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LAMASUS - Biodiversity estimates for agricultural management and other statistics
No full textWe provide key outputs from ‘D5.2 Coefficients of estimated biodiversity responses to land use and maps of conservation priorities’, including estimated model coefficients, biodiversity response functions, and spatially projected biodiversity indicator values.
Biodiversity estimates from two different institutes are provided:
(i) GLOBIO - Mean species abundance (MSA) estimates for different agricultural management types are provided.
(ii) IIASA - Biodiversity intactness index (BII) estimates for different agricultural and forest management types are provided.
This dataset has been created as part of LAMASUS Project under the scope of Deliverable 5.2 titled "Coefficients of estimated biodiversity responses to land use and maps of conservation priorities", which can be found here: https://www.lamasus.eu/wp-content/uploads/LAMASUS_D5.2_Coefficients-biodiversity_final.pdf.
GLOBIO estimates (MSA):
Biodiversity estimates for the LAMASUS deliverable D5.2. The "Statistics.xls" file includes biodiversity estimates and confidence intervals for different types of agricultural management as described in the methodology of "LAMASUS_D5.2_Coefficients-biodiversity_final.pdf". Additionally, the file contains post-hoc test outcomes, estimates for threatened biodiversity, coefficients for relationships over time since the establishment of an agricultural management system, as well as model comparisons with continent as a fixed effect to assess whether spatial variability explains the results. Explanations can be found in the "LAMASUS_D5.2_Coefficients-biodiversity_final.pdf" file.
IIASA estimates (BII):
Data are split into two file types, ‘BASE’ and ‘OPTIMAL’. BASE refers to outputs from the Base model structure as described in D5.2, using only PREDICTS data (i.e., models presented in Figure 2, PREDICTS weight = 1). OPTIMAL refers to the Optimal model structure described in D5.2, and incorporating our data-integration approach (i.e., models presented in Figures 4, 5, 6, coloured lines, PREDICTS weight = 0.7). Data for all indicators presented in D5.2 (Species richness, Total abundance, Geometric mean abundance, Sørensen, Bray-Curtis, Canberra and the biodiversity intactness index [BII]) are included. However, results for the combination of Optimal and Species richness are missing due to model convergence issues.
Within the BASE files, we provide model coefficients (coefficient_estimates.csv, ‘(Intercept)’ corresponds to Primary(-Primary)), response estimates relative to Primary(-Primary) (response_functions.csv), and spatial predictions given the LAMASUS Land Use Management Data Set (See et al., 2025, https://zenodo.org/records/15488011). Spatial predictions are provided for the EU (plus UK) at 1km (eur_1km.tif), NUTS2 (eur_NUTS2.csv), and country (eur_countries.csv) scales, for 2000, 2010 and 2018.
Model coefficients and spatial predictions are similarly provided in the OPTIMAL files. Rescaled response estimates are not provided for the Optimal models due to dependence on continuous covariates. However, given the model coefficients, responses can be generated for specific variable combinations
Natura2000 sites on the EEA referece grid (1km)
No full textThis dataset provides spatial information linking Natura 2000 site designations to the EEA 1x1 km² reference grid. Each grid cell is associated with Natura 2000 site codes and corresponding site area coverage (in km²). The dataset enables spatially explicit analyses of Natura 2000 sites across the European Union
LAMASUS - Simulated Crop Yields and Fertilizer Application Rates for Nine Crops under Six Management Intensity Scenarios in the EU
No full textAs part of the knowledge base on climate impacts of land-use management (LUM), delivered under Deliverable D5.1 of the EU project LAMASUS, we provide a dataset of simulated crop yields and associated nitrogen fertilizer application rates. The dataset covers nine crop types under six management intensity scenarios, simulated with the EPIC-IIASA model. Reported values represent averages for the period 2001–2020, at a spatial resolution of 5 arc-minutes, and are provided in NetCDF format. Further details are available in the accompanying ReadMe file
Functional diversity in the first FACE experiment in a hyperdiverse Amazon forest
No full textThe Amazon rainforest acts as a significant carbon store and plays a crucial role in partially offsetting global anthropogenic CO2 emissions. Climate change and rising CO2 levels are altering ecosystem functions and this is projected to continue into the future. However, uncertainties remain on how individual trees and the hyperdiverse forest community will respond. To address this, the first FACE (free-air CO2 enrichment) experiment in the tropics is being installed in the Brazilian Amazon. Due to its high biodiversity, many dominant tree species occur at < 1 individual/ha; following standard practice to attempt full species replication would require experimenting in over 10 ha of forest, which is impractical. Here, we show how functional space-diversity is used to solve this challenge by assessing the main morphological, anatomical and hydraulic functional traits of the tree community identified at the experimental site. We measured traits across 414 species to create a functional group framework which represents a gradient from acquisitive (fast-growing) to conservative (slow-growing) species in terms of carbon, nutrient, and water uses, allowing us to elucidate mechanisms in a species-independent way. We found a separation emerged between acquisitive (high SLA, low CN) and conservative species, alongside a hydraulic axis distinguishing high stomatal density (higher gas exchange) from high wood density (more drought resistant). Moreover, we compared the functional space occupied by the AmazonFACE tree community to that of the Amazon basin to assess representativeness at a large scale.
