Seasonal shifts in collective tendencies of floodplain-associated schooling fishes

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Boyle, Guillaume Rieucau This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7039953/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Seasonal flood pulses are a key driver of environmental variability in large river-floodplain ecosystems, yet their influence on the behavior of many floodplain associated fish remains poorly understood. We used high-resolution imaging sonar to test the hypothesis that, despite the irregular and episodic nature of inundation in the Lower Mississippi River Basin, floodplain-associated schooling fishes would exhibit shifts in collective tendencies in response to changes in floodplain connectivity. As schooling is known to be an adaptive strategy, greater behavioral plasticity would allow schooling individuals to appropriately react to changes in environmental conditions, predation risk, and foraging opportunities. We recorded 56 hours of video across sites located near and far from the initial point of floodplain inundation during connected (high-water) and disconnected (low-water) periods spanning all four seasons. School area, alignment (polarization), and inter-individual distance (nearest-neighbor distance) were quantified from 5,085 schools comprising 120,114 individuals using a semi-automated approach. School areas did not differ across conditions, except for smaller schools observed at near sites during disconnected-fall. Fish swam in a more aligned fashion during connected-summer, while inter-individual distances were lowest during connected-spring and disconnected-summer. Altogether, our results indicate schooling fishes inhabiting the floodplain exhibit behavioral changes at the level of their collective in response to changes in the local environmental conditions. Given the inter-annual variation in flood pulse dynamics, unravelling the functional explanations (e.g., antipredatory, foraging) of the observed modifications of schooling tendencies mediated by water level and river-floodplain connectivity will require more work. Collective behavior Plasticity Schooling Floodplain Imaging sonar Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction In many fish, the dynamic nature of schooling reflects the continuous trade-off between minimizing predation risk while maximizing other fitness-enhancing activities (Pitcher 1993 ; Sumpter 2010 ). In general, schooling is thought to enhance safety through the dilution of the risk of predation (Turner and Pitcher 1986 ; Lehtonen and Jaatinen 2016 ), a diminution of predator catch efficiency (Ioannou et al. 2017; Goodale et al. 2019 ), and an improved transfer of threat-related information and collective evasion (Ward et al. 2011 ; Rieucau et al. 2016 ). In turn, larger and more coordinated schools may allow for more rapid food detection and acquisition (Pitcher et al. 1982 ; Hintz and Lonzarich 2018 ) at the cost of increased competitive interactions with conspecifics. Variation in collective behavior, detectable at the individual level (Herbert-Read 2016 ), results from the acute and rapid adjustments made in response to local environmental and social cues from conspecifics. These adjustments often occur on short timescales, lending support to the idea that fish schools display a high degree of structural and behavioral plasticity (Partridge 1980 ; Hemelrijk and Hildenbrandt 2012 ; Rieucau et al. 2015 ; Romenskyy et al. 2020 ; Ioannou and Laskowkski 2023). Fine-scale modifications in schooling structure, such as the alignment and distances between individuals, are mediated by the visual and lateral line senses (Partridge and Pitcher 1980 ; McKee et al. 2020 ; Tidswell et a. 2024). The effectiveness of collective behaviors in mitigating predation risk relies on precise sensory input, highlighting the need to further understand how both abiotic (i.e., flow, turbidity) and biotic factors (i.e., predator and food abundance) influence the structure and behavior of schooling fishes in dynamic or disturbed habitats. A growing body of literature supports the idea that schooling fishes display a high degree of structural and behavioral plasticity in response to changes in environmental factors including habitat complexity (Rodriguez-Pinto et al. 2020 ), tidal fluctuations (Rieucau et al. 2015 ), temperature (Kuruvilla et al. 2022), turbidity (Kimbell and Morrell 2015 ), and flow rates (Zhang et al. 2024 ) in addition to anthropogenic changes to the environment such as water control structures (Rodriguez-Pinto et al. 2021). The ability to adjust collective behaviors in response to environmental variability is thought to help maintain efficient information transfer among schooling fishes (Rieucau et al. 2015 ; 2016 ; Encel et al. 2021 ; Mukherjee and Bhat 2024 ). For instance, inter-individual distances (i.e., nearest neighbors) as well as the alignment of individuals (i.e., polarization) are important factors in determining the strength of coordinated responses to predators (Rieucau et al. 2016 ; Romenskyy et al. 2020 ; Bartaschevich et al. 2024). Schooling individuals that inappropriately adjust their behavior to that of their school mates may become more vulnerable to predation (Penry-Williams et al. 2018 ; Quattrini et al. 2018 ; Aivaz et al. 2019). In systems where environmental change is frequent and periodic, such as tidal driven estuaries, these predictable cycles may allow schooling fishes to learn or anticipate shifting conditions. In contrast, far less is known about how schools respond to unpredictable and episodic changes to the environment. This gap in understanding is especially pronounced in floodplain systems, where seasonal inundation events occur irregularly and vary not only in timing and magnitude, but also in duration, often leading to changes in habitat structure, predator-prey dynamics, and the sensory environment. Within unconstrained large river-floodplain ecosystems, schooling fish experience changes in environmental conditions through the lateral overflow of the main-stem river, known as the seasonal flood pulse (Junk 1989; Bayley 1995 ). Flood waters inundate terrestrial habitats, creating a mosaic of submerged areas that in turn provide critical resources for both prey and predator species (Pongruktham and Ochs 2015 ; Mosepele et al. 2022 ; Quade et al. 2025a ). Floodplain-associated schooling fishes must balance the trade-off between food acquisition and detection and mitigating predation risk within newly inundated habitats. Rising water levels, synchronized with increasing water temperatures, facilitates primary production and cues for the immigration of large bodied piscivorous fishes to backwater habitats from the main channel (Mosepele et al. 2022 ; Quade et al. 2025b ). Several abiotic factors known to impact collective behaviors of schooling fishes are mediated by flood pulse inundation (Domenici et al. 2016; Kuruvilla et al. 2022; Allibhai et al. 2023 ). For example, elevated turbidity that can occur during the onset of the flood pulse (Pongruktham and Ochs 2014) is generally thought to disrupt group cohesion and promote more individualistic behaviors through the disruption of the visual sense (see Zanghi and Ioannou 2024 for recent review). Abiotic and biotic changes associated with the flood pulse are not necessarily uniform or predictable given the variability of seasonal flood pulses, particularly within heavily modified systems such as the Lower Mississippi River Basin (LMRB). Levees, dams, and water control structures that were designed to reduce flooding have decoupled much of the LMRB from the seasonal flood pulse, reducing this system to less than 8% of its’ original 10.1 million ha (Schramm and Ickes 2016 ). The disruption of regular inundation patterns negatively affects floodplain fish species with life histories tied to the natural hydrological cycles of high water in spring and low water in fall (King et al. 2009 ; Kemp et al. 2014 ; Eggleton et al. 2016 ; Luo and Criss 2018 ). The effects of abiotic and biotic factors on individual and group-level schooling metrics have been extensively studied through simulations and laboratory experiments (Ginnaw et al. 2020 ; Lambert et al. 2021 ; Zanghi et al. 2023 ), while field-based studies remain challenging to conduct, particularly in complex, low-visibility environments where direct observation of behavior remains challenging. To overcome these limitations, imaging sonars have emerged as effective tools for observing fish behavior in turbid or low-light environments where traditional video-based or fisheries-dependent methods fall short (Speas et al. 2004 ; Wei et al. 2022 ; Sibley et al. 2023 ; Munnelly et al. 2024). Operating at high frequencies and producing video-like imagery, imaging sonars are minimally invasive and capable of capturing individual and group-level behaviors across a range of spatial and temporal scales (Narrins et al. 2011; Velez 2015 ). For example, recent studies have demonstrated the utility of this technology in quantifying relative abundance and size-class distributions of floodplain-associated fishes under varying levels of floodplain connectivity within the LMRB (Quade et al. 2025a , b ). Here, our goal was to explore how floodplain-associated schooling fishes collectively respond to variation in floodplain connectivity at the Richard K. Yancey Wildlife Management Area. To achieve this, schooling tendencies were described through the quantification of three (3) distinct metrics of school structure: school area, fish swimming alignment (i.e., polarization), and inter-individual distance (i.e., nearest neighbor distance; Rieucau et al. 2018 ; Pinto-Rodriguez et al. 2020;2021) using an ARIS Explorer 3000 imaging sonar (Adaptive Resolution Imaging Sonar, Sound Metrics Corporation, Bellevue, Washington, USA). Observations were made across four seasons during both high-water (connected) and low-water (disconnected) periods at four sites located near and far from the initial point of floodplain inundation. We hypothesized that, despite the irregular and episodic nature of inundation, floodplain-associated fishes would exhibit measurable shifts in school structure in response to changes in connectivity. Specifically, we