Reconstructions and simulations disagree on whether the Holocene exhibited a long-term cooling or warming signal. Anthropogenic land-use could be an important forcing regionally, but available population-based estimates differ widely. We examine transient Holocene climate model simulations forced with three population-based disturbed-land reconstructions and compare this with a fourth scenario derived entirely from fossil pollen records. The direct biophysical temperature effects are broadly similar across the scenarios but the pollen-based product suggests an earlier onset of disturbance, particularly in China and accounting for its limited spatial coverage, falls closer to the upper limit of the existing uncertainty range. Impacts in many areas begin during the mid-Holocene but emergence of a signal varies spatially with earliest impacts over Europe, China and the North Atlantic. Significant uncertainties remain, and these could be tackled by improving the representation of land-use effects in climate models or by merging different information sources related to Holocene land-use.

Pollen records and models of pollen-vegetation relationships are required to reconstruct past plant abundances during the Holocene to answer specific questions on climate history, human impact, biodiversity, and their interactions. An important parameter for model applications is pollen productivity, estimated as relative pollen productivity (RPP) using a modern dataset of pollen assemblages and related plant cover using the extended R value (ERV) model. We present here the first study performed in India to obtain estimates of RPP for key plant taxa of the tropical dry evergreen forest (TDEF) formations in southeastern India. Pollen samples collected following standard protocols at 14 sites with a stratified random distribution provided 96 identified pollen morphotypes corresponding to 228 plant species in the field surveys. To facilitate comparison of these results with RPP values obtained in other tropical regions, the approach and programs of Sugita were used. Several combinations of 20 selected pollen morphotypes were deployed in the model runs that comprised different combinations of three Prentice-Sugita ERV submodels, with three pollen dispersion models for distance weighting of the vegetation data. The best RPP estimates were obtained for six major TDEF plant taxa including the reference taxon Poaceae with ERV submodel 3 and Prentice's dispersion model, as follows (+/- SD): Justicia-t. (herb) (19.02 +/- 0.11) > Dodonaea viscosa (shrub) (17.70 +/- 0.03) > Acacia-t. (tree) (13.48 +/- 0.11) > Melastomataceae/Combretaceae (tree) (4.22 +/- 0.01) > Randia (shrub) (1.97 +/- 0.02) > Poaceae (herb) (1.00 +/- 0.00). While several of these taxa occur elsewhere in Asia, the Caribbean and Africa, published RPP values for comparison are only available for Acacia-t. and Melastomataceae/Combretaceae in Africa. They differ greatly from the values in this study, implying a strong pollen underrepresentation of the two taxa compared to Poaceae in Africa, while there is a strong pollen overrepresentation for the same two taxa in southern India. This is tentatively explained by the different constituent species involved and differences in landscape structure and related field work strategies. These results highlight that large between-continent differences in RPPs for the same taxa may occur.

Land cover governs the biogeophysical and biogeochemical feedbacks between the land surface and atmosphere. Holocene vegetation-atmosphere interactions are of particular interest, both to understand the climate effects of intensifying human land use and as a possible explanation for the Holocene temperature conundrum, a widely studied mismatch between simulated and reconstructed temperatures. Progress has been limited by a lack of data-constrained, quantified, and consistently produced reconstructions of Holocene land cover change. As a contribution to the Past Global Changes (PAGES) LandCover6k Working Group, we present a new suite of land cover reconstructions with uncertainty for North America, based on a network of 1445 sedimentary pollen records and the REVEALS pollen-vegetation model (PVM) coupled with a Bayesian spatial model. These spatially comprehensive land cover maps are then used to determine the pattern and magnitude of North American land cover changes at continental to regional scales. Early Holocene afforestation in North America was driven by rising temperatures and deglaciation, and this afforestation likely amplified early Holocene warming via the albedo effect. A continental-scale mid-Holocene peak in summergreen trees and shrubs (8.5 to 4 ka) is hypothesized to represent a positive and understudied feedback loop among insolation, temperature, and phenology. A last-millennium decrease in summergreen trees and shrubs with corresponding increases in open land was likely driven by a spatially varying combination of intensifying land use and neoglacial cooling. Land cover trends vary within and across regions, due to individualistic taxon-level responses to environmental change. Major species-level events, such as the mid-Holocene decline in Tsuga canadensis (eastern hemlock), may have altered regional climates. The substantial land cover changes reconstructed here support the importance of biogeophysical and biogeochemical vegetation feedbacks to Holocene climate-carbon dynamics. However, recent model experiments that invoke vegetation feedbacks to explain the Holocene temperature conundrum may have overestimated land cover forcing by replacing Northern Hemisphere grasslands >30 degrees N with forests, an ecosystem state that is not supported by these land cover reconstructions. These Holocene reconstructions for North America, along with similar LandCover6k products now available for other continents, serve the Earth system modeling community by providing better-constrained land cover scenarios and benchmarks for model evaluation, ultimately making it possible to better understand the regional- to global-scale processes driving Holocene land cover, carbon cycle, and climate dynamics.

