Low-velocity, shallow water riparian zones in large rivers are productive habitats supporting primary and secondary production for many aquatic organisms [1
]. Many fishes use vegetated riparian zones as spawning and sheltered nursery habitats [4
]. Additionally, these low-velocity areas often retain zooplankton prey for larval and juvenile fishes, providing more efficient foraging opportunities for early life stages than in swifter main-channel habitats [2
]. Riparian areas also provide societal and economic services that can interfere with natural ecological processes. Riverine modifications to support navigation and shoreline development have contributed to losses of many shallow water riparian areas in large rivers [10
]. The St. Clair–Detroit River System (SCDRS) on the Canada–United States (U.S.) border is a unique system that shares a common history of habitat degradation with many large rivers worldwide. As a connecting channel of the Laurentian Great Lakes, the SCDRS has a relatively consistent discharge and lacks a floodplain [13
]. However, like most of the world’s large rivers, the SCDRS was altered to better accommodate transportation, trade, and development. Channels were re-routed and deepened in the early 1900s to facilitate navigation of deep-draft vessels, removing over 46 million m3
of substrate and burying over 4050 ha of fish spawning habitat with dredged spoils [15
]. Through this process, shallow water areas were converted to deep shipping channels and artificial islands. Industrial and residential development along the SCDRS further altered the riparian zone. Wetlands were in-filled and shallow sloping banks were converted to deep, vertical banks to allow boats direct access to loading docks and marinas [14
]. Shorelines were hardened with an estimated 55% of U.S. mainland shoreline on the Detroit River converted to steel sheet piling or concrete breakwater by 1985 [17
]. The cumulative result of these alterations was a loss of approximately 97% of riparian wetlands in the Detroit River [18
]. Although the St. Clair River still features a river delta marsh, wetland losses in the delta from 1868–1873 to 1973 were estimated as 68% (Jaworski and Raphael 1976 as cited in [19
Declines and impairments of habitat and fish and wildlife populations were contributors leading to the St. Clair and Detroit rivers’ designations as Great Lakes Areas of Concern (AOC) in 1987 [18
]. In 1987, fish populations were not designated as impaired based on reports of a rich fish community (>60 species in Detroit River; [21
]); however, recognition of the linkage of negative impacts of large-scale habitat degradation on fish and wildlife populations contributed to eventual listing as a beneficial use impairment (BUI, see [20
] for definition) [22
]. Consequently, although Francis et al. [19
] noted 63 and 56 fish species in nearshore habitats of the Detroit River (sampled in 2004, 2006, and 2008) and the St. Clair River Delta (sampled in 2007), respectively, carrying capacity of the system has likely changed and fish communities differ from pre-colonial times [23
]. Work in the Detroit River supported that uncommon and imperiled fishes (e.g., pugnose minnow Opsopoeodus emiliae
and spotted sucker Minytrema melanops
) were found in areas with wetland habitats, whereas upstream habitats featured few uncommon species and more non-native fishes [7
]. In 1991, resource managers identified increasing or improving wetland habitats as a way to improve conditions in the Detroit River [23
]. Previous research has shown that riparian and shoreline habitat enhancement projects benefit larval and juvenile fishes by supporting greater fish densities, feeding, and growth [24
]. Additional information on fish community–habitat associations could help guide riparian and shoreline habitat enhancement projects to maximize benefits and assess potential non-target effects to at-risk or undesirable species.
Establishing an ecological baseline that identifies attributes and processes supporting functional riparian habitat is an important first step for rehabilitation efforts [26
] and was the impetus for this study. Development and implementation of restoration projects guided by key habitat attributes and processes can lead to achievement and maintenance of desirable restoration outcomes, such as higher richness of small-bodied and juvenile fishes. Additionally, establishing a baseline facilitates development of tangible (achievable and measurable) objectives and provides a starting point to gauge the effectiveness of restoration projects [28
]. Further, jurisdictional wildlife action plans have specified a need to understand habitat use of at-risk fishes [29
]. Therefore, the objectives of this study were to assess shallow water riparian fish communities in the SCDRS and identify habitat attributes associated with fish species richness based on a shoreline seine survey conducted from 2013 to 2019. Further, we examined habitat associations of commonly collected species to inform targeted restoration projects to meet management goals for individual species of interest, as well as the entire fish community.
