Discontinuities and functional resilience of large river fish assemblages

Discontinuities and functional resilience of large river fish assemblages KRISTEN L. BOUSKA U.S. Geological Survey, Upper Midwest Environmental Sciences Center, 2630 Fanta Reed Road, La Crosse, Wisconsin 54603 USA Citation: Bouska, K. L. 2018. Discontinuities and functional resilience of large river fish assemblages. Ecosphere 9(7): e02351. 10.1002/ecs2.2351

Abstract. Functional composition of communities across scales is increasingly used to infer resilience of biotic communities to environmental change. To assess the relevance of these concepts to management of large rivers, analyses were applied to fish community data of the Upper Mississippi River. First, to evaluate whether there was evidence for structural patterns in fish size distributions, a discontinuity analysis was performed. Using long-term fish data, consistent discontinuities were identified across 14 reaches, suggesting similar structuring processes occur throughout the nearly 1300 river kilometers represented by those reaches. Increased variability in species abundance in relation to proximity to edges of body size aggregations supports the discontinuity hypothesis that body size aggregations are structured by key processes. Functional richness and redundancy were quantified within and across identified scales for each of 14 river reaches. Diversity of trophic and spawning guilds was generally greater in the upstream reaches in comparison with downstream reaches, with the exception of the diversity of large-bodied spawning guilds. Evidence of functional shifts in the composition of fishes occurred, but differed by size aggregations, likely reflecting scale-specific resource availability. Redundancy of spawning and trophic groups across body size aggregations suggested downstream reaches of this system may be less resilient to disturbances and were weakly associated with reduced habitat diversity. These findings suggest that discontinuities in large river fish assemblages do occur and may provide indication of shifting resource availability. Further investigation of the underlying processes and scales that support resource availability will be critical to managing for resilience in large river ecosystems. Key words: discontinuity; functional diversity; functional redundancy; habitat diversity; resilience; Upper Mississippi River. Received 20 March 2018; revised 9 May 2018; accepted 4 June 2018. Corresponding Editor: Stephanie M. Carlson. Copyright: Published 2018. This article is a U.S. Government work and is in the public domain in the USA. Ecosphere published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. E-mail: [email protected]

INTRODUCTION

organisms interact with their environment. Clusters of organisms with similar body size, often called aggregations, are thought to indicate persistent scales at which resources are available, whereas gaps in size distributions represent transitions between scales (Nash et al. 2014a). Aggregations and discontinuities in body size distributions have been documented in a wide range of taxa, including birds (Thibault et al. 2011), mammals (Lambert and Holling 1998),

Ecosystems are structured in nested hierarchies, hypothesized to be a consequence of key processes in the environment (Holling 1992). Structural patterns that emerge reflect resource opportunities to which organisms evolve (Angeler et al. 2015). As a result, body sizes of biotic communities often exhibit discontinuous distributions that represent different scales at which ❖ www.esajournals.org

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geomorphic discontinuities arise as a result of the hierarchical and directional structure of river networks (Poole 2002, Kiffney et al. 2006). Flow regimes are well recognized to influence physical habitat availability, patterns of connectivity, and disturbance regimes through interactions between hydrology with geomorphology (Poff et al. 1997, Ward 1998). In regulated river systems, human alterations often modify geomorphic processes and flow regimes, which ultimately reduce physical complexity, alter disturbance regimes, and negatively impact native biotic communities (Bunn and Arthington 2002, McCluney et al. 2014). It is likely that physical habitat diversity and flow regimes are strong driving factors of resource availability and therefore the diversity and redundancy of fish functional assemblages. At the same time, species–discharge curves suggest species richness generally increases with discharge (Xenopoulos and Lodge 2006, McGarvey and Hughes 2008), which may contribute to longitudinal differences in functional diversity and redundancy. To assess the relevance of resilience concepts to large rivers, analyses were applied to fisheries data from the Upper Mississippi River (UMR). The first question guiding analyses was whether discontinuities were present in the length distribution of fishes and, if so, whether those discontinuities were consistent across the longitudinal gradient of the river. Further, to assess whether body size aggregations represented structuring processes, I tested the effect of distance to aggregation edge on variability in abundance. The second question was whether metrics of functional diversity and redundancy within and across scales could be explained by habitat diversity or flow metrics. The latter question is posed to improve our understanding of the resilience of fish communities to habitat degradation relative to differences in flow regimes. Physical habitat diversity is thought to support a wide breadth of trophic and spawning resources and predictability of seasonal flows to support consistency of these resources; thus, I hypothesize both factors to be positively associated with fish diversity and redundancy metrics.

