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One of the challenges in global change research is the significant uncertainty in global historical land use and land cover (LUCC) datasets, which are widely used as foundational data. In addition to the regional cropland area reconstructions, improving the grid allocation method is another feasible way to raise the reliability of historical LUCC data. In this study, an integrated reconstruction of the national cropland areas over the past 200 years was developed for 36 European countries. After that, the allocation algorithm was built using physiogeographic variables and historical city sites for accounting for land suitability and cultivation preferences, respectively. Finally, cropland data in Europe with a spatial resolution of 5′×5′ at five time sections from AD 1800 to 2000 were generated using the optimal allocation algorithm in accordance with the stages of the regional history. The results were as follows: (1) The dominant factors governing the distribution of croplands in Europe vary at different agricultural stages, but the results can be merged together. Land suitability was more optimal for allocation during the modern agricultural stage (AD 1950 and 2000); the priority index combined with land suitability and cultivation preference was more reasonable for allocation during the traditional agricultural stage (AD 1800). The average of the allocations by priority index and the land suitability could be adopted as the allocation results during the transitional stage (AD 1850 and 1900) because the grids for absolute differences within ±10 and ±20 percentage points between the results obtained from the above two allocations were above 80% and 95%, respectively, which means the two allocation results could be merged. (2) Over the past 200 years, the total cropland area in Europe first increased to a peak in AD 1900 and then decreased. Spatially, the centre of the higher cropland fraction shifted from the western part of Europe in AD 1800 to the eastern part of the continent after AD 1950. (3) Both the cropland area and the spatial distribution in this study are more reasonable than the global dataset HYDE3.2. [ABSTRACT FROM AUTHOR]

ABSTRACT Motivation Main Types of Variables Contained Spatial Location and Grain Time Period and Grain Major Taxa and Level of Measurement Software Format Accurate estimates of species distributions are crucial for biogeography, spatial conservation, and for assessing the impacts of human activities on species. However, existing approaches to estimate species distributions have typically neglected the influence of land use intensity, potentially overlooking the negative impacts of high‐intensity land uses on biodiversity. Here, we build a dataset documenting the habitat suitability of European land systems for terrestrial vertebrate species, based on a novel land system map of Europe that factors in land use intensity. Our database offers refined and up‐to‐date information on terrestrial vertebrate distributions in Europe by explicitly considering land use intensity.We created a table defining the suitability of land use classes as habitats for each species. We then built Area of Habitat (AOH) maps for each species by filtering out unsuitable habitat from the latest available estimates of species ranges. AOH maps were then compared with occurrence records from the Global Biodiversity Information Facility (GBIF). Processed datasets and R scripts are publicly available online, facilitating the use of our approach to refine expert‐based distributions for other taxa, land system classifications and regions worldwide.The AOH maps cover the spatial extent of the European Union (EU) with the United Kingdom, Norway, Switzerland, and the Western Balkans. The AOH maps are at a 1 km2 resolution.The dataset uses information published during the last 10 years.Habitat suitability was documented for 1155 terrestrial vertebrate species known to occur in Europe: 279 mammals, 520 birds, 251 reptiles and 104 amphibians.We provide the habitat suitability table in a comma‐separated values (csv) format. The AOH maps are available as raster files. R scripts are publicly accessible on GitHub. [ABSTRACT FROM AUTHOR]

Land degradation is a complex socio-environmental threat, which generally occurs as multiple concurrent pathways that remain largely unexplored in Europe. Here we present an unprecedented analysis of land multi-degradation in 40 continental countries, using twelve dataset-based processes that were modelled as land degradation convergence and combination pathways in Europe's agricultural (and arable) environments. Using a Land Multi-degradation Index, we find that up to 27%, 35% and 22% of continental agricultural (~2 million km2) and arable (~1.1 million km2) lands are currently threatened by one, two, and three drivers of degradation, while 10–11% of pan-European agricultural/arable landscapes are cumulatively affected by four and at least five concurrent processes. We also explore the complex pattern of spatially interacting processes, emphasizing the major combinations of land degradation pathways across continental and national boundaries. Our results will enable policymakers to develop knowledge-based strategies for land degradation mitigation and other critical European sustainable development goals. This study presents an unprecedented analysis of agricultural land multi-degradation in 40 European countries, using twelve dataset-based processes that were modelled as land degradation convergence and combination pathways across the continent. [ABSTRACT FROM AUTHOR]

The present study, detailed a survey of the academic debate and scientific trends regarding generational succession in agriculture. Hence this study is categorized under quantitative and qualitative bibliometric research. For this research, the Scopus database was accessed to identify scientific articles from publications between the years 2010 and 2021. The search, which included keywords like "successors" and "farm*", resulted in 57 relevant articles. For the study, eleven thematic categories were selected, viz., Factors that influence generational succession; Gender issues in generational succession; Educational aspects in succession; Coping strategies in relation to the future of rural properties and utilization of agricultural land; Succession planning; Issues related to the dairy farming activity and the presence of successors; The role of rural youth in the succession; Socioeconomic effects on rural properties from the presence of successors; Agricultural transfers to "new" farmers; Emotional and belonging aspects in generational transfer; and Relationships and perceptions of non-successors with respect to rural property and succession. However, the factors that affect generational renewal and gender issues in generational succession are the themes that recur most often in the research. Europe is in the forefront in terms of research on succession, and reveals new research pathways and is on the frontline for the development of public policies on generational succession in agriculture. Finally, the other emerging themes were observed to be those which dealt with the relationship that exists between the emotional aspects and succession, as well as agricultural transfers to "new" farmers. [ABSTRACT FROM AUTHOR]

Since 2023, a new format of the Common Agricultural Policy (CAP) has been implemented in Europe. Market forces alone cannot guarantee land services, which can be described as flows of goods and services from ecosystems to human systems as functions of nature. Market forces also cannot ensure food security everywhere and at all times, so deliberate measures should incentivize farmers to adopt sustainable agricultural practices and maintain necessary skills and resources. This study identifies, quantifies, and interprets four narratives that are typical in the approach to food security and the public debate about the land services in the CAP Strategic Plans: (A) provision of land services within the Pillar 1 economics; (B) small vs. large farms; (C) direct payments in comparison with rural development; and (D) choices by the old and new member states. Participatory processes, descriptive statistics, and partial component analysis were used in terms of the methodology. The key finding is that the importance attached to eco-schemes varies among member states, although a majority dedicate approximately 25% of the Pillar 1 budget to them. We showed that small-scale farming countries move resources from Pillar 2 to strengthen direct payments. In contrast, affluent countries with robust agricultural structures can afford to reinforce Pillar 2 rural development through transfers from direct payments. To support small-scale and medium farms, appropriate support requires a combination of several measures, including the sizable hectare payment in Pillar 1 and farmer-oriented agri-environmental measures. [ABSTRACT FROM AUTHOR]

Land-use change (LUC) impacts biospheric carbon, encompassing biomass carbon and soil organic carbon (SOC). Despite the use of dynamic global vegetation models (DGVMs) in estimating the anthropogenic perturbation of biospheric carbon stocks, critical evaluations of model performance concerning LUC impacts are scarce. Here, we present a systematic evaluation of the performance of the DGVM ORCHIDEE to reproduce observed LUC impacts on biospheric carbon stocks over Europe. First, we compare model predictions with observation-based gridded estimates of net and gross primary productivity (NPP and GPP), biomass growth patterns, and SOC stocks. Second, we evaluate the predicted response of carbon stocks to LUC based on data from forest inventories, paired plots, chronosequences and repeated sampling designs. Third, we use interpretable machine learning to identify factors contributing to discrepancies between simulations and observations, including drivers and processes not resolved in ORCHIDEE (e.g. erosion, soil fertility). Results indicate agreement between the model and observed spatial patterns and temporal trends, such as the increase in biomass with age, when simulating biosphere carbon stocks. The direction of the SOC responses to LUC generally aligns between simulated and observed data. However, the model underestimates carbon gains for cropland-to-grassland and carbon losses for grassland-to-cropland and forest-to-cropland conversions. These discrepancies are attributed to bias arising from soil erosion rate, which is not fully captured in ORCHIDEE. Our study provides an oriented benchmark for assessing the DGVMs against observations and explores its potential in studying the impact of LUCs on SOC stocks. [ABSTRACT FROM AUTHOR]