Over the seven-year study period, 38,451 fish representing 60 species were collected in 269 seine hauls, with a mean observed species richness of 5 (SD = 4) species per seine haul. Identification to species was achieved for 30,873 individuals, whereas 7578 individuals were identified to higher taxonomic levels (e.g., family or genus) or were impractical to identify (e.g., due to size). Fourteen seine hauls from three different sites (S-001, S-002, and S-004) had catches of zero fish. The maximum observed species richness for individual seine hauls was 17 from the S-006 site in 2017. Emerald shiner Notropis atherinoides
composed the largest proportion of the catch; 11,668 individuals (38% of individuals identified to species) were collected during the study period and the species was observed at every site except S-006 in the St. Clair River Delta (Supplementary Materials Table S1
). The next most abundant species were bluntnose minnow Pimephales notatus
= 4193; 14% of individuals identified to species),
brook silverside Labidesthes sicculus
= 2105; 7%), round goby Neogobius melanostomus
= 1916; 6%), and spottail shiner Notropis hudsonius
= 1799; 6%).
The species composition of samples featured a mix of species of management interest including at-risk, economically important, and non-native species. At-risk species collected during seine surveys (based on state, provincial, or federal designations covering the SCDRS) included grass pickerel Esox americanus, lake chubsucker Erimyzon sucetta, northern sunfish Lepomis peltastes, pugnose minnow, pugnose shiner Notropis anogenus, and spotted sucker, comprising 3% of fish collected (n = 851). The most commonly collected at-risk species was pugnose shiner (n = 614), all of which were collected at site S-006. Five of the six at-risk species collected were sampled exclusively at one site, with four of those collected at site S-006 in the St. Clair River delta (lake chubsucker, grass pickerel, pugnose minnow, and pugnose shiner). Several species of recreational or commercial interest were collected such as largemouth bass Micropterus salmoides, Lepomis spp., muskellunge Esox masquinongy, northern pike Esox niger, smallmouth bass Micropterus dolomieu, and yellow perch Perca flavescens, with yellow perch being the most common (n = 1313). A total of nine non-native species were collected, including alewife Alosa pseudoharengus, brown trout Salmo trutta, common carp Cyprinus carpio, ghost shiner Notropis buchanani, goldfish Carassius auratus, rainbow smelt Osmerus mordax, round goby, tubenose goby Proterorhinus marmoratus, and white perch Morone americana. Non-native fishes made up 9% of the total sample identifiable to species (2795 individuals) and were dominated by round goby and tubenose goby.
Fifteen species were unique to individual sampling sites. The S-009 site on the Detroit River had the most unique species (n
= 4), whereas seven other sites had at least one unique species (Table S1
). A total of 16 species was unique to the Detroit River, whereas 9 species were exclusively collected in the St. Clair River. Only three species (round goby, spottail shiner, and yellow perch) were collected at all sites. Centrarchidae species were more common in the Detroit River: 94% of centrarchids collected during the study were from Detroit River sites, 88% of which came from S-009 and S-010. Fishes from the family Catostomidae were found at relatively few sites and most species were uncommonly collected (Table S1
). Additional details on the species composition of samples can be obtained and summarized using the supplemental datafile produced by Fischer et al. [52
In-river substrate types differed across sites and through the time series. As many as four substrate types were documented at a site in a given year (Table 2
). Upstream sites within both rivers were generally characterized by sand and gravel substrates, whereas the downstream site(s) were more likely to feature silt, organic matter, or algal substrates (Table 2
). Cobble and algal substrates were only documented in the St. Clair River, whereas all other substrate types were documented at sites in both rivers. Aquatic macrophytes were present at all sites at some point in the time series, except the most upstream site in the St. Clair River, S-001 (Table 3
). Macrophyte richness was greatest at the S-006 and S-009 sites in 2017, where 10 species were collected within the time series (Table 3
Of the 256 candidate models describing fish species richness, no model was clearly superior based on AICc but 4 models had ΔAICc values less than 2 and were interpreted as substantially supported (Table 4
). All four models featured sand, cobble, algae, and shoreline vegetation type as predictor variables. Further, all candidate models with ΔAICc < 4 featured sand, cobble, algae, and shoreline vegetation as a predictor variable. None of the most-supported models (ΔAICc < 4) featured aquatic macrophyte richness as a predictor variable, but all substrate types were represented in at least one of the most-supported candidate models.