invertebrates (McAbendroth et al. 2005), reptiles and amphibians (Allen et al. 1999), plankton (Havlicek and Carpenter 2001), and fish (Nash et al. 2014b). Species with body masses at the edges of aggregations have been found to exhibit greater variability in abundance than those species with body masses at the center of aggregations, suggesting that species nearer structural transitions experience greater resource variability and instability (Wardwell and Allen 2009, Angeler et al. 2014). Further, temporal or spatial shifts in body size aggregations have been associated with changes in underlying structural processes of a system (Spanbauer et al. 2016). The redundancy and diversity of functional groups represented by species within and across scales are characteristics of resilient ecosystems (Peterson et al. 1998, Allen et al. 2005). Functional diversity describes the range of functional groups comprised by species, whereas functional redundancy refers to the number of species within the same functional group. Response diversity, or the range of reactions to environmental change among species contributing to the same function (Elmqvist et al. 2003), is not characterized explicitly in the cross-scale resilience model, but it is suggested that redundancy of a functional group across scales reflects response diversity in that species that operate at different spatial scales likely respond differently to disturbances (Peterson et al. 1998). Therefore, high functional diversity within scales and functional redundancy across scales suggests ecosystem functions and processes will be more stable and recover more quickly from disturbances than an ecosystem with relatively low functional diversity and redundancy (Walker et al. 1999, Nystrom 2006). Applications of these resilience theories remain few and have only recently taken place, but provide evidence that functional redundancy across scales can be an effective indicator of ecosystem recovery (Nash et al. 2015). Mechanisms that contribute to enhanced resilience have been increasingly evaluated in different ecosystems. For example, changes in size aggregations and reduced functional richness of bird communities coincided with the conversion of natural land cover to intensive agriculture, suggesting that the simplification of the landscape shifted the processes and resources structuring bird communities (Fischer et al. 2007). In river and streams, ❖ www.esajournals.org

METHODS Study area The UMR begins at the outlet of Lake Itasca, Minnesota, and transitions into the Lower 2

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Lengths of remaining individual fishes collected between 1993 and 2015 were log10-transformed. To evaluate body size distribution change over space, sampling events were combined annually for each LTRM reach. For each analysis, body size distributions were tested for unimodality using Hartigan’s dip test (Hartigan and Hartigan 1985), which in all cases suggested the logtransformed length distributions to be multimodal (P < 0.001). From there, aggregations and discontinuities in the length distribution of individual fishes were identified using Gaussian mixture model estimates of distribution parameters (i.e., mean, standard deviation). Gaussian mixture models are algorithms for density estimation and do so by finding a mixture of Gaussian probability distributions that best describe the distribution of the data. Mixture models were evaluated for fit using an Akaike’s information criterion (AIC) approach to identify the appropriate number of components (i.e., aggregations) in the size distribution. Mixture models with greater than four components generally failed to converge. Mixture models were developed and evaluated using the R package mixtools (Benaglia et al. 2009). Following discontinuity theory, variability in abundance should be greater for species near the edges of a size aggregation as opposed to the center (Wardwell and Allen 2009, Nash et al. 2014a). To test for this relationship, the variance in species abundance was evaluated in association with distance-to-edge of a size aggregation. The following procedure was conducted separately for each of the five LTRM reaches. The coefficient of variation (CV) of annual abundance was calculated for all fish species collected within a reach. Distance-to-edge was calculated as the proximity of species’ reach-specific mean length (log10length) to the nearest edge of its reach-specific body size aggregation. Within each reach, species collected in less than three of the 23 yr evaluated were removed due to inflated CV values. Values from all reaches were combined, and a linear regression model was fit to the data with CV as the dependent variable and distance-toedge as the independent variable. To determine whether size aggregation structure was consistent across the longitudinal gradient, non-metric multidimensional scaling (NMDS) and permutational multivariate analysis of

