Luck in Food-Finding Affects Individual Performance and Population Trajectories

Abstract

Energy harvesting by animals is important because it provides the power needed for all metabolic processes. Beyond this, efficient food-finding enhances individual fitness [1] and population viability [2], although rates of energy accumulation are affected by the environment and food distribution. Typically, differences between individuals in the rate of food acquisition are attributed to varying competencies [3] even though food encounter rates are known to be probabilistic [4]. We used animal-attached technology to quantify food intake in four disparate free-living vertebrates (condors, cheetahs, penguins and sheep) and found that inter-individual variability depended critically on the probability of food encounter. We modelled this to reveal that animals taking rarer food, such as apex predators and scavengers, are particularly susceptible to breeding failure because this variability results in larger proportions of the population failing to accrue the necessary resources for their young before they starve, and because even small changes in food abundance can affect this variability disproportionately. A test of our model on wild animals indicated why Magellanic penguins have a stable population while the congeneric African penguin population has declined for decades. We suggest that such models predicting probabilistic ruin can help predict the fortunes of species operating under globally changing conditions. RESULTS AND DISCUSSION Consumer resource theory recognizes the importance of food-finding and deals with broad issues ranging from optimal diet models [5] through behavioural strategies [6] to population dynamics and food web structure [7]. However, although some work recognizes the importance of variation in rates of energy accumulation [8] and how animal condition depends on foraging decisions [9], many models ignore such variation and so cannot build appropriate risks of breeding failure or starvation into their outputs. In fact, resources are generally considered to be distributed probabilistically [10], which does not necessarily equate with linear rates of food

Advances in biologging can identify nuanced energetic costs and gains in predators

“…The energy required for the separate composite behaviours comprising predation can be estimated through the collection of biologging data (Figure 4). Further, the fine-scale frequencies at which these sensors operate allows detailed activity and behavioural budgets to be estimated [161][162][163][164]. GPS and accelerometer data allow the start and end points of predation to be identified so that time spent hunting can be quantified.…”