One of the new papers online in Oikos is about the importance of full understanding of demography of wild populations for management programs. One of the authors, Eleanor Devenish-Nelson gives us here the background to the study “Demography of a carnivore, the red fox, Vulpes vulpes: what have we learnt from 70 years of published studies?”:
The successful management of wildlife depends on the ability to predict the consequences of management actions. That, in turn, often requires a good knowledge of a species’ demography and dynamics. We can use that knowledge, of issues such as birth and death rates, to produce predictive models with which we can simulate different management strategies. In situations in which we don’t know enough about a population of interest, it is common to use ‘surrogate data’ (demographic parameters from other populations of the same, or closely related, species) in order to construct predictive models.
One species of considerable management concern is the red fox. Red foxes are widely hunted and are important hosts for several diseases. The management of red foxes is often contentious, invoking strong feelings in many people. We wanted to produce what we thought would be a straightforward model of red fox dynamics, as the foundation for answering several applied questions. At first glance, foxes appear to be well studied: a quick search brings up over 1000 papers on aspects of their demography. However, an initial assessment of that literature revealed that the demography of this widespread species was surprisingly poorly known, with limited data for most populations and, even for several better-studied populations, missing information on birth or death rates. Some of the demographic rates that we collated were highly variable between populations – but was this a result of genuine differences, or of poorly defined or presented data?
Although the available data on red fox populations are often uncertain and frequently based on relatively short-term studies, we were able to analyse the demography of eight different populations. Those analyses revealed considerable variation in demography among the populations. Differences were sufficient to be of consequence for management. More importantly, by substituting demographic parameters between fox populations, we showed that using surrogate data could often be very misleading for managers. Data substitution is often a necessity but our analyses suggest that it can guide how managers prioritise measuring demographic parameters for their focal populations. In general, for example, a model using surrogate data on the probability with which females breed will be more misleading than if surrogate data on litter size is used. Hence, managers should prioritise accurate estimates of the former.
Overall, what started out as a simple study revealed the significant gaps in our understanding of fox demography, especially in relation to the selection pressures this species faces, such as hunting, disease and a highly variable climate across its range. Owing to variability between populations and the dangers of using surrogate data, the need for more widespread, long-term monitoring is clear. Emerging technologies should be harnessed to make routine the widespread collection of demographic data on wildlife populations. This paper emphasises why a better understanding of the demography of fox populations is of relevance for management.
Photo © Paul Cecil