This study highlights the challenges and opportunities posed by biodiversity in conducting ecosystem-level experiments in tropical forests and underscores the potential of a functional trait approach to interpret findings regarding broader ecological contexts. Filling this knowledge gap is key to assessing the confidence in the projections of the future of the global carbon cycle in Earth System Models, and ultimately improving their accuracy and robustness
Beyond tradition: Unveiling the socio-psychological drivers of sustainable water use in farming
No full textWater conservation policies in agriculture, the largest consumer of water, are unlikely to succeed unless farmers voluntarily engage in water conservation behaviors (WCBs). Effective measures to reduce agricultural water consumption include cultivating low-water consumption (LWC) crops and adopting modern irrigation systems (MIS). Therefore, identifying the socio-psychological drivers influencing these WCBs and analyzing their distinctions are critical policy considerations for promoting sustainable water conservation actions. Hence, this study aimed to: (1) Explore the intentions and behaviors related to farmers' adoption of LWC crops and MIS, identify key determinants, and comparing them; and (2) Extend the Theory of Planned Behavior (TPB) by incorporating information publicity and personal involvement as social factors, and evaluate the robustness of this extended TPB (ETPB) compared to the original TPB in explaining farmers' WCBs. A cross-sectional survey and face-to-face interviews were conducted with 280 farmers living in Ardabil plain, Iran, and Structural equation modeling (SEM) was employed to analyze the data. Findings from ETPB revealed that information publicity was the dominant predictor of farmers' intention to adopt LWC crops (β = 0.65). Conversely, perceived behavioral control was the most significant predictor of farmers' intention to adopt MIS (β = 0.37). In terms of actual adoption, personal involvement (β = 0.41) was the strongest determinant for adopting LWC crops, whereas intention (β = 0.46) was the dominant predictor for adopting MIS. The ETPB model demonstrated a notable increase in predictive power. Specifically, it showed a 79 % improvement in predicting intention and a 31 % improvement in predicting behaviors for adopting LWC crops compared to the original TPB. For adopting MIS, the ETPB model exhibited a 25 % increase in predicting intention and a 5 % increase in predicting behavior
The short-term dynamics of conflict-driven displacement: Bayesian modeling of disaggregated data from Somalia
No full textUnderstanding the short-run dynamics of conflict and forced displacement is crucial for the design of effective policy responses, yet quantitative analyses in this realm are sparse. This is primarily due to the scarcity of high-frequency displacement data and methodological challenges arising when modeling imperfect data collected in conflict zones. Addressing both issues, we develop a Bayesian panel regression model to assess the short-term impact of conflict on displacement in Somalia, utilizing weekly panel data that encompasses eight million displacements and 19,000 conflict events from 2017 to 2023. Results suggest a rapid and nonlinear displacement response postconflict, with significant heterogeneity in effects dependent on the nature of conflict events. In a displacement forecasting exercise, our model outperforms standard benchmarks, underscoring its potential for informing decision-makers in crisis scenarios
Developing a Safe Operating Space framework for water resources in the Danube River basin
Get PDFThe Danube River Basin, spanning 19 countries and covering 801,000 km², is the most international river basin in the world. This region faces diverse challenges related to water quantity, quality, groundwater management, and biodiversity, all of which are expected to intensify due to climate change. To address these challenges, a holistic and sustainable water management approach is needed—one that integrates environmental, social, and economic dimensions, ensures stakeholder involvement, and aligns with regulatory frameworks.
