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International audience; This article was submitted without an abstract, please refer to the full-text PDF file.

Aim: Climate change impacts on biota are variable across sites, among species and throughout individual species' ranges. Niche theory predicts that population performance should decline as site climate becomes increasingly different from the species' climate niche centre, though studies find significant variation from these predictions. Here, we propose that predictions about climate responses can be improved by incorporating species' trait information. Location: Europe. Methods: We used observations of plant species abundance change over time to assess variation in climate difference sensitivity (CDS), defined as how species performance (colonization, extinction and abundance change) relates to the difference of site climate from the mean temperature and precipitation of each species' range. We then investigated if leaf economics, plant size and seed mass traits were associated with the species' CDS. Results: Species that performed better (e.g. increased in abundance) towards sites progressively cooler than their niche centre were shorter and had more resource-acquisitive leaves (i.e. lower leaf dry matter content or LDMC) relative to species with zero or the opposite pattern of temperature difference sensitivity. This result supports the hypothesis that if sites cooler than niche centres are more stressful for a species, then shorter stature is advantageous compared with taller species. The LDMC result suggests the environment selects for more resource-acquisitive leaf strategies towards relatively cooler climates with shorter growing seasons, counter to expectations that conservative strategies would be favoured in such environments. We found few consistent relationships between precipitation difference sensitivities and traits. Main Conclusions: The results supported key a priori foundations on how trait-based plant strategies dictate species responses to climate variation away from their niche centre. Furthermore, plant height emerged as the most consistent trait that varied with species CDS, suggesting height will be key for theory development around species response to climate change. publishedVersion

As Open Science practices become more commonplace, there is a need for the next generation of scientists to be well versed in these aspects of scientific research. Yet, many training opportunities for early career researchers (ECRs) could better emphasize or integrate Open Science elements. Field courses provide opportunities for ECRs to apply theoretical knowledge, practice new methodological approaches, and gain an appreciation for the challenges of real‐life research, and could provide an excellent platform for integrating training in Open Science practices. Our recent experience, as primarily ECRs engaged in a field course interrupted by COVID‐19, led us to reflect on the potential to enhance learning outcomes in field courses by integrating Open Science practices and online learning components. Specifically, we highlight the opportunity for field courses to align teaching activities with the recent developments and trends in how we conduct research, including training in: publishing registered reports, collecting data using standardized methods, adopting high‐quality data documentation, managing data through reproducible workflows, and sharing and publishing data through appropriate channels. We also discuss how field courses can use online tools to optimize time in the field, develop open access resources, and cultivate collaborations. By integrating these elements, we suggest that the next generation of field courses will offer excellent arenas for participants to adopt Open Science practices., Open Science methodology is becoming an increasingly important goal of scientific research. Yet, our higher education system does not necessarily reflect these developments, even though such methods are beneficial for the advancement of early career researchers. Here we highlight how field courses can be a valuable resource for early career researchers and our learning of best practice in Open Science methodology, and how online workflows can support this process.

Open Science (OS) comprises a variety of practices and principles that are broadly intended to improve the quality and transparency of research, and the concept is gaining traction. Since OS has multiple facets and still lacks a unifying definition, it may be interpreted quite differently among practitioners. Moreover, successfully implementing OS broadly throughout science requires a better understanding of the conditions that facilitate or hinder OS engagement, and in particular, how practitioners learn OS in the first place. We addressed these issues by surveying OS practitioners that attended a workshop hosted by the Living Norway Ecological Data Network in 2020. The survey contained scaled-response and open-ended questions, allowing for a mixed-methods approach. Out of 128 registered participants we obtained survey responses from 60 individuals. Responses indicated usage and sharing of data and code, as well as open access publications, as the OS aspects most frequently engaged with. Men and those affiliated with academic institutions reported more frequent engagement with OS than women and those with other affiliations. When it came to learning OS practices, only a minority of respondents reported having encountered OS in their own formal education. Consistent with this, a majority of respondents viewed OS as less important in their teaching than in their research and supervision. Even so, many of the respondents’ suggestions for what would help or hinder individual OS engagement included more knowledge, guidelines, resource availability and social and structural support; indicating that formal instruction can facilitate individual OS engagement. We suggest that the time is ripe to incorporate OS in teaching and learning, as this can yield substantial benefits to OS practitioners, student learning, and ultimately, the objectives advanced by the OS movement.

Northern and southern hemispheric influences—particularly changes in Southern Hemisphere westerly winds (SSW) and Southern Ocean ventilation—triggered the stepwise atmospheric CO2increase that accompanied the last deglaciation. One approach for gaining potential insights into past changes in SWW/CO2upwelling is to reconstruct the positions of the northern oceanic fronts associated with the Antarctic Circumpolar Current. Using two deep-sea cores located ~600 km apart off the southern coast of Australia, we detail oceanic changes from ~23 to 6 ka using foraminifer faunal and biomarker alkenone records. Our results indicate a tight coupling between hydrographic and related frontal displacements offshore South Australia (and by analogy, possibly the entire Southern Ocean) and Northern Hemisphere (NH) climate that may help confirm previous hypotheses that the westerlies play a critical role in modulating CO2uptake and release from the Southern Ocean on millennial and potentially even centennial timescales. The intensity and extent of the northward displacements of the Subtropical Front following well-known NH cold events seem to decrease with progressing NH ice sheet deglaciation and parallel a weakening NH temperature response and amplitude of Intertropical Convergence Zone shifts. In addition, an exceptional poleward shift of Southern Hemisphere fronts occurs during the NH Heinrich Stadial 1. This event was likely facilitated by the NH ice maximum and acted as a coup-de-grâce for glacial ocean stratification and its high CO2capacitance. Thus, through its influence on the global atmosphere and on ocean mixing, “excessive” NH glaciation could have triggered its own demise by facilitating the destratification of the glacial ocean CO2state.

