Determining the relative importance of catchment- and site-scale factors in structuring fish assemblages in small coastal streams

Jounela

et al. 2021

Ecology and Evolution

Studying the relationship between species and their environment is at the core of ecology. Modeling this relationship has long been performed, using a wide array of methods (Domisch et al., 2015;Franklin, 1995;Guisan & Zimmermann, 2000). The focus in developing these models may be to study species-environment relationships or to predict the occurrence of the studied species. In fisheries research, the identification of the environmental variables that characterize fish distributions has been one of the main objectives (Nelson et al., 1992;Rieman & McIntyre, 1995). Predictive models may help in fish-based bioassessment (Brosse et al., 2001;Oberdorff et al., 2001Oberdorff et al., , 2002 and in focusing inventory and management activities on areas where species are considered likely to occur (Porter et al., 2000).Several studies have indicated that field-measured site-scale (local) variables such as stream width, water depth, water chemistry, riverbed substrate, flowrate, undercut banks, canopy cover, riparian vegetation, and the slope at the sampling site can predict the

Section: Discussionmentioning

confidence: 99%

Species–environment relationships of fish and map‐based variables in small boreal streams: Linkages with climate change and bioassessment

Jounela

et al. 2021

Ecology and Evolution

“…However, the dominance of large-scale regional factors affecting riverine fish assemblages has also been documented (e.g. Koel & Peterka, 2003;DeRolph et al, 2015;Mitsuo, 2017). A wide variety of hypotheses or theories has been put forward concerning the balance of local and regional factors affecting riverine fish assemblages.…”

Section: Discussionmentioning

confidence: 99%

“…An easier way to predict species occurrence would be to use large-scale map-based (regional) variables such as the size of the upper catchment, the elevation and land use in the upper catchment (Porter et al, 2000). Indeed, catchment-scale variables can have a greater impact than site-scale variables on stream fish assemblages (DeRolph, Nelson, Kwak, & Hain, 2015;Mitsuo, 2017).…”

Section: Introductionmentioning

confidence: 99%

Species-environment relationships of fish and map-based variables in small boreal streams: linkages with climate change and bioassessment

Jounela

et al. 2021

Preprint

Species-environment relationships were studied between the occurrence of 13 fish and lamprey species and 9 mainly map-based environmental variables of Finnish boreal small streams. A self-organizing map (SOM) analysis showed strong relationships between the fish species and environmental variables in a single model (explained variance 55.9%). Besides basic environmental variables such as altitude, catchment size, and mean temperature, landcover variables were also explored. A logistic regression analysis indicated that the occurrence probability of brown trout, Salmo trutta L., decreased with an increasing percentage of peatland ditch drainage in the upper catchment. Ninespine stickleback, Pungitius pungitius (L.), and three-spined stickleback, Gasterosteus aculeatus L., seemed to benefit from urban areas in the upper catchment. Discovered relationships between fish species occurrence and land-use attributes are encouraging for the development of fish-based bioassessment for small streams. The presented ordination of the fish species in the mean temperature gradient will help in predicting fish community responses to climate change.

“…The results indicated, however, that within ecoregion geology could be used to diminish the variation in fish assemblage structure and thus improve the efficiency to reveal the level of human impact. The effect of land use as a major human pressure affecting water quality and the fish assemblage structure has been recognised by numerous studies (Budnick et al, 2019;Meador & Goldstein, 2003;Schlosser, 1991;Young, Quarterman, Eyles, Smith, & Bowden, 2005), and this is the case also in boreal rivers (Sutela & Vehanen, 2009, 2017. Land use, depending on its intensity, is likely to affect the nutrient and suspended solids loading from the catchment, and thus change the effect of impacted catchment geology, by increased diffuse loading especially from the modified areas of the catchment.…”

Section: Siliceousmentioning

confidence: 99%

“…The hierarchical approach that analyses small-scale features within large-scale units tends to be the most effective one in explaining the interaction of fish-habitat associations on different spatial scales (Poizat & Pont, 1996). The relative importance of catchment-and site-scale factors in structuring lotic fish communities is, however, largely unknown (Mitsuo, 2017).…”

Section: Introductionmentioning

confidence: 99%

The effects of ecoregions and local environmental characteristics on spatial patterns in boreal riverine fish assemblages

Ecology of Freshwater Fish

Harjunpää

2020

The conservation, management and monitoring of aquatic resources should benefit from understanding their spatial structuring. In this paper, we used the reference condition approach (RCA) to test if the variability in biotic communities, riverine fish assemblages in the present case, is better controlled with a spatial delineation based on ecoregions or by grouping rivers with local catchment characteristics. Electrofishing data from 493 riffles in 99 rivers in Finland were used in the analysis. We completed multivariate analyses (nonmetric multidimensional scaling, multiresponse permutation procedures) to identify differences in fish community composition among groups based on ecoregions or catchment characteristics. We concluded that both regional processes and local environmental characteristics structured fish populations, and bioassessment of freshwaters should be based on regional spatial delineations, supported by local scale characteristics. Spatial delineations like ecoregions should be used to assist the bioassessment to improve the efficiency to detect the human impacts.