arXiv subjects

Florian Schunck

Publications and source records attributed to Florian Schunck.

4 recordsLinked to original sources

arXiv2026

From Lab to Landscape: Assessing the Impact of Pesticides on Pollinator Populations Based on Laboratory Data by Combining ALMaSS and BufferGUTS

Pesticides are designed to eradicate pests from crops, fulfilling an important role in the current agricultural system. However, nature conservation requires that pesticide applications are protective for non-target organisms, which provide ecosystem services on the other hand. Environmental risk assessment (ERA) is supposed to strike this balance, but the current use of laboratory derived toxicity thresholds in the landscape context, without consideration of population and landscape dynamics might be too coarse to achieve this task. Here, we propose to overcome this limitation by coupling the Animal, Landscape, and Man Simulation System with the BufferGUTS model for non-target arthropods. We conducted a case study of the solitary bee Osmia bicornis exposed to the pesticide formulation Closer (a.i. sulfoxaflor) to assess the integration. Laboratory survival data of topical and oral exposure to Closer were used to calibrate BufferGUTS models. The resulting parameters were used to parametrise model organisms in ALMaSS simulations to extrapolate the effects of sulfoxaflor at different exposure levels on population dynamics. The integration of BufferGUTS into ALMaSS landscape simulation was achieved with high numerical precision, allowing for the calculation of daily survival probabilities for model organisms in the ALMaSS framework. We found that even extreme application rates only led to negligible population effects in ALMaSS simulations, but an exploratory analysis of pesticide-driven larval mortality showed that effects might be more severe when all life stages are considered. The work demonstrates how mechanistic modelling embedded into individual based modelling frameworks can support ERA by combining exposure and effect in systems-based ERA tools, bridging the gap between controlled laboratory experiments and realistic landscape-scale risk assessments for next generation ERA.

q-bio.PE↗

arXiv2024

Integrating time-resolved $nrf2$ gene-expression data into a full GUTS model as a proxy for toxicodynamic damage in zebrafish embryo

The immense production of the chemical industry requires an improved predictive risk assessment that can handle constantly evolving challenges while reducing the dependency of risk assessment on animal testing. Integrating 'omics data into mechanistic models offers a promising solution by linking cellular processes triggered after chemical exposure with observed effects in the organism. With the emerging availability of time-resolved RNA data, the goal of integrating gene expression data into mechanistic models can be approached. We propose a biologically anchored TKTD model, which describes key processes that link the gene expression level of the stress regulator $nrf2$ to detoxification and lethality by associating toxicodynamic damage with $nrf2$ expression. Fitting such a model to complex datasets consisting of multiple endpoints required the combination of methods from molecular biology, mechanistic dynamic systems modeling and Bayesian inference. In this study we successfully integrate time-resolved gene expression data into TKTD models, and thus provide a method for assessing the influence of molecular markers on survival. This novel method was used to test whether, $nrf2$, can be applied to predict lethality in zebrafish embryos. With the presented approach we outline a method to successively approach the goal of a predictive risk assessment based on molecular data.

q-bio.QM↗

arXiv2023

A dynamic network model of societal complexity and resilience inspired by Tainter's theory of collapse

In recent years, several global events have severely disrupted economies and social structures, undermining confidence in the resilience of modern societies. While empirical evidence on the dynamics and drivers of past societal collapse is mounting, a process-based understanding of these dynamics is still in its infancy. Here we aim to identify and illustrate the underlying drivers of such societal instability or even collapse. The inspiration for this work is Joseph Tainter's theory of the "collapse of complex societies", which postulates that the complexity of societies increases as they solve problems, leading to diminishing returns on complexity investments, and ultimately to collapse. In this work we have abstracted this theory into a low-dimensional and stylised model of two classes of networked agents, hereafter referred to as "laborers" and "administrators". We numerically modeled the dynamics of societal complexity, measured as the fraction of "administrators", which is assumed to affect the productivity of connected energy-producing "laborers". We show that collapse becomes increasingly likely as the complexity of the model society continuously increases in response to external stresses that emulate Tainter's abstract notion of problems that societies must solve. We also provide an analytical approximation of the system's dominant dynamics, which matches well with the numerical experiments, and use it to study the influence on network link density, social mobility and productivity. Our work advances the understanding of social-ecological collapse and illustrates its potentially direct link to an ever-increasing societal complexity in response to external shocks or stresses via a self-reinforcing feedback.

physics.soc-ph↗

arXiv2023

Persistent disruption of interspecific competition after ultra-low esfenvalerate exposure

Field and mesocosm studies repeatedly show that higher tier process reduce the predictive accuracy of toxicity evaluation and consequently their value for pesticide risk assessment. Therefore, understanding the influence of ecological complexity on toxicant effects is crucial to improve realism of aquatic risk assessment. Here we investigate the influence of repeated exposure to ecologically realistic concentrations of esfenvalerate on the similarly sensitive species Daphnia magna and Culex pipiens in a food limited and highly competitive environment. We show that significant perturbations in population development are only present close to the EC50. In contrast, interspecific competition between species is already reduced at concentrations 3-4 orders of magnitude below the acute EC50. We conclude that extremely low, environmentally relevant concentrations can disrupt species interactions. This toxicant mediated alteration of competitive balances in ecological communities may be the underlying mechanism for shifts in species distribution at ultra-low pesticide concentrations. A realistic risk assessment should therefore consider these processes in order to predict potential pesticide effects on the structure of communities.

q-bio.PE↗