Individual behaviour, growth, survival and vulnerability to hunting in a large mammal
Cite this dataset
Cusson, Pier-Olivier; Pelletier, Fanie (2024). Individual behaviour, growth, survival and vulnerability to hunting in a large mammal [Dataset]. Dryad. https://doi.org/10.5061/dryad.t4b8gtj8c
Abstract
Humans have exploited wild animals for thousands of years. Recent studies indicate that harvest-induced selection on life-history and morphological traits may lead to ecological and evolutionary changes. Less attention has been given to harvest-induced selection on behavioural traits, especially in terrestrial systems. We assessed in a wild population of large terrestrial mammals whether decades of hunting led to harvest-induced selection on trappability, a proxy of risk-taking behaviour. We investigated links between trappability, horn growth and survival across individuals in early life and quantified the correlations between early life trappability and horn growth with availability to hunters and probability of being shot. We found positive among-individual correlations between early life trappability and horn growth, early life trappability and survival, and early life horn growth and survival. Faster growing individuals were more likely to be available to hunters and shot at a young age. We found no correlations between early life trappability and availability to hunters or probability of being shot. Our results show that correlations between behaviour and growth can occur in wild terrestrial population but may be context dependent. This result highlights the difficulty in formulating general predictions about harvest-induced selection on behaviour, which can be affected by species ecology, harvesting regulations, and harvesting methods used. Future studies should investigate mechanisms linking physiological, behavioural, and morphological traits and how this effects harvest vulnerability to evaluate the potential for harvest to drive selection on behaviour in wild animal populations.
README: Individual behaviour, growth, survival and vulnerability to hunting in a large mammal
This data set was collected for males of a wild bighorn sheep population. It contains information on rams early life behavior, growth and survival as well as two measures of their vulnerability to hunting later in life.
Description of the data and file structure
All the necessary data are contained in a single csv file where:
- ID, is the individual identity of each ram.
- Year, is a grouping variable regrouping every observations that were taken in the same year.
- Cohort, is a grouping variable regrouping rams that were born the same year.
- Age, is the age of rams in years when the measures was taken.
- PopSize, is the total population size when the measure was taken.
- MeanPopSize, is the mean population size individuals experienced from ages 1 to 4.
- Trappability, is the annual number of captures of rams in a corral trap baited with salt.
- HornGrowth, is the annual growth in horn length oh rams in centimeters (cm).
- Survival, is the annual survival of rams. 1 for rams that survived, 0 for rams that died at this age.
- Legal6, reflects whether a ram could be legality harvested by hunters, based on a 4/5 horn curl regulation, at or prior to 6 years of age. Rams that were legal to harvest at or prior to 6 years of age, were assigned a value of 1. Rams that had not achieved a 4/5 horn curl by age 6 wetre coded as 0 as it was not available for hunters. Males that died before reaching 6 years of age while not being legal were assigned NA.
- Harvested6, reflects whether a ram was shot by hunters at or prior to 6 years of age. Males that were shot at 6 years old or younger were assigned the value 1. Individuals that died at 6 years old or older from natural causes or were shot after reaching 6 years old, were given the value 0. Males that died of natural cause before reaching 6 years of age or were never exposed to hunters (when hunting stopped) were assigned NA for fate.
- AgeDeath, is the age at death of rams.
- obs, is a dummy variable uniquely identifying each observation. In this case it reflects the row number.
Code/Software
R code to visualise the data , run the analysis and generate figures and tables is also provided.
The script is a Quarto document.
Funding
Natural Sciences and Engineering Research Council, Award: RGPIN-2018-05405, Discovery Grant
Natural Sciences and Engineering Research Council, Canada Graduate Scholarships – Master’s (CGS M)
Fonds de Recherche du Québec – Nature et Technologies, Master’s Training Scholarships