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

Abstract

Temporal 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 (ca. 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 generation time of the focal population is required, especially under global warming where the cyclicality in resource dynamics is likely to change.

Stability of consumer–resource interactions in periodic environments

“…B 290: 20231636 similar influence (influence on dynamics is related to relative speeds) or periodicities (e.g. figure 4), similar to results regarding the amplification of noise when periodicities are aligned in other models [22,39,40]. As a first step towards describing this complex and interactive effect of coupled oscillators (abiotic and biotic rhythms), we characterized the effects of environmental forcing across a range of temporal scales by describing qualitatively consistent 'zones' of dynamical responses, based on the dynamic responses of R and C, as dynamics transition towards chaos with decreasing forcing speeds (figures 2 and 4).…”

“…Additionally, under certain intermediate conditions, temporal forcing can interact with the underlying dynamics in complex ways through the effect of coupling these oscillators and driving increased instability; this happens when the forcing and underlying dynamics have similar influence (influence on dynamics is related to relative speeds) or periodicities (e.g. figure 4 ), similar to results regarding the amplification of noise when periodicities are aligned in other models [ 22 , 39 , 40 ].…”

How to measure mast seeding?

“…The trends in volatility reveal that the breakdown of masting in Fagus sylvatica populations is associated with less frequent years of no reproduction and a decline in the amplitude of variation at high frequency, but not at low frequency. This trend decomposition is crucial as the response of consumers to changes in food availability varies depending on whether they are exposed to more frequent famines, higher variance in temporal food availability at low or high frequencies, or all of the above (Yang et al ., 2008; Clark et al ., 2019; Touzot et al ., 2023). For instance, consumer population growth rates are maximized when the masting periodicity and consumer generation times are synchronized (Touzot et al ., 2023).…”

“…This trend decomposition is crucial as the response of consumers to changes in food availability varies depending on whether they are exposed to more frequent famines, higher variance in temporal food availability at low or high frequencies, or all of the above (Yang et al ., 2008; Clark et al ., 2019; Touzot et al ., 2023). For instance, consumer population growth rates are maximized when the masting periodicity and consumer generation times are synchronized (Touzot et al ., 2023). The coefficient of variation, which is unable to differentiate between changes in the proportion of zeroes and changes in variance at high and low frequencies, cannot provide insights into the changes revealed by volatility and periodicity.…”