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Recent climate change has effectively rewound the climate clock by approximately 120 000 years and is expected to reverse this clock a further 50 Myr by 2100. We aimed to answer two essential questions to better understand the changes in ecosystems worldwide owing to predicted climate change. Firstly, we identify the locations and time frames where novel ecosystems could emerge owing to climate change. Secondly, we aim to determine the extent to which biomes, in their current distribution, will experience an increase in climate-driven ecological novelty. To answer these questions, we analysed three perspectives on how climate changes could result in novel ecosystems in the near term (2100), medium (2200) and long term (2300). These perspectives included identifying areas where climate change could result in new climatic combinations, climate isoclines moving faster than species migration capacity and current environmental patterns being disaggregated. Using these metrics, we determined when and where novel ecosystems could emerge. Our analysis shows that unless rapid mitigation measures are taken, the coverage of novel ecosystems could be over 50% of the land surface by 2100 under all change scenarios. By 2300, the coverage of novel ecosystems could be above 80% of the land surface. At the biome scale, these changes could mean that over 50% of locations could shift towards novel ecosystems, with the majority seeing these changes in the next few decades. Our research shows that the impact of climate change on ecosystems is complex and varied, requiring global action to mitigate and adapt to these changes. This article is part of the theme issue 'Biodiversity dynamics and stewardship in a transforming biosphere'. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'. [ABSTRACT FROM AUTHOR]

Human-induced global changes, including anthropogenic climate change, biotic globalization, trophic downgrading and pervasive land-use intensification, are transforming Earth's biosphere, placing biodiversity and ecosystems at the forefront of unprecedented challenges. The Anthropocene, characterized by the importance of Homo sapiens in shaping the Earth system, necessitates a re-evaluation of our understanding and stewardship of ecosystems. This theme issue delves into the multifaceted challenges posed by the ongoing ecological planetary transformation and explores potential solutions across four key subthemes. Firstly, it investigates the functioning and stewardship of emerging novel ecosystems, emphasizing the urgent need to comprehend the dynamics of ecosystems under uncharted conditions. The second subtheme focuses on biodiversity projections under global change, recognizing the necessity of predicting ecological shifts in the Anthropocene. Importantly, the inherent uncertainties and the complexity of ecological responses to environmental stressors pose challenges for societal responses and for accurate projections of ecological change. The RAD framework (resist-accept-direct) is highlighted as a flexible yet nuanced decision-making tool that recognizes the need for adaptive approaches, providing insights for directing and adapting to Anthropocene dynamics while minimizing negative impacts. The imperative to extend our temporal perspective beyond 2100 is emphasized, given the irreversible changes already set in motion. Advancing methods to study ecosystem dynamics under rising biosphere novelty is the subject of the third subtheme. The fourth subtheme emphasizes the importance of integrating human perspectives into understanding, forecasting and managing novel ecosystems. Cultural diversity and biological diversity are intertwined, and the evolving relationship between humans and ecosystems offers lessons for future stewardship. Achieving planetary stewardship in the Anthropocene demands collaboration across scales and integration of ecological and societal perspectives, scalable approaches fit to changing, novel ecological conditions, as well as cultural innovation. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'. [ABSTRACT FROM AUTHOR]

Litter decomposition represents a major path for atmospheric carbon influx into Arctic soils, thereby controlling below‐ground carbon accumulation. Yet, little is known about how tundra litter decomposition varies with microenvironmental conditions, hindering accurate projections of tundra soil carbon dynamics with future climate change. Over 14 months, we measured landscape‐scale decomposition of two contrasting standard litter types (Green tea and Rooibos tea) in 90 plots covering gradients of micro‐climate and ‐topography, vegetation cover and traits, and soil characteristics in Western Greenland. We used the tea bag index (TBI) protocol to estimate relative variation in litter mass loss, decomposition rate (k) and stabilisation factor (S) across space, and structural equation modelling (SEM) to identify relationships among environmental factors and decomposition. Contrasting our expectations, microenvironmental factors explained little of the observed variation in both litter mass loss, as well as k and S, suggesting that the variables included in our study were not the major controls of decomposer activity in the soil across the studied tundra landscape. We use these unexpected findings of our study combined with findings from the current literature to discuss future avenues for improving our understanding of the drivers of tundra decomposition and, ultimately, carbon cycling across the warming Arctic. [ABSTRACT FROM AUTHOR]

Aim: Reconstructing megafauna diversity in the past before anthropogenic impacts is crucial for developing targeted restoration strategies. We estimated the diversity and functional decline of European megafauna in the present compared with the nearest in‐time climate period analogue to the present but prior to the worldwide diffusion of Homo sapiens. Location: Europe. Time Period: Last Interglacial (LIG; ca. 127,000 years ago) to present. Major Taxa Studied: Wild, large (≥10 kg) terrestrial mammals. Methods: We assessed the distribution of 48 European megafauna species during the LIG using hindcasting modelling and fossil records. Then, we estimated the decline in megafauna community diversity and potential trait‐based functional effects from the LIG to the present, accounting for climate differences between the two periods. Results: Species richness and community biomass dropped by 70.8% (±11.7%) and by 94.5% (±9.9%). Functional diversity dropped by 80.3% (±15.3%) for herbivores and by 64.9% (±29.1%) for carnivores, while trait‐informed potential vegetation and meat consumptions dropped by 82.3% (±13.4%) and 60.5% (±26.0%). The loss in megafauna diversity and associated ecological processes were high everywhere, but particularly in western Europe for carnivores and in the East European Plain for herbivores. Potential megafauna richness in the two periods was similar if only climate‐driven differences were considered. Main Conclusions: Severe, size‐biased defaunation has degraded megafauna assemblages and megafauna‐mediated ecological processes across Europe from the LIG to the present. These patterns cannot be explained by climate differences between the two periods, thus were likely driven by prehistoric Homo sapiens. The results suggest that the structure of wild ecosystems of the present strongly deviates from the evolutionary norm, with decreased functional heterogeneity and decreased fluxes of biogeochemical compounds across the trophic networks, highlighting the importance of ambitious policies of megafauna community restoration to support ecosystem functioning. [ABSTRACT FROM AUTHOR]

Following deglaciation during the final stages of the Pleistocene, vast landscapes became increasingly accessible for human dispersal. With no historical analogs, it remains uncertain how people were adapting to these unknown and often unstable environments and whether dispersals were sustained or characterized by local retreat or extinction events. We here address these uncertainties by using climate niche modeling to investigate the relationship between climate and the archaeological record of such a dispersal event: the Late Upper Paleolithic Hamburgian settlement of northern Europe. Our models consider temperature and precipitation from paleoclimate models with high temporal and spatial resolution. They suggest that rising temperatures instead of precipitation changes drove dispersal events by allowing carriers of the Hamburgian tradition to occupy a specific northward-shifting climate space. Similarly, our models suggest a subsequent constriction and fragmentation of this climate space caused by declining temperatures. This climatic downturn and shifting climate space coincide with the disappearance of the Hamburgian tradition from the archaeological record. We argue that this sudden climatic change altered the social and demographic costs of northward dispersal to become unsustainable, leading to a depopulation of the region. [ABSTRACT FROM AUTHOR]

