New spatially explicit population model – APODEMUS to improve pesticide risk assessments in agricultural landscapes

A formal model published in the open-access Agricultural and Environmental Modelling Journal describes the development of APODEMUS, which aims to improve risk assessments of pesticides for the wood mouse (Apodemus sylvaticus) in European agricultural landscapes.

A team of international scientists and risk assessment experts has developed a foundational blueprint for an innovative population model, designed to improve environmental safety testing for agricultural pesticides. The tool, named APODEMUS (A POpulation Dynamical spatially Explicit Model of the wood moUSe), was recently published as a “Formal Model” – a novel article type, in the Agricultural and Environmental Modelling journal.

Bridging the Gap Between the Lab and the Field

Currently, environmental risk assessments rely heavily on laboratory toxicity tests (often using Norway rats instead of wild mice) and field studies. While field studies are realistic, they are highly expensive, time-consuming, and are often limited to a few specific locations, crops, and weather conditions.

Wood mouse (Apodemus sylvaticus)
Wood mouse (Apodemus sylvaticus). Photo credit to Laura Fokkema via Canva.

The wood mouse (Apodemus sylvaticus) is extremely common across Europe and lives in a wide variety of habitats, including farmlands. Because they eat a broad diet of seeds, plants, and insects, they frequently forage in agricultural fields. Consequently, the European Union uses the wood mouse as a primary “focal species” to evaluate whether a plant protection product (pesticide) poses an unacceptable risk to small mammals.

APODEMUS acts as a virtual testing ground

By creating a population model, scientists can simulate complex, real-world agricultural landscapes and farming scenarios to predict how pesticide exposure impacts animal survival and reproduction over the long term.

How does it work?

Overview diagram of the conceptual population model for APODEMUS.

Overview diagram of the conceptual population model for APODEMUS. The model simulates the wood mouse life cycle, growth and reproduction. Landscape composition is captured by habitat types (numbers) and influences the space use of the simulated wood mice. Exposures can be linked to the use of defined habitat patches and types. Credit to Singer et al., 2026.

Published as a Formal Model (a new peer-reviewed publishing format designed to make modelling research FAIR (Findable, Accessible, Interoperable, and Reusable) by enabling scholarly credit for diverse research outputs and enhance the transparency and rigor of complex ecological and systems modelling). The current study focuses on the “conceptual model“,  meaning the researchers have defined the biological and ecological rules the computer program will follow, essentially building a highly realistic “virtual wood mouse” before adding the complexities of exposure and effects of Plant Protection Products (PPPs) such as pesticides.

What differentiates APODEMUS from previous models is the explicit implementation of “Dynamic Energy Budget” that tracks how individual mice convert consumed food into energy for growth, body maintenance, and reproduction. These virtual mice are placed into realistic, grid-based landscapes (like woods, pastures, and crop fields) where they dynamically establish home ranges based on habitat attractiveness, with female territoriality naturally preventing overpopulation. Finally, the model simulates diet-based exposure by correlating the time a mouse spends foraging in specific fields to its food intake, which will be used in future updates to calculate exact pesticide ingestion.

Built on Massive Data and Unprecedented Collaboration

Diagram showing the number of publications providing at least one data item to inform a population model characteristic for the wood mouse
Number of publications providing at least one data item to inform a population model characteristic for the wood mouse. Credit to Singer et al., 2026.

To ensure the simulation is scientifically rigorous and acceptable to government regulators, a massive foundation of real-world data was used. The authors conducted a systematic review of 341 scientific publications, extracting 1,295 specific data points about wood mouse biology.

A key highlight of this study is that the model was built through a collaboration with stakeholders – including ecological experts, risk assessors, and chemical regulators – in a dedicated workshop. By following a European standard for ecological modeling such as the European Food Safety Authority (EFSA) and “Pop-GUIDE,” they ensured that every decision in the model’s design is highly transparent and justified.

What happens next?

The researchers are currently translating this conceptual blueprint into functioning computer code. Once the virtual wood mouse population is up and running, scientists will introduce virtual pesticide applications into the model. This will allow them to evaluate how individual mice absorb toxins, whether they survive, and whether the overall population can recover under various real-world farming scenarios.

Ultimately, APODEMUS offers an innovative foundational blueprint and a practical tool aimed at helping regulators accurately test the environmental safety of agricultural pesticides by simulating their long-term effects on wild animal populations across a variety of realistic landscapes that would be otherwise impossible to assess through physical field studies

Original study:

Singer A, Schmolke A, Becher MA, von Blanckenhagen F, van den Brink N, Grimm T, Ibrahim L, Imholt C, Jacob J, Jakoby O, Laucht S, Løvik AN, Martin T, Muñoz CC, Preuss TG, Galic N (2026) Concept for APODEMUS – a wood mouse population model for pesticide risk assessment. Food and Ecological Systems Modelling Journal 7: e175714. https://doi.org/10.3897/fmj.7.175714

Modelling Life Beneath Our Feet: A New Step Towards Realistic Soil Ecology At The Landscape Scale

New Formal Model in the open-access Agricultural and Environmental Modelling journal contributes to a more realistic soil ecology modelling at the landscape level.

