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There are substantial concerns about impaired honey bee health and colony losses due to several poorly understood factors. We used MALDI profiling (MALDI BeeTyping®) analysis to investigate how some environmental and management factors under field conditions across Europe affected the honey bee haemolymph peptidome (all peptides in the circulatory fluid), as a profile of molecular markers representing the immune status of Apis mellifera. Honey bees were exposed to a range of environmental stressors in 128 agricultural sites across eight European countries in four biogeographic zones, with each country contributing eight sites each for two different cropping systems: oilseed rape (OSR) and apple (APP). The full haemolymph peptide profiles, including the presence and levels of three key immunity markers, namely the antimicrobial peptides (AMPs) Apidaecin, Abaecin and Defensin-1, allowed the honey bee responses to environmental variables to be discriminated by country, crop type and site. When considering just the AMPs, it was not possible to distinguish between countries by the prevalence of each AMP in the samples. However, it was possible to discriminate between countries on the amounts of the AMPs, with the Swedish samples in particular expressing high amounts of all AMPs. A machine learning model was developed to discriminate the haemolymphs of bees from APP and OSR sites. The model was 90.6 % accurate in identifying the crop type from the samples used to build the model. Overall, MALDI BeeTyping® of bee haemolymph represents a promising and cost-effective "blood test" for simultaneously monitoring dozens of peptide markers affected by environmental stressors at the landscape scale, thus providing policymakers with new diagnostic and regulatory tools for monitoring bee health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The Mediterranean basin is one of the most vulnerable regions worldwide due to its population density, the concentration of economic activities along the coasts and borderline climatic balance. It is identified as one of the most critical erosion hotspots in Europe, mainly due to the degradation of coastal areas, overexploitation and unsustainable practices affecting beach tourism, agriculture and fishing. The region is also affected by other phenomena such as storms and floods, which are exacerbated by climate change. To mitigate and adapt to these environmental and climatic changes, Nature based Solutions (NbSs) are considered a promising step-forward. However, despite their global recognition in both research and policy, few scientific papers and documents on the state of NbSs implementation for coastal risk management in the Mediterranean exist. This paper aims to provide an understanding of the status of NbS adoption for coastal risk management in the Mediterranean through a literature review. Out of 162 scientific papers and documents, only 23 were found to be relevant to the study. Through the definition and support of an innovative matrix-based approach, the analysis of the state of adoption of NbSs have been performed. Despite the limited information on the state of the adoption of NbSs for coastal risk management in the Mediterranean due to the low numbers of scientific research and documents available, some key considerations have been revealed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This research combines Strontium (87Sr/86Sr) and Oxygen (δ18O) isotope analysis to challenge the prevailing interpretation of patrilocal exogamic practices among eastern European Early Neolithic Linearbandkeramik (LBK) communities. Patrilocality has been considered the key factor influencing the mobility patterns of central Europe's first farmers (c. 5500–4900 cal. BC), especially in the south-eastern Moravian region (Czech Republic). Focusing our attention on both male and female tooth enamel samples from cemeteries, settlement graves and small clusters of graves, this paper reassesses the correlation between mobility, biological sex, and funerary practices. This task is accomplished by establishing a new isotopic footprint using new 87Sr/86Sr data, as well as significantly increasing the number of sampled individuals for 87Sr/86Sr and δ18O. The outcome of this research contributes to a better understanding of the mobility patterns among early farmers in central Europe, challenging existing theories and providing new insights into their social and cultural dynamics. [ABSTRACT FROM AUTHOR]

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In Europe, increasing the area of legume crops has been identified as a key measure to achieve the objectives set by the European Green Deal and transition toward more sustainable food systems. Although the role of grain legumes in climate change mitigation has been closely examined, little research has focused on how climate change will challenge the development of these crops. This article systematically reviews recent simulation studies to assess the impact of climate change on grain legume performances in Europe and the effect of adaptation strategies. Forty papers using process-based, ecological niche, or statistical models were selected to simulate the response of eight grain legume species to future climate (2020–2100) in Europe. The lack of data on adaptation strategies in Europe was compensated for by enlarging the study area to climatically similar regions. The review highlights a notable imbalance between research about soybean versus other grain legumes, with soybean representing approximately 80% of selected studies. Studies focused on soybean found good agreement, with yield or suitability gains found in northern Europe and a higher probability of yield losses in southern and south-eastern Europe. While a similar spatial pattern may be expected for other grain legumes, the scarcity of data makes this result more uncertain. The review also shows that several adaptation strategies have the potential to mitigate the negative impact of climate change on grain legume performances or enhance its positive impact. The most promising strategies tested include irrigation, change in sowing date, and cultivar choice. In addition, we identify several knowledge gaps that, if addressed, would support legume development in Europe. In particular, key species such as field pea, faba bean, lentil, and chickpea remain blind spots, despite their prominent role in European environmental, agricultural, and nutritional policies. Other knowledge gaps include a lack of accounting for crop response to elevated CO 2 , ozone, and future biotic pressure, and a limited range of adaptation strategies tested and indicators assessed. Implementing multi-criteria analyses that involve stakeholders would help identify relevant inputs and outputs for future simulations. • We review 40 papers assessing grain legume response to climate change in Europe. • Grain legumes other than soybean are blind spots despite their role in policies. • For soybean, yield gains are expected in the north and yield losses in the south. • Adaptation strategies can mitigate the impact of climate change on grain legumes. • We identify several knowledge gaps, including a lack of data on key legume species. [ABSTRACT FROM AUTHOR]

