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British Columbia experienced three years with notably large and severe wildfires since 2015. Multiple stand-replacing wildfires occurred in coastal-transitional forests, where large fires are typically rare, and thus, information on post-fire carbon is lacking. Because of their carbon storage potential, coastal-transitional forests are important in the global carbon cycle. We examined differences in surface fuel carbon among fire severity classes in 2016, one year after the Boulder Creek fire, which burned 6 735 ha of coastal-transitional forests in 2015. Using remotely sensed indices (dNBR), we partitioned the fire area into unburned (control), low-, moderate-, and high-severity classes. Field plots were randomly located in each class. At each plot, surface fuel carbon was quantified by type, namely coarse, small, and fine woody material, duff, and litter, and carbon mass by fuel type was compared among severity classes. Total surface fuel carbon did not differ significantly between burned and unburned plots; however, there was significantly less duff and litter carbon in burned plots. Remotely sensed severity classes did not properly capture wildfire impacts on surface fuels, especially at lower severities. Pre-fire stand characteristics are also important drivers of surface fuel loads. This case study provides baseline data for examining post-fire fuel carbon dynamics in coastal-transitional British Columbia. Key words: wildfire, forest carbon, fire severity, forest floor, surface fuels. Depuis 2015 la Colombie-Britannique a connu trois annees durant lesquelles sont survenus des feux de forets particulierement vastes et severes. De multiples feux de foret qui entrainent le renouvellement des peuplements sont survenus dans les forets transitionnelles cotieres oU de tels feux sont typiquement rares et oU l'information sur le carbone apres feu est par consequent inexistante. Etant donne leur capacite a emmagasiner le carbone, les forets transitionnelles cotieres sont importantes dans le cycle global du carbone. Nous avons etudie les differences dans la quantite de carbone contenu dans les combustibles de surface parmi les classes de severite du feu en 2016, un an apres le feu de Boulder Creek qui a brule 6735 ha de foret transitionnelle cotiere en 2015. A l'aide d'indices determines par teledetection (reflectance des zones brulees), nous avons decoupe la region touchee par le feu en fonction de la classe de severite du feu : nulle (temoin non brule), faible, moderee, elevee. Des places echantillons ont ete localisees au hasard sur le terrain dans les zones correspondant a chacune des classes de severite. Dans chaque place echantillon, le carbone des combustibles de surface a ete quantifie par type : materiel ligneux grossier, petit et fin, humus et litiere. La masse de carbone par type de combustibles a ete comparee parmi les classes de severite. La quantite totale de carbone dans les combustibles de surface n'etait pas significativement differente que les places echantillons aient ete brulees ou non. Cependant il y avait significativement moins de carbone dans l'humus et la litiere dans les places echantillons brulees. Les classes de severite determinee par teledetection ne refletaient pas adequatement les impacts des feux de foret sur les combustibles de surface, particulierement dans le cas des feux de faible severite. Les caracteristiques du peuplement avant feu sont egalement d'importants determinants des charges de combustibles de surface. Cette etude de cas fournit les donnees de base pour etudier la dynamique du carbone apres feu dans la zone transitionnelle cotiere en Colombie-Britannique. [Traduit par la Redaction] Mots-cles : feu de foret, carbone forestier, severite du feu, couverture morte, combustibles de surface., Introduction Wildfire is a common disturbance in many forest ecosystems, with historical fire regimes ranging from frequent surface fires that cause minimal overstory tree mortality to infrequent but intense stand-replacing [...]