Since 1950, European rivers have been put under increasing pressure by anthropogenic activities, resulting in changes in climate, land cover, soil properties and channel morphologies. These evolving environmental conditions can translate into changes in hydrological conditions. The availability of consistent estimates of river flow at global and continental level is a necessity to assess and attribute changes in the hydrological cycle. To overcome limitations posed by observations (incomplete records, inhomogeneous spatial coverage), we simulate river discharge for Europe for the period 1950 - 2020 using a state-of-the-art hydrological modelling approach. We use the new European set up of the LISFLOOD model, running at 1 arcminute (-1.8 km) with six-hourly time steps. The hydrological model is forced by climate reanalysis data (ERA5-land) bias-corrected and downscaled to the model resolution with weather observations. The model also ingests 72 surface fields maps representing catchment morphology, vegetation, soil properties, land use, water demand, lakes and reservoirs. Inputs related to human activities are evolving through time to emulate changes in society. The resulting Hydrological European ReAnalysis (HERA), provides sixhourly river discharge for 282 521 river pixels with upstream area > 100km2. We assess its skill using 2901 river gauging stations distributed across Europe. Overall, HERA delivers satisfying results, with a general weak underestimation of observed mean discharge and flow variability. We find that the performance of HERA increases through time between 1950 and 2020. The fine spatial and temporal resolution result in an enhanced performance compared to other reanalysis for small-to-medium-scale catchments (100-10 000 km2), with degraded performance remaining for small catchments. HERA is the first long-term, high resolution hydrological reanalysis for Europe. Despite its limitations, it enables the analysis of hydrological dynamics related to extremes, human influences, and climate change at a continental scale while keeping local relevance. It also creates the opportunity to study these dynamics in ungauged catchments across Europe. [ABSTRACT FROM AUTHOR]

Ecosystem benefits, now known as ecosystem services (ESs), confront continuous threats from human activities and lack adequate protection, often suffering degradation and destruction despite their inherent advantages. This paper aims to introduce the geosystem approach as an exact scientific basis for assessing ESs. By emphasizing the interconnectedness of abiotic and biotic components within ecosystems, this method involves in-depth research across landscape dimensions and socioeconomic factors influencing the utilization of ecosystem services (ESs). It highlights a deep understanding of their connections and interactions. The key operational units, termed landscape–ecological complexes or geoecological complexes, result from fundamental research. Their interpretation as potentially useful for the chosen ESs is already an applied procedure. ES assessment employs two approaches: participatory and biophysical assessments. The outcomes contribute to the development of management measures for preserving or enhancing ESs in the broader study area. Methodological procedures were tested in the Little Danube model area, a unique lowland stream in Central Europe's Rye Island and a significant drinking water reservoir. The assessment results provide a foundation, supporting arguments, and criteria for ecologically appropriate landscape planning, as well as the sustainable management, utilization, and conservation of natural resources. [ABSTRACT FROM AUTHOR]

The predicting groundwater nitrate pollution risk, especially in terms of changes in fertilizing, has not been fully investigated so far. In particular, there is no comprehensive method to assess this risk in areas of different land use type, and not only in agricultural areas. The aim of this study was to develop a novel multicriteria methodology for groundwater nitrate pollution risk assessment, which meets these issues. A further aim was to determine how much this risk would change if the amount of organic and synthetic fertilization was reduced. An assumption was that groundwater pollution risk is a combination of the potential adverse impacts of land use, fertilization, and intrinsic groundwater vulnerability to pollution. The impact of fertilization was holistically evaluated by balancing nitrogen from spatially differentiated the size of the breeding, species of livestock, manure and synthetic fertilizers input, and spatially differentiated topsoil, with nitrogen uptake by different crops. The nitrate concentration in the leachate was used as a measure of the impact of fertilization. This concentration was compared to the natural baseline nitrate concentration in groundwater. Three fertilization scenarios for groundwater pollution risk assessment in two study areas were discussed. Under typical agricultural, climatic, soil, and geological conditions in Europe for the current total fertilization level of 95-120 kg N ha−1 groundwater nitrate pollution risk is low and moderate, but for fertilization of 150-180 kg N ha−1, a reduction in the total fertilization (synthetic and manure) by 40 to 50% may be required to achieve low risk of degradation of natural groundwater quality. Predictive simulations of groundwater nitrate pollution risk confirmed that reducing synthetic and organic fertilization has an effect, especially in areas with intensive fertilization. This method may allow for a holistic and scenario-based assessment of groundwater pollution risk and may help decision-makers introduce solutions to manage this risk under conditions of climate change, preservation of groundwater quality, and food security. [ABSTRACT FROM AUTHOR]

Agrivoltaics is the dual use of land by combining agricultural crop production and photovoltaic (PV) systems. In this work, we have analyzed three different agrivoltaic configurations: static with optimal tilt, vertically mounted bifacial, and single‐axis horizontal tracking. A model is developed to calculate the shadowing losses on the PV panels along with the reduced solar irradiation reaching the area under them for different PV capacity densities. First, we investigate the trade‐offs using a location in Denmark as a case study and second, we extrapolate the analysis to the rest of Europe. We find that the vertical and single‐axis tracking produce more uniform irradiance on the ground, and a capacity density of around 30 W/m2 is suitable for agrivoltaic systems. Based on our model and a 100‐m‐resolution land cover database, we calculate the potential for agrivoltaic in every region within the European Union. The potential for agrivoltaic is enormous as the electricity generated by agrivoltaic systems could produce 25 times the current electricity demand in Europe. Overall, the potential capacity for agrivoltaic in Europe is 51 TW, which would result in an electricity yield of 71,500 TWh/year. [ABSTRACT FROM AUTHOR]

The climate is changing in Europe: average temperatures are increasing, and so is the frequency of extreme weather events. Climate change has a severe impact on areas suitable for growing certain crops and on food safety, for example, affecting the occurrence of the aflatoxin contamination of maize. The aim of this study was to obtain insights into the impact of climate change on possible changes in land use in Europe, particularly in areas suitable for maize cultivation, and on the probability of the mycotoxin contamination of maize in order to give directions for long-term adaptation to climate change. By combining a land use model and a mycotoxin prediction model, the suitability of land for maize cultivation and the probability of aflatoxin contamination were estimated for suitable areas in Europe, comparing the current climate with the 2050 scenario. In 2050, the occurrence of aflatoxin contamination in Europe is predicted to severely increase, especially in Central and Southern Europe. More northern regions, presently unsuitable for maize cultivation, will become suitable for maize cultivation in 2050. In the baseline scenario, most regions suitable for maize cultivation have a low probability of aflatoxin contamination, whereas in 2050, about half of the regions suitable for maize cultivation have a medium to high probability of aflatoxin contamination. Regions for safely growing maize for human consumption will shift from the southern to the northern half of Europe. [ABSTRACT FROM AUTHOR]