predicted that the largest and most structurally organized schools would be observed during connected-spring and connected-summer, when predation risk is expected to be higher (Quade et al. 2025a ) and abiotic conditions are more variable. Conversely, we expected schools to decrease in size and become less cohesive during later seasonal inundation levels as predation pressure and environmental variability subside. This study was conducted prior to hydrologic restoration efforts at the Richard K. Yancey Wildlife Management Area, providing a critical baseline for future assessments of collective behavior in response to restoration. Materials and Methods Study site This study took place in the Richard K. Yancey Wildlife Management Area (WMA), a 28,328-ha floodplain managed by the Louisiana Department of Wildlife and Fisheries, located south of Vidalia, Louisiana. The WMA lies on the western edge of the Mississippi River and features flat terrain dominated by bottomland hardwoods. Three floodplain lakes in the southern WMA connect first to the main-stem river during seasonal flooding. As water rises, these lakes connect to northern areas through culverts and natural channels. Our study focused on the 283-ha designated for culvert replacement and weir repair to improve hydrologic connectivity. A rock weir at the southern lake’s outlet marks the initial inundation point for flood pulse inundation. Topography and anthropogenic structures (e.g., levees, berms) restrict floodwaters from entering elsewhere until river stages exceed moderate flood levels. Four sites that experienced a moving littoral edge (i.e., aquatic-terrestrial transition zone; Junk et al. 1989 ) were haphazardly chosen based on their relative position to the initial point of flood pulse inundation. These sites were grouped qualitatively as “near” or “far” sites based on the straight-line distances to the rock-weir. The first near site (2.8 km straight-line distance from rock weir) is positioned just north of the northwestern most floodplain lake, separated by an anthropogenic berm. The second near site, approximately 3.0 km straight-line distance from the rock weir), lies slightly farther up the floodplain. The two far sites (6.2 km and 8.6 km straight-line distance from rock weir) are typically more isolated hydrologically, requiring higher river stages for flood water waters to over-top natural and anthropogenic barriers between near and far sites. All sites retain standing water between flooding events and remain large enough to not restrict fish movement within each site. Thirteen sampling events occurred between 7 August 2021 to 20 January 2023. Sampling events were first grouped by flood pulse status; “connected” when all four sites were inundated simultaneously and “disconnected” when all four sites were isolated. Sampling events were then grouped by the season in which they occurred. Connected periods included connected-spring (2-March-2022, 9-April-2022, 29-April-2022, and 27-May-2022) and one connected-summer date (16-June-2022) due to rapid dewatering of the floodplain after this sampling event. Disconnected periods included disconnected-summer (7-August-2021, 22-July 2022, 30-July-2022), disconnected-fall (30-October-2021, 15-September-2022, 30-October-2022) and disconnected-winter (18-December 2022,-20 January 2023). Sampling on 22-July-2022 was abbreviated due to sonar power source failure, however one near and one far site were sampled prior to failure. Inundation status was confirmed using USGS river stage data from Knox Landing (Gauge ID: 07294800) and field observations. Data collection At each of the four study sites, the ARIS imaging sonar was deployed manually from a fixed position within 1 meter of the shoreline, resting directly on the floodplain substrate. Prior to deployment, the sonar was affixed to a polyethylene platform measuring 33 × 33 × 28 cm. The ARIS platform was oriented perpendicular to the water column during deployment to reduce interference from both the water surface and bottom. In part because all sites exceeded the sonar's maximum range of 20 meters, a reduced operating range of approximately 8 meters was selected to optimize recorded image resolution, resulting in video-like recordings at an average of 10 frames per second with a 30° horizontal by 14° vertical field of view. To maximize spatial coverage, the ARIS platform was manually rotated 90 degrees every 20 minutes, resulting in approximately 1 hour of observation per site and covering nearly 270° of the surrounding floodplain, excluding the portion directly behind the unit facing the bank. The order in which sites were sampled was randomized prior to each field day. Sampling was conducted during daylight hours, between approximately 06:30 and 17:30, except on 22 July 2022, when only one near and one far site were recorded due to a sonar power failure. Quantification of collective behaviors Unique floodplain-associated fish schools, here defined as groups containing at least three individuals swimming in apparent coordination, were identified by reviewing each recorded video in its entirety. Although the definition of a school was not restricted by fish size, the majority of observed schools consisted of individuals less than 20 cm total length. Screenshots were captured for each school using ArisFish (Sound Metrics Corporation), and when possible, taken when the school was centered within the field of view of the ARIS. For schools that extended beyond the field of view, multiple screenshots were taken, assessed separately, and then combined. Collective behaviors were quantified using a semi-automated MATLAB script (MathWorks; www.mathworks.com ) developed by Rieucau et al. ( 2018 ) to estimate inter-individual distance (IID) and alignment (polarization). School area (m 2 ) was measured using ImageJ (Version 1.54p; Schneider et al. 2012 ). To reduce overestimation of schooling area, measurements were taken using a consistent approach that minimized spacing between individuals by outlining only the main body masses (i.e., fish to fish), excluding extended gaps between schooling individuals. School area was used a proxy for group size (i.e., number of individuals) given the potential for estimation bias in direct counts resulting from occlusion of schooling members within the video-like dataset. Therefore, in lieu of direct counts of individuals, school area was interpreted alongside inter-individual distances in order to provide insight into school density. Scale bars in both MATLAB and ImageJ were set to one meter using the grid overlay provided in ArisFish screenshots (Fig. 1 ). Statistical analysis Each unique fish school identified was treated as an independent observational unit based on natural variability between sampling events and the assumption that schools observed at different times and locations were biologically distinct. Linear mixed-effects models were fitted for each collective behavior (school area, polarization, and inter-individual distance) using the lmerTest package in R (Kuznetsova et al. 2017 ). Site location, seasonal inundation level, and their interaction were included as fixed effects in all three models. The lmerTest package provides p-values in type III ANOVA tables for linear mixed models using the Satterthwaite approximation for degrees of freedom, which is well-suited to unbalanced designs and allows each fixed effect to be tested independently of the others. In addition to significance testing, model comparisons using likelihood ratio tests were used to assess whether interaction terms or main effects improved model fit and warranted inclusion. School area was log 10 transformed prior to model fitting, however, results are reported as back-transformed (geometric mean) values. Inter-individual distances were normalized for body size by dividing the distance between nearest neighbors and the total length of the individual. It is possible that the selected images of each school may not have been satisfactory independent units of replication, therefore, we included each 20-minute (video_ID) that the image was taken from as a random effect to control for possible pseudoreplication. Polarization and IID were assessed at the level of the individual, therefore, to control for possible pseudoreplication school_ID nested within video_ID was treated as a random effect. Post-hoc pairwise comparisons with Bonferroni correction were conducted using the emmeans package (Lenth 2025 ). All statistical analyses were performed in R version 4.2.2 (R Core Team 2022). Results We collected 56 hours of video footage from 7 August 2021 to 10 January 2023 that included 5,085 unique schools, comprising a total of 120,114 fish. Model comparison likelihood ratio tests supported the inclusion an interaction between seasonal inundation levels and site (χ² = 27.02, df = 4, P < 0.001). No difference in schooling area was detected between near and far sites (F 1,115.17 = 1.92, P = 0.1681). However, we detected a difference between school area among seasonal inundation levels (F 4,116.49 = 15.02, P < 0.0001) and an interaction of seasonal inundation levels and site (F 4,116.49 = 6.90, P < 0.0001; Fig. 2 ). Pairwise comparisons suggest that schools observed at near sites during disconnected-fall periods were consistently smaller (x̅ g−near = 0.016) than other schools observed at near and far sites during connected-spring (x̅ g−near = 0.134, P < 0.000; x̅ g−far = 0.101, P < 0.0001), connected-summer (x̅ g−near = 0.117, P = 0.00017; x̅ g − far = 0.173, P < 0.0001), disconnected-summer (x̅ g − near = 0.074, P = 0.0105; x̅ g − far = 0.085, P < 0.0001), disconnected-fall (x̅ g − far = 0.077, P = 0.0011), and disconnected-winter (x̅ g − near = 0.211, P < 0.0001; x̅ g − far = 0.079, P = 0.0017). Larger schools were documented to have occurred at far sites during connected-summer periods (x̅ g − far = 0.173) when compared to schools at both near and far sites during disconnected-summer periods (x̅ g − near = 0.074, P = 0.0247; x̅ g − far = 0.085, P = 0.0182). Differences in the alignment of individuals (Fig. 3 ) were detected between seasonal inundation levels (F 4,95.16 = 4.48, P = 0.0023). Model comparison using likelihood ratio tests did not support inclusion of the interaction between