The Landsat satellites provide decades of near‐global surface reflectance measurements that are increasingly used to assess interannual changes in terrestrial ecosystem function. These assessments often rely on spectral indices related to vegetation greenness and productivity (e.g. Normalized Difference Vegetation Index, NDVI). Nevertheless, multiple factors impede multi‐decadal assessments of spectral indices using Landsat satellite data, including ease of data access and cleaning, as well as lingering issues with cross‐sensor calibration and challenges with irregular timing of cloud‐free acquisitions. To help address these problems, we developed the 'LandsatTS' package for R. This software package facilitates sample‐based time series analysis of surface reflectance and spectral indices derived from Landsat sensors. The package includes functions that enable the extraction of the full Landsat 5, 7, and 8 records from Collection 2 for point sample locations or small study regions using Google Earth Engine accessed directly from R. Moreover, the package includes functions for 1) rigorous data cleaning, 2) cross‐sensor calibration, 3) phenological modeling, and 4) time series analysis. For an example application, we show how 'LandsatTS' can be used to assess changes in annual maximum vegetation greenness from 2000 to 2022 across the Noatak National Preserve in northern Alaska, USA. Overall, this software provides a suite of functions to enable broader use of Landsat satellite data for assessing and monitoring terrestrial ecosystem function during recent decades across local to global geographic extents. [ABSTRACT FROM AUTHOR]

Classic ecological research into the determinants of biodiversity patterns emphasised the important role of three‐dimensional (3D) vegetation heterogeneity. Yet, measuring vegetation structure across large areas has historically been difficult. A growing focus on large‐scale research questions has caused local vegetation heterogeneity to be overlooked compared with more readily accessible habitat metrics from, for example, land cover maps.Using newly available 3D vegetation data, we investigated the relative importance of habitat and vegetation heterogeneity for explaining patterns of bird species richness and composition across Denmark (42,394 km2).We used standardised, repeated point counts of birds conducted by volunteers across Denmark alongside metrics of habitat availability from land‐cover maps and vegetation structure from rasterised LiDAR data (10 m resolution). We used random forest models to relate species richness to environmental features and considered trait‐specific responses by grouping species by nesting behaviour, habitat preference and primary lifestyle. Finally, we evaluated the role of habitat and vegetation heterogeneity metrics in explaining local bird assemblage composition.Overall, vegetation structure was equally as important as habitat availability for explaining bird richness patterns. However, we did not find a consistent positive relationship between species richness and habitat or vegetation heterogeneity; instead, functional groups displayed individual responses to habitat features. Meanwhile, habitat availability had the strongest correlation with the patterns of bird assemblage composition.Our results show how LiDAR and land cover data complement one another to provide insights into different facets of biodiversity patterns and demonstrate the potential of combining remote sensing and structured citizen science programmes for biodiversity research. With the growing coverage of LiDAR surveys, we are witnessing a revolution of highly detailed 3D data that will allow us to integrate vegetation heterogeneity into studies at large spatial extents and advance our understanding of species' physical niches. [ABSTRACT FROM AUTHOR]

Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces. Functional trait data could guide predictions of species responses to environmental change. Here, the authors show that winner and loser shrub species in the warming tundra biome overlap in trait space and may therefore be difficult to predict based on commonly measured traits. [ABSTRACT FROM AUTHOR]

Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces. Functional trait data could guide predictions of species responses to environmental change. Here, the authors show that winner and loser shrub species in the warming tundra biome overlap in trait space and may therefore be difficult to predict based on commonly measured traits. [ABSTRACT FROM AUTHOR]

The exploration of factors and processes affecting biodiversity loss is central to nature management and wildlife conservation, but only recently has knowledge about the absence of species been recognized as a valuable asset to understand the current biodiversity crisis. In this paper, we explore the dark diversity (species that belong to a site-specific species pool but that are not locally present) of breeding birds in Denmark assessed through species co-occurrence patterns. We apply a nation-wide atlas survey of breeding birds (with a 5 × 5 km resolution), to investigate how landscape characteristics may influence avian diversity, and whether threatened and near threatened species are more likely to occur in dark diversity than least concern (LC) species. On average, the dark diversity constituted 41% of all species belonging to the site-specific species pools and threatened and near-threatened species had a higher probability of belonging to the dark diversity than least concern species. Habitat heterogeneity was negatively related to dark diversity and the proportional cover of intensive agriculture positively related, implying that homogeneous landscapes dominated by agricultural interests led to more absent avian species. Finally, we found significant effects of human disturbance and distance to the coast, indicating that more breeding bird species were missing when human disturbance was high and in near-coastal areas. Our study provides the first attempt to investigate dark diversity among birds and highlights how important landscape characteristics may shape breeding bird diversity and reveal areas of considerable species impoverishment. [ABSTRACT FROM AUTHOR]

High-resolution, downscaled climate model data are used in a wide variety of applications across environmental sciences. Here we introduce a new, high-resolution dataset, CHELSA-TraCE21k. It is obtained by downscaling TraCE-21k data, using the "Climatologies at high resolution for the earth's land surface areas" (CHELSA) V1.2 algorithm with the objective to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100-year time steps for the last 21 000 years. Paleo-orography at high spatial resolution and for each time step is created by combining high-resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases and interpolations using data from a global model of glacial isostasy (ICE-6G_C) and a coupling to mean annual temperatures from TraCE21k (Transient Climate Evolution of the last 21 000 years) based on the Community Climate System Model version 3 (CCSM3). Based on the reconstructed paleo-orography, mean annual temperature and precipitation were downscaled using the CHELSA V1.2 algorithm. The data were validated by comparisons with the glacial extent of the Laurentide ice sheet based on expert delineations, proxy data from Greenland ice cores, historical climate data from meteorological stations, and a dynamic simulation of species distributions throughout the Holocene. Validations show that the CHELSA-TraCE21k V1.0 dataset reasonably represents the distribution of temperature and precipitation through time at an unprecedented 1 km spatial resolution, and simulations based on the data are capable of detecting known LGM refugia of species. [ABSTRACT FROM AUTHOR]

