DOI: 10.5061/dryad.v9s4mw77z
title: Does genetic rescue disrupt local adaptation? An experimental test using thermally adapted <em>Tribolium castaneum</em> lines

description: Anthropogenic drivers are restricting many species to small, genetically
 isolated populations. These are prone to inbreeding depression and are at
 an increased risk of extinction. Genetic rescue, the controlled
 introduction of genetic variation from another population, can alleviate
 inbreeding effects. A major conservation concern, restricting the use of
 this technique, is that such augmented gene flow may disrupt local
 adaptation crucial to a population’s persistence. Using populations of the
 red flour beetle (Tribolium castaneum) experimentally adapted to reproduce
 at higher temperatures, we assess whether genetic rescue attempts disrupt
 thermal adaptation. Rescuers, drawn from populations adapted to either
 30°C or 38°C, were introduced into populations adapted to 38°C, which had
 been inbred for two generations. We recorded population productivity for
 three generations post-rescue, in the adapted 38°C environment. Rescuers
 with and without local adaptation significantly increased the productivity
 of recipient inbred populations but, importantly, those sharing local
 adaptation to reproduction at 38°C provided greater increases in
 productivity. For the first time, we show that co-adaptation between
 rescuing individuals and rescuee population maybe an essential aspect of
 achieving desired conservation outcomes.
description: Husbandry <em>T. castaneum</em>
 populations were maintained on standard fodder (90% white organic flour,
 10% brewer’s yeast and a layer of oats for traction) in a controlled
 environment of 30°C (unless otherwise stated) and 60% humidity with a
 12:12 light-dark cycle. Populations were maintained following a standard
 cycle of virgin adults having seven days of mating and oviposition
 followed by the removal of adult beetle, using 2 mm and 850 µm sieves, so
 that only eggs remain in the fodder. Each generation is initiated with a
 number of adults (line dependent, see below) that are given 7 days to mate
 and lay eggs before being removed. The eggs are left for 35 days to
 develop into mature adults. <em>Tribolium
 castaneum</em> lines Krakow super strain (KSS): A
 combination of fourteen laboratory strains bred to maximise genetic
 diversity in one population maintained at a census size of 600 individuals
 (Laskowski et al., 2015). This line is highly productive at 30°C but has
 reduced fitness at 38°C. This was used as the non-adapted rescuer
 population. Thermal lines: Ten independent lines
 (census size = 100 adults) founded from KSS, and  experimentally evolved
 for ~150 generations at an environmental temperature of 38°C (Dickinson,
 2018), thus imposing selection for development and reproduction at this
 temperature, considerably above the thermal optimum for *T. castaneum
 *(Howe, 1962). All other conditions were as described above aside from a
 shorter development period of 27 days, reflecting accelerated development
 at 38°C. These were used as the thermally adapted rescuer
 populations. Inbred lines: Ten inbred populations were
 created, one from each of the ten thermal lines described above. Adult
 beetles from each thermal line were housed individually for two weeks to
 ensure any fertilized eggs were laid. Single-pair matings were formed by
 housing together a previously isolated male and a female for 7 days of
 mating and oviposition, resulting in a single pair bottleneck for each
 thermal line. Full sibling offspring resulting from this pairing were
 again paired for a second bottleneck. The following generation was
 initiated with 10 male and 10 female full sibling offspring of full
 sibling pairs.  From the offspring of these groups, six inbred
 experimental populations (10 males and 10 females) were created from each
 of the 10 inbred thermal lines, to act as recipient populations for
 genetic rescue. One inbred population only produced four experimental
 populations, resulting in a total of 58 experimental populations split
 over two temporal blocks of 30 and 28. The two blocks were maintained one
 day apart for ease of handling but otherwise received identical treatment.
 Each population received a random ID number to blind the experiment and
 avoid bias. Experimental populations were initiated every generation using
 10 males and 10 females sourced from the offspring of the previous
 generation to reduce density dependent effects (Duval et al., 1939; King
 and Dawson, 1972; Janus, 1989). All experimental inbred recipient
 populations were kept at 38°C in A.B. Newlife 75 Mk4 forced air egg
 incubators (A.B. Incubators, Suffolk, UK); all other conditions were kept
 as described above. Genetic rescue protocol
 Populations were kept in 125 ml tubs containing 70 ml of standard
 fodder. After seven days, adults were discarded and eggs were left to
 develop for ~21 days when 10 male and 10 female pupae were randomly
 selected to establish the next generation. Remaining individuals were
 maintained for 10 days following this and were then frozen and manually
 counted. Pupae taken at day ~21 were housed in plastic dishes containing
 10ml standard fodder in single-sex groups until they matured into adults
 after 10±2 days, and the next generational cycle began with unmated
 adults, avoiding overlapping generations. After a rest
 generation a single male from each inbred recipient population was removed
 and replaced with a single male rescuer to avoid demographic rescue
 effects (increased population fitness due to increased population size)
 (Bell et al., 2019; Ingvarsson, 2001). Three treatments were created: 1)
 control - 19 populations received no rescue (the male was not removed); 2)
 locally adapted rescue - 19 populations received a 38°C-adapted rescuer (a
 male from a different thermally adapted population); 3) non-locally
 adapted rescue - 20 populations received a non-thermally adapted rescuer
 (a KSS male, see above) (figure 1). Population fitness
 was measured using productivity: the number of mature adult offspring the
 population produced each generation. Populations were maintained for three
 non-overlapping generations following rescue. Two replicates were lost
 after two generations due to human error, resulting in a third generation
 with 19 control, 18 thermally adapted rescue, and 19 non-thermally adapted
 rescue populations. Data for populations lost in generation three was
 included in the analysis of generations one and two.
