@misc{KaestnerVijselCaviedesVoulliemeetal., author = {K{\"a}stner, Karl and Vijsel, Roeland C. van de and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {Unravelling the spatial structure of regular environmental spatial patterns}, series = {EGU General Assembly 2024, Vienna, Austria \& Online, 14-19 April 2024}, journal = {EGU General Assembly 2024, Vienna, Austria \& Online, 14-19 April 2024}, publisher = {Copernicus GmbH}, doi = {10.5194/egusphere-egu24-3412}, abstract = {Spatial patterns where patches of high biomass alternate with bare ground occur in many resource-limited ecosystems. Especially fascinating are regular patterns, which are self-similar at a lag distance corresponding to the typical distance between patches. Regular patterns are understood to form autogenously through self-organization, which can be generated with deterministic reaction-diffusion models. Such models generate highly regular patterns, which repeat at the characteristic wavelength and are therefore periodic. Natural patterns do not repeat, as they are noisy and as the patch size and spacing vary. Natural patterns are therefore usually perceived as perturbed periodic patterns. However, the self-similarity of natural patterns decreases at longer lag distances, which indicates that their spatial structure is not a perturbed periodic structure originating through deterministic processes. Here, we provide an overview of our recent work on the spatial structure and formation of natural environmental spatial patterns as a basis for discussion: First, we develop a statistical periodicity test and compile a large dataset of more than 10,000 regular environmental spatial patterns. We find that neither isotropic (spotted) nor anisotropic (banded) patterns are periodic. Instead, we find that their spatial structure can be well described as random fields originating through stochastic processes. Second, we recognize the regularity as a gradually varying property, rather than a dichotomous property of being periodic or not. We develop a method for quantifying the regularity and apply it in a metastudy to a set of natural and model-generated patterns found in the literature. We find that patterns generated with deterministic reaction-diffusion models do not well reproduce the spatial structure of environmental spatial structure, as they are too regular. Third, we develop an understanding of pattern formation through stochastic reaction-diffusion processes, which incorporate random environmental heterogeneities. We find that regular patterns form through filtering of the environmental heterogeneities and identify stochastic processes which reproduce both isotropic and anisotropic patterns.}, language = {en} } @misc{KaestnerVijselCaviedesVoulliemeetal., author = {K{\"a}stner, Karl and Vijsel, Roeland C. van de and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {A scale-invariant method for quantifying the regularity of environmental spatial patterns}, series = {Ecological Complexity}, volume = {60}, journal = {Ecological Complexity}, publisher = {Elsevier BV}, issn = {1476-945X}, doi = {10.1016/j.ecocom.2024.101104}, pages = {13}, abstract = {Spatial patterns of alternating high and low biomass occur in a wide range of ecosystems. Patterns can improve ecosystem productivity and resilience, but the particular effects of patterning depend on their spatial structure. The spatial structure is conventionally classified as either regular, when the patches of biomass are of similar size and are spaced in similar intervals, or irregular. The formation of regular patterns is driven by scale-dependent feedbacks. Models incorporating those feedbacks generate highly regular patterns, while natural patterns appear less regular. This calls for a more nuanced quantification beyond a binary classification. Here, we propose measuring the degree of regularity by the maximum of a pattern's spectral density, based on the observation that the density of highly regular patterns consists of a narrow and high peak, while the density of highly irregular patterns consists of a low and wide lobe. We rescale the density to make the measure invariant with respect to the characteristic length-scale of a pattern, facilitating the comparison of patterns observed or modelled under different conditions. We demonstrate our method in a metastudy determining the regularity of natural and model-generated patterns depicted in previous studies. We find that natural patterns have an intermediate degree of regularity, resembling random surfaces generated by stochastic processes. We find that conventional deterministic models do not reproduce the intermediate regularity of natural patterns, as they generate patterns which are much more regular and similar to periodic surfaces. We call for appreciating the stochasticity of natural patterns in systems with scale-dependent feedbacks.