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The Larch Budmoth in the Alps
Abstract and Figures
During the late 1940s, immediately after World War II, the lush green forests of the Engadine Valley, high in the Swiss Alps, turned an ugly red-brown in the midst of the tourist season. This was due to a spectacular outbreak of the larch budmoth, Zeiraphera
diniana Guenée (Lepidoptera: Tortricidae). Preparing for a revival of the tourist industry, and having the new insecticide DDT at hand, it seemed only appropriate that the tourist office urge the forest service to control the pest. This was the beginning of what was to become a 34-year study of the population dynamics of the larch budmoth (Fig. 1).
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... Recently, an unprecedented outbreak of the Mountain pine beetle in the western United States and Canada produced tree mortality over 374,000 km 2 from 2000-2020; the ensuing fires, decay and growth losses are estimated to have released 270 megatons (Mt) of carbon, contributing measurably to global carbon dioxide pools (Aukema et al. 2006;Kurz et al. 2008;Reed et al. 2014). Some species experience cyclical dynamics with peaks and troughs in abundance that occur at strikingly regular intervals ranging from a few years to multiple decades (Baltensweiler and Fischlin 1988;Tenow et al. 2013;Pureswaran et al. 2016). Others experience yearly fluctuations that can appear random or chaotic and are much more difficult to predict. ...
... The larch budmoth (Zeiraphera diniana) (hereafter LBM) exhibits highly regular cycles of 8-10 years in the Swiss Alps (Fig. 5.5) and has been the subject of sustained study. Swiss researchers kept meticulous records over decades (Baltensweiler et al. 1977;Baltensweiler and Fischlin 1988), not only on caterpillar population densities, but also on tree responses to defoliation, as well as parasitism by a suite of over 100 species of parasitoids. Initial hypotheses emphasized parasitoids (especially the suite of eulophid and ichneumon wasps) and infection by a granulosis virus as a mechanism for observed population cycles, but later analyses indicated that fluctuations in parasitism or infection rates were more likely a consequence than a cause of moth density fluctuations (Baltensweiler and Fischlin 1988). ...
... Swiss researchers kept meticulous records over decades (Baltensweiler et al. 1977;Baltensweiler and Fischlin 1988), not only on caterpillar population densities, but also on tree responses to defoliation, as well as parasitism by a suite of over 100 species of parasitoids. Initial hypotheses emphasized parasitoids (especially the suite of eulophid and ichneumon wasps) and infection by a granulosis virus as a mechanism for observed population cycles, but later analyses indicated that fluctuations in parasitism or infection rates were more likely a consequence than a cause of moth density fluctuations (Baltensweiler and Fischlin 1988). Now, it appears that the cycles arise from density-dependent feedbacks involving both host plant quality and parasitoids. ...
Most insect species are rare most of the time, but populations of certain taxa exhibit dramatic fluctuations in abundance across years. These fluctuations range from highly regular, cyclical dynamics to mathematical chaos. Peaks in abundance, or “population outbreaks” are notable both for the damage they can cause in natural and planted forests and for the rich body of research and theory they have inspired focused on elucidating drivers of population fluctuations across time and space. This chapter explores some of the key mechanisms that explain the population dynamics of outbreaking species, including variation in intrinsic growth rates, lagged endogenous feedbacks linked to top-down and/or bottom-up effects, nonlinearities in the density dependent relationship, and the existence of multiple stable and unstable equilibria, among others. We explore some basic mathematical and graphical approaches to modeling and representing these dynamics and provide a suite of empirical examples from the recent and historical literature.
... Site abbreviations combine a letter for the respective valley (M = Matter Valley and S = Simplon) and a number for the elevational distance (in meters) from the local treeline derived from satellite images to account for varying exposures and microclimates. A Swiss stone pine (Pinus cembra L.) site (M40NH) was additionally included as a non-host site, representing tree growth un- Whereas several approaches for detecting insect outbreaks in tree-ring data have been applied over the last few years [22,25,29,34], only comparisons between host and non-host information potentially enable the differentiation between defoliation and cooling events. However, such techniques may have their own limitations, such as differing temperature responses between species, secondary effects of outbreak events, or simply a lack of availability of non-host material [35]. ...