Question: How does naturalistic grazing (trophic rewilding with large herbivores), in contrast to mowing and free succession (no grazing), affect plant community composition and species richness in temperate grassland grazed by semi‐feral cattle and horses? Location: Mols Laboratory, Denmark. Methods: We investigated grazing exclosures in the rewilding area of the Mols Laboratory, four years after its establishment. We focused on moist to dry grassland vegetation, that is, excluding scrub and woodland. Each experimental block consisted of five 5 × 9 m plots, representing four fenced treatments, that is, summer‐only grazing, winter‐only grazing, full exclosure with annual autumn mowing and full exclosure with passive succession. The matrix (the fifth treatment) was grazed by large herbivores at close‐to‐natural densities, that is, regulated bottom‐up by the carrying capacity of the area. Hence, even the seasonal grazing treatments were grazed at close‐to‐natural animal density. Quantitative plant community composition was assessed using the point‐intercept method in 25 × 25 cm quadrats, supplemented with biomass calibration models based on additional quadrats, in which above‐ground plant biomass was harvested after recording and the material sorted to species and weighed. Uniqueness was assessed as the sum of inverse range sizes for constituent species (unicity). Results: We found an appreciably higher plant species richness in grazing treatments than under both annual mowing and full exclosure, but only minor differences between seasonal grazing treatments. Uniqueness was highest in year‐round and winter‐only grazing and lowest in summer‐only grazing. The forb:graminoid ratio tended to be high in the winter‐only grazing treatment, whereas annual mowing was associated with dominance of graminoids over forbs. Full‐exclosure plots had accumulation of litter and the lowest species richness. Initial heterogeneity between plots within blocks and a systematic difference between blocks in moist and dry grasslands may have diluted treatment effects at this early point after the onset of the experiment. Data analysis using the biomass estimates derived from the calibration models yielded only minor differences in the patterns described above, when compared to the results obtained using the raw number of intercepts. Conclusions: Naturalistic grazing is a goal in itself in ecological restoration, but also proposed as an efficient management tool to promote conservation of grassland plants and communities. We found both plant species richness and the prevalence of regionally rarer species (uni) to be higher with grazing than mowing or abandonment. Similarly, the tendency for forbs to prevail under grazing may translate into enhanced floral resources for anthophilous insects. Summer‐only grazing at low density of large herbivores was not significantly different from winter‐only and year‐round grazing, but this treatment was much closer to natural grazing than intensive summer grazing typical of agri‐environmental practices.Grazing is a natural ecosystem process and, thus, restoring naturalistic grazing using feral animals may be seen as a restoration goal in itself, notwithstanding the effects on biodiversity. Nevertheless, the present study demonstrates that naturalistic grazing as a management tool may indeed create habitat for regionally uncommon species of conservation concern and probably enhance resource availability to flower‐seeking insects. [ABSTRACT FROM AUTHOR]

Climate warming is inducing widespread vegetation changes in Arctic tundra ecosystems, with the potential to alter carbon and nutrient dynamics between vegetation and soils. Yet, we lack a detailed understanding of how variation in vegetation and topography influences fine‐scale temperatures ("microclimate") that mediate these dynamics, and at what resolution vegetation needs to be sampled to capture these effects. We monitored microclimate at 90 plots across a tundra landscape in western Greenland. Our stratified random study design covered gradients of topography and vegetation, while nested plots (0.8–100 m2) enabled comparison across different sampling resolutions. We used Bayesian mixed‐effect models to quantify the direct influence of plot‐level topography, moisture and vegetation on soil, near‐surface and canopy‐level temperatures (−6, 2, and 15 cm). During the growing season, colder soils were predicted by shrub cover (−0.24°C per 10% increase), bryophyte cover (−0.35°C per 10% increase), and vegetation height (−0.17°C per 1 cm increase). The same three factors also predicted the magnitude of differences between soil and above‐ground temperatures, indicating warmer soils at low cover/height, but colder soils under closed/taller canopies. These findings were consistent across plot sizes, suggesting that spatial predictions of microclimate may be possible at the operational scales of satellite products. During winter, snow cover (+0.75°C per 10 snow‐covered days) was the key predictor of soil microclimate. Topography and moisture explained little variation in the measured temperatures. Our results not only underline the close connection of vegetation and snow with microclimate in the Arctic tundra but also point to the need for more studies disentangling their complex interplay across tundra environments and seasons. Future shifts in vegetation cover and height will likely mediate the impact of atmospheric warming on the tundra soil environment, with potential implications for below‐ground organisms and ecosystem functioning. [ABSTRACT FROM AUTHOR]

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species‐specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing. Plain Language Summary: Biodiversity monitoring based on field data is almost inconceivable at the scale of the entire Earth. Over the past decades, remote sensing has opened possibilities for Earth observation from air and space, allowing us to monitor ecological change, primarily expressed by changes in vegetation cover, distribution, and functioning, which can be subsequently linked to drivers of change in space and time, from local to global scale. Recently, the spectral species concept—an algorithm that clusterizes pixels from spectral images having a similar spectral signal (referred to as 'spectral species')—has brought attention. The aim of this paper is to review the ecological functioning principles of the spectral species concept and to refine its definition by a better linkage with field observations of plant species distribution data (i.e., presence‐absence data) available from vegetation surveys. Key Points: Remote sensing has opened possibilities for Earth observation from air and space, allowing us to monitor ecological changeBiodiversity monitoring based on field data is almost inconceivable at the scale of the entire EarthThe spectral species concept, relating field to remotely sensed data, can open new ways to measure diversity from space [ABSTRACT FROM AUTHOR]

Aim: Improving species distribution models (SDMs) and species abundance models (SAMs) of woody shrubs is critical for predicting biodiversity changes in the Arctic, which is experiencing especially high warming rates. Yet, it remains relatively unexplored if SDMs and SAMs can explain local scale patterns. We aim to identify predictor differences for the distribution versus abundance of two widespread Arctic shrub species with high resolution models and to compare validation approaches to assess the models' predictive abilities. Location: Nuup Kangerlua (NK) and Kangerluarsunnguaq (K), two adjacent fjords in Southwest Greenland. Methods: We conducted two separate field surveys in either fjord to construct high resolution (~90 m) SDMs and SAMs for Betula nana and Salix glauca, analysing the predictive influences of local scale climate, topography and soil moisture indicators. We then alternatively trained and validated models in either NK or K fjord and compared these results with the common split‐sample validation approach. Finally, we assessed if including local scale biotic predictors improves SAM performance. Results: Temperature extremes and precipitation best predicted the distributions of both species, whereas insolation and soil moisture indicators best predicted abundances. Compared to split‐sample validation, both SDM and SAM performance was substantially reduced with separate survey validation. Regardless of validation approach, models performed poor to moderately well, and including local scale biotic parameters improved SAM performance. Main conclusions: Substantial differences in model performance between validation approaches highlight the usefulness of using a separate survey for validating model predictive performance. We discuss various factors that might have caused poor model performance, such as not capturing all relevant predictors or enough local scale heterogeneity in predictor or response variables. We emphasise the need to include predictors relevant at the spatial scale of study, such as local scale biotic interactions, for improved predictions at high spatial resolution. [ABSTRACT FROM AUTHOR]

