Forests around the world are experiencing increasingly severe droughts and elevated competitive intensity due to increased tree density. However, the influence of interactions between drought and competition on forest growth remains poorly understood. Using a unique dataset of stand‐scale dendrochronology sampled from 6405 trees, we quantified how annual growth of entire tree populations responds to drought and competition in eight, long‐term (multi‐decadal), experiments with replicated levels of density (e.g., competitive intensity) arrayed across a broad climatic and compositional gradient. Forest growth (cumulative individual tree growth within a stand) declined during drought, especially during more severe drought in drier climates. Forest growth declines were exacerbated by high density at all sites but one, particularly during periods of more severe drought. Surprisingly, the influence of forest density was persistent overall, but these density impacts were greater in the humid sites than in more arid sites. Significant density impacts occurred during periods of more extreme drought, and during warmer temperatures in the semi‐arid sites but during periods of cooler temperatures in the humid sites. Because competition has a consistent influence over growth response to drought, maintaining forests at lower density may enhance resilience to drought in all climates.

As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate prominent tree crowns from a canopy height model. We here introduce a novel segmentation method, layer stacking, which slices the entire forest point cloud at 1-m height intervals and isolates trees in each layer. Merging the results from all layers produces representative tree profiles. When compared to watershed delineation (a widely used segmentation algorithm), layer stacking correctly identified 15% more trees in uneven-aged conifer stands, 7%–17% more in even-aged conifer stands, 26% more in mixedwood stands, and 26%–30% more (with 75% of trees correctly detected) in pure deciduous stands. Overall, layer stacking's commission error was mostly similar to or better than that of watershed delineation. Layer stacking performed particularly well in deciduous, leaf-off conditions, even those where tree crowns were less prominent. We conclude that in the tested forest types, layer stacking represents an improvement in segmentation when compared to existing algorithms.

The Northern Research Station of the USDA Forest Service

Well-known patterns in the fundamental relationship between tree-level stemwood volume increment (VINC) and projected leaf area (PLA) are examined and quantified for Tsuga canadensis (L.) Carrière (eastern hemlock) and Picea rubens Sarg. (red spruce) growing in managed, mixed-species, multiaged stands in east-central Maine, U.S.A. Both species follow a sigmoid pattern, suggesting a peak growth efficiency (GE, stemwood volume growth per unit of PLA) in mid- to upper-canopy trees with PLAs of less than half that of the largest trees sampled. Tree age negatively influenced the VINC–PLA relationship in the expected manner: at a given PLA, older trees produce less stemwood than younger ones. The combined effect of leaf area and age is accurately modeled with a Weibull-like function in which the asymptote is an index of tree maturity defined as tree age relative to an estimated maximum for the species. Although previous studies have independently documented both the sigmoid relationship between VINC and PLA and the negative effect of age, their conclusions have been confounded by the strong correlation between age and mean tree PLA. This study addresses both issues simultaneously, and is the first to demonstrate a decline in GE with age independent from the effect of increasing PLA.

Developing strategies for reducing atmospheric CO₂ is one of the foremost challenges facing natural resource professionals today. The goal of this study was to evaluate total ecosystem and harvested wood product carbon (C) stocks among alternative forest management treatments (selection cutting, shelterwood cutting, commercial clearcutting, and no management) in mixed-species stands in central Maine, USA. These treatments were initiated in the 1950s and have been maintained since, and ecosystem C pools were measured in 2012. When compared across managed treatments, the commercial clearcut had the lowest total ecosystem C stocks by 21%, on average (P < 0.05), while the selection and shelterwood treatments had similar total ecosystem C stocks. Including the C stored in harvested wood products did not influence observed differences in C storage among treatments. Total ecosystem C stocks in the reference stand were 247.0 ± 17.7 Mg·ha⁻¹ (mean ± SD) compared with 161.7 ± 31.3 Mg·ha⁻¹ in the managed stands (171.2 ± 31.7 Mg·ha⁻¹ with products C). This study highlights the impacts of long-term forest management treatments on C storage and indicates that the timing of harvests and the species and sizes of trees removed influence C stored in harvested wood products.