The pace of Holocene vegetation change: Although much is known about the rapid environmental changes that have occurred since the Industrial Revolution, the patterns of change over the preceding millennia have been only patchily understood. Using a global set of >1100 fossil pollen records, Mottlet al.explored the rates of vegetation change over the past 18,000 years (see the Perspective by Overpeck and Breshears). The authors show that the rates of change accelerated markedly during the Late Holocene (∼4.6 to 2.9 thousand years ago), even more rapidly than the climate-driven vegetation changes associated with the end of the last glacial period. In addition, the Late Holocene acceleration began for terrestrial communities as a whole, suggesting that the acceleration in turnover over the past two centuries is the tip of a deeper trend.Science, abg1685, this issue p.860; see also abi9902, p.786

Aims: Understanding fine‐grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine‐grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups).Location: Palaearctic biogeographic realm.Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m² and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class.Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi‐natural) grasslands and natural grasslands are the richest vegetation type. The open‐access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats.Conclusions: The GrassPlot Diversity Benchmarks provide high‐quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation‐plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology.

Aim: Palaeoecological data are crucial for comprehending large‐scale biodiversity patterns and the natural and anthropogenic drivers that influence them over time. Over the last decade, the availability of open‐access research databases of palaeoecological proxies has substantially increased. These databases open the door to research questions needing advanced numerical analyses and modelling based on big‐data compilations. However, compiling and analysing palaeoecological data pose unique challenges that require a guide for producing standardized and reproducible compilations.Innovation: We present a step‐by‐step guide of how to process fossil pollen data into a standardized dataset compilation ready for macroecological and palaeoecological analyses. We describe successive criteria that will enhance the quality of the compilations. Though these criteria are project and research question‐dependent, we discuss the most important assumptions that should be considered and adjusted accordingly. Our guide is accompanied by an R‐workflow—called FOSSILPOL—and corresponding R‐package—called R‐Fossilpol—that provide a detailed protocol ready for interdisciplinary users. We illustrate the workflow by sourcing and processing Scandinavian fossil pollen datasets and show the reproducibility of continental‐scale data processing.Main Conclusions: The study of biodiversity and macroecological patterns through time and space requires large‐scale syntheses of palaeoecological datasets. The data preparation for such syntheses must be transparent and reproducible. With our FOSSILPOL workflow and R‐package, we provide a protocol for optimal handling of large compilations of fossil pollen datasets and workflow reproducibility. Our workflow is also relevant for the compilation and synthesis of other palaeoecological proxies and as such offers a guide for synthetic and cross‐disciplinary analyses with macroecological, biogeographical and palaeoecological perspectives. However, we emphasize that expertise and informed decisions based on palaeoecological knowledge remain crucial for high‐quality data syntheses and should be strongly embedded in studies that rely on the increasing amount of open‐access palaeoecological data.

Questions: Species–area relationships (SARs) are fundamental for understanding biodiversity patterns and are generally well described by a power law with a constant exponent z. However, z‐values sometimes vary across spatial scales. We asked whether there is a general scale dependence of z‐values at fine spatial grains and which potential drivers influence it.Location: Palaearctic biogeographic realm.Methods: We used 6,696 nested‐plot series of vascular plants, bryophytes and lichens from the GrassPlot database with two or more grain sizes, ranging from 0.0001 m² to 1,024 m² and covering diverse open habitats. The plots were recorded with two widespread sampling approaches (rooted presence = species “rooting” inside the plot; shoot presence = species with aerial parts inside). Using Generalized Additive Models, we tested for scale dependence of z‐values by evaluating if the z‐values differ with gran size and tested for differences between the sampling approaches. The response shapes of z‐values to grain were classified by fitting Generalized Linear Models with logit link to each series. We tested whether the grain size where the maximum z‐value occurred is driven by taxonomic group, biogeographic or ecological variables.Results: For rooted presence, we found a strong monotonous increase of z‐values with grain sizes for all grain sizes below 1 m². For shoot presence, the scale dependence was much weaker, with hump‐shaped curves prevailing. Among the environmental variables studied, latitude, vegetation type, naturalness and land use had strong effects, with z‐values of secondary peaking at smaller grain sizes.Conclusions: The overall weak scale dependence of z‐values underlines that the power function generally is appropriate to describe SARs within the studied grain sizes in continuous open vegetation, if recorded with the shoot presence method. When clear peaks of z‐values occur, this can be seen as an expression of granularity of species composition, partly driven by abiotic environment.

Compositional changes in Himalayan vegetation in response to the major drivers of biodiversity loss, climate change and land‐use change, are barely documented. We quantify temporal changes in the alpine vegetation of central Nepal and attribute these changes to temporally varying climatic and land‐use factors. We re‐surveyed the alpine vegetation of two locations within Langtang National Park, central Nepal, after 25 yr using 127 plots of 100 m². Using ordination, regression, and weighted average regression and calibration techniques, we analyzed the changes in terms of species abundance, frequency, and elevational shift in relation to changing atmospheric temperature, precipitation, and livestock grazing. We found a significant increase in the frequency and relative abundance of the majority of species, which was significantly related to the temporal trends in climatic factors and grazing intensity. Out of 12 species with unimodal responses along the elevation gradient during both surveys, the optima of eight species decreased over the time period. The observed elevations of 62 out of 92 sample plots (hence, species composition) in 2014 were lower than the elevations calibrated from species composition and elevation of 1990, indicating an overall downward shift of species assemblages. However, an upward shift of assemblages was also observed at higher elevations. These results indicate that the observed temporal changes in alpine vegetation, largely contrasting the expected upslope shift of species due to climate warming, are driven most likely by interactions of contemporary climate and land‐use changes, especially reduced grazing. The complex interactions and feedback mechanisms between warmer winters, increased precipitation, reduced grazing pressure, and thereby altered species interactions most likely facilitated the downslope shift of alpine species assemblages. Climatic and land‐use responses of plant species assemblages should therefore be studied focusing on the potential interactions between both the climatic and the land‐use factors because such interactions and feedback mechanisms have potential to mask or modify the expected climatic or land‐use response of biodiversity.