Mississippi River at the confluence of the Ohio River. Between Minneapolis, Minnesota, and St. Louis, Missouri, a series of locks and dams were constructed in the early twentieth century in support of an inland navigation industry (Fig. 1). Downstream of St. Louis, the navigation channel is maintained through the use of river training structures. Levees isolate a significant amount of the floodplain from the river south of Rock Island, Illinois. These physical changes to the river–floodplain environment have influenced the composition and accessibility of habitat conditions available to support aquatic organisms. For our purposes, river reaches are numbered in consecutive order from upstream to downstream and reaches between locks and dams are numbered based on its downstream lock and dam (Fig. 1).

Fish data Fish community data originated from two long-term programs: the Long Term Resource Monitoring (LTRM) element of the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program and the Illinois Natural History Survey’s Long Term Survey and Assessment of Large River Fishes in Illinois (LTEF). Since 1993, LTRM has implemented a stratified random sampling design with multiple gears to assess fish communities in five study reaches on the mainstem of the Mississippi River (Ratcliff et al. 2014). The LTEF program adopted LTRM sampling protocols for daytime electrofishing of main channel borders in 2010 and extended sampling to an additional nine reaches of the Mississippi River (Fig. 1), though 2015 was the first time that all nine reaches were sampled in the same year (DeBoer et al. 2015). Both programs sampled fish during three distinct time periods between June 15 and October 31 of each year. Electrofishing data from the main channel border habitat from LTRM and LTEF were used in subsequent analyses.

Discontinuities in body size distribution Fish exhibit indeterminate growth; therefore, an individual-level approach was taken to estimate discontinuities as opposed to a species-level approach (Nash et al. 2014b). Young-of-year fishes were removed from the dataset based on published cutoff lengths (Barko et al. 2005). ❖ www.esajournals.org

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Fig. 1. Within the Upper Mississippi River, the Long Term Survey and Assessment of Large River Fishes in Illinois (LTEF) and Long Term Resource Monitoring (LTRM) element of the Upper Mississippi River Restoration Program sampled fish communities at 14 reaches.

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information within the LTRM life history database (https://umesc.usgs.gov/data_library/fisheries/ fish_page.html), FishBase (www.fishbase.org), and NatureServe (www.natureserve.org). Functional diversity and redundancy were evaluated for spawning and trophic groups separately, following Allen et al. (2005). Within each size aggregation, species richness for each group was quantified at each sampling location. Functional richness is calculated as the number of functional groups present within a size aggregation. Further, at each sampling location, the number of aggregations in which each group was present was quantified to represent cross-scale redundancy.

variance using distance matrices (PERMANOVA) were used to evaluate differences between LTRM reaches. Following Spanbauer et al. (2016), distributional parameter estimates (i.e., mu and sigma) from each year and reach combination were compiled to construct a Bray–Curtis dissimilarity matrix from which NMDS was conducted with 999 permutations. Multivariate dispersion was assessed for homogeneity between reaches, and PERMANOVA was used to test whether size discontinuity structure differed significantly between reaches (Anderson 2006, Anderson and Walsh 2013). Post hoc pairwise comparisons were analyzed to further assess differences in multivariate dispersion using Tukey’s honestly significant difference (HSD) and differences in size aggregation structure across reaches using the R package pairwiseAdonis (Martinez Arbizu 2017). Non-metric multidimensional scaling, multivariate dispersion, Tukey’s HSD, and PERMANOVA were analyzed using the R package vegan (Oksanen et al. 2017).

