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Microclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high-resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open-access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution. ISSN:1354-1013 ISSN:1365-2486

Patterns and processes shaping ecosystems vary across spatiotemporal scales. As plant functional traits reflect ecosystem properties, investigating their relationships with environment provides an important tool to understand and predict ecosystem structure and functioning. This is particularly important in the tundra where a changing climate may trigger severe alterations in plant communities as both summer and winter conditions are changing. Here, we investigate the relationships between key environmental drivers including summer temperature, snow persistence, topographic position and soil pH, and species height, specific leaf area (SLA) and seed mass as plant traits. The study is carried out at three spatial extents in the arctic-alpine region of Fennoscandia, modelling the trait-environment relationships at each scale to investigate whether the relationships are scale dependent. Our results show that summer temperature and snow persistence are the most important variables explaining community trait composition. Temperature is important especially to vegetation height, which increased towards higher temperatures, whereas seed mass and SLA are related to snow persistence. Seed mass decreased towards longer snow persistence, while SLA responded in scale-dependent ways. Topographic position and soil pH affect community trait composition moderately. Overall, our study demonstrates that trait-environment relationships in the tundra are largely consistent across spatial scales. Our findings highlight the ecological relevance of snow for all three functional traits regardless of scale, showing that snow information could be particularly important to better understand large-scale trends in plant community composition and ecosystem functioning as seasonal snow cover is shrinking globally.

Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km2). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) daytime GHG fluxes across the landscape at 2-m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO2 uptake, it also revealed small but widespread CH4 uptake in upland vegetation types, shifting this region to an average net CH4 sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N2O fluxes were negligible. CO2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH4 fluxes by soil moisture (increases net emissions) and vegetation type, and N2O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO2 fluxes across the tundra landscape, but suggest that CH4 uptake might play a significant role in the regional GHG budget.

Considerable uncertainty exists regarding the strength, direction and relative importance of the drivers of decomposition in the tundra biome, partly due to a lack of coordinated decomposition field studies in this remote environment. Here, we analysed 3717 incubations of two uniform litter types, green and rooibos tea, buried at 330 circum-Arctic and alpine sites to quantify the effects of temperature, moisture and litter quality on decomposition. We found a surprisingly linear positive relationship between decomposition and soil temperature across all sites, counter to theory and previous model estimates. Litter mass loss was greater at wetter sites, even where soils reached almost full water saturation. However, litter quality was the strongest driver of litter mass loss across the tundra biome, explaining six times more variation in summer decomposition than soil temperature. Our results indicate that climate warming will directly increase decomposition across tundra environments. However, the indirect effects of climate change on vegetation communities, and thus plant litter inputs and quality, could have a more profound impact than direct effects on the balance of this globally important carbon store.

Species are altering their ranges as a response to climate change, but the magnitude and direction of observed range shifts vary considerably among species. The ability to persist in current areas and colonize new areas plays a crucial role in determining which species will thrive and which decline as climate change progresses. Several studies have sought to identify characteristics, such as morphological and life-history traits, that could explain differences in the capability of species to shift their ranges together with a changing climate. These characteristics have explained variation in range shifts only sporadically, thus offering an uncertain tool for discerning responses among species. As long-term selection to past climates have shaped species’ tolerances, metrics describing species’ contemporary climatic niches may provide an alternative means for understanding responses to on-going climate change. Species that occur in a broader range of climatic conditions may hold greater tolerance to climatic variability and could therefore more readily maintain their historical ranges, while species with more narrow tolerances may only persist if they are able to shift in space to track their climatic niche. Here, we provide a first-filter test of the effect of climatic niche dimensions on shifts in the leading range edges in three relatively well-dispersing species groups. Based on the realized changes in the northern range edges of 383 moth, butterfly, and bird species across a boreal 1,100 km latitudinal gradient over c. 20 years, we show that while most morphological or life-history traits were not strongly connected with range shifts, moths and birds occupying a narrower thermal niche and butterflies occupying a broader moisture niche across their European distribution show stronger shifts towards the north. Our results indicate that the climatic niche may be important for predicting responses under climate change and as such warrants further investigation of potential mechanistic underpinnings.

