Disturbances, both natural and anthropogenic, affect the configuration, composition, and function of forested ecosystems. Complex system behaviors emerge from the interactions between disturbance regimes, the vegetation response to those disturbances, and their interplay with multiple drivers (climate, topography, land use, etc.) across spatial and temporal scales. Here, we summarize conceptual advances and empirical approaches to disturbance interaction investigation, and used those insights to evaluate and categorize 146 landscape modeling studies emerging from a systematic review of the literature published since 2010. Recent conceptual advances include formal disaggregation of disturbances into their constituent components, embedding disturbance processes into system dynamics, and clarifying terminology for interaction factors, types, and ecosystem responses. Empirical studies investigating disturbance interactions now span a wide range of approaches, including (most recently) advanced statistical methods applied to an expanding set of spatial and temporal datasets. Concurrent development in spatially-explicit landscape models, informed by these empirical insights, integrate the interactions among natural and anthropogenic disturbances by coupling these processes to account for disturbance stochasticity, disturbance within and across scales, and non-linear landscape responses to climate change. Still, trade-offs between model elegance and complexity remain. We developed an index for the degree of process integration (i.e., balance of static vs. dynamic components) within a given disturbance agent and applied it to the studies from our systematic review. Contemporary model applications in this line of research have applied a wide range process integration, depending on the specific question, but also limited in part by data and knowledge. Non-linear “threshold” behavior and cross-scaled interactions remain a frontier in temperate, boreal, and alpine regions of North America and Europe, while even simplistic studies are lacking from other regions of the globe (e.g., subtropical and tropical biomes). Understanding and planning for uncertainty in system behavior—including disturbance interactions—is paramount at a time of accelerated anthropogenic change. While progress in landscape modeling studies in this area is evident, work remains to increase model transparency and confidence, especially for understudied regions and processes. Moving forward, a multi-dimensional approach is recommended to address the uncertainties of complex human-ecological dynamics.

A fundamental question in forest insect ecology is the role of forest landscape structure, particularly the amount and spatial configuration of host tree species, in shaping the dynamics of recurring forest insect outbreaks. For forest tent caterpillar (FTC), independent studies do not converge on a singular conclusion, although all indicate that forest structure influences outbreak dynamics. These studies also vary in how they treat climate as a covariate. We evaluated the relative importance of host forest landscape composition and configuration, as well as climate, for their influence on FTC outbreak cycling in the twentieth century. We predicted that FTC outbreaks would exhibit greater synchrony and intensity within areas associated with higher abundance of host trees. We reconstructed FTC outbreaks from 1928 to 2006 using tree‐ring analysis within a well‐structured experimental landscape located in northwestern Ontario and northern Minnesota. Time‐series clustering and spatial nonparametric covariance were used to determine whether similarities in time series and patterns in spatial synchrony corresponded with land management history. Using constrained ordination, we compared statistical properties of outbreak time series to landscape variables representing host abundance, forest configuration, and climate. We found no evidence of climatic effects at the scale of this study, but a significant albeit small influence of landscape structure on outbreak dynamics. Outbreaks were more synchronous and more cyclic within managed zones containing a greater relative abundance of aspen and other hardwood host tree species, compared with the more conifer‐dominated Wilderness area. Yet, we also observed asynchronous outbreak dynamics across the study area, such that correlations with slower‐changing forest landscape variables varied starkly among outbreak pulses. Consequently, the strength of relationship between landscape variables and FTC outbreak patterns varied strongly through time—a result that may explain why short‐term studies yield conclusions that are at odds with one another. Our results speak to the importance of long time series, contrasting landscape structure, use of multivariate methods, and controlling for climatic variation when investigating the effects of forest landscape structure on the cyclic‐eruptive spatial dynamics for forest defoliators.

We describe an individual-based model of spruce budworm moth migration founded on the premise that flight liftoff, altitude, and duration are constrained by the relationships between wing size, body weight, wingbeat frequency, and air temperature. We parameterized this model with observations from moths captured in traps or observed migrating under field conditions. We further documented the effects of prior defoliation on the size and weight (including fecundity) of migrating moths. Our simulations under idealized nocturnal conditions with a stable atmospheric boundary layer suggest that the ability of gravid female moths to migrate is conditional on the progression of egg-laying. The model also predicts that the altitude at which moths migrate varies with the temperature profile in the boundary layer and with time during the evening and night. Model results have implications for the degree to which long-distance dispersal by spruce budworm might influence population dynamics in locations distant from outbreak sources, including how atmospheric phenomena such as wind convergence might influence these processes. To simulate actual migration flights en masse, the proposed model will need to be linked to regional maps of insect populations, a phenology model, and weather model outputs of both large- and small-scale atmospheric conditions.