processionary moth (Thaumetopoea pityocampa L.) expansion in France

III. MODÈLE ÉTENDU À LA FRANCE

Méthodes. Une régression multiple permet de définir plus précisément un indicateur climatique, appelé ici indicateur climatique global. Nous utilisons cette régression pour estimer les capacités d’alimentation des chenilles à l’échelle spatiale de la France et à l’échelle temporelle du réchauffement climatique (période de 30 ans). Puis nous utilisons le krigeage pour donner la cartographie correspondante.

Résultats. La régression multiple sélectionne la moyenne des températures minimales journalières d’Octobre à Mars (°C) ainsi que la radiation solaire moyenne (W/m²) durant la même période pour expliquer le nombre de jours d’alimentation des chenilles (R²=0.81, P<0.001). La projection spatiale des conditions d’alimentation ainsi estimées sur les périodes 2001-2030 montre une progression potentielle de la processionnaire vers le nord mais surtout vers l’est de la France. En revanche, la progression semble moins accentuée sur la période 2031-2060. Ces résultats montrent également que ce modèle, ajusté dans le Bassin-Parisien, n’est pas valable dans les zones montagneuses (notamment dans le Massif-Central et les Alpes).

CONCLUSION

Même si ce modèle ne détermine pas directement l’enveloppe bioclimatique de la processionnaire du pin, il permet d’obtenir une première approximation sur la potentialité d’expansion de la population. La processionnaire du pin aurait donc la possibilité de progresser encore, en particulier vers le nord et l’est de la France. Comme, a priori, la présence des pins ne limite pas cette progression, seules les perturbations dues à des événements climatiques extrêmes ou un moyen de lutte à grande échelle pourraient venir ralentir cette progression. Il est également indispensable de comprendre la dynamique même de l’expansion et sa vitesse en fonction de l’hétérogénéité du milieu et des capacités de dispersion pour affiner ces prévisions.

Contribution personnelle à ce travail

La modélisation des capacités d’alimentation des chenilles a été appliquée à la fois sur la zone d’expansion vers le nord (Bassin-Parisien) et les zones d’expansion en altitude (Alpes françaises et italiennes). J’ai pris en charge la modélisation dans le Bassin-Parisien tout en travaillant en collaboration avec l’équipe autrichienne qui coordonnait ce travail. Deux séjours l’université BOKU de Vienne (Autriche) m’ont permis de démarrer ce travail. L’estimation de la température à l’intérieur du nid ainsi que le traitement des données issues des images satellite ont été réalisés par l’équipe autrichienne.

Running title: Effects of climate change on the feeding activity

Modelling the effects of climate change on the potential feeding

activity of Thaumetopoea pityocampa (Den. &Schiff.)

(Lep., Notodonidae) in France

Christelle Robinet, Peter Baier, Josef Pennerstorfer, Axel Schopf and Alain Roques

C. Robinet ( ) · A. Roques

INRA Zoologie Forestière, Av. de la pomme de pin, BP 20619 Ardon, 45166 Olivet, France. Tel. +33-2-38-41-78-61; Fax +33-2-38-41-78-79

e-mail: robinet@orleans.inra.fr

P. Baier · J. Pennerstorfer · A. Schopf

BOKU - Dept. of Forest and Soil Sciences. Institute of Forest Entomology, Forest Pathology & Forest Protection, Hasenauerstr. 38, A-1190 Vienna, Austria

ABSTRACT

Aim As for many species, the range distribution of the pine processionary moth (PPM), Thaumetopoea pityocampa L., is currently expanding in higher latitudes and elevations. Since a recent study (Battisti et al. 2005) suggests that climate affects the PPM feeding activity, we intend to identify areas which are susceptible to PPM invasion according to the change of potential feeding activity.

Location The model was initially applied to a localized area covering central France up to the Paris Basin where the PPM is currently expanding, then it was extended to the whole France.

Methods The historical model which determined the potential distribution area (Huchon & Démolin 1970) fails with climate warming. So we applied the potential feeding model to climatic conditions recorded in the field and we compared the resulting feeding change to the PPM expansion. Then we extended this localized model to a larger temporal and spatial scale.

Results The PPM border coincided with a relatively unfavourable stripe in the Paris Basin during 1992-1996, and the PPM succeeded to cross this stripe when feeding conditions became more favourable in 2000-2004. The feeding indicator (minimum temperature from October to March) gives an evidence of a general trend started since the end of the 1980s. At a larger scale, this model forecasts ameliorated feeding conditions in the North-Western quarter of France in the next decades.