Background: The Arctic tundra is subject to the greatest climate change-induced temperature rises of any biome. Both terrestrial and freshwater biota are responding to recent climate warming through variability in their distribution, abundance, and richness. However, uncertainty arises within models of future change when considering processes that operate over centennial timescales. A systematic evidence synthesis of centennial-scale variability in biodiversity does not currently exist for the Arctic biome. Here, we sought to address the primary research question: what evidence exists for temporal variability in Arctic terrestrial and freshwater biodiversity throughout the Holocene (11,650 years before present (yBP)—0yBP)? Methods: Consultation with stakeholders informed key definitions, scoping and the appropriateness of the research question. The research question was structured using a PECO framework—Arctic biota (P), a timestamped year in the Holocene (E), another year in the Holocene (C), and the dimensions of biodiversity that have been measured (O)—to inform the search strategy. Search strings were benchmarked against a test list of 100 known sources to ensure a specific and comprehensive return of literature. Searches will occur across 13 bibliographic databases. The eligibility criteria specify that sources must: (a) use 'proxy' methods to measure biodiversity; (b) fall within the spatial extent of the contemporary Arctic tundra biome; and (c) consist of a time-series that overlaps with 11,650yBP to 0yBP (1950AD). Information coded from studies will include proxy-specific information to account for both temporal uncertainty (i.e., the characteristics of age-depth models and dating methods) and taxonomic uncertainty (i.e., the samples and processes used for taxonomic identification). We will assess temporal uncertainty within each source by determining the quality of dating methods and measures; this information will be used to harmonise dates onto the IntCal20 calibration curve and determine the available temporal resolution and extent of evidence through space. Key outputs of this systematic map will be: (1) a graph database containing the spatial–temporal properties of each study dataset with taxonomic harmonisation; and (2) a geographical map of the evidence base. [ABSTRACT FROM AUTHOR]

The combined effects of climate change and nutrient availability on Arctic vegetation growth are poorly understood. Archaeological sites in the Arctic could represent unique nutrient hotspots for studying the long-term effect of nutrient enrichment. In this study, we analysed a time-series of ring widths of Salix glauca L. collected at nine archaeological sites and in their natural surroundings along a climate gradient in the Nuuk fjord region, Southwest Greenland, stretching from the edge of the Greenlandic Ice Sheet in the east to the open sea in the west. We assessed the temperature-growth relationship for the last four decades distinguishing between soils with past anthropogenic nutrient enrichment (PANE) and without (controls). Along the East–West gradient, the inner fjord sites showed a stronger temperature signal compared to the outermost ones. Individuals growing in PANE soils had wider ring widths than individuals growing in the control soils and a stronger climate-growth relation, especially in the inner fjord sites. Thereby, the individuals growing on the archaeological sites seem to have benefited more from the climate warming in recent decades. Our results suggest that higher nutrient availability due to past human activities plays a role in Arctic vegetation growth and should be considered when assessing both the future impact of plants on archaeological sites and the general greening in landscapes with contrasting nutrient availability. [ABSTRACT FROM AUTHOR]

Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as light detection and ranging (lidar). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote sensing knowledge. We processed Denmark's publicly available national airborne laser scanning (ALS) data set acquired in 2014/15, together with the accompanying elevation model, to compute 70 rasterised descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than 40 000 km 2 covering almost all of Denmark's terrestrial surface. The resulting data set is comparatively small (∼94 GB, compressed 16.8 GB), and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark's national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterised data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond. The full data set is available on Zenodo: 10.5281/zenodo.4756556 (Assmann et al., 2021); a 5 MB teaser subset is also available: 10.5281/zenodo.6035188 (Assmann et al., 2022a). [ABSTRACT FROM AUTHOR]

High resolution, downscaled climate model data are used in a wide variety of applications across environmental sciences. Here we introduce the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100-year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm. The data were validated by comparisons with the glacial extent of the Laurentide ice shield based on expert delineations, proxy data from Greenland ice cores, historical climate data from meteorological stations, and a dynamic simulation of species distribution throughout the Holocene. Validations show that CHELSA TraCE21k output creates a reasonable representation of the distribution of temperature and precipitation through time at a high spatial resolution, and simulations based on the data are capable of detecting effective LGM refugia of species. [ABSTRACT FROM AUTHOR]

Questions: Shrub vegetation has been expanding across much of the rapidly changing Arctic. Yet, there is still uncertainty about the underlying drivers of shrub community composition. Here, we use extensive vegetation surveys and a trait-based approach to answer the following questions: which abiotic and biotic factors explain abundance of shrub species and functional groups in the Arctic tundra, and can we interpret these relationships using plant traits related to resource acquisition? Location: Nuup Kangerlua (Godthåbsfjord), western Greenland. Methods: We tested the power of nine climatic, topographic and biotic variables to explain the abundances of nine shrub species using a Bayesian hierarchical modelling framework. Results: We found highly variable responses among species and functional groups to both abiotic and biotic environmental variation. The overall most important abiotic explanatory variable was annual air temperature variability, which was highly correlated with winter minimum air temperature. Functional community composition and graminoid abundance were the most influential biotic factors. While we did not find systematic patterns between shrub abundances and abiotic variables with regard to resource acquisition traits, these traits did explain relationships between shrub abundances and biotic variables. Conclusions: Shrub abundance responses to abiotic variables rarely aligned with expectations based on plants’ resource acquisition traits or functional groups. Our results, therefore, indicate that approaches exclusively based on resource acquisition traits might be limited in their ability to predict abundances of individual groups and species, particularly in response to complex abiotic environments. However, integrating community theory and functional trait concepts represents a promising pathway to better predict biotic interactions and ultimately responses of dominant shrub vegetation to rapid environmental changes across the arctic tundra biome. [ABSTRACT FROM AUTHOR]

Shrub encroachment in seminatural grasslands threatens local biodiversity unless management is applied to reduce shrub density. Dense vegetation of Cytisus scoparius homogenizes the landscape negatively affecting local plant diversity. Detecting structural change (e.g., biomass) is essential for assessing negative impacts of encroachment. Hence, exploring new monitoring tools to achieve this task is important for effectively capturing change and evaluating management activities.This study combines traditional field‐based measurements with novel Light Detection and Ranging (LiDAR) observations from an Unmanned Aircraft System (UAS). We investigate the accuracy of mapping C. scoparius in three dimensions (3D) and of structural change metrics (i.e., biomass) derived from ultrahigh‐density point cloud data (>1,000 pts/m2). Presence–absence of 12 shrub or tree genera was recorded across a 6.7 ha seminatural grassland area in Denmark. Furthermore, 10 individuals of C. scoparius were harvested for biomass measurements. With a UAS LiDAR system, we collected ultrahigh‐density spatial data across the area in October 2017 (leaf‐on) and April 2018 (leaf‐off). We utilized a 3D point‐based classification to distinguish shrub genera based on their structural appearance (i.e., density, light penetration, and surface roughness).From the identified C. scoparius individuals, we related different volume metrics (mean, max, and range) to measured biomass and quantified spatial variation in biomass change from 2017 to 2018. We obtained overall classification accuracies above 86% from point clouds of both seasons. Maximum volume explained 77.4% of the variation in biomass.The spatial patterns revealed landscape‐scale variation in biomass change between autumn 2017 and spring 2018, with a notable decrease in some areas. Further studies are needed to disentangle the causes of the observed decrease, for example, recent winter grazing and/or frost events.Synthesis and applications: We present a workflow for processing ultrahigh‐density spatial data obtained from a UAS LiDAR system to detect change in C. scoparius. We demonstrate that UAS LiDAR is a promising tool to map and monitor grassland shrub dynamics at the landscape scale with the accuracy needed for effective nature management. It is a new tool for standardized and nonbiased evaluation of management activities initiated to prevent shrub encroachment. [ABSTRACT FROM AUTHOR]

