DOI: 10.5683/sp3/gmallx
title: Climate induced stress and mortality in vervet monkeys

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;As the effects of global climate change become more apparent, animal species will become increasingly affected by extreme climate and its effect on the environment. There is a pressing need to understand animal physiological and behavioural responses to climatic stressors. We used the reactive scope model as a framework to investigate the influence of drought conditions on vervet monkey (Chlorocebus pygerythrus) behaviour, physiological stress and survival across 2.5-years in South Africa. Data were collected on climatic, environmental and behavioural variables and physiological stress via faecal glucocorticoid metabolites (fGCMs). There was a meaningful interaction between water availability and resource abundance: when food availability was high but standing water was unavailable, fGCMs were higher compared to when food was abundant and water was available. Vervet monkeys adapted their behaviour during a drought period by spending a greater proportion of time resting at the expense of feeding, moving, and social behaviour. As food availability decreased, vervet mortality increased. Peak mortality occurred when food availability was at its lowest and there was no standing water. A survival analysis revealed that higher fGCMs were associated with an increased probability of mortality. Our results suggest that with continued climate change, the increasing prevalence of drought will negatively affect vervet abundance and distribution in our population. Our study contributes to knowledge of the limits and scope of behavioural and physiological plasticity among vervet monkeys in the face of rapid environmental change.
description: &lt;b&gt;Usage notes&lt;/b&gt;&lt;br /&gt;&lt;div class="o-metadata__file-usage-entry"&gt;&lt;h4 class="o-heading__level3-file-title"&gt;Young_Data&lt;/h4&gt;&lt;div class="o-metadata__file-description"&gt;Contains data for the four different anaylsis run in the paper. It is an excel sheet with four tabs, each one for each model run in the paper. Headings correspond to the headings used in the R code for each model. R codes are attached separately.&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class="o-metadata__file-usage-entry"&gt;&lt;h4 class="o-heading__level3-file-title"&gt;Mod1_Young_RCode&lt;/h4&gt;&lt;div class="o-metadata__file-description"&gt;File contains R code to run analysis for model 1 in the paper&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class="o-metadata__file-usage-entry"&gt;&lt;h4 class="o-heading__level3-file-title"&gt;Mod2_Young_RCode&lt;/h4&gt;&lt;div class="o-metadata__file-description"&gt;File contains R code to run analysis for model 2 in the paper.&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class="o-metadata__file-usage-entry"&gt;&lt;h4 class="o-heading__level3-file-title"&gt;Mod3_Young_RCode&lt;/h4&gt;&lt;div class="o-metadata__file-description"&gt;File contains R code to run the analysis for model 3 in the paper.&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class="o-metadata__file-usage-entry"&gt;&lt;h4 class="o-heading__level3-file-title"&gt;Mod4_Young_RCode&lt;/h4&gt;&lt;div class="o-metadata__file-description"&gt;File contains R code to run the analysis for model 4 in the paper.&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;
description: <b>Dryad version number:</b> 4
<b>Version status:</b> submitted
<b>Dryad curation status:</b> Published
<b>Sharing link:</b> http://datadryad.org/stash/dataset/doi:10.5061/dryad.8jm8496
<b>Storage size:</b> 3680634
<b>Visibility:</b> public