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I outline the "definitional problem" in forest insect outbreak analytics and show how it is related to the "counting problem" in dendroentomology and the "forecasting problem" in forest insect population dynamics, through the ubiquitous presence of non-stationary complex periodicity. Using real-world examples from the spruce budworm (Choristoneura fumiferana Clem.) system, I show that regardless how outbreak patterning is characterized—whether by peak impact, cycle frequency, interval duration, or interval severity—the distribution in pattern attributes appears to be extremely variable, regardless how the data are processed through definitional filters. I show that this extreme variability is an unavoidable and key feature of the system's dynamics and argue that it needs to be viewed as an object of study, instead of a nuisance problem to be swept under the rug. The single biggest opportunity for rapid gains in spruce budworm predictive ecology is determining the environmental and ecological factors that separate high-intensity from low-intensity outbreak cycling. [ABSTRACT FROM AUTHOR]

Since the mountain pine beetle (MPB) breached the Rocky Mountains and first appeared in the province of Alberta, Canada, in alarming numbers in the summer of 2005, it has spread eastward across Alberta at an average rate of 80 km/year. In the absence of aggressive control, the beetle will undoubtedly continue to spread eastward. The spread rate is expected to slow as the leading edge invasion front moves further from significant population sources in the dense pine of the Rocky Mountain foothills into the scattered pine of the boreal plains region. However, the realized rate of spread is uncertain, as it will be regulated by a number of factors, some of which are uncertain (e.g. how an insect behaves in a novel environment), inherently unpredictable (e.g. weather), or under human control (e.g. spread control efforts). Whereas previous studies have examined factors affecting spread individually, we present a synthetic framework that models future spread rates as a function of coupled nonlinear recruitment dynamics that arise from the distinct population phases of MPB, and correlated thermal response functions that are characteristic of the influence of climate and climate change on ecosystem processes. We analyzed the model’s behavior under two climatic driving scenarios (drying climate and warming climate) and one forest health scenario (an increase in the ratio of stressed to vigorous trees), with the hypothesis that these scenarios would produce unanticipated outcomes in the severity and timing of beetle outbreaks. Our results showed a classic “tipping-point” model capable of generating sudden, unanticipated behavior, demonstrating that MPB populations may respond very strongly to small changes in climate. The MPB may be the first of many systems to behave in unprecedented ways. The model makes clear that the eastward rate of spread will depend on whether, when, and where the system transitions from the current epidemic state to a new endemic state. However, major uncertainties in the system limit our ability to make robust predictions of spread under natural conditions. The integrating framework presented here provides insight into scientific uncertainties worth targeting for applied research into spread management. In the absence of ability to predict beetle spread, forest management should continue to explore ways of coping with unpredictable disturbances, including adaptive capacity to adjust to transformational ecosystem changes expected under climate change. [ABSTRACT FROM AUTHOR]

The spruce budworm, Choristoneura fumiferana, Clem., is the most significant defoliating pest of boreal balsam fir (Abies balsamea (L.) Mill.) and spruce (Picea sp.) in North America. Historically, spruce budworm outbreaks have been managed via a reactive, foliage protection approach focused on keeping trees alive rather than stopping the outbreak. However, recent theoretical and technical advances have renewed interest in proactive population control to reduce outbreak spread and magnitude, i.e., the Early Intervention Strategy (EIS). In essence, EIS is an area-wide management program premised on detecting and controlling rising spruce budworm populations (hotspots) along the leading edge of an outbreak. In this article, we lay out the conceptual framework for EIS, including all of the core components needed for such a program to be viable. We outline the competing hypotheses of spruce budworm population dynamics and discuss their implications for how we manage outbreaks. We also discuss the practical needs for such a program to be successful (e.g., hotspot monitoring, population control, and cost–benefit analyses), as well as the importance of proactive communications with stakeholders. [ABSTRACT FROM AUTHOR]