Hemp cultivation is becoming increasingly common worldwide, although it still raises many concerns. These plants are gaining popularity due to their versatility and the ability to use virtually every part of them in almost all economic branches. Hemp products are sought after and appreciated by consumers. The cultivation of hemp does not place a large burden on the environment. All this makes hemp an ideal plant in terms of land use, which is closely related to the idea of sustainable development. This paper describes the legal aspects of hemp cultivation in Europe and briefly presents its breeding and cultivation. The possibilities of their versatile use are presented, with particular reference to biofuel production. Moreover, the suitability for ecological cultivation, description of the economic and social aspects of industrial hemp cultivation, as well as future outlooks, are also described. [ABSTRACT FROM AUTHOR]

With immensely growing pressure on land and its scarcity, conflicting societal expectations concerning land use increasingly result in land use conflicts (LUCs). In this paper, we explore local LUCs, which we define as the complex situations, where fragmented planning policies encounter place-based societal conceptions and perceptions of site-specific developmental priorities. The paper adopts a dynamic approach and introduces a theory-driven typology of potentially conflicting planning decisions. The typology is employed as an analytic framework to reveal the open-ended successive planning decisions that lead to complex local LUCs. Two case studies from Central Europe are explored to narrate the evolutionary complexity of LUCs. Our results show that local LUCs emerged as the past planning decisions lined-up into a sequence creating lock-in situations, where different planning policies can be hardly reconciled. Finally, we discuss applicability, transferability and limits of the proposed typology as an analytic framework advancing management of planning conflicts. [ABSTRACT FROM AUTHOR]

Anthropogenic land use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently being extensively investigated within the World Climate Research Program (WCRP) Coordinated Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) Land Use and Climate Across Scales (LUCAS) using an ensemble of different regional climate models (RCMs) coupled with diverse land surface models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM–LSM simulations. To account for these needs, we generated the LUCAS Land Use and land Cover change (LUC) dataset version 1.1 at 0.1 ∘ resolution for Europe with annual LULC maps from 1950 to 2100 (10.26050/WDCC/LUC_hist_EU_v1.1, , 10.26050/WDCC/LUC_future_EU_v1.1,), which is tailored to use in state-of-the-art RCMs. The plant functional type (PFT) distribution for the year 2015 (i.e. the Modelling human LAND surface Modifications and its feedbacks on local and regional cliMATE – LANDMATE – PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details on the conversion method, cross-walking procedure, and evaluation of the LANDMATE PFT dataset are given in the companion paper by. Subsequently, we applied the land use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25 ∘ resolution as input for Coupled Modelling Intercomparison Project Phase 6 (CMIP6) experiments, to derive LULC distributions at high spatial resolution and at annual time steps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a land use translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to other annual LULCC datasets. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different shared socioeconomic pathway (SSP) and representative concentration pathway (RCP) combinations used in the framework of CMIP6. The resulting LULCC maps can be applied as land use forcing to the new generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions worldwide. [ABSTRACT FROM AUTHOR]

Understanding the main drivers of biodiversity loss in Europe's agricultural landscapes has been a research priority in the last decades. One of the most important factors promoting biodiversity in farmed landscapes is habitat heterogeneity, which has often proved crucial for avian species and communities. Birds are highly sensitive to environmental changes and make use of a broad range of ecological niches, thus being exceptionally sensitive to the loss of habitat heterogeneity. Remote sensing data are particularly suited to quantify habitat heterogeneity at fine scales over relatively large extents, allowing to consider how different measures of heterogeneity may affect biotic communities at a regional scale. Here, we used airborne LiDAR (Light Detection And Ranging) and satellite multispectral data to derive vegetation canopy height and primary productivity for 118 sites in complex agricultural landscapes in a region in the Central Alps. We computed different bird diversity indices and classified bird species into guilds according to specific traits to analyse the relationship between avian communities and different facets of habitat heterogeneity. Results confirmed that habitat heterogeneity is essential in shaping rich and diverse bird communities, and it is particularly important for several farmland birds. By comparing the effects of canopy height, primary productivity, and specific vegetation features (e.g., cover of grassland, shrub, and tree layers), we showed how different habitat characteristics as well as landscape heterogeneity affected bird richness, diversity, functional entropy, and trait patterns. Landscape and height heterogeneity, estimated by NDVI and LiDAR Rao's Q indices, strongly influenced all response variables, for example, high NDVI values promoted species diversity and ground-understory nesters, and shrub layer was important for ground-understory nesters and forest specialists. Finally, we provide recommendations for conservation practices and mitigation measures to improve bird diversity in agricultural landscapes. [ABSTRACT FROM AUTHOR]

We compare Holocene tree cover changes in Europe derived from a transient Earth system model simulation (Max Planck Institute Earth System Model – MPI-ESM1.2, including the land surface and dynamic vegetation model JSBACH) with high-spatial-resolution time slice simulations performed in the dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) and pollen-based quantitative reconstructions of tree cover based on the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. The dynamic vegetation models and REVEALS agree with respect to the general temporal trends in tree cover for most parts of Europe, with a large tree cover during the mid-Holocene and a substantially smaller tree cover closer to the present time. However, the decrease in tree cover in REVEALS starts much earlier than in the models, indicating much earlier anthropogenic deforestation than the prescribed land use in the models. While LPJ-GUESS generally overestimates tree cover compared to the reconstructions, MPI-ESM indicates lower percentages of tree cover than REVEALS, particularly in central Europe and the British Isles. A comparison of the simulated climate with chironomid-based climate reconstructions reveals that model–data mismatches in tree cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments indicate that the model results strongly depend on the tuning of the models regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid for past climate and vegetation states totally different from today's. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present-day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model–data comparisons with additional challenges. Moreover, our study suggests that land use is the main driver of forest decline in Europe during the mid-Holocene and late Holocene. [ABSTRACT FROM AUTHOR]

This paper studies the impact of land use and land cover change (LULCC) on the climate around 2500 years ago (2.5 ka), a period of rapid transitions across the European landscape. One global climate model was used to force two regional climate models (RCMs). The RCMs used two land cover descriptions. The first was from a dynamical vegetation model representing potential land cover, and the second was from a land cover description reconstructed from pollen data by statistical interpolation. The two different land covers enable us to study the impact of land cover on climate conditions. Since the difference in landscape openness between potential and reconstructed land cover is mostly due to LULCC, this can be taken as a measure of early anthropogenic effects on climate. Since the sensitivity to LULCC is dependent on the choice of climate model, we also use two RCMs. The results show that the simulated 2.5 ka climate was warmer than the simulated pre-industrial (PI, 1850 CE) climate. The largest differences are seen in northern Europe, where the 2.5 ka climate is 2–4 ∘ C warmer than the PI period. In summer, the difference between the simulated 2.5 ka and PI climates is smaller (0–3 ∘ C), with the smallest differences in southern Europe. Differences in seasonal precipitation are mostly within ± 10 %. In parts of northern Europe, the 2.5 ka climate is up to 30 % wetter in winter than that of the PI climate. In summer there is a tendency for the 2.5 ka climate to be drier than the PI climate in the Mediterranean region. The results also suggest that LULCC at 2.5 ka impacted the climate in parts of Europe. Simulations including reconstructed LULCC (i.e. those using pollen-derived land cover descriptions) give up to 1 ∘ C higher temperature in parts of northern Europe in winter and up to 1.5 ∘ C warmer in southern Europe in summer than simulations with potential land cover. Although the results are model dependent, the relatively strong response implies that anthropogenic land cover changes that had occurred during the Neolithic and Bronze Age could have affected the European climate by 2.5 ka. [ABSTRACT FROM AUTHOR]

