Regionalization strategy affects the determinants of fish community structure. Issue 4 (16th May 2022)

• Record Type: Journal Article
• Authors: Baldan, Damiano; Chattopadhyay, Somsubhra; Prus, Paweł; Funk, Andrea; Keller, Agata; Piniewski, Mikołaj
• Is Part Of: Ecohydrology. Volume 15:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-16
• Subjects: biomonitoring data -- environmental predictors -- fish community structure -- regionalization strategy -- spatial subsetting; Ecohydrology -- Periodicals; Hydrology -- Periodicals; Water -- Environmental aspects -- Periodicals; 577.6
• DOI: 10.1002/eco.2425
• Languages: English
• ISSNs: 1936-0584

Abstract

Abstract: Freshwater bioassessment programmes yield valuable information for assessing the diversity and distribution of freshwater organisms and can be related to environmental variables through the use of multivariate methods. Regionalization and subsetting strategies are widely used in this regard, but the effects on the discerned relationships are largely unexplored. In this paper, we used a partial redundancy analysis (pRDA) to investigate the influence of different environmental variables on (i) fish community structure, (ii) the explanatory power of spatial and environmental variables, and (iii) ranking of the most relevant variables for the fish community structure in Poland. We performed the analysis at the national level and for different regionalization/subsetting strategies based on hydrography (coarse resolution: river basins, fine resolution: water regions), topography, biogeography and fish‐based river typology. Depth, slope and sediment type were three most relevant predictors at the national level and for the majority of subsets. However, compared to the national level, a significant misalignment in predictors rankings was found for a large fraction of the identified subsets. Overall, river basin subsetting provided limited gain in information compared to the national level, while water region subsetting yielded higher variability in the predictive capacity of the pRDA models and increased the share of variance explained by spatial pattern which might obscure environmental effects. Thus, it is recommended to use biotic relevant subsetting methods based on elevation or fish indicators to better capture the variability of the dataset and provide simple and informative relationships between the fish community structure and the environmental variables.