Building on the Planetary Boundaries framework, the concept of Safe Operating Space (SOS) has emerged in the last decades to assess sustainable resource use within the Earth’s carrying capacity while maintaining human well-being. Within the Horizon Europe SOS-Water project, we are working to define the SOS for water resources in four case study sites across Europe and beyond (Danube, Rhine, Jucar and Mekong basins) using integrated modeling, monitoring, advanced indicators, and an inclusive and iterative participatory approach that actively engages stakeholders to co-define visions, water values, and management options.
The resulting co-created SOS framework will inform the design of sustainable water management pathways that address current and future challenges. It aims to maximize the socio-economic and ecological value of water while promoting resilience and sustainability across the different river basins.
This proposed talk will showcase the application of the SOS framework to the Danube Basin, highlighting its capability to integrate all the different aspects of the water dimension with stakeholder engagement and co-development of management pathways. We will present the preliminary framework co-developed with stakeholders for the Danube Basin and provide insights into the how it can be used to inform sustainable water management practices and address the critical water challenges facing the Danube Basin and other transboundary regions worldwide
Graphical representation of global water models
Get PDFNumerical models are simplified representations of the real world at a finite level of complexity. Global water models are used to simulate the terrestrial part of the global water cycle, and their outputs contribute to the evaluation of important natural and societal issues, including water availability, flood risk, and ecological functioning. Whilst global water modeling is an area of science that has developed over several decades, and individual model-specific descriptions exist for some models, there has to date been no attempt to visualize the ways that several models work, using a standardized visualization framework. Here, we address this gap by presenting a community-driven process that developed a framework to visualize several global water models. The models considered participate in the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). The diagrams were co-produced between a graphics designer and 16 modeling teams, based on extensive discussions and pragmatic decision-making that balanced the need for accuracy and detail against the need for effective visualization. The model diagrams are based on a standardized ISIMIP2b-complete global water model that represents what is theoretically possible to represent in the current generation of state-of-the-art global water models participating in ISIMIP2b. Model-specific diagrams are then copies of the ISIMIP2b-complete model, with individual processes either included or grayed out. An open-source tool has been developed and published jointly with the diagrams, which allows someone to generate a diagram for their own global water model by adapting the diagrams presented here. As well as serving an educational purpose, we envisage that the diagrams will help researchers in and outside of the global water model community to select suitable model(s) for specific applications, stimulate a community learning process, and identify missing components to help direct future model developments
Assessing the Need and Demand for a Community Emergency Paramedic Strategy in the Ambulance Rescue System of Hamburg, Germany
Get PDFBackground: Demand for Hamburg’s ambulance rescue system (ARS) in Germany, which is managed by the fire service, increased by more than 10% between 2019 and 2021. This increase was mainly driven by a more than 20% increase in non-critical ambulance rescues, while critical rescues decreased over the same period. Factors contributing to this trend include demographic changes, longer waiting times in primary care and declining quality in out-of-hospital care. To address this issue, the introduction of community emergency paramedics (CEPs)—who provide treatment and advice to patients at home before ambulance services are called—has been proposed as a potential solution to alleviate pressure on the ARS. Methods: In this study, 17 ARS stations in Hamburg, categorized into three operational areas (East, South, West), were analyzed using comprehensive statistical methods such as hypothesis testing, correlation analysis, regression modeling and clustering. Data from 2019 and 2021 were examined to assess the feasibility of integrating CEPs into the existing system. Results: Key findings identified specific stations with high potential for CEP support and optimal mission times (based on time of day, day of week and calendar week) to improve operational efficiency. The impact of regulatory measures introduced during the COVID-19 pandemic was also evident in the 2021 data. Conclusions: Finally, four policy scenarios—taking into account different synergy effects among the 17 stations—are presented, providing projections of the managerial and economic benefits for Hamburg policymakers. These policy implications aim to support the development of a robust CEP strategy to improve the overall efficiency and sustainability of the ARS