Diameter distributions and tree-lists provide information about forest stocks disaggregated by size and species and are key for informing forest management. Diameter distributions and tree-lists are multivariate responses, which makes the evaluation of methods for their prediction reliant on the use of dissimilarity metrics to summarize differences between observations and predictions. We compared four strategies for selection of k nearest neighbors (k-NN) methods to predict diameter distributions and tree-lists using LiDAR and stand-level auxiliary data and analyzed the effect of the k-NN distance and number of neighbors in the performance of the predictions. Strategies differed by the dissimilarity metric used to search for optimal k-NN configurations and the presence or absence of post-stratification. We also analyzed how alternative k-NN configurations ranked when tree-lists were aggregated using different DBH classes and species groupings. For all dissimilarity metrics, k-NN configurations using random-forest distance and three or more neighbors provided the best results. Rankings of k-NN configurations based on different dissimilarity metrics were relatively insensitive to changes on the width of the DBH classes and the definition of the species groups. The selection of the k-NN methods was clearly dependent on the choice of the dissimilarity metric. Further research is needed to find suitable ways to define dissimilarity metrics that reflect how forest managers evaluate differences between predicted and observed tree-lists and diameter distributions. Key words: tree-lists, diameter distributions, k-NN, Reynolds index, LiDAR. Les distributions de diametre et les listes d'arbres fournissent des informations sur les stocks forestiers, ventilees par taille et par espece, et sont des informations de gestion forestiere essentielles. Les distributions de diametre et les listes d'arbres sont influencees par plusieurs variables, par consequent l'evaluation des methodes servant a les predire depend de l'utilisation de mesures de dissimilarite pour exprimer les differences entre les observations et leurs predictions. Nous avons compare quatre strategies de selection des k plus proches voisins (k-NN) pour predire les distributions de diametre et les listes d'arbres a l'aide de donnees auxiliaires LiDAR et de peuplement. Nous avons egalement analyse les effets de la distance k-NN et du nombre de voisins sur la qualite des predictions. Les strategies differaient par la mesure de dissimilarite utilisee pour obtenir les configurations k-NN optimales et par l'utilisation, ou non, de la post-stratification. Nous avons egalement analyse le classement des differentes configurations de k-NN lorsque les listes d'arbres etaient agregees selon differentes classes de diametre et groupes d'especes. Pour toutes les mesures de dissimilarite, les configurations k-NN utilisant une distance fondee sur les forets d'arbres decisionnels et trois voisins ou plus ont donne les meilleurs resultats. Les classements des configurations k-NN fondees sur differentes mesures de dissimilarite etaient relativement insensibles aux modifications de : l'etendue des classes de diametre et la definition des groupes d'especes. Le choix des methodes k-NN dependait clairement du choix de la mesure de dissimilarite. Des recherches supplementaires sont necessaires pour trouver des moyens appropries de definir des mesures de dissimilarite qui refletent l'evaluation que font les amenagistes forestiers des differences entre les listes d'arbres et les distributions de diametre predites et observees. [Traduit par la Redaction] Mots-cles: liste d'arbres, distribution de diametre, k-NN, indice de Reynolds, LiDAR., 1. Introduction To make informed decisions, forest managers require information about the current state of the forest. Knowledge of the total stand volume or basal area is not enough for [...]

We examined the dynamics of aboveground forest woody carbon pools--live trees, standing dead trees, and down wood--during the first 6 years following wildfire across a wide range of conditions, which are characteristic of California forest fires. From repeated measurements of the same plots, we estimated change in woody carbon pools as a function of crown fire severity as indicated by a post-fire index, years since fire, pre-fire woody carbon, forest type group (hardwood vs. softwood), elevation, and climate attributes. Our analysis relied on 130 U.S. national forest inventory plots measured before and 1 year after fire, with one additional remeasurement within 6 years after fire. There was no evidence of net change in total wood carbon, defined for this study as the wood in standing trees larger than 12.7 cm diameter at breast height and down wood larger than 7.6 cm in diameter, over the post-fire period in any of the three severity classes. Stands that burned at low severity exhibited considerable shifts from live to standing dead and down wood pools. In stands that burned at moderate severity, live wood decreased significantly whereas no net change was detected in standing dead or down wood. High severity fire burning resulted in movement from standing dead to down wood pools. Our results suggest that the carbon trajectories for stand-replacing fires may not be appropriate for the majority of California's forest area that burned at low to moderate severities. Key words: longitudinal analysis, post-fire dynamics, forest stand recovery, disturbance, Forest Inventory and Analysis. Nous avons etudie la dynamique des reservoirs de carbone ligneux de la partie aerienne des forets (les arbres vivants, les arbres morts sur pied et au sol) au cours des six premieres annees apres un feu pour une large gamme de conditions caracteristiques des feux de foret de la Californie. A partir de mesures repetees des memes placettes, nous avons estime les changements dans les reservoirs de carbone ligneux en fonction de la severite des dommages a la cime des arbres selon un indice apres feu, du nombre d'annees apres le feu, du carbone ligneux avant le feu, du groupe de types forestiers (feuillus ou resineux), de l'altitude et des caracteristiques du climat. Nos analyses ont porte sur 130 placettes de l'inventaire national etats-unien (FIA) mesurees avant et un an apres le feu de meme qu'une autre fois au cours des six premieres annees apres le feu. Il n'y a pas eu d'indices de changement net du carbone ligneux total apres feu, correspondant dans cette etude au bois des arbres sur pied ayant un diametre a hauteur de poitrine plus grand que 12,7 cm et des arbres au sol ayant un diametre superieur a 7,6 cm, dans aucune des trois classes de severite du feu. Les peuplements ayant subi un feu de severite faible ont connu des changements considerables dans les reservoirs de carbone ligneux, passant d'une dominance d'arbres vivants a une dominance d'arbres morts sur pied et au sol. Dans les peuplements brules par un feu de severite moderee, les arbres vivants ont diminue significativement alors qu'aucun changement net n'a ete detecte chez les arbres morts sur pied ou au sol. Le feu de severite elevee a provoque un deplacement de reservoir ligneux des arbres morts sur pied vers les arbres au sol. Nos resultats indiquent que les trajectoires de carbone typiques des feux qui entrainent le remplacement des peuplements peuvent ne pas etre appropriees pour les cas plus communs de peuplements subissant des feux d'intensites faible a moderee. [Traduit par la Redaction] Mots-cles: analyse longitudinale, dynamique apres feu, retablissement des peuplements forestiers, perturbation, programme d'analyse et d'inventaire forestiers (FIA)., Introduction Natural disturbances such as wildfire are increasing in frequency, severity, and extent across forested ecosystems of the western U.S. (Westerling et al. 2006; Miller et al. 2009; Stephens 2005; [...]

The quantity and characteristics of coarse woody debris (CWD) were examined in four distinct pine ecosystems of north-western (NW) Spain, NW Russia and the NW USA. The average CWD volume and biomass ranged from 3.76 m3 ha-1, 1.55 Mg ha-1 in pine plantations in NW Spain to 24.86 m3 ha-1, 6.69 Mg ha-1 in Scots pine forest in NW Russia to 55.35 m3 ha-1, 20.38 Mg ha-1 and 77.04 m3 ha-1, 28.84 Mg ha-1 in ponderosa and lodgepole pine forests in the NW USA. Despite differences in species, ecological conditions and management histories, in all four ecosystems the mean snag volume was less than that of logs, most of the CWD mass was in an intermediate degree of decay, and mature stands had the greatest amount of CWD mass, followed by middle-age and then young stands. The CWD ratio (ratio of dead to live wood volume) ranged from 2.8% to 126.6%, depending on pine ecosystem and stand age, and was influenced by the type of natural and human disturbance. The difference in CWD amount and distribution among the regions studied reflected differences in disturbance history and management practices. Only in NW USA was the sample size large enough to examine the effect of disturbance type on CWD amount and distribution. There, fire and insect damage were found to considerably influence the amount of CWD in both lodgepole and ponderosa pine forests. Comparison of how different factors affect the amount and distribution of CWD in different ecosystems could be useful in developing ecologically sustainable forest management guidelines.

One of the challenges often faced in forestry is the estimation of forest attributes for smaller areas of interest within a larger population. Small-area estimation (SAE) is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and auxiliary information is available. Selected SAE methods were compared for estimating a variety of forest attributes for small areas using ground data and light detection and ranging (LiDAR) derived auxiliary information. The small areas of interest consisted of delineated stands within a larger forested population. Four different estimation methods were compared for predicting forest density (number of trees/ha), quadratic mean diameter (cm), basal area ([m.sup.2]/ha), top height (m), and cubic stem volume ([m.sup.3]/ha). The precision and bias of the estimation methods (synthetic prediction (SP), multiple linear regression based composite prediction (CP), empirical best linear unbiased prediction (EBLUP) via Fay-Herriot models, and most similar neighbor (MSN) imputation) are documented. For the indirect estimators, MSN was superior to SP in terms of both precision and bias for all attributes. For the composite estimators, EBLUP was generally superior to direct estimation (DE) and CP, with the exception of forest density. Un des defis souvent rencontres en foresterie est l'estimation des attributs forestiers pour de plus petites zones d'interet au