Topics

Topic 1 Monitoring

Real-world terrestrial wildlife food chain case studies

TerraChem Work Package 1 focuses on monitoring of exposure to chemicals and effects of chemical mixtures in real-world terrestrial wildlife food chains. This research will deliver a very large dataset (> 50 million data points) on chemicals in soil and biota to underpin:

  • modelling source-to-damage pathways in terms of damage to species populations, functional diversity, genetic diversity and ecosystem services
  • improving risk prevention and mitigation in relation to the effects of chemicals on terrestrial biodiversity, and
  • developing a database and early warning system for chemicals in terrestrial biota and soils in Europe.

Twelve case studies

TerraChem is implementing 12 real-world wildlife food chain case studies. These case studies cover representative biomes (e.g. agricultural, forest, grassland, dry scrub) located in northern, southern, central, western and eastern Europe. Each case study involves sampling soil as well as biota, from the bottom of the food chain (plants, invertebrates) to the top (apex species).

Six case studies address the food chain of an avian apex species, the European barn owl Tyto alba, in The Netherlands, Germany, Spain, Portugal, Greece and Romania. Together, these constitute a pan-European study, allowing for comparisons between countries.

Six case studies address the food chains of mammalian apex (or near-apex) species, namely those of: the beech marten Martes foina in The Netherlands; the grey wolf Canis lupus in Germany; the European badger Meles meles in Spain; the Egyptian mongoose Herpestes ichneumon in Portugal; the northern white-breasted hedgehog Erinaceus roumanicus in Greece; and the red fox Vulpes vulpes in Romania.

Map of apex mammal and owl case studies
(one barn owl case study in each of the six mammal case study countries).

Sampling of apex species and food chain samples

In each case study, we sample soil and each level of the food chain – plants, invertebrates (herbivores, fungivores and detritivores), rodents (herbivores, omnivores and carnivores) and the apex species.

Opportunistic and systematic sampling

Sampling of apex species is opportunistic, largely relying on animals found dead on road verges as a result of collision with vehicles, but in some cases (e.g. beech marten, mongoose) resulting from official pest control programmes. Similarly, sampling of rodents is opportunistic, involving collection of animals found dead. No vertebrates are trapped and killed specifically for TerraChem case studies. Invertebrates are systematically sampled using pitfall traps. Plant and soil samples are also systematically sampled from the feeding territories of the apex animals.

Six replicate sample sets per apex species sample

For each case study, we collect 6 apex animals. Within the assumed territory of each apex animal, we collect 4 bulk soil samples, 4 mixed-species invertebrate samples, and up to eight rodent specimens (ideally of at least two species, e.g. wood mouse Apodemus sylvaticus and field vole Microtus agrestis).

Co-location of samples in space and time

Sampling within each case study is co-located, as far as possible, in space and in time. Soil and biota samples are collected within the assumed feeding territory of the apex animal in each instance, and in most cases within a few weeks of finding the apex animal.

Sample matrices, pooling of samples

The liver of each apex animal is dissected for chemical analysis. The four soil samples in each apex specimen territory are pooled for chemical analysis. The invertebrate contents of four pitfall traps from each apex animal territory are sorted and pooled to make one herbivore (including detritivore, fungivore) pooled sample and one non-herbivore (omnivore, carnivore) pooled sample. Rodents in each apex animal territory are sorted and pooled to give two pools (two herbivore pools or two omnivore/carnivore pools or one of each).

Chemical analyses

All samples are sent to the lab for lyophilisation (freeze-drying) and chemical analysis. The following chemical analyses are carried out on all samples (sample mass permitting), covering more-or-less the universe of environmentally relevant anthropogenic chemicals:

  • Instrumental analysis using ultra-high-performance LC-HRMS and GC-HRMS for the confident identification of (a) c. 2500 known emerging and legacy substances; (b) non-target screening of >950,000 suspect and unknown substances.
  • Sensitive targeted methodologies for the determination of substances not amenable to LC- and GC- analysis, including metals and other elements, siloxanes, organotins, volatile organic compounds (VOCs), and AMPA/Glyphosate.

Supplementary analyses

In addition, the following analyses will be carried out on subsets of samples:

  • A battery of CALUX bioassays (on selected soil and invertebrate samples) for analysis of mixture effects.
  • Stable isotope analysis (on biota samples) to inform analysis of routes of transfer of chemicals through the food chains and calculations of biomagnification and trophic magnification.
  • Metabarcoding of soil and invertebrate samples to provide data on species composition/richness to support modelling of effects of chemicals on species richness.
  • Analysis of soil physical characteristics to support modelling work.