Model-averaged slope parameter estimates were similar to model selection outcomes, as most predictor variables common to all most-supported models were deemed significant based on lacking overlap of 95% confidence intervals with zero (Figure 3
). Cobble, algae, grassy shoreline vegetation, and woody shoreline vegetation were interpreted as significant. Although sand was present as a predictor variable in all most-supported models, it was not interpreted as a significant predictor variable to explain species richness based (95% CI: −0.70, 0.07). Cobble was not associated with greater richness based on observed data (Figure 4
) but had a positive influence on richness based on model-averaged slope estimates from mixed effects models (Figure 3
). Algal substrates were associated with greater species richness based on the positive value of the model-averaged parameter estimate. Woody shoreline vegetation was the vegetation type associated with greatest fish species richness (Figure 3
and Figure 4
). However, grassy shoreline vegetation was typically associated with greater fish richness than no or mixed shoreline vegetation (Figure 4
). Fitted values from model averaging suggested greatest richness at the S-006, S-008, S-009, and S-010 sites (Figure 5
After excluding uncommon species, 256 species-specific candidate GLMMs were fitted for 33 species for a total of 8448 model estimation runs. Given that we strived to include as many species as possible in individual species analyses, some models were not well fitted, and convergence issues arose. A total of 1394 models were unable to converge using default settings for GLMMs in the glmmTMB package. The average number of model convergence failures per species was 42 (SD = 37), with a range of 0–140. Nine species achieved convergence for all candidate models, including bluntnose minnow, brook silverside, largemouth bass, mimic shiner Notropis volucellus, round goby, spotfin shiner Cyprinella spiloptera, spottail shiner, tubenose goby, and yellow perch. Green sunfish Lepomis cyanellus had the most model convergence failures (n = 140).
The best model explaining habitat and catch rate associations varied by species (Table S2
). For three species (goldfish, northern hogsucker Hypentelium nigricans
, northern sunfish), models with random effects of site and year and no fixed effects were supported as the AICc best supported model. The global model (i.e., all predictor variables included) was not supported as the best model describing habitat associations for any species, but best models included as many as seven predictor variables (hornyhead chub Nocomis buguttatus
). For 18 examined species, all model-averaged slope parameters were non-significant (Table S2
). In these and many other cases, unconditional standard errors were large, sometimes 4+ orders of magnitude greater than the model-averaged parameter estimates (Table S2
). All statistically significant slope parameters were featured in the “best” models selected by AICc.