Estimating the distribution of phenotypes in populations and communities is central to many questions in ecology and evolutionary biology. These distributions can be characterized by their moments: the mean, variance, skewness, and kurtosis. Typically, these moments are calculated using a community-weighted approach (e.g. community-weighted mean) which ignores intraspecific variation. As an alternative, bootstrapping approaches can incorporate intraspecific variation to improve estimates, and also quantify uncertainty in the estimate. Here, we compare the performance of different approaches for estimating the moments of trait distributions across a variety of sampling scenarios, taxa, and datasets. We introduce the traitstrap R package to facilitate inferences of trait distributions via bootstrapping. Our results suggest that randomly sampling ~9 individuals per sampling unit and species, focusing on covering all species in the community, and analysing the data using nonparametric bootstrapping generally enables reliable inference on trait distributions, including the central moments, of communities.

Context-dependencies in species' responses to the same climate change frustrate attempts to generalize and make predictions based on experimental and observational approaches in biodiversity science. Here, we propose predictability may be enhanced by explicitly incorporating macroecological context into analyses of species' responses to climate manipulations. We combined vascular plant species' responses to an 8-year, 12-site turf transplant climate change experiment set in southwestern Norway with climate niche data from the observed 151 species. We used the difference between a species' mean climate across their range and climate conditions at the transplant site (“climate differences”) to predict colonization probability, extinction probability, and change in abundance of a species at a site. In analyses across species that ignore species-specific patterns, colonization success increased as species' distribution optima were increasingly warmer than the experimental target site. Extinction probability increased as species' distribution optima were increasingly colder than the target site. These patterns were reflected in change in abundance analyses. We found weak responses to increased precipitation in these oceanic climates. Climate differences were better predictors of species' responses to climate manipulations than range size. Interestingly, similar patterns were found when analyses focused on variation in species-specific responses across sites. These results provide an experimental underpinning to observational studies that report thermophilization of communities and suggest that space-for-time substitutions may be valid for predicting species' responses to climate warming, given other conditions are accounted for (e.g., soil nutrients). Finally, we suggest that this method of putting climate change experiments into macroecological context has the potential to generalize and predict species' responses to climate manipulations globally. publishedVersion

Future precipitation levels under a warming climate remain uncertain because current climate models have largely failed to reproduce observed variations in temperature-precipitation correlations. Our analyses of Holocene proxy-based temperature-precipitation correlations from 1647 Northern Hemisphere extratropical pollen records reveal a significant latitudinal dependence, temporal variations between the early, middle, and late Holocene, and differences between short and long timescales. These proxy-based variations are largely consistent with patterns obtained from transient climate simulations for the Holocene. Temperature-precipitation correlations increase from short to long time-scales. While high latitudes and subtropical monsoon areas show mainly stable positive correlations throughout the Holocene, the mid-latitude pattern is temporally and spatially more variable. In particular, we identified a reversal to negative temperature-precipitation correlations in the eastern North American and European mid-latitudes during the mid-Holocene that mainly related to slowed down westerlies and a switch to moisture-limited convection under a warm climate. We conclude that the effect of climate change on land areas is more complex than the commonly assumed “wetter climate in a warmer world”. Future predictions need to consider that warming related precipitation change is time-scale dependent.

In this letter we present comments on the article “A global-scale ecological niche model to predict SARS-CoV-2 coronavirus” by Coro published in 2020. AC is supported by NSF grant DBI-1565128.

Species distribution models are a powerful tool for ecological inference, but not every use is biologically justified. Applying these tools to the COVID-19 pandemic is unlikely to yield new insights, and could mislead policymakers at a critical moment.

Switches of temperature-precipitation correlation in northern Hemisphere extra-tropicsFuture precipitation response to warming remains uncertain because climate models poorly reproduce observed changes of temperature-precipitation correlations. However, restricting model validations to the observational period may yield to misleading conclusions due to the complexity of the involved processes. Our analyses of Holocene proxy-based temperature-precipitation correlations from 1500 northern Hemisphere extratropic pollen records portrayed significant latitudinal dependance, temporal changes from the early to late Holocene as well as differences between short and long time-scales. These observed variations were found to be mostly consistent with patterns simulated by Holocene transient climate simulations. Our results suggest that the strength of positive temperature-precipitation correlations in high-latitudes is sensitive to the background temperature while monsoonal subtropics reflect spatial shifts of circulation systems; and correlation sign switches in mid-latitudes relate to changes of westerlies strength. We conclude that regional and continental climate change on land is more complex than the expected “wetter climate in a warmer world” assumption which holds well at the global scale. On the other hand, long-term projections of precipitation may be better than previously thought as major processes seem to be already implemented correctly in general circulation models.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Fossil pollen records are well-established indicators of past vegetation changes. The prevalence of pollen across environmental settings including lakes, wetlands, and marine sediments, has made palynology one of the most ubiquitous and valuable tools for studying past environmental and climatic change globally for decades. A complementary research focus has been the development of statistical techniques to derive quantitative estimates of climatic conditions from pollen assemblages. This paper reviews the most commonly used statistical techniques and their rationale and seeks to provide a resource to facilitate their inclusion in more palaeoclimatic research. To this end, we first address the fundamental aspects of fossil pollen data that should be considered when undertaking pollen-based climate reconstructions. We then introduce the range of techniques currently available, the history of their development, and the situations in which they can be best employed. We reviewthe literature on how to define robust calibration datasets, produce high-quality reconstructions, and evaluate climate reconstructions, and suggest methods and products that could be developed to facilitate accessibility and global usability. To continue to foster the development and inclusion of pollen climate reconstruction methods, we promote the development of reporting standards. When established, such standards should 1) enable broader application of climate reconstruction techniques, especially in regions where such methods are currently underused, and 2) enable the evaluation and reproduction of individual reconstructions, structuring them for the evolving open-science era, and optimising the use of fossil pollen data as a vital means for the study of past environmental and climatic variability. We also strongly encourage developers and users of palaeoclimate reconstruction methodologies to make associated programming code publicly available, which will further help disseminate these techniques to interested communities.