Changes in Arctic vegetation can have important implications for trophic interactions and ecosystem functioning leading to climate feedbacks. Plot-based vegetation surveys provide detailed insight into vegetation changes at sites around the Arctic and improve our ability to predict the impacts of environmental change on tundra ecosystems. Here, we review studies of changes in plant community composition and phenology from both long-term monitoring and warming experiments in Arctic environments. We find that Arctic plant communities and species are generally sensitive to warming, but trends over a period of time are heterogeneous and complex and do not always mirror expectations based on responses to experimental manipulations. Our findings highlight the need for more geographically widespread, integrated, and comprehensive monitoring efforts that can better resolve the interacting effects of warming and other local and regional ecological factors. [ABSTRACT FROM AUTHOR]

Aim: Tundra ecosystems are highly vulnerable to climate change, and climate–growth responses of Arctic shrubs are variable and altered by microsite environmental conditions and biotic factors. With warming and drought during the growing season, insect‐driven defoliation is expected to increase in frequency and severity with potential broad‐scale impacts on tundra ecosystem functioning. Here we provide the first broad‐scale reconstruction of spatio‐temporal dynamics of past insect outbreaks by assessing their effects on shrub growth along a typical Greenlandic fjord climate gradient from the inland ice to the sea. Location: Nuuk Fjord (64°30′N/51°23′W) and adjacent areas, West Greenland. Taxa: Great brocade (Eurois occulta L.) and grey willow (Salix glauca L.). Methods: We combined dendro‐anatomical and remote sensing analyses. Time series of ring width (RW) and wood‐anatomical traits were obtained from chronologies of >40 years established from 153 individuals of S. glauca collected at nine sites. We detected anomalies in satellite‐based Normalized Difference Vegetation Index (NDVI) related to defoliation and reconstructed past changes in photosynthetic activity across the region. Results: We identified outbreaks as distinctive years with reduced RW, cell‐wall thickness and vessel size, without being directly related to climate but matching with years of parallel reduction in NDVI. The two subsequent years after the defoliation showed a significant increase in RW. The reconstructed spatio‐temporal dynamics of these events indicate substantial regional variation in outbreak intensity linked to the climate variability across the fjord system. Main conclusions: Our results highlight the ability of S. glauca to cope with severe insect defoliation by changing carbon investment and xylem conductivity leading to high resilience and rapid recovery after the disturbance. Our multiproxy approach allows us to pinpoint biotic drivers of narrow ring formation and to provide new broad‐scale insight on the C‐budget and vegetation productivity of shrub communities in a widespread arctic ecosystem. [ABSTRACT FROM AUTHOR]

Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this "Big Data" trend, with a strong rise in the volume of data that we are using for our research. Here, we summarize the most recent developments in macroecology in the age of Big Data that were presented at the 2018 annual meeting of the Specialist Group Macroecology of the Ecological Society of Germany, Austria and Switzerland (GfÖ). Supported by computational advances, macroecology has been a rapidly developing field over recent years. Our meeting highlighted important avenues for further progress in terms of standardized data collection, data integration, method development and process integration. In particular, we focus on (a) important data gaps and new initiatives to close them, for example through space‐ and airborne sensors, (b) how various data sources and types can be integrated, (c) how uncertainty can be assessed in data‐driven analyses and (d) how Big Data and machine learning approaches have opened new ways of investigating processes rather than simply describing patterns. We discuss how Big Data opens up new opportunities, but also poses new challenges to macroecological research. In the future, it will be essential to carefully assess data quality, the reproducibility of data compilation and analytical methods, and the communication of uncertainties. Major progress in the field will depend on the definition of data standards and workflows for macroecology, such that scientific quality and integrity are guaranteed, and collaboration in research projects is made easier. [ABSTRACT FROM AUTHOR]

Aim: Theory suggests that increasing productivity and climate stability towards the tropics favours specialization, thus contributing to the latitudinal richness gradient. A positive relationship between species richness and specialization should therefore emerge as a fundamental biogeographical pattern. However, land‐use and climate changes disproportionally increase the local extirpation risk for specialists, potentially weakening the relationship between richness and specialization. Here, we quantify empirically the richness–specialization prediction and test how 50 years of climate and land‐use change has affected the richness–specialization relationship. Location: USA. Time period: 1966–2015. Major taxa studied: Birds. Methods: We used the North American Breeding Bird Survey to quantify bird community richness and specialization to habitat and climate. We (a) quantify temporal change in the slope of the richness–specialization relationship, using a generalized mixed model; (b) assess how this change translates spatially, using generalized additive models; and (c) attribute spatio‐temporal change in the richness–specialization relationship to land use, climate and topographic drivers. Results: We found evidence for a positive but weak richness–specialization relationship in bird communities that greatly weakened over time. Given that specialization was not the main driver of richness, this relationship did not translate spatially into a linear spatial covariation between richness and specialization. Instead, the spatial covariation in richness and specialization followed a unimodal pattern, the peak of which shifted towards less specialized communities over time. These temporal changes were associated with precipitation change, decreasing temperature stability and land use. Main conclusions: Recent climate and land‐use changes have induced two contrasting types of community responses. In human‐dominated areas, the decoupling of richness and specialization drove a general trend for biotic homogenization. In areas of low human impact experiencing increasing climate harshness, specialization increased, whereas richness decreased. Our results offer new support for specialization as a key driver of macroecological diversity patterns and show that global changes are weakening this fundamental macroecological pattern. [ABSTRACT FROM AUTHOR]

Aims: Phylogenetic endemism describes the extent to which unique phylogenetic lineages are constrained to restricted geographic areas. Previous studies indicate that species endemism is related to both past and modern climate, but studies of phylogenetic endemism are relatively rare and mainly focused on smaller regions. Here, we provide the first assessment of the patterns of species and phylogenetic endemism in angiosperm trees across the Northern Hemisphere as well as the relative importance of modern climate and glacial–interglacial climate change as drivers of these patterns. Location: Northern Hemisphere. Major taxa: Angiosperm trees. Methods: Using tree assemblages at the scale of 100 km × 100 km grid cells and simultaneous autoregressive (SAR) models, we assessed the relationships between species endemism, phylogenetic endemism and modern climate variables, Last Glacial Maximum (LGM) to present temperature velocity. Results: Species and phylogenetic endemism were associated with both modern climate and glacial–interglacial climate change, with higher values in areas with stable historical climate and warmer and wetter modern conditions. Notably, the multivariate SAR analyses showed that the combinations of variables with highest Akaike's information criterion (AIC) weight always included both LGM–present climate instability and modern climate, that is, modern precipitation and temperature. Main conclusions: Our results show that high phylogenetic endemism is partially dependent on long‐term climate stability, highlighting the threat posed by future climate changes to the preservation of rare, phylogenetically distinct lineages of trees. [ABSTRACT FROM AUTHOR]

