Individual variation in disturbance vulnerability (i.e. the likelihood that disturbance negatively affects an individual’s fitness) can affect how disturbance impacts animal populations, as even at low disturbance levels some individuals could be severely affected and die. Individual variation in vulnerability can arise due to different responses to disturbance. We propose a new hypothesis that even when individuals respond similarly to disturbance, time-limited individuals are more at risk that their condition deteriorates since they have limited ability to extend their foraging time to compensate for disturbance. We investigate this ‘time-limitation hypothesis’ both empirically and mathematically by studying how individuals that differ in their average foraging time (presumably due to differences in foraging efficiency) are affected by disturbance. We used tracking data of 22 wintering Eurasian oystercatchers Haematopus ostralegus to compare time budgets between disturbed and undisturbed tidal periods. In three tidal periods with severe disturbance by transport airplane, more than a third of the variation in additional flight time and foraging time loss was explained by individual differences. Inefficient individuals that foraged longer in undisturbed tidal periods experienced higher costs in disturbed tidal periods, since they lost more foraging time. We next used an analytical energy balance model to study how time-limited individuals differed in their maximum disturbance thresholds. Both our theoretical model and empirical study suggest that inefficient individuals in a time-limited environment may be unable to increase their foraging time to compensate for the effects of disturbance. Consequently, the magnitude of individual variation in time budgets strongly determines what proportion of the population is at risk that their condition deteriorates due to disturbance. Our hypothesis implies that, when assessing disturbance effects on a population, it is not only important to consider individual variation in disturbance responses, but also variation in time budgets that determine the consequences of disturbance.
See the article in Oikos for how data was collected.
The dataset consists of four files:
Tidal_Foraging_and_Flight_times.csv includes all tidal flight time and tidal foraging time estimates and all covariates. Column descriptions.xlsx provides a description of each column in the tidal foraging and flight time csv data file.
Code for the mathematical model used to calculate disturbance thresholds, foraging times and energetic losses is provided in model_disturbance_costs_foraging_time.R. mean_FT_all_2017_2019.csv is a file containing mean foraging times of all GPS tracked individuals in our study area (see Supplementary Text 2 in main article in Oikos for more information) and needed as input for the R script.