The warming and thawing of ice-rich permafrost pose considerable threat to the integrity of polar and high-altitude infrastructure, in turn jeopardizing sustainable development. In this Review, we explore the extent and costs of observed and predicted infrastructure damage associated with permafrost degradation, and the methods available to mitigate such adverse consequences. Permafrost change imposes various threats to infrastructure, namely through warming, active layer thickening and thaw-related hazards such as thermokarst and mass wasting. These impacts, often linked to anthropogenic warming, are exacerbated through increased human activity. Observed infrastructure damage is substantial, with up to 80% of buildings in some Russian cities and ~30% of some road surfaces in the Qinghai–Tibet Plateau reporting damage. Under anthropogenic warming, infrastructure damage is projected to continue, with 30–50% of critical circumpolar infrastructure thought to be at high risk by 2050. Accordingly, permafrost degradation-related infrastructure costs could rise to tens of billions of US dollars by the second half of the century. Several mitigation techniques exist to alleviate these impacts, including convection embankments, thermosyphons and piling foundations, with proven success at preserving and cooling permafrost and stabilizing infrastructure. To be effective, however, better understanding is needed on the regions at high risk.

1) Species distribution models (SDMs) are currently the main tools to derive species niche estimates and spatially explicit predictions for species geographical distribution. However, unobserved environmental conditions and ecological processes may confound the model estimates if they have direct impact on the species and, at the same time, they are correlated with the observed environmental covariates. This, so-called spatial confounding, is a general property of spatial models and it has not been studied in the context of SDMs before. 2) We examine how the estimation accuracy of SDMs depends on the type of spatial confounding. We construct two simulation studies where we alter spatial structures of the observed and unobserved covariates and the level of dependence between them. We fit generalized linear models with and without spatial random effects applying Bayesian inference and recording the bias induced to model estimates by spatial confounding. After this we examine spatial confounding also with real vegetation data from northern Norway. 3) Our results show that model estimates for coarse scale covariates, such as climate covariates, are likely to be biased if a species distribution depends also on an unobserved covariate operating on a finer spatial scale. Pushing higher probability for a relatively weak and smoothly varying spatial random effect compared to the observed covariates improved the model's estimation accuracy. The improvement was independent of the actual spatial structure of the unobserved covariate. 4) Our study addresses the major factors of spatial confounding in SDMs and provides a list of recommendations for pre-inference assessment of spatial confounding and for inference-based methods to decrease the chance of biased model estimates.

Ground ice content of the Arctic soils largely dictates the effects of climate change-induced permafrost degradation and top ground destabilization. The current circumarctic information on ground ice content is overly coarse for many key applications, including assessments of hazards to Arctic infrastructure, while detailed data are restricted to very few regions. This study aims to address these gaps by presenting spatially comprehensive data on pore and segregated ground ice content across the Northern Hemisphere permafrost region at a 1-km resolution. First, ground ice content datasets (n=437 and 380 1-km grid cells for volumetric and gravimetric ice content, respectively) were compiled from field observations over the permafrost region. Spatial estimates of ground ice content in the near-surface permafrost north of the 30th parallel north were then produced by relating observed ground ice content to physically relevant environmental data layers of climate, soil, topography, and vegetation properties using a statistical modelling framework. The produced data show that ground ice content varies substantially across the permafrost region. The highest ice contents are found on peat-dominated Arctic lowlands and along major river basins. Low ice contents are associated with mountainous areas and many sporadic and isolated permafrost regions. The modelling yields relatively small prediction errors (a mean absolute error of 13.6 % volumetric ice content) over evaluation data and broadly congruent spatial distributions with earlier regional-scale studies. The presented data allow the consideration of ground ice content in various geomorphological, ecological, and environmental impact assessment applications at a scale that is more relevant than previous products. The produced ground ice data are available in the supplement for this study and at Zenodo https://doi.org/10.5281/zenodo.7009875 (Karjalainen et al., 2022).

