Meta-populations under multiple stressor risks - simulation studies using a new process-based, spatially explicit model

  • Biodiversity is declining at an accelerating rate unprecedented in human history. Globally, most ecosystems are at high risk from multiple stressors related to anthropogenic global change, including climate change and land use change. Distinct stressors often co-occur in time and space, so joint effects are not only a result of individual severity or the speed of change but also of how they interact. To estimate and address (future) risks from intensified stressor regimes, it is needed to best understand the mechanisms of stressor joint effects and interactions. However, research on the topic is not well developed yet and current knowledge is relatively low. In the context of this thesis, the lack of (theoretical) knowledge will be reduced. Chapter 1 provides a brief introduction outlining the need for the presented research and the overall objectives of the thesis. Chapter 2 introduces a new process-based, spatially explicit meta-population model for a generic freshwater species which was applied to investigate how decreasing landscape permeability and fragmentation following global change will impact species meta-populations. It is shown that global change likely increases extinction risks by reduced habitat connectivity, however, management actions to enhance patch density can strengthen meta-populations resilience. Chapter 3 presents an extended version of the meta-population model, used to investigate how two stressors (i.e., climatic events and land use) with different spatiotemporal profiles combine over time. It was found that joint effects and interactions were mainly determined by land use, demonstrating the effectiveness of regional management to compensate for an intensified global stressor. Following on, Chapter 4 explores potential changes from more realistic scenarios, by incorporating dynamic stressor profiles (i.e., random climatic events and land use trends over time) plus adaptation into the model. It is highlighted that such complex scenarios are critical for understanding how species respond to global change, as simplified static scenarios are likely insufficient for reliable prediction of joint effects and interactions. Finally, chapter 5 briefly concludes the key findings of chapters 2-4, discusses the limitations of the individual studies’ approaches and gives a brief general outlook. Overall, the presented thesis provides new insights into the mechanistic understanding of joint effects and interactions of multiple stressors and, thereby, contributes to extending the conceptual framework of related research.

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Author:Lucas Streib
Advisor:Ralf B. Schäfer, Jürg Spaak
Document Type:Doctoral Thesis
Cumulative document:Yes
Language of publication:English
Date of Publication (online):2024/07/05
Date of first Publication:2024/07/08
Publishing Institution:Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Granting Institution:Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Acceptance Date of the Thesis:2024/01/19
Date of the Publication (Server):2024/07/08
Page Number:154 Seiten
Faculties / Organisational entities:Landau - Fachbereich Natur- und Umweltwissenschaften
DDC-Cassification:5 Naturwissenschaften und Mathematik / 570 Biowissenschaften, Biologie
Licence (German):Creative Commons 4.0 - Namensnennung, nicht kommerziell, keine Bearbeitung (CC BY-NC-ND 4.0)