Amplified Cyclicality in Mast Seeding Dynamics Positively Influences the Dynamics of a Seed Consumer Species.

AbstractTemporal autocorrelation in environmental conditions influences population dynamics through its effects on vital rates. However, a comprehensive understanding of how and to what extent temporal autocorrelation shapes population dynamics is still lacking because most empirical studies have unrealistically assumed that environmental conditions are temporally independent. Mast seeding is a biological event characterized by highly fluctuating and synchronized seed production at the tree population scale as well as a marked negative temporal autocorrelation. In the current context of global change, mast seeding events are expected to become more frequent, leading to strengthened negative temporal autocorrelations and thereby amplified cyclicality in mast seeding dynamics. Theory predicts that population growth rates are maximized when the environmental cyclicality of consumer resources and their generation times are closely matched. To test this prediction, we took advantage of the long-term monitoring of a wild boar population, a widespread seed consumer species characterized by a short generation time (∼2 years). As expected, simulations indicated that its stochastic population growth rate increased as mast seeding dynamics became more negatively autocorrelated. Our findings demonstrate that accounting for temporal autocorrelations in environmental conditions relative to the generation time of the focal population is required, especially under conditions of global warming, where the cyclicality in resource dynamics is likely to change.

How does increasing mast seeding frequency affect population dynamics of seed consumers? Wild boar as a case study.

Mast seeding in temperate oak populations shapes the dynamics of seed consumers and numerous communities. Mast seeding responds positively to warm spring temperatures and is therefore expected to increase under global warming. We investigated the potential effects of changes in oak mast seeding on wild boar population dynamics, a widespread and abundant consumer species. Using long-term monitoring data, we showed that abundant acorn production enhances the proportion of breeding females. With a body-mass-structured population model and a fixed hunting rate of 0.424, we showed that high acorn production over time would lead to an average wild boar population growth rate of 1.197 whereas non-acorn production would lead to a stable population. Finally, using climate projections and a mechanistic model linking weather data to oak reproduction, we predicted that mast seeding frequency might increase over the next century, which would lead to increase in both wild boar population size and the magnitude of its temporal variation. Our study provides rare evidence that some species could greatly benefit from global warming thanks to higher food availability and therefore highlights the importance of investigating the cascading effects of changing weather conditions on the dynamics of wild animal populations to reliably assess the effects of climate change.

Many, large and early: Hunting pressure on wild boar relates to simple metrics of hunting effort.

Wild boar populations have increased dramatically over the last decades throughout Europe and in France in particular. While hunting is considered the most efficient way to control game populations, many local conflicts persist after the hunting period due to remaining high densities of wild boar despite the large number of animals culled every year. Therefore, increasing the efficiency of hunting is a timely issue. Herein, we assessed how hunting effort can be measured, and we determined whether the hunting effort carried out by hunters explains the observed hunting pressure. We measured the characteristics and results of all hunts that occurred in the experimental forest of Châteauvillain-Arc-en-Barrois (Northeastern France), and we modelled the number of animals culled as a function of the hunting effort, measured by the number of beaters, hunters, and dogs, as well as the size of the hunting area. We also accounted for variables suspected to affect the hunting efficiency achieved with a given effort, such as time of day (AM/PM), the month during which hunting occurred. We found that more posted hunters, larger hunted areas, and hunts carried out early in the season, i.e. before February, increased the number of culled animals. Our model can be used by wildlife managers to adjust hunting effort in order to reach the hunting pressure expected to meet management objectives.