Caio Graco-Roza was funded by the Coordination for the Improvement of Higher Education Personnel (CAPES), the Carlos Chagas Filho Research Support Foundation (FAPERJ) and the Ella and Georg Erhnrooth Foundation; Jan Altman by research grants INTER-EXCELLENCE LTAUSA19137 provided by Czech Ministry of Education, Youth and Sports, 20-05840Y of the Czech Science Foundation, and long-term research development project no. RVO 67985939 of the Czech Academy of Sciences; Otso Ovaskainen was funded by Academy of Finland (grant no. 309581), Jane and Aatos Erkko Foundation, Research Council of Norway through its Centres of Excellence Funding Scheme (223257), and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 856506; ERC-synergy project LIFEPLAN); and Jianjun Wang was funded by CAS Key Research Program of Frontier Sciences (QYZDB-SSW-DQC043) and National Natural Science Foundation of China (91851117). The "sPlot" project was initiated by sDiv, the Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Research Foundation (DFG FZT 118), and is now a platform of iDiv. The study was supported by the TRY initiative on plant traits (). We are also grateful to Jens Kattge and TRY database. TRY is hosted, developed and maintained at the Max Planck Institute for Biogeochemistry (MPI-BGC) in Jena, Germany, in collaboration with the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. The CESTES database of metacommunities is also an initiative of iDiv led by Alienor Jeliazkov. We thank sDiv for supporting the open science initiative., Aim: Understanding the variation in community composition and species abundances (i.e., β-diversity) is at the heart of community ecology. A common approach to examine β-diversity is to evaluate directional variation in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distance. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 148 datasets comprising different types of organisms and environments. Location: Global. Time period: 1990 to present. Major taxa studied: From diatoms to mammals. Method: We measured the strength of the decay using ranked Mantel tests (Mantel r) and the rate of distance decay as the slope of an exponential fit using generalized linear models. We used null models to test whether functional similarity decays faster or slower than expected given the taxonomic decay along the spatial and environmental distance. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm and organismal features. Results: Taxonomic distance decay was stronger than functional distance decay along both spatial and environmental distance. Functional distance decay was random given the taxonomic distance decay. The rate of taxonomic and functional spatial distance decay was fastest in the datasets from mid-latitudes. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distance but a higher rate of decay along environmental distance. Marine ecosystems had the slowest rate of decay along environmental distances. Main conclusions: In general, taxonomic distance decay is a useful tool for biogeographical research because it reflects dispersal-related factors in addition to species responses to climatic and environmental variables. Moreover, functional distance decay might be a cost-effective option for investigating community changes in heterogeneous environments., Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio De Janeiro (FAPERJ), Ella and Georg Erhnrooth Foundation, Ministry of Education, Youth & Sports - Czech Republic LTAUSA19137 Grant Agency of the Czech Republic 20-05840Y Czech Academy of Sciences RVO 67985939, Academy of Finland 309581, Jane and Aatos Erkko Foundation, Research Council of Norway through its Centres of Excellence Funding Scheme 223257, European Research Council (ERC) 856506, CAS Key Research Program of Frontier Sciences QYZDB-SSW-DQC043, National Natural Science Foundation of China (NSFC) 91851117, German Research Foundation (DFG) DFG FZT 118, TRY initiative on plant traits