Improving agricultural nitrogen management is one of the key objectives of the recent Green Deal in Europe. Current technological developments in agriculture offer new opportunities to improve nitrogen fertilization practices. The aim of this study was to adapt to Sentinel-2 data a proven delineation method initially developed for yield maps, in order to facilitate precise nitrogen management by farmers. The study was conducted in two steps. Firstly, an analysis at annual level was conducted to assess the relationship between vegetation indices and yield at the subfield scale, for different sensing period. The second step consisted in performing a pluri- annual analysis through the delineation of management zones and compare the results achieved from yield maps and from NDVI maps. Among different vegetation indices, NDVI proved to be an interesting candidate for subfield detection of yield variation, specifically when the index was sensed was sensed around the second half of May. In this area, this period usually corresponds to phenological development between the flag leaf stage and heading stage, just prior the initiation of winter wheat flowering. Using NDVI maps within Blackmore's delineation approach instead of yield maps. Allowed to reach an accuracy of 69% on zone classification. However, as yields and NDVI distribution do not respond to similar statistical distributions, we considered that the delineation threshold used to differentiate high from low yielding zones had to be adapted. The adaptation of the "performance threshold" in favor of the median NDVI, made it possible to achieve a higher accuracy (71%) of the delineation. But above all, the improvement lies also in a more robust satellite-based delineation. [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]

Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model's applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP , last access: 4 April 2024). [ABSTRACT FROM AUTHOR]

In April 2023, the Taliban banned poppy cultivation and the trade of all narcotics. This caused a 95% reduction in opium production. Usually, that would be good news. But there is a substantial worry: synthetic opioids might fill the void left by heroin. This is concerning because these drugs have led to health emergencies in areas where they are prevalent. This paper highlights the limitations of the current drug surveillance system in Europe and proposes improvements. It argues that reliance on secondary data is insufficient. Instead, we need to interview a sentinel group of people who inject drugs and adjust city-level sentinel systems, such as wastewater analysis, to specifically track the spread of synthetic opioids. Without these proactive steps, we risk only noticing a transition from heroin to synthetic opioids after it has occurred, with its harmful impacts already in place. [ABSTRACT FROM AUTHOR]

The aim of this study was to understand the needs of European users for successful development and uptake of a digital land-based knowledge platform. The 'discover and define' phases of the design thinking double diamond framework were applied to inform the construction of 16 user-personas and journeys. Qualitative and quantitative data were collected from users across Europe using a multi-step approach and thematically analysed. User-personas and associated user journeys present useful methods for understanding the requirements of key stakeholders in the land-based sectors to aid the development of a digital knowledge reservoir, tailored to their needs. Problem urgency plays a key role in stakeholder touchpoint decisions, with acute problems approached by direct calls or interactions with important advisors. Digital platforms are more likely to be used for chronic problems or general knowledge exchange and upskilling. The touchpoints, challenges and emotions of users are not significantly linked to geographical location but are more likely to be influenced by age, gender and existing digital knowledge. Design thinking can be used to understand the needs of stakeholders in the land-based sectors for the development of tools, products and services as well as understanding specific knowledge requirements. This study provides a theoretical framework for understanding the digital knowledge needs of different land-based users. The development of user-personas and journeys is limited in the land-based sectors, and this research provides a framework for use. [ABSTRACT FROM AUTHOR]

One of the biggest challenges in the construction industry in recent times is the mitigation of the environmental impact of this sector, the reduction in dependence on primary raw materials, and the reduction in CO2 production while maintaining functional properties. Alkaline activation of a number of waste products represents a promising way to achieve the above-mentioned goals, but the availability of a number of waste products changes over time, especially in Europe. While freshwater sediments were in the past widely utilized as an agricultural fertilizer, recent precautions have significantly decreased such application, and thus new destinations must be delivered. To explore the potential of freshwater sediments, select samples from various locations were subjected to detailed characterization to verify the applicability of the material for alkali activation. As recognized, the selected sediments contain a substantial volume of desired mineralogical compounds that can serve, after 900 °C curing, as suitable precursors. Such samples have consequently activated the mixture of alkaline activators to obtain dense structures and were subjected to detailed investigation aimed at understanding the mechanical parameters. The obtained mechanical results ranging between 14.9 MPa and 36.8 MPa reveal the engineering potential of sediments for valorization through alkali activation and outline new research challenges in this area. [ABSTRACT FROM AUTHOR]

A significant part of the world economy is devoted to agriculture. The sector accounts for 27% of global employment and 4% of global GDP. Approximately 28.5 million farms are located in Europe and Latin America. In this sector, many uncertainties negatively impact farmers' mental and emotional well-being. Many factors contribute to increased stress and a worsening of farmers' mental health, including health problems resulting from the conducting their profession, economic uncertainty, the effects of climate change, and technological changes in the agricultural sector. Despite the existence of literature review studies related to mental health in agriculture, no bibliometric review study has been conducted. This article presents the first in-depth bibliometric analysis of the scientific literature on mental health in agriculture and operates based on Scopus and Web of Science databases. The results are presented as tables and explanatory diagrams describing the findings. The findings show the exponential increase in research in the last ten years and the evolution towards more social and health-related topics across the previous five years. The most common keywords are "suicide", "stress", and "depression". No topic has been found where the current scientific production was significantly larger than the rest, indicating the wide variety of research sub-topics in this field. [ABSTRACT FROM AUTHOR]