site and inundation level (χ² = 7.50, df = 4, P = 0.1116), and the main effect of site (Near vs. Far) did not significantly improve model fit (χ² = 0.15, df = 1, P = 0.697). Pairwise comparisons suggest that schooling fishes observed during connected-summer periods were swimming in a more aligned manner (θ = 7.478) than schooling fishes observed during disconnected-summer (θ = 10.047, P = 0.0137) and disconnected-fall periods (θ = 9.668; P = 0.0004), with a possible trend observed between disconnected-winter (θ = 12.584, P = 0.061). Differences in inter-individual distances (Fig. 4 ) were detected for seasonal inundation level (F₄,₁₄₃.94 = 21.04, P < 0.0001). Model comparison using likelihood ratio tests did not support inclusion of the interaction between site and inundation level (χ² = 3.60, df = 4, P = 0.4622), and the main effect of site (Near vs. Far) did not significantly improve model fit (χ² = 2.17, df = 1, P = 0.14). Pairwise comparisons for seasonal inundation levels suggest that schooling individuals observed during connected-spring periods were generally swimming closer to their nearest neighbor (1.225 body lengths) than compared to connected-summer (1.547 body lengths, P = 0.0045), disconnected-fall (1.972 body lengths, P < 0.0001), and disconnected winter (1.659 body lengths, P 0.999). Similarly, schooling individuals observed during disconnected-summer periods tended to be closer to their nearest neighbor (1.135 body lengths) than compared to disconnected-fall (1.972 body lengths, P < 0.0001) and disconnected-winter (1.659 body lengths, P < 0.0001). A possible trend was documented between connected-summer (1.547 body lengths) and disconnected-summer (1.135 body lengths, P = 0.0705). Discussion Our results revealed that river-floodplain connectivity mediates the collective tendencies of schooling fishes within the floodplain. Contrary to our predictions of more cohesive schools during connected periods followed by a gradual decline throughout the disconnected periods, there appears to be shifts in collective behavior with floodplain connectivity, particularly within seasonal inundation levels. Fish tended to swim in a more aligned manner during connected-summer periods, but were generally closer to each other during connected-spring periods and disconnected-summer periods. The observed variation in alignment and inter-individual distances across seasonal inundation levels, despite relatively similar schooling areas, strengthens the idea that floodplain-associated schooling fishes have the ability to adjust their collective tendencies to the prevailing environmental conditions they are facing. This behavioral flexibility reflects a high degree of plasticity in schooling structure. The similarities in alignment and inter-individual distances between connected and disconnected periods likely reflects their response to trade-offs in predation risk, foraging opportunities, and/or environmental conditions mediated by the seasonal flood pulse. Given the considerable year-to-year variation in the timing, magnitude, and duration of seasonal flood pulses in highly altered floodplain systems, patterns observed within the current study may vary across years. For instance, predation risk annually may be highly variable, as the recruitment of predator species has been linked to flood magnitude and duration in preceding years (Alford and Walker 2013; Buckmeier et al. 2017 ), and well-timed flood pulses often serve as cues for many floodplain-associated fishes to immigrate from the main channel into backwater habitats (Stoffels et al. 2022 ; Mosepele et al. 2022 ). Long-term monitoring of behavioral patterns across variable hydrologic conditions will be essential to understand how altered flood regimes influence the ecological functions of collective behavior in floodplain systems. During the onset of the flood pulse (i.e., connected-spring), floodplain associated schooling fishes must balance the functional benefits of schooling and the cost of doing so in an altered environment. High flow velocities (Liao 2007 ) and turbidity (Kimbell and Morrell 2015 ; Allibhai et al. 2023 ) during the initial inundation phase may disrupt the hydrodynamic and collective benefits of schooling. At the same time, rising waters cue for the immigration of large-bodied piscivorous fishes (Roberts et al. 2023 ; Quade et al. 2025) and enhance foraging opportunities through enhanced productivity (Junk et al. 1989 ; Bayley 1995 ). During connected-spring periods, where flow, turbidity, and predation pressure are expected to be the greatest (Turner 2022 ; van der Sleen & Rams 2023; Quade et al. 2025), schooling individuals swam closer together as compared to disconnected-winter and connected-summer. Given that school areas observed during connected-spring were similar to most other seasonal inundation levels, excepting disconnected-fall, the low inter-individual distances observed during connected-spring would suggest that these schools were denser (i.e., greater number of individuals per area) than connected-summer, disconnected-fall, and disconnected-winter. The higher degree of school structural organization (denser schools comprised of aligned individuals that are closer together) observed during connected-spring should in fact allow for more efficient information transfer among group members during connected-spring periods, facilitating coordinated threat-related collective responses (Rieucau et al. 2016 ; Poel et al. 2022). These effects occur despite the potentially disruptive influences of elevated flow velocities and turbidity, suggesting that the benefits of forming large, dense schools outweigh the costs under such conditions (Turner and Pitcher 1986 ; Hintz and Lonzarich 2018 ). Surprisingly, our results highlights that schools observed during the connected-summer periods exhibited greater inter-individual distances despite fish swimming in a more organized fashion (e.g., lowest angles between nearest neighbors), suggesting a more aligned yet less dense school structure. This collective configuration is thought to enhance hydrodynamic efficiency by reducing individual drag and enabling energy savings while schooling (Weihs 1973; Hemelrijk et al. 2014). As inundation spreads laterally, declining flow rates and turbidity likely reduce abiotic constraints on collective behavior, even as predation risk and foraging opportunities mediated by the flood pulse persist. Low-water periods during disconnected-fall and disconnected-winter impose a different set of environmental conditions for schooling fishes, including reduced turbidity and a significant reduction of flow (Pongruktham and Ochs 2014). Although overall predator abundance is generally lower during these periods (Walker et al. 2022 ; Quade et al. 2025), increased water clarity and shallower depths may elevate perceived predation risk by enhancing visibility and exposure to visually mediated, piscivorous predators such as wading birds (Lantz et al. 2011 ). At the same time, these habitats serve as nursery and refuge areas for young-of-the-year predator species such as gar (McAllister et al. 2023 ; Quade et al. 2025). Concurrently, diminished allochthonous and autochthonous inputs likely reduce food availability, intensifying intraspecific competition. Under such conditions, foraging motivation may drive schooling fish toward more individualistic or exploratory behaviors (Stenberg and Persson 2005 ; Harpaz and Schneidman 2020 ) over cohesive schooling strategies aimed at mitigating predation risk (Pitcher 1993 ; Sumpter 2010 ), as nutritional stress has been shown to increase inter-individual distances (Robinson and Pitcher 1989 ; Hansen et al. 2015 ; Wilson et al. 2019 ). Our results are consistent with this pattern, as greater inter-individual distances were observed during disconnected-fall and disconnected-winter compared to connected-spring. The magnitude of this pattern was most pronounced in disconnected-fall, particularly at near sites, where fish formed smaller and less cohesive schools. By disconnected-winter, however, fish swam in schools of greater areas despite similar inter-individual distances suggesting that those schools were in fact composed of a greater number of individuals, potentially reflecting a trade-off between competitive pressures and the benefits of group foraging in resource-limited environments (Godin 1986 ; Hintz and Lonzarich 2018 ; Polyakov et al. 2022 ). Disconnected-summer periods offer insight into the complexity of collective behaviors exhibited by floodplain-associated schooling fishes and the trade-offs individuals make to maximize fitness. During this period, both the collective behaviors and the estimated group sizes matched those observed during connected-spring. These similarities are unlikely to be driven by foraging motivation alone, as nutrient accumulation and elevated temperatures during drawdown sustain high productivity (Bayley 1995 ). Instead, the rapid decline in Mississippi River water levels prior to the first disconnected-summer sampling event potentially played a central role in the observed collective organization of fish schools. Dewatering is expected to have generated substantial flow and turbidity within monitored sites, reducing visual acuity and affecting fish capacity to detect potential threats. This drawdown phase also serves as a cue for large-bodied piscivorous fishes to emigrate to deeper habitats (Castello et al. 2019 ; Roberts et al. 2023 ), such as floodplain lakes or the main channel. However, our monitoring occurred several weeks before this hydrologic transition and thus these interpretations are speculative. Nevertheless, the observed patterns reinforce the critical need for fine-scale temporal assessments to better capture the behavioral adjustments made by schooling fish during dynamic transitional periods. Altogether, our results suggest that the collective behaviors of floodplain-associated schooling fishes are influenced by floodplain connectivity, specifically seasonal inundation levels. Given the variability in the timing, magnitude, and duration of seasonal flood pulses in the LMRB, continued monitoring of collective behaviors across seasonal inundation levels is required for establishing broader ecological patterns. Specific