South rear-edge populations of widely distributed temperate and boreal tree species such as birches (Betula pubescens and Betula pendula) are considered particularly vulnerable to climate warming, and at the same time, they constitute genetic reservoirs of drought-adapted ecotypes. Here, we compared radial growth patterns and responses to climate, river, or reservoir flows and a drought index of rear-edge (southernmost) populations (Toledo Mountains, central-southern Spain) with populations located in northern Spain of B. pubescens and B. pendula. Then, we performed a comparative analysis across Europe of B. pendula populations. The main climatic constraint of birch growth was a high summer water deficit, although the effect of local hydrological conditions was particularly important in rear-edge populations. We found declining growth trends in rear-edge stands dating from the early 21st century, related to decreasing water availability and increasing aridity. Our results also suggested distinct growth patterns and climate-growth associations of B. pendula across Europe that show how populations further south and in warmer locations were more sensitive to drought stress. Drought-induced growth decline can be exacerbated by local human land uses, leading to reduced river inflow, thus endangering birch populations at their southern distribution limit. Protection of threatened rear-edge birch populations requires adequate management of local water resources. [ABSTRACT FROM AUTHOR]

Understanding the influence of climate change on past extreme weather impacts is a vital research task. However, the effects of climate change are obscured in the observed impact data series due to the rapid evolution of the social and economic circumstances in which the events occurred. The HANZE v2.0 (Historical Analysis of Natural HaZards in Europe) dataset presented in this study quantifies the evolution of key socioeconomic drivers in Europe since 1870, namely land use, population, economic activity and assets. It consists of algorithms to reallocate baseline (2011) land use and population for any given year based on a large collection of historical subnational- and national-level statistics, and then disaggregate data on production and tangible assets by economic sector into a high-resolution grid. Raster datasets generated by the model enable reconstructing exposure within the footprint of any extreme event both at the time of occurrence and anytime between 1870 and 2020. This allows the separation of the effects of climate change from the effects of exposure change. [ABSTRACT FROM AUTHOR]

Wildfires are key drivers of land use/land cover (LULC) dynamics by burning vegetation and affecting human infrastructure. On the contrary, LULC changes (LULCCs) may affect the fire regime by influencing vegetation type, burnable areas, fuel loads and continuity. This study investigates the relationship between LULCC and wildfires. We developed a methodology based on different indicators, which allowed us to quantitatively assess and better understand the transitions between LULC classes and burnt area (BA) in Europe in the last two decades (2000–2019). The assessment was performed for the entire European continent and, independently, for each of the five European countries most affected by wildfires: Portugal, Spain, France, Italy and Greece. The main results are the following: (i) LULCC analysis revealed a net loss in forests and arable land and a net gain in shrubs; (ii) most of the BA occurred in forests (42% for the whole of Europe), especially in coniferous forests; (iii) transitions from BA generally were to transitional woodland/shrub or, again, to BA. Overall, our results confirm the existence of a strong relationship between wildfires and LULCCs in Europe, which was quantified in the present study. These findings are of paramount importance in fire and environmental system management and ecology. [ABSTRACT FROM AUTHOR]

Land-use intensification and climate change threaten ecosystem functions. A fundamental, yet often overlooked, function is decomposition of necromass. The direct and indirect anthropogenic effects on decomposition, however, are poorly understood. We measured decomposition of two contrasting types of necromass, rat carrion and bison dung, on 179 study sites in Central Europe across an elevational climate gradient of 168–1122 m a.s.l. and within both local and regional land uses. Local land-use types included forest, grassland, arable fields, and settlements and were embedded in three regional land-use types (near-natural, agricultural, and urban). The effects of insects on decomposition were quantified by experimental exclusion, while controlling for removal by vertebrates. We used generalized additive mixed models to evaluate dung weight loss and carrion decay rate along elevation and across regional and local land-use types. We observed a unimodal relationship of dung decomposition with elevation, where greatest weight loss occurred between 600 and 700 m, but no effects of local temperature, land use, or insects. In contrast to dung, carrion decomposition was continuously faster with both increasing elevation and local temperature. Carrion reached the final decomposition stage six days earlier when insect access was allowed, and this did not depend on land-use effect. Our experiment identified different major drivers of decomposition on each necromass form. The results show that dung and carrion decomposition are rather robust to local and regional land use, but future climate change and decline of insects could alter decomposition processes and the self-regulation of ecosystems. [ABSTRACT FROM AUTHOR]

Large‐scale bioenergy plays a key role in climate change mitigation scenarios, but its efficacy is uncertain. This study aims to quantify that uncertainty by contrasting the results of three different types of models under the same mitigation scenario (RCP2.6‐SSP2), consistent with a 2°C temperature target. This analysis focuses on a single bioenergy feedstock, Miscanthus × giganteus, and contrasts projections for its yields and environmental effects from an integrated assessment model (IMAGE), a land surface and dynamic global vegetation model tailored to Miscanthus bioenergy (JULES) and a bioenergy crop model (MiscanFor). Under the present climate, JULES, IMAGE and MiscanFor capture the observed magnitude and variability in Miscanthus yields across Europe; yet in the tropics JULES and IMAGE predict high yields, whereas MiscanFor predicts widespread drought‐related diebacks. 2040–2049 projections show there is a rapid scale up of over 200 Mha bioenergy cropping area in the tropics. Resulting biomass yield ranges from 12 (MiscanFor) to 39 (JULES) Gt dry matter over that decade. Change in soil carbon ranges from +0.7 Pg C (MiscanFor) to −2.8 Pg C (JULES), depending on preceding land cover and soil carbon.2090–99 projections show large‐scale biomass energy with carbon capture and storage (BECCS) is projected in Europe. The models agree that <2°C global warming will increase yields in the higher latitudes, but drought stress in the Mediterranean region could produce low yields (MiscanFor), and significant losses of soil carbon (JULES and IMAGE). These results highlight the uncertainty in rapidly scaling‐up biomass energy supply, especially in dry tropical climates and in regions where future climate change could result in drier conditions. This has important policy implications—because prominently used scenarios to limit warming to 'well below 2°C' (including the one explored here) depend upon its effectiveness. [ABSTRACT FROM AUTHOR]

The agriculture sector can contribute to climate change mitigation by reducing its own greenhouse gas (GHG) emissions, sequestering carbon in vegetation and soils, and providing biomass to substitute for fossil fuels and other GHG‐intensive products. The sector also needs to address water, soil, and biodiversity impacts caused by historic and current practices. Emerging EU policies create incentives for cultivation of perennial plants that provide biomass along with environmental benefits. One such option, common in northern Europe, is to include grass in rotations with annual crops to provide biomass while remediating soil organic carbon (SOC) losses and other environmental impacts. Here, we apply a spatially explicit model on >81,000 sub‐watersheds in EU27 + UK (Europe) to explore the effects of widespread deployment of such systems. Based on current accumulated SOC losses in individual sub‐watersheds, the model identifies and quantifies suitable areas for increased grass cultivation and corresponding biomass‐ and protein supply, SOC sequestration, and reductions in nitrogen emissions to water as well as wind and water erosion. The model also provides information about possible flood mitigation. The results indicate a substantial climate mitigation potential, with combined annual GHG savings from soil‐carbon sequestration and displacement of natural gas with biogas from grass‐based biorefineries, equivalent to 13%–48% of current GHG emissions from agriculture in Europe. The environmental co‐benefits are also notable, in some cases exceeding the estimated mitigation needs. Yield increases for annual crops in modified rotations mitigate the displacement effect of increasing grass cultivation. If the grass is used as feedstock in lieu of annual crops, the displacement effect can even be negative, that is, a reduced need for annual crop production elsewhere. Incentivizing widespread deployment will require supportive policy measures as well as new uses of grass biomass, for example, as feedstock for green biorefineries producing protein concentrate, biofuels, and other bio‐based products. [ABSTRACT FROM AUTHOR]