The Leeuwin Current (LC), an eastern boundary current, transports tropical waters from the Indo-Pacific Warm Pool (IPWP) towards southern latitudes and modulates oceanic conditions offshore southern Australia. New, high-resolution planktic foraminifer assemblage data and alkenone-derived sea surface temperatures (SST) provide an in-depth view on LC variability and mechanisms driving the current's properties during the mid to late Holocene (last c. 7.4 ka BP). Our marine reconstructions highlight a longer-term mid to late Holocene reduction of tropical heat export from the IPWP area into the LC. Mid Holocene (c. 7.4 to 3.5 ka BP) occurrence of high SSTs (>19.5 °C), tropical planktic foraminifera and a well-stratified water column document an enhanced heat export from the tropics. From c. 3.5 ka BP onwards, a weaker LC and a notably reduced tropical heat export cause oceanic cooling offshore southern Australia. The observed mid to late Holocene trends likely result from large-scale changes in the IPWP's heat storage linked to the El Nino-Southern Oscillation (ENSO) phenomenon. We propose that a strong and warm LC occurs in response to a La Nina-like state of ENSO during the mid Holocene. The late Holocene LC cooling, however, results from a shift towards an El Nino-like state and a more variable ENSO system that causes cooling of the IPWP. Superimposed on these longer-term trends we find evidence of distinct late Holocene millennial-scale phases of enhanced El Nino/La Nina development, which appear synchronous with northern hemispheric climatic variability. Phases of dominant El Nino-like states occur parallel to North Atlantic cold phases: the ‘2800 years BP cooling event’, the ‘Dark Ages’ and the ‘Little Ice Age’, whereas the ‘Roman Warm Period’ and the ‘Medieval Climate Anomaly’ parallel periods of a predominant La Nina-like state. Our findings provide further evidence of coherent interhemispheric climatic and oceanic conditions during the mid to late Holocene, suggesting ENSO as a potential mediator.

Traditionally, the evaluation of pollen-based quantitative paleoclimate reconstructions focuses on the ability of calibration sets to infer present climatic conditions and/or the similarity between fossil and modern assemblages. Objective criteria for choosing the most appropriate climate parameter(s) to be reconstructed at a specific site are thus lacking. Using a novel approach for testing the statistical significance of a quantitative reconstruction using random environmental data, in combination with the advantageous large environmental gradients, abundant vegetation types and comprehensive modern pollen databases in China, we describe a new procedure for pollen-based quantitative paleoclimatic reconstructions. First, the most significant environmental variable controlling the fossil pollen assemblage changes is identified. Second, a calibration set to infer changes in this targeted variable is built up, by limiting the modern ranges of other environmental variables. Finally, the pollen-based quantitative reconstruction is obtained and its statistical significance assessed. This novel procedure was used to reconstruct the mean annual precipitation ( P ann) from Gonghai Lake in the Lvliang Mountains, and Tianchi Lake in the Liupan Mountains, on the eastern and western fringe of the Chinese Loess Plateau, respectively. Both P ann reconstructions are statistically significant ( p

Remnant forest fragments provide an opportunity for conservation in fragmented landscapes but some patches are more useful than others. Forest fragments around Budongo Forest Reserve, an Important Bird Area in western Uganda, were surveyed to explore the effects of different aspects of habitat fragmentation on bird guild composition. We recorded 1 128 individuals of 75 bird species over 7 056 net hours. The greatest number of birds and species were recorded in the forest fragments that were large, near to the continuous forest and surrounded by subsistence farmland. However, rarefied species richness was not affected by distance, size or matrix type; instead, forest specialist species were replaced by generalists and visitors with increasing fragmentation. The proportion of forest specialists and of terrestrial insectivores decreased with distance from the main forest, canopy openness and matrix intensity but not with fragment area. The findings show that bird assemblages vary in their response to habitat fragmentation but within guilds the response to fragmentation can be consistent, and can make ecological sense. Forest bird conservation can therefore benefit from information on species ecology when deciding which bird species and which parts of the landscape are to be prioritised for conservation or monitoring purposes.Keywords: forest specialist, fragment size, frugivore, insectivore, isolation, land use, matrix, species richness