The anthropogenic climate change threatens northern permafrost environments. This compromises the existence of permafrost landforms, such as palsas and peat plateaus, which have been assessed to be critically endangered habitats. In this study, for the first time we integrated geospatial datasets and statistical methods, to model the distribution of palsas and peat plateaus across the Northern Hemisphere permafrost region. The models were calibrated using data from years 1950–2000. The effects of climate change on the future distribution of palsas were assessed by using moderate and high emission scenarios (Representative Concentration Pathways; RCP4.5 and RCP8.5, respectively) for two periods (2041–2060 and 2061–2080). Hotspots for palsas and peat plateaus occurred in Northern Europe, Western Siberia, and subarctic Canada. Climate change was predicted to cause an almost complete loss (˗98.2 %) of suitable environmental spaces under a high emissions scenario by 2061–2080, while under a moderate emissions scenario 89.3 % were predicted to disappear. The comparison with previously published thermokarst data supported our findings regarding the recent degradation of palsa and peat plateau environments. Our results fill the knowledge gaps in the distribution of the permafrost landforms in less studied areas such as Central and Eastern Siberia. In addition, the projections provide insights into the changing geoecological conditions of the circumpolar region with important implications for greenhouse gas emissions.

Aim: Geomorphological processes profoundly affect plant establishment and distributions, but their influence on functional traits is insufficiently understood. Here, we unveil trait–geomorphology relationships in Arctic plant communities. Location: High-Arctic Svalbard, low-Arctic Greenland and sub-Arctic Fennoscandia. Time period: 2011– 2018. Major taxa studied: Vascular plants. Methods: We collected field-quantified data on vegetation, geomorphological processes, microclimate and soil properties from 5,280 plots and 200 species across the three Arctic regions. We combined these data with database trait records to relate local plant community trait composition to dominant geomorphological processes of the Arctic, namely cryoturbation, deflation, fluvial processes and solifluction. We investigated the relationship between plant functional traits and geomorphological processes using hierarchical generalized additive modelling. Results: Our results demonstrate that community-level traits are related to geomorphological processes, with cryoturbation most strongly influencing both structural and leaf economic traits. These results were consistent across regions, suggesting a coherent biome- level trait response to geomorphological processes. Main conclusions: The results indicate that geomorphological processes shape plant community traits in the Arctic. We provide empirical evidence for the existence of generalizable relationships between plant functional traits and geomorphological processes. The results indicate that the relationships are consistent across these three distinct tundra regions and that geomorphological processes should be considered in future investigations of functional traits.

Due to climate change, increased microbial activity in high-latitude soils may lead to higher greenhouse gas (GHG) emissions. However, microbial GHG production and consumption mechanisms in tundra soils are not thoroughly understood. To investigate how the diversity and functional potential of bacterial and archaeal communities vary across vegetation types and soil layers, we analyzed 116 soil metatranscriptomes from 73 sites in the Finnish sub-Arctic. Meadow soils were characterized by higher pH and lower soil organic matter (SOM) and carbon/nitrogen ratio. By contrast, dwarf shrub-dominated ecosystems had higher SOM and lower pH. Although Actinobacteria, Acidobacteria, Alphaproteobacteria and Planctomycetes were dominant in all communities, there were significant differences at the genus level between vegetation types; plant polymer-degrading groups were more active in shrub-dominated soils than in meadows. Given that climate-change scenarios predict the expansion of shrubs at high latitudes, our results indicate that tundra soil microbial communities harbor potential decomposers of increased plant litter, which may affect the rate of carbon turnover in tundra soils. Additionally, transcripts of methanotrophs were detected in the mineral layer of all soils, which may moderate methane fluxes. This study provides new insights into possible shifts in tundra microbial diversity and activity due to climate change. Active microbial communities were significantly different in the organic and mineral soil layers and the communities differed significantly between four different vegetation types both in the organic and mineral layers.