Land use and cover (LUC) of southern European mountains is dramatically changing, mainly due to observed socioeconomic demands and climatic changes. It is therefore important to understand LUC changes to accurately predict future landscapes and their threats. Simulation models of LUC change are ideal for this task because they allow the in silico experimentation under different socioeconomic and climatic scenarios. In the present study, we employed the trans-CLUE-S model, to predict for 2055 the LUC of a typical southern European sub-mountainous area, which has experienced widespread abandonment until recently. Four demand scenarios were tested, and under each demand scenario, we compared three climatic scenarios, ranging from less to more warm and dry conditions. We found that farmland declined from 3.2% of the landscape in 2015 to 0.4% in 2055 under the business-as-usual demand scenario, whereas forest further increased from 62.6% to 79%. For any demand scenario, differences in LUC between maps predicted under different climatic scenarios constituted less than 10% of the landscape. In the less than 10% that differed, mainly farmland and forest shifted to higher elevation under a warmer and drier climate, whereas grassland and scrubland to lower. Such insights by modelling analyses like the present study's can improve the planning and implementation of management and restoration policies which will attempt to conserve ecosystem services and mitigate the negative effects of socioeconomic and climatic changes in the mountainous regions of southern Europe. [ABSTRACT FROM AUTHOR]

Anthropogenic land-use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently extensively investigated within the WCRP CORDEX Flagship Pilot Study (FPS) LUCAS - "Land Use and Climate Across Scales" using an ensemble of different Regional Climate Models (RCMs) coupled with diverse Land Surface Models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM-LSM simulations. To account for these needs, we generated the LUCAS LUC dataset Version 1.1 at 0.1° resolution for Europe with annual LULC maps from 1950-2100 (Hoffmann et al., 2022b, a), which is tailored towards the use in state-of-the-art RCMs. The plant functional type distribution (PFT) for the year 2015 (i.e., LANDMATE PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details about the conversion method, cross-walking procedure and the evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (2022b). Subsequently, we applied the land-use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25? resolution as input for CMIP6 experiments, to derive LULC distribution at high spatial resolution and at annual timesteps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a Land Use Translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to other annual LULCC datasets. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the Coupled Modelling Intercomparison Project Phase 6 (CMIP6). The resulting LULCC maps can be applied as land use forcing to the new generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions world-wide. [ABSTRACT FROM AUTHOR]

Land use, land resource demands, and landscape management practices are linked to many of the environmental, climatic, and socio-economic challenges faced by contemporary society. The study focuses on a comparative analysis of the experience of the land resource management (LRM); thus, the study aims respond to how the land-related resources are managed, what policy instruments support it, and what improvements would promote the sustainable management of these resources. Exploring LRM policies in selected countries, the experience of three Baltic countries and two other countries under the jurisdiction of continental Europe was analyzed, and their comparison was made based on qualitative research methodology. Based on the study's results, the most important comparative characteristics of LRM policies are discussed. The findings of the study in selected countries provide recommendations for improving the institutional framework related to LRM. However, the outcome encourages a transfer of the research experience to other jurisdictions. [ABSTRACT FROM AUTHOR]

The phyllosphere harbours a diverse and specific bacterial community, which influences plant health and ecosystem functioning. In this study, we investigated the impact of urban green areas connectivity and size on the composition and diversity of phyllosphere bacterial communities. Hereto, we evaluated the diversity and composition of phyllosphere bacterial communities of 233 Platanus x acerifolia and Acer pseudoplatanus trees in 77 urban green areas throughout 6 European cities. The community composition and diversity significantly differed between cities but only to a limited extent between tree species. We could show that urban intensity correlated significantly with the community composition of phyllosphere bacteria. In particular, a significant correlation was found between the relative abundances for 29 out of the 50 most abundant families and the urban intensity: the abundances of classic phyllosphere families, such as Acetobacteraceae , Planctomycetes , and Beijerinkiaceae , decreased with urban intensity (i.e. more abundant in areas with more green, lower air pollution, and lower temperature), while those related to human activities, such as Enterobacteriaceae and Bacillaceae , increased with urban intensity. The results of this study suggest that phyllosphere bacterial communities in European cities are associated with urban intensity and that effect is mediated by several combined stress factors. [ABSTRACT FROM AUTHOR]

Afforestation can make an important contribution mitigating the effects of changing climate and provide structural and functional benefits. Afforestation also provides challenges for forest managers connected with past land-use history; therefore, there is an urgent need to summarize knowledge about such habitats and point out the gaps in knowledge for planning future studies. Although post-agricultural forests cover a large forest area in Europe, our understanding of the mechanisms governing the below-ground environment is still poor, especially when soil fauna is considered. In this study, we revised knowledge about the soil environment and the response of soil fauna to afforestation on former agricultural lands located in Europe based on research articles from the ISI Web of Science database. Data came from various but distinct locations, compared forests with different types of agricultural lands, and presented previous knowledge about soil chemistry and accompanying soil fauna communities. Finally, we selected 15 studies, investigating soil fauna communities on post-agricultural lands. The meta-analysis was based on response ratio (R) for available data, although in many cases the data were incomplete. Results indicated that post-agricultural forests differ from arable lands in reference to soil pH, but not for soil organic matter and carbon content. Different soil animal groups were represented by a similar number of studies: microfauna (seven studies) and mesofauna (nine), whereas macrofauna were represented by five studies. Meta-analysis revealed that the response of soil fauna to afforestation differed between soil fauna size classes. Additionally, in total, 18 tree species, 12 soil types, and 20 soil parameters were provided in the literature but only a few of them were presented in a single study. Future studies should include the impact of microclimate, detailed stand characteristics and soil conditions, which could help to clearly describe the impact of certain tree species growing on certain soil types. In future soil fauna ecological studies, the data should include mean values, standard deviation (SD) and/or standard effort of means (SE) for abundance, species richness, diversity indices and number of collected samples. Providing the above mentioned information will give the broad audience the opportunity to include data in future comparative analyses. [ABSTRACT FROM AUTHOR]

Soil protists have vital roles as major microbiome predators in soil functioning and plant performance. Protists are also suggested to be the most responsive microbial group to external changes, such as anthropogenic land use types. While protists were long used as models for biogeography such as to investigate if 'everything is everywhere' among microbes, their biogeography at the taxonomic level has never been explored in depth at the continental scale and linked to anthropogenic drivers. Here we evaluated how land-use types affect the diversity and structure of soil protist communities across 885 locations in Europe based on the European Commission's Land Use and Coverage Area frame Survey (LUCAS). We observed higher α-diversity of soil protists but lower community structure dissimilarity (β-diversity) in croplands compared with woodlands, with grasslands in an intermediate position. The diversity of protist groups with a broader spatial niche was higher in croplands, whereas taxa with a narrower niche increased in woodlands. The importance of climate factors on α-diversity variations reduced as land use intensity increased, but the opposite trend was observed for the effect of soil properties. Our study suggests that there is an interaction between land use type, environmental effects, and spatial niche attributes of soil protist groups, highlighting the importance of land-use type on the dynamics of protist communities. • Land use intensity affect α- and β-diversity of soil protist groups in an opposite manner. • There were interactions between environmental effects and land use types on α-diversity. • Generalist protists tend to be more diverse in more intensive land use types. [ABSTRACT FROM AUTHOR]

Understanding and quantifying the influence of climate change on past extreme weather impacts is vital for climate litigation, the loss and damage debate, and for building more accurate models to assess future impacts. However, the effects of climate change are obscured in the observed impact data series due to the rapid evolution of the social and economic circumstances in which the extreme events occurred. The model and data presented in this study (HANZE v2.0) aims at quantifying the evolution of key socioeconomic drivers in Europe since 1870, namely land use, population, economic activity and assets. It consists of algorithms to reallocate baseline (2011) land use and population for any given year based on a large collection of historical subnational- and national-level statistics, and then disaggregate data on production and tangible assets by economic sector into a high-resolution grid. Maps generated by the model enable reconstructing exposure within the footprint of any extreme event both at the time of the event and in any other moment in the past 150 years. This allows the separation of the effects of climate change from the effects of exposure change. In addition, HANZE v2.0 can be used for assessing socio-economic influences on hazard (e.g. effects of land use-change on hydrological extremes) and vulnerability (e.g. the changing structure of assets at risk). [ABSTRACT FROM AUTHOR]