The Norwegian Atlantic Current represents the northernmost reaches of the (sub)surface limb of the Atlantic Meridional Overturning Circulation. Its shelf-edge branch, the Norwegian Atlantic Slope Current (NwASC), is of particular interest as it seems to be the main conduit for advected heat towards the Arctic. The objective of this study was to investigate northward oceanic heat transport in the NwASC on longer, geologically meaningful time scales. To this end, we reconstructed variations in the strength of the NwASC over the late Holocene using the sortable-silt method. We then analysed the statistical relationship between our palaeo-flow reconstructions and published upper-ocean hydrography proxy records from the same location on the mid-Norwegian Margin. Our sortable-silt time series show prominent multi-decadal to multi-centennial variability, but no clear long-term trend over the past 4200 years. These records we thus interpret to represent perturbations in a relatively stable late-Holocene mean flow. Our in-depth statistical analysis indicates that upper-ocean temperatures at the mid-Norwegian Margin may have varied independently from the strength of the NwASC on multi-decadal to multi-centennial time scales over the past few millennia.

The construction of accurate age–depth relationships and a realistic assessment of their uncertainties is one of the fundamental prerequisites for comparing and correlating late Quaternary stratigraphical proxy records. Four widely used age–depth modelling routines – CLAM, OxCal, Bacon and Bchron – were tested using radiocarbon dates simulated from varved sediment stratigraphies. All methods produce mean age–depth models that are close to the true varve age, but the uncertainty estimation differs considerably among models. Age uncertainties are usually underestimated by CLAM, whereas age uncertainties produced by Bchron are often too large. With OxCal and Bacon, the setting of model-specific parameters influences the estimated uncertainties, which vary from too large to too small. The variability of sediment accumulation rates is underestimated by CLAM but overestimated by Bacon and Bchron. Bayesian age–depth models mainly improve the assessment of uncertainties of age–depth models.

The progression of key plant life-history events, such as spring leaf-out and flowering, along bioclimatic gradients in elevation and latitude is one of the more conspicuous patterns in nature, and, as such, it has served as a source of opportunity, industry, inspiration, and wonder for farmers, natural scientists, and artists alike (1⇓–3). For example, in many regions across the world, transhumance, traditional land-use practices that involve the seasonal movement of people and their livestock between fixed summer and winter pastures, has developed to exploit such phenological gradients across the landscape (2, 4, 5). These phenological patterns are tightly linked to temperature, leading to the formulation of bioclimatic “laws” about phenology (6). Advancing spring phenologies were also among the first clear empirical examples of biotic responses to a warming climate (7, 8). In PNAS, Vitasse et al. (9) show convincingly that climate change is now altering not only the timing of the phenological events but also the underlying patterns in phenology along environmental gradients, to an extent where these patterns are no longer in concordance with “Hopkins bioclimatic law” (6). In particular, the elevation-induced shift in the time of leaf-out in four common tree species in the Swiss Alps between low and high elevation has contracted by 35% from the 1960s until today (i.e., an increase in the rate of progression of spring leaf-out with elevation). Vitasse et al. (9) investigated three possible explanations for the observed discrepancy: ( i ) stronger warming at high elevation, ( ii ) stronger warming later in the season affecting plants at high elevation more because of later leaf-out, and ( iii ) changes in the number of chilling days (mean temperature of 0–8 °C between November and mean leaf-out date). Their analyses show that the number of chilling days during warmer winters has … [↵][1]1To whom correspondence should be addressed. Email: vigdis.vandvik{at}uib.no. [1]: #xref-corresp-1-1

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

Synthesising trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Despite the well-recognised importance of traits for addressing ecological and evolutionary questions, trait-based approaches still struggle with several basic data requirements to deliver openly accessible, reproducible, and transparent science. Here, we introduce the Open Traits Network (OTN) – a decentralised alliance of international researchers and institutions focused on collaborative integration and standardisation of the exponentially increasing availability of trait data across all organisms. The OTN embraces the use of Open Science principles in trait research, particularly open data, open source, and open methodology protocols and workflows, to accelerate the synthesis of trait data across the Tree of Life. Increased efforts at all levels – from individual scientists, research networks, scientific societies, funding agencies, to publishers – are necessary to fully exploit the opportunities offered by Open Science in trait research. Democratising access to data, tools and resources will facilitate rapid advances in the biological sciences and our ability to address pressing environmental and societal demands.

1. Climate change is a world-wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high-quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re-use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. 2. To overcome these challenges, we collected best-practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re-use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re-use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second-order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's best practice, coordinated experiments, data management and documentation, ecosystem, experimental macroecology, methodology, open science, vegetation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Very high, even annual, resolution quantitative palaeoenvironmental reconstructions have been generated from microfossil assemblage data using transfer functions. Evidence of the utility of some of these reconstructions is given by the high correlations between the reconstructions and instrumental records. Such performance is despite several ecological and taphonomic issues that can become more problematic at subdecadal resolution than at multidecadal resolution. This paper explores these timescale dependent issues and tests the reproducibility of the several of published reconstructions. It demonstrates that the previously reported exceptionally good performance of several published chironomid-based reconstructions is not reproducible. publishedVersion

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches. ©2019. American Geophysical Union. All Rights Reserved., Code and data to reproduce the figures of this article are available on GitHub and released on Zenodo (doi:10.5281/zenodo.3165019). Definition of properties and recommendations are summarized here: http://wiki.linked.earth/PaCTS_v1.0 . This work was supported by the National Science Foundation through the EarthCube Program with Grant ICER‐1541029. Feedback solicitation on the standard was facilitated by the Past Global Changes (PAGES) organization. The 2016 workshop on Paleoclimate Data Standards was hosted by the World Data Service for Paleoclimatology (WDS/NOAA‐Paleo), and the participation of international attendees was made possible by a PAGES travel grant. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400–2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r 2 = 0.61–0.88, RMSEmean = 12%–64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.

