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Canopy defoliation is an important source of disturbance in forest ecosystems that has rarely been represented in large-scale manipulation experiments. Scalable crown to canopy level experimental defoliation is needed to disentangle the effects of variable intensity, timing, and frequency on forest structure, function, and mortality. We present a novel pressurewashing-based defoliation method that can be implemented at the canopy-scale, throughout the canopy volume, targeted to individual leaves or trees, and completed within a timeframe of hours or days. Pressure washing proved successful at producing consistent leaf-level and whole-canopy defoliation, with 10%-20% reduction in leaf area index and consistent leaf surface area removal across branches and species. This method allows for stand-scale experimentation on defoliation disturbance in forested ecosystems and has the potential for broad application. Studies utilizing this standardized method could promote mechanistic understanding of defoliation effects on ecosystem structure and function and development of synthetic understanding across forest types, ecoregions, and defoliation sources. Key words: defoliation, experiment, herbivory, canopy, disturbance. La defoliation du couvert forestier est une source importante de perturbation dans les ecosystemes forestiers qui a rarement ete etudiee dans des experiences de manipulation a grande echelle. Une defoliation experimentale transposable de l'echelle de la cime a celle du couvert forestier est necessaire pour distinguer les effets de la variation de l'intensite, du moment et de la frequence sur la structure, la fonction et la mortalite de la foret. Nous presentons une nouvelle methode de defoliation fondee sur le lavage a la pression qui peut etre : appliquee a l'echelle du couvert forestier, a tout le volume du couvert forestier, appliquee a des arbres ou des feuilles individuellement et realisee a l'interieur d'une periode de quelques heures a quelques jours. Le lavage a la pression a reussi a produire une defoliation constante a l'echelle des feuilles et de l'ensemble du couvert forestier avec une reduction de 10-20 % de l'indice de surface foliaire et l'elimination d'une surface foliaire constante parmi les branches et les especes. Cette methode permet d'experimenter a l'echelle du peuplement avec les perturbations causees par une defoliation dans les ecosystemes forestiers et pourrait avoir un vaste champ d'application. Des etudes utilisant cette methode standardisee pourraient faciliter la comprehension mecaniste des effets de la defoliation sur les fonctions et la structure des ecosystemes ainsi que la comprehension synthetique des types forestiers, des ecoregions et des sources de defoliation. [Traduit par la Redaction] Mots-cles: defoliation, experimentation, broutage, couvert forestier, perturbation., 1. Introduction Large-scale experimental manipulations have been essential to advancing knowledge about ecosystem processes (e.g., Ainsworth and Long 2005; Templer et al. 2017). For example, experiments emulating variable disturbance severity, [...]

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]

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]

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatial scales ≤10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5-4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure. [ABSTRACT FROM AUTHOR]

Canopy structure affects forest function by determining light availability and distribution. Many forests throughout the upper Great Lakes region are dominated by mature, even-aged, early successional aspen and birch, which comprise 35%-40% of canopy leaf area, and which are senescing at accelerating rates. In 2008 at the University of Michigan Biological Station, we initiated the Forest Accelerated Succession Experiment (FASET) by stem girdling all aspen and birch in replicated stands to induce mortality. Our objective was to understand type and rate of canopy structural changes imposed by rapid but diffuse disturbance consisting of mortality of a single age-species cohort. We characterized changes in canopy structural features in 2008-2011 using ground-based Portable Canopy Lidar (PCL) in paired treated and control stands. As aspen and birch in treated plots died, gap fraction of the upper canopy increased, average leaf height decreased, total canopy height declined, and openness of the whole-canopy increased. All of these trends became more pronounced with time. Our findings suggest that as forests throughout the region pass through the impending successional transition prompted by widespread mortality of canopy-dominant early successional aspen and birch species, the canopy will undergo significant structural reorganization with consequences for forest carbon assimilation. [ABSTRACT FROM AUTHOR]

