DOI: 10.5061/dryad.76dc375
title: Data from: Conservation through the lens of (mal)adaptation: concepts and meta-analysis

description: Evolutionary approaches are gaining popularity in conservation science,
 with diverse strategies applied in efforts to support adaptive population
 outcomes. Yet conservation strategies differ in the type of adaptive
 outcomes they promote as conservation goals. For instance, strategies
 based on genetic or demographic rescue implicitly target adaptive
 population states whereas strategies utilizing transgenerational
 plasticity or evolutionary rescue implicitly target adaptive processes.
 These two goals are somewhat polar: adaptive state strategies optimize
 current population fitness, which should reduce phenotypic and/or genetic
 variance, reducing adaptability in changing or uncertain environments;
 adaptive process strategies increase genetic variance, causing
 maladaptation in the short term, but increase adaptability over the long
 term. Maladaptation refers to suboptimal population fitness, adaptation
 refers to optimal population fitness, and (mal)adaptation refers to the
 continuum of fitness variation from maladaptation to adaptation. Here we
 present a conceptual classification for conservation that implicitly
 considers (mal)adaptation in the short-term and long-term outcomes of
 conservation strategies. We describe cases of how (mal)adaptation is
 implicated in traditional conservation strategies, as well as strategies
 that have potential as a conservation tool but are relatively
 underutilized. We use a meta-analysis of a small number of available
 studies to evaluate whether the different conservation strategies employed
 are better suited toward increasing population fitness across multiple
 generations. We found weakly increasing adaptation over time for
 transgenerational plasticity, genetic rescue, and evolutionary rescue.
 Demographic rescue was generally maladaptive, both immediately after
 conservation intervention and after several generations. Interspecific
 hybridization was adaptive only in the F1 generation, but then rapidly
 lead to maladaptation. Management decisions that are made to support the
 process of adaptation must adequately account for (mal)adaptation as a
 potential outcome and even as a tool to bolster adaptive capacity to
 changing conditions.
description: Table S1 database effect
 sizes - (Mal)adaptation meta-analysisThe following keywords
 were used in our literature searches of conservation strategies: `assisted
 colonization`, `assisted migration`, `translocation`, `genetic rescue`,
 `evolutionary rescue`, `transgenerational plasticity`, `hybridi*ation AND
 outbreeding`, `hybridi*ation OR hybrid AND viability AND conservation`;
 (January 2018 using Web of Science or Google Scholar). To determine if an
 article had usable data on maladaptation, we used the following four
 criteria: (1) data must include a fitness metric, including survival,
 fecundity or egg/seed size, or abundance or recruitment; correlates of
 fitness such as growth or body size were rejected; (2) either data from a
 control without a conservation intervention (to measure relative fitness),
 or data from the population before conservation was implemented (to
 measure absolute fitness), must be available; (3) data from at least two
 different time periods after the conservation intervention must be
 available; (4) sample size, and a metric of sampling variance (standard
 error or deviation, or confidence intervals) for the fitness metrics must
 be reported. A total of 15 articles on a total of 15 species were selected
 based on these four criteria. The species covered a wide taxonomic
 breadth, including yeast, plants, invertebrate animals, and vertebrate
 animals. A total of 95 entries were included, with multiple entries from
 most studies. The type of conservation intervention (i.e., the
 conservation “strategy”) was gleaned from study abstracts. We also
 recorded whether the experimental conditions imposed were stressful (40
 entries, experimental stress treatment, e.g., high salt or heat shock) or
 benign (55 entries, control treatment, e.g., low salt or no heat shock, or
 no implicit stress treatment imposed).Table S1 database effect
 sizes.csvTable S2- Meta-analysis:
 larger dataset of conservation strategies based on categorical data
 (fitness improved, declined, or did not change)Using a larger dataset
 than Table S1 that also included studies without sampling variability or
 sample size, we were table to extract data from 35 studies on a total of
 33 species. This dataset included all 95 entries from the smaller dataset
 described above, and an additional 35 entries, for a grand total of 130
 entries. For each entry, we recorded whether the longer time period
 increased or decreased fitness relative to the short time period, using
 the equation: (w2 – w0 or wcontrol2) – (w1 – w0 or wcontrol1) = difference
 This difference was recorded as “positive”, “negative” or 0. This was done
 for each of the 130 entries. We then created a collapsed database, with
 only one entry per combination of study, species, and conservation
 strategy (noting that some studies included multiple species or
 strategies). If all entries for a study or species or strategy had
 differences (as above) that were positive, we assigned that entry as
 “positive”, and similarly for differences that were all “negative”. If
 some entries were positive and others were negative for a given
 study/species/strategy, we assigned that entry a 0, meaning we were unable
 to conclusively determine whether the conservation implementation was
 beneficial over the long term.Table
 S2.csv