to our study area, future high-resolution imaging sonar work should focus on how increased connectivity and improved hydrology impact the collective behaviors of schooling fishes in the floodplain, particularly at the culverts designed to improve fish passage. Our study was not designed to specifically explore the mechanisms and ecological functions of schooling in floodplain systems; however, the explanations provided are plausible and should serve as a framework for future research. For instance, in order to ascertain the function explanations of the collective-level adjustments made by aggregated fish could involve altering the floodplain’s visual background to create a higher-contrast environment. This change would make schooling fishes more conspicuous and would be expected to trigger an elevated perception of non-consumptive predation risk. High-contrast environments have been successfully used to elicit changes in collective behavior (Rieucau et al. 2016 ), offering a minimally invasive method for field studies. Future research should adopt a stepwise approach to studying the ecological function of schooling in floodplain systems, ensuring that antipredator and foraging treatments are not confounded during in situ experiments. Furthermore, a comparison of the differences in collective structure of the same fish species assemblages in floodplains that experience consistent annual inundation (e.g., Atchafalaya Basin in southern Louisiana) with those in floodplain systems that undergo irregular inundation could provide insight into how schooling fishes adapt their collective behaviors to different environmental conditions. Declarations Author Contributions: AHQ and GR conceived and designed the experiment. AHQ performed the experiment. AHQ, KSB, GR analyzed the data. AHQ, KSB, GR wrote the manuscript. Ethical approval: Not applicable. No capture or handling of animals have been conducted in our study that was solely based on non-intrusive observations. Competing interests: No applicable. Funding statement: This project was funded through a National Fish and Wildlife Foundation grant to GR. Acknowledgments This project was funded through a National Fish and Wildlife Foundation grant to GR. We thank the Richard K. Yancey staff for their assistance and hospitality. We thank Ashleigh Lambiotte, Brianna Jordan, Erica Teschke, Leflore James Press, Franchesca Basalo, Adalyn Thibodeaux, and Robert Bergeron for the assistance in the field and the laboratory. Data availability: The data collected and analyzed during our study are available upon reasonable request. References Aivaz, A. N., A. Manica, P. Neuhaus, & K. E. Ruckstuhl, 2020. Picky predators and odd prey: colour and size matter in predator choice and zebrafish’s vulnerability – a refinement of the oddity effect. Ethology Ecology & Evolution 32: 135–147. https://doi.org/10.1080/03949370.2019.1680445. Alford, J. B., & M. R. Walker, 2011. Managing the flood pulse for optimal fisheries production in the Atchafalaya River basin, Louisiana (USA). River Research and Applications 29: 279–296. https://doi.org/10.1002/rra.1610. Allibhai, I., C. Zanghi, M. J. How, & C. C. Ioannou, 2023. 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08:44:38","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":153209,"visible":true,"origin":"","legend":"","description":"","filename":"OECOD25003590structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/e670d007993dbf85996662a0.xml"},{"id":95278489,"identity":"6ff894b2-70da-45d9-9a8c-99d6cd31d717","added_by":"auto","created_at":"2025-11-06 08:44:38","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162886,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/772aa58b71fc1fb85251686a.html"},{"id":95278472,"identity":"b414b002-7f9e-482e-ad05-1f86a725f5c5","added_by":"auto","created_at":"2025-11-06 08:44:38","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":864323,"visible":true,"origin":"","legend":"\u003cp\u003eExample of high-resolution sonar data from the ARIS Explorer 3000, presented as a video-derived screenshot. The left panel shows school area measurement in ImageJ, with outlines drawn around individual fish to calculate total school area. The inset (right panel) displays output from the semi-automated MATLAB script, in which the user marks the head and tail of each fish to estimate alignment (polarization) and inter-individual distances. Vectors indicate swimming direction, and points represent the center of mass for each individual.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/0b76c958e719ff98c92c9262.jpeg"},{"id":95313691,"identity":"054a8e66-19e9-450b-8991-5b0d33938ebd","added_by":"auto","created_at":"2025-11-06 15:51:52","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":663969,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distributions of fish school areas (log\u003csub\u003e10\u003c/sub\u003e-transformed), visualized as concentric circles. Each ring of the circle corresponds to a log\u003csub\u003e10\u003c/sub\u003e-transformed school area. The color of each ring corresponds to the frequency of occurrence of each value. Ring that lack color indicate values of school area that were not observed. Frequencies were calculated for each combination of seasonal inundation level and proximity to the Mississippi River. Areas were then scaled to a common range to enable visual comparisons. Labels at the outermost ring of each set of concentric circles indicate the largest observed log\u003csub\u003e10\u003c/sub\u003e-transformed school area per combination.\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/03d80bb308b49fd9f931c726.jpeg"},{"id":95313449,"identity":"c995c98a-edf4-4358-95af-713ceab8fc70","added_by":"auto","created_at":"2025-11-06 15:51:27","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":229388,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distributions of angles (in degrees) between nearest neighbors across seasonal inundation levels, shown as radial heatmaps, ranging from 0 – 35 degrees. Each segment of the arc corresponds to an angle along the arc. The color of each segment corresponds to the frequency of occurrence of each value. Frequency values were calculated based on the full dataset, from 0 – 180 degrees. Arcs were trimmed to 35 degrees to emphasize the central patterns.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/f11f2615637897b9600501d7.jpeg"},{"id":95313762,"identity":"cbe070d4-50a1-4ca3-9873-0d60cb3eaf98","added_by":"auto","created_at":"2025-11-06 15:51:57","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":319871,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distributions of inter-individual distances (in body lengths) between nearest neighbors across seasonal inundation levels shown as heatmaps. Each row represents the frequency of occurrence of each inter-individual distances relative to the nearest neighbor, ranging from 0 – 3 body lengths. For each individual, the distance to the nearest neighbor was divided by the individual’s total length to yield a standardized distance in body lengths. Density values are calculated using the full dataset, but were trimmed to 3 body lengths to emphasize the central patterns. Colors indicate the relative frequency of each distance.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/48b03726ecbca47cdb6408b9.jpeg"},{"id":104405128,"identity":"9c65b595-6335-4571-8bf6-e0c2529c6ddc","added_by":"auto","created_at":"2026-03-11 12:21:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2549235,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7039953/v1/99bbbd60-7487-4af0-a676-d2a03bd567b1.pdf"}],"financialInterests":"","formattedTitle":"Seasonal shifts in collective tendencies of floodplain-associated schooling fishes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn many fish, the dynamic nature of schooling reflects the continuous trade-off between minimizing predation risk while maximizing other fitness-enhancing activities (Pitcher \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Sumpter \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In general, schooling is thought to enhance safety through the dilution of the risk of predation (Turner and Pitcher \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Lehtonen and Jaatinen \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), a diminution of predator catch efficiency (Ioannou et al. 2017; Goodale et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and an improved transfer of threat-related information and collective evasion (Ward et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rieucau et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In turn, larger and more coordinated schools may allow for more rapid food detection and acquisition (Pitcher et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Hintz and Lonzarich \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) at the cost of increased competitive interactions with conspecifics. Variation in collective behavior, detectable at the individual level (Herbert-Read \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), results from the acute and rapid adjustments made in response to local environmental and social cues from conspecifics. These adjustments often occur on short timescales, lending support to the idea that fish schools display a high degree of structural and behavioral plasticity (Partridge \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Hemelrijk and Hildenbrandt \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rieucau et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Romenskyy et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ioannou and Laskowkski 2023). Fine-scale modifications in schooling structure, such as the alignment and distances between individuals, are mediated by the visual and lateral line senses (Partridge and Pitcher \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; McKee et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tidswell et a. 2024). The effectiveness of collective behaviors in mitigating predation risk relies on precise sensory input, highlighting the need to further understand how both abiotic (i.e., flow, turbidity) and biotic factors (i.e., predator and food abundance) influence the structure and behavior of schooling fishes in dynamic or disturbed habitats.