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Pollen records from archaeological sites provide a direct reflection of the vegetation in the immediate vicinity, enabling an accurate depiction of anthropogenic impacts on vegetation. In this study, we applied the biomization technique to fossil pollen data to reconstruct human impact on the biome at the Chengzishan archaeological site in western Liaoning, China, and hence to explore the response of temperate forest vegetation to human activities. The results indicate that the original vegetation at Chengzishan was warm temperate coniferous and broadleaved mixed forest (TEDE). The findings suggest a shift in biome dominance over time, with cool temperate steppe (STEP) replacing TEDE as the dominant biome in response to human activities. Combined with archaeobotanical records, we conclude that the observed vegetation changes in the pollen record were closely linked to deforestation, fire use, and agricultural activities.

This research focuses on the recent pollen image of several vegetation types in NW Italy. In 201 arboreal, shrubby, and herbaceous plant populations, pollen samples were taken from moss polsters, and the corresponding vegetation was recorded using the phytosociological method. Since studies on recent pollen rain in the Mediterranean mountains and coast are rare, this research aims to provide new data and tools to better interpret fossil pollen spectra. Pollen analysis provided data for the comparison between surface spectra and vegetation. Davis indices, fidelity, dispersion, and the relation with vegetation data were calculated for each taxon, and PCA was carried out. Most vegetation types are identifiable through the taxa dominating the pollen spectra, as frequently happens in woodlands (e.g., beech woods, chestnut woods, etc.). Characterizing shrubland and certain tree-dominated vegetation types (e.g., Larix forests) through pollen data is more complex. In this regard, Davis indices are particularly useful for identifying pollen/plant association, over- and underrepresentation of pollen, and taxa indicating vegetation types. Pollen threshold values were calculated which allow the assessment of the local presence of a plant. Overall, the achieved results partially confirm those of previous research carried out in the region, greatly expanding the comparisons between several different plant communities and the database in view of future sharing through the EMPD.

Recently, the evolutionary history of the Caribbean mangroves has been reconsidered using partial palynological databases organized by the time intervals of interest, namely Late Cretaceous to Eocene for the origin, the Eocene–Oligocene transition for major turnover and Neogene to Quaternary for diversification. These discussions have been published in a set of sequential papers, but the raw information remains unknown. This paper reviews all the information available and provides the first comprehensive and updated compilation of the abovementioned partial databases. This compilation is called CARMA-F (CARibbean MAngroves-Fossil) and includes nearly 90 localities from the present and past Caribbean coasts, ranging from the Late Cretaceous to the Pliocene. Details on the Quaternary localities (CARMA-Q) will be published later. CARMA-F lists and illustrates the fossil pollen from past mangrove taxa and their extant representatives, and includes a map of the studied localities and a conventional spreadsheet with the raw data. The compilation is the most complete available for the study of the origin, evolution and diversification of Caribbean mangroves, and is open to modifications for adapting it to the particular interests of each researcher.

The two major aims of this study are (1) To test the performance of the Landscape Reconstruction Algorithm (LRA) to quantify past landscape changes using historical maps and related written sources, and (2) to use the LRA and map reconstructions for a better understanding of the origin of landscape diversity and the recent loss of species diversity. Southern Sweden, hemiboreal vegetation zone. The LRA was applied on pollen records from three small bogs for four time windows between AD 1700 and 2010. The LRA estimates of % cover for woodland/forest, grassland, wetland, and cultivated land were compared with those extracted from historical maps within 3‐km radius around each bog. Map‐extracted land‐use categories and pollen‐based LRA estimates (in % cover) of the same land‐use categories show a reasonable agreement in several cases; when they do not agree, the assumptions used in the data (maps)‐model (LRA) comparison are a better explanation of the discrepancies between the two than possible biases of the LRA modeling approach. Both the LRA reconstructions and the historical maps reveal between‐site differences in landscape characteristics through time, but they demonstrate comparable, profound transformations of the regional and local landscapes over time and space due to the agrarian reforms in southern Sweden during the 18th and 19th centuries. The LRA was found to be the most reasonable approach so far to reconstruct quantitatively past landscape changes from fossil pollen data. The existing landscape diversity in the region at the beginning of the 18th century had its origin in the long‐term regional and local vegetation and land‐use history over millennia. Agrarian reforms since the 18th century resulted in a dramatic loss of landscape diversity and evenness in both time and space over the last two centuries leading to a similarly dramatic loss of species (e.g., beetles). We studied the last three centuries of land‐use history in central Småland (Southern Sweden) using historical maps, pollen records from three small bogs and models of the relationship between pollen and vegetation (the Landscape Reconstruction Algorithm, LRA). The aims of the study is to (1) evaluate the performance of the LRA for quantitative pollen‐based reconstructions of past landscape and (2) discuss the impact of recent land‐use changes (over the last three centuries) on changes in biodiversity (mainly landscape diversity and beetle fauna). The results indicate that the LRA is a robust modelling approach to translate pollen data into vegetation/plant cover, and that the transformation of the landscape since the 18th century strongly diminished biodiversity both at the landscape and species level.