Mapping changes in vegetation cover is essential for understanding the consequences of climate change on Arctic ecosystems. Classification of ultra-high spatial-resolution (UHR, < 1 cm) imagery can provide estimates of vegetation cover across space and time. The challenge of this approach is to assure comparability of classification across many images taken at different illumination conditions and locations. With warming, vegetation at higher elevation is expected to resemble current vegetation at lower elevation. To investigate the value of classification of UHR imagery for monitoring vegetation change, we collected visible and near-infrared images from 108 plots with hand-held cameras along an altitudinal gradient in Greenland and examined the classification accuracy of shrub cover on independent images (i.e. classification transferability). We implemented several models to examine if colour calibration improves transferability based on an in-image calibration target. The classifier was trained on different number of images to find the minimum training subset size. With a training set of ~ 20% of the images the overall accuracy levelled off at about 81% and 68% on the non-calibrated training and validation images, respectively. Colour calibration improved the accuracy on training images (1–4%) while it only improved the classifier transferability significantly for training sets < 20%. Linear calibration only based on the target's grey series improved transferability most. Reasonable transferability of Arctic shrub cover classification can be obtained based only on spectral data and about 20% of all images. This is promising for vegetation monitoring through multi-image classification of UHR imagery acquired with hand-held cameras or Unmanned Aerial Systems. [ABSTRACT FROM AUTHOR]

The satellite record has revealed substantial land surface "greening" in the northern hemisphere over recent decades. Process‐based Earth system models (ESMs) attribute enhanced vegetation productivity (greening) to CO2 fertilisation. However, the models poorly reproduce observed spatial patterns of greening, suggesting that they ignore crucial processes. Here, we explore whether fine‐scale land cover dynamics, as modified by ecological and land‐use processes, can explain the discrepancy between models and satellite‐based estimates of greening. We used 500 m satellite‐derived Leaf Area Index (LAI) to quantify greening. We focus on semi‐natural vegetation in Europe, and distinguish between conservation areas and unprotected land. Within these ecological and land‐use categories, we then explored the relationships between vegetation change and major climatic gradients. Despite the relatively short time‐series (15 years), we found a strong overall increase in LAI (i.e., greening) across all European semi‐natural vegetation types. The spatial pattern of vegetation change identifies land‐use change, particularly land abandonment, as a major initiator of vegetation change both in‐ and outside of protected areas. The strongest LAI increases were observed in mild climates, consistent with more vigorous woody regrowth after cessation of intensive management in these environments. Surprisingly, rates of vegetation change within protected areas did not differ significantly from unprotected semi‐natural vegetation. Overall, the detected LAI increases are consistent with previous, coarser‐scale, studies. The evidence indicates that woody regrowth following land abandonment is an important driver of land surface greening throughout Europe. The results offer an explanation for the large discrepancies between ESM‐derived and satellite‐derived greening estimates and thus generate new avenues for improving the ESMs on which we rely for crucial climate forecasts. The satellite record revealed substantial land surface "greening" in the northern hemisphere over recent decades, but process‐based Earth system models (ESMs) poorly reproduce observed spatial patterns of greening. Here, we show strong greening over Europe during the past 15 years. The spatial patterns of vegetation change indicate that woody regrowth following land abandonment is an important driver of land surface greening throughout Europe. The results offer an explanation for the large discrepancies between ESM‐derived and satellite‐derived greening estimates, and thus generate new avenues for improving the ESMs on which we rely for crucial climate forecasts. [ABSTRACT FROM AUTHOR]

Motivation: The Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub‐Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release. [ABSTRACT FROM AUTHOR]

The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming. Analyses of the relationships between temperature, moisture and seven key plant functional traits across the tundra and over time show that community height increased with warming across all sites, whereas other traits lagged behind predicted rates of change. [ABSTRACT FROM AUTHOR]

Arctic plant communities are altered by climate changes. The magnitude of these alterations depends on whether species distributions are determined by macroclimatic conditions, by factors related to local topography, or by biotic interactions. Our current understanding of the relative importance of these conditions is limited due to the scarcity of studies, especially in the High Arctic. We investigated variations in vascular plant community composition and species richness based on 288 plots distributed on three sites along a coast-inland gradient in Northeast Greenland using a stratified random design. We used an information theoretic approach to determine whether variations in species richness were best explained by macroclimate, by factors related to local topography (including soil water) or by plant-plant interactions. Latent variable models were used to explain patterns in plant community composition. Species richness was mainly determined by variations in soil water content, which explained 35% of the variation, and to a minor degree by other variables related to topography. Species richness was not directly related to macroclimate. Latent variable models showed that 23.0% of the variation in community composition was explained by variables related to topography, while distance to the inland ice explained an additional 6.4 %. This indicates that some species are associated with environmental conditions found in only some parts of the coast-inland gradient. Inclusion of macroclimatic variation increased the model's explanatory power by 4.2%. Our results suggest that the main impact of climate changes in the High Arctic will be mediated by their influence on local soil water conditions. Increasing temperatures are likely to cause higher evaporation rates and alter the distribution of late-melting snow patches. This will have little impact on landscape-scale diversity if plants are able to redistribute locally to remain in areas with sufficient soil water. [ABSTRACT FROM AUTHOR]

Recent changes in arctic vegetation might not be driven by climate change alone. Legacies of human activities have received little attention as a contributing factor. We examine the extent to which traditional human activities (hunting, herding, fire, wood extraction, and agriculture) have had lasting effects on arctic woody plant communities and therefore might continue to affect biome-wide responses to climate change. Evidence suggests that legacies are likely to be evident across meters to hundreds of kilometers and for decades, centuries, and millennia. The evidence, however, is currently sparse, and we highlight the potential to develop systematic assessments through a circumarctic collaboratory consisting of a network of interdisciplinary field sites, standardized protocols, participatory research, and new approaches. We suggest that human activities should be brought into consideration to increase our understanding of arctic vegetation dynamics in general and to assess woody plant responses to climate change in particular. [ABSTRACT FROM AUTHOR]