In this study, we investigate the interplay between relative sea-level changes, the development of human settlements and land-cover changes in the Västervik-Gamlebyviken region on the southeast coast of Sweden, an important archaeological area from the Mesolithic until recent times. The reconstruction of shore displacement was based on diatom analysis of radiocarbon-dated sediment cores from three lake basins combined with previously published lake isolation data. The resulting curve was used to construct palaeogeographical maps for selected time windows. Land-cover changes were inferred from pollen data from three lakes using the Landscape Reconstruction Algorithm with its two models REVEALS and LOVE. Our data suggest that people took advantage of the land gained due to an overall fall in relative sea level from similar to 35 to similar to 3 metres above sea level (m a.s.l.) over the last 10 000 years, interrupted by periods of transgression and highstands. A sea-level regression of similar to 16 m occurred between 10 000 and 8500 cal a BP followed by an similar to 3-4-m sea-level rise, reaching similar to 22 m a.s.l. at similar to 7500 cal a BP, which corresponds to the maximum Littorina Sea shoreline in the area. The available archaeological findings for the Mesolithic and Early Neolithic (8950-5450 cal a BP) agree well with the shore displacement curve showing that settlements and human activities were concentrated along or above the shorelines as defined from our study. During the transgression after 8500 cal a BP, however, seasonal settlements were submerged (as shown by findings of polished stone tools and hearths buried in sand) and used again during the subsequent regression after 4600 cal a BP. The Iron Age (2450-900 cal a BP) corresponds partly to a highstand at similar to 11 m a.s.l. between 3600 and 2000 cal a BP and partly to a rapid regression of similar to 8 m between 2000 and 1500 cal a BP, and both periods coincide with known human activities along the contemporaneous shoreline. The rapid regression after 2000 cal a BP corresponds to an increase of both regional and local landscape openness and the beginning of a continuous record of crop cultivation. (c) 2024 The Author(s) Journal of Quaternary Science Published by John Wiley & Sons Ltd.

Reconstructions of past land use and related land-cover changes at local and regional scales are needed to evaluate the potential long-term impacts of land use on the coastal waters of the Baltic Sea. In this purpose, we selected the Gamleby area at the Swedish Baltic Sea coast for a case study. We use a new, high resolution pollen record from a small lake (Lillsjon) located 3.6 km NNW of the bay Gamlebyviken and detailed analysis of the available archeological data to reconstruct local land-use changes over the last 3000 years. To estimate land-cover change at local (2-3 km radius area) and regional (50 km radius area) scales we use four additional, published pollen records from two small and two large lakes (25-70 km S of Lillsjon) and the Landscape Reconstruction Algorithm, a pollen-vegetation modeling scheme. Results show that regional and local (small lakes Lillsjon and Hyttegol) land-cover changes are comparable over the last 1500 years (Late Iron Age to present), and that landscape openness was much larger locally than regionally (difference of 20-40% cover over the last 500 years). The periods of largest potential impacts on the Gamlebyviken Bay from regional and local land use are 200-950 CE (Late Iron Age) and 1450 CE to present, and of lowest potential impacts 950-1450 CE. The question on whether the large landscape openness 1150-50 BCE and significant afforestation 50 BCE-200 CE reconstructed for Lillsjon's area are characteristic of the Gamlebyviken region will require additional pollen records in the catchment area.