Guest blog post by Liyan Xie

Why focus on soil organisms?

Agricultural landscape
Agricultural landscape. Image via Canva.

Soil health is a core priority of the EU Soil Strategy for 2030, and soil organisms like Collembola (springtails) play a fundamental role in sustaining it. With an estimated 100,000 individuals per square meter in healthy soils, these invertebrates drive essential processes like nutrient cycling, organic matter fragmentation, and microbial regulation, while also serving as crucial prey for predators like spiders and mites. Despite their ecological importance and their distinct chemical exposure pathways compared to earthworms, they remain underrepresented in landscape-level environmental risk assessments, which often rely on simplified laboratory studies.

Moving beyond simplified tests

Assessing multiple ecosystem stressors
A framework for assessing multiple ecosystem stressors. Image credit to Liyan Xie.

Traditional ecotoxicological testing, such as standard OECD laboratory tests, has provided valuable baseline data for over 60 years, but these tests are typically conducted under constant, highly controlled conditions. While informative, this approach overlooks the dynamic nature of environmental drivers like temperature and soil moisture, which jointly shape physiological performance.

For example, existing population models often ignore soil moisture entirely or rely on simplistic constant temperatures. Addressing this gap requires advanced modelling tools that can represent non-linear life-history processes, such as stage transitions and vital rates, under realistic, fluctuating conditions.

To achieve this, the researchers utilized the Animal, Landscape and Man Simulation System (ALMaSS), a spatially explicit modelling framework that integrates static landscape features like soil types with dynamic, daily components like hourly weather data, crop management practices, and vegetation growth to simulate realistic environments for species populations

A mechanistic model of a soil species

In a recently published Formal Model in the open-access Agricultural and Environmental Modelling journal, researchers developed a spatially explicit stage-structured population model for the springtail Folsomia candida within the ALMaSS framework. The model explicitly represents egg, juvenile, and adult life stages, linking development, reproduction, and survival to environmental conditions using empirically parameterized thermal performance curves and dose-response functions. 

A key highlight of the model is its advanced estimation of surface soil water potential, which integrates high-resolution ERA5 weather data, evapotranspiration, and physical soil properties. By grounding these processes in biological mechanisms and factoring in food quality, the model provides a highly realistic representation of how soil populations respond to their environment

Scaling up: from local processes to landscapes

Spatial and temporal populations modelling.
Spatial and temporal populations modelling. Image credit to Liyan Xie.

The model is spatially explicit, simulating populations across large agricultural landscapes, typically 10 km by 10 km, divided into detailed polygons and grid cells. 

Using daily time steps for simulations lasting up to five years, the model captures subpopulation dynamics at a high-resolution spatial scale of 100 square meters. It even incorporates realistic, density-dependent dispersal behaviors, triggering adult springtails to migrate to surrounding cells when population densities exceed 100,000 per square meter or when food availability is severely restricted

This allows local environmental conditions to shape subpopulations, which together determine broader population dynamics. Such an approach enables exploration of how small-scale processes propagate to landscape-level patterns, including population persistence and recovery.

A foundation for future risk assessment

Even though the current version of the model focuses purely on environmental stressors without chemical exposure, its flexible structure serves as a foundational framework that can be easily extended. By eventually integrating toxicity modules, the model will enable the investigation of population-level impacts driven by agrochemical usage, such as pesticides and fertilizers, across different European farming practices. This mechanistic framework improves the interpretation of standardised laboratory and higher-tier mesocosm tests, providing a crucial tool for assessing the impact of multiple stressors under environmentally realistic scenarios.

Why this matters

This work highlights the critical importance of developing robust, process-based ecological models before introducing the additional complexities of chemical stressors. By carefully balancing biological realism with empirical data availability, the model provides actionable outputs, such as population growth rates, spatial distributions, and population recovery times, which serve as essential indicators of relative environmental risk. Ultimately, models like this offer a pathway towards more scientifically grounded, realistic assessments of ecosystem health in a changing environment

Original source:

Xie L, Duan X, Norouzi S, de Jonge LW, Topping CJ (2026) Integrating spatial and environmental stressors in a population model of Folsomia candida (Collembola, Isotomidae): a Formal Model within ALMaSS framework. Agricultural and Environmental Modelling 8: e184962. https://doi.org/10.3897/aem.8.184962