\u003c/p\u003e\u003cp\u003eA growing body of literature supports the idea that schooling fishes display a high degree of structural and behavioral plasticity in response to changes in environmental factors including habitat complexity (Rodriguez-Pinto et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), tidal fluctuations (Rieucau et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), temperature (Kuruvilla et al. 2022), turbidity (Kimbell and Morrell \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and flow rates (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in addition to anthropogenic changes to the environment such as water control structures (Rodriguez-Pinto et al. 2021). The ability to adjust collective behaviors in response to environmental variability is thought to help maintain efficient information transfer among schooling fishes (Rieucau et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Encel et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mukherjee and Bhat \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). For instance, inter-individual distances (i.e., nearest neighbors) as well as the alignment of individuals (i.e., polarization) are important factors in determining the strength of coordinated responses to predators (Rieucau et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Romenskyy et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bartaschevich et al. 2024). Schooling individuals that inappropriately adjust their behavior to that of their school mates may become more vulnerable to predation (Penry-Williams et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Quattrini et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Aivaz et al. 2019). In systems where environmental change is frequent and periodic, such as tidal driven estuaries, these predictable cycles may allow schooling fishes to learn or anticipate shifting conditions. In contrast, far less is known about how schools respond to unpredictable and episodic changes to the environment. This gap in understanding is especially pronounced in floodplain systems, where seasonal inundation events occur irregularly and vary not only in timing and magnitude, but also in duration, often leading to changes in habitat structure, predator-prey dynamics, and the sensory environment.\u003c/p\u003e\u003cp\u003eWithin unconstrained large river-floodplain ecosystems, schooling fish experience changes in environmental conditions through the lateral overflow of the main-stem river, known as the seasonal flood pulse (Junk 1989; Bayley \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Flood waters inundate terrestrial habitats, creating a mosaic of submerged areas that in turn provide critical resources for both prey and predator species (Pongruktham and Ochs \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mosepele et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Quade et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e). Floodplain-associated schooling fishes must balance the trade-off between food acquisition and detection and mitigating predation risk within newly inundated habitats. Rising water levels, synchronized with increasing water temperatures, facilitates primary production and cues for the immigration of large bodied piscivorous fishes to backwater habitats from the main channel (Mosepele et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Quade et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). Several abiotic factors known to impact collective behaviors of schooling fishes are mediated by flood pulse inundation (Domenici et al. 2016; Kuruvilla et al. 2022; Allibhai et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For example, elevated turbidity that can occur during the onset of the flood pulse (Pongruktham and Ochs 2014) is generally thought to disrupt group cohesion and promote more individualistic behaviors through the disruption of the visual sense (see Zanghi and Ioannou 2024 for recent review).\u003c/p\u003e\u003cp\u003eAbiotic and biotic changes associated with the flood pulse are not necessarily uniform or predictable given the variability of seasonal flood pulses, particularly within heavily modified systems such as the Lower Mississippi River Basin (LMRB). Levees, dams, and water control structures that were designed to reduce flooding have decoupled much of the LMRB from the seasonal flood pulse, reducing this system to less than 8% of its\u0026rsquo; original 10.1\u0026nbsp;million ha (Schramm and Ickes \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The disruption of regular inundation patterns negatively affects floodplain fish species with life histories tied to the natural hydrological cycles of high water in spring and low water in fall (King et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kemp et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Eggleton et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Luo and Criss \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe effects of abiotic and biotic factors on individual and group-level schooling metrics have been extensively studied through simulations and laboratory experiments (Ginnaw et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lambert et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zanghi et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), while field-based studies remain challenging to conduct, particularly in complex, low-visibility environments where direct observation of behavior remains challenging. To overcome these limitations, imaging sonars have emerged as effective tools for observing fish behavior in turbid or low-light environments where traditional video-based or fisheries-dependent methods fall short (Speas et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wei et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sibley et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Munnelly et al. 2024). Operating at high frequencies and producing video-like imagery, imaging sonars are minimally invasive and capable of capturing individual and group-level behaviors across a range of spatial and temporal scales (Narrins et al. 2011; Velez \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). For example, recent studies have demonstrated the utility of this technology in quantifying relative abundance and size-class distributions of floodplain-associated fishes under varying levels of floodplain connectivity within the LMRB (Quade et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003eb\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHere, our goal was to explore how floodplain-associated schooling fishes collectively respond to variation in floodplain connectivity at the Richard K. Yancey Wildlife Management Area. To achieve this, schooling tendencies were described through the quantification of three (3) distinct metrics of school structure: school area, fish swimming alignment (i.e., polarization), and inter-individual distance (i.e., nearest neighbor distance; Rieucau et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Pinto-Rodriguez et al. 2020;2021) using an ARIS Explorer 3000 imaging sonar (Adaptive Resolution Imaging Sonar, Sound Metrics Corporation, Bellevue, Washington, USA). Observations were made across four seasons during both high-water (connected) and low-water (disconnected) periods at four sites located near and far from the initial point of floodplain inundation. We hypothesized that, despite the irregular and episodic nature of inundation, floodplain-associated fishes would exhibit measurable shifts in school structure in response to changes in connectivity. Specifically, we predicted that the largest and most structurally organized schools would be observed during connected-spring and connected-summer, when predation risk is expected to be higher (Quade et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e) and abiotic conditions are more variable. Conversely, we expected schools to decrease in size and become less cohesive during later seasonal inundation levels as predation pressure and environmental variability subside. This study was conducted prior to hydrologic restoration efforts at the Richard K. Yancey Wildlife Management Area, providing a critical baseline for future assessments of collective behavior in response to restoration.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cem\u003eStudy site\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThis study took place in the Richard K. Yancey Wildlife Management Area (WMA), a 28,328-ha floodplain managed by the Louisiana Department of Wildlife and Fisheries, located south of Vidalia, Louisiana. The WMA lies on the western edge of the Mississippi River and features flat terrain dominated by bottomland hardwoods. Three floodplain lakes in the southern WMA connect first to the main-stem river during seasonal flooding. As water rises, these lakes connect to northern areas through culverts and natural channels. Our study focused on the 283-ha designated for culvert replacement and weir repair to improve hydrologic connectivity. A rock weir at the southern lake\u0026rsquo;s outlet marks the initial inundation point for flood pulse inundation. Topography and anthropogenic structures (e.g., levees, berms) restrict floodwaters from entering elsewhere until river stages exceed moderate flood levels.\u003c/p\u003e\u003cp\u003eFour sites that experienced a moving littoral edge (i.e., aquatic-terrestrial transition zone; Junk et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) were haphazardly chosen based on their relative position to the initial point of flood pulse inundation. These sites were grouped qualitatively as \u0026ldquo;near\u0026rdquo; or \u0026ldquo;far\u0026rdquo; sites based on the straight-line distances to the rock-weir. The first near site (2.8 km straight-line distance from rock weir) is positioned just north of the northwestern most floodplain lake, separated by an anthropogenic berm. The second near site, approximately 3.0 km straight-line distance from the rock weir), lies slightly farther up the floodplain. The two far sites (6.2 km and 8.6 km straight-line distance from rock weir) are typically more isolated hydrologically, requiring higher river stages for flood water waters to over-top natural and anthropogenic barriers between near and far sites. All sites retain standing water between flooding events and remain large enough to not restrict fish movement within each site.