Spatial Synchrony of Insect Outbreaks

Abstract

Introduction6.3.3 Trophic interactions 119 6.4 The ubiquity of synchrony and its implications 120 Acknowledgments 122 References 122The concept of "spacial synchrony" refers to the tendency of tbe densities of spatially disjunct populations to be correlated in time (Bj0rnscad et al. 1999a, Liebhold et al. 2004. Oucbreaking forest insects offer many of the classic examples of chis phenomenon (Figure 6.1). The spatial extent of synchrony of outbreaks is probably one of the most important -yet most underappreciated -characteristics that cause certain insect species to be classified as noxious pests. Locally eruptive population behavior alone would rarely qualify a species for "outbreak" status. Rather, regionalization of eruptions is what elevates ecologicaJ and socioeconomic impacts of certain species co bigh levels of concern, which gives chem pest status. Consider for example the contrast between the fall web worm, Hyphantria cunea, and the gypsy 1110th, Lymantria dispar (Figure 6.2). The former can reach very high localized densities and denude branches of leaves, but in North America this defoliation is typically limited to isolated colonies on different branches on different trees over several years. Due to the highly localized narure of its d::image, this species is nor considered a major pest in the eastern United States. The gypsy moth in contrast is considered a highly noxious species because its defoliation is extremely synchronized, extending continuously over thousands of hectares in a single year.Outbreaks of forest insects can bave vast impacts on ecosystem functions. These effects include nitrogen leacbing, carbon sequestration, and alteration of fire regimes (

Replacement of a dominant viral pathogen by a fungal pathogen does not alter the collapse of a regional forest insect outbreak

“…The "upward" phase in gypsy moth outbreaks may be promoted by low oak mast production, which subsequently decreases vertebrate predation on gypsy moth pupae Liebhold et al 2012). For the "downward" phase, epizootics of both E. maimaiga and LdNPV are known to drive the collapse of high-density populations, and both pathogens have stages that can remain dormant and thus facilitate their persistence, which is especially important between outbreaks.…”

“…Spatial synchrony of population fluctuations is generally thought to occur either as a result of the dispersal of individuals or due to spatially synchronous fluctuations in weather or other environmental factors (Liebhold et al 2004). In forest insect pests, the latter hypothesis appears to better explain observations of synchronous population fluctuations over large distances (Peltonen et al 2002;Liebhold et al 2012). For example, Haynes et al (2013) found that the most likely driver of synchrony in gypsy moth outbreaks was precipitation, which could synchronize gypsy moth populations directly by affecting gypsy moth survival or reproduction, producing a Moran effect, or indirectly through effects on pathogens, predators, or oak masting.…”

Periodicity and synchrony of pine processionary moth outbreaks in France

“…While the exact reasons for regular fluctuations in population abundance are still actively debated, there is a consensus to consider that they arise from trophic interactions or maternal effects that trigger delayed negative feedback (Liebhold and Kamata, 2000;Berryman, 2002;Esper et al, 2007;Büntgen et al, 2009;Liebhold et al, 2012). Recently Myers and Cory (2013) listed three main factors necessary for cyclic population dynamics: high fecundity to allow fast population growth; density dependent mortality factors to initiate decline in population at peak density; delayed-density dependent mechanisms that prolong population decline.…”

Increasing frequency of low summer precipitation synchronizes dynamics and compromises metapopulation stability in the Glanville fritillary butterfly

“…We examined the effects of metapopulation size in the previous year (log 10 (N t21 )), logtransformed rainfall in July, log-transformed rainfall in August and the percentage of dry plants on the logarithm of metapopulation change (log 10 (N t /N t21 ). We selected a priori a set of ecologically plausible models and used the function model.sel in the package MuMIn v. 1.13.4 to rank the models based on their Akaike information criterion for finite sample sizes (AICc) [39,40].…”

“…Many studies have examined spatial synchrony in population dynamics from a more general perspective, examining the possible causes of synchrony [6][7][8][9][10]. The two causes most discussed are dispersal and spatial autocorrelation in the factors affecting population growth, i.e.…”