Aims Long-term climate stability is hypothesized to drive the emergence of species assemblages with large species age differences due to the accumulation of relict species and relatively newly arisen species via reduced extinction and increased speciation. Few studies have addressed these predictions and so far no study has done so for plants across the Northern Hemisphere. Here, we linked Quaternary-scale climate variability to phylogenetic age differences between the oldest and youngest group of species in tree assemblages in 100 km × 100 km grid cells across the Northern Hemisphere to test these predictions. Location Northern Hemisphere. Methods Last Glacial Maximum (LGM)-to-present shifts in temperature and precipitation were used as proxies for Quaternary-scale glacial-interglacial climate variability. Simultaneous autoregressive (SAR) models were used to assess the relationships between phylogenetic age differences and Quaternary-scale climate variability. Results We found that phylogenetic age differences overall were largest in China and smallest in Europe, and they declined with increasing temperature instability as predicted, but only in Europe and North America. In China, the relatively mild Quaternary climate changes did not appear to have strongly affected phylogenetic age differences in tree assemblages. Main conclusions Our results show that phylogenetically diverse assemblages with large phylogenetic age differences among species are associated with relatively high long-term climate stability, with intra-regional links between long-term climate variability and phylogenetic composition especially strong in the more unstable regions. These findings point to future climate change as a key risk to the preservation of the phylogenetically diverse assemblages in regions characterized by relatively high paleoclimate stability, with China as a key example. [ABSTRACT FROM AUTHOR]

Climate change has been reported to affect shrub growth positively at several sites at high northern latitudes, including several arctic environments. The observed growth rates are, however, not uniform in space and time, and the mechanistic drivers of these patterns remain poorly understood. Here we investigated spatio-temporal interactions between climatic conditions, xylem anatomical traits, and annual growth of 21 Betula nana L. individuals from western Greenland for the period 2001-2011. Structural equation modeling showed that summer precipitation and winter temperature are affecting annual growth positively. Furthermore, vessel lumen area and vessel grouping, which are related to water conductivity and hydraulic connectivity of the xylem, respectively, positively influenced annual growth. To optimize growth B. nana was thus able to adjust its water transporting system. Annual variation in vessel lumen area seemed to be driven mostly by spring and summer temperatures, whereas annual variation in vessel grouping was driven by winter temperature. Linear models did not reveal a pattern in the spatial variation of xylem anatomical traits across the sampled climatic gradient. However, growth was positively correlated with local variation in insolation. Our results suggest that B. nana can adjust its hydraulic capacity to annual fluctuations in climatic conditions in order to optimize its total radial stem growth rate. [ABSTRACT FROM AUTHOR]

Whether non-arctic species persisted in northern Europe during the Last Glacial Maximum (LGM) is highly debated. Until now, the debate has mostly focused on plants, with little consideration for other groups of organisms, e.g. the numerous plant-dependent insect species. Here, we study the late-Quaternary evolution of the European range of a boreo-montane leaf beetle, Gonioctena intermedia, which feeds exclusively on the boreal and temperate trees Prunus padus and Sorbus aucuparia. Using species distribution models, we estimated the congruence between areas of past and present suitable climate for this beetle and its host plants. Then we derived historical hypotheses from the congruent range estimates and evaluated their compatibility with observed DNA sequence variation at five independent loci. We investigated compatibility using computer simulations of population evolution under various coalescence models. We find strong evidence for range modifications in response to late-Quaternary climate changes, and support for the presence of populations of G. intermedia in northern Europe since the beginning of the last glaciation. The presence of a co-dependent insect in the region through the LGM provides new evidence supporting the glacial survival of cold-tolerant tree species in northern Europe. [ABSTRACT FROM AUTHOR]

Aim Mapping the distribution and diversity of plant functional traits is critical for projecting future changes to vegetation under global change. Maps of plant functional traits, however, are scarce due very sparse global trait data matrices. A potential solution to this data limitation is to utilize the known levels of phylogenetic signal in trait data to predict missing values. Here we aim to test existing phylogenetic comparative methods for imputing missing trait data for the purpose of producing continental-scale maps of plant functional traits. Location North America and Europe. Methods Phylogenetic imputation models and trait data from one continent were used to predict the trait values for tree species on the other continent and to produce trait maps. Predicted maps of trait means, variances and functional diversity were compared with known maps to quantify the degree to which predicted trait values could estimate spatial patterns of trait distributions and diversity. Results We show that the phylogenetic signal in plant functional trait data can be used to provide robust predictions of the geographical distribution of tree functional diversity. However, predictions for traits with little phylogenetic signal, such as maximum height, are error prone. Lastly, trait imputation methods based on phylogenetic generalized least squares tended to outperform those based on phylogenetic eigenvectors. Main conclusions It is possible to predict patterns of functional diversity across continental settings with novel species assemblages for most of the traits studied for which we have no direct trait information, thereby offering an effective method for overcoming a key data limitation in global change biology, macroecology and ecosystem modelling. [ABSTRACT FROM AUTHOR]

Arthropods form a major part of the terrestrial species diversity in the Arctic, and are particularly sensitive to temporal changes in the abiotic environment. It is assumed that most Arctic arthropods are habitat generalists and that their diversity patterns exhibit low spatial variation. The empirical basis for this assumption, however, is weak. We examine the degree of spatial variation in species diversity and assemblage structure among five habitat types at two sites of similar abiotic conditions and plant species composition in southwest Greenland, using standardized field collection methods for spiders, beetles and butterflies. We employed non-metric multidimensional scaling, species richness estimation, community dissimilarity and indicator species analysis to test for local (within site)- and regional (between site)-scale differences in arthropod communities. To identify specific drivers of local arthropod assemblages, we used a combination of ordination techniques and linear regression. Species richness and the species pool differed between sites, with the latter indicating high species turnover. Local-scale assemblage patterns were related to soil moisture and temperature. We conclude that Arctic arthropod species assemblages vary substantially over short distances due to local soil characteristics, while regional variation in the species pool is likely influenced by geographic barriers, i.e., inland ice sheet, glaciers, mountains and large water bodies. In order to predict future changes to Arctic arthropod diversity, further efforts are needed to disentangle contemporary drivers of diversity at multiple spatial scales. [ABSTRACT FROM AUTHOR]

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. [ABSTRACT FROM AUTHOR]

The relationship between large-scale gradients in species richness and functional diversity provides important information regarding the mechanisms driving patterns of biodiversity. A classic hypothesis in ecology is that strong interspecific interactions should result in an increase in the functional volume of assemblages as the species richness increases, whereas climatic constraints may result in no change in functional volume. Most research of this kind examines latitudinal gradients in species richness, but the results are likely confounded by underlying gradients in climate and phylogenetic composition. We take an alternative approach that examines functional richness across a tree species richness anomaly where species richness doubles from Europe to eastern North America. The results demonstrate that the functional richness on both continents saturates at a similar point as species richness increases and that the packing of functional space becomes tighter. Further, the species richness anomaly is driven primarily by genera unique to North America, but those genera contribute less than expected functional richness to the region, indicating a high level of redundancy with genera shared between the continents. Taken together, the results indicate that the species richness anomaly is associated with diversification within a climatically constrained trait space. More generally, the work demonstrates the power of utilizing species richness anomalies in biodiversity research, particularly when they are coupled with information regarding organismal function. [ABSTRACT FROM AUTHOR]

