Ecology and Risk Modelling

THEME 3: Population dynamics of the MPB system in novel habitats

 3.1 Endemic dynamics in novel habitats


 (1) Quantify the endemic niche in novel habitats east of the Rocky Mountains.

(2) Determine the endemic-epidemic threshold in these novel habitats of Objective 1.

(3) Determine the effect of population density on MPB dispersal capacity.

3.2 MPB productivity and spread

3.2.1 Invasion status: leading edge vs established invaders


 (1) Determine if host finding and acceptance by MPB changes at the leading edge of an invasion.

(2) Ascertain if there a difference in sex ratios at the leading edge of an invasion, and whether this affects the propensity for dispersal.

(3) Identify the impact of variable emergence and flight timing on establishment of invading populations.

3.2.2 Host defenses


 (1) Determine whether it is possible to discern the signature of a vulnerable tree.

(2) Determine how tree defense capacity affects MPB establishment, productivity and spread.

(3) Determine how tree defense capacity varies with the growing conditions, particularly drought and nutrients, and whether this affects MPB beetle productivity.

(4) Determine if tree mortality due to low density MPB attacks is related to defensive capacity of these trees, and if so, if this is mediated by host tree genotype.

3.2.3 Symbiotic fungi


(1) Assess whether the fitness of MPB (i.e. fat body content and subsequent pheromone production) is affected when their immatures develop in N rich versus N poor hosts.

3.3 Modeling stand risk


(1) Develop a stand-level risk model for MPB in novel pine habitats.

 3.4 Spread/risk modeling


(1) Develop a statistical model for absolute spread risk.

(2) Develop a process-based model for spread risk.

(3) Conduct a quantitative analysis of the process-based spread model.

3.5 Emergent management tactics


(1) Synthesize emerging knowledge from Network Research Programme into management tactics that will facilitate the direct and indirect management of MPB in novel pine habitats.

 Within its historic range, MPB populations exhibit predictable eruptive dynamics that arise as a function of a distinct suite of trophic interactions associated with endemic and epidemic population phases. Endemic populations comprise too few beetles to overcome the defenses of a single large diameter, healthy tree, and are therefore confined to trees with impaired vigour/defenses. Epidemic populations are those that have exceeded the threshold density for successful attack of highly defensive mature trees. To date, all beetles detected in newly invaded pine habitats have exhibited epidemic behaviour as characterized by attempted mass attacks of large trees. Although it is generally accepted that similar biotic and abiotic factors occur within historic and newly invaded regions, it is unknown whether the specific suite of conditions for endemic beetles exists, and therefore whether beetles will persist in the long term, in novel pine habitats. Furthermore, evidence has begun to accumulate indicating altered interactions with host trees by epidemic beetles in novel pine habitats. The broad objective of this proposal component is to synthesize and extend research into the population genomics of MPB, its symbiotic organisms and the host tree to quantify the spatial and temporal dynamics of the beetle in novel habitats. We seek to answer the following questions:

  • Can MPB exist in the endemic phase in novel pine habitats, and if so, what density of beetles is required to transition to the epidemic phase?
  • How is dispersal/spread of epidemic MPB in novel habitats affected by (i) population state, (ii) invasion status, and (iii) host-tree conditions?

Answers to these questions will enable realization of the following specific objectives intended to facilitate management of MPB in novel habitats through development of a functional model of stand susceptibility and spread risk models. Four distinct but interconnected projects will address the questions/objectives outlined above. Given the interrelatedness of the projects, where feasible HQP will be shared and co-supervised by PIs, with other PIs included on supervisory committees, thereby providing students with an enhanced breadth of basic and applied research experience.

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