A statistical-reaction–diffusion approach for analyzing expansion processes

Roques, Lionel; Soubeyrand, Samuel; Rousselet, Jérôme

doi:10.1016/j.jtbi.2011.01.006

Cited by 32 publications

(33 citation statements)

References 31 publications

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“…In the future, it will be important to quantify this chance of accidental transportation to predict these long-distance jumps and the expansion of the species' distribution. Furthermore, these jumps may also occur within the main range of PPM because the diffusion coefficient (rate of spread) was relatively high in the Paris Basin between 2007 and 2009 (Roques et al 2011).…”

Section: Greater Dispersal Capabilitiesmentioning

confidence: 99%

Human-mediated long-distance jumps of the pine processionary moth in Europe

Robinet¹,

Imbert²,

Rousselet³

et al. 2011

Biol Invasions

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Although climate change is currently affecting the distribution of many species, insects are particularly impacted because of their high sensitivity to temperature. The pine processionary moth, Thaumetopoea pityocampa, is a forest insect extending its distribution in response to climate warming. Some pioneer colonies were recently detected far beyond the main range, near Paris and in eastern France. This study tracked the origin and pathways of these pioneer colonies through a combined use of genetic markers, measurement of female flight capabilities, and comparative analyses of the natural enemy complexes. This study also aimed to determine the establishment capability beyond the main range, considering the survival rate during two recent cold periods. The larval survival rate was higher in pioneer colonies (which behave like urban heat islands) than in main range. The flight capacity of females would not have allowed them to come from the main range or the nearest established colonies, and molecular tools further showed that individuals from at least three pioneer colonies were not assigned or similar to individuals at the edge of the main range. Egg parasitoids were absent while pupal parasitoids were present in the pioneer colonies suggesting an introduction at the pupal stage. These approaches provided strong evidence that this species has been accidentally moved near Paris and to eastern France, supporting the hypothesis of human-mediated transportation over natural dispersal. This type of dispersal was unexpected because of risks from urticating hairs and the easy detection of the species.

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Section: Greater Dispersal Capabilitiesmentioning

confidence: 99%

Human-mediated long-distance jumps of the pine processionary moth in Europe

Robinet¹,

Imbert²,

Rousselet³

et al. 2011

Biol Invasions

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“…The PPM was sampled within each individual cell throughout each sampling grid according to a protocol defined to monitor the species range expansion towards northern France [30], [34] on the basis of nest road sampling. Each cell is visited by car and PPM host trees are observed by eye and with binoculars (when necessary) from the road and public land.…”

Section: Methodsmentioning

confidence: 99%

Assessing Species Distribution Using Google Street View: A Pilot Study with the Pine Processionary Moth

et al. 2013

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Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.

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“…Several types of data can be used for the estimation of dispersal parameters in population models. Most studies bear on abundance data (Roques et al 2011) or on mark-recapture experiments (Turchin 1998;Ovaskainen et al 2008), where individuals are marked with different technics, such as color markers or radioactive isotopes (Southwood and Henderson 2009). As opposed to this marking experiments, passive surveys of the relative abundance of genetic markers that are naturally present in a population lead to spatio-temporal data which can be easier to obtain and more informative (Robledo-Arnuncio 2012).…”

Section: Introductionmentioning

confidence: 99%

Using genetic data to estimate diffusion rates in heterogeneous landscapes

et al. 2015

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Having a precise knowledge of the dispersal ability of a population in a heterogeneous environment is of critical importance in agroecology and conservation biology as it can provide management tools to limit the effects of pests or to increase the survival of endangered species. In this paper, we propose a mechanistic-statistical method to estimate space-dependent diffusion parameters of spatially-explicit models based on stochastic differential equations, using genetic data. Dividing the total population into subpopulations corresponding to different habitat patches with known allele frequencies, the expected proportions of individuals from each subpopulation at each position is computed by solving a system of reaction-diffusion equations. Modelling the capture and genotyping of the individuals with a statistical approach, we derive a numerically tractable formula for the likelihood function associated with the diffusion parameters. In a simulated environment made of three types of regions, each associated with a different diffusion coefficient, we successfully estimate the diffusion parameters with a maximum-likelihood approach. Although higher genetic differentiation among subpopulations leads to more accurate estimations, once a certain level of differentiation has been reached, the finite size of the genotyped population becomes the limiting factor for accurate estimation.

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A statistical-reaction–diffusion approach for analyzing expansion processes

Cited by 32 publications

References 31 publications

Human-mediated long-distance jumps of the pine processionary moth in Europe

Human-mediated long-distance jumps of the pine processionary moth in Europe

Assessing Species Distribution Using Google Street View: A Pilot Study with the Pine Processionary Moth

Using genetic data to estimate diffusion rates in heterogeneous landscapes

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