Priorities to advance monitoring of ecosystem services using Earth observation

Managing ecosystem services in the context of global sustainability policies requires reliable monitoring mechanisms. While satellite Earth observation offers great promise to support this need, significant challenges remain in quantifying connections between ecosystem functions, ecosystem services, and human well-being benefits. Here, we provide a framework showing how Earth observation together with socioeconomic information and model-based analysis can support assessments of ecosystem service supply, demand, and benefit, and illustrate this for three services. We argue that the full potential of Earth observation is not yet realized in ecosystem service studies. To provide guidance for priority setting and to spur research in this area, we propose five priorities to advance the capabilities of Earth observation-based monitoring of ecosystem services

Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward

Ecosystem structure, especially vertical vegetation structure, is one of the six essential biodiversity variable classes and is an important aspect of habitat heterogeneity, affecting species distributions and diversity by providing shelter, foraging, and nesting sites. Point clouds from airborne laser scanning (ALS) can be used to derive such detailed information on vegetation structure. However, public agencies usually only provide digital elevation models, which do not provide information on vertical vegetation structure. Calculating vertical structure variables from ALS point clouds requires extensive data processing and remote sensing skills that most ecologists do not have. However, such information on vegetation structure is extremely valuable for many analyses of habitat use and species distribution. We here propose 10 variables that should be easily accessible to researchers and stakeholders through national data portals. In addition, we argue for a consistent selection of variables and their systematic testing, which would allow for continuous improvement of such a list to keep it up-to-date with the latest evidence. This initiative is particularly needed not only to advance ecological and biodiversity research by providing valuable open datasets but also to guide potential users in the face of increasing availability of global vegetation structure products

Archetypes of agri-environmental potential: a multi-scale typology for spatial stratification and upscaling in Europe

Developing spatially-targeted policies for farmland in the European Union (EU) requires synthesized, spatially-explicit knowledge of agricultural systems and their environmental conditions. Such synthesis needs to be flexible and scalable in a way that allows the generalization of European landscapes and their agricultural potential into spatial units that are informative at any given resolution and extent. In recent years, typologies of agricultural lands have been substantially improved, however, agriculturally relevant aspects have yet to be included. We here provide a spatial classification approach for identifying archetypal patterns of agri-environmental potential in Europe based on machine-learning clustering of 17 variables on bioclimatic conditions, soil characteristics and topographical parameters. We improve existing typologies by (a) including more recent biophysical data (e.g. agriculturally-important soil parameters), (b) employing a fully data-driven approach that reduces subjectivity in identifying archetypal patterns, and (c) providing a scalable approach suitable both for the entire European continent as well as smaller geographical extents. We demonstrate the utility and scalability of our typology by comparing the archetypes with independent data on cropland cover and field size at the European scale and in three regional case studies in Germany, Czechia and Spain. The resulting archetypes can be used to support spatial stratification, upscaling and designation of more spatially-targeted agricultural policies, such as those in the context of the EU's Common Agricultural Policy post-2020

A bird’s eye view over ecosystem services in Natura 2000 sites across Europe

Recent ‘New Conservation’ approaches called for more ecosystem services (ES) emphasis in conservation. We analysed data from 3757 Natura 2000 special protection areas (SPAs) and translated positive and negative impacts listed by conservation managers into indicators of the use of nine provisioning, regulating and cultural ES. Overall, the use of ES is considered by SPA managers to affect conservation goals more negatively than positively. ES associated with livestock keeping and fodder production are recorded as having the highest fraction of positive impacts on SPAs, ranging from 88% and 78% in the Boreal biogeographic region to 20% and 6% in the Mediterranean. The use of ES varied according to dominant habitat class, highlighting the dependence of specific ES on associated ecosystem functions. For instance, fibre production was the predominant ES throughout forest habitats while crop, fodder and livestock exhibit similar patterns of dominance across agricultural landscapes. In contrast, the use of wild food and recreation activities are seen as causing mainly negative effects across all habitats. Our analysis suggests that most uses of ES result in negative effects on conservation goals. These outcomes should be considered when implementing future conservation strategies

A Range of Earth Observation Techniques for Assessing Plant Diversity

AbstractVegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation diversity using RS

Quantifying agricultural land-use intensity for spatial biodiversity modelling: implications of different metrics and spatial aggregation methods

