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Structural diversity (SD) characterizes the volume and physical arrangement of biotic components in an ecosystem which control critical ecosystem functions and processes. LiDAR data provides detailed 3-D spatial position information of components and has been widely used to calculate SD. However, the intensive computation of SD metrics from extensive LiDAR datasets is time-consuming and challenging for researchers who lack access to high-performance computing resources. Moreover, a lack of understanding of LiDAR data and algorithms could lead to inconsistent SD metrics. Here, we developed a SD product using the Discrete-Return LiDAR Point Cloud from the NEON Aerial Observation Platform. This product provides SD metrics detailing height, density, openness, and complexity at a spatial resolution of 30 m, aligned to the Landsat grids, for 211 site-years for 45 Terrestrial NEON sites from 2013 to 2022. To accommodate various ecosystems with different understory heights, it includes three different cut-off heights (0.5 m, 2 m, and 5 m). This structural diversity product can enable various applications such as ecosystem productivity estimation and disturbance monitoring. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Trees respond to global change in myriad ways, many of which may be linked to adaptations relating to tree crown architecture. However, there is a paucity of theory capable of predicting the adaptive importance and dynamics of crown architecture, most likely because of the difficulties involved in measuring the three‐dimensional arrangement and orientation of tree leaves within individual crowns. Here, we describe a theory of tree crown economics, and use measurements from new lidar (light detection and ranging) instruments, UAVs (unoccupied aerial vehicles), and time‐lapse camera imagery to identify support for two predictions of the theory, that (1) a light competition versus water use economic trade‐off drives covariance among three tree crown functional traits (mean leaf angle, crown density, and crown rugosity), and (2) crown traits can drive spatial and temporal variability in near‐infrared spectral reflectance and related ecosystem functions. Tree crown economic theory can complement leaf economic theory in helping ecologists map and model forest ecosystem responses to global change. [ABSTRACT FROM AUTHOR]

Aim: Canopy structural complexity, which describes the degree of heterogeneity in vegetation density, is strongly tied to a number of ecosystem functions, but the community and structural characteristics that give rise to variation in complexity at site to subcontinental scales are poorly defined. We investigated how woody plant taxonomic and phylogenetic diversity, maximum canopy height, and leaf area index (LAI) relate to canopy rugosity, a measure of canopy structural complexity that is correlated with primary production, light capture, and resource‐use efficiency. Location: Our analysis used 122 plots distributed across 10 ecologically and climatically variable forests spanning a > 1,500 km latitudinal gradient within the National Ecological Observatory Network (NEON) of the USA. Time period: 2016–2018. Taxa studied: Woody plants. Methods: We used univariate and multivariate modelling to examine relationships between canopy rugosity, and community and structural characteristics hypothesized to drive site and subcontinental variation in complexity. Results: Spatial variation in canopy rugosity within sites and across the subcontinent was strongly and positively related to maximum canopy height (r2 =.87 subcontinent‐wide), with the addition of species richness in a multivariate model resolving another 2% of the variation across the subcontinent. Individually, woody plant species richness and phylogenetic diversity (r2 =.17 to.44, respectively) and LAI (r2 =.16) were weakly to moderately correlated with canopy rugosity at the subcontinental scale, and inconsistently explained spatial variation in canopy rugosity within sites. Main conclusions: We conclude that maximum canopy height is a substantially stronger predictor of complexity than diversity or LAI within and across forests of eastern North America, suggesting that canopy volume places a primary constraint on the development of structural complexity. Management and land‐use practices that encourage and sustain tall temperate forest canopies may support greater complexity and associated increases in ecosystem functioning. [ABSTRACT FROM AUTHOR]

