Influence of the aquatic vegetation landscape on larval fish abundance
Introduction
Aquatic vegetation (AV) increases habitat complexity in both marine (Boström et al., 2006) and freshwater (Jeppesen and Søndergaard, 1998) ecosystems. In addition to the many effects it has on ecosystem functioning by modulating oxygen availability (Caraco et al., 2006) and nutrient cycling (Kalff and Rooney, 2003, Tall et al., 2011), AV is a key component of physical habitat structure. Characteristics such as individual plant architecture as well as AV patch size and fragmentation structure the aquatic habitats at different spatial scales (Boström et al., 2006). By increasing habitat complexity, AV influences predator–prey interactions (Dionne and Folt, 1991, Diehl, 1992) as well as spatial distribution (Eklöv, 1997, Nurminen and Horppila, 2002), abundance (Boström et al., 2006) and community structure of aquatic organisms (Meerhoff et al., 2007).
Even though these effects are relatively well studied at small and meso-scales, the effects of AV landscapes (i.e., at the ecosystem scale) on animal ecology have received little attention and have been mainly studied in marine, coastal and estuarine ecosystems (reviewed in Boström et al., 2006). From these studies, it is generally accepted that AV increases the abundance of some animal populations, supports higher species richness and increases the survival of various animal taxa, including fishes (Smokorowski and Pratt, 2007). For example, many freshwater fish species occupy AV habitats at some stage of their life cycle (Petr, 2000). Near-shore habitats dominated by AV provide (i) refuge from predators, (ii) support for invertebrates, and (iii) foraging habitats for small fish (Pratt and Smokorowski, 2003, Yamaki and Yamamuro, 2013). It was also reported that larval and juvenile fish are more abundant in near-shore lacustrine habitats in mid and late summer, not only because of high temperature, but also because of the shelter and food associated to AV (Wang and Eckmann, 1994, Randall et al., 1996).
Understanding how variations in AV at the landscape scale influence fish abundance in freshwater ecosystems is a considerable challenge due to the difficulty of collecting the high-resolution data needed for such analyses (Deaton et al., 2010). In these ecosystems, AV is often coarsely characterized using qualitative information (i.e., presence/absence, density) estimated locally by visual inspection (Randall et al., 1996, Bertolo et al., 2012), which does not provide the fine-scale variations in AV biomass that is necessary for characterizing landscapes. Consequently, the influence of AV structure on predator–prey interactions has been mostly studied in laboratory (Christensen and Persson, 1993) or pond (Persson and Eklov, 1995) experiments, whereas studies on populations and communities were typically limited to comparing systems with and without AV (Jeppesen and Søndergaard, 1998).
The global loss of AV beds is occurring rapidly in many freshwater ecosystems (Batiuk et al., 2000, Deaton et al., 2010, Vermaire et al., 2012), resulting in a decrease of their carrying capacity (Egertson and Downing, 2004). Negative impacts on fish communities are expected because in their ontogenetic stages, many species use AV for foraging or as shelter to avoid predation or cannibalism (Petr, 2000). A compelling example of the strong linkage between AV habitats and fish carrying capacity is provided in Lake Saint-Pierre (LSP, Hudon et al., 2012), where historically important commercial and sport yellow perch fisheries were supported until the mid-1990s (Guénette et al., 1994). Yellow perch experienced a dramatic collapse beginning in the mid-1990s (Guénette et al., 1994). Despite a major reduction in fishing effort, mainly between 2005 and 2010, yellow perch abundance continued to decrease, likely as a consequence of low recruitment (Magnan et al., 2008). The yellow perch stock has been considered as collapsed since 2011, when a five-year moratorium was imposed on both commercial and sport fishing in 2012. The decrease of aquatic habitat quality was suggested as one of the possible causes of the observed collapse. The progressive transformation of 50 km2 of spring-flooded marshland into perennial crops (1950–1964) and intensive annual cropland between 1964 and 1997 (Richard et al., 2011, de la Chenelière et al., 2014) combined with the shift from AV beds to benthic cyanobacteria documented in 2005–2007 (Vis et al., 2008, Hudon et al., 2012), have profoundly impacted this aquatic ecosystem.
Given that many freshwater fishes have economic and recreational values, studies at the landscape level are critically needed to understand the role of AV on fish abundance and productivity. Here we used yellow perch (Perca flavescens) as a biological model to test the hypothesis that larval fish abundance is positively related to AV abundance at the landscape level. To test this hypothesis, we modeled the probability of observing perch larvae in LSP using data from a seven-year survey of larval abundance (2005–2011) that included more than 200 stations per year in conjunction with an annual index of aquatic vegetation derived from satellite imagery.
Section snippets
Study site
LSP is the largest fluvial lake (≈ 400 km2) of the St. Lawrence River (Fig. 1). This lake, formed by a widening in the river, has a relatively slow current (< 0.5 m × s− 1) and is shallow (mean depth = 3 m), except for a man-made navigation channel (depth > 11 m) that concentrates much of the river flow into its central portion (57–88% of total discharge; Hudon and Carignan, 2008). LSP receives the inflow of five major tributaries (cumulative watershed area = 21,127 km2) distinguished on the basis of their
Larval sampling
Yellow perch larvae were collected approximately 2–3 weeks after hatching (≈ end of May, see ESM Fig. S1) from 2005 to 2011 following the protocol presented in Bertolo et al. (2012). Each year, sampling sites (n = 216) were located all along the LSP perimeter on two isobaths (60–80 cm and 100–120 cm; Fig. 1). Larvae were sampled using pushnets (2 m long plankton-type net, 0.4 × 0.4 m square mount, 500 μm mesh size) at a velocity of 1 m × s− 1. A 50 m long transect parallel to the shore was sampled at each
Prediction of AV biomass
In 2012, EVI was found to be a relatively good predictor of in situ AV biomass in LSP (Fig. 2, R2 = 0.44, p = 0.00033, n = 25). A cross-validation procedure (number of folds = 5) using the CVlm() function from the DAAG R package showed a good predictive accuracy of the model and consequently its reliability to predict EVI from 2004 and 2011 (unpublished data). EVI calculated from 2004 to 2011 ranged between − 0.025 and 0.101; highest values were observed in the nearshore areas and bays of LSP, where
Discussion
Combining seven years of extensive larval sampling (n = 1505) and satellite imageries, and after controlling for spatial auto-correlation among nursery areas at a broad scale, our results clearly suggest that yellow perch larvae tend to be associated with AV habitats within a few weeks of hatching. Whereas the position of spawning grounds is known only at a rough/large scale (Bertolo et al., 2012, see Fig. 1), it is clear that in LSP yellow perch spawns at the beginning of spring in temporary
Acknowledgments
This work was supported by the Centre de recherche sur les interactions bassins versants-écosystèmes aquatiques (RIVE) (1480000) and the Canada Research Chair in Freshwater Ecology (both from the Université du Québec à Trois-Rivières, Québec, Canada) (950-205922) and the Ministère des Forêts de la Faune et des Parcs du Québec. We thank Mr. Rémi Bacon and Nicolas Auclair for larval identification and the staff and research assistants from the Ministère des Forêts de la Faune et des Parcs du
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