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Quantifying individual variation in reaction norms: Mind the residual.

ABSTRACT: Phenotypic plasticity is a central topic in ecology and evolution. Individuals may differ in the degree of plasticity (individual-by-environment interaction (I × E)), which has implications for the capacity of populations to respond to selection. Random regression models (RRMs) are a popular tool to study I × E in behavioural or life-history traits, yet evidence for I × E is mixed, differing between species, populations, and even between studies on the same population. One important source of discrepancies between studies is the treatment of heterogeneity in residual variance (heteroscedasticity). To date, there seems to be no collective awareness among ecologists of its influence on the estimation of I × E or a consensus on how to best model it. We performed RRMs with differing residual variance structures on simulated data with varying degrees of heteroscedasticity and plasticity, sample size and environmental variability to test how RRMs would perform under each scenario. The residual structure in the RRMs affected the precision of estimates of simulated I × E as well as statistical power, with substantial lack of precision and high false-positive rates when sample size, environmental variability and plasticity were small. We show that model comparison using information criteria can be used to choose among residual structures and reinforce this point by analysis of real data of two study populations of great tits (Parus major). We provide guidelines that can be used by biologists studying I × E that, ultimately, should lead to a reduction in bias in the literature concerning the statistical evidence and the reported magnitude of variation in plasticity.

SUBMITTER: Ramakers JJC

PROVIDER: S-EPMC7079083 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Quantifying individual variation in reaction norms: Mind the residual.

Ramakers Jip J C JJC Visser Marcel E ME Gienapp Phillip P

Journal of evolutionary biology 20191209 3

Phenotypic plasticity is a central topic in ecology and evolution. Individuals may differ in the degree of plasticity (individual-by-environment interaction (I × E)), which has implications for the capacity of populations to respond to selection. Random regression models (RRMs) are a popular tool to study I × E in behavioural or life-history traits, yet evidence for I × E is mixed, differing between species, populations, and even between studies on the same population. One important source of di ...[more]

PMID: 31746497

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Project description:Local adaptation and its underlying molecular basis has long been a key focus in evolutionary biology. There has recently been increased interest in the evolutionary role of plasticity and the molecular mechanisms underlying local adaptation. Using transcriptome analysis, we assessed differences in gene expression profiles for three brown trout (Salmo trutta) populations, one resident and two anadromous, experiencing different temperature regimes in the wild. The study was based on an F2 generation raised in a common garden setting. A previous study of the F1 generation revealed different reaction norms and significantly higher QST than FST among populations for two early life-history traits. In the present study we investigated if similar reaction norm patterns were present at the transcriptome level. Eggs from the three populations were incubated at two temperatures (5 and 8 degrees C) representing conditions encountered in the local environments. Global gene expression for fry at the stage of first feeding was analysed using a 32k cDNA microarray. The results revealed differences in gene expression between populations and temperatures and population M-CM-^W temperature interactions, the latter indicating locally adapted reaction norms. Moreover, the reaction norms paralleled those observed previously at early life-history traits. We were able to identify 90 cDNA clones among the genes with an interaction effect that were differently expressed between the ecologically divergent populations. These included genes involved in immune- and stress response. We observed less plasticity in the resident as compared to the anadromous populations, possibly reflecting that the degree of environmental heterogeneity encountered by individuals throughout their life cycle will select for variable level of phenotypic plasticity at the transcriptome level. Our study demonstrates the usefulness of transcriptome approaches to identify genes with different temperature reaction norms. The responses observed suggest that populations may vary in their susceptibility to climate change. Brown trout populations from three rivers in Denmark were studied: the Karup (KAR), Norring Moellebaek (NOR) and Lilleaa Rivers (LIL). These rivers experience different temperature regimes during the period lasting from egg incubation until fry emergence. During the autumn of 2004 and the winter of 2004/2005, adults from the three populations were collected by electro fishing. The fish were stripped for milt and eggs to establish an F1 generation. In autumn/winter 2008/2009, mature F1s were used to establish F2 offspring for each of the three populations. For KAR and LIL, 20 full-sib families were established, whereas for NOR, 15 full-sib families were established. Eggs from each full sib family were divided into two pools that were incubated at 5 and 8M-BM-!C in separate hatching troughs. At the time of first feeding (ca. 750-780 day-degrees), 10 individuals from each family and temperature were collected and transferred to separate tubes containing RNAlater (QIAGEN, Hilden, Germany). A 32K cDNA microarray developed for salmonids by cGRASP was used for the analyses. Ten families were randomly selected from each population. From each family two individuals were analyzed for each temperature (5 and 8oC, respectively), amounting to a total of 120 individuals. Of the two individuals from each temperature treatment within a family, one was labeled with CY5 and the other with CY3. For each family there were two comparisons of individuals representing different temperatures, but with dyes swapped between comparisons.

Project description:The thermal reaction norms of 4 closely related intertidal Nacellid limpets, Antarctic (Nacella concinna), New Zealand (Cellana ornata), Australia (C. tramoserica) and Singapore (C. radiata), were compared across environments with different temperature magnitude, variability and predictability, to test their relative vulnerability to different scales of climate warming. Lethal limits were measured alongside a newly developed metric of "duration tenacity", which was tested at different temperatures to calculate the thermal reaction norm of limpet adductor muscle fatigue. Except in C. tramoserica which had a wide optimum range with two break points, duration tenacity did not follow a typical aerobic capacity curve but was best described by a single break point at an optimum temperature. Thermal reaction norms were shifted to warmer temperatures in warmer environments; the optimum temperature for tenacity (T(opt)) increased from 1.0°C (N. concinna) to 14.3°C (C. ornata) to 18.0°C (an average for the optimum range of C. tramoserica) to 27.6°C (C. radiata). The temperature limits for duration tenacity of the 4 species were most consistently correlated with both maximum sea surface temperature and summer maximum in situ habitat logger temperature. Tropical C. radiata, which lives in the least variable and most predictable environment, generally had the lowest warming tolerance and thermal safety margin (WT and TSM; respectively the thermal buffer of CT(max) and T(opt) over habitat temperature). However, the two temperate species, C. ornata and C. tramoserica, which live in a variable and seasonally unpredictable microhabitat, had the lowest TSM relative to in situ logger temperature. N. concinna which lives in the most variable, but seasonally predictable microhabitat, generally had the highest TSMs. Intertidal animals live at the highly variable interface between terrestrial and marine biomes and even small changes in the magnitude and predictability of their environment could markedly influence their future distributions.

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Quantifying individual variation in reaction norms: Mind the residual.

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Quantifying individual variation in reaction norms: Mind the residual.

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