The initial dispersal and spread of an intentional invader at three spatial scales

Identification of genes and gene expression associated with dispersal capacity in the mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae)

Dispersal flights by the mountain pine beetle have allowed range expansion and major damage to pine stands in western Canada. We asked what the genetic and transcriptional basis of mountain pine beetle dispersal capacity is. Using flight mills, RNA-seq and a targeted association study, we compared strong-flying, weak-flying, and non-flying female beetles from the recently colonized northern end of their range. Nearly 3,000 genes were differentially expressed between strong and weak flying beetles, while weak fliers and nonfliers did not significantly differ. The differentially expressed genes were mainly associated with lipid metabolism, muscle maintenance, oxidative stress response, detoxification, endocrine function, and flight behavior. Three variant loci, two in the coding region of genes, were significantly associated with flight capacity but these genes had no known functional link to flight. Several differentially expressed gene systems may be important for sustained flight, while other systems are downregulated during dispersal and likely to conserve energy before host colonization. The candidate genes and SNPs identified here will inform further studies and management of mountain pine beetle, as well as contribute to understanding the mechanisms of insect dispersal flights.

The Parasitoid Eretmocerus hayati Is Compatible with Barrier Cropping to Decrease Whitefly (Bemisia tabaci MED) Densities on Cotton in China

The whitefly, Bemisia tabaci (Gennadius) cryptic species Mediterranean (MED), is a destructive insect pest worldwide. In order to contribute to controlling B. tabaci by non-chemical methods, we examined the possibility of using a combination of trap/barrier crops and a parasitoid natural enemy in cotton. We performed field experiments using cantaloupe (Cucumis melo) and sunflower (Helianthus annuus) as trap crops and maize (Zea mays) as a barrier crop combined with periodic releases of the parasitoid Eretmocerus hayati in Hebei Province, Northern China. All treatments significantly reduced immature whitefly densities. Parasitism rate was significantly higher in cotton plots intercropped with sunflower and with perimeter-planted cantaloupe. Adult whitefly density was negatively related to parasitoid abundance and was significantly lower in cotton plots intercropped with maize than in the control plots. Intercropping was more effective than perimeter-planting at reducing B. tabaci densities and increasing yield. Parasitoid dispersal was not hampered by barrier crops, indicating that the two methods of control are compatible. These results contribute to the development of integrated pest management methods against this important pest.

Dispersal Kernels may be Scalable: Implications from a Plant Pathogen

AIM

Understanding how spatial scale of study affects observed dispersal patterns can provide insights into spatiotemporal population dynamics, particularly in systems with significant long-distance dispersal (LDD). We aimed to investigate the dispersal gradients of two rusts of wheat with spores of similar size, mass, and shape, over multiple spatial scales. We hypothesized that a single dispersal kernel could fit the dispersal from all spatial scales well, and that it would be possible to obtain similar results in spatiotemporal increase of disease when modeling based on differing scales.

LOCATION

Central Oregon and St. Croix Island.

TAXA

Puccinia striiformis f. sp. tritici, Puccinia graminis f. sp. tritici, Triticum aestivum.

METHODS

We compared empirically-derived primary disease gradients of cereal rust across three spatial scales: local (inoculum source and sampling unit = 0.0254 m, spatial extent = 1.52m) field-wide (inoculum source = 1.52 m, sampling unit = 0.305 m, and spatial extent = 91.44 m), and regional (inoculum source and sampling unit = 152 m, spatial extent = 10.7 km). We then examined whether disease spread in spatially explicit simulations depended upon the scale at which data were collected by constructing a compartmental time-step model.

RESULTS

The three data sets could be fit well by a single inverse-power law dispersal kernel. Simulating epidemic spread at different spatial resolutions resulted in similar patterns of spatiotemporal spread. Dispersal kernel data obtained at one spatial scale can be used to represent spatiotemporal disease spread at a larger spatial scale.

MAIN CONCLUSIONS

Organisms spread by aerially dispersed small propagules that exhibit LDD may follow similar dispersal patterns over a several hundred- or thousand-fold expanse of spatial scale. Given that the primary mechanisms driving aerial dispersal remain constant, it may be possible to extrapolate across scales when empirical data are unavailable at a scale of interest.

Consequences of Long-Distance Dispersal for Epidemic Spread: Patterns, Scaling, and Mitigation

Epidemics caused by long-distance dispersed pathogens result in some of the most explosive and difficult to control diseases of both plants and animals (including humans). Yet the factors influencing disease spread, especially in the early stages of the outbreak, are not well-understood. We present scaling relationships, of potentially widespread relevance, that were developed from more than 15 years of field and in silico single focus studies of wheat stripe rust spread. These relationships emerged as a consequence of accounting for a greater proportion of the fat-tailed disease gradient that may be frequently underestimated in disease spread studies. Leptokurtic dispersal gradients (highly peaked and fat-tailed) are relatively common in nature and they can be represented by power law functions. Power law scale invariance properties generate patterns that repeat over multiple spatial scales, suggesting important and predictable scaling relationships between disease levels during the first generation of disease outbreaks and subsequent epidemic spread. Experimental wheat stripe rust outbreaks and disease spread simulations support theoretical scaling relationships from power law properties and suggest that relatively straightforward scaling approximations may be useful for projecting the spread of disease caused by long-distance dispersed pathogens. Our results suggest that, when actual dispersal/disease data are lacking, an inverse power law with exponent = 2 may provide a reasonable approximation for modeling disease spread. Furthermore, our experiments and simulations strongly suggest that early control treatments with small spatial extent are likely to be more effective at suppressing an outbreak caused by a long-distance dispersed pathogen than would delayed treatment of a larger area. The scaling relationships we detail and the associated consequences for disease control may be broadly applicable to plant and animal pathogens characterized by non-exponentially bound, fat-tailed dispersal gradients.