The effects of temperature and precipitation, and the impacts of changes in these climatic conditions, on plant communities have been investigated extensively. The roles of other climatic factors are, however, comparatively poorly understood, despite potentially also strongly structuring community patterns. Wind, for example, is seldom considered when forecasting species responses to climate change, despite having direct physiological and mechanical impacts on plants. It is, therefore, important to understand the magnitude of potential impacts of changing wind conditions on plant communities, particularly given that wind patterns are shifting globally. Here, we examine the relationship between wind stress (i.e. a combination of wind exposure and wind speed) and species richness, vegetation cover and community composition using fine-scale, field-collected data from 1,440 quadrats in a windy sub-Antarctic environment. Wind stress was consistently a strong predictor of all three community characteristics, even after accounting for other potentially ecophysiologically important variables, including pH, potential direct incident solar radiation, winter and summer soil temperature, soil moisture, soil depth and rock cover. Plant species richness peaked at intermediate wind stress, and vegetation cover was highest in plots with the greatest wind stress. Community composition was also related to wind stress, and, after the influence of soil moisture and pH, had a similar strength of effect as winter soil temperature. Synthesis. Wind conditions are, therefore, clearly related to plant community characteristics in this ecosystem that experiences chronic winds. Based on these findings, wind conditions require greater attention when examining environment-community relationships, and changing wind patterns should be explicitly considered in climate change impact predictions.

A fundamental assumption in trait-based ecology is that relationships between traits and environmental conditions are globally consistent. We use field-quantified microclimate and soil data to explore if trait–environment relationships are generalizable across plant communities and spatial scales. We collected data from 6,720 plots and 217 species across four distinct tundra regions from both hemispheres. We combined these data with over 76,000 database trait records to relate local plant community trait composition to broad gradients of key environmental drivers: soil moisture, soil temperature, soil pH and potential solar radiation. Results revealed strong, consistent trait–environment relationships across Arctic and Antarctic regions. This indicates that the detected relationships are transferable between tundra plant communities also when fine-scale environmental heterogeneity is accounted for, and that variation in local conditions heavily influences both structural and leaf economic traits. Our results strengthen the biological and mechanistic basis for climate change impact predictions of vulnerable high-latitude ecosystems. acceptedVersion

In the tundra, woody plants are dispersing towards higher latitudes and altitudes due to increasingly favourable climatic conditions. The coverage and height of woody plants are increasing, which may influence the soils of the tundra ecosystem. Here, we use structural equation modelling to analyse 171 study plots and to examine if the coverage and height of woody plants affect the growing-season topsoil moisture and temperature (

Boreal upland forests are generally considered methane (CH4) sinks due to high methane consumption rates. However, some studies have shown a boreal upland forest soil turning from a CH4 sink to a source after long-term abundant precipitation but the factors affecting this change remain largely unknown. In a simulated rainfall experiment, we investigated soil moisture effects on CH4 flux. We also evaluated the influence of simultaneous soil temperature increase, organic litter addition and root exclusion on CH4 flux.The study was conducted in a northern boreal upland forest soil (Kenttärova forest in Kittilä, Finland) in summer 2018. Split-plot design was used in the experiment with soil moisture being the main treatment variable and soil warming (T), organic litter addition (A) and organic litter and root exclusion (E) subtreatment variables. The design included two main plots: irrigation (I) and control (C), within which each subtreatment was replicated three times. In addition to the T, A and E manipulations, plots without additional manipulations (O) were included for the assessment of the effect of only soil moisture increase (n=4). CH4 flux was measured at least once a week using chambers. Soil moisture and temperature were also continuously measured.Contrary to our expectation, the soil remained a CH4 sink after experimental rainfall increase but irrigation and control sites differed significantly in their CH4 fluxes, indicating a strong decreasing effect of soil moisture on soil CH4 sink. All treatments had lowest CH4 uptake rates in August, possibly as a result of high soil moisture. The IA treatment had the lowest uptake rates possibly due to a reduction in gas diffusion. The IE treatment had contrasting results to all other treatments and showed a positive relationship between uptake rate and soil moisture, but the causes remained unsolved and the results were highly uncertain. T treatment had no effect on uptake likely due to a failure to create soil temperature differences and thus the interactions were not reliably analyzed. Our results suggest that the CH4 flux response to soil moisture may have been more related to changes in CH4 consumption than production. Based on these results, future irrigation experiments should especially assess the combined effect of organic litter addition and soil moisture on soil CH4 sink over multiple years. Improvements in the manipulation methods, experimental design and sensors will also be needed.