Accurate maps of past land cover and human land use are necessary for studying the impact of anthropogenic land‐cover changes, such as deforestation, on the climate. The maps of past land cover should ideally be separated into naturally occurring vegetation and human‐induced changes, thereby enabling the quantification of the effect of human land use on the past climate. We developed a Bayesian hierarchical model that combines fossil pollen‐based reconstructions of actual land cover with estimates of past human land use. The model interpolates the fractions of unforested land as well as coniferous and broadleaved forest from the pollen data, and uses the human land‐use estimates to decompose the unforested land into natural vegetation and human deforestation. This results in maps of both natural and human‐induced vegetation, which can be used by climate modelers to quantify the influence of deforestation on the past climate. The model was applied to five time periods from 1900 CE to 4000 BCE over Europe. The model uses a latent Gaussian Markov random field (GMRF) for the interpolation and Markov chain Monte Carlo for the estimation. The sparse precision matrix of the GMRF, together with an adaptive Metropolis‐adjusted Langevin step, allows for rapid inference. [ABSTRACT FROM AUTHOR]

The use of in situ references in Earth observation monitoring is a fundamental need. LUCAS (Land Use and Coverage Area frame Survey) is an activity that has performed repeated in situ surveys over Europe every three years since 2006. The dataset is unique in many aspects; however it is currently not available through a standardized interface, machine-to-machine. Moreover, the evolution of the surveys limits the performance of change analysis using the dataset. Our objective was to develop an open-source system to fill these gaps. This paper presents a developed system solution for the LUCAS in situ data harmonization and distribution. We have designed a multi-layer client-server system that may be integrated into end-to-end workflows. It provides data through an OGC (Open Geospatial Consortium) compliant interface. Moreover, a geospatial user may integrate the data through a Python API (Application Programming Interface) to ease the use in workflows with spatial, temporal, attribute, and thematic filters. Furthermore, we have implemented a QGIS plugin to retrieve the spatial and temporal subsets of the data interactively. In addition, the Python API includes methods for managing thematic information. The system provides enhanced functionality which is demonstrated in two use cases. [ABSTRACT FROM AUTHOR]

Lateral carbon transport from soils to the ocean through rivers has been acknowledged as a key component of the global carbon cycle, but it is still neglected in most global land surface models (LSMs). Fluvial transport of dissolved organic carbon (DOC) and CO 2 has been implemented in the ORCHIDEE LSM, while erosion-induced delivery of sediment and particulate organic carbon (POC) from land to river was implemented in another version of the model. Based on these two developments, we take the final step towards the full representation of biospheric carbon transport through the land–river continuum. The newly developed model, called ORCHIDEE-C lateral , simulates the complete lateral transport of water, sediment, POC, DOC, and CO 2 from land to sea through the river network, the deposition of sediment and POC in the river channel and floodplains, and the decomposition of POC and DOC in transit. We parameterized and evaluated ORCHIDEE-C lateral using observation data in Europe. The model explains 94 %, 75 %, and 83 % of the spatial variations of observed riverine water discharges, bankfull water flows, and riverine sediment discharges in Europe, respectively. The simulated long-term average total organic carbon concentrations and DOC concentrations in river flows are comparable to the observations in major European rivers, although our model generally overestimates the seasonal variation of riverine organic carbon concentrations. Application of ORCHIDEE-C lateral for Europe reveals that the lateral carbon transfer affects land carbon dynamics in multiple ways, and omission of this process in LSMs may lead to an overestimation of 4.5 % in the simulated annual net terrestrial carbon uptake over Europe. Overall, this study presents a useful tool for simulating large-scale lateral carbon transfer and for predicting the feedbacks between lateral carbon transfer and future climate and land use changes. [ABSTRACT FROM AUTHOR]

Land Use/Land Cover (LULC) maps can be effectively produced by cost-effective and frequent satellite observations. Powerful cloud computing platforms are emerging as a growing trend in the high utilization of freely accessible remotely sensed data for LULC mapping over large-scale regions using big geodata. This study proposes a workflow to generate a 10 m LULC map of Europe with nine classes, ELULC-10, using European Sentinel-1/-2 and Landsat-8 images, as well as the LUCAS reference samples. More than 200 K and 300 K of in situ surveys and images, respectively, were employed as inputs in the Google Earth Engine (GEE) cloud computing platform to perform classification by an object-based segmentation algorithm and an Artificial Neural Network (ANN). A novel ANN-based data preparation was also presented to remove noisy reference samples from the LUCAS dataset. Additionally, the map was improved using several rule-based post-processing steps. The overall accuracy and kappa coefficient of 2021 ELULC-10 were 95.38% and 0.94, respectively. A detailed report of the classification accuracies was also provided, demonstrating an accurate classification of different classes, such as Woodland and Cropland. Furthermore, rule-based post processing improved LULC class identifications when compared with current studies. The workflow could also supply seasonal, yearly, and change maps considering the proposed integration of complex machine learning algorithms and large satellite and survey data. [ABSTRACT FROM AUTHOR]

Seasonal snow cover plays a major role in the climate system of the Northern Hemisphere via its effect on land surface albedo and fluxes. In climate models the parameterization of interactions between snow and atmosphere remains a source of uncertainty and biases in the representation of local and global climate. Here, we evaluate the ability of an ensemble of regional climate models (RCMs) coupled with different land surface models to simulate snow–atmosphere interactions over Europe in winter and spring. We use a previously defined index, the snow-albedo sensitivity index (SASI), to quantify the radiative forcing associated with snow cover anomalies. By comparing RCM-derived SASI values with SASI calculated from reanalyses and satellite retrievals, we show that an accurate simulation of snow cover is essential for correctly reproducing the observed forcing over middle and high latitudes in Europe. The choice of parameterizations, and primarily the choice of the land surface model, strongly influences the representation of SASI as it affects the ability of climate models to simulate snow cover accurately. The degree of agreement between the datasets differs between the accumulation and ablation periods, with the latter one presenting the greatest challenge for the RCMs. Given the dominant role of land surface processes in the simulation of snow cover during the ablation period, the results suggest that, during this time period, the choice of the land surface model is more critical for the representation of SASI than the atmospheric model. [ABSTRACT FROM AUTHOR]

In recent years, regulatory agencies in the USA and Europe have begun to require documentation that land used to produce crops and biofuels has not been converted from carbon-capturing grasslands or forests. Precise measurement of these land cover changes, however, has proven difficult. Analysis to date has focused primarily on moderate resolution (30 m) satellite imagery, which has not provided the land cover granularity or accuracy needed. These studies have estimated large-scale land conversion to crops in the USA. This study analyzed the satellite datasets but included tabular datasets and aerial imagery of the USA to determine whether the combination of datasets, focusing on more detailed analysis in these locations, could more accurately identify potential locations of land use change. Analyses of satellite imagery data from 1985 to 2020 found that much of the land that 2008 to 2020 satellite datasets classified as natural-to-crop land change was idle cropland. The results indicate a dynamic landscape of marginal land moving in and out of cropland. Approximately as much land was allowed to go fallow (6145 hectares) as land going into crop (7901 hectares) from 1985 to 2020. The results from this study indicate regulatory agencies could more accurately measure the impacts of conversion of natural lands to crop if long-term historical land cover/land use was also analyzed. [ABSTRACT FROM AUTHOR]

