A climate service for ecologists: sharing pre-processed EURO-CORDEX regional climate scenario data using the eLTER information system

eLTER was a “Horizon 2020” project with the aim of advancing the development of long-term ecosystem research infrastructure in Europe. This paper describes how eLTER Information System infrastructure has been expanded by a climate service data product providing access to specifically pre-processed regional climate change scenario data from a state-of-the-art regional climate model ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) for 702 registered ecological research sites across Europe. This tailored, expandable, easily accessible dataset follows FAIR principles and allows researchers to describe the climate at these sites, explore future projections for different climate change scenarios and make regional climate change assessments and impact studies. The data for each site are available for download from the EUDAT collaborative data infrastructure B2SHARE service and can be easily accessed and visualised through the Dynamic Ecological Information Management System – Site and Dataset Registry (DEIMS-SDR), a web-based information management system which shares detailed information and metadata on ecological research sites around the globe. This paper describes these data and how they can be accessed by users through the extended eLTER Information System architecture. The data and supporting information are available from B2SHARE. Each individual site (702 sites are available) dataset has its own DOI. To aid data discovery, a persistent B2SHARE lookup table has been created which matches the DOIs of the individual B2SHARE record with each DEIMS site ID. This lookup table is available at https://doi.org/10.23728/b2share.bf41278d91b445bda4505d5b1eaac26c (eLTER EURO-CORDEX Climate Service, 2020)

DEIMS-SDR – A web portal to document research sites and their associated data

Climate change and other drivers are affecting ecosystems around the globe. In order to enable a better understanding of ecosystem functioning and to develop mitigation and adaptation strategies in response to environmental change, a broad range of information, including in-situ observations of both biotic and abiotic parameters, needs to be considered. Access to sufficient and well documented in-situ data from long term observations is therefore one of the key requirements for modelling and assessing the effects of global change on ecosystems. Usually, such data is generated by multiple providers; often not openly available and with improper documentation. In this regard, metadata plays an important role in aiding the findability, accessibility and reusability of data as well as enabling reproducibility of the results leading to management decisions. This metadata needs to include information on the observation location and the research context. For this purpose we developed the Dynamic Ecological Information Management System – Site and Dataset Registry (DEIMS-SDR), a research and monitoring site registry (https://www.deims.org/) that not only makes it possible to describe in-situ observation or experimentation sites, generating persistent, unique and resolvable identifiers for each site, but also to document associated data linked to each site. This article describes the system architecture and illustrates the linkage of contextual information to observational data. The aim of DEIMS-SDR is to be a globally comprehensive site catalogue describing a wide range of sites, providing a wealth of information, including each site's location, ecosystems, facilities, measured parameters and research themes and enabling that standardised information to be openly available

Taller sobre Gestión de Información de la Red LTER Europa

info:eu-repo/semantics/publishedVersio

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence-absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals

A High-Resolution Map of Emerald Ash Borer Invasion Risk for Southern Central Europe

Ash species (Fraxinus spp.) in Europe are threatened by the Emerald Ash Borer (Agrilus planipennis, EAB), an invasive wood boring beetle native to East Asia and currently spreading from European Russia westwards. Based on a high-resolution habitat distribution map (grid cell size: 25 × 25 m) and data on distribution and abundance of Common Ash (Fraxinus excelsior), the most widespread and highly susceptive host species of EAB in Europe, we assess the spatial distribution of EAB invasion risks for southern Central Europe (Austria, Switzerland, Liechtenstein, southern Germany, South Tyrol). We found highest F. excelsior abundance and thus invasion risks in extensive lowland floodplain forests, medium risks in zonal lowland forests and low risks in upper montane and subalpine forests. Based on average velocities of spread in Russia (13–31 km/year) and North America (2.5–80 km/year) from flight and human-assisted transport, EAB is likely to cover the distance (1500 km) between its current range edge in western Russia and the eastern border of the study region within few decades. However, secondary spread by infested wood products make earlier introductions likely. The high susceptibility and mortality of F. excelsior leave no doubt that this beetle will become a major forest pest once it reaches Central Europe. Therefore, developing and testing management approaches with the aim to halt or at least slow down the invasion of EAB in Europe have to be pursued with great urgency

Towards interoperable research site documentation – Recommendations for information models and data provision

Information related to research sites is essential when describing the context of observations. It is a key element of site-based research infrastructures (RIs) and their catalogues. This paper is dedicated to the comparison of (meta)data models describing research sites in the ecosystem domain. A special focus is on sites in terrestrial and freshwater ecosystems. This should provide the basis for a common site-based data model to exchange data from different site-based catalogue services. This should substantially improve interoperability of site-level information between different RIs. For this purpose, we selected well-established site catalogues that feature web-accessible documentation of the sites and means to export this information. Using either dedicated descriptions of the data models, or, if these were not available, by deriving the data model from the records extracted from the catalogues, we identified the commonalities, differences and gaps of the underlying data models. Based on the findings, we define a set of mandatory core fields to be used in every site catalogue in the ecosystem domain. A set of additional fields are recommended to be implemented. In addition, we formulate general recommendations on how to best serve site data, considering the technical interface, the data format and the data license. The aim of these recommendations is to increase interoperability between site catalogues in general and the selected catalogues in particular. This fosters analyses of the existing ecosystem research infrastructures on a national, regional and global scale and increase the ability of these infrastructures to answer large-scale environmental questions