Main conclusions The PPM range distribution close to the Paris Basin is not limited by the feeding conditions. The pattern of expansion is now governed mainly by dispersal capacities and host plant distribution. At the country scale, this approach gives a roughly indication of the PPM distribution even if this model fails in mountainous regions.

Key words bioclimatic envelope, climate change, ecological modelling, feeding activity, forest defoliator, range expansion, spatial dynamics, Thaumetopoea pityocampa

INTRODUCTION

Climate has already encountered a significant warming of 0.6°C during the last century and this mean global temperature is projected to continue increasing by 1.4-5.8°C till 2100 (IPCC 2001). Europe has warmed more than the global average and winter temperature has increased more than summer temperature (European Environment Agency, 2004). The response of overall ecosystem remains difficult to predict. Many recent studies already highlighted the fingerprint of the global climate change on animal and vegetal species (Hughes 2000, Walther et al. 2002, Parmesan & Yohe 2003, Root et al. 2003). They showed a great variety of reactions and notably the displacement of the species range distribution. Thus, European species whose distribution is closely associated with winter temperatures are particularly susceptible to undergo a tremendous change in the next years. Birds (Thomas & Lennon 1999, Visser et al. 2003), vegetation (Theurillat & Guisan. 2001, Bakkenes et al. 2002) and insects, and more particularly butterflies (Parmesan et al.1999, Thomas et al. 2001, Warren et al. 2001, Hill et al. 2002, Konvicka et al. 2003, Crozier 2004), are already affected by this change in Europe. Some non-migratory European butterflies have shifted from 35 to 240 km northward during the last century (Parmesan et al. 1999), while the climatic isotherms have shifted the equivalent of 120 km northward (Watson et al. 1998).

The spatial distribution of a given species is mainly governed by environmental constraints. Among them, climatic conditions that enable the species to survive and to grow define a bioclimatic envelope. Modelling this constraint generally provides an efficient way to approximate the disturbance of the species range distribution face to the climate change (Pearson & Dawson, 2003). Even if no systematic behaviour is presently observed, we expect that climate warming make such bioclimatic envelopes shift poleward: species living at low latitudes are likely to shift or expand poleward whereas the others would rather contract and eventually disappear.

Phytophagous insects generally provide convenient models to explore this disturbance due to their physiological dependence on climate (Karban & Strauss 2004) and, consequently their rapid response to climate change (Bale et al. 2002). In this paper, we investigate the impact of climate warming on the expansion of the pine processionnary moth (PPM), Thaumetopoea pityocampa (Denis & Schiffermüller) (Lepidoptera, Notodontidae) in order to identify areas susceptible to be invaded in future. Latitudinal and altitudinal expansion of the PPM outbreaks has been reported in the whole Europe (Hellrigl 1995, Benigni & Battisti 1999, Goussard et al. 1999, Hodar et al. 2003, Battisti et al., in press). The northward expansion of the PPM was more particularly surveyed in the South of the Paris Basin (France). The front has shifted by 27.1 km/decade between 1972 and 2004 and has accelerated during the last ten years (55.6 km/decade) (Battisti et al., in press). Phenology of this insect depends on the climatic region and this strategy allows the moth to emerge after the warmest temperatures in low latitudes and to avoid eventual heat waves (Démolin 1969a). To date, we have not enough information to determine the effect of global warming on southerly distributed PPM populations.

The study of climate impact on PPM phenology and distribution began far before the question of climate warming. A first model, proposed by Huchon & Démolin (1970), integrated two climatic variables: the annual sunshine duration and the mean of minimum temperature in January. According to their theory, two minimum thresholds are required to allow PPM survival: 1800 hours of annual sunshine duration and a minimum temperature of -4°C, then sunshine could balance cold temperatures. These conditions were projected on a map to define the theoretical exclusion area.

The distribution of the PPM is limited by direct temperature effects on its survival capacities. Battisti et al. (in press) showed that microclimatic conditions could constrain the

PPM distribution by governing the feeding activity of the larvae during the cold period. The understanding of this ecophysiological process was based on a combination of lab and field experiments.

In this paper, we firstly modified the historical model taking into account the climate warming. A discriminant analysis permits to characterize current favourable areas and to calculate projections for the next decades. Then we developed an original mechanistic model based on the microclimatic conditions for the feeding activity. We constructed a spatially and temporary localized model in the South of the Paris Basin. Thereafter, we made a generalization at the country scale and at the temporal scale of climate change in order to give a first approximation of the potential change magnitude of the PPM distribution.

METHODS

Dans le document Modélisation mathématique des phénomènes d'invasion en écologie: exemple de la chenille processionnaire du pin (Page 123-127)