Associations between functional metrics and ecosystem properties Four reach-scale metrics were calculated as potential explanatory variables of functional diversity and redundancy. Aquatic area diversity was calculated using Simpson’s diversity index on a geomorphic classification of the system (Wilcox 1993). The geomorphic classification includes eight geomorphic classes: main channel, channel borders, side channels, contiguous floodplain lakes, contiguous floodplain shallow aquatic habitats, contiguous impounded areas, isolated floodplain lakes, and tributary channels. Further, lentic area was quantified as the proportion of area represented by contiguous floodplain lakes, contiguous floodplain shallow aquatic habitats, contiguous impounded areas, and isolated floodplain lakes. Seasonal flow predictability represents an additive metric of temporal invariance and periodicity for flows (Colwell 1974). Mean annual flow was calculated for each reach to account for variability resulting from the longitudinal gradient. Flow metric calculations were made using daily discharge data at tailwater gages (www.rivergages.com) from 1986 to 2015 and the Indicators of Hydrologic Alteration software (The Nature Conservancy 2009). Residuals were evaluated for normality and heteroscedasticity. Linear mixed models were used to evaluate the fixed effects (i.e., aquatic diversity, lentic area, mean annual flow, and flow predictability) on within-scale diversity and cross-scale redundancy while accounting for collection time period as a random effect. An AIC approach was used to identify the best-fitting

Cross-scale resilience model To compare cross-scale resilience across all 14 river reaches, functional analyses were restricted to fish captured in 2015. First, Gaussian mixture models were fit and evaluated as described in the previous section for all individual fishes within groups of river reaches that had consistent size aggregation structure. Each species was then assigned to a size aggregation based on mean size in 2015 (Appendix S1: Table S1). To evaluate functional diversity and redundancy, each species was assigned a spawning and trophic group. Spawning groups were based on unique combinations of substrate and current requirements (Table 1), while trophic status followed Winemiller and Rose (1992). Functional groups were assigned based on available Table 1. A description of substrate and current requirements for each spawning group. Spawning group

Substrate

Current

Pelagophils Lithopelagophils Lithophils Phytophils Psammophils Speleophils Polyphils

Rocks/gravel Rock/gravel Submerged vegetation Sand Holes/crevices Generalist

Yes Yes No No No No No


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model for explaining cross-scale redundancy and within-scale diversity. Linear mixed models were developing using the R package lme4 (R Core Team 2015).

RESULTS Discontinuities in body size distribution Size distribution groupings for each year and reach combinations were best fit by two modes or aggregations (Fig. 2; Appendix S1: Table S2). The linear regression model showed an effect of distance-to-edge on CV of abundance (F1, 142 = 4.34, P = 0.04; Fig. 3). Species near the edge of a size aggregation (low distance-to-edge) generally had greater variation in abundance over the 23-yr data record as compared to species near the center of a size aggregation (high distance-to-edge). Overlap of size aggregation structure between reaches was observed in NMDS results (Fig. 4; stress = 0.05). There were significant differences in multivariate spread, attributed to reduced dispersion in reach 4 compared to the other four reaches (Appendix S1: Fig. S1; P = 0.03). The PERMANOVA results suggested an effect of reach on size aggregation structure (F4, 110 = 4.91, P < 0.001). Pairwise comparisons showed significant differences between reaches 4 and 8 (P = 0.01) and reaches 8 and 26 (P = 0.01). Sensitivities of PERMANOVA to differences in multivariate spread (Anderson 2001) suggest that differences in reaches 4 and 8 may be attributable to differences in multivariate spread. Differences between reaches 8 and 26 appear to be primarily driven by reduced estimated means of both size aggregations in reach 8 compared to 26 (Fig. 2). However, given the variability in estimated distribution parameters within each reach for any given year and the high similarity of size aggregation structure across reaches in 2015, it was assumed that no major shifts in size aggregation structure occurred along the river’s longitudinal gradient in 2015.

Cross-scale resilience model

In 2015, a total of 8504 individual fish were collected from the group of 14 reaches, representing 81 species combined. Assessment of multimodal distributions using AIC identified two size aggregations (i.e., small and large) to best fit the


Fig. 2. Annual body size aggregations for each of the five Long Term Resource Monitoring study reaches, based on estimated distributional parameters (i.e., mu and sigma).

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Fig. 3. Linear regression analysis highlighting the relationship of abundance variability of individual species and the distance-to-edge of reach-specific body size aggregations.

Fig. 5. A histogram of length distribution of all individual fish (n = 8504) caught within the 14 reaches in 2015, superimposed with size aggregations and parameters estimated using Gaussian mixture models.

Fig. 4. Non-metric multidimensional scaling analysis showing the similarity of annual body size aggregations among Long Term Resource Monitoring study reaches (1993–2015). The points circled are those from each reach in 2015.