}, language = {en} } @misc{KaestnerVijselCaviedesVoulliemeetal., author = {K{\"a}stner, Karl and Vijsel, Roeland C. van de and Caviedes-Voulli{\`e}me, Daniel and Frechen, Nanu T. and Hinz, Christoph}, title = {Unravelling the spatial structure of regular dryland vegetation patterns}, series = {CATENA}, volume = {247}, journal = {CATENA}, publisher = {Elsevier BV}, issn = {0341-8162}, doi = {10.1016/j.catena.2024.108442}, pages = {13}, abstract = {Many resource-limited ecosystems exhibit spatial patterns where patches of biomass alternate with bare ground. Patterns can enhance ecosystem functioning and resilience, depending on their spatial structure. Particularly conspicuous are regular patterns, where patches are of similar size and spaced in similar intervals. The spatial structure of regular patterns is often described to be periodic. This has been corroborated by statistical testing of natural patterns and generation of periodic patterns with deterministic reaction-diffusion models. Yet, natural regular patterns appear conspicuously erratic compared to periodic patterns. So far, this has been attributed to perturbations by noise, varying patch size and spacing. First, we illustrate by means of an example that the spatial structure of regular vegetation patterns cannot be reproduced by perturbing periodic patterns. We then compile a large dataset of regular dryland patterns and find that their spatial structure systematically differs from periodic patterns. We further reveal that previous studies testing for periodicity overlook two aspects which dramatically inflate the number of false positives and result in the misclassification of patterns as periodic. We amend the test procedure by accounting for both aspects, finding that regular natural patterns have no significant periodic components. Lastly, we demonstrate that stochastic processes can generate regular patterns with similar visual appearance, spatial structure and frequency spectra as natural regular patterns. We conclude that new methods are required for quantifying the regularity of spatial patterns beyond a binary classification and to further investigate the difference between natural and model generated patterns.}, language = {en} } @misc{LehmkuhlGerwinRaabetal., author = {Lehmkuhl, Frank and Gerwin, Werner and Raab, Thomas and Birkhofer, Klaus and Hinz, Christoph and Letmathe, Peter and Leuchner, Michael and Roß-Nickoll, Martina and R{\"u}de, Thomas R. and Trachte, Katja and W{\"a}tzold, Frank}, title = {Perspectives for the lignite post-mining landscapes of the lignite mining landscapes under changing environmental conditions - what can we learn from a comparison between the Rhenish and the Lusatian regions in Germany? : EGU General Assembly 2024, Vienna, Austria \& Online | 14-19 April 2024}, publisher = {Copernicus GmbH}, doi = {10.5194/egusphere-egu24-2791}, abstract = {The German government's decision to phase out lignite mining by 2038 or earlier, as recently 2030 has been agreed for the Rhineland, will trigger a number of transition processes in Germany's remaining lignite mining areas. The two largest lignite mining areas are located in geographically different regions: Rhineland in the west and Lusatia in the east. As the socio-economic and environmental conditions in these two mining areas are set to change dramatically, the German government has adopted extensive economic support measures. However, the environmental changes will also lead to changes in the ecosystem functions and services provided by the future post-mining landscapes. Gerwin et al. (2023) compare the two main lignite producing regions of Germany in terms of their natural and cultural environments. The economic situation and its history are reflected and differences are outlined. Part of the differences in cultural development can be explained by the natural conditions, especially the edaphic factors and the climatic situation. Because of the specific geological settings, tailored mining technologies were developed and used in the two regions, with different effects on the resulting post-mining landscapes. We conclude that the landscapes of Lusatia and the Rhineland have been radically restructured by the long and varied history of lignite mining. Both regions will change significantly as the mining industry continues to decline and is expected to cease altogether within the next decade. These changes in the post-mining landscapes and the ecosystem services will provide both challenges and opportunities. The preconditions for positive socio-economic development and for sustainable land use concepts that also consider ecological aspects are different for the two regions. The exchange of knowledge and experience between the two mining regions is crucial to the success of this major transformation process, despite, or perhaps because of, these differences. Gerwin, W., Raab, T., Birkhofer, K., Hinz, C., Letmathe, P., Leuchner, M., Ro\&\#223;-Nickoll, M., R\&\#252;de, T., Trachte, K., W\&\#228;tzold, F., Lehmkuhl, F. (2023): Perspectives of lignite post-mining landscapes under changing environmental conditions: what can we learn from a comparison between the Rhenish and Lusatian region in Germany? Environmental Sciences Europe 35:36. https://doi.org/10.1186/s12302-023-00738-z}, language = {en} }