The study of vegetation community and structural change has been central to ecology for over acentury, yet the ways in which disturbances reshape the physical structure of forest canopies remain relatively unknown. Moderate severity disturbances affect different canopy strata and plant species, resulting in variable structural outcomes and ecological consequences. Terrestrial lidar (light detection and ranging) offers an unprecedented view of the interior arrangement and distribution of canopy elements, permitting the derivation of multidimensional measures of canopy structure that describe several canopy structural traits (CSTs)with known links to ecosystem function. We used lidar-derived CSTs within a machine learning framework to detect and describe the structural changes that result from various disturbance agents, including moderate severity fire, ice storm damage, age-related senescence, hemlock woolly adelgid, beech bark disease, and chronic acidification. We found that fire and ice storms primarily affected the amount and position of vegetation within canopies, while acidification, senescence, pathogen, and insect infestation altered canopy arrangement and complexity. Only two of the six disturbance agents significantly reduced leaf area, counter to common assumptions regarding many moderate severity disturbances. While findings are limited in their generalizability due to lack of replication among disturbances, they do suggest that the current limitations of standard disturbance detection methods—such as optical-based remote sensing platforms, which are often above-canopy perspectives—limit our ability to understand the full ecological and structural impacts of disturbance, and to evaluate the consistency of structural patterns within and among disturbance agents. A more broadly inclusive definition of ecological disturbance that incorporates multiple aspects of canopy structural change may potentially improve the modeling, detection, and prediction of functional implications of moderate severity disturbance as well as broaden our understanding of the ecological impacts of disturbance. [ABSTRACT FROM AUTHOR]

Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest sub‐set of this spectrum, we assess gradients in canopy structural traits, characterise canopy structural types (CST) and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within‐ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub‐continental variation in forest types and eco‐climatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modelling structure–function relationships in vegetated ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: Terrestrial LiDAR (light detection and ranging) technologies have created new means of quantifying forest canopy structure, allowing not only the estimation of biomass, but also descriptions of the position and variability in canopy elements in space. Such measures provide novel structural information broadly useful to ecologists. There is a growing need for both a detailed taxonomy of forest canopy structural complexity (CSC) and open, transparent, and flexible tools to quantify complexity in ways that will advance foundational ecological knowledge of structure‐function relationships. The CSC taxonomy we present groups structural descriptors into five categories: leaf area and density, canopy height, canopy arrangement, canopy openness, and canopy variability. This paper also introduces the r package forestr, the first open‐source r package for the calculation of CSC metrics from terrestrial LiDAR data. The r package forestr is an analysis toolbox that works with portable canopy LiDAR (PCL) data and other pixelated/voxelized point clouds derived from terrestrial LiDAR scanning (TLS) data to calculate CSC metrics of interest to ecologists, modellers, forest managers, and remote sensing scientists. [ABSTRACT FROM AUTHOR]

Moderate severity disturbances, which only kill a subset of canopy trees (e.g., via insects, pathogens, and windthrow), are increasingly widespread in North America, and can alter forest structure and production. Whether the net primary production (NPP) of forest stands differing in pre-disturbance site quality and composition respond similarly to moderate severity disturbance, however, is unknown, but critical to understanding the disturbance response dynamics of patchy landscapes. We experimentally disturbed three, 2-ha stands varying in pre-disturbance primary production and community composition, temporarily reducing live stand basal area by 38% to 66% through the stem girdling of all mature early successional aspen (Populus tremuloides Michx. and Populus grandidentata Michx.) and birch (Betula papyrifera Marshall). Disturbance significantly altered stand-scale physical and biological structure and prompted a similar decade-long pattern of wood NPP decline and recovery. All stands exhibited an initial reduction in wood NPP, followed by a recovery period and eventual return to pre-disturbance levels within eight years, with the most productive stand exhibiting an increase in primary production following recovery. Following wood NPP recovery, more biologically diverse forest canopies with higher leaf area indexes intercepted more light, and, consequently, had higher rates of wood NPP.We conclude that, despite substantial pre-disturbance differences in productivity and community composition, relative wood NPP recovery patterns can be similar, though long-term post-recovery primary production may trend higher in more productive and compositionally diverse stands. We suggest that improved mechanistic understanding of different forest ecosystems' responses to disturbances remains critical to informing management decisions across diverse landscape mosaics. [ABSTRACT FROM AUTHOR]