Peripheral arterial surgery is challenging, operations are frequently long and associated with insidious blood loss. Because of the high incidence of co-morbidities these patients are a high-risk group with a high incidence of morbidity and mortality. They key to successful outcome is meticulous attention to detail by all those professions involved in their care.

Background: Newly protected, tropical forests recovering from logging and clearance are increasingly important targets for conservation. Recovery is typically evaluated or monitored by using a few easily identified species groups, but this may not be sufficient as unmonitored groups of equivalent ecological importance are unlikely to respond in a similar manner due to physiological or dispersal differences. Aims: We compared four groups of plants: large trees, shrubs and saplings, herbs and ferns in a forest recovering from disturbance. We quantified the relative importance of disturbance history and local environmental conditions in determining species richness and community composition of these groups and assessed whether the groups could act as surrogate indicators for one another. Methods: Vegetation was surveyed on a gradient of disturbance intensity and recovery time (20–60 years) in Mabira Forest, Uganda. We looked for correlations between species groups in richness or composition across sites and used constrained ordinations to identify important environmental variables. Results: Neither species richness nor composition patterns were correlated between groups. All groups were weakly related to disturbance history; trees and shrubs were related to soil, herbs to microhabitat and ferns to microclimate. Conclusions: No group acted as an indicator for another. The relative influence of disturbance and local environmental effects varied in the manner predicted, with disturbance stronger for trees and environment stronger for ferns.

In the version of this Perspective originally published, the first author of reference 39 was incorrectly listed as W. Cornwell and the publication year was incorrect. The reference should have read as follows: “Flores-Moreno, H. et al. fungaltraits aka funfun: a dynamic functional trait database for the world's fungi (GitHub, 2019); https://doi.org/10.5281/zenodo.1216257”. This has now been corrected.

We demonstrate that the temperature signal in the planktonic foraminifera assemblage data from the North Atlantic typically does not originate from near surface waters and argue that this has the potential to bias sea surface temperature reconstructions using transfer functions calibrated against near surface temperatures if the thermal structure of the upper few hundred metres of ocean changes over time. CMIP5 climate models indicate that ocean thermal structure in the N Atlantic changed between the Last Glacial Maximum (LGM) and the pre-industrial (PI), with some regions, mainly in the tropics, of the LGM ocean lacking good thermal analogues in the PI. Transfer functions calibrated against different depths reconstruct a marked subsurface cooling in the tropical Atlantic during the last glacial, in contrast to previous studies that reconstructed only a modest cooling. These possible biases in temperatures reconstructions may affect estimates of climate sensitivity based on the difference between LGM and pre-industrial climate. Quantifying these biases has the potential to alter our understanding of Last Glacial Maximum climate and improve estimates of climate sensitivity.

Conventional cross validation schemes for assessing transfer-function performance assume that observations are independent. In spatially structured environments this assumption is violated, resulting in over-optimistic estimates of transfer-function performance. H-block cross validation, where all samples within h kilometres of the test samples are omitted, is a method for obtaining unbiased transfer-function performance estimates. In this study, we assess three methods for determining the optimal h. Using simulated data, we find that all three methods result in comparable values of h. Applying the three methods to published transfer functions, we find they yield similar values for h. Some transfer functions perform notably worse when h-block cross validation is used.

Benthic macrofauna is one of the most widely used biological groups to assess the ecological status of marine systems. Lately, attention has been paid to similar use of benthic foraminifera. In this study, distribution patterns of benthic foraminiferal and macrofaunal species were investigated simultaneously in 11 fjords in southeastern Norway in order to assess correlations and responses to environmental conditions. Selected fjords allowed to investigate contrasted environmental conditions from low total organic carbon (TOC) content (sediment TOC 2 mL O2.L−1) up to high TOC content (> 3.4%) in severe hypoxia (< 0.5 mL O2.L−1). Environmental parameters comprised bottom-water dissolved oxygen, grain size, total organic carbon, total nitrogen (TN), pigments and depth below threshold (DBT). Foraminiferal and macrofaunal community data were significantly correlated (Procrustes analysis m2 = 0.66, p = 0.001). Hence, benthic foraminiferal distribution patterns mirror those of benthic macrofauna. However, as opposed to the foraminifera, macrofauna was not recorded at the most oxygen-depleted stations and, hence, was more sensitive to severe oxygen depletion. With regard to assigning species to ecological groups for ecological quality status assessment, the results suggest that species, e.g. Spiroplectammina biformis (foraminifera), Scalibregma inflatum (macrofauna), may exhibit different ecological requirements depending on their habitat. Considering the observed congruent patterns of benthic foraminifera and macrofauna, palaeo-communities of benthic foraminifera could be used as indicators of reference conditions for benthic macrofaunal community structure. This would however need further developments of algorithms to perform such a translation.

