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The fitness landscape of a community of Darwin’s finches
Borealis
Beausoleil, Marc-Olivier; Carrión-Avilés, Paola; Podos, Jeffrey; Camacho, Carlos; Rabadán-González, Julio; Richard, Roxanne; Lalla, Kristen; Raeymaekers, Joost A. M.; Knutie, Sarah A.; De León, Luis F.; Chaves, Jaime A.; Clayton, Dale H.; Koop, Jennifer A. H.; Sharpe, Diana M. T.; Gotanda, Kiyoko M.; Huber, Sarah K.; Barrett, Rowan D. H.; Hendry, Andrew P. — 2023-08-22 <h3>Purpose</h3> The dataset and script were developed to <ol> <li>estimate the fitness landscape for Darwin's ground finch species (<i>Geospiza</i> spp.) at El Garrapatero over 2003 to 2020, and </li> <li> use the fitness landscape to consider theoretical expectations and previous empirical assertions regarding the topology of fitness and adaptive landscapes. </li> </ol> <h3>Brief Methodology</h3> To fulfil these aims, we used the data from our long-term monitoring site El Garrapatero on Santa Cruz in the Galápagos, Ecuador. We calculated lifespan as a fitness proxi from our recapture data to construct a fitness and adaptive landscape using the beak length and depth. <h3>Data</h3> Please, download and consult the <i>README</i> text file which explains the contents of <i>adaptive.landscapes.finches.zip</i>. The <i>.zip</i> file preserves the folder structure needed to run the scripts. The main program needed for the analysis is <a href="https://cran.r-project.org">R (open-source)</a>, but to fully reproduce all the code, <a href="https://imagemagick.org/index.php">ImageMagick (open-source)</a> and <a href="https://ffmpeg.org">FFMPEG (open-source)</a> programs. <h3>References</h3> <ul> <li><a href="https://github.com/beausoleilmo/adaptive.landscapes.finches">GitHub repository of 'adaptive.landscapes.finches'</a> </li> <li>The scripts and data and for the R language (R Core Team 2023; R version, 4.2.1 (Funny-Looking Kid)). </li> </ul>
Dryad Translation missing: fr.blacklight.search.logo
Temporally varying disruptive selection in the medium ground finch (Geospiza fortis).
Dryad
Beausoleil, Marc-Olivier; Frishkoff, Luke; M'Gonigle, Leithen; Raeymaekers, Joost A. M.; Knutie, Sarah; De León, Luis F.; Huber, Sarah; Chaves, Jaime; Clayton, Dale; Koop, Jennifer A. H.; Podos, Jeffrey; Sharpe, Diana; Hendry, Andrew; Barrett, Rowan D. H. — 2019-12-03 <p><span><span style="font-style:normal;"><span><span style="font-weight:normal;"><span style="letter-spacing:normal;"><span><span><span style="white-space:normal;"><span><span><span>Disruptive natural selection within populations exploiting different resources is considered to be a major driver of adaptive radiation and the production of biodiversity. Fitness functions, which describe the relationships between trait variation and fitness, can help to illuminate how this disruptive selection leads to population differentiation. However, a single fitness function represents only a particular selection regime over a single specified time period (often a single season or a year), and therefore might not capture longer-term dynamics. Here, we build a series of annual fitness functions that quantify the relationships between phenotype and apparent survival. These functions are based on a nine-year mark-recapture dataset of over 600 medium ground finches (<i>Geospiza fortis</i>) within a population bimodal for beak size. We then relate changes in the shape of these functions to climate variables. We find that disruptive selection between small and large beak morphotypes, as reported previously for two years, is present throughout the study period, but that the intensity of this selection varies in association with the harshness of environment. In particular, we find that disruptive selection was strongest when precipitation was high during the dry season of the previous year. Our results shed light on climatic factors associated with disruptive selection in Darwin’s finches, and highlight the role of temporally varying fitness functions in modulating the extent of population differentiation. </span></span></span></span></span></span></span></span></span></span></span></p>

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(auteur : Beausoleil, Marc-Olivier)

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