\u003c/p\u003e\u003cp\u003eThirteen sampling events occurred between 7 August 2021 to 20 January 2023. Sampling events were first grouped by flood pulse status; \u0026ldquo;connected\u0026rdquo; when all four sites were inundated simultaneously and \u0026ldquo;disconnected\u0026rdquo; when all four sites were isolated. Sampling events were then grouped by the season in which they occurred. Connected periods included connected-spring (2-March-2022, 9-April-2022, 29-April-2022, and 27-May-2022) and one connected-summer date (16-June-2022) due to rapid dewatering of the floodplain after this sampling event. Disconnected periods included disconnected-summer (7-August-2021, 22-July 2022, 30-July-2022), disconnected-fall (30-October-2021, 15-September-2022, 30-October-2022) and disconnected-winter (18-December 2022,-20 January 2023). Sampling on 22-July-2022 was abbreviated due to sonar power source failure, however one near and one far site were sampled prior to failure. Inundation status was confirmed using USGS river stage data from Knox Landing (Gauge ID: 07294800) and field observations.\u003c/p\u003e\u003cp\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAt each of the four study sites, the ARIS imaging sonar was deployed manually from a fixed position within 1 meter of the shoreline, resting directly on the floodplain substrate. Prior to deployment, the sonar was affixed to a polyethylene platform measuring 33 \u0026times; 33 \u0026times; 28 cm. The ARIS platform was oriented perpendicular to the water column during deployment to reduce interference from both the water surface and bottom. In part because all sites exceeded the sonar's maximum range of 20 meters, a reduced operating range of approximately 8 meters was selected to optimize recorded image resolution, resulting in video-like recordings at an average of 10 frames per second with a 30\u0026deg; horizontal by 14\u0026deg; vertical field of view. To maximize spatial coverage, the ARIS platform was manually rotated 90 degrees every 20 minutes, resulting in approximately 1 hour of observation per site and covering nearly 270\u0026deg; of the surrounding floodplain, excluding the portion directly behind the unit facing the bank. The order in which sites were sampled was randomized prior to each field day. Sampling was conducted during daylight hours, between approximately 06:30 and 17:30, except on 22 July 2022, when only one near and one far site were recorded due to a sonar power failure.\u003c/p\u003e\u003cp\u003e\u003cem\u003eQuantification of collective behaviors\u003c/em\u003e\u003c/p\u003e\u003cp\u003eUnique floodplain-associated fish schools, here defined as groups containing at least three individuals swimming in apparent coordination, were identified by reviewing each recorded video in its entirety. Although the definition of a school was not restricted by fish size, the majority of observed schools consisted of individuals less than 20 cm total length. Screenshots were captured for each school using ArisFish (Sound Metrics Corporation), and when possible, taken when the school was centered within the field of view of the ARIS. For schools that extended beyond the field of view, multiple screenshots were taken, assessed separately, and then combined. Collective behaviors were quantified using a semi-automated MATLAB script (MathWorks; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.mathworks.com\" target=\"_blank\"\u003ewww.mathworks.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.mathworks.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) developed by Rieucau et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) to estimate inter-individual distance (IID) and alignment (polarization). School area (m\u003csup\u003e2\u003c/sup\u003e) was measured using ImageJ (Version 1.54p; Schneider et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). To reduce overestimation of schooling area, measurements were taken using a consistent approach that minimized spacing between individuals by outlining only the main body masses (i.e., fish to fish), excluding extended gaps between schooling individuals. School area was used a proxy for group size (i.e., number of individuals) given the potential for estimation bias in direct counts resulting from occlusion of schooling members within the video-like dataset. Therefore, in lieu of direct counts of individuals, school area was interpreted alongside inter-individual distances in order to provide insight into school density. Scale bars in both MATLAB and ImageJ were set to one meter using the grid overlay provided in ArisFish screenshots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eEach unique fish school identified was treated as an independent observational unit based on natural variability between sampling events and the assumption that schools observed at different times and locations were biologically distinct. Linear mixed-effects models were fitted for each collective behavior (school area, polarization, and inter-individual distance) using the lmerTest package in R (Kuznetsova et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Site location, seasonal inundation level, and their interaction were included as fixed effects in all three models. The lmerTest package provides p-values in type III ANOVA tables for linear mixed models using the Satterthwaite approximation for degrees of freedom, which is well-suited to unbalanced designs and allows each fixed effect to be tested independently of the others. In addition to significance testing, model comparisons using likelihood ratio tests were used to assess whether interaction terms or main effects improved model fit and warranted inclusion. School area was log\u003csub\u003e10\u003c/sub\u003e transformed prior to model fitting, however, results are reported as back-transformed (geometric mean) values. Inter-individual distances were normalized for body size by dividing the distance between nearest neighbors and the total length of the individual. It is possible that the selected images of each school may not have been satisfactory independent units of replication, therefore, we included each 20-minute (video_ID) that the image was taken from as a random effect to control for possible pseudoreplication. Polarization and IID were assessed at the level of the individual, therefore, to control for possible pseudoreplication school_ID nested within video_ID was treated as a random effect. Post-hoc pairwise comparisons with Bonferroni correction were conducted using the emmeans package (Lenth \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). All statistical analyses were performed in R version 4.2.2 (R Core Team 2022).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe collected 56 hours of video footage from 7 August 2021 to 10 January 2023 that included 5,085 unique schools, comprising a total of 120,114 fish. Model comparison likelihood ratio tests supported the inclusion an interaction between seasonal inundation levels and site (χ\u0026sup2; = 27.02, df\u0026thinsp;=\u0026thinsp;4, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No difference in schooling area was detected between near and far sites (F\u003csub\u003e1,115.17\u003c/sub\u003e = 1.92, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1681). However, we detected a difference between school area among seasonal inundation levels (F\u003csub\u003e4,116.49\u003c/sub\u003e = 15.02, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and an interaction of seasonal inundation levels and site (F\u003csub\u003e4,116.49\u003c/sub\u003e = 6.90, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Pairwise comparisons suggest that schools observed at near sites during disconnected-fall periods were consistently smaller (x̅\u003csub\u003eg\u0026minus;near\u003c/sub\u003e = 0.016) than other schools observed at near and far sites during connected-spring (x̅\u003csub\u003eg\u0026minus;near\u003c/sub\u003e = 0.134, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.000; x̅\u003csub\u003eg\u0026minus;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.101, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), connected-summer (x̅\u003csub\u003eg\u0026minus;near\u003c/sub\u003e =\u0026thinsp;0.117, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00017; x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.173, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), disconnected-summer (x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;near\u003c/sub\u003e =\u0026thinsp;0.074, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0105; x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.085, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), disconnected-fall (x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.077, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0011), and disconnected-winter (x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;near\u003c/sub\u003e =\u0026thinsp;0.211, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.079, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0017). Larger schools were documented to have occurred at far sites during connected-summer periods (x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.173) when compared to schools at both near and far sites during disconnected-summer periods (x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;near\u003c/sub\u003e =\u0026thinsp;0.074, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0247; x̅\u003csub\u003eg\u0026thinsp;\u0026minus;\u0026thinsp;far\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.085, \u003cem\u003eP\u003c/em\u003e = 0.0182).