Background. The accuracy of predictions of invasive species ranges is dependent on niche similarity between invasive and native populations and on our ability to identify the niche characteristics. With this work we aimed to compare the niche dynamics of two genetically related invasive populations of Vespa velutina (an effective predator of honeybees and wild pollinators), in two distinct climatic regions, one in central Europe and another one in the north-western Iberian Peninsula, and hence to identify uninvaded regions susceptible to invasion. Methods. Niche dynamics and shifts of V. velutina were assessed by comparing the environmental niches of the native and of the two invasive populations, using climatic, topographic and land use variables. We also ran reciprocal distribution models using different algorithms and records from both native and invasive ranges to compare model predictions and estimate which regions are at a greater risk of being invaded. Results. An apparent niche shift was detected in the population of the NW of Iberian Peninsula, where the species is living under environmental conditions different from the native niche. In central Europe, large suitable areas remain unoccupied. The fact that both invasive populations are well established, despite occupying environmentally distinct regions indicates that V. velutina has a high ability to successfully invade different environmental envelopes from those existing in its native range. For example, in north-western Iberian Peninsula the species is now thriving out of its native niche limits. Moreover, the large extent of still unoccupied environmental space with similar conditions to those used by the species in its native range suggests that there is still a large area of central and eastern Europe that can be potentially invaded by the species. [ABSTRACT FROM AUTHOR]

Sustainable biofuels are an important tool for the decarbonisation of transport. This is especially true in aviation, maritime, and heavy-duty sectors with limited short-term alternatives. Their use by conventional transport fleets requires few changes to the existing infrastructure and engines, and thus their integration can be smooth and relatively rapid. Provision of feedstock should comply with sustainability principles for (i) producing additional biomass without distorting food and feed markets and (ii) addressing challenges for ecosystem services, including biodiversity, and soil quality. This paper performs a meta-analysis of current research for low indirect land use change (ILUC) risk biomass crops for sustainable biofuels that benefited either from improved agricultural practices or from cultivation in unused, abandoned, or severely degraded land. Two categories of biomass crops are considered here: oil and lignocellulosic. The findings confirm that there are significant opportunities to cultivate these crops in European agro-ecological zones with sustainable agronomic practices both in farming land and in land with natural constraints (unused, abandoned, and degraded land). These could produce additional low environmental impact feedstocks for biofuels and deliver economic benefits to farmers. [ABSTRACT FROM AUTHOR]

The concept of plant functional types (PFTs) is shown to be beneficial in representing the complexity of plant characteristics in land use and climate change studies using regional climate models (RCMs). By representing land use and land cover (LULC) as functional traits, responses and effects of specific plant communities can be directly coupled to the lowest atmospheric layers. To meet the requirements of RCMs for realistic LULC distribution, we developed a PFT dataset for Europe (LANDMATE PFT Version 1.0; http://doi.org/10.26050/WDCC/LM%5fPFT%5fLandCov%5fEUR2015%5fv1.0 ,). The dataset is based on the high-resolution European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset and is further improved through the additional use of climate information. Within the LANDMATE – LAND surface Modifications and its feedbacks on local and regional cliMATE – PFT dataset, satellite-based LULC information and climate data are combined to create the representation of the diverse plant communities and their functions in the respective regional ecosystems while keeping the dataset most flexible for application in RCMs. Each LULC class of ESA-CCI is translated into PFT or PFT fractions including climate information by using the Holdridge life zone concept. Through consideration of regional climate data, the resulting PFT map for Europe is regionally customized. A thorough evaluation of the LANDMATE PFT dataset is done using a comprehensive ground truth database over the European continent. The assessment shows that the dominant LULC types, cropland and woodland, are well represented within the dataset, while uncertainties are found for some less represented LULC types. The LANDMATE PFT dataset provides a realistic, high-resolution LULC distribution for implementation in RCMs and is used as a basis for the Land Use and Climate Across Scales (LUCAS) Land Use Change (LUC) dataset which is available for use as LULC change input for RCM experiment set-ups focused on investigating LULC change impact. [ABSTRACT FROM AUTHOR]

Land cover in sub-polar and alpine regions of northern and eastern Europe have already begun changing due to natural and anthropogenic changes such as afforestation. This will impact the regional climate and hydrology upon which societies in these regions are highly reliant. This study aims to identify the impacts of afforestation/reforestation (hereafter afforestation) on snow and the snow-albedo effect and highlight potential improvements for future model development. The study uses an ensemble of nine regional climate models for two different idealised experiments covering a 30-year period; one experiment replaces most land cover in Europe with forest, while the other experiment replaces all forested areas with grass. The ensemble consists of nine regional climate models composed of different combinations of five regional atmospheric models and six land surface models. Results show that afforestation reduces the snow-albedo sensitivity index and enhances snowmelt. While the direction of change is robustly modelled, there is still uncertainty in the magnitude of change. The greatest differences between models emerge in the snowmelt season. One regional climate model uses different land surface models which shows consistent changes between the three simulations during the accumulation period but differs in the snowmelt season. Together these results point to the need for further model development in representing both grass–snow and forest–snow interactions during the snowmelt season. Pathways to accomplishing this include (1) a more sophisticated representation of forest structure, (2) kilometre-scale simulations, and (3) more observational studies on vegetation–snow interactions in northern Europe. [ABSTRACT FROM AUTHOR]

Climate plays a major role in shaping biodiversity patterns over time and space, with ongoing changes leading to the reorganization of ecosystems, which challenges conservation initiatives. Identifying areas that could serve as possible climate change refugia for future biodiversity is, thus, critical for both conservation and management. Here, we identify potential future climatic refugia within the Euro‐Mediterranean biome, which is a global biodiversity hotspot, while accounting for multiple emission climate change projections over the next 50 years. We developed two metrics of climatic variability: temporal stability and spatial heterogeneity. We then used a systematic conservation planning approach to identify climate‐based priority areas. While we used a climate‐based, species‐neutral methodology, we deliberately implemented low climatic velocity thresholds, so that the identified climatic refugia would even be compatible with the needs of species with low dispersal capacity, such as plants. Our projections showed that future climatic refugia would be more frequently observed in mid‐altitudes, for gradients with steep elevations, and mainly in the eastern part of the Euro‐Mediterranean biome, with possible conflicts with existing land uses and future conservation implications. Climatic, land use, and topography results indicated that only a limited number of refugia would be hosted by high elevation habitats (>1500 m), raising possible concerns about the biodiversity of Mediterranean mountain regions. Our analyses show that the current network of protected areas captures future climatic refugia disproportionally, despite their importance for safeguarding present and future biodiversity in the Mediterranean. Key climatic refugia could limit the impacts of future climate change on biodiversity in mid‐altitude and mountainous regions, and should be included in management guidelines for a climate‐ready conservation design in the Mediterranean biome. [ABSTRACT FROM AUTHOR]

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions. • Complete networks exhibited higher robustness than incomplete ones. • Cropland in summer and forest in autumn and summer exhibited the lowest robustness. • Connectivity of complete networks was controlled mostly by stochasticity than determinism. • Stochasticity was higher in forest (natural soil) than cropland (man-affected soils). • Stochasticity implies the necessity for more proactive management practices and less remedial actions. [ABSTRACT FROM AUTHOR]