Harsh winters are a characteristic element of Arctic ecosystems, yet the importance of winter conditions for Arctic plant communities is still underrepresented in climate change impact studies. Here, we use fine-scale microclimate data with plot-scale records of vascular plants, lichens and bryophytes from three Arctic areas, and show that topographically heterogeneous tundra holds marked spatial variation, especially in winter temperatures. Winter conditions are the strongest environmental variable related to the fine-scale patterns in tundra vegetation, whereas summer temperatures mainly explain the coarse-scale differences among the Arctic areas. Nonetheless, the three plant groups (and also individual species) show often contrasting and complex responses along the local environmental gradients. Our results highlight the importance of local conditions and heterogeneity for tundra plants, and knowing that the Arctic winters are warming faster than summers, a greater focus should be placed on winter conditions in simulations of climate change impacts in tundra ecosystems. Winter conditions are the strongest environmental variable relating to fine-scale patterns in tundra vegetation. Vascular plants, lichens and bryophytes nonetheless show complex responses across environmental gradients, highlighting the importance of local heterogeneity.

The ecological impacts of extreme climatic events on population dynamics and community composition are profound and predominantly negative. Using extensive data of an ecological model system, we tested whether predictions from ecological models remain robust when environmental conditions are outside the bounds of observation. We observed a 10-fold demographic decline of the Glanville fritillary butterfly (Melitaea cinxia) metapopulation on the Åland islands, Finland in the summer of 2018 and used climatic and satellite data to demonstrate that this year was an anomaly with low climatic water balance values and low vegetation productivity indices across Åland. Population growth rates were strongly associated with spatiotemporal variation in climatic water balance. Covariates shown previously to affect the extinction probability of local populations in this metapopulation were less informative when populations were exposed to severe drought during the summer months. Our results highlight the unpredictable responses of natural populations to extreme climatic events.El Efecto de la Sequía Estival sobre la Previsibilidad de las Extinciones Locales en una Metapoblación de Mariposas Resumen Los impactos ecológicos de los eventos climáticos extremos sobre las dinámicas metapoblacionales y la composición de la comunidad son profundos y predominantemente negativos. Con los extensos datos de un sistema de modelos ecológicos probamos si las predicciones de los modelos ecológicos todavía son sólidos cuando las condiciones ambientales se encuentran fuera de los límites de observación. Observamos una declinación demográfica ocurrir diez veces en la metapoblación de la mariposa Melitaea cinxia en las Islas Aland de Finlandia durante el verano de 2018. Usamos datos climáticos y satelitales para demostrar que ese año fue una anomalía al contar con valores bajos de balance hídrico e índices bajos de productividad de la vegetación en todas las islas. Las tasas de crecimiento poblacional estuvieron fuertemente asociadas con la variación espaciotemporal del balance hídrico climático. Las covarianzas que previamente han afectado a la probabilidad de extinción de las poblaciones locales de esta metapoblación fueron menos informativas cuando las poblaciones estuvieron expuestas a sequías severas durante los meses de verano. Nuestros resultados resaltan las respuestas impredecibles de las poblaciones naturales ante los eventos climáticos extremos.极端气候事件会对种群动态和群落组成产生深远的生态影响, 且主要为负面影响。本研究利用生态模型系统的大量数据, 测试了在环境条件超出观测范围时, 生态模型的预测结果是否仍然稳健。我们观测到在 2018 年夏天, 芬兰奥兰群岛的庆网蛱蝶 (Melitaea cinxia) 集合种群的种群数量下降了十倍, 同时气候和卫星数据表明奥兰群岛当年出现了气候异常, 气候水平衡值和植被生产力指数都很低。种群增长率与气候水平衡的时空变化密切相关。当种群面临夏季严重干旱时, 之前研究发现在这个集合种群中会影响当地种群灭绝概率的协变量不再能提供丰富信息。我们的研究结果强调了自然种群会对极端气候事件产生不可预测的响应。 【翻译: 胡怡思; 审校: 聂永刚】.