(Fig. 5) and used to assign individual species to each aggregation. Spawning groups were identified for 73 species and trophic groups for 78 species (Appendix S1: Table S1). The mean size of the small-bodied aggregation was 71 mm and included 47 fish species

log-transformed length distribution (Appendix S1: Table S3) of all individual fish collected across the 14 reaches. Distribution parameters (e.g., mu and sigma) were estimated for each aggregation ❖ www.esajournals.org

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Functional richness of large-bodied spawning guilds generally increased in a downstream direction (Fig. 6B). The highest average species richness of large-bodied lithophilic spawners were in reaches 4 and 8, which subsequently decreased downstream. In contrast, the average species richness of large-bodied pelagophils and speleophils was lowest in the upstream reaches and increased in a downstream direction. Functional richness of large-bodied trophic groups showed a slightly increasing trend downstream through reach 27 (Fig. 7B). Richness of large-bodied invertivores was greatest upstream of reach 13, while the richness of large-bodied invertivore/carnivores was greatest downstream of reach 13. Cross-scale redundancy, or the average number of size aggregations that each functional guild is present, had a similar longitudinal pattern between spawning and trophic groups (Fig. 8). Cross-scale redundancy for both

(Appendix S1: Table S1). Functional richness of spawning groups within this size aggregation was relatively high in reaches 4 through 19, decreased sharply at reaches 20 and 21, increased in reaches 25–27, and then decreased in the downstream most reaches (Fig. 6A). Small-bodied pelagophils, lithopelagophils, and psammophils had consistent average species richness across all reaches. Average species richness of small-bodied polyphils, phytophils, and speleophils was highest in the upstream reaches. Functional richness of trophic groups within the small-bodied size aggregation was highest in upstream reaches and lowest in downstream reaches (Fig. 7A). The small-bodied invertivore guild had high species richness upstream of reach 20, and the small-bodied invertivore/carnivore guild had high species richness upstream of reach 16. The large-bodied size aggregation had a mean size of 417 mm and included 34 fish species.

Fig. 6. Average species richness for small-bodied (A) and large-bodied (B) spawning groups across study reaches. Functional richness represents the average number of spawning groups present within each reach.


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Fig. 7. Average species richness for small-bodied (A) and large-bodied (B) trophic groups across study reaches. Functional richness represents the average number of trophic groups present within each reach.

spawning and trophic groups was generally highest between reaches 8 and 18 and lowest in reaches 20, 21, and 30. Downstream of reach 21, cross-scale redundancy of both spawning and trophic guilds slightly increased in reaches 25 and 26 and then decreased through reach 30.

small-bodied guilds. A substantial amount of variance remained unexplained, with conditional R2 values ranging between 0.07 and 0.27.

DISCUSSION The identification and verification of discontinuities of fish assemblages in the UMR provide support that resilience concepts, such as the discontinuity hypothesis, are relevant to large river systems. Findings herein of heightened variability in species abundance in relation to proximity to edges of body size aggregation support the theory that body size aggregations represent persistent scales at which resources are available and maintained by controlling variables (Wardwell and Allen 2009). Variability in abundance is one method to assess whether body size aggregations are structured by key processes; however, a wide range of methods have been used to test

Associations between functional metrics and ecosystem properties The comparison of linear mixed effects models suggested the importance of independent covariates differed depending upon response variable (Table 2; Appendix S1: Table S4). Across all redundancy and diversity metrics, there were positive associations with aquatic area diversity, and negative associations with mean annual discharge. Most associations with proportion of flow predictability were positive in the best fit models. Associations with lentic areas were negative for large-bodied fish guilds and positive for ❖ www.esajournals.org

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Fig. 8. Average number of size aggregations per (A) spawning and (B) trophic group, or cross-scale redundancy, within each study reach.