Understanding the environmental and climate influence on the Holocene stable isotope record in peat is essential for applying the proxies in the paleoenvironmental reconstruction of lake and bog ecosystems. Here, we report total organic carbon (TOC), TOC to total nitrogen (N) ratio (C/N), and stable isotope ratios of organic carbon (S13C) and nitrogen (S15N) of bulk sediment and peat organic matter (OM) from a radiocarbon-dated core collected from Stavs & aring;kra bog in southern Sweden. Changes in the TOC, C/N, S13C and S15N between 12 ka and 10.4 ka BP represent shifts in the OM source from aquatic primary producers to terrestrial swamp vegetation and pinpoint the transition of a highly productive water body into a reed swamp. The variation in S13C values and increase in peat accumulation rate (AR) from 10.8 ka BP imply a rapid transition of the aquatic body into a peatforming swamp and a shift from aquatic to atmospheric CO2 as the source of carbon (C) to the vegetation at the site. A sharp drop in N and S15N in the reed swamp peat may indicate fixed-N in the soil as the source of N to the growing vegetation. Heavier S13C and higher C/N ratio at the bottom of wood carr peat may reflect fire events. The rapid increase in peat AR between 7 ka and 6.5 ka BP suggests increased peat deposition under warmer and drier conditions. Lighter S15N and S13C, lower N, and TOC concentrations between 1.1 ka and 0.8 ka BP likely suggest warmer conditions related to the 'Medieval Climate Anomaly'. The research demonstrates the successful application of stable C and N isotope ratios of bulk peat in palaeoenvironment and palaeoecological interpretations.

This paper studies the impact of land use and land cover change (LULCC) on the climate around 2500 years ago (2.5 ka), a period of rapid transitions across the European landscape. One global climate model was used to force two regional climate models (RCMs). The RCMs used two land cover descriptions. The first was from a dynamical vegetation model representing potential land cover, and the second was from a land cover description reconstructed from pollen data by statistical interpolation. The two different land covers enable us to study the impact of land cover on climate conditions. Since the difference in landscape openness between potential and reconstructed land cover is mostly due to LULCC, this can be taken as a measure of early anthropogenic effects on climate. Since the sensitivity to LULCC is dependent on the choice of climate model, we also use two RCMs. The results show that the simulated 2.5 ka climate was warmer than the simulated pre-industrial (PI, 1850 CE) climate. The largest differences are seen in northern Europe, where the 2.5 ka climate is 2-4 degrees C warmer than the PI period. In summer, the difference between the simulated 2.5 ka and PI climates is smaller (0-3 degrees C), with the smallest differences in southern Europe. Differences in seasonal precipitation are mostly within +/- 10 %. In parts of northern Europe, the 2.5 ka climate is up to 30% wetter in winter than that of the PI climate. In summer there is a tendency for the 2.5 ka climate to be drier than the PI climate in the Mediterranean region. The results also suggest that LULCC at 2.5 ka impacted the climate in parts of Europe. Simulations including reconstructed LULCC (i.e. those using pollen-derived land cover descriptions) give up to 1 degrees C higher temperature in parts of northern Europe in winter and up to 1.5 degrees C warmer in southern Europe in summer than simulations with potential land cover. Although the results are model dependent, the relatively strong response implies that anthropogenic land cover changes that had occurred during the Neolithic and Bronze Age could have affected the European climate by 2.5 ka.