Though frequently used in dendroclimatology, European larch (Larix decidua Mill.) is regularly defoliated by mass outbreaks of the larch budmoth (Zeiraphera griseana Hb., LBM). The near-cyclic growth depressions are unrelated to but possibly coincide with cold summers, which challenges signal detection on interannual timescales. LBM defoliation events cause sharp maximum latewood density declines and irregular earlywood/latewood ratios in the outbreak year, followed by one or two anomalously narrow rings. Here, we present a process-based method integrating these diverse response patterns to identify and distinguish LBM-related signals from climate-induced deviations. Application to larch sites along elevational transects in the Swiss Alps reveals the algorithm to perform better than existing extreme event detection methods, though our approach enables additional differentiation between insect- and climate-induced signatures. The new process-based multi-parameter algorithm is a suitable tool to identify different causes of growth disturbances and will therefore help to improve both tree-ring-based climate and insect defoliation reconstructions.
... Moreover, cycles of larch budmoth population interaction have been reported by many researchers (cf. [5,6,7,8,9,10,11]). Due to seasonal variation (non-overlapping generations) in the interaction related to larch budmoth, it is more appropriate to model such interaction with discrete-time systems of host-parasitoid type. ...
... Only delayed induced resistance can cause the delayed density-dependent responses (see Chapter 7) that might cause forest insects to exhibit population cycles. Such effects have been proposed for autumnal moth (Haukioja 1991) and for larch budmoth (see Chapter 7; Baltensweiler and Fischlin 1988). In many cases it is not clear whether the changes in foliage chemistry involve defensive compounds or delayed effects on foliage that affect their nutrient quality. ...
One of the most significant categories of insect that cause damage to trees are the defoliators. While many orders of insects feed on tree foliage, in this chapter we will focus on Lepidoptera, as there are so many Lepidopteran larvae (caterpillars) that are known for their extensive tree damage. In this chapter we review the impact of foliage feeders on forest trees and stand composition, and the ways in which densities of these species or the defoliation they cause are monitored. We do not cover insects attacking ornamental trees in the landscape, nor do we cover insects feeding exclusively on foliage tips or buds.
... The two main species characterizing the treeline ecotone along the Alpine chain are European larch (Larix decidua Mill.) and Swiss stone pine (Pinus cembra L.). The TRW and MXD of European larch were largely used for millennial long temperature reconstructions (Büntgen et al. 2006(Büntgen et al. , 2011Corona et al. 2010Corona et al. , 2011, although this species is the main host of the larch budmoth (Zeiraphera diniana Guénée), which alters the year-to-year tree-ring pattern with its regular outbreaks (Baltensweiler and Fischlin 1988;Esper et al. 2007;Büntgen et al. 2009Büntgen et al. , 2020Cerrato et al. 2019a). Similarly, the TRWs of Swiss stone pine have often been used for climatic or glaciological reconstructions Büntgen et al. 2005;Corona et al. 2010;Leonelli et al. 2016), although the climate/growth response of this proxy proved to be unstable across the Alps (Oberhuber 2004;Carrer et al. 2007;Leonelli et al. 2011). ...
Tree rings are widely used for climatic reconstructions and for improving our understanding of ongoing climate change in high-altitude sensitive areas. X-ray maximum latewood density is a very powerful parameter to reconstruct past climatic variations, especially if compared to tree-ring width, but this method is neither inexpensive nor timesaving. However, blue intensity (BI) has resulted in an excellent maximum wood density surrogate that measures the intensity of reflected light from latewood in the blue spectra. This methodology is still considered a prototype parameter, and more data are needed for validation of the method. We present the first BI values coming from Swiss stone pine (Pinus cembra L.) collected on the southern margin of the Alps. Analyses were performed by testing different solvents and polishing techniques, as well as different CooRecorder pixel percentage settings. The results demonstrate that solvents and software parameters have little influence on the final chronologies. Dendroclimatic analyses demonstrate that Swiss stone pine BI can be a useful tool to extract at least the high-frequency variations in July–August temperatures with a correlation coefficient of up to 0.6 (over the 1800–2017 time period). The immunity of Swiss stone pine to insect defoliator outbreaks further enhances the reliability of the BI values of this species in reconstructing past high-frequency temperature variations in high-altitude sensitive areas.