The regrowing forests of eastern North America have been an important global C sink over the past 100+ years, but many are now transitioning into late succession. The consequences of this transition are unclear due to uncertainty around the C dynamics of oldgrowth forests. Canopy structural complexity (CSC) has been shown to be an important source of variability in C dynamics in younger forests (e.g., in productivity and resilience to disturbance), but its role in late-successional forests has not been widely addressed. We investigated patterns of CSC in two old-growth forest landscapes in the Upper Peninsula of Michigan, USA, to assess factors associated with CSC and its influence on productivity and disturbance resilience (to moderate-severity windstorm). CSC was quantified using a portable below-canopy LiDAR (PCL) system in 65 plots that also had long-term (50-70 + years) inventory data, which were used to quantify aboveground net primary productivity (ANPP), disturbance history, and stand characteristics. We found high and variable CSC relative to younger forests across a suite of PCL-derived metrics. Variation in CSC was driven by species composition and size structure, rather than disturbance history or site characteristics. Recent moderate severity wind disturbance decreased plot-scale CSC, but increased stand-scale variation in CSC. The strong positive correlation between CSC and productivity illustrated in younger forests was not present in undisturbed portions of these late-successional ecosystems. Moderate severity disturbance appeared to reestablish the positive link between CSC and productivity, but this relationship was scale and severity dependent. A positive CSCproductivity relationship was evident at the plot scale with low-severity, dispersed disturbance, but only at a patch scale in more severely disturbed areas. CSC does not appear to strongly correlate with variation in productivity in undisturbed old-growth forests, but may play a very important (and scale/severity-dependent) role in their response to disturbance. Understanding potential drivers and consequences of CSC in late-successional forests will inform management focused on promoting complexity and old-growth conditions, and illustrate potential impacts of such treatments on regional C dynamics. [ABSTRACT FROM AUTHOR]

Structural diversity is a key feature of forest ecosystems that influences ecosystem functions from local to macroscales. The ability to measure structural diversity in forests with varying ecological composition and management history can improve the understanding of linkages between forest structure and ecosystem functioning. Terrestrial LiDAR has often been used to provide a detailed characterization of structural diversity at local scales, but it is largely unknown whether these same structural features are detectable using aerial LiDAR data that are available across larger spatial scales. We used univariate and multivariate analyses to quantify cross-compatibility of structural diversity metrics from terrestrial versus aerial LiDAR in seven National Ecological Observatory Network sites across the eastern USA. We found strong univariate agreement between terrestrial and aerial LiDAR metrics of canopy height, openness, internal heterogeneity, and leaf area, but found marginal agreement between metrics that described heterogeneity of the outermost layer of the canopy. Terrestrial and aerial LiDAR both demonstrated the ability to distinguish forest sites from structural diversity metrics in multivariate space, but terrestrial LiDAR was able to resolve finer-scale detail within sites. Our findings indicated that aerial LiDAR could be of use in quantifying broad-scale variation in structural diversity across macroscales. [ABSTRACT FROM AUTHOR]

Globally, planted forests are rapidly replacing naturally regenerated stands but the implications for canopy structure, carbon (C) storage, and the linkages between the two are unclear. We investigated the successional dynamics, interlinkages and mechanistic relationships between wood net primary production (NPPw) and canopy structure in planted and naturally regenerated red pine (Pinus resinosa Sol. ex Aiton) stands spanning ≥ 45 years of development. We focused our canopy structural analysis on leaf area index (LAI) and a spatially integrative, terrestrial LiDAR-based complexity measure, canopy rugosity, which is positively correlated with NPPw in several naturally regenerated forests, but which has not been investigated in planted stands. We estimated stand NPPw using a dendrochronological approach and examined whether canopy rugosity relates to light absorption and light–use efficiency. We found that canopy rugosity increased similarly with age in planted and naturally regenerated stands, despite differences in other structural features including LAI and stem density. However, the relationship between canopy rugosity and NPPw was negative in planted and not significant in naturally regenerated stands, indicating structural complexity is not a globally positive driver of NPPw. Underlying the negative NPPw-canopy rugosity relationship in planted stands was a corresponding decline in light-use efficiency, which peaked in the youngest, densely stocked stand with high LAI and low structural complexity. Even with significant differences in the developmental trajectories of canopy structure, NPPw, and light use, planted and naturally regenerated stands stored similar amounts of C in wood over a 45-year period. We conclude that widespread increases in planted forests are likely to affect age-related patterns in canopy structure and NPPw, but planted and naturally regenerated forests may function as comparable long-term C sinks via different structural and mechanistic pathways. [ABSTRACT FROM AUTHOR]