The CCA model including all predictor variables was significant (F
= 9.45, df = 11, 240, p
= 0.001) and explained 30% of the variability in species catches. The first CCA axis could be interpreted as an axis of course substrates (e.g., sand, gravel, and cobble) and low aquatic vegetation richness versus very fine substrate particles (e.g., silt) and high organic matter (i.e., vegetated shores, high aquatic macrophyte richness, and organic substrates; Figure 6
). The second CCA axis was largely characterized by segregation of woody shoreline vegetation versus silt and algal substrates (Figure 6
). Most fish species were congregated in the bottom-right quadrant (characterized by woody shorelines and high organic matter), but some species were more strongly associated with CCA axes (Figure 6
). Emerald shiner catches were most associated with the first CCA axis (course substrates and low aquatic vegetation richness), whereas most species were more associated with fine substrates and high organic matter (Figure 6
). In terms of the second CCA axis, blackchin shiner Notropis heterodon
, pugnose minnow, and pugnose shiner were associated with algal substrates, whereas species such as goldfish, northern sunfish, rock bass Ambloplites rupestris
, spotted sucker, striped shiner Luxilus chrysocephalus
, and white sucker Catostomus commersonii
were more associated with woody shorelines (Figure 6
This study provides important information on fish community–habitat associations in shoreline zones of the St. Clair and Detroit rivers. Shoreline habitats have been degraded over time in the SCDRS, but this study supports that a diverse shoreline fish community exists. This work improves our understanding of habitat associations with fish species richness, as well as several at-risk, invasive, and economically important fishes. Species richness was associated with substrate types (e.g., sand, cobble, algae) and shoreline vegetation, providing possible opportunities for habitat enrichment to enhance fish communities and improve ecosystem function via flow and sediment management and restoring wetland connectivity. Further, this work permits identification of tradeoffs in habitat enhancement projects in relation to individual species. For instance, restoration practitioners can identify which species are likely to colonize or increase in abundance in response to habitat improvements and which may be less likely to be present for a given restoration prescription. Finally, this work informs future monitoring programs by aiding scientists and managers to target habitats associated with species of management importance and understand biases in abundance indices based on characteristics of selected sampling sites.
This study provides a description of the nearshore fish community of the SCDRS and supports the presence of habitat diversity and importance of riparian and wetland habitats for maintenance of native fish assemblages. The St. Clair River generally featured species characteristic of a coolwater fish assemblage in a fast, flowing river. However, the St. Clair River Delta site (S-006) is characterized by slower flow velocities and marsh habitat. The fish community in the St. Clair River Delta was more characteristic of a warmwater fish community and appears to provide important habitat by supporting several at-risk fishes not collected elsewhere in the study. In the St. Clair River, species such as emerald shiner, sand shiner Notropis stramineus, and spottail shiner were predominant, with species such as banded killifish Fundulus diaphanus, largemouth bass, pugnose minnow, and pugnose shiner collected in the St. Clair Delta. The Detroit River also featured a warmwater fish community but was most characteristic of a warmwater community toward the mouth where habitats were more vegetated. Riverine fishes (e.g., northern hogsucker, smallmouth bass) were more common in upstream Detroit River sites than those closer to the mouth of the river.
Model selection criteria supported sand, cobble, and algae substrate as important predictors of fish species richness in the St. Clair and Detroit rivers. Model-averaged parameter estimates indicated a positive effect of the presence of algae and cobble on species richness. Although algal substrates were generally associated with greater richness, there was a lack of evidence of a positive influence of cobble in plots of site and year-aggregated observations of richness. However, median richness estimates were higher when cobble was present at sites where cobble was observed within the time series. Cobble may have represented a proxy for substrate heterogeneity as cobble was never observed as the only substrate type present. Sarkar and Bain [53
] suggested maintenance of a range of habitat types given that habitat requirements of species occupying erosional and depositional habitats differed. Sites dominated by sand substrates (e.g., S-001) tended to have low species richness, possibly reflective of low habitat complexity [54
]. High flow velocities in the upper reaches of the St. Clair River may also reduce habitat suitability for some fishes as Lapointe et al. [6
] found many small and juvenile fishes were associated with fine sediments in the Detroit River.