\u003c/p\u003e\u003cp\u003eDifferences in the alignment of individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) were detected between seasonal inundation levels (F\u003csub\u003e4,95.16\u003c/sub\u003e = 4.48, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0023). Model comparison using likelihood ratio tests did not support inclusion of the interaction between site and inundation level (χ\u0026sup2; = 7.50, df\u0026thinsp;=\u0026thinsp;4, P\u0026thinsp;=\u0026thinsp;0.1116), and the main effect of site (Near vs. Far) did not significantly improve model fit (χ\u0026sup2; = 0.15, df\u0026thinsp;=\u0026thinsp;1, P\u0026thinsp;=\u0026thinsp;0.697). Pairwise comparisons suggest that schooling fishes observed during connected-summer periods were swimming in a more aligned manner (θ\u0026thinsp;=\u0026thinsp;7.478) than schooling fishes observed during disconnected-summer (θ\u0026thinsp;=\u0026thinsp;10.047, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0137) and disconnected-fall periods (θ\u0026thinsp;=\u0026thinsp;9.668; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004), with a possible trend observed between disconnected-winter (θ\u0026thinsp;=\u0026thinsp;12.584, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.061).\u003c/p\u003e\u003cp\u003eDifferences in inter-individual distances (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) were detected for seasonal inundation level (F₄,₁₄₃.94\u0026thinsp;=\u0026thinsp;21.04, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Model comparison using likelihood ratio tests did not support inclusion of the interaction between site and inundation level (χ\u0026sup2; = 3.60, df\u0026thinsp;=\u0026thinsp;4, P\u0026thinsp;=\u0026thinsp;0.4622), and the main effect of site (Near vs. Far) did not significantly improve model fit (χ\u0026sup2; = 2.17, df\u0026thinsp;=\u0026thinsp;1, P\u0026thinsp;=\u0026thinsp;0.14). Pairwise comparisons for seasonal inundation levels suggest that schooling individuals observed during connected-spring periods were generally swimming closer to their nearest neighbor (1.225 body lengths) than compared to connected-summer (1.547 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0045), disconnected-fall (1.972 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and disconnected winter (1.659 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), but not when compared disconnected-summer periods (1.135 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.999). Similarly, schooling individuals observed during disconnected-summer periods tended to be closer to their nearest neighbor (1.135 body lengths) than compared to disconnected-fall (1.972 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and disconnected-winter (1.659 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). A possible trend was documented between connected-summer (1.547 body lengths) and disconnected-summer (1.135 body lengths, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0705).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results revealed that river-floodplain connectivity mediates the collective tendencies of schooling fishes within the floodplain. Contrary to our predictions of more cohesive schools during connected periods followed by a gradual decline throughout the disconnected periods, there appears to be shifts in collective behavior with floodplain connectivity, particularly within seasonal inundation levels. Fish tended to swim in a more aligned manner during connected-summer periods, but were generally closer to each other during connected-spring periods and disconnected-summer periods. The observed variation in alignment and inter-individual distances across seasonal inundation levels, despite relatively similar schooling areas, strengthens the idea that floodplain-associated schooling fishes have the ability to adjust their collective tendencies to the prevailing environmental conditions they are facing. This behavioral flexibility reflects a high degree of plasticity in schooling structure. The similarities in alignment and inter-individual distances between connected and disconnected periods likely reflects their response to trade-offs in predation risk, foraging opportunities, and/or environmental conditions mediated by the seasonal flood pulse. Given the considerable year-to-year variation in the timing, magnitude, and duration of seasonal flood pulses in highly altered floodplain systems, patterns observed within the current study may vary across years. For instance, predation risk annually may be highly variable, as the recruitment of predator species has been linked to flood magnitude and duration in preceding years (Alford and Walker 2013; Buckmeier et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and well-timed flood pulses often serve as cues for many floodplain-associated fishes to immigrate from the main channel into backwater habitats (Stoffels et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mosepele et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Long-term monitoring of behavioral patterns across variable hydrologic conditions will be essential to understand how altered flood regimes influence the ecological functions of collective behavior in floodplain systems.\u003c/p\u003e\u003cp\u003eDuring the onset of the flood pulse (i.e., connected-spring), floodplain associated schooling fishes must balance the functional benefits of schooling and the cost of doing so in an altered environment. High flow velocities (Liao \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and turbidity (Kimbell and Morrell \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Allibhai et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) during the initial inundation phase may disrupt the hydrodynamic and collective benefits of schooling. At the same time, rising waters cue for the immigration of large-bodied piscivorous fishes (Roberts et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Quade et al. 2025) and enhance foraging opportunities through enhanced productivity (Junk et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Bayley \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). During connected-spring periods, where flow, turbidity, and predation pressure are expected to be the greatest (Turner \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; van der Sleen \u0026amp; Rams 2023; Quade et al. 2025), schooling individuals swam closer together as compared to disconnected-winter and connected-summer. Given that school areas observed during connected-spring were similar to most other seasonal inundation levels, excepting disconnected-fall, the low inter-individual distances observed during connected-spring would suggest that these schools were denser (i.e., greater number of individuals per area) than connected-summer, disconnected-fall, and disconnected-winter. The higher degree of school structural organization (denser schools comprised of aligned individuals that are closer together) observed during connected-spring should in fact allow for more efficient information transfer among group members during connected-spring periods, facilitating coordinated threat-related collective responses (Rieucau et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Poel et al. 2022). These effects occur despite the potentially disruptive influences of elevated flow velocities and turbidity, suggesting that the benefits of forming large, dense schools outweigh the costs under such conditions (Turner and Pitcher \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Hintz and Lonzarich \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Surprisingly, our results highlights that schools observed during the connected-summer periods exhibited greater inter-individual distances despite fish swimming in a more organized fashion (e.g., lowest angles between nearest neighbors), suggesting a more aligned yet less dense school structure. This collective configuration is thought to enhance hydrodynamic efficiency by reducing individual drag and enabling energy savings while schooling (Weihs 1973; Hemelrijk et al. 2014). As inundation spreads laterally, declining flow rates and turbidity likely reduce abiotic constraints on collective behavior, even as predation risk and foraging opportunities mediated by the flood pulse persist.\u003c/p\u003e\u003cp\u003eLow-water periods during disconnected-fall and disconnected-winter impose a different set of environmental conditions for schooling fishes, including reduced turbidity and a significant reduction of flow (Pongruktham and Ochs 2014). Although overall predator abundance is generally lower during these periods (Walker et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Quade et al. 2025), increased water clarity and shallower depths may elevate perceived predation risk by enhancing visibility and exposure to visually mediated, piscivorous predators such as wading birds (Lantz et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). At the same time, these habitats serve as nursery and refuge areas for young-of-the-year predator species such as gar (McAllister et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Quade et al. 2025). Concurrently, diminished allochthonous and autochthonous inputs likely reduce food availability, intensifying intraspecific competition. Under such conditions, foraging motivation may drive schooling fish toward more individualistic or exploratory behaviors (Stenberg and Persson \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Harpaz and Schneidman \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) over cohesive schooling strategies aimed at mitigating predation risk (Pitcher \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Sumpter \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), as nutritional stress has been shown to increase inter-individual distances (Robinson and Pitcher \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Hansen et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wilson et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our results are consistent with this pattern, as greater inter-individual distances were observed during disconnected-fall and disconnected-winter compared to connected-spring. The magnitude of this pattern was most pronounced in disconnected-fall, particularly at near sites, where fish formed smaller and less cohesive schools. By disconnected-winter, however, fish swam in schools of greater areas despite similar inter-individual distances suggesting that those schools were in fact composed of a greater number of