, Michigan, but modern analogs existed for almost all Holocene samples from these two sites and Brandreth Bog, New York.
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