aggregations is warranted to more explicitly determine the underlying structural drivers of fish assemblage body size structure. Given ecological resilience is generated through a diversity of functions available within scales and redundant functions available across scales (Peterson et al. 1998), the majority of functional diversity and redundancy metrics (with the exception of large-bodied spawning guild diversity) suggest an apparent shift around reaches 18 and 19 of the UMR, whereby upstream reaches generally exhibit greater resilience of fish communities to disturbance in comparison with the downstream reaches. Functional diversity and redundancy of fish communities were weakly explained by the predictor variables, but generally decreased with increasing mean annual flow and increased with habitat diversity, and flow predictability. Due to covarying longitudinal gradients in discharge, total suspended solids, nutrient concentrations, channelization efforts, active floodplain area, and flow regime metrics, there are likely interactions

the discontinuity hypothesis. Non-random associations of invasion and extinction with edges of body size aggregations provided early evidence for this concept (Allen et al. 1999), while more recently, non-random associations between animal fitness and proximity to body size discontinuities have also been found to support the discontinuity hypothesis (Angeler et al. 2014). Consistent body size aggregations across the nearly 1300 km encompassed by the study reaches suggest similar structuring processes throughout. Across all years, reach 8 did have reduced mean parameter estimates of both smalland large-bodied size aggregations compared to reach 26, but for 2015, parameter estimates were similar. This study did not investigate the identification of underlying controlling variables that structure fish body size aggregations, but others have suggested size aggregations may be constrained by habitat structure, biotic interactions, and biogeography (Allen et al. 2006, Graham and Nash 2013). Further investigation of temporal and spatial dynamics of body size ❖ www.esajournals.org

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BOUSKA Table 2. Summary of the best fit linear mixed model for each functional redundancy and diversity response variables. SE

t value

R2

1.14 0.04 0.03 0.03

0.06 0.02 0.02 0.02

19.50 2.21 1.63 1.41

0.14

Intercept Aquatic area diversity Mean annual flow Flow predictability Aquatic area diversity 9 Mean annual flow Aquatic area diversity 9 Flow predictability Mean annual flow 9 Flow predictability

1.16 0.03 0.14 0.05 0.08 0.13 0.05

0.05 0.05 0.04 0.05 0.04 0.06 0.11

22.09 0.60 3.33 1.08 1.93 2.213 0.47

0.15

Aquatic diversity 9 Mean flow 9 Predictability Intercept Lentic area Flow predictability

0.09 3.26 0.37 0.11

0.10 0.13 0.06 0.06

0.97 24.20 6.46 1.97

Intercept Aquatic area diversity Lentic area Aquatic area diversity 9 Lentic area

3.03 0.19 0.22 0.05

0.06 0.08 0.07 0.05

47.78 2.35 3.17 0.89

0.07

Intercept Mean annual flow Lentic area Flow predictability Mean annual flow 9 Lentic Mean annual flow 9 Flow predictability Lentic area 9 Flow predictability Mean annual flow 9 Lentic area 9 Predictability

3.39 0.64 0.35 1.68 0.17 2.22 3.72 3.70

0.48 0.49 0.78 0.60 0.65 0.63 1.34 1.49

7.11 1.31 0.45 2.79 0.26 3.51 2.78 2.49

0.26

Intercept Aquatic area diversity Lentic area Mean annual flow Flow predictability

2.85 0.17 0.29 0.26 0.08

0.18 0.08 0.09 0.09 0.07

15.36 2.18 3.04 2.89 1.24

0.27

Response variable

Independent variable

Coef.

Cross-scale spawning redundancy

Intercept Aquatic area diversity Mean annual flow Flow predictability

Cross-scale trophic redundancy

Large-scale spawning diversity

Large-bodied trophic diversity

Small-bodied spawning diversity

Small-bodied trophic diversity

0.19

Note: Coef., coefficient; SE, standard error.