The Late Holocene fossil pollen records from the Zemu glacier, located in Yabuk, North Sikkim, in the eastern Himalayas, effectively generated quantitative climate reconstructions based on the transfer function model. The transfer function model was developed by establishing a modern pollen–climate calibration set from the temperate alpine belt of North Sikkim. A redundancy analysis was carried out to detect the pattern of variation of climatic variables in the modern pollen datasets. The mean annual precipitation (MAP) and mean temperature of the warming month (MTWA) had the strongest influence on the composition of the modern pollen samples among the climatic variables considered in the analysis. Proxy data in the form of fossil pollen records were analyzed for reconstructing past climate based upon the relationships between modern pollen vegetation assemblages and climatic patterns. Transfer functions for MAP and MTWA were developed with the partial least squares (PLS) approach, and model performance was assessed using leave-one-out cross-validation. The validated model was used to reconstruct MAP and MTWA for the last 2992 cal years BP (1042 BC) in North Sikkim. The variability observed in the reconstructions was analyzed for past global climatic events. It was further compared with the available regional and hemispheric proxy-based climate reconstructions. The reconstructions captured comparable Medieval Warm Period (MWP) and Little Ice Age (LIA)-like events from the Zemu glacier region. The fossil pollen data and climate reconstructions were further compared with the mineral magnetism data of the subsurface sediment profile.

Proxy-based reconstructions and modeling of Holocene spatiotemporal precipitation patterns for China and Mongolia have hitherto yielded contradictory results indicating that the basic mechanisms behind the East Asian Summer Monsoon and its interaction with the westerly jet stream remain poorly understood. We present quantitative reconstructions of Holocene precipitation derived from 101 fossil pollen records and analyse them with the help of a minimal empirical model. We show that the westerly jet-stream axis shifted gradually southward and became less tilted since the middle Holocene. This was tracked by the summer monsoon rain band resulting in an early-Holocene precipitation maximum over most of western China, a mid-Holocene maximum in north-central and northeastern China, and a late-Holocene maximum in southeastern China. Our results suggest that a correct simulation of the orientation and position of the westerly jet stream is crucial to the reliable prediction of precipitation patterns in China and Mongolia. The basic mechanisms behind the East Asian Summer Monsoon remain poorly understood. Using proxy-based reconstructions and simulations, here the authors show that changes in the orientation and position of the westerly jet stream resulted in regionally asynchronous Holocene precipitation maxima.

Aim To quantify the effect of Pleistocene climate fluctuations on habitat connectivity across páramos in the Northern Andes. Location Northern Andes. Methods The unique páramos habitat underwent dynamic shifts in elevation in response to changing climate conditions during the Pleistocene. The lower boundary of the páramos is defined by the upper forest line, which is known to be highly responsive to temperature. Here, we reconstruct the extent and connectivity of páramos over the last 1 million years (Myr) by reconstructing the upper forest line from the long fossil pollen record of Funza09, Colombia, and applying it to spatial mapping on modern topographies across the Northern Andes for 752 time slices. Data provide an estimate of how often and for how long different elevations were occupied by páramos and estimate their connectivity to provide insights into the role of topography in biogeographical patterns of páramos. Results Our findings show that connectivity amongst páramos of the Northern Andes was highly dynamic, both within and across mountain ranges. Connectivity amongst páramos peaked during extreme glacial periods but intermediate cool stadials and mild interstadials dominated the climate system. These variable degrees of connectivity through time result in what we term the ‘flickering connectivity system’. We provide a visualization (video) to showcase this phenomenon. Patterns of connectivity in the Northern Andes contradict patterns observed in other mountain ranges of differing topographies. Main conclusions Pleistocene climate change was the driver of significant elevational and spatial shifts in páramos causing dynamic changes in habitat connectivity across and within all mountain ranges. Some generalities emerge, including the fact that connectivity was greatest during the most ephemeral of times. However, the timing, duration and degree of connectivity varied substantially among mountain ranges depending on their topographical configuration. The flickering connectivity system of the páramos uncovers the dynamic settings in which evolutionary radiations shaped the most diverse alpine biome on Earth.

“Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time fossil pollen data. We present an approach for fossil pollen analysis that uses optical superresolution microscopy and machine learning to create a quantitative and higher throughput workflow for producing palynological identifications and hypotheses of biological affinity. We developed three convolutional neural network (CNN) classification models: maximum projection (MPM), multislice (MSM), and fused (FM). We trained the models on the pollen of 16 genera of the legume tribe Amherstieae, and then used these models to constrain the biological classifications of 48 fossil Striatopollis specimens from the Paleocene, Eocene, and Miocene of western Africa and northern South America. All models achieved average accuracies of 83 to 90% in the classification of the extant genera, and the majority of fossil identifications (86%) showed consensus among at least two of the three models. Our fossil identifications support the paleobiogeographic hypothesis that Amherstieae originated in Paleocene Africa and dispersed to South America during the Paleocene-Eocene Thermal Maximum (56 Ma). They also raise the possibility that at least three Amherstieae genera (Crudia, Berlinia, and Anthonotha) may have diverged earlier in the Cenozoic than predicted by molecular phylogenies.