A comprehensive understanding of the scale dependency of environmental filtering and biotic interactions influencing the local assembly of species is paramount to derive realistic forecasts of the future of biodiversity and efficiently manage ecological communities. A classical assumption is that environmental filters are more prevalent at coarser scales with diminishing effects towards the finest scales where biotic interactions become more decisive. Recently, a refinement was proposed stipulating that the scale dependency of biotic interactions should relate to the type of interaction. Specifically, the effect of negative interactions (e.g. competition) should diminish with coarsening scale, whereas positive interactions (i.e. facilitation) should be detected irrespective of the scale. We use multiple vascular plant species datasets sampled at nested spatial scales (plot size varying from 0.04 to 64 m(2)) and recently developed joint species distribution models to test the hypotheses. Our analyses indicate slightly stronger environmental filtering with increasing plot size. While the overall strength of biotic interactions did not vary consistently across scales, we found a tendency for negative interactions to fade away with increasing plot size slightly more than positive interactions. Synthesis. We provide partial, but not unambiguous, evidence of the scale dependency of ecological assembly rules. However, our correlative methodology only allows us to interpret the findings as indication of environmental filtering and biotic interactions.

Biological communities are reshuffling owing to species range shifts in response to climate change. This process inherently leads to novel assemblages of interacting species. Yet, how climatic change and local dynamics in biotic interactions jointly affect range shifts is still poorly understood. We combine a unique long-term transplant competition-exclusion experiment with species distribution models (SDMs) to test the effects of biotic interactions on understorey species range shifts under climate change in European temperate forests. Using a time series of 18?years of individual-level demographic data of four common understorey plant species transplanted beyond their cold range edge to plots with and without interspecific competition, we built integral projection models (IPMs) and analysed the effects of competition on five key vital rates and population growth (?). We assessed the results of the transplant experiment in the context of the modelled species' current and future potential distributions. We find that species' population performances in the transplant experiment decreased with lower predicted habitat suitability from the SDMs. The population performance at the transplant sites was mediated by biotic interactions with the local plant community: for two species with intermediate levels of predicted habitat suitability at the transplant sites, competition effects could explicitly differentiate between net population growth (??>?1) or shrinkage (??1). Synthesis. Our findings contest the long-standing idea that at cold range edges, mainly abiotic factors structure species' distributions. We conclude that biotic interactions, through acting on local population dynamics, may impact species distributions at the continental scale. Hence, predicting climate-change impacts on biodiversity redistributions ultimately requires us to also integrate dynamics in biotic interactions. https://doi.org/10.1111/1365-2745.13907 ispartof: Journal Of Ecology vol:110 issue:8 status: Published online

Soil moisture has a fundamental influence on the processes and functions of tundra ecosystems. Yet, the local dynamics of soil moisture are often ignored, due to the lack of fine resolution, spatially extensive data. In this study, we modelled soil moisture with two mechanistic models, SpaFHy (a catchment-scale hydrological model) and JSBACH (a global land surface model), and examined the results in comparison with extensive growing-season field measurements over a mountain tundra area in northwestern Finland. Our results show that soil moisture varies considerably in the study area and this variation creates a mosaic of moisture conditions, ranging from dry ridges (growing season average 12 VWC%, Volumetric Water Content) to water-logged mires (65 VWC%). The models, particularly SpaFHy, simulated temporal soil moisture dynamics reasonably well in parts of the landscape, but both underestimated the range of variation spatially and temporally. Soil properties and topography were important drivers of spatial variation in soil moisture dynamics. By testing the applicability of two mechanistic models to predict fine-scale spatial and temporal variability in soil moisture, this study paves the way towards understanding the functioning of tundra ecosystems under climate change. This article is protected by copyright. All rights reserved.

