The change in the distribution of arable weeds in Europe as a consequence of climate change

This study aimed at exploring the future distribution of 25 weeed species, representing different distribution patterns and taxa, at European scale. Using generalized additive models, and data on current climate and species distributions and two different climate scenarios for the period 2051-2080, we developed predictions of the currently suitable area and potential range size changes of 25 European weed species

Significant shallow–depth soil warming over Russia during the past 40 years

Knowledge of the spatiotemporal dynamics of the soil temperature in cold environment is key to understanding the effects of climate change on land-atmosphere feedback and ecosystem functions. Here, we quantify the recent thermal status and trends in shallow ground using the most up-to-date data set of over 457 sites in Russia. The data set consists of in situ soil temperatures at multiple depths (0.8, 1.6, and 3.2 m) collected from 1975 to 2016. For the region as a whole, significant soil warming occurred over the period. The mean annual soil temperature at depths of 0.8, 1.6, and 3.2 m increased at the same level, at ca 0.30-0.31 degrees C/decade, whereas the increase in maximum soil temperature ranged from 0.40 degrees C/decade at 0.8 m to 0.31 degrees C/decade at 3.2 m. Unlike the maximum soil temperature, the increases in minimum soil temperature did not vary (ca 0.25 degrees C/decade) with depth. Due to the overall greater increase in maximum soil temperature than minimum soil temperature, the intra-annual variability of soil temperature increased over the decades. Moreover, the soil temperature increased faster in the continuous permafrost area than in the discontinuous permafrost and seasonal frost areas at shallow depths (0.8 and 1.6 m depth), and increased slower at the deeper level (3.2 m). The warming rate of the maximum soil temperature at the shallower depths was less than that at the deeper level over the discontinuous permafrost area but greater over the seasonal frost area. However, the opposite was found regarding the increase in minimum soil temperature. Correlative analyses suggest that the trends in mean and extreme soil temperatures positively relate to the trends in snow cover thickness and duration, which results in the muted response of intra-annual variability of the soil temperature as snow cover changes. This study provides a comprehensive view of the decadal evolutions of the shallow soil temperatures over Russia, revealing that the temporal trends in annual mean and extreme soil temperatures vary with depth and permafrost distribution.Peer reviewe

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Peer reviewe

Decadal Changes in Soil and Atmosphere Temperature Differences Linked With Environment Shifts Over Northern Eurasia

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Modelling soil moisture in a high-latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non-climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape-scale soil moisture variation by utilizing high-resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high-latitude landscape of mountain tundra in north-western Finland. We measured the plots three times during growing season 2016 with a hand-held time-domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R-2 = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R-2 = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R-2 = 0.47 and RMSE 9.34 VWC%, and for the latter R-2 = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high-resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1m(2) digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine-scale soil moisture variation. In the temporal variation models, the strongest predictor was the field-quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright (c) 2017 John Wiley & Sons, Ltd.Peer reviewe

Models of Arctic-alpine refugia highlight importance of climate and local topography

Projected climatic warming calls for increased attention to the identification of suitable refugia for the preservation of biota and ecosystems in changing high-latitude environments. One such way is the development of models for drivers of refugia. Here, we investigate the distribution and species richness of Arctic-alpine vascular plant species' refugia. The study is carried out in an environmentally variable area in N Europe, encompassing the northern boreal to the Arctic-alpine zone. We defined refugia as isolated 1 km x 1 km grid cells with multiple Arctic-alpine plant species occurrences outside their main distribution area and assessed the main environmental factors underlying their distribution and richness using cross-validated boosted regression tree modelling. In the modelling, we examined the effects of climatic, topographic, and geologic factors, and the connectivity of sites with refugia incrementally, i.e. first modelling climatic impact alone, then with separate additions of topographic, geologic and connectivity variables, concluding with a model including all predictor variables. The inclusion of slope and connectivity significantly improved model performance. Although climate has a central role in controlling the occurrence of refugia, topography provides important clues for recognizing heterogeneous locations that harbour refugia with suitable local thermal and moisture conditions. Results suggest considering refugia as, on the one hand, isolated pockets of suitable habitat, but on the other hand as potentially interconnected habitat networks. In general, our study demonstrates that the spatial patterns of refugia can be successfully modelled, but emphasizes a need for high-quality data sampled at resolutions reflecting significant environmental gradients.Peer reviewe

Arctic shrubification mediates the impacts of warming climate on changes to tundra vegetation

Peer reviewe

Monthly microclimate models in a managed boreal forest landscape

The majority of microclimate studies have been done in topographically complex landscapes to quantify and predict how near-ground temperatures vary as a function of terrain properties. However, in forests understory temperatures can be strongly influenced also by vegetation. We quantified the relative influence of vegetation features and physiography (topography and moisture-related variables) on understory temperatures in managed boreal forests in central Sweden. We used a multivariate regression approach to relate near-ground temperature of 203 loggers over the snow-free seasons in an area of ∼16,000 km2 to remotely sensed and on-site measured variables of forest structure and physiography. We produced climate grids of monthly minimum and maximum temperatures at 25m resolution by using only remotely sensed and mapped predictors. The quality and predictions of the models containing only remotely sensed predictors (MAP models) were compared with the models containing also on-site measured predictors (OS models). Our data suggest that during the warm season, where landscape microclimate variability is largest, canopy cover and basal area were the most important microclimatic drivers for both minimum and maximum temperatures, while physiographic drivers (mainly elevation) dominated maximum temperatures during autumn and early winter. The MAP models were able to reproduce findings from the OS models but tended to underestimate high and overestimate low temperatures. Including important microclimatic drivers, particularly soil moisture, that are yet lacking in a mapped form should improve the microclimate maps. Because of the dynamic nature of managed forests, continuous updates of mapped forest structure parameters are needed to accurately predict temperatures. Our results suggest that forest management (e.g. stand size, structure and composition) and conservation may play a key role in amplifying or impeding the effects of climate-forcing factors on near-ground temperature and may locally modify the impact of global warming.Peer reviewe