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Temporal Instability of Lake Charr Phenotypes: Synchronicity of Growth Rates And bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249557; this version posted August 14, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 Temporal instability of lake charr phenotypes: synchronicity of growth rates and 2 morphology linked to environmental variables? 3 4 Chavarie, L.1,2, Steve Voelker3, M.J. Hansen4, C.R., Bronte5, A.M., Muir6, M.S. Zimmerman7, 5 C.C. Krueger2 6 1University of British Columbia, Beaty Biodiversity Research Center, Vancouver, Canada 7 2Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, 8 Michigan State University, East Lansing, Michigan, USA 9 3 Utah State University, Department of Plants, Soils, and Climate, Logan, Utah, USA 10 4U.S. Geological Survey (retired), Hammond Bay Biological Station, Michigan, USA 11 5U.S. Fish and Wildlife Service, Green Bay Fish and Wildlife Conservation Office, New 12 Franken, Wisconcin, USA 13 6Great Lakes Fishery Commission, Ann Arbor, Michigan, USA 14 7Coast Salmon Partnership, Aberdeen, Washington, USA 15 16 *Corresponding author: 17 Email:[email protected], 18 Keywords: Allometry, developmental stability, morphological modulation, plasticity, 19 temporal changes, otolith, dendrochronology, Salvelinus namaycush 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249557; this version posted August 14, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 20 Abstract: 21 Pathways through which phenotypic variation arises among individuals arise can be 22 complex. One assumption often made in relation to intraspecific diversity is that the stability or 23 predictability of the environment will interact with expression of the underlying phenotypic 24 variation. To address biological complexity below the species level, we investigated variability 25 across years in morphology and annual growth increments between and within two sympatric lake 26 charr ecotypes in Rush Lake, USA. We found a rapid phenotypic shift in body and head shape 27 within a decade. The magnitude and direction of the observed phenotypic change was consistent 28 in both ecotypes, which suggests similar pathways caused the temporal variation over time. Over 29 the same time period, annual growth increments declined for both lake charr ecotypes and 30 corresponded with a consistent phenotypic shift of each ecotype. Despite ecotype-specific annual 31 growth changes in response to winter conditions, the observed annual growth shift for both 32 ecotypes was linked, to some degree, with variation in the environment. Particularly, a declining 33 trend in regional cloud cover was associated with an increase of early stage (age 1-3) annual growth 34 for lake charr of Rush Lake. Underlying mechanisms causing reduced growth rates and constrained 35 morphological modulation are not fully understood. An improved knowledge of the biology hidden 36 within the expression of phenotypic variation promises to clarify our understanding of temporal 37 morphological diversity and instability. 38 39 40 41 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249557; this version posted August 14, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 42 Introduction: 43 A rapidly changing climate can have wide-ranging effects on organisms across ecosystems, 44 which fosters a need to understand how ecosystems will respond to this variation in terms of 45 structure and function (Montoya José & Raffaelli 2010; Pacifici et al. 2015). Contemporary 46 climate change, which includes rapid increases in global temperatures, represents one of the most 47 serious and current challenges to ecosystems, not only by threatening ecosystems directly (Norberg 48 et al. 2012), but also by contributing to cumulative and additive effects with other perturbations 49 (e.g., industrial development, pollution, overhavest, non-native species; CAFF 2013; Poesch et al. 50 2016). Ecosystems are mosaics of different habitats, climate change combined with abiotic and 51 biotic variation across these habitats may lead to major eco-evolutionary responses (Grimm et al. 52 2013; Ware et al. 2019). Rapid biological responses to variation associated with climate change 53 have already been detected at all levels, from individuals to species, communities, and ecosystems 54 (Heino et al. 2009). 55 The importance of phenotypic variability has been emphasised in evolutionary and 56 ecological population dynamics (Kinnison & Hairston Jr 2007; Schoener 2011), because variation 57 fuels evolutionary change (Stearns 1989). Pathways through which phenotypic variation arises 58 among individuals can be complex. Intraspecific trait variation as expressed within phenotypes, 59 such as morphology or growth, can affect population dynamics through reproductive and mortality 60 pathways (Bolnick et al. 2011). Furthermore, the magnitude of plasticity in the variation of trait 61 expression differs among populations and ecotypes within a population (Skúlason et al. 2019). A 62 conceptual framework to predict evolutionary and ecological consequences of climate change is 63 currently limited by the scarcity of empirical data demonstrating phenotypic changes over time 64 among individuals within ecosystems. The causes, patterns, and consequences of ecological and 3 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249557; this version posted August 14, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 65 evolutionary responses to differences induced by environmental variability need to be quantified 66 across species, space, and time. 67 The effect of growth rate heterogeneity on morphology modulation (e.g., heterochonry, 68 allometry; Klingenberg 2014) is not a mechanism fully understood, despite being observed to 69 constrain or enhance morphological differences in several fish species (Olsson et al. 2006; Heino 70 2014; Jacobson et al. 2015). Variation in developmental rate associated with juvenile growth rates 71 has been demonstrated to have an effect on the origin of some ecotypes (Alexander & Adams 72 2004; Helland et al. 2009; McPhee et al. 2015). Yet how variation in early development and 73 juvenile growth rate influence later morphology remains ambiguous, with almost no attention 74 focused on among-individual variation within an ecotype. Models have often assumed simple 75 population (and ecotype) dynamics, with populations (and ecotypes) commonly showing a stable 76 ecological evolutionary equilibrium (Svanbäck et al. 2009; Skúlason et al. 2019). 77 Persistence of phenotypes within a system is generally associated with a relatively stable 78 ecological environment that favors canalized phenotypes (e.g., reduction of phenotypic variance 79 at either the within-genotype-among-individual or within-individual levels) over plastic 80 phenotypes (Schluter 2000; Nosil 2012; Westneat et al. 2015; Skúlason et al. 2019). The 81 propensity for growth has both environmental and heritable components with variability in 82 phenotypic expression (van der Have & de Jong 1996; Kingsolver et al. 2004), even for canalized 83 phenotypes. Given rapid environmental change occurring within aquatic ecosystems, phenotypic 84 changes among individuals must not be taken as negligible, because phenotypic variation is driven 85 by switches along developmental pathways (West-Eberhard 2003), in cases where developmental 86 system flexibility can adjust immediately to environmentally variable conditions (Japyassú & 4 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249557; this version posted August 14, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 87 Malange 2014). Thus, temporal variation in phenotypes within an ecotype may not be ecologically 88 trivial in a rapidly changing world. 89 Records of organismal growth patterns provide long-term data sets that reflect 90 environmental variation (Pereira 1995). The diversity of species and ecosystems for which growth 91 chronologies exist (e.g., trees, bivalves, corals, fishes; Black 2009) provide robust datasets for 92 assessment of temporal and spatial environmental variation and its ecological consequences across 93 ecotypes and species, trophic levels, and communities that link ecosystems and biomes. The lake 94 charr (Salvelinus namaycush) is a suitable fish species to link growth chronologies with 95 environmental variation because their longevity that can exceed 60 years (Smith et al. 2008; 96 Chavarie et al. 2016 ). Lake charr are also known to display intraspecific variation, mainly 97 diversifying along a depth gradient, with shallow- versus deep-water ecotypes exploiting different 98 prey resources within
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