Abstract Context Agricultural intensification is a major driver of farmland biodiversity declines. However, the relationship between land-use intensity (LUI) and biodiversity is complex and difficult to characterise, not least because of the difficulties in accurately quantifying LUI across heterogeneous agricultural regions. Objectives We investigated how the use of different LUI metrics and spatial aggregation methods can lead to large variations in LUI estimation across space and thus affect biodiversity modelling. Methods We used three spatial aggregation methods (square, hexagonal, and voronoi grids) to calculate ten commonly used LUI metrics describing three LUI dimensions: land use, land management and landscape structure. Using a virtual species approach, we compared how LUI values sampled at biodiversity monitoring sites vary across different metrics and grids. We modelled the distribution of three virtual species using Generalised Additive Models to test how omitting certain LUI dimensions from the models affected the model results. Results The density distributions of LUI values at the presence points of the virtual species were significantly different across metrics and grids. The predefined species-environment relationships characterising the environmental niches of two out of three virtual species remained undetected in models that omitted certain LUI dimensions. Conclusions We encourage researchers to consider the implications of using alternative grid types in biodiversity models, and to account for multiple LUI dimensions, for a more complete representation of LUI. Advances in remote sensing-derived products and increased accessibility to datasets on farm structure, land-use and management can greatly advance our understanding of LUI effects on biodiversity

Current use and costs of electronic health records for clinical trial research : a descriptive study

Electronic health records (EHRs) may support randomized controlled trials (RCTs). We aimed to describe the current use and costs of EHRs in RCTs, with a focus on recruitment and outcome assessment.; This descriptive study was based on a PubMed search of RCTs published since 2000 that evaluated any medical intervention with the use of EHRs. Cost information was obtained from RCT investigators who used EHR infrastructures for recruitment or outcome measurement but did not explore EHR technology itself.; We identified 189 RCTs, most of which (153 [81.0%]) were carried out in North America and were published recently (median year 2012 [interquartile range 2009-2014]). Seventeen RCTs (9.0%) involving a median of 732 (interquartile range 73-2513) patients explored interventions not related to EHRs, including quality improvement, screening programs, and collaborative care and disease management interventions. In these trials, EHRs were used for recruitment (14 [82%]) and outcome measurement (15 [88%]). Overall, in most of the trials (158 [83.6%]), the outcome (including many of the most patient-relevant clinical outcomes, from unscheduled hospital admission to death) was measured with the use of EHRs. The per-patient cost in the 17 EHR-supported trials varied from US$44 to US$2000, and total RCT costs from US$67 750 to US$5 026 000. In the remaining 172 RCTs (91.0%), EHRs were used as a modality of intervention.; Randomized controlled trials are frequently and increasingly conducted with the use of EHRs, but mainly as part of the intervention. In some trials, EHRs were used successfully to support recruitment and outcome assessment. Costs may be reduced once the data infrastructure is established

Subclones in B-lymphoma cell lines: isogenic models for the studyof gene regulation

Genetic heterogeneity though common in tumors has been rarely documented in celllines. To examine how often B-lymphoma cell lines are comprised of subclones, weperformed immunoglobulin (IG) heavy chain hypermutation analysis. Revealing thatsubclones are not rare in B-cell lymphoma cell lines, 6/49 IG hypermutated cell lines(12%) consisted of subclones with individual IG mutations. Subclones were alsoidentified in 2/284 leukemia/lymphoma cell lines exhibiting bimodal CD markerexpression. We successfully isolated 10 subclones from four cell lines (HG3, SUDHL-5, TMD-8, U-2932). Whole exome sequencing was performed to molecularlycharacterize these subclones. We describe in detail the clonal structure of cell lineHG3, derived from chronic lymphocytic leukemia. HG3 consists of three subcloneseach bearing clone-specific aberrations, gene expression and DNA methylationpatterns. While donor patient leukemic cells were CD5+, two of three HG3 subcloneshad independently lost this marker. CD5 on HG3 cells was regulated byepigenetic/transcriptional mechanisms rather than by alternative splicing as reportedhitherto. In conclusion, we show that the presence of subclones in cell lines carryingindividual mutations and characterized by sets of differentially expressed genes is notuncommon. We show also that these subclones can be useful isogenic models forregulatory and functional studies

Learning from your neighbor: tax-benefit systems swaps in Latin America

Over the last decades, Latin American countries have experienced a noticeable decrease in income inequality. While this trend is mainly associated with a decline in wage inequality, progressive reforms of the tax-benefit systems of the region may have pl