Guest blog post by Liyan Xie
Why focus on soil organisms?
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
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
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