and resulted in predominantly deep, fast habitats (Stevens et al. 1975, Chen and Simons 1986, Peck and Smart 1986). Such losses of physical complexity are well documented to result in the loss of specialized species in large rivers across the world (Galat and Zweimuller 2001, Aarts et al. 2004). Spatial shifts in functional richness differed by size aggregation, suggesting that both functional requirements and body size are important factors in how fishes interact with their environment. Fishes with similar functional requirements but differing body size may respond to changing environmental conditions differently. For example, upstream reaches (i.e., 4–19) had a greater richness of small-bodied speleophils, while

among variables that coincide to drive longitudinal changes. Reach-scale estimates of habitat diversity are coarse, yet associations signal positive effects of habitat diversity on fish functional diversity and redundancy and support the notion that maintenance of spatial heterogeneity is critical to managing for resilience (O’Neill 1998). Previous research across the longitudinal gradient of the UMR found fish assemblages of the undammed section of the river (reaches 27– 30) to be distinct from the impounded sections (reaches 4–26) and suggested channel complexity and flow variability as possible factors (Angradi et al. 2009, Taylor et al. 2013). Channelization has substantially altered the geomorphology and hydraulics of the undammed section of the river ❖ www.esajournals.org

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predictor of recovery in coral reef systems (Nash et al. 2015). If the cross-scale resilience model does provide a meaningful indicator of fish community resilience, the need to understand the structuring processes of body size aggregations and how they influence functional diversity and redundancy will be of great importance to inform management decisions in support of ecological resilience.

downstream reaches (i.e., 25 and 30) had a greater richness of large-bodied speleophils. Isolation of where shifts in functional richness occur by size aggregation may assist in identifying potential structuring processes and constraints. For example, longitudinal fragmentation resulting from physical infrastructure (e.g., dams) and water extraction has been detrimental to pelagicspawning fishes that require current to distribute eggs and early life stages long distances until they are capable of swimming independently to suitable nursery environments (Dudley and Platania 2007, Perkin et al. 2015). Although not investigated fully here, functional richness and the breakdown of species richness by functional group across space can provide insight into specific resource availability and associated structuring processes within and across reaches. Improved understanding of the scales at which fish of different body size aggregations interact with the environment is needed to quantify and evaluate environmental drivers at the appropriate scales. It is well established that larger fish tend to move longer distances (Radinger and Wolter 2014). For example, many large-bodied fish can exhibit broadscale migratory movements (Pellett et al. 1998, Zigler et al. 2003) and may be more strongly linked to variables quantified at those broad scales. However, movements of small-bodied fishes in the Mississippi River are relatively unknown. Improved tracking technologies and investment in tools such as microchemistry and genetics analyses can provide a more complete understanding of the spatial ecology of riverine fishes (Campana and Thorrold 2001, Collins et al. 2013, Porreca et al. 2016) to identify biologically meaningful scales at which to assess, manage, and restore fish populations and their habitats. The cross-scale resilience model provides a simple assessment of functional presence of the fish community across scales from which we might infer the communities’ ability to cope with disturbances. Relying upon long-term data to isolate responses of fish communities following a disturbance (e.g., invasive species establishment, flood, drought) will provide a useful test of the model. Future investigations should also consider the inclusion of body mass into the cross-scale resilience model to provide a more complete representation of the distribution of functional guilds, which has been a successful ❖ www.esajournals.org

CONCLUSIONS Using long-term fisheries data, discontinuities in body size were identified across the longitudinal gradient of a large river. Associations between distance-to-edge of body size aggregations and variability in abundance provide evidence in support of the discontinuity hypothesis. These findings suggest that two body size groupings are structured by consistent structuring processes across the system. Cross-scale redundancy of spawning and trophic functional groups suggests downstream reaches of this system may be less resilient to disturbances and may be related to habitat simplification. These findings provide insight into the relative resilience of fish communities within the UMR; however, additional investigations of the underlying structuring processes and the role of cross-scale redundancy of functional groups in relation to ecological disturbances will improve our understanding of the usefulness and reliability of these metrics.

ACKNOWLEDGMENTS Appreciation is given to the Long Term Resource Monitoring and Long Term Survey and Assessment of Large River Fishes in Illinois field stations and individual crew members that collected the fisheries data that this work relied upon. Additional thanks are given to Jason DeBoer for answering questions related to the LTEF program and database. I thank Jeff Houser and Craig Allen for feedback on earlier drafts of this manuscript. This work was funded as part of the U.S. Army Corps of Engineers Upper Mississippi River Restoration Program. Use of trade, product, or firm names does not imply endorsement by the US Government.

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SUPPORTING INFORMATION Additional Supporting Information may be found online at: http://onlinelibrary.wiley.com/doi/10.1002/ecs2. 2351/full


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