sein d'une population plus large qu'est la foret. Les methodes d'estimation pour petites zones sont des techniques bien adaptees a l'estimation d'attributs forestiers sur de petites superficies pour lesquelles la taille de l'echantillon existant est faible et l'information auxiliaire est disponible. Quatre methodes d'estimation pour petites zones ont ete selectionnees et comparees pour estimer une variete d'attributs forestiers sur de petites superficies a l'aide de donnees terrain et de donnees auxiliaires derivees du lidar. Les deux premieres methodes etaient indirectes (la prediction synthetique (PS) et l'imputation par les plus proches voisins (PPV)); les deux autres etaient composites (la meilleure prediction empirique lineaire sans biais (PSB) basee sur les modeles de Fay-Herriot et la prediction composite basee sur la regression lineaire multiple (PC)). Les petites superficies d'interet etaient representees par les peuplements delimites dans une foret. Les attributs forestiers qui ont ete compares etaient la densite de la foret (nombre de tiges/ha), le diametre moyen quadratique (cm), la surface terriere ([m.sup.2]/ha), la hauteur maximale (m) et le volume des tiges ([m.sup.3]/ha). La precision et le biais des quatre methodes d'estimation sont documentes. Dans le cas des estimateurs indirects, l'imputation par les PPV etait superieure a la PS en termes de precision et de biais pour tous les attributs. Dans le cas des estimateurs composites, la PSB etait generalement superieure a l'estimation direct et la PC, excepte pour la densite de la foret. [Traduit par la Redaction], Introduction Generally, estimates of forest attributes for areas of interest have been derived by using ground data extracted from plots taken within the area. For forest management and planning purposes, [...]

In forest inventory, it is not enough to formulate a definition; it is also necessary to define the 'measurement procedure.' In the classification of forestland by dominant cover type, the measurement design (the plot) can affect the outcome of the classification. We present results of a simulation study comparing classification of the dominant cover type between fixed- and variable-radius plot designs. We also show the effect of species distribution and partially sampled plots on these classifications. Plot type, area sampled, and the way in which the species are distributed influence the outcome of the classification. Thus, estimated changes in forest area may be an artifact of plot design changes, rather than actual population change. Resume: En inventaire forestier, il ne suffit pas de formuler une definition; il faut egalement definir la procedure de mesure. Dans la classification des forets par type de couvert dominant, le dispositif de mesure (la placette) peut influencer le resultat de la classification. Nous presentons les resultats d'une etude de simulation qui compare la classification du type de couvert dominant selon qu'on utilise des placettes a rayon fixe ou a rayon variable. Nous montrons aussi l'effet de la repartition des especes et celui des placettes partiellement echantillonnees sur ces classifications. Le type de placette, la zone echantillonnee et la facon dont les especes sont reparties influencent le resultat de la classification. Ainsi, les changements estimes dans la zone forestiere peuvent etre un artefact cause par des changements dans le dispositif de placettes, plutot qu'un changement reel de la population. [Traduit par la Redaction], Introduction Estimation of forest attributes such as volume, number of trees, and area are mainstays of forest inventories. Classification of forest area into dominant species type (often referred to as [...]

Subsampling and subsequent imputation of tree heights can improve the predictive performance of stand volume estimation but may also introduce biases. Using coastal Douglas-fir data from southwest Oregon, USA, the predictive performance of several height imputation strategies for estimating stand volume was evaluated. A subsample of 1-15 trees was randomly selected per stand, and missing heights were imputed using a regional Chapman-Richards function with diameter only and diameter plus stand density measures, fitted using a nonlinear least-squares model (NFEM) and a nonlinear mixed-effects model (NMEM). Missing heights were imputed using the regional height-diameter equation and by adjusting the equation with a correction factor (NFEM) or with predicted random effects (NMEM) to calibrate the height-diameter relationship to each stand. Differences in actual stand volumes, calculated with measured heights, and predicted stand volumes, calculated using measured heights for the subsampled trees and predicted heights for those with missing heights, were used to compare the alternative height imputation methods. Precision and bias were poorest for the regional models, especially NMEM, and best for the adjusted models also using NMEM. Results suggest that a similar subsample of heights (n = 4) is required for precise stand volume estimation as has been reported for height. Le sons-echantillonnage et l'imputation subsequente de la hauteur des arbres pent ameliorer la performance previsionnelle de l'estimation du volume d'un peuplement, mais pent aussi introduire des biais. A l'aide de donnees sur le douglas de Menzies du sud-ouest de l'Oregon (Etats-Unis), nous avons evalue la