DOI: 10.5061/dryad.rbnzs7hs7
title: Density dependence during evolutionary rescue increases extinction risk but does not prevent adaptation

description: Evolutionary rescue allows populations to adapt and persist despite severe
 environmental change. While well studied under density-independent
 conditions, the role of density dependence, including competition, remains
 unclear. Theoretical models offer conflicting predictions, with density
 dependence either increasing extinction risk or enhancing adaptation. We
 empirically tested how density dependence influences evolutionary rescue
 by exposing experimental populations to a stressful environment for six
 generations under density-dependent or independent conditions, with
 populations where either evolution was possible or was prevented by
 replacing individuals each generation. Density dependence suppressed
 population size and increased extinction risk, whereas density
 independence enabled rapid growth, especially in genetically diverse
 populations where evolution was possible. Although density dependence
 raises extinction risk, it does not prevent populations from responding to
 selection, since surviving density-dependent populations still exhibited
 increased intrinsic and realized fitness. These findings reconcile
 theoretical discrepancies, showing density dependence can simultaneously
 increase extinction risk but may favor adaptation. Our results underscore
 the importance of considering density dependence in conservation
 strategies.
description: # Density dependence during evolutionary rescue increases extinction risk
 but does not prevent adaptation Dryad DOI:
 [https://doi.org/10.5061/dryad.rbnzs7hs7](https://doi.org/10.5061/dryad.rbnzs7hs7) ## GENERAL INFORMATION #### 1. Description This research compendium describes how to analyze population size, extinction, and life-history traits data from an evolutionary rescue experiment conducted in 2022. [here](https://github.com/olazlaure/AnalysisNDDDelta). The analyses of this research compendium are described in: "Density dependence during evolutionary rescue increases extinction risk but does not prevent adaptation." Article DOI: [https://doi.org/10.1101/2024.12.12.628101v3](https://doi.org/10.1101/2024.12.12.628101v3) #### 2. Author information and main investigator: ``` Name: Laure Olazcuaga Institution: Colorado State University, USA Email: olaz.laure@gmail.com ORCID: 0000-0001-9100-1305 ``` For the complete list of authors of the manuscript, see the manuscript. #### 3. Date and geographic location of data collection 2022 Colorado, USA. #### 4. Funding sources that supported the collection of the data Data collection was supported by NSF. #### 5. Recommended citation for this dataset: Olazcuaga, Laure; Melbourne, Brett A.; Nordstrom, Scott W.; Hufbauer, Ruth A. (2026). Density dependence during evolutionary rescue increases extinction risk but does not prevent adaptation [Dataset]. Dryad. https://doi.org/10.5061/dryad.rbnzs7hs7 ## CONTENTS #### Data and file overview * Data_CensusRemoval_NDD_DELTA_Clean.csv: Dataset containing evolutionary rescue experiment data. * Data_Phenotyping_NDD_Delta_Clean.csv: Database containing phenotyping data. #### Details of the dataset ###### Data-specific information for Data_Phenotyping: Data_CensusRemoval_NDD_DELTA_Clean.csv 1. Number of variables: 15 2. Number of cases/rows: 1316 3. Variable List: Block: Temporal block; 1, 2, 4, or 5\ Gen_adults: Generation of the parents for the census measurement; [0:6] POP_ID: Population ID from the experiment; from N1 to N192\ Nb_Box_adults: number of boxes of adults counted; [0:81]\ Census_adults: Number of individuals counted; [0:2827]\ Individuals: Origin of the individuals; lab populations or experimental populations\ Gen_eggs: Generation of the eggs for the census measurement; [1:7]\ Date_start: Start date on which the eggs are laid; mm/dd/yyyy\ Date_end: End date on which the eggs are laid; mm/dd/yyyy\ Origin_population: ID of the ancestral individuals; Label\ Density_dependence: Density of the population; Density_independence or Negative_density_independece\ Genetic_variance: Genetic variance of the population; Non-bottlenecked or Bottlenecked\ Evolution: Evolution treatment of the population; Evolving or Non-evolving\ Treatment: Treatment of the population; Label\ Treatment_all: Full treatment of the population; Label 4. Missing data codes:\ None 5. Abbreviations used:\ NA; not applicable 6. Other relevant information: None ###### Data-specific information for Data_EvolrescueExp: Data_Phenotyping_NDD_DELTA_Clean.csv 1. Number of variables: 30 2. Number of cases/rows: 527 3. Variable List:\ Block: Temporal block; 1, 2, 4, or 5\ POP_ID_ind: ID of the population from the experiment or from the lab stock\ Media: Media of the development; Standard or Extreme\ Density: Density of the adults; 10ind, 50ind or 100ind\ Nb_box: Number of boxes counted; [1:12]\ Census1: Number of offspring in the 1st box; [1:1000]\ Census2: Number of offspring in the 1st box; [1:1000]\ Census3: Number of offspring in the 1st box; [1:1000]\ Census4: Number of offspring in the 4th box; [1:1000]\ Census5: Number of offspring in the 5th box; [1:1000]\ Census6: Number of offspring in the 6th box; [1:1000]\ Census7: Number of offspring in the 7th box; [1:1000]\ Census8: Number of offspring in the 8th box; [1:1000]\ Census9: Number of offspring in the 9th box; [1:1000]\ Census10: Number of offspring in the 10th box; [1:1000]\ Census11: Number of offspring in the 11th box; [1:1000]\ Census12: Number of offspring in the 12th box; [1:1000]\ Who_Census: Person who count the individuals in the lab; Flannery, Hailee, Harley, Morgan or Laura\ Date_start: Start date on which the eggs are laid; mm/dd/yyyy\ Date_end: End date on which the eggs are laid; mm/dd/yyyy\ Gen_adults: Generation of the parents for the census measurement; 5 Gen_eggs: Generation of the eggs for the census measurement; 6\ Density_ind: Density of the adults; [10:100]\ Origin_population: ID of the ancestral individuals; Label\ Density_dependence: Density of the population; Density_independence or Negative_density_independece\ Genetic_variance: Genetic variance of the population; Non-bottlenecked or Bottlenecked\ Evolution: Evolution treatment of the population; Evolving or Non-evolving\ Treatment: Treatment of the population; Label\ Treatment_all: Full treatment of the population; Label\ POP_ID: Population ID from the experiment; from N1 to N147 4. Missing data codes: None 5. Abbreviations used: NA; not applicable 6. Other relevant information: None ## HOW TO RUN IT? This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need to install the [R software](https://cloud.r-project.org/) itself and optionally [RStudio Desktop](https://rstudio.com/products/rstudio/download/). You can download the compendium by cloning this [repository](https://github.com/olazlaure/AnalysisNDDDelta.git): * open the `.Rproj` file in RStudio * open scripts `.Rmd` in reports folder and run it to produce all the analyses and associated reports. * launch the `README.html` to be able to explore the contents on your web browser