Aim High intra-specific genetic diversity is necessary for species adaptation to novel environments under climate change, but species tracking suitable conditions are losing alleles through successive founder events during range shift. Here, we investigated the relationship between range shift since the Last Glacial Maximum ( LGM) and extant population genetic diversity across multiple plant species to understand variability in species responses. Location The circumpolar Arctic and northern temperate alpine ranges. Methods We estimated the climatic niches of 30 cold-adapted plant species using range maps coupled with species distribution models and hindcasted species suitable areas to reconstructions of the mid-Holocene and LGM climates. We computed the species-specific migration distances from the species glacial refugia to their current distribution and correlated distances to extant genetic diversity in 1295 populations. Differential responses among species were related to life-history traits. Results We found a negative association between inferred migration distances from refugia and genetic diversities in 25 species, but only 11 had statistically significant negative slopes. The relationships between inferred distance and population genetic diversity were steeper for insect-pollinated species than wind-pollinated species, but the difference among pollination system was marginally independent from phylogenetic autocorrelation. Main conclusion The relationships between inferred migration distances and genetic diversities in 11 species, independent from current isolation, indicate that past range shifts were associated with a genetic bottleneck effect with an average of 21% loss of genetic diversity per 1000 km−1. In contrast, the absence of relationship in many species also indicates that the response is species specific and may be modulated by plant pollination strategies or result from more complex historical contingencies than those modelled here. [ABSTRACT FROM AUTHOR]

Earth's climate has experienced strong changes on timescales ranging from decades to millions of years. As biodiversity has evolved under these circumstances, dependence on these climate dynamics is expected. In this review, we assess the current state of knowledge on paleoclimatic legacies in biodiversity and ecosystem patterns. Paleoclimate has had strong impacts on past biodiversity dynamics, driving range shifts and extinctions as well as diversification. We outline theory for how these dynamics may have left legacies in contemporary patterns and review the empirical evidence. We report ample evidence that Quaternary glacial-interglacial climate change affects current patterns of species distributions and diversity across a broad range of organisms and regions. We also report emerging evidence for paleoclimate effects on current patterns in phylogenetic and functional diversity and ecosystem functioning and for legacies of deeper-time paleoclimate conditions. Finally, we discuss implications for Anthropocene ecology and outline an agenda to improve our understanding of paleoclimate's role in shaping contemporary biodiversity and ecosystems. [ABSTRACT FROM AUTHOR]

The effects of climate change on Arctic ecosystems can range between various spatiotemporal scales and may include shifts in population distribution, community composition, plant phenology, primary productivity and species biodiversity. The growth rates and age structure of tundra vegetation as well as its response to temperature variation, however, remain poorly understood because high-resolution data are limited in space and time., Anatomical and morphological stem characteristics were recorded to assess the growth behaviour and age structure of 871 dwarf shrubs from 10 species at 30 sites in coastal East Greenland at ˜70°N. Recruitment pulses were linked with changes in mean annual and summer temperature back to the 19th century, and a literature review was conducted to place our findings in a pan-Arctic context., Low cambial activity translates into estimated average/maximum plant ages of 59/204 years, suggesting relatively small turnover rates and stable community composition. Decade-long changes in the recruitment intensity were found to lag temperature variability by 2 and 6 years during warmer and colder periods, respectively ( r = 0.851961-2000 and 1881-1920)., Synthesis. Our results reveal a strong temperature dependency of Arctic dwarf shrub reproduction, a high vulnerability of circumpolar tundra ecosystems to climatic changes, and the ability of evaluating historical vegetation dynamics well beyond the northern treeline. The combined wood anatomical and plant ecological approach, considering insights from micro-sections to community assemblages, indicates that model predictions of rapid tundra expansion (i.e. shrub growth) following intense warming might underestimate plant longevity and persistence but overestimate the sensitivity and reaction time of Arctic vegetation. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges. [ABSTRACT FROM AUTHOR]

Detecting the legacy of time-lagged migration in species ranges is an urgent matter for understanding range dynamics. KISSMig is a simple migration model which generates maps of accessibility from areas of origin and allows the generation and testing of hypotheses about the influence of specific spread patterns on species distributions. KISSMig has important applications: 1) uncovering the influence of limited migration relative to other drivers, 2) detecting areas of origin and their importance as sources of migration, and 3) accounting for limited migration in modeling species distributions. Here we introduce KISSMig and use the oak species Quercus cerris to illustrate these applications. [ABSTRACT FROM AUTHOR]

Ongoing and predicted global change makes understanding and predicting species' range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species. [ABSTRACT FROM AUTHOR]

Warming-induced expansion of trees and shrubs into tundra vegetation will strongly impact Arctic ecosystems. Today, a small subset of the boreal woody flora found during certain Plio-Pleistocene warm periods inhabits Greenland. Whether the twenty-first century warming will induce a re-colonization of a rich woody flora depends on the roles of climate and migration limitations in shaping species ranges. Using potential treeline and climatic niche modelling, we project shifts in areas climatically suitable for tree growth and 56 Greenlandic, North American and European tree and shrub species from the Last Glacial Maximum through the present and into the future. In combination with observed tree plantings, our modelling highlights that a majority of the non-native species find climatically suitable conditions in certain parts of Greenland today, even in areas harbouring no native trees. Analyses of analogous climates indicate that these conditions are widespread outside Greenland, thus increasing the likelihood of woody invasions. Nonetheless, we find a substantial migration lag for Greenland's current and future woody flora. In conclusion, the projected climatic scope for future expansions is strongly limited by dispersal, soil development and other disequilibrium dynamics, with plantings and unintentional seed dispersal by humans having potentially large impacts on spread rates. [ABSTRACT FROM AUTHOR]

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: ( i) integrating pairwise dependencies, ( ii) using integrative predictors, and ( iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim To identify potential source and sink locations for climate-driven species range shifts in Europe since the Last Glacial Maximum (LGM). Location Europe. Methods We developed a new approach combining past-climate simulations with the concept of analogous climate space. Our index gives a continuous measure of the potential of a location to have acted as a source or a sink for species that have shifted their ranges since the LGM. High glacial source potential is indicated by LGM climatic conditions that are widespread now; high post-glacial sink potential is indicated by current climatic conditions that were widespread at the LGM. The degree of isolation of source and sink areas was calculated as the median distance to areas with analogous climate conditions. Results We identified areas of high glacial source potential in the previously recognized refugial areas in the southern European peninsulas, but also in large areas in central-western Europe. The most climatically isolated source areas were located in northern Spain, in north-western Europe and in eastern Turkey. From here species would have had to cover substantial distances to find current climate conditions analogous to LGM conditions of these areas. Areas with high post-glacial sink potential were mainly located in Fennoscandia and in central and south-eastern Europe. Some of the most isolated sink areas were located in the Spanish highlands and around the Baltic Sea. Main conclusions Our species-independent approach successfully identified previously recognized glacial refugial areas with high source potential for species range shifts in southern Europe and in addition highlighted other potential source areas in central Europe. This study offers new insights into how the distribution of past and current climatic conditions may have influenced past species range shifts and current large-scale biodiversity patterns. [ABSTRACT FROM AUTHOR]