Land-use changes are considered one of the main drivers of biodiversity loss. Agricultural intensification, pastoral abandonment, and changes in forest management have led to the homogenisation of landscapes. In particular, the encroachment of grasslands and the densification of forests that are no longer pastured threaten species that require multiple habitats to nest and forage, such as the European Nightjar Caprimulgus europaeus. Whereas previous studies have focused on understanding factors influencing the decrease of nightjars at regional or national scales, here, we aimed to assess fine-scaled habitat selection by nightjars within nesting and foraging sites based on high-resolution GPS tracking data. Vegetation structure and composition were quantified in the field. In the nesting habitat, nightjars prefer open forests with a low percentage of trees and where the ground is not covered by more than 40% of grass and crawling bushes (dwarf bushes such as Juniperus species). In contrast, when foraging, nightjars select open grasslands and biodiversity-friendly managed vineyards, both richly structured, i.e. interspersed or surrounded by other land-use types such as hedges or isolated trees. Both the nesting and foraging habitats are currently threatened, either by the abandonment of forest management, which makes stands denser and more homogeneous, or through agricultural intensification, which reduces land-use diversity. Clear habitat-specific management recommendations and political incentives are needed to simultaneously preserve and/or restore these critical habitats, which are important for nightjars that use complementary resources for nesting and foraging.
We have applied the Moran–Ricker model with a time lag to describe the dynamics of two populations of larch bud moth. The model takes into account intrapopulation self-regulatory mechanisms. Data on populations inhabiting Switzerland in Graubunden (Baltensweiler, Fischlin, 1988; the Global Population Dynamics Database: Data set 1525) and Oberengadin (Baltensweiler, 1991) locations were used. We have found estimates of model parameter values by minimizing the sum of squared deviations of empirical and model trajectories. The point estimates of the population parameters were shown to satisfy the statistical criteria. The point estimates are located in the region of quasi-periodic oscillations, where, as a rule, they are adjacent to other dynamics modes. Consequently, the variation of population parameters caused by, for example, evolutionary processes or modifying factors influence can change the observed dynamics mode. To test the predictive properties of these models, we use the first part of the data to estimate the parameter values and the rest to compare the real dynamics with the model forecast. As it turned out, the quality of the forecast significantly depends on the nature of the dynamics at the end of the training sample used to estimate the parameters. The best prediction can be obtained if the training sample ends at the population peak phase. In the case of a low abundance phase, the forecast may have an acceptable error, but the nature of the predicted dynamics may change: for example, a shift in the population peak. For Data set 1525, we compare the point estimates obtained from a training sample of different lengths with the dynamic modes of the Moran–Riker model. This allows us to get an insight into the dynamic mode evolution in the Zeiraphera griseana population and to identify transitions from one dynamics mode to another.
What determines population density? Animal ecologists debated this question in the postwar years with as much fervour as bishops at an Ecumenical Council, and with as little thought of settling their differences experimentally. As one of the heretics, I was in schism with the orthodox doctrine of density dependence to which David Lack adhered (Nicholson, 1933; Smith, 1935; Lack 1954a). One of Lack’s contributions was putting this doctrine into an evolutionary context; it is therefore ironical that certain ideas he disapproved of (Chitty, 1952; Lack 1954b) should, after a long metamorphosis, have led to my outdoing him in attempting to tie together natural selection and the regulation of numbers (Chitty, 1967a; 1970). However gross the errors of this still-untested view, they are at least in a direction Lack approved of.