The I-ADOPT Interoperability Framework for FAIRer data descriptions of biodiversity

Biodiversity, the variation within and between species and ecosystems, is essential for human well-being and the equilibrium of the planet. It is critical for the sustainable development of human society and is an important global challenge. Biodiversity research has become increasingly data-intensive and it deals with heterogeneous and distributed data made available by global and regional initiatives, such as GBIF, ILTER, LifeWatch, BODC, PANGAEA, and TERN, that apply different data management practices. In particular, a variety of metadata and semantic resources have been produced by these initiatives to describe biodiversity observations, introducing interoperability issues across data management systems. To address these challenges, the InteroperAble Descriptions of Observable Property Terminology WG (I-ADOPT WG) was formed by a group of international terminology providers and data center managers in 2019 with the aim to build a common approach to describe what is observed, measured, calculated, or derived. Based on an extensive analysis of existing semantic representations of variables, the WG has recently published the I-ADOPT framework ontology to facilitate interoperability between existing semantic resources and support the provision of machine-readable variable descriptions whose components are mapped to FAIR vocabulary terms. The I-ADOPT framework ontology defines a set of high level semantic components that can be used to describe a variety of patterns commonly found in scientific observations. This contribution will focus on how the I-ADOPT framework can be applied to represent variables commonly used in the biodiversity domain.Comment: submitted to S4BioDiv 2021: 3rd International Workshop on Semantics for Biodiversity, September 15, 2021, Bozen, Ital

Long-term environmental monitoring infrastructures in Europe : observations, measurements, scales, and socio-ecological representativeness

The challenges posed by climate and land use change are increasingly complex, with ever-increasing and accelerating impacts on the global environmental system. The establishment of an internationally harmonized, integrated, and long-term operated environmental monitoring infrastructure is one of the major challenges of modern environmental research. Increased efforts are currently being made in Europe to establish such a harmonized pan-European observation infrastructure, and the European network of Long-Term Ecological Research sites – LTER-Europe – is of particular importance. By evaluating 477 formally accredited LTER-Europe sites, this study gives an overview of the current distribution of these infrastructures and the present condition of long-term environmental research in Europe. We compiled information on long-term biotic and abiotic observations and measurements and examined the representativeness in terms of continental biogeographical and socio-ecological gradients. The results were used to identify gaps in both measurements and coverage of the aforementioned gradients. Furthermore, an overview of the current state of the LTER-Europe observation strategies is given. The latter forms the basis for investigating the comparability of existing LTER-Europe monitoring concepts both in terms of observational design as well as in terms of the scope of the environmental compartments, variables and properties covered

Towards an integrated model of socioeconomic biodiversity drivers, pressures and impacts. A feasibility study based on three European long-term socio-ecological research platforms

Effective policies to slow the rate of anthropogenic biodiversity loss should reduce socioeconomic pressures on biodiversity, either directly or by modifying their underlying socioeconomic driving forces. The design of such policies is currently hampered by the limited understanding of socioeconomic drivers of and pressures on biodiversity as well as by lacking data, indicators and models. In order to improve understanding of these issues we here propose a conceptual model of socioeconomic biodiversity drivers and pressures. The model is based on the drivers-pressures-impacts-states-responses (DPSIR) scheme and on the socioeconomic metabolism approach. The aim of the model is to guide research aimed at improving our understanding of socioeconomic biodiversity pressures and drivers and to serve as a basis for the development of formal, quantitative models in that field. Based on three European long-term socio-ecological research (LTSER) platforms, we analyze the model's applicability and suitability as well as data availability and research needs. These platforms are the Danube Delta Wetland System in Romania, the Doana in Spain and the Eisenwurzen in Austria. An empirical analysis of the relationship between the human appropriation of net primary production (HANPP) and breeding bird richness in the Eisenwurzen demonstrates the ability of HANPP to provide a link between socioeconomic pressures/drivers and biodiversity. The analysis of the case studies underlines the potential utility of the conceptual model to guide future research into socioeconomic biodiversity drivers and pressures. However, considerable investments in monitoring and reconstruction of past trajectories as well as in model development will be required before mathematical (computer) models of the interrelation processes between society and ecosystems can be successfully deployed.Biodiversity Long-term socio-ecological research (LTSER) Socioeconomic drivers Pressures on biodiversity Human appropriation of net primary production (HANPP) Socioeconomic metabolism