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124 results for “temperature adaptation”

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dryad32/100

Data from: Northern range expansion of European populations of the wasp spider Argiope bruennichi is associated with global warming correlated genetic admixture and specific temperature adaptations

Poleward range expansions are observed for an increasing number of species, which may be an effect of global warming during the past decades. However, it is still not clear in how far these expansions reflect simple geographical shifts of species ranges, or whether new genetic adaptations play a role as well. Here, we analyse the expansion of the wasp spider Argiope bruennichi into Northern Europe during the last century. We have used a range-wide sampling of contemporary populations and historical specimens from museums to trace the phylogeography and genetic changes associated with the range shift. Based on the analysis of mitochondrial, microsatellite and SNP markers, we observe a higher level of genetic diversity in the expanding populations, apparently due to admixture of formerly isolated lineages. Using reciprocal transplant experiments for testing overwintering tolerance, as well as temperature preference and tolerance tests in the laboratory, we find that the invading spiders have possibly shifted their temperature niche. This may be a key adaptation for survival in Northern latitudes. The museum samples allow a reconstruction of the invasion's genetic history. A first, small-scale range shift started around 1930, in parallel with the onset of global warming. A more massive invasion of Northern Europe associated with genetic admixture and morphological changes occurred in later decades. We suggest that the latter range expansion into far Northern latitudes may be a consequence of the admixture that provided the genetic material for adaptations to new environmental regimes. Hence, global warming could have facilitated the initial admixture of populations and this resulted in genetic lineages with new habitat preferences.

opencc-zeroDec 2012View details →

dryad32/100

Data from: Genetically distinct populations of northern shrimp, Pandalus borealis, in the North Atlantic: adaptation to different temperatures as an isolation factor

The large-scale population genetic structure of northern shrimp, Pandalus borealis, was investigated over the species' range in the North Atlantic, identifying multiple genetically distinct groups. Genetic divergence among sample localities varied among 10 microsatellite loci (range: FST = −0.0002 to 0.0475) with a highly significant average (FST = 0.0149; P < 0.0001). In contrast, little or no genetic differences were observed among temporal replicates from the same localities (FST = 0.0004; P = 0.33). Spatial genetic patterns were compared to geographic distances, patterns of larval drift obtained through oceanographic modelling, and temperature differences, within a multiple linear regression framework. The best-fit model included all three factors and explained approximately 29% of all spatial genetic divergence. However, geographic distance and larval drift alone had only minor effects (2.5–4.7%) on large-scale genetic differentiation patterns, whereas bottom temperature differences explained most (26%). Larval drift was found to promote genetic homogeneity in parts of the study area with strong currents, but appeared ineffective across large temperature gradients. These findings highlight the breakdown of gene flow in a species with a long pelagic larval phase (up to 3 months) and indicate a role for local adaptation to temperature conditions in promoting evolutionary diversification and speciation in the marine environment.

opencc-zeroDec 2014View details →

dryad32/100

Data from: Adaptive maternal behavioral plasticity and developmental programming mitigate the transgenerational effects of temperature in dung beetles

Phenotypic plasticity allows organisms to cope with rapid environmental change. Yet exactly when during ontogeny plastic responses are elicited, whether plastic responses produced in one generation influence phenotypic variation and fitness in subsequent generations, and the role of plasticity in shaping population divergences, remains overall poorly understood. Here, we use the dung beetle Onthophagus taurus to assess plastic responses to temperature at several life stages bridging three generations and compare these responses across three recently diverged populations. We find that beetles reared at hotter temperatures grow less than those reared at mild temperatures, and that this attenuated growth has transgenerational consequences by reducing offspring size and survival in subsequent generations. However, we also find evidence that plasticity may mitigate these consequences in two ways: (i) mothers modify the temperature of their offspring's developmental environment via behavioral plasticity and (ii) in one population, offspring exhibit accelerated growth when exposed to hot temperatures during very early development ("developmental programming"). Lastly, our study reveals that offspring responses to temperature diverged among populations in fewer than 100 generations, possibly in response to range-specific changes in climatic or social conditions.

opencc-zeroDec 2017View details →

zenodo32/100

Data from: Balanced mitochondrial function at low temperature is linked to cold adaptation in Drosophila species

Data from: Balanced mitochondrial function at low temperature is linked to cold adaptation in Drosophila species

opencc-by-4.0Mar 2023View details →

zenodo32/100

Data and Code for: Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America

This submission contains all the code and data necessary for reproducing 1) the dataset, 2) the main results, and 3) all supplemental analyses appearing in the manuscript titled: Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America (Ramirez-Parada, Park, Record, Davis, Ellison, and Mazer, 2023). A preprint of this manuscript can be accessed at: https://doi.org/10.21203/rs.3.rs-3131821/v1.   Extracting the compressed file will generate a folder titled "Project folder", containing sub-folders named "Data" and "R code". In order for the code to work, users need to preserve the folder structure of the code and data, as the R Markdown files in the "R code" folder have relative file paths that read and write data within the "Data" folder. Moving either would require re-writing the filepaths across Rmds for the code to run. To replicate the results, the following R Markdowns must be run in sequence (once they have been run, the Rmds for supplemental analyses can be used in any order): "1. Subsetting Dataset.Rmd" This file processes a specimen dataset of ca. 2.3 million specimens that we assembled for this project (publicly available on Dryad: <a href="https://doi.org/10.25349/D9WP6S">https://doi.org/10.25349/D9WP6S</a>), filtering out duplicates, specimens out of the spatial scope of the PRISM data used for all analyses,  and subsetting to only those species represented by a minimum of 300 specimens. This filtering yields a dataset of 1,038,047 specimens in flower across 1,605 species. For an in-depth description of the starting dataset, please refer to the "READ ME.txt" file within the "Project folder", and visit its corresponding Dryad repository (linked above). "2. Main Analysis - Estimating S_space, S_time, and S_diff.Rmd" This file uses the subset dataset produced by the previous Rmd to fit the varying-intercepts, varying-slopes model that produced the estimates of apparent plasticity and apparent adaptation underlying all main analyses. This Rmd exports a dataset of species-specific estimates of Sspace, Stime, and Sspace - Stime that is used to recreate Figures 2, 3, and 4 of the main text in the next step. This is the most time consuming R Markdown file to run, as each MCMC chain used to fit the model in Stan must be run on a dedicated processor (limiting the usefulness of parallel computation). Fitting the model using 3 MCMC chains, 1000 iterations for warmup, and 4000 iterations for sampling, took approximately 24 hours using an Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz processor.     "3. Main Analysis - Figures 2, 3, and 4.Rmd" Finally, this Rmd uses the dataset of species-specific estimates to conduct all analyses underlying Figures 2, 3, and 4, recreating each of these figures. For detailed descriptions of all materials (code and data) and instructions for using them, please refer to the "READ ME.txt" file within "Project folder".

openSep 2023View details →

dryad32/100