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Stand age is often hard to measure accurately. Measurement error in age affects height estimates when height is projected from one age to another age. In this study, our objective was to derive an estimator for the variance of the component of projection error associated with the error in age. To evaluate the estimator, a simulation approach was employed and the results showed that the estimator worked well in most cases. When the variance of the error in age increases and the projection is forward, however, the estimator might not work as well as in other cases. Another objective was to examine how the error in age behaved under different height-age models and to what extent it affected height and site index estimates. The effect of the error in age depended on its magnitude, the height-age model, initial value of dominant height and age, and projection length. It was also shown that the effect was sometimes negligible, but it could be considerable in other cases. Data from 80 ponderosa pine (Pinus ponderosa Dougl. ex Laws.) trees in British Columbia, Canada, were used in an illustrative example. L'age d'un peuplement est souvent difficile a mesurer precisement. Les erreurs de mesure de l'age influencent les estimations de la hauteur lorsque la hauteur est projet ee d'une valeur d'age a une autre. Dans cette etude, notre objectif etait de calculer un estimateur de la variance de la composante de l'erreur de projection associ ee a l'erreur sur l'age. Une approche de simulation a et e utilis ee pour evaluer cet estimateur et les r esultats montrent qu'il est ad equat dans la plupart des cas. Cependant, lorsque la variance de l'erreur sur l'age augmente et que la projection est vers l'avant, l'estimateur pourrait ne pas fonctionner aussi bien que dans les autres cas. Un autre objectif etait d' etudier le comportement de l'erreur sur l'age pour diff erents modeles reliant la hauteur a l'age et de d eterminer dans quelle mesure cette erreur influence les estimations de la hauteur et de l'indice de qualit e de station. L'effet de l'erreur sur l'age d ependait de son ampleur, du modele reliant la hauteur a l'age, des valeurs initiales de la hauteur dominante et de l'age, ainsi que de la p eriode de projection. Les r esultats ont aussi montr e que l'effet de l'age etait parfois n egligeable, mais qu'il pouvait etre consid erable dans d'autres cas. Les donn ees de 80 tiges de pin ponderosa (Pinus ponderosa Dougl. ex Laws.) de la Colombie-Britannique, au Canada, ont et e utilis ees comme exemple. [Traduit par la R edaction], Introduction Dominant height is an important explanatory variable in forest growth and yield modeling systems (e.g., Pienaar and Shiver 1986; Borders 1989; Lynch and Murphy 1995). Site index, often defined [...]

Insect outbreaks, such as the current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forests in British Columbia, are major disturbances in many forests. After an insect outbreak, the advance regeneration typically forms a new canopy, which may be adequate for timber objectives in some stands. Our purpose was to quantify and then model the abundance and spatial distribution of advance regeneration (trees Les epidemies d'insectes constituent une perturbation majeure dans beaucoup de forets, incluant l'epidemie actuelle du dendroctone du pin ponderosa dans les forets de pin tordu latifolie (Pinus contorta var. latifolia Engelm.) en Colombie-Britannique. La regeneration preetablie forme typiquement un nouveau couvert qui peut etre adequat pour satisfaire les objectifs de production de matiere ligneuse dans certains peuplements. Notre objectif consistait a quantifier puis a modeliser l'abondance et la distribution spatiale de la regeneration preetablie (arbres [Traduit par la Redaction], Introduction Many forests contain large numbers of small trees in the understory, which often fill small canopy gaps and can also form new stands following a major disturbance to the [...]

Abstract: Shade-tolerant trees that start in the understory but ultimately reach the canopy persist through different microhabitat conditions during their ontogeny. We evaluate how the height to diameter ratio and [...]