The coarseness of the 10-63 µm terrigenous silt (i.e. sortable silt) fraction tends to vary independently of sediment supply in current-sorted muds in the world's oceans, with coarser sediments representing relatively greater near-bottom flow speeds. Traditionally the coarseness of this size fraction is described using an index called sortable-silt mean size (SS-), which is an arithmetic average calculated from the differential volume or mass distribution of grains within the 10-63 µm terrigenous silt fraction, where the relative weights of the individual size bins become increasingly disproportionate, with respect to the actual number of grains within those size bins, towards the coarse end of the size range. This not only increases the absolute value of the apparent “mean size” within the 10-63 μm terrigenous silt fraction, but it may also affect the apparent pattern of relative changes in the coarseness of the sortable-silt fraction along the core. In addition, it makes SS- more prone to biases due to, for example, analytical errors. Here we present a detailed analysis of grain-size distributions over three selected Holocene time intervals from two complementary sediment cores (JM97-948/2A, MD95-2011), extracted from the center of a high-accumulation area along the flow path of the main branch of the Atlantic Inflow into the Nordic Seas and show that differential-number-based statistics, which likely better describes variations in the actual coarseness of the sortable-silt fraction, may provide a more robust alternative to SS-. This article is protected by copyright. All rights reserved.

Forest-dependent biodiversity is threatened throughout the tropics by habitat loss and land-use intensification of the matrix habitats. We resampled historic data on two moth families, known to play central roles in many ecosystem processes, to evaluate temporal changes in species richness and community structure in three protected forests in central Uganda in a rapidly changing matrix. Our results show some significant declines in the moth species richness and the relative abundance and richness of forest-dependent species over the last 20–40 years. The observed changes in species richness and composition among different forests, ecological types, and moth groups highlight the need to repeatedly monitor biodiversity even within protected and relatively intact forests. publishedVersion

Palaeoecology and ecology have a lot in common. However, the two disciplines have evolved almost separately, leading to an ongoing debate on how to link them better, as both would undoubtedly benefit from a higher degree of cross-fertilisation of ideas, research insights and questions. In this paper, we explore similarities and differences in the two branches of ecology over the past 40 years by assessing the publication output from an unusually large cohort of ‘academic siblings’ – researchers in ecology and palaeoecology who all share one of the strongest career-shaping influences on researchers; their supervisor. This was made possible by John Birks’ long and active career within ecology and palaeoecology, and his supervision of a large number of students in both fields ( n = 12 and 21, respectively). Among them, John Birks’ academic progeny has published 934 papers in the international peer-reviewed literature. We collected information on the year, titles, keywords and journals of all these publications and used these data to assess the extent of, and find potential explanations for, the historical and present-day separation of ecology and palaeoecology. Despite considerable thematic overlap, there is a real and possibly widening division between the two branches that is visible both at the scale of individual research careers, journals and papers. We argue that rather than being unique to the relationship between palaeoecology and ecology, this reflects trends for thematic and methodological specialisation evident across the research landscape. We propose that both individual researchers and journals would benefit from, and can contribute to, closing the gaps developing between various ‘special branches’ in science. A good title, an informative abstract, a careful and thought-through selection of keywords and a focus on readability and avoidance of jargon will likely improve readership and impact both within one’s own ‘special branch’ and beyond.

Transfer functions are widely used in palaeoecology to provide quantitative environmental reconstructions using biological proxies. Most models use all but the rarest taxa present in the training set, even though many may be unrelated to the environmental variable of interest. We hypothesise that retaining such non-informative taxa will reduce model robustness and present a method for variable selection motivated by the statistical learning algorithm in random forests. We apply our species-pruning algorithm into weighted averaging (WA) and maximum likelihood calibration of response curves (MLRCs), and compare results of boosted regression trees (BRTs) using artificial and real datasets. Results from the artificial data show that WA is particularly sensitive to the influence of both non-informative taxa and secondary environmental variables in the training set or fossil assemblage, and that BRTs are relatively immune to these effects. Furthermore, species-pruned WA and MLRCs offer substantial improvements over all-species models when the training set includes non-informative taxa but does not guard against confounding effects when species have bi- or multivariate responses to the primary and one or more secondary variables. Tests with a limited set of examples of real data indicate that BRTs, MLRCs or species-pruned models have no apparent advantage over WA. We discuss possible reasons for this contradiction and suggest that more tests are needed to properly evaluate BRTs and species-pruned models.

A modern pollen dataset from China and Mongolia (18–52°N, 74–132°E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables — mean annual precipitation (Pann): 35–2091 mm, mean annual temperature (Tann): –12.1–25.8 °C, mean temperature in the coldest month (Mtco): –33.8–21.7 °C, and mean temperature in the warmest month (Mtwa): 0.3–29.8 °C. Modern pollen–climate relationships are assessed using canonical correspondence analysis (CCA), Huisman–Olff–Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that Pann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r2) and root mean square error of prediction (RMSEP). Mtco and Mtwa may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power.