The Landscape Reconstruction Algorithm (LRA) is regarded as the soundest approach for quantifying taxon-specific plant cover from pollen data. The reliability of relative pollen productivity (RPP) estimates is fundamental in the accuracy of quantitative vegetation reconstruction using the LRA approach. Inconsistent RPP estimates produced by different studies can cast doubt on the reliability and applicability of quantitative vegetation reconstruction. Therefore, it is crucial that the RPP estimates are evaluated before being applied for quantitative vegetation reconstruction. We have tested two alternative approaches, namely, a leave-one-out cross-validation (LOO) method and a splitting-by-subregion strategy, using surface pollen assemblages and the REVEALS model-the first step in the LRA-to evaluate the reliability of RPPs estimates of 10 target taxa obtained in the cultural landscape of Shandong. We compared the REVEALS estimates (RVs) with observations of regional vegetation abundance (OBVs) and pollen proportions (PPs). The RVs of all taxa are generally closer to OBVs than PPs, and the degree of similarity depends strongly on the abundance of individual taxa in plant and pollen; taxa dominant in the region show the highest similarity between RVs and OBVs, such as Artemisia, Poaceae, and Humulus. The RVs of all herb taxa except Humulus and Asteraceae SF Cichorioideae are slightly overrepresented, and the RVs of all tree taxa are underrepresented except for Castanea. The comparison of RVs with OBVs collected from different spatial extents shows that the RVs of all herb taxa are more similar to OBVs collected from shorter distances (100 km and 75 km for the entire region and the subregion, respectively), whereas the RVs of all tree taxa are more similar to OBVs collected from longer distances (150 km and 100 km for the entire region and the subregion, respectively). Furthermore, our findings highlight the importance to test different sizes of area for vegetation surveys for evaluation of the RVs given that the appropriate size of vegetation survey may vary between low pollen producers (mainly herbs) and high pollen producers (mainly trees). We consider that the LOO strategy is the best approach in this case study for evaluating the RPP estimates from surface moss polsters. The evaluation confirms the reliability of the obtained RPP estimates for their potential application in quantitative reconstruction of vegetation abundance in temperate China.

We present the first gridded and temporally continuous quantitative pollen-based plant-cover reconstruction for temperate and northern subtropical China over the Holocene (11.7 ka to present) obtained by applying the Regional Estimates of VEgetation Abundance from Large Sites (REVEALS) model. The objective is to provide a dataset of pollen-based land cover for the last ca. 12 millennia that is suitable for palaeoclimate modelling and for the evaluation of simulated past vegetation cover from dynamic vegetation models and anthropogenic land-cover change (ALCC) scenarios. The REVEALS reconstruction was achieved using 94 selected pollen records from lakes and bogs at a 1 degrees x 1 degrees spatial scale and a temporal resolution of 500 years between 11.7 and 0.7 ka and in three recent time windows (0.7-0.35 ka, 0.35-0.1 ka, and 0.1 ka to present). The dataset includes REVEALS estimates of cover and their standard errors (SEs) for 27 plant taxa in 75 1 degrees x 1 degrees grid cells distributed within the study region. The 27 plant taxa were also grouped into 6 plant functional types and 3 land-cover types (coniferous trees CT, broadleaved trees BT, and C-3 herbs/open land (C3H/OL)), and their REVEALS estimates of cover and related SEs were calculated. We describe the protocol used for the selection of pollen records and the REVEALS application (with parameter settings) and explain the major rationales behind the protocol. As an illustration, we present, for eight selected time windows, gridded maps of the pollen-based REVEALS estimates of cover for the three land-cover types (CT, BT, and C3H/OL). We then discuss the reliability and limitations of the Chinese dataset of Holocene gridded REVEALS plant cover, and its current and potential uses. The dataset is available at the National Tibetan Plateau Data Center (TPDC; Li, 2022; ).

We compare Holocene forest-cover changes in Europe derived from a transient MPI-ESM1.2 simulation with high spatial resolution time-slice simulations conducted in LPJ-GUESS and pollen-based quantitative reconstructions of forest cover based on the REVEALS model (pol-RVs). The dynamic vegetation models and pol-RVs agree with respect to the general temporal trends in forest cover for most parts of Europe, with a large forest cover during the mid-Holocene and substantially smaller forest cover closer to the present time. However, the age of the start of decrease in forest cover varies between regions, and is much older in the pol-RVs than in the models. The pol-RVs suggest much earlier anthropogenic deforestation than the prescribed land-use in the models starting 2000 years ago. While LPJ-GUESS generally overestimates forest cover compared to pol-RVs, MPI-ESM indicates lower percentages of forest cover than pol-RVs, particularly in Central Europe. A comparison of the simulated climate with chironomid-based climate reconstructions reveal that model-data mismatches in forest cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments show that the model results strongly depend on the models tuning regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid during climate and vegetation states totally different from today’s. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model-data comparisons with additional challenges. Moreover, our study suggests that land-use is the main driver of forest decline in Europe during the mid- and late-Holocene.