individuals, potentially reflecting a trade-off between competitive pressures and the benefits of group foraging in resource-limited environments (Godin \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Hintz and Lonzarich \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Polyakov et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDisconnected-summer periods offer insight into the complexity of collective behaviors exhibited by floodplain-associated schooling fishes and the trade-offs individuals make to maximize fitness. During this period, both the collective behaviors and the estimated group sizes matched those observed during connected-spring. These similarities are unlikely to be driven by foraging motivation alone, as nutrient accumulation and elevated temperatures during drawdown sustain high productivity (Bayley \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Instead, the rapid decline in Mississippi River water levels prior to the first disconnected-summer sampling event potentially played a central role in the observed collective organization of fish schools. Dewatering is expected to have generated substantial flow and turbidity within monitored sites, reducing visual acuity and affecting fish capacity to detect potential threats. This drawdown phase also serves as a cue for large-bodied piscivorous fishes to emigrate to deeper habitats (Castello et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Roberts et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), such as floodplain lakes or the main channel. However, our monitoring occurred several weeks before this hydrologic transition and thus these interpretations are speculative. Nevertheless, the observed patterns reinforce the critical need for fine-scale temporal assessments to better capture the behavioral adjustments made by schooling fish during dynamic transitional periods.\u003c/p\u003e\u003cp\u003eAltogether, our results suggest that the collective behaviors of floodplain-associated schooling fishes are influenced by floodplain connectivity, specifically seasonal inundation levels. Given the variability in the timing, magnitude, and duration of seasonal flood pulses in the LMRB, continued monitoring of collective behaviors across seasonal inundation levels is required for establishing broader ecological patterns. Specific to our study area, future high-resolution imaging sonar work should focus on how increased connectivity and improved hydrology impact the collective behaviors of schooling fishes in the floodplain, particularly at the culverts designed to improve fish passage. Our study was not designed to specifically explore the mechanisms and ecological functions of schooling in floodplain systems; however, the explanations provided are plausible and should serve as a framework for future research. For instance, in order to ascertain the function explanations of the collective-level adjustments made by aggregated fish could involve altering the floodplain\u0026rsquo;s visual background to create a higher-contrast environment. This change would make schooling fishes more conspicuous and would be expected to trigger an elevated perception of non-consumptive predation risk. High-contrast environments have been successfully used to elicit changes in collective behavior (Rieucau et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), offering a minimally invasive method for field studies. Future research should adopt a stepwise approach to studying the ecological function of schooling in floodplain systems, ensuring that antipredator and foraging treatments are not confounded during \u003cem\u003ein situ\u003c/em\u003e experiments. Furthermore, a comparison of the differences in collective structure of the same fish species assemblages in floodplains that experience consistent annual inundation (e.g., Atchafalaya Basin in southern Louisiana) with those in floodplain systems that undergo irregular inundation could provide insight into how schooling fishes adapt their collective behaviors to different environmental conditions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eAHQ and GR conceived and designed the experiment. AHQ performed the experiment. AHQ, KSB, GR analyzed the data. AHQ, KSB, GR wrote the manuscript.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003ch2\u003eEthical approval:\u003c/h2\u003e\u003cp\u003eNot applicable. No capture or handling of animals have been conducted in our study that was solely based on non-intrusive observations.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003cp\u003eNo applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding statement:\u003c/h2\u003e\u003cp\u003eThis project was funded through a National Fish and Wildlife Foundation grant to GR.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThis project was funded through a National Fish and Wildlife Foundation grant to GR. We thank the Richard K. Yancey staff for their assistance and hospitality. We thank Ashleigh Lambiotte, Brianna Jordan, Erica Teschke, Leflore James Press, Franchesca Basalo, Adalyn Thibodeaux, and Robert Bergeron for the assistance in the field and the laboratory.\u003c/p\u003e\u003ch2\u003eData availability:\u003c/h2\u003e\u003cp\u003eThe data collected and analyzed during our study are available upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAivaz, A. N., A. Manica, P. Neuhaus, \u0026amp; K. E. Ruckstuhl, 2020. Picky predators and odd prey: colour and size matter in predator choice and zebrafish\u0026rsquo;s vulnerability \u0026ndash; a refinement of the oddity effect. Ethology Ecology \u0026amp; Evolution 32: 135\u0026ndash;147. https://doi.org/10.1080/03949370.2019.1680445.\u003c/li\u003e\n\u003cli\u003eAlford, J. B., \u0026amp; M. R. Walker, 2011. Managing the flood pulse for optimal fisheries production in the Atchafalaya River basin, Louisiana (USA). 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Fast and accurate decisions through collective vigilance in fish shoals. Proceedings of the National Academy of Sciences 108: 2312\u0026ndash;2315. https://doi.org/10.1073/pnas.1007102108.\u003c/li\u003e\n\u003cli\u003eWei, Y., Y. Duan, \u0026amp; D. An, 2022. Monitoring fish using imaging sonar: Capacity, challenges and future perspective. Fish and Fisheries 23: 1347\u0026ndash;1370. https://doi.org/10.1111/faf.12693.\u003c/li\u003e\n\u003cli\u003eWilson, A. D. M., A. L. J. Burns, E. Crosato, J. Lizier, M. Prokopenko, T. M. Schaerf, \u0026amp; A. J. W. Ward, 2019. Conformity in the collective: differences in hunger affect individual and group behavior in a shoaling fish. Behavioral Ecology 30: 968\u0026ndash;974. https://doi.org/10.1093/beheco/arz036.\u003c/li\u003e\n\u003cli\u003eZanghi, C., \u0026amp; C. C. Ioannou, 2025. The impact of increasing turbidity on the predator\u0026ndash;prey interactions of freshwater fishes. Freshwater Biology 70: 1\u0026ndash;17. https://doi.org/10.1111/fwb.14354.\u003c/li\u003e\n\u003cli\u003eZanghi, C., M. Munro, \u0026amp; C. C. Ioannou, 2023. Temperature and turbidity interact synergistically to alter anti-predator behaviour in the Trinidadian guppy. Proceedings of the Royal Society B: Biological Sciences 290: 1\u0026ndash;10. https://doi.org/10.1098/rspb.2023.0961.\u003c/li\u003e\n\u003cli\u003eZhang, Y., H. Ko, M. A. Calicchia, R. Ni, \u0026amp; G. V. Lauder, 2024. Collective movement of schooling fish reduces the costs of locomotion in turbulent conditions. PLOS Biology 22: 1\u0026ndash;28. https://doi.org/10.1371/journal.pbio.3002501.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Collective behavior, Plasticity, Schooling, Floodplain, Imaging sonar","lastPublishedDoi":"10.21203/rs.3.rs-7039953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7039953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSeasonal flood pulses are a key driver of environmental variability in large river-floodplain ecosystems, yet their influence on the behavior of many floodplain associated fish remains poorly understood. We used high-resolution imaging sonar to test the hypothesis that, despite the irregular and episodic nature of inundation in the Lower Mississippi River Basin, floodplain-associated schooling fishes would exhibit shifts in collective tendencies in response to changes in floodplain connectivity. As schooling is known to be an adaptive strategy, greater behavioral plasticity would allow schooling individuals to appropriately react to changes in environmental conditions, predation risk, and foraging opportunities. We recorded 56 hours of video across sites located near and far from the initial point of floodplain inundation during connected (high-water) and disconnected (low-water) periods spanning all four seasons. School area, alignment (polarization), and inter-individual distance (nearest-neighbor distance) were quantified from 5,085 schools comprising 120,114 individuals using a semi-automated approach. School areas did not differ across conditions, except for smaller schools observed at near sites during disconnected-fall. Fish swam in a more aligned fashion during connected-summer, while inter-individual distances were lowest during connected-spring and disconnected-summer. Altogether, our results indicate schooling fishes inhabiting the floodplain exhibit behavioral changes at the level of their collective in response to changes in the local environmental conditions. Given the inter-annual variation in flood pulse dynamics, unravelling the functional explanations (e.g., antipredatory, foraging) of the observed modifications of schooling tendencies mediated by water level and river-floodplain connectivity will require more work.\u003c/p\u003e","manuscriptTitle":"Seasonal shifts in collective tendencies of floodplain-associated schooling fishes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 08:44:33","doi":"10.21203/rs.3.rs-7039953/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d2c592eb-abb9-48e7-8d7f-0f48b59a344d","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-08T22:20:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 08:44:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7039953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7039953","identity":"rs-7039953","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}