Land use is a key factor driving changes in soil carbon (C) cycle and contents worldwide. The priming effect (PE)—CO2 emissions from changed soil organic matter decomposition in response to fresh C inputs—is one of the most unpredictable phenomena associated with C cycling and related nutrient mobilization. Yet, we know very little about the influence of land use on soil PE across contrasting environments. Here, we conducted a continental‐scale study to (i) determine the PE induced by 13C‐glucose additions to 126 cropland and seminatural (forests and grasslands) soils from 22 European countries; (ii) compare PE magnitude in soils under various crop types (i.e., cereals, nonpermanent industrial crops, and orchards); and (iii) model the environmental factors influencing PE. On average, PEs were negative in seminatural (with values ranging between −60 and 26 µg C g−1 soil after 35 days of incubation; median = −11) and cropland (from −55 to 27 µC g−1 soil; median = −4.3) soils, meaning that microbial communities preferentially switched from soil organic C decomposition to glucose mineralization. PE was significantly less negative in croplands compared with seminatural ecosystems and not influenced by the crop type. PE was driven by soil basal respiration (reflecting microbial activity), microbial biomass C, and soil organic C, which were all higher in seminatural ecosystems compared with croplands. This cross European experimental and modeling study elucidated that PE intensity is dependent on land use and allowed to clarify the factors regulating this important C cycling process. [ABSTRACT FROM AUTHOR]

Human-induced salinization caused by the use of road deicing salts, agricultural practices, mining operations, and climate change is a major threat to the biodiversity and functioning of freshwater ecosystems. Yet, it is unclear if freshwater ecosystems are protected from salinization by current water quality guidelines. Leveraging an experimental network of land-based and in-lake mesocosms across North America and Europe, we tested how salinization— indicated as elevated chloride (Cl2) concentration—will affect lake food webs and if two of the lowest Cl2 thresholds found globally are sufficient to protect these food webs. Our results indicated that salinization will cause substantial zooplankton mortality at the lowest Cl2 thresholds established in Canada (120 mg Cl2/L) and the United States (230 mg Cl2/L) and throughout Europe where Cl2 thresholds are generally higher. For instance, at 73% of our study sites, Cl2 concentrations that caused a ≥50% reduction in cladoceran abundance were at or below Cl2 thresholds in Canada, in the United States, and throughout Europe. Similar trends occurred for copepod and rotifer zooplankton. The loss of zooplankton triggered a cascading effect causing an increase in phytoplankton biomass at 47% of study sites. Such changes in lake food webs could alter nutrient cycling and water clarity and trigger declines in fish production. Current Cl2 thresholds across North America and Europe clearly do not adequately protect lake food webs. Water quality guidelines should be developed where they do not exist, and there is an urgent need to reassess existing guidelines to protect lake ecosystems from human-induced salinization. [ABSTRACT FROM AUTHOR]

The droughts that hit North and North Western Europe in 2018 and 2019 served as a wake-up call that temperate regions are also affected by these kinds of slow progressing or creeping disasters. Long-term drivers, such as land-use changes, may have exacerbated the impacts of these meteorological droughts. These changes, which are spread over a long time span, may even be difficult to perceive for an individual, but make a big difference in how these rare weather events impact a region. In this paper, we introduce three long-term drivers: forest fires in Europe, global urbanisation, and global deforestation. We attempt to provide a first assessment of their trends, mainly using statistics derived from satellite imagery published in recent literature. Due to the complexity of drought impacts, and the scarcity of quantitative impact data, the relationship between drought impact and these three processes for land use change is difficult to quantify; however, hence we present a survey of the recent trends in these land use change processes and the possible mechanics by which they affect drought impacts. Based on this survey we can conclude that the extent and the number of wildfires have increased markedly in Europe since 2010. Deforestation is still occurring in the tropics, with a loss of 12% in the last 30 years but has halted in the northern regions. Urbanisation has more than doubled in the same time span in the tropics and subtropics, mostly at the expense of forests, while in Europe urbanisation took place mainly in the northern part of the continent. We can conclude that none of these implicit drought drivers followed a favourable trend in the last 30 years. With consistent and worldwide monitoring, for example, by using satellite imagery, we can regularly inform the scientific community on the trends in these drought impact affecting processes, thus helping decision makers to understand how far we have progressed in making the world resilient to drought impacts. [ABSTRACT FROM AUTHOR]

New High-Speed Rail stations are often expected to act as catalysts for regional and local urban and economic development. Accessibility improvements are assumed to increase locational attractiveness for households and companies, motivating municipal decision-makers to allocate land for urban development projects, particularly in the immediate vicinity of new stations. However, most empirical studies call such automatic effects into question, pointing to the importance of additional local factors, such as station location within the urban context. We construct a dataset of 232 stations in 11 countries in Europe to analyse evolving station placement strategies as well as land use changes in the surroundings of High-Speed Rail stations before and after construction. We find that stations close to the existing urban fabric and well connected by complementary regional and local public transport are on average associated with more land use change, while peripheral stations outside of metropolitan regions hardly attract any development. [ABSTRACT FROM AUTHOR]

A reliable and comparative fungicide index (FI) was assessed to describe the fungicide use in the agricultural land of Europe during the first 20 years of the twenty-first century (from 2000 to 2018). FI is not uniform across EU27. The highest mean value (1.34 kg ha−1) of FI was observed in Southern Europe compared to the other sub-regions of the EU, while this variation existed mainly due to the inorganic fungicide use. The mean value of inorganic fungicide index (FIinorg) in agricultural land area (AL) in Southern Europe was 1.69 kg ha−1, about three times higher than the average value (0.63 kg ha−1) across the EU. The higher mean values of organic fungicide index (FIorg) in conventional agricultural land area (convAL) was observed in Western Europe (0.54 kg ha−1), while an upward trend was observed in the FIorg mainly in Central and Eastern and Northern Europe during the period 2000–2018. Linear discriminant analysis (LDA) of 19 agri-environmental indicators (FI, FIorg, FIinorg, agricultural land use, crop groups, fungicide chemical families) was assessed to describe this differentiation of the four geographical sub-regions of EU. Despite the linear growth of the organic farmland area, the fungicide use in the agricultural land remained relatively stable, while the larger the farm size (ha), the greater the amounts (kg of a.s.) of fungicides which were used in the cropland of EU. The impact assessment of each variable which was examined on the FI could contribute to the implementation of European agricultural policy, reducing in this way the environmental impact. [ABSTRACT FROM AUTHOR]

This paper presents palaeoecological reconstructions and late Neanderthal responses to environmental conditions in two different palaeoecological zones (continental south‐central Europe and the eastern Adriatic) during MIS 3. Our interpretations are based on the available records of climatic conditions, characteristics of Mousterian industries and site characteristics. A variety of data obtained by different methods of analyses (sediments and biological remains) were used for palaeoecological reconstructions, while hominin behaviour was examined from various perspectives based on lithic remains (technology, typology, raw material use), subsistence strategies, land use and site structures. In both regions, Neanderthals practised a broad exploitation of different faunal and lithic resources available to them and successfully adapted to local environments. Based on a variety of evidence, we offer a new synthesis and examine whether continental south‐central Europe and the Adriatic really acted as refugia during the time of late Neanderthal occupations. We also consider the possible causes and/or timing of Neanderthal disappearance in these regions. [ABSTRACT FROM AUTHOR]

Currently, we expected a altitudinal shift of forest vegetation upward under predicted climate changes impacts to European mountains ecosystems. In this context can be very interesting, that changes in alpine tree line ecotone in high European mountains were induced by human activities relatively often also in history. Probably one of the most important driver in land-use changes in high mountains was grazing, which significantly have influenced both mountain spruce forests and open alpine grasslands in central-Europe. This paper deals with historical changes of land-use in Hruby Jesenik Mountains (Czech Republic) during 19th and 20th centuries. Results revealed consequences of former grazing in mountain grasslands above alpine tree line ecotone in the frame of land-use analyses based on historical maps and other sources. These results, based on historical data, support our better understanding to current dynamic changes in European mountain landscapes. [ABSTRACT FROM AUTHOR]