performance previsionnelle de plusieurs strategies d'imputation de la hauteur pour estimer le volume des peuplements. Un sons-echantillon de un a 15 arbres a ete selectionne aleatoirement pour chaque peuplement et les hauteurs manquantes ont ete imputees en utilisant une fonction regionale de Chapman-Richards basee soit sur des mesures de diametre seules soit sur des mesures de diametre et de density du peuplement. Cette fonction a ete ajustee a l'aide des moindres carres non lineaires (NFEM) et d'effets mixtes non lineaires (NMEM). Les hauteurs manquantes ont ete imputees en utilisant 1'equation regionale hauteur-diametre qui a ete ajustee avec un facteur de correction (NFEM) on avec des effets aleatoires de prevision (NMEM) pour etalonner la relation hauteur-diametre de chaque peuplement. Pour comparer ces methodes d'imputation de la hauteur, nous avons utilise les Diffrences de volume de peuplement entre les valeurs reelles, calculees a partir des hauteurs mesurees, et les valeurs predites, calculees a partir des hauteurs mesurees du sons-echantillon d'arbres et des hauteurs predites pour les arbres dont la hauteur etait manquante. Les moins bonnes valeurs de precision et de biais ont ete obtenues avec les modeles regionaux, particulierement NMEM, alors que les meilleures valeurs ont ete obtenues avec les modeles qui utilisaient aussi NMEM. Les resultats indiquent qu'un sons-echantillon similaire de hauteur (n = 4) est requis pour une estimation precise du volume d'un peuplement comme il a deja ete rapporte pour la hauteur. [Traduit par la Redaction], Introduction Imputation of values for selected tree- and stand-level attributes is a necessary component of forest inventory. The estimation of tree and stand volumes generally requires an estimate of tree [...]

A Bayesian probabilistic modeling platform was used and evaluated for application in a relatively complex individual-tree growth and yield model for coastal Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco), which was expressed as a mixed discrete and continuous Bayesian Network for annual projections. The modeling platform used a common and open-source Bayesian analysis program (JAGS v3.3.0), and was sufficiently exible to handle a relatively complex model structure; namely, a differential form, highly dynamic, recursive, hierarchical, non-linear system of equations with rather complex error structures. This novel probabilistic modeling platform met certain desirable criteria, including: (1) accurate and tractable projections that included full error propagation; (2) exible and comprehensive analytic capabilities; (3) full consideration of hierarchical and multi-level model structures; (4) capacity for random effects calibration; (5) allowance of hypothesis testing and updating knowledge across different system components, simultaneously with varying sources of information (i.e., new data); (6) computational efficiency; and (7) relatively simple implementation as demonstrated in a compiled scripting language. Probabilistic projections of forest growth and yield included all sources of errors and uncertainty (e.g., estimated parameters, state variables, random effects, and residual errors). Cumulative error projections over a 40-year period for three sample Douglas-fir stands were determined. Projection errors for key metrics summed across all trees, such as total basal area and stem density, had coefficient of variations between 4-6% and 7-8%, respectively. Probabilistic projections were markedly different from deterministic projections made with the same model structure. Overall, this novel probabilistic platform showed strong promise as a general platform for ecological modeling, particularly when tractable and analytically correct error projections are required. In particular, the Bayesian probabilistic modeling approach used provided a natural platform for cross-disciplinary research, particularly between social and ecological research domains. [ABSTRACT FROM AUTHOR]

The effects of prescribed underburning on soil total C pools, total and inorganic N pools, and in situ net N mineralization were examinedduring a 1-year study in ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.) sites that had been experimentally burned 4 months, 5 years, or 12 years earlier. At the sites burned 4 months previously, total C concentration and inorganic N concentration increased significantly (p< 0.1) after prescribed burning, compared with unburned controls. However, inorganic N concentration declined during the 1-year duration of this study to reach the levels of the control plots at the end of the second growing season. At the site burned 5 years previously, total C and N concentrations, inorganic N concentration, and net N mineralization decreased significantly after prescribed burning. Atthe sites burned 12 years previously, N and C pools were not affected, but net N mineralization decreased significantly after burning. The decrease in net N mineralization is likely caused by a decrease in substrate quantity 5 years after burning, and by changes in substratequality 12 years after burning. A long-term decrease in net N mineralization in the N-poor ponderosa pine stands of central Oregon may result in a decrease in long-term site productivity and may explain theobserved pattern of long-term decrease in stand growth after prescribed burning. [ABSTRACT FROM AUTHOR]