Light Detection and Ranging (LiDAR) has demonstrated potential for forest inventory at the individual tree-level. The aim in this study was to predict individual tree height (Ht; m), basal area (BA; m 2 ) and stem volume (V; m 3 ) attributes using Random Forest k-nearest neighbor (RF k-NN) imputation and individual tree-level based metrics extracted from a LiDAR-derived canopy height model (CHM) in a longleaf pine (Pinus palustris Mill.) forest in southwestern Georgia, USA. We developed a new framework for modeling tree-level forest attributes that was comprised of three steps: (1) individual tree detection, crown delineation and tree-level based metrics computation from LiDAR-derived CHM; (2) automatic matching of LiDAR-derived trees and field-based trees for a regression modeling step using a novel algorithm; and (3) RF k-NN imputation modeling for estimating tree-level Ht, BA, and V, and subsequent summarization of these metrics at the plot-and stand-levels. RMSDs for tree-level Ht, BA and V were 2.96%, 58.62% and 8.19%, respectively. Although BA estimation accuracy was poor because of the longleaf pine growth habit, individual tree locations, Ht, and V were estimated with high accuracy, especially in low canopy cover conditions. Future efforts based on the findings could help to improve the estimation accuracy of individual tree-level attributes like BA. RésuméLe lidar a démontré son potentiel pour l'inventaire forestier à l'échelle de l'arbre. Le but de cette étude était de prédire la hauteur individuelle des arbres (Ht; m), la surface terrière (BA; m 2 ) et le volume des tiges (V; m 3 ) en utilisant une imputation basée sur la méthode des forêts aléatoires et des k plus proches voisins (RF k-NN; Random Forest k-nearest neighbor) et de mesures à l'échelle de l'arbre extraites à partir d'un modèle de la hauteur de la canopée (MHC) Downloaded by [Boston University] at 03:50 29 June 2016 ACCEPTED MANUSCRIPT ACCEPTED MANUSCRIPT 3 dérivés du lidar dans une forêt de pins des marais (Pinus palustris Mill.) dans le sud-ouest de laGéorgie, aux États-Unis. Nous avons développé un nouveau cadre pour la modélisation des attributs forestiers à l'échelle de l'arbre composé de trois étapes : 1. la détection des arbres individuels, la délimitation des couronnes et le calcul de paramètres à l'échelle de l'arbre à partir de modèles MHC obtenus à partir du lidar; 2. la mise en correspondance automatique entre les arbres obtenus à partir du lidar et les arbres observés sur le terrain pour une étape de modélisation de régression en utilisant un nouvel algorithme; et 3. l'imputation par modélisation en utilisant RF k-NN pour estimer la Ht, la BA et le V à l'échelle de l'arbre et la synthèse ultérieure de ces mesures à l'échelle de la parcelle et du peuplement. Les REQM pour la Ht, la BA et le V à l'échelle de l'arbre étaient de 2,96 %, 58,62 % et 8,19 %, respectivement. Bien que la précision de l'estimation de la BA fût faible en raison du port et du mode de croissance des pins des marais, l'emplacement des arbres individuels, la...

A trenching study was used to investigate above- and below-ground competition in a longleaf pine ( Pinus palustris P. Mill.) woodland. Trenched and nontrenched plots were replicated in the woodland matrix, at gap edges, and in gap centers representing a range of overstory stocking. One-half of each plot received a herbicide treatment to remove the understory. We monitored pine survival and growth, understory productivity, light level (gap fraction), and soil resources. The overstory facilitated pine seedling survival. Pine seedling growth was reduced as overstory stocking increased. Reduced growth of seedlings was also observed in gaps when the understory was left intact. Understory plants competed with seedlings by filling the root gaps that developed as a result of overstory disturbance. Hardwood growth increased in gaps, owing to decreased belowground competition with adult pines, while growth of herbaceous plants and pine seedlings increased with light availability. Large overstory gaps are not required to initiate regeneration in longleaf pine woodlands. Retaining overstory dispersed throughout the stand but variable in density, through single-tree selection approaches, may be an alternative to gap-based approaches. This approach would allow for the fuel continuity needed to sustain the frequent fire required to maintain the diversity characteristic of this type of woodland.

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The dead foliage of scorched crowns is one of the most conspicuous signatures of wildland fires.Globally, crown scorch from fires in savannas, woodlands, and forests causes tree stress and death across diverse taxa. The term crown scorch, however, is inconsistently and ambiguously defined in the literature, causing confusion and conflicting interpretation of results. Furthermore, the underlying mechanisms causing foliage death from fire are poorly understood. The consequences of crown scorch-alterations in physiological, biogeochemical, and ecological processes and ecosystem recovery pathways-remain largely unexamined. Most research on the topic assumes the mechanism of leaf and bud death is exposure to lethal air temperatures, with few direct measurements of lethal heating thresholds. Notable information gaps include how energy transfer injures and kills leaves and buds, how nutrients, carbohydrates, and hormones respond, and what physiological consequences lead to mortality. We clarify definitions to encourage use of unified terminology for foliage and bud necrosis resulting from fire. We review the current understanding of the physical mechanisms driving foliar injury, discuss the physiological responses, and explore novel ecological consequences of crown injury from fire. From these elements, we propose research needs for the increasingly interdisciplinary study of fire effects.