Case study collaborators

The 12 case studies are implemented in collaboration with scientific institutions and ecological research companies that have relevant expertise in sampling of wild biota.

Barn owl food chain case studies

CS1.1 Tyto alba Netherlands – Dr Jasja Dekker (Jasja Dekker Dierecologie) & Henri Zomer (Aestas Ecologie)

CS1.2 Tyto alba Germany – Dr Oliver Krone (Leibniz Institute for Zoo & Wildlife Research, Berlin)

CS1.3 Tyto alba Spain – Dr Pilar Gomez-Ramirez (University of Murcia)

CS1.4 Tyto alba Portugal – Dr Rui Lourenco & Dr (University of Evora)

CS1.5 Tyto alba Greece – Dr Petros Lymberakis (University of Crete, Heraklion)

CD1.6 Tyto alba Romania – Dr Emanuel Baltag (SC. Naturserv SRL)

Apex mammal food chain case studies

CS2.1 Beech marten Martes foina Netherlands – Dr Jasja Dekker (Jasja Dekker Dierecologie) & Henri Zomer (Aestas Ecologie)

CS2.2 Grey wolf Canis lupus Germany – Dr Oliver Krone (Leibniz Institute for Zoo & Wildlife Research, Berlin)

CS2.3 European badger Meles meles Spain – Dr Pilar Gómez-Ramírez (University of Murcia)

CS2.4 Egyptian mongoose Herpestes Ichneumon Portugal – Dr Rui Lourenço & Dr Inês Roque (University of Evora)

CS2.5 Northern white-breasted hedgehog Erinaceus roumanicus Greece – Dr Petros Lymberakis (University of Crete, Heraklion)

CS2.6 Red fox Vulpes vulpes Romania – Dr Emanuel Baltag (SC Naturserv SRL)

Review and extraction of secondary data on chemicals in terrestrial wildlife

In addition to the collection of primary data from the 12 case studies, TerraChem is extracting data from the literature and from related databases on chemicals in terrestrial wildlife in Europe.

This includes data on plant protection products (PPPs), on other organic substances (e.g. industrial chemicals such as PFAS) and on metals and metalloids. This work focuses on the same taxa addressed by our case studies – owls, canids, mustelids, mongooses and hedgehogs. Where studies on apex species also report data on food chain biota (rodents, invertebrates, plants) and/or soil we are also extracting this data. This extracted secondary data will be uploaded to the TerraChem database and made available for TerraChem work on modelling and prevention and mitigation, as well as made available (open access) for the use of regulators, researchers and others.

Topic 2 Modelling Chemical Source-to-Damage Pathways in Terrestrial Ecosystems

Objective

WP2 aims to develop a comprehensive framework to understand how chemical pollutants move through terrestrial environments and impact biodiversity at multiple biological levels — from genes and species to functional diversity and ecosystem services.

The specific objectives of WP2 are to:

  • Provide a set of terrestrial source-to-receptor pathways for chemicals and compare them against receptor limits for these chemicals.
  • Characterize the link between terrestrial ecotoxicity effects and damage to species and genetic diversity.
  • Derive metrics for damage to multi-trophic functional diversity and selected ecosystem services.

Modelling the Impact of Chemical Pollution on Biodiversity

WP2 develops a source-to-damage modelling framework to quantify the effects of chemical pollution on biodiversity.

The modeling framework in Work Package 2

We model the distribution and fate of selected chemicals across different compartments (air, water, and soil) using geospatial multimedia models (i.e., Pangea), as shown in the Figure below for the concentration of Lambda-Cyhalothrin in freshwater and agricultural soil. And link these exposure patterns to ecological impacts across multiple levels of biological organization.

Maps showing the distribution of Lambda-Cyhalothrin (insecticide field application) in Europe, as an output from Pangea

Species Diversity

Our approach links ecotoxicity, expressed as the multi-substance Potentially Affected Fraction of species (msPAF) for a chemical mixture, to observed biodiversity impacts. By calibrating this relationship using biomonitoring data, we estimate the Potentially Disappeared Fraction of species (PDF) as the final impact metric indicating species loss across ecotoxicity gradients.

Genetic Diversity

We assess the impacts of chemical pollution on genetic diversity by integrating chemical activity data with existing knowledge on genetic variability within and across species. By working with publicly available datasets, we form connections between potential chemical exposures and genetic variability in wild populations. These purely computational methods aim to address some of the challenges in lab and field assessments of chemical impacts on genetically diverse populations by filling knowledge gaps and highlighting areas for further assessment.

