This topic 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 work on topics 2 to 4:

• 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.

Objectives

1. To detect and determine chemicals present, and predominant chemical mixtures, in selected food chains (from plants and primary consumers to apex predators), in representative terrestrial ecosystems.
2. For detected and determined chemicals, understand routes of exposure including routes and extent of trophic transfer.
3. To explore patterns for individual contaminants and predominant mixtures in terrestrial trophic chains.
4. To elucidate toxic effects of chemical mixtures in terrestrial food chains using an effects-based approach.
5. To identify and collate secondary data on contaminants along trophic chains in terrestrial ecosystems in Europe.

Work being carried out

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.