The transition from the last ice age to the present-day interglacial was interrupted by the Younger Dryas (YD) cold period. While many studies exist on this climate event, only few include high-resolution marine records that span the YD. In order to better understand the interactions between ocean, atmosphere and ice sheet stability during the YD, more high-resolution proxy records from the Arctic, located proximal to ice sheet outlet glaciers, are required. Here we present the first diatom-based high-resolution quantitative reconstruction of sea surface conditions from central-eastern Baffin Bay, covering the period 14.0–10.2 kyr BP. Our record reveals warmer sea surface conditions and strong interactions between the ocean and the West Greenland ice margin during the YD. These warmer conditions were caused by increased Atlantic-sourced water inflow combined with amplified seasonality. Our results emphasize the importance of the ocean for ice sheet stability under the current changing climate., We would like thank the captain and all members of the cruise MSM09/2. We also thank O. Hyttinen, University of Helsinki, for her help with grain size distribution analysis. Funding from the Finnish Graduate School in Geology is kindly acknowledged as is the funding from the Academy of Finland (A.E.K. Ojala, QUAL-project 259343). We are grateful to F.M. Nick, H. Machguth, T. Luoto, and K. Pauli for insightful discussions.

The past of the Baltic Sea has been intensively investigated using a wealth of techniques. By far the largest number of studies has focused on sea level and salinity changes, driven by global climate and isostatic crustal rebound after the Baltic Sea emerged underneath the Weichselian Ice Sheet ca. 15,000 cal. years BP. The post-glacial history of the Baltic has included both freshwater and brackish water stages depending on the connection of the Baltic Sea with the world’s oceans. As the Baltic is one of the most polluted sea areas in the world, many studies have also focused on both the long-term trends in nutrients and productivity and the relatively recent anthropogenic eutrophication. The long-term changes in the trophic state of the Baltic Sea have been found to be linked to changes in climate, which controls freshwater discharge from the catchment and weathering rates, as well as marine water inflow from the North Sea. The productivity of the Baltic Sea has followed major climate patterns: it was high during warm periods and lower during phases of deteriorating climate. Recent eutrophication of the Baltic Sea can mainly be explained by a marked increase in discharge of nutrients caused by a growing population and changes in the agricultural practice, although long-term climate variability also plays a part. Signs of recovery have recently been detected, however, the Baltic Sea is still far from its pre-industrial trophic state.

Pollen-based quantitative reconstructions of past climate variables is a standard palaeoclimatic approach. Despite knowing that the spatial extent of the calibration-set affects the reconstruction result, guidance is lacking as to how to determine a suitable spatial extent of the pollen-climate calibration-set. In this study, past mean annual precipitation (P-ann) during the Holocene (since 11.5 cal ka BP) is reconstructed repeatedly for pollen records from Qinghai Lake (36.7 degrees N, 100.5 degrees E; north-east Tibetan Plateau), Gonghai Lake (38.9 degrees N, 112.2 degrees E; north China) and Sihailongwan Lake (42.3 degrees N, 126.6 degrees E; north-east China) using calibration-sets of varying spatial extents extracted from the modern pollen dataset of China and Mongolia (2559 sampling sites and 168 pollen taxa in total). Results indicate that the spatial extent of the calibration-set has a strong impact on model performance, analogue quality and reconstruction diagnostics (absolute value, range, trend, optimum). Generally, these effects are stronger with the modern analogue technique (MAT) than with weighted averaging partial least squares (WA-PLS). With respect to fossil spectra from northern China, the spatial extent of calibration-sets should be restricted to radii between ca. 1000 and 1500 km because small-scale calibration-sets (1500 km radius) will include taxa with very different pollen-climate relationships. (C) 2017 Elsevier Ltd. All rights reserved.

The so-called "8.2 ka Event" has been widely regarded as a major climate perturbation over the Holocene. It is most readily identifiable in the oxygen-isotope records from Greenland ice cores as an approximately 160 yr-long cold interval between 8250–8090 yr BP. The prevailing view has been that the cooling over Greenland, and potentially over the northern North Atlantic at least, was triggered by the catastrophic final drainage of the Agassiz-Ojibway proglacial lake as part of the remnant Laurentide Ice Sheet collapsed over Hudson Bay at around 8420 ± 80 yr BP. The consequent freshening of surface waters in the northern North Atlantic Ocean and the Nordic Seas resulted in weaker overturning, hence reduced northward heat transport. Here we present proxy records from site JM97-MD95-2011 on the mid-Norwegian Margin indicating a (sharp) decline in the strength of the eastern branch of the Atlantic Inflow into the Nordic Seas immediately following a uniquely large drop in (sub)surface ocean temperatures coeval with the lake outbursts. We propose that the final drainage of Lake Agassiz-Ojibway was accompanied by a major iceberg discharge from Hudson Bay, which resulted in the cooling of the northward-directed northern Gulf Stream-North Atlantic Drift-Norwegian Atlantic Current system. Since our current-strength proxy records from the mid-Norwegian Margin do not evidence an exceptionally strong reduction in the main branch of the Atlantic Inflow into the Nordic Seas at the time, we argue that a chilled northward-directed (sub)surface-current system and an already colder background climate state could be the main factors responsible for the 8.2 ka climate perturbation.

