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Bayesian analysis of biodiversity patterns via beam trawl versus video transect : a comparative case study of Svalbard rhodolith beds

Title data

Straube, Eileen ; Neumann, Hermann ; Wisshak, Max ; Mathes, Gregor H. ; Teichert, Sebastian:
Bayesian analysis of biodiversity patterns via beam trawl versus video transect : a comparative case study of Svalbard rhodolith beds.
In: Biodiversity and Conservation. Vol. 33 (2024) . - pp. 1099-1123.
ISSN 1572-9710
DOI: https://doi.org/10.1007/s10531-024-02788-y

Official URL: Volltext

Abstract in another language

Knowledge of spatial biodiversity patterns is important for ecosystem assessment. Rhodoliths, free-living calcareous algae, are biotic components that structure the sea floor through their complex calcareous skeletons and their tendency to accumulate in an area to form rhodolith beds. Thereby, rhodoliths are considered to act as ecosystem engineers promoting local biodiversity. In this study, the biodiversity of rhodolith beds in Mosselbukta, Svalbard, was investigated to analyse the proposed link between local biodiversity and the presence of rhodoliths by evaluating beam trawl and underwater video transect data. The comparative analysis of two sampling methods addressing the same research question allowed us to assess the suitability of these two methods. To test our hypothesis and the utility of the two methods, evaluations of the two data sets were carried out separately by using Bayesian statistics. The results confirm a positive relationship between the presence of rhodoliths and local biodiversity with a posterior probability of 70% for the video transects and 85% for the beam trawl data. The similarity of the results of the two methods suggests that both methods are well-suited for the analysis of local biodiversity patterns. The combination of the two methods, with their individual strengths and weaknesses, has provided stronger support for the results and a broader view on different components of the biodiversity in the Svalbard rhodolith beds.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Research Institutions > Central research institutes > Bayreuth Center of Ecology and Environmental Research- BayCEER
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 570 Life sciences, biology
Date Deposited: 15 Mar 2024 08:55
Last Modified: 15 Mar 2024 08:55
URI: https://eref.uni-bayreuth.de/id/eprint/88882