Herbivore-induced plant volatiles and tritrophic interactions across spatial scales

Herbivore-induced plant volatiles (HIPVs) are an important cue used in herbivore location by carnivorous arthropods such as parasitoids. The effects of plant volatiles on parasitoids have been well characterised at small spatial scales, but little research has been done on their effects at larger spatial scales. The spatial matrix of volatiles ('volatile mosaic') within which parasitoids locate their hosts is dynamic and heterogeneous. It is shaped by the spatial pattern of HIPV-emitting plants, the concentration, chemical composition and breakdown of the emitted HIPV blends, and by environmental factors such as wind, turbulence and vegetation that affect transport and mixing of odour plumes. The volatile mosaic may be exploited differentially by different parasitoid species, in relation to species traits such as sensory ability to perceive volatiles and the physical ability to move towards the source. Understanding how HIPVs influence parasitoids at larger spatial scales is crucial for our understanding of tritrophic interactions and sustainable pest management in agriculture. However, there is a large gap in our knowledge on how volatiles influence the process of host location by parasitoids at the landscape scale. Future studies should bridge the gap between the chemical and behavioural ecology of tritrophic interactions and landscape ecology.

Inferring stratified parasitoid dispersal mechanisms and parameters from coarse data using mathematical and Bayesian methods

Biological invasions have movement at the core of their success. However, due to difficulties in collecting data, medium- and long-distance dispersal of small insects has long been poorly understood and likely to be underestimated. The agricultural release of parasitic hymenoptera, a group of wasps that are critical for biological pest control, represents a rare opportunity to study the spread of insects on multiple spatial scales. As these insects are typically less than 1 mm in size and are challenging to track individually, a first-time biocontrol release will provide a known spatial position and time of initial release for all individuals that are subsequently collected. In this paper, we develop and validate a new mathematical model for parasitoid wasp dispersal from point release, as in the case of biocontrol. The model is derived from underlying stochastic processes but is fully deterministic and admits an analytical solution. Using a Bayesian framework, we then fit the model to an Australian dataset describing the multi-scale wind-borne dispersal pattern of Eretmocerus hayati Zolnerowich & Rose (Hymenoptera: Aphelinidae). Our results confirm that both local movements and long-distance wind dispersal are significant to the movement of parasitoids. The model results also suggest that low velocity winds are the primary indicator of dispersal direction on the field scale shortly after release, and that average wind data may be insufficient to resolve long-distance movement given inherent nonlinearities and heterogeneities in atmospheric flows. The results highlight the importance of collecting wind data when developing models to predict the spread of parasitoids and other tiny organisms.

Whitefly parasitoids: distribution, life history, bionomics, and utilization

Whiteflies are small hemipterans numbering more than 1,550 described species, of which about 50 are agricultural pests. Adults are free-living, whereas late first to fourth instars are sessile on the plant. All known species of whitefly parasitoids belong to Hymenoptera; two genera, Encarsia and Eretmocerus, occur worldwide, and others are mostly specific to different continents. All parasitoid eggs are laid in-or in Eretmocerus, under-the host. They develop within whitefly nymphs and emerge from the fourth instar, and in Cales, from either the third or fourth instar. Parasitized hosts are recognized by conspecifics, but super- and hyperparasitism occur. Dispersal flights are influenced by gender and mating status, but no long-range attraction to whitefly presence on leaves is known. Studies on En. formosa have laid the foundation for behavioral studies and biological control in general. We review past and ongoing studies of whitefly parasitoids worldwide, updating available information on species diversity, biology, behavior, tritrophic interactions, and utilization in pest management.

Movement of entomophagous arthropods in agricultural landscapes: links to pest suppression

Entomophagous arthropods can provide valuable biological control services, but they need to fulfill their life cycle in agricultural landscapes often dominated by ephemeral and disturbed habitats. In this environment, movement is critical to escape from disturbances and to find resources scattered in space and time. Despite considerable research effort in documenting species movement and spatial distribution patterns, the quantification of arthropod movement has been hampered by their small size and the variety of modes of movement that can result in redistribution at different spatial scales. In addition, insight into how movement influences in-field population processes and the associated biocontrol services is limited because emigration and immigration are often confounded with local-scale population processes. More detailed measurements of the habitat functionality and movement processes are needed to better understand the interactions between species movement traits, disturbances, the landscape context, and the potential for entomophagous arthropods to suppress economically important pests.