<p> This study assessed biomass and carbon (C) allocation in a chronosequence of four White pine (Pinus strobus L.) plantation forests planted in 2002 (WPP02), 1989 (WPP89), 1974 (WPP74), and in 1939 (WPP39), in southern Ontario, Canada. A plotbased inventory and destructive tree sampling were conducted in 2004 to assess allocation of oiomass and C in ecosystem components, as well as allometry of tree biomass. Seasonal and annual patterns of litter and branch fall were also determined.</p> <p>Individual tree biomass components as well as sapwood area have strong site specific allometric relationships with tree diameter. Except for foliage biomass, strong single allometric equations could also be obtained across all sites and stand ages. Whereas allometry of individual tree components may be affected by site conditions and stand age, total tree biomass solely depended on tree diameter. This suggests that total biomass of White pine may be predicted from single allometric equations with DBH as input variable across sites and even across regions.</p> <p>Relative partitioning of tree biomass components was strongly related to tree age. Stem biomass gains major importance with increasing tree age at the cost of all other components comprising 69% of total tree biomass after 65 years. Whereas site conditions influenced the absolute amount of biomass and allometry of individual tree components, they did not affect their relative partitioning </p> <p> Only biomass of trees, woody debris, and small roots (2-5mm) showed agerelated patterns by increasing with greater stand age. Increase in tree biomass was highest during the early decades after establishment and after thinning practices. </p> <p> C storage in forest floor was 0.8, 7.5, 5.4, and 12.1 t C ha⁻¹ and C content in mineral soil was 37.2, 33.9, 39.1, and 36.7 t C ha⁻¹ at WPP02, WPP89, WPP74, and WPP39, respectively. Biomass of roots < 5mm was 0.3, 6.0, 8.9, and 7.5 t ha⁻¹ at WPP02, WPP89, WPP74 and WPP39, respectively. Annual litter fall was age independent with 5, 3 and 4 t ha⁻¹ y⁻¹ at WPP89, WPP74, and WPP39, whereas branch fall increased with age and basal area to 0.007, 0.17, and 1.38 t ha⁻¹ y⁻¹ at WPP89, WPP74, and WPP39, respectively. Average total tree biomass was 0.4, 67, 122, and 547 kg per tree with an uncertainty of less than 1, 5, 3, and 1 % at WPP02, WPP89, WPP74 and WPP39, respectively. Belowground to aboveground tree biomass ratio was 0.35, 0.19, 0.14, and 0.17 forWPP02, WPP89, WPP74, and WPP39, respectively, which suggests a considerable amount of C stored in root biomass. Above and below ecosystem C increased with an average rate of 1.9 and 0.5 t C ha⁻¹ y⁻¹ across the chronosequence, reaching 122 and 66 t C ha⁻¹ y⁻¹ respectively at age 65. Total net ecosystem C accumulation between age 2 and 65 was 147 t C ha⁻¹. Inventories limited to stem biomass may underestimate total tree biomass by up to 3 5% and total ecosystem C by up to 62%.</p> <p> Thus, estimations of C storage in forest ecosystems should include all above and belowground C pools, and its accuracy may be improved by predicting total treebiomass with allometric equations related to stand age and tree diameter.</p> / Thesis / Master of Science (MSc)

The Forest Vegetation Simulator (FVS) is a growth and yield modeling system widely-used for predicting stand and tree-level attributes for management and planning applications in North American forests. The accuracy of FVS predictions for a range of tree and stand level attributes depends a great deal on the performance of the diameter increment model and its predictions of change in diameter at breast height (DBH) over time. To address the challenge of predicting growth in highly variable and geographically expansive forest systems, FVS was designed to include an internal calibration algorithm that makes use of growth observations, when available, from permanent inventory plots. The basic idea is that observed growth rates on a collection of remeasured trees are used to adjust or "calibrate" FVS diameter growth predictions. Therefore, DBH modeling was the focus of this investigation. Five methods were proposed for local calibration of individual tree DBH growth predictions and compared to two sets of results generated without calibration. Data from the US Forest Service's Forest Inventory and Analysis (FIA) program were used to test the methods for eleven widely-distributed forest tree species in Virginia. Two calibration approaches were based on median prediction errors from locally-observed DBH increments spanning a five year average time interval. Two were based on simple linear regression models fitted to the locally-observed prediction errors, and one method employed a mixed effects regression model with a random intercept term estimated from locally-observed DBH increments. Data witholding, specifically a leave-one-out cross-validation was used to compare results of the methods tested. Results showed that any of the calibration approaches tested in general led to improved accuracy of DBH growth predictions, with either of the median-based methods or regression based methods performing better than the random-effects-based approach. Equivalence testing showed that median or regression-based local calibration methods met error tolerances within ± 12% of observed DBH increments for all species with the random effects approach meeting a larger tolerance of ± 17%. These results showed improvement over uncalibrated models, which failed to meet tolerances as high as ± 30% for some species in a newly-fitted DBH growth model for Virginia, and as high as ± 170% for an existing model fitted to data from a much larger region of the Southeastern United States. Local calibration of regional DBH increment models provides an effective means of substantially reducing prediction errors when a relatively small set of observations are available from local sources such as permanent forest inventory plots, or the FIA database. / MS / The Forest Vegetation Simulator (FVS) is a growth and yield model widely-used for predicting stand dynamics, management and decision support in North American forests. Diameter increment is a major component in modeling tree growth. The system of integrated analytical tools in FVS is primarily based on the performance of the diameter increment model and the subsequent use of predicted in diameter at breast height (DBH) over time in forecasting tree attributes. To address the challenge of predicting growth in highly variable and geographically expansive forest systems, FVS was designed to include an internal calibration algorithm that makes use of growth observations, when available, from permanent inventory plots. The basic idea was that observed growth rates on a small set of remeasured trees are used to adjust or “calibrate” FVS growth predictions. The FVS internal calibration was the subject being investigated here. Five alternative methods were proposed attributed to a specific site or stand of interest and compared to two sets of results, which were based on median prediction errors, generated without calibration. Results illustrated that median-based methods or regression based methods performed better than the random-effects-based approach using independently observed growth data from Forest Service FIA re-measurements in Virginia. Local calibration of regional DBH increment models provides an effective means of substantially reducing prediction errors. The results of this study should also provide information to evaluate the efficiency of FVS calibration alternatives and a possible method for future implementation.

Knowledge of ecological characteristics of trees, sites and tree growth on different sites is fundamental for silvicultural decