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- 2021 (2) (entfernen)
Schlagworte
- Clustering coefficient (1)
- Ganzzahlige Optimierung (1)
- Gemischt-ganzzahlige Optimierung (1)
- Graph theory (1)
- Graphentheorie (1)
- Habitat loss (1)
- Habitat networks (1)
- Habitatsverlust (1)
- Mathematical optimisation (1)
- Metapopulation dynamics (1)
- Metapopulationsdynamiken (1)
- Mixed integer programming (1)
- Network robustness (1)
- Netzwerkrobustheit (1)
- Neuroactive chemicals (1)
- Toxicological characterization (1)
- Toxicology (1)
Despite the significant presence of neuroactive substances in the environment, bioassays that allow to detect diverse groups of neuroactive mechanisms of action are not well developed and not properly integrated into environmental monitoring and chemical regulation. Therefore, there is a need to develop testing methods which are amenable for fast and high-throughput neurotoxicity testing. The overall goal of this thesis work is to develop a test method for the toxicological characterization and screening of neuroactive substances and their mixtures which could be used for prospective and diagnostic hazard assessment.
In this thesis, the behavior of zebrafish embryos was explored as a promising tool to distinguish between different neuroactive mechanisms of action. Recently, new behavioral tests have been developed including photomotor response (PMR), locomotor response (LMR) and spontaneous tail coiling (STC) tests. However, the experimental parameters of these tests lack consistency in protocols such as exposure time, imaging time, age of exposure, endpoint parameter etc. To understand how experimental parameters may influence the toxicological interpretation of behavior tests, a systematic review of existing behavioral assays was conducted in Chapter 2. Results show that exposure concentration and exposure duration highly influenced the comparability between different test methods and the spontaneous tail coiling (STC) test was selected for further testing based on its relative higher sensitivity and capacity to detect neuroactive substances (Chapter 2).
STC is the first observable motor activity generated by the developing neural network of the embryo which is assumed to occur as a result of the innervation of the muscle by the primary motor neurons. Therefore, STC could be a useful endpoint to detect effect on the muscle innervation and also the on the whole nervous system. Consequently, important parameters of the STC test were optimized and an automated workflow to evaluate the STC with the open access software KNIME® was developed (Chapter 3).
To appropriately interpret the observed effect of a single chemical and especially mixture effects, requires the understanding of toxicokinetics and biotransformation. Most importantly, the biotransformation capacity of zebrafish embryos might be limited and this could be a challenge for assessment of chemicals such as organophosphates which require a bioactivation step to effectively inhibit the acetylcholinesterase (AChE) enzyme. Therefore, the influence of the potential limited biotransformation on the toxicity pathway of a typical organophosphate, chlorpyrifos, was investigated in Chapter 5. Chlorpyrifos could not inhibit AChE and this was attributed to possible lack of biotransformation in 24 hpf embryos (Chapter 5).
Since neuroactive substances occur in the environment as mixtures, it is therefore more realistic to assess their combined effect rather than individually. Therefore, mixture toxicity was predicted using the concentration addition and independent action models. Result shows that mixtures of neuroactive substances with different mechanisms of action but similar effects can be predicted with concentration addition and independent action (Chapter 4). Apart
from being able to predict the combined effect of neuroactive substances for prospective risk assessment, it is also important to assess in retrospect the combined neurotoxic effect of environmental samples since neuroactive substances are the largest group of chemicals occurring in the environment. In Chapter 6, the STC test was found to be capable of detecting neurotoxic effects of a wastewater effluent sample. Hence, the STC test is proposed as an effect based tool for monitoring environmental acute and neurotoxic effects.
Overall, this thesis shows the utility and versatility of zebrafish embryo behavior testing for screening neuroactive substances and this allows to propose its use for prospective and diagnostic hazard assessment. This will enhance the move away from expensive and demanding animal testing. The information contained in this thesis is of great potential to provide precautionary solutions, not only for the exposure of humans to neuroactive chemicals but for the environment at large.
Mathematical models of species dispersal and the resilience of metapopulations against habitat loss
(2021)
Habitat loss and fragmentation due to climate and land-use change are among the biggest threats to biodiversity, as the survival of species relies on suitable habitat area and the possibility to disperse between different patches of habitat. To predict and mitigate the effects of habitat loss, a better understanding of species dispersal is needed. Graph theory provides powerful tools to model metapopulations in changing landscapes with the help of habitat networks, where nodes represent habitat patches and links indicate the possible dispersal pathways between patches.
This thesis adapts tools from graph theory and optimisation to study species dispersal on habitat networks as well as the structure of habitat networks and the effects of habitat loss. In chapter 1, I will give an introduction to the thesis and the different topics presented in this thesis. Chapter 2 will then give a brief summary of tools used in the thesis.
In chapter 3, I present our model on possible range shifts for a generic species. Based on a graph-based dispersal model for a generic aquatic invertebrate with a terrestrial life stage, we developed an optimisation model that models dispersal directed to predefined habitat patches and yields a minimum time until these patches are colonised with respect to the given landscape structure and species dispersal capabilities. We created a time-expanded network based on the original habitat network and solved a mixed integer program to obtain the minimum colonisation time. The results provide maximum possible range shifts, and can be used to estimate how fast newly formed habitat patches can be colonised. Although being specific for this simulation model, the general idea of deriving a surrogate can in principle be adapted to other simulation models.
Next, in chapter 4, I present our model to evaluate the robustness of metapopulations. Based on a variety of habitat networks and different generic species characterised by their dispersal traits and habitat demands, we modeled the permanent loss of habitat patches and subsequent metapopulation dynamics. The results show that species with short dispersal ranges and high local-extinction risks are particularly vulnerable to the loss of habitat across all types of networks. On this basis, we then investigated how well different graph-theoretic metrics of habitat networks can serve as indicators of metapopulation robustness against habitat loss. We identified the clustering coefficient of a network as the only good proxy for metapopulation robustness across all types of species, networks, and habitat loss scenarios.
Finally, in chapter 5, I utilise the results obtained in chapter 4 to identify the areas in a network that should be improved in terms of restoration to maximise the metapopulation robustness under limited resources. More specifically, we exploit our findings that a network’s clustering coefficient is a good indicator for metapopulation robustness and develop two heuristics, a Greedy algorithm and a deducted Lazy Greedy algorithm, that aim at maximising the clustering coefficient of a network. Both algorithms can be applied to any network and are not specific to habitat networks only.
In chapter 6, I will summarize the main findings of this thesis, discuss their limitations and give an outlook of future research topics.
Overall this thesis develops frameworks to study the behaviour of habitat networks and introduces mathematical tools to ecology and thus narrows the gap between mathematics and ecology. While all models in this thesis were developed with a focus on aquatic invertebrates, they can easily be adapted to other metapopulations.