In our study, grassy and woody shorelines were associated with greater fish species richness. The benefits of wooded riparian zones to fishes have been well described (e.g., [56
]), but have received greater research attention in smaller systems than those examined here. Woody riparian vegetation contributes leaf litter, which supports productivity of invertebrates [58
] and woody inputs enhance structural complexity, providing cover for fishes [59
]. Further, woody vegetation provides benefits of stabilizing banks, thereby reducing sedimentation [60
]. Grassy shoreline vegetation provides many of the same benefits as woody shoreline vegetation and can support greater abundances and species richness than more complex riparian plant assemblages [63
]. Improving habitat complexity and diversity of shoreline areas of the St. Clair and Detroit rivers may benefit the diverse fish community present [64
Aquatic macrophyte richness was not included as a fixed effect in any of the most-supported models (i.e., models with ΔAICc < 4) and was not supported as an important factor explaining species richness in this study. However, sites with the greatest fitted fish species richness typically had greater aquatic macrophyte richness. Consequently, a lack of support for increased species richness with greater aquatic macrophyte richness (and correlated percent macrophyte coverage) was unexpected. Most of the fish collected in this study were small (mean length = 48 mm, SD = 24 mm) and juvenile fishes for which previous research has supported the value of aquatic macrophytes [4
]. Other studies in the Detroit River have shown juvenile fishes to be more strongly associated with microhabitat than their larger conspecifics and juvenile fishes were more abundant in areas with aquatic macrophytes [6
]. Aquatic macrophytes can reduce predation risk and prey fish tend to concentrate in vegetated areas when predators are present [65
]. Predation pressure may be a strong driver in habitat selection for small and juvenile fishes and prey availability may also be higher in vegetated areas. Grenouillet et al. [8
] documented higher abundances of juvenile fishes in vegetated areas, which they attributed to higher availability of zooplankton prey and shelter from predators. Zooplankton have a limited ability to swim against the current and are more likely to be retained in slow-moving, vegetated portions of rivers [2
]. Furthermore, vegetated areas of river systems may provide better feeding opportunities and yield higher growth rates for some fishes [66
]. Consequently, further study may be needed to more explicitly evaluate relationships between fish communities and aquatic vegetation in the SCDRS to inform shoreline and wetland restoration projects.
While our models highlight structural components of sites with high species richness, it is also important to consider the processes that maintain those components to improve success and longevity of restoration [26
]. Given that strong currents and turbulence are unfavorable for primary producers, aquatic macrophytes are more likely to establish in areas of low water velocity [1
]. Additionally, deposition of particulate matter provides minerals and nutrients, in part, leading to the high primary and secondary productivity of large floodplain rivers [1
] and supporting macroinvertebrate detritivores consumed by fish [71
]. Since organic substrates are easily displaced by flowing water, they are most likely to accumulate in low-velocity areas. These are the same areas highlighted by the “inshore retention concept” as being crucial for larval fish development and retention of zooplankton food sources [2
]. Areas that retain organic matter are therefore likely to have lower advection and higher colonization of larval fish. In the SCDRS, Pritt et al. [72
] found larval fish assemblages in the upper river reaches to be a nested subset of lower river communities. Hydrologic processes within the St. Clair River delta and portions of the Detroit River may more be conducive to retention of larval fish that may later recruit to juvenile stages. However, riparian wetlands and shallow beds of aquatic macrophytes have been restricted to the lower portions of each river [18
] and these vegetated areas may provide spawning habitat to a different suite of species [74
]. Thus, high fish species richness at these locations may arise from both pattern (e.g., physical habitat) and process (e.g., larval retention).
The use of an information theoretic approach and multimodel inference allowed us to make inferences related to fish–habitat associations, while accounting for model selection uncertainty [43
]. In most cases, several models were supported by the data and assuming one model was the correct model would have resulted in information loss, although not all models achieved convergence. Model fitting issues appeared to arise due to several factors. Low occurrence in samples was likely a contributing factor to model fitting issues as some species were rarely observed (e.g., spotted sucker or green sunfish) or were collected at single sites. Goldfish were only collected at the S-009 site with most fish collected in 2014. Another issue may have been related to segregation of species among habitat types. Some species have relatively specific habitat use tendencies and were collected exclusively in samples from one category of the included predictor variables or presumably avoided some habitat types which may have contributed to large uncertainty estimates. Further, some generalist species were collected across levels of predictor variables but were collected relatively infrequently among the total number of seine hauls yielding large estimates of uncertainty. Although model fitting issues arose for some specified models, the use of a multimodel approach allowed us to model habitat associations for species despite data limitations and gain some insights on catch rates and associations with habitat variables.