Forest canopies buffer macroclimatic temperature fluctuations. However, we do not know if and how the capacity of canopies to buffer understorey temperature will change with accelerating climate change. Here we map the difference (offset) between temperatures inside and outside forests in the recent past and project these into the future in boreal, temperate and tropical forests. Using linear mixed-effect models, we combined a global database of 714 paired time series of temperatures (mean, minimum and maximum) measured inside forests vs. in nearby open habitats with maps of macroclimate, topography and forest cover to hindcast past (1970–2000) and to project future (2060–2080) temperature differences between free-air temperatures and sub-canopy microclimates. For all tested future climate scenarios, we project that the difference between maximum temperatures inside and outside forests across the globe will increase (i.e. result in stronger cooling in forests), on average during 2060–2080, by 0.27 ± 0.16 °C (RCP2.6) and 0.60 ± 0.14 °C (RCP8.5) due to macroclimate changes. This suggests that extremely hot temperatures under forest canopies will, on average, warm less than outside forests as macroclimate warms. This knowledge is of utmost importance as it suggests that forest microclimates will warm at a slower rate than non-forested areas, assuming that forest cover is maintained. Species adapted to colder growing conditions may thus find shelter and survive longer than anticipated at a given forest site. This highlights the potential role of forests as a whole as microrefugia for biodiversity under future climate change.

Questions Species distribution models have traditionally relied heavily on temperature and precipitation, often ignoring other potentially important variables. However, recent advances have shown other climatic variables, including snow cover and solar radiation, may strongly improve predictions of species occurrence. Wind has long been known to have mechanical and physiological impacts on plants, but has not yet received adequate attention as a driver of species distributions. Location Marion Island, sub-Antarctic. Methods Using data from 1,440 plots in a chronically windy system, we test if wind stress (a combination of wind exposure and wind speed) improves species distribution models of vascular plant species, examining predictions for both species occurrence and cover. Results Wind stress was a significant predictor of the occurrence of 12 of the 16 species, even after accounting for seven other ecophysiologically important abiotic variables. Species showed differential responses to wind, but wind stress was among the four most important drivers for the majority of species when modelling occurrence patterns (10 of 16) and variation in cover (12 of 16). Further, wind stress was more important than all temperature and precipitation variables in predicting the occurrence of six species (and three species' cover). Conclusions Wind conditions were most influential for species that are characteristic of open, wet environments and for pteridophyte species, likely due to high wind speeds and exposure increasing the potential for moisture loss. This research highlights the value of incorporating wind metrics into species distribution models, particularly under changing wind patterns.

Tundra ecosystems have experienced changes in vegetation composition, distribution, and productivity over the past century due to climate warming. However, the increase in above-ground biomass may be constrained by cryogenic land surface processes that cause topsoil disturbance and variable microsite conditions. These effects have remained unaccounted for in tundra biomass models, although they can impact multiple opposing feedbacks between the biosphere and atmosphere, ecosystem functioning and biodiversity. Here, by using field-quantified data from northern Europe, remote sensing, and machine learning, we show that cryogenic land surface processes substantially constrain above-ground biomass in tundra. The three surveyed processes (cryoturbation, solifluction, and nivation) collectively reduced biomass by an average of 123.0 g m(-2) (-30.0%). This effect was significant over landscape positions and was especially pronounced in snowbed environments, where the mean reduction in biomass was 57.3%. Our results imply that cryogenic land surface processes are pivotal in shaping future patterns of tundra biomass, as long as cryogenic ground activity is retained by climate warming. Vegetation in tundra ecosystems is constrained by cryogenic land surface processes, despite the fact that models of future biomass changes rarely take these into account, according to field and remote sensing data from northern Europe.