Landscape Moderation of Ecological Patterns and Processes

Hanß, Sebastian

dc.contributor.advisor	Wiegand, Kerstin Prof. Dr.
dc.contributor.author	Hanß, Sebastian
dc.date.accessioned	2025-02-25T18:00:28Z
dc.date.available	2025-03-04T00:50:04Z
dc.date.issued	2025-02-25
dc.identifier.uri	http://resolver.sub.uni-goettingen.de/purl?ediss-11858/15848
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-11079
dc.format.extent	136	de
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject.ddc	570	de
dc.title	Landscape Moderation of Ecological Patterns and Processes	de
dc.type	doctoralThesis	de
dc.contributor.referee	Tscharntke, Teja Prof. Dr.
dc.date.examination	2025-01-29	de
dc.description.abstracteng	This dissertation studies landscape moderation of ecological patterns and processes by employing different modeling approaches to investigate how landscape patterns influence ecological processes and, reversely, how ecological processes form landscape patterns. The research presented in this dissertation combines two powerful modeling frameworks: pattern-oriented modeling and individual-based modeling. Pattern-oriented modeling integrates empirical data with theory to enhance predictive accuracy, while individual-based modeling simulates patterns emerging from the behavior and interactions of individual organisms within their ecosystems. The dissertation is structured into three main chapters, each targeting a distinct question on the relationship between landscape patterns and ecological processes: In the first study, we investigated the relative effects of habitat amount and fragmentation on species population sizes using the MOBILE simulation model. We model the species’ population sizes because the population dynamics allow us to infer possible threats to biodiversity over time, such as an extinction debt due to small population sizes. We simulated 17 modeled ground beetle species on 600 artificial landscapes to disentangle the independent effects of fragmentation and habitat amount. Our results showed an independent negative effect of fragmentation on the simulated populations, but the effect was smaller than that of habitat loss. The relative effect of fragmentation on the population size was stronger for smaller amounts of habitat and species-specific. We also found that species with higher dispersal abilities were less affected by fragmentation in our model. Our study demonstrates the utility of simulation models for analyzing the complex relationships between species and their landscape context. The second study introduced the FACIA model, which we used to simulate spatial vegetation self-organization and showed how can lead to fairy circles, i.e. to circular barren patches that are regularly distributed in space in a hexagonal pattern. FACIA models only two mechanisms, local facilitation and non-local competition, which generate the emergent patterns of fairy circles. The FACIA model successfully replicated the characteristic spatial patterns of fairy circles. Further simulation experiments showed that self-organization can reproduce the deformed fairy circle patterns found under local disturbance by car tracks. With a combination of simplicity and structural realism, we demonstrated with FACIA how combining individual-based and pattern-oriented modeling leads to a deeper understanding of how small-scale processes can lead to landscape-scale patterns. In the third study, we developed the R package spectre, which uses minimal biological data to estimate regional community compositions at fine spatial resolutions. Based on an optimization algorithm and α-, β-, and γ-diversity estimates from scarcely sampled field data, spectre can predict realistic species presences and absences at hundreds of unsampled sites in a landscape. In ecological modeling, spectre may become especially useful to realistically initialize simulation models when field data with α-, β- and γ-diversity is available. In this application, spectre would be used to apply the same diversity functions on different artificial landscapes, and the resulting spatially explicit biodiversity patterns could then be used as an input to simulation experiments. All three studies emphasize the advantages of integrating models with empirical data, thereby facilitating a more comprehensive understanding of ecological dynamics and ultimately informing and even enabling effective conservation strategies. Our findings advance ecological theory while at the same time providing practical insights for managing and preserving biodiversity in a changing world. The dissertation concludes with a general discussion integrating findings from all three studies. It emphasizes the necessity of combining theoretical approaches with computational tools for investigating complex ecological phenomena. In modeling beetle populations, simulating the formation of fairy circles, and developing the spectre R package, we demonstrated the significance of addressing species-specific responses to habitat fragmentation, understanding the mechanisms of landscape pattern formation, and developing computational tools to enhance biodiversity research in order to ultimately support the sustainable management of biodiversity in changing landscapes.	de
dc.contributor.coReferee	Kreft, Holger Prof. Dr.
dc.subject.eng	Landscape ecology	de
dc.subject.eng	Ecological modeling	de
dc.subject.eng	Pattern-oriented modeling	de
dc.subject.eng	Individual-based modeling	de
dc.subject.eng	Habitat fragmentation	de
dc.subject.eng	Simulation models	de
dc.subject.eng	Fairy Circles	de
dc.subject.eng	Computational ecology	de
dc.subject.eng	Ground beetles	de
dc.subject.eng	Self-organization	de
dc.subject.eng	Habitat amount	de
dc.subject.eng	Spatial vegetation patterns	de
dc.subject.eng	R-package	de
dc.identifier.urn	urn:nbn:de:gbv:7-ediss-15848-1
dc.affiliation.institute	Fakultät für Forstwissenschaften und Waldökologie	de
dc.subject.gokfull	Forstwirtschaft (PPN621305413)	de
dc.description.embargoed	2025-03-04	de
dc.identifier.ppn	1918667160
dc.identifier.orcid	0000-0002-3990-4897	de
dc.notes.confirmationsent	Confirmation sent 2025-02-25T19:45:01	de

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