Although this work provides insights on fish–habitat associations, the results of this study should not be interpreted as definitive depictions of habitat use by examined species. Factors such as gear efficiency and fish behavior may influence observed results. For instance, more species were generally collected at vegetated sites (i.e., S-006 and S-009) than those without vegetation which could indicate that fish use those habitats with greater prevalence. However, Pierce et al. [76
] reported a positive association between gear efficiency and vegetation biomass for beach seines sampling fishes in lakes. Behaviorally, small-bodied fishes may spend most of their time in those habitats or move there to seek shelter from perceived threats [77
], whereas fish in unvegetated habitats may be more likely to flee to open water, making them unavailable to sampling. Given the size of these rivers, the use of techniques employed in smaller systems to reduce emigration such as block netting were not feasible. Consequently, seine hauls are not from the exact same location at a given site and are not true replicates. As a result, we were unable to address detection probabilities for species in relation to the sampling gear or habitat characteristics. Further, characteristics of certain sampling sites may present challenges in sampling. Silt-bottomed sites may reduce mobility for scientists working the seine upstream relative to rocky-bottomed sites and differences in flow velocity may result in different speeds during seining. Additional study may be necessary to understand detectability of species at sites in relation to habitat use and gear efficiency.
Future work related to the fish community of the SCDRS may also benefit from inclusion of additional habitat characteristics and integration of multiple sampling gears. Factors discussed above such as flow velocity and channel morphology may be important factors in understanding habitat and fish community associations and may influence other habitat features. Additional factors found to influence species-site associations include river bottom slope or contour, depth, turbidity, and distance from shore [6
]. Because our sampling was shore based and limited to wadable areas, comparable depths and distances to shore were sampled at all sites. However, slope and distance to the main channel may be more meaningful metrics to explain variability in fish species richness at our sample sites. Slope provides information on the transition to deep main-channel habitat and distance to the main channel provides information on the area of shallow water available to small and juvenile fishes. Additionally, areas with a greater distance between the bank and main channel provide more area for retention of drifting larvae [78
]. Indeed, some of the highest species counts we observed were at sites with large distances between the riverbank and main channel (e.g., S-006, S-009, and S-010). Given that seining limits sampling to wadable stream segments with public access, the number of sampling sites possible were quite limited. Inclusion of additional sampling gears, such as boat-mounted electrofishing, may allow researchers to take a more randomized approach to site selection and enhance the amount of space that can be feasibly sampled. Using these methods, Francis et al. [19
] were able to collect species undetected in our seine surveys. However, electrofishing has limitations in sampling fishes of interest in this study as small-bodied fishes are less susceptible to electrofishing [79
]. Expansion and refinement of predictor variables to better explain species–habitat associations and enhanced sampling coverage may improve understanding of the community ecology of SCDRS fishes and better inform habitat restoration decisions.
This study provides guidance for establishment of tangible objectives for shallow water riparian habitat restoration by evaluating habitat associations with species richness and individual species. When setting fish community objectives, sites with high species richness could represent the maximum number of fish species restored or managed habitats could realistically support. Observed richness can be used to derive system specific goals for restoration projects directed at removing the loss of fish and wildlife habitat BUI in the St. Clair and Detroit River AOCs. Several at-risk, economically important, and invasive species were observed within the sampling area, sometimes with similar associations to habitat features. Restoration efforts that provide functional habitat for a broad number of species and life history stages will likely benefit both desirable native species and undesirable invasive species. For example, increasing aquatic vegetative cover to improve Centrarchidae populations without benefitting tubenose gobies is unrealistic because both taxa prefer vegetated areas [80
]. Additionally, not all native fishes will benefit from increased macrophyte richness, such as those that require shallow sandy areas for reproduction and development. Understanding and evaluating tradeoffs associated with habitat restoration and community and individual species responses is likely a critical step when developing restoration goals and objectives.