Abstract: Recent observations demonstrate that, against expectations, some forests maintain high carbon (C) storage rates for centuries, though the underlying mechanisms remain poorly understood. To test the hypothesis that age-related increases in canopy structural complexity improve resource-use efficiency and to evaluate canopy structural influences on forest C storage over successional timescales, we measured the fraction of photosynthetically active radiation absorbed by the canopy (fAPAR), foliar Nmass, and aboveground net primary production (ANPP) in a chronosequence of 39 passively managed stands spanning >160years of forest development in Northern Lower Michigan, USA. We used ground-based portable canopy LiDAR to quantify canopy structural complexity as rugosity, an integrated metric of 3D heterogeneity in canopy leaf area arrangement. Here, we describe a mechanism capable of maintaining high rates of ANPP over nearly two centuries of forest development. Results support our hypothesis that increasing canopy complexity over the course of forest development mediates greater resource-use efficiency in these forests. Forest stands with more structurally complex canopies had higher light and nitrogen use efficiencies (LUE & NUE) and higher ANPP. LAI was stable across stands older than 50years, while canopy complexity (rugosity) increased with age through >160years of stand development. Rugosity had a bigger influence on ANPP across all stands than did LAI, demonstrating the greater long-term influence of leaf area arrangement, rather than quantity within the canopy on forest C storage. We conclude that canopy structural complexity may facilitate greater resource use efficiency (RUE) in aging forests and so increase ANPP compared to structurally simpler canopies in young forests, thus maintaining significant C storage potential in aging forests. We suggest that forest managers should incorporate canopy structural complexity as a robust proxy of stand C storage potential in forests differing widely in age and disturbance history. [Copyright &y& Elsevier]

The even-aged northern hardwood forests of the Upper Great Lakes Region are undergoing an ecological transition during which structural and biotic complexity is increasing. Early-successional aspen (Populus spp.) and birch (Betula papyrifera) are senescing at an accelerating rate and are being replaced by middle-successional species including northern red oak (Quercus rubra), red maple (Acer rubrum), and white pine (Pinus sirobus). Canopy structural complexity may increase due to forest age, canopy disturbances, and changing species diversity. More structurally complex canopies may enhance carbon (C) sequestration in old forests. We hypothesize that these biotic and structural alterations will result in increased structural complexity of the maturing canopy with implications for forest C uptake. At the University of Michigan Biological Station (UMBS), we combined a decade of observations of net primary productivity (NPP), leaf area index (LAI), site index, canopy tree-species diversity, and stand age with canopy structure measurements made with portable canopy lidar (PCL) in 30 forested plots. We then evaluated the relative impact of stand characteristics on productivity through succession using data collected over a nine-year period. We found that effects of canopy structural complexity on wood NPP (NPPw) were similar in magnitude to the effects of total leaf area and site quality. Furthermore, our results suggest that the effect of stand age on NPPw is mediated primarily through its effect on canopy structural complexity. Stand-level diversity of canopy-tree. species was not significantly related to either canopy structure or NPPw. We conclude that increasing canopy structural complexity provides a mechanism for the potential maintenance of productivity in aging forests. [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]

Forest canopy structure (CS) controls many ecosystem functions and is highly variable across landscapes, but the magnitude and scale of this variation is not well understood. We used a portable canopy LiDAR system to characterize variation in five categories of CS along N = 3 transects (140–800 m long) at each of six forested landscapes within the eastern USA. The cumulative coefficient of variation was calculated for subsegments of each transect to determine the point of stability for individual CS metrics. We then quantified the scale at which CS is autocorrelated using Moran’s I in an Incremental Autocorrelation analysis. All CS metrics reached stable values within 300 m but varied substantially within and among forested landscapes. A stable point of 300 m for CS metrics corresponds with the spatial extent that many ecosystem functions are measured and modeled. Additionally, CS metrics were spatially autocorrelated at 40 to 88 m, suggesting that patch scale disturbance or environmental factors drive these patterns. Our study shows CS is heterogeneous across temperate forest landscapes at the scale of 10 s of meters, requiring a resolution of this size for upscaling CS with remote sensing to large spatial scales. [ABSTRACT FROM AUTHOR]