Functional Diversity

We quantify the potentially affected fraction of functional diversity with a focus on functional richness by linking species-specific toxicity data to species abundance and trait information, where different traits are associated with different ecological functions.

Ecosystem Services

We evaluate the effects of chemical stress on key ecosystem functions for species with ample exposure and ecotoxicity data. Using chemical interference on the roles that species play in certain ecosystem functions, we aim to understand how pollution alters service delivery.

All models will be trained and validated using empirical observations and secondary datasets, supported by those provided by WP1, ensuring robust and data-driven outcomes.

Topic 3 Risk prevention and mitigation

WP3 will utilize the results of WP1 and WP2 to reach a more realistic risk assessment and to trigger risk management of chemicals with strongest that impact different levels of biodiversity. The focus is on

  • the development of a prioritization framework
  • a reality check study
  • the optimization of current environmental risk assessment (ERA) practices & the analysis on alternative risk mitigation measures (RMM)

Illustration of different drivers of biodiversity loss

Prioritization scheme:

Based on a regulatory perspective, a new prioritization scheme for a hazard- and risk-based identification and prioritization of substances posing a risk to biodiversity will be developed. This scheme should incorporate and integrate various empirical evidence (lines of evidence) on the effects of chemicals at molecular, organism, population and ecosystem level. Some of this evidence is based on AI-supported models. Artificial intelligence (AI) in combination with high computational performance enables a deeper understanding of the interactions in ecosystems and food webs, which are crucial for the characterization of indirect effects. In addition, new indicators for the effects of chemicals on genetic and functional diversity (from WP2) will also be integrated. Combining these evidences in a scheme will enable the generation of a list of substances that are suspected of damaging ecosystems and should be focused on as part of Europe-wide monitoring programs to determine their specific effects.

Reality-case study:

Based on 20 model substances, a real-world case study for reliability testing of registration data from industry will be evaluated in which monitoring data on chemical pollution and accumulation of chemicals are compared with model predictions and publicly available industry data. Relevant information on inherent properties (persistency, mobility, bioaccumulation, toxicity) of the selected compounds (industrial chemicals, biocides, plant protection products, etc.) will be extracted from public databases and compared with summarize data on exposure information and risk ratios.

Improvement of the ERA & analysis of RMM:

Based on reviews, in depth analysis and problem analysis of the “big five” European chemical regulatory frameworks for industrial chemicals (REACH), biocidal products (BP), plant protection products (PPP), medicinal products for human use (HMP), medicinal products for veterinary use (VMP) as well as the crosscutting CLP (classification, labeling and packaging) regulation, current data gaps on terrestrial hazard and risk assessment (species level) and damage to biodiversity and ecosystem services will be addressed, refinements and ways to implement novel approaches will be examined and novel RMM & policy options will be proposed.

Topic 4 Data management

TerraChem Data Management System (TDMS), TerraChem Early Warning System (TEWS) and TerraChem dashboard

At present, there is no single location where data on chemicals in terrestrial ecosystems in Europe can be store, analysed and accessed. The NORMAN Database System (NDS), and in particular the biota modules and related data treatment tools developed under the precursor LIFE APEX project (2019-2022), offer a promising location in this respect. NDS is already widely used by regulators, industry and academia, already stores several million data points on chemicals in biota as well as on chemicals in abiotic media and is linked to IPCHEM, the European Commission’s data portal on chemicals in the environment.

The TerraChem Data Management System (TDMS) builds on NDS by:

  • populating, with primary data from the TerraChem case studies and with relevant secondary data (extracted from literature and related databases), existing NDS modules:
    • Sample Catalogue (data on biota samples used for contaminant analysis)
    • Chemical Occurrence database (data from wide-scope target analysis and conventional target analyses)
  • developing additional database modules to accommodate new types of data arising from TerraChem, such as data on effects of chemicals on genetic diversity, functional diversity and ecosystem services
  • developing new data interpretation tools, for example, to provide information on routes of exposure (where the databases house data on co-located samples along trophic chains), to provide information on bioaccumulation, biomagnification and trophic transfer, and tools allowing users to run models developed under WP2 using data stored in or uploaded to the databases, including a new TerraChem Early Warning System
  • developing a front-end TerraChem Dashboard that gives access to the data and data interpretation tools, and that conveys key findings to end users.