Moderate severity disturbances, those that do not result in stand replacement, play an essential role in ecosystem dynamics. Despite the prevalence of moderate severity disturbances and the significant impacts they impose on forest functioning, little is known about their effects on forest canopy structure and how these effects differ over time across a range of disturbance severities and disturbance types. Using longitudinal data from the National Ecological Observatory Network project, we assessed the effects of three moderate severity press disturbances (beech bark disease, hemlock woolly adelgid and emerald ash borer, which are characterized by continuous disturbance and sustained mortality) and three moderate severity pulse disturbances (spring cankerworm moth, spongy moth and ground fire, which are associated with discrete and relatively short mortalities) on temperate forest canopy structure in eastern US. We studied (1) how light detection and ranging (LiDAR)‐derived metrics of canopy structure change in response to disturbance and (2) whether initial canopy complexity offsets impact of disturbances on canopy structure over time. We used a mixed‐effects modelling framework which included a non‐linear term for time to represent changes in canopy structure caused by disturbance, and interactions between time and both disturbance intensity and initial canopy complexity. We discovered that high intensity of both press and pulse disturbances inhibited canopy height growth while low intensity pulse disturbances facilitated it. In addition, high intensity pulse disturbances facilitated increases in the complexity of the canopy over time. Concerning the impact of initial canopy complexity, we found that the initial canopy complexity of disturbed plots altered the effects of moderate disturbances, indicating potential resilience effects. Synthesis. This study used repeated measurements of LiDAR data to examine the effects of moderate disturbances on various dimensions of forest canopy structure, including height, openness, density and complexity. Our study indicates that both press and pulse disturbances can inhibit canopy height growth over time. However, while the impact of press disturbances on other dimensions of canopy structure could not be clearly detected, likely because of compensatory growth, the impact of pulse disturbances over time was more readily apparent using multi‐temporal LiDAR data. Furthermore, our findings suggest that canopy complexity might help to mitigate the impact of moderate disturbances on canopy structures over time. Overall, our research highlights the usefulness of multi‐temporal LiDAR data for assessing the structural changes in forest canopies caused by moderate severity disturbances.

Defoliators cause extensive damage in boreal and temperate forests of the world. Considerable effort has been invested to understand their individual population dynamics, and despite ample theorising, there is little empirical evidence on factors causing spatial synchrony of pest eruptions at landscape scales. We report on the landscape‐level effect of forest configuration and composition on the intensity of outbreaks of spruce budworm and forest tent caterpillar in a mixedwood boreal forest in northern Minnesota (USA) and adjacent Ontario (Canada), and how this is related to the degree of spatial synchrony in each species' outbreak cycling. Using a large spatiotemporal tree‐ring reconstruction of outbreak impacts across these two systems, we evaluate two contrasting theories governing defoliator outbreaks: harmonic oscillation (a.k.a. ‘clockwork’) and relaxation oscillation (a.k.a. ‘catastrophe’), each with consequences linked to top‐down versus bottom‐up influences on outbreak behaviour in time and space. We find synchrony varies temporally, among outbreak cycles and in direct proportion to cycle peak intensity; however, cycle peak intensities are distributed bimodally in time, and so, therefore, are synchrony coefficients. Spatially, the area where each pest species currently cycles with the greatest peak intensity and synchrony is where their preferred host trees are currently found in greatest proportion. Despite overall synchrony in cycling, we found, in both systems, a persistent negative spatial correlation among successive eruptive pulses of defoliation. Many of these eruptions failed to spread spatially and to coalesce with other spot eruptions to form extensive area‐wide outbreaks. Eruptions often fail to spread at the hardwood‐conifer interface, resulting in outbreak pulses that systematically bounce back and forth between landscape types, particularly when systems were cycling at low amplitude. These over‐dispersed spatial patterns of pulse impact are consistent with a contagious theory of eruption and outbreak spread. They could be considered consistent with harmonic oscillation theory only for populations cycling at different frequencies, with cycling frequency determined by host forest landscape structure. Synthesis. We find that defoliator outbreak dynamics across systems include spatiotemporal signatures of each theoretical paradigm—suggesting a hybrid approach will better characterise outbreak behaviour. Host concentration influences which paradigm dominates the spatial dynamics in any given forest landscape context. Because of the synchronising effect of host concentration on forest insect spatial dynamics, mixedwoods appear to be less prone to intense, synchronised defoliator attack than forests of pure hardwood or pure conifer.

Effective modelling of forest susceptibility to defoliating insect outbreaks requires a better understanding of outbreak dynamics, which includes detailed knowledge of the pre- and post-outbreak forest status as well as subsequent feedback mechanisms. In this paper, we strive to fill the forest status need by combining archived Landsat sensor data (pre- and post-outbreak) with different formats and dates of the U.S. Forest Service’s Forest Inventory and Analysis (FIA) data (periodic [1970s, 1990s] and annual [2003–2006]). Specifically, we explore the utility of these FIA ground data for calibrating models of forest species and type abundance for mapping past forest composition in the Border Lakes Ecoregion (BLE) of Upper Midwest of the US. Model calibration results between Landsat reflectance and FIA ground data for both total forest basal area and balsam fir (Abies balsamea) relative basal area, a preferred host of the spruce budworm (SBW, Choristoneura fumiferana), were poor to moderate (R²_adj 0.39 and 0.48, respectively). Results for aspen (Populous tremuloides) and spruce (Picea glauca and P. mariana) abundance yielded substantially better accuracies (R²_adj 0.64 and 0.78; RMSE 15.56 and 10.65 m² ha⁻¹, respectively). Groupings of tree species into broadleaved and conifers substantially improved model calibration result (R²_adj range: 0.72–0.91), except for the SBW host group (A. balsamea, P. glauca, and P. mariana). Periodic FIA ground data from the early 1990s generated stronger models compared to other FIA-Landsat date combinations tested. A paired t-test of abundance differences between undisturbed forest from the older 1977 and 1990 periodic inventories was significant (p-value < 0.0001), suggesting possible effects of variable FIA sampling protocol or ground plot positional accuracy through time. However, a similar paired t-test of abundance difference between periodic FIA (1990) and annual FIA (2003–2006) was not significant (p-value = 0.249). We posit four potential factors that may have contributed to weak Landsat-FIA calibration results for species abundance: 1) variation in FIA subplot arrangement and sampling protocols through time, 2) variability in species abundance and heterogeneity among FIA sampling across adjacent Landsat orbital paths, 3) understory species (balsam fir) that are largely hidden from remote detection, and 4) cloud cover and orbital phase mismatches preventing capture of key forest phenology aids. While past and present FIA sampling protocols were not specifically designed for integration with 30-meter satellite sensor data, careful pairing of FIA ground data (past or present) with Landsat sensor data can facilitate reasonable estimates, of forest abundance for generalized forest types, and possibly forest species when heterogeneity is low. Nevertheless, we recommend that FIA subplot sampling protocols be augmented to include measurements of forest conditions that are more amenable to integration with 30-meter Landsat sensor data.