1. We report patterns of temporal variation in the recruitment of roach (Rutilus rutilus). The data consist of the annual abundance of the first 2 year‐classes, 0+ and 1+ fish, at four sites in the Rhône River (France) between 1987 and 1997. Over this 11‐year period both 0+ and 1+ fish fluctuated strongly. 
2. Cross‐correlation indicated high spatial synchrony in 0+ dynamics, although correlations among sites in 1+ dynamics were weaker. No clear pattern was apparent in the relationship between the level of synchrony and distance between pairs of sites. 
3. The spatial synchrony in 0+ fish could be attributable to large‐scale variations in weather, influencing water temperature. Total body length of 0+ roach was correlated with water temperature (expressed in degree‐days over 12 °C), and water temperature was the main factor explaining inter‐annual variation in 0+ cohort size. Monthly variation in abiotic factors (measured by standard deviation in water temperature and discharge) did not influence 0+ fluctuations. Correlations with June water temperature suggest that year‐class strength was mainly determined by abiotic factors during the first few months of life. 
4. The absence of spatial synchrony in 1+ fluctuations suggests little correlation between survival and abiotic conditions during the first year of life, other factors influencing survival. 
5. Survival in the first year was density‐dependent. Intraspecific competition within the 0+ cohort could thus influence the fluctuations in recruitment to older age‐classes. 
6. The implications of age‐ or stage‐dependent synchrony in temporal variation for species with complex life histories are discussed. Studying spatial synchrony for the different life history stages could enhance our understanding of the population dynamics of spatially structured species.

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With 5 figures and 4 tables

Summary To assess how climate warming, flow regulation and flow restoration affect community dynamics, we analysed long‐term (15–25 years) series of fish community data from four restored and two unrestored reaches of the Rhône River. Environmental variables (low and high flow hydraulics, temperature, sediment flushing operations) were measured in all reaches. Five of the reaches were bypassed by artificial channels, downstream from diversion dams whose construction finished in 1984. Minimum flows in four of these reaches were restored (i.e. increased by factors up to 10) between 2000 and 2006. We examined hypotheses concerning the inter‐annual response of fish community guilds and size structure to flow restoration, climate warming and dam completions. We also performed a principal component analysis (PCA) to explore observed community changes at the river scale (all reaches pooled). We used mixed‐effects linear models to infer potential environmental effects not included in our hypotheses. Our results indicated an inter‐annual effect of flow restoration in the two reaches where minimum flows were most modified (higher percentages of ‘midstream’ species preferring deep and fast water). They also revealed effects of climate warming in the two warmed reaches (higher percentages of southern and small individuals and higher total density). These effects were consistent with our hypotheses. In contrast, dam construction had no consistent effects across reaches. The first PCA axis indicated that the longitudinal organisation of fish communities at the river scale was unchanged, but independent inter‐annual effects of flow restoration and climate change were apparent along the second and third axes. Observed annual variations within sites were weakly related to annual variation in environmental variables. This may be due to the presence of long‐term or time‐lagged environmental effects and the difficulty of estimating community structure of large river fishes accurately enough for this kind of analysis. Fish community responses to flow restoration and other environmental changes may be consistent across multiple reaches when the degree of environmental change is taken into account. Our results support the effectiveness of flow restoration on communities of large rivers subjected to multiple environmental changes.

Microhabitat selection models are frequently used in rivers to evaluate anthropogenic effects on aquatic organisms. Fish models are generally developed from few rivers, with debatable statistical treatments for coping with overdispersed abundance distributions. Analyses of data from multiple rivers are needed to test their transferability and increase their relevance for stakeholders. Using 3,528 microhabitats sampled in nine French rivers during 129 surveys, we developed models for 35 specific size classes of 22 fish species. We used mixed‐effects generalized linear models (accounting for multiple surveys), involving B‐spline transformations (accounting for nonlinear responses) and assuming a negative binomial distribution (accounting for abundance overdispersion). We compared models of increasing complexity: no selection (M1), an “average” selection similar in all surveys (M2), two models with different selection across surveys (M3–M4). Of 132 univariate cases (specific size classes by habitat), 63% indicated selection for depth, 71% for velocity, 45% for substratum size and 13% for substratum heterogeneity. A total of 50 models were retained, involving 26/35 specific size classes. Model fits indicated low explained deviance (R2MF < 0.19) and higher rank correlations (ρ < 0.69) between observed and modelled values. However, Bayesian posterior predictive checks validated these results since excellent fits would generate R2MF lower than 0.59 and ρ lower than 0.78. We found high transferability among rivers and dates, because (a) M2 was the most appropriate in 26/50 cases; (b) the R2MF and ρ values by M2 was, respectively, 72% and 75% of that explained by the complex M4 and (c) independent river cross‐validations showed good transferability. Bivariate models for selected specific size classes improved univariate model fits (ρ from 0.30 to 0.38). Overall, using a nonlinear mixed‐effect approach, our results confirmed the relevance of “average” models based on several rivers for developing helpful e‐flow tools. Finally, our modelling approach opens opportunities for integrating additional effects as the spatial distribution of competitors.