Seed banks contribute to forest regeneration after disturbance, but less is known about fern spore banks, particularly in a paleotropical context. We sampled the buried seed and fern spore bank in Mabira Forest, a 300 km2 forest in central Uganda, to explore the effect of time since disturbance. Soil cores (5 cm depth) were taken from 39 plots across three different classes of ‘recovery’: (1) not disturbed since 1950; (2) logged between 1950 and 1980; and (3) cleared for agriculture between 1970 and 1990 but reforested since. Plant emergence was monitored in a glasshouse. We predicted that the seed bank would reflect time since disturbance, with more pioneer species in recently disturbed stands, and that the fern spore bank would reflect stand age less closely due to greater dispersal capacity. We recorded a median 752 seeds per square meter, most of which were trees; the most abundant species was the invasive tree Broussonetia papyrifera. The fern spore bank was twice as dense, but 95 percent of fern spores were of one species, Christella parasitica. Tree seed density was significantly affected by time since disturbance with fewer seeds in the older stands. Herb seed density, fern spore density, and species richness for all groups were not significantly affected by time since disturbance. Neither seed bank nor fern spore bank closely resembled the aboveground vegetation. We compared our results to existing literature on seed banks in tropical forests, finding that our densities are relatively high for African forests, but low compared to the Neotropics and Australia. RESUME Les banques de graines contribuent a la regeneration des forets apres perturbation, mais nous savons encore peu de choses au sujet des banques de spores de fougeres, particulierement dans un contexte paleotropical. Nous avons enregistre les graines ainsi que les spores de fougeres enterrees dans la foret de Mabira, une foret de 300 km² au centre de l'Ouganda, et explore l'impact du temps passe depuis une perturbation. Les echantillons de terre ont ete preleves jusqu’a 5 cm de profondeur dans 39 parcelles caracterisees par differents degres de “reconstruction”: non perturbee depuis 1950, exploitee entre 1950 et 1980, et deboisee pour des fins d'agriculture entre 1970 et 1990 puis reboisee. L’emergence a ete suivie dans une serre. Nous avons predit que la banque de graines allait refleter le temps passe depuis la perturbation, avec davantage d'especes pionnieres dans les parcelles recemment perturbees, mais que ce patron serait moins remarquable pour la banque de spores en raison de meilleures capacites de dispersion. Nous avons enregistre une mediane de 752 graines par metre carre, dons la plupart etaient des graines d'arbres ; la graine la plus abondante etait le petit arbre invasif Broussonetia papyrifera. La banque de spores de fougeres etait deux fois plus dense mais 95 pourcent de ces spores appartenaient a une seule espece, Christella parasitica. La densite de graines d'arbres etait significativement affectee par le temps passe depuis la perturbation, avec moins de graines dans les parcelles les plus anciennes. La densite de graines d'herbes, la densite de spores de fougeres et la richesse specifique pour tous les groupes n’etaient pas significativement affectees par le temps passe depuis la perturbation. Ni la banque de graines, ni la banque de spores de fougeres ne ressemblait vraiment a la vegetation de surface. Nous avons compare nos resultats a la litterature existant sur les banques de graines en foret tropicale, et trouve que nos densites etaient relativement fortes par rapport aux forets africaines, mais basses comparees aux forets neotropicales et australiennes.

Aim Fossil pollen spectra from lake sediments in central and western Mongolia have been used to interpret past climatic variations, but hitherto no suitable modern pollen–climate calibration set has been available to infer past climate changes quantitatively. We established such a modern pollen dataset and used it to develop a transfer function model that we applied to a fossil pollen record in order to investigate: (1) whether there was a significant moisture response to the Younger Dryas event in north-western Mongolia; and (2) whether the early Holocene was characterized by dry or wet climatic conditions. Location Central and western Mongolia. Methods We analysed pollen data from surface sediments from 90 lakes. A transfer function for mean annual precipitation (Pann) was developed with weighted averaging partial least squares regression (WA-PLS) and applied to a fossil pollen record from Lake Bayan Nuur (49.98° N, 93.95° E, 932 m a.s.l.). Statistical approaches were used to investigate the modern pollen–climate relationships and assess model performance and reconstruction output. Results Redundancy analysis shows that the modern pollen spectra are characteristic of their respective vegetation types and local climate. Spatial autocorrelation and significance tests of environmental variables show that the WA-PLS model for Pann is the most valid function for our dataset, and possesses the lowest root mean squared error of prediction. Main conclusions Precipitation is the most important predictor of pollen and vegetation distributions in our study area. Our quantitative climate reconstruction indicates a dry Younger Dryas, a relatively dry early Holocene, a wet mid-Holocene and a dry late Holocene.

We test and analyse a new calibration method, boosted regression trees (BRTs) in palaeoclimatic reconstructions based on fossil pollen assemblages. We apply BRTs to multiple Holocene and Lateglacial pollen sequences from northern Europe, and compare their performance with two commonly-used calibration methods: weighted averaging regression (WA) and the modern-analogue technique (MAT). Using these calibration methods and fossil pollen data, we present synthetic reconstructions of Holocene summer temperature, winter temperature, and water balance changes in northern Europe. Highly consistent trends are found for summer temperature, with a distinct Holocene thermal maximum at ca 8000–4000 cal. a BP, with a mean T jja anomaly of ca +0.7 °C at 6 ka compared to 0.5 ka. We were unable to reconstruct reliably winter temperature or water balance, due to the confounding effects of summer temperature and the great between-reconstruction variability. We find BRTs to be a promising tool for quantitative reconstructions from palaeoenvironmental proxy data. BRTs show good performance in cross-validations compared with WA and MAT, can model a variety of taxon response types, find relevant predictors and incorporate interactions between predictors, and show some robustness with non-analogue fossil assemblages.

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model–proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this “correlative uniformitarianism” assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate–vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate–vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.