Growth response functions (GRFs) that relate the growth of a population to the climate of the sites in which it is tested are gaining attention for their ability to predict impacts of climate change on tree growth. However, nonclimatic site to site variation introduces error into GRFs. Using data from a large lodgepole pine (Pinus contorta Dougl. ex Loud.) provenance test in British Columbia and the Yukon, Canada, a technique is presented that accounts for the effect of nonclimatic variation in GRFs. The mean height of the 'local' provenances at each test site was used to predict 'site height' from site climate variables in multiple regression. Residuals from the site height equation provided an index of the nonclimatic effect for each site and were included as a covariate in quadratic GRFs that related provenance height at each test site to mean annual temperature at each test site. Inclusion of the nonclimatic index in the model resulted in a moderate or large displacement of GRFs for 25% of the provenances, while increasing mean [R.sup.2] values for 138 of 140 provenances and decreasing the root mean squared error for 113 of 140 provenances. These results suggest that inclusion of the nonclimatic index in GRF models could substantially affect height predictions for some provenances and reduce prediction error for most provenances. Les fonctions de reaction de la croissance (FRC) qui relient la croissance d'une population au climat des stations oh elles sont testees gagnent en popularity; a cause de leur capacity; a predire les impacts des changements climatiques sur la croissance des arbres. Cependant, les variations non climatiques entre les stations introduisent des erreurs dans les FRC. A partir des donnees d'un test de provenance de pin tordu latifolie (Pinus contorta Dougl. ex Loud.) de grande envergure en Colombie-Britannique et au Yukon, au Canada, nous presentons une technique qui tient compte de l'effet des variations non climatiques dans les FRC. La hauteur moyenne des provenances <> a chaque endroit oU le test a ete etabli a ete utilisee pour predire, a l'aide de la regression multiple, la <> a partir des variables climatiques de la station. Les residus de l'equation de la hauteur specifique a la station ont fourni un indice de l'effet non climatique dans chaque station et ont etes inclus comme covariable dans des FRC quadratiques qui reliaient la hauteur de la provenance dans chaque station a la temperature annuelle moyenne de la station. L'introduction de l'indice non climatique dans le modele a produit un dylplacement modere a grand des FRC chez 25 % des provenances, a augmente la valeur moyenne du [R.sup.2] de 138 des 140 provenances et a diminue l'erreur quadratique moyenne chez 113 des 140 provenances. Ces resultats indiquent que l'introduction de l'indice non climatique dans les modeles de FRC pourrait substantiellement affecter les predictions de hauteur pour quelques provenances et diminuer l'erreur de prediction pour la plupart des provenances. [Traduit par la Redaction], Introduction With climate change raising the spectre of significant changes to forest productivity due to altered adaptation, provenance tests have encountered a resurgence of interest, as modellers attempt to mitigate [...]

Byline: Gordon D. Nigh (1) Abstract: Future climate change is expected to have many impacts on forest ecosystems. It is important to have some understanding of these impacts in order to make informed forest management decisions. A major consideration in making forest management decisions is the productivity of a site, as measured by site index. In this study, I relate Douglas-fir site index to accumulated growing degree-days greater than [5.sup.deg]C (DD5), as well as to soil moisture and nutrient regime. This allows the impact of climate change on forest productivity to be estimated. A two step approach was followed. The first step derived models to estimate various climate variables to latitude, longitude, and elevation using data from climate stations. Then, these climate variables were used along with soil moisture and nutrient data to predict site index for the site index plots. A two step approach was taken because climatic data were not available for the site index plots. The trend was for site index to increase with both increasing soil moisture and nutrients, although the site index decreased on the wetter sites. Site index also increased with DD5 at the rate of 1.2 m for every increase of 100 units in DD5. These models can be used together to evaluate the impact of various climate change scenarios on site index. Author Affiliation: (1) Research Branch, BC Ministry of Forests, P.O. Box 9519, Stn. Prov. Govt., Victoria, British Columbia, V8W 9C2, Canada Article History: Registration Date: 13/12/2005 Accepted Date: 04/10/2005 Online Date: 25/04/2006

Future climate change is expected to have many impacts on forest ecosystems. It is important to have some understanding of these impacts in order to make informed forest management decisions. A major consideration in making forest management decisions is the productivity of a site, as measured by site index. In this study, I relate Douglas-fir site index to accumulated growing degree-days greater than 5[degrees]C (DD5), as well as to soil moisture and nutrient regime. This allows the impact of climate change on forest productivity to be estimated. A two step approach was followed. The first step derived models to estimate various climate variables to latitude, longitude, and elevation using data from climate stations. Then, these climate variables were used along with soil moisture and nutrient data to predict site index for the site index plots. A two step approach was taken because climatic data were not available for the site index plots. The trend was for site index to increase with both increasing soil moisture and nutrients, although the site index decreased on the wetter sites. Site index also increased with DD5 at the rate of 1.2 m for every increase of 100 units in DD5. These models can be used together to evaluate the impact of various climate change scenarios on site index.