 Statistical analysis R v.4.4.1 (R Core Team,
 2024) was used with R Studio version 2024.04.2+764 (Posit team, 2024).
 Data management and exploration were performed with tidyverse (Wickham et
 al., 2019), stats (R Core Team, 2024), Rmisc (Hope, 2022) and
 googlesheets4 (Bryan, 2023). ggplot2 (Wickham, 2016) was used to visualise
 results. Data distribution was checked using the shapiro.test function (R
 Core Team, 2024). The glmmTMB package (Brooks et al., 2017) was used to
 fit generalised linear mixed models (GLMMs). DHARMa (Hartig, 2022) was
 used to check model fit and the check_collinearity function from the
 performance package (Lüdecke et al., 2021) to test variance inflation
 factor scores (VIF). No overdispersion or collinearity (VIF&lt;3 for
 all variables) was found. R^2 ^was determined using the r.squaredGLMM
 function in MuMIn (Bartoń, 2024). Counts of population
 productivity over all generations was analysed using a GLMM with a
 negative binomial errors and a log link function. Fixed explanatory
 variables were rescue treatment and generation as well as the interaction
 between these variables. To account for populations variance and
 relatedness between replicate populations a random factor was added
 nesting individual ID within the stock thermal line the population
 descended from. The control treatment was set as the baseline factor for
 comparison. The baseline was changed to non-adapted to compare between the
 two rescue treatments post-hoc. GLMMs, constructed as
 described above, but excluding the generation variable, were then run
 post-hoc on each generation individually to test if there were significant
 differences between the treatments in each generation. The baseline was
 changed to non-adapted rescuers, to compare between the two rescue
 treatments post-hoc.
description: # Does genetic rescue disrupt local adaptation? An experimental test using
 thermally adapted *Tribolium castaneum* lines Dataset DOI:
 [10.5061/dryad.v9s4mw77z](10.5061/dryad.v9s4mw77z) ## Description of the
 data and file structure Test of genetic rescuers with or without an
 adaptation effect on the fitness of an adapted, inbred population. Null
 entries in the data sets were not included in that or any future
 generations. #### Abbreviations KSS - Krakow Super Strain, Outbred
 ancestral population. C - Control treatment, Inbred populations that
 received no rescue. A - Adapted rescue treatment, Inbred populations that
 received rescue by a male from a thermally adapted population. N -
 Non-adapted rescue treatment, Inbred populations that received rescue by a
 male from a none-adapted population. ### Files and variables #### File:
 DAGR_-_Sheet1.csv **Description:** Productivity data for an experiment
 with genetic rescue of inbred populations by rescuers from adapted or
 non-adapted populations. ##### Variables * ID: Identifying number of
 population * Generation: Generation after rescue * Productivity: Number of
 adult offspring produced * Thermal: The thermal line that the inbred
 population was descended from * Treatment: Treatment applied to the inbred
 population * Rescuer: Identity of the population the rescuer was sourced
 from * Set: Which of the two sets the population was in #### File:
 DAGRclean.R **Description:** R code for the analysis and visualization of
 the data ## Code/software R v.4.4.1 (R Core Team, 2024) was used with R
 Studio version 2024.04.2+764 (Posit team, 2024). Data management and
 exploration were performed with tidyverse (Wickham et al., 2019), stats (R
 Core Team, 2024), Rmisc (Hope, 2022), and googlesheets4 (Bryan, 2023).
 ggplot2 (Wickham, 2016) was used to visualize results. Data distribution
 was checked using the shapiro.test function (R Core Team, 2024). The
 glmmTMB package (Brooks et al., 2017) was used to fit generalized linear
 mixed models (GLMMs). The emmeans package (Lenth R, 2024) was used for
 post-hoc Tukey tests. DHARMa (Hartig, 2022) was used to check model fit,
 and the check_collinearity function from the performance package (Lüdecke
 et al., 2021) to test variance inflation factor scores (VIF). No
 overdispersion or collinearity (VIF&lt;3 for all variables) was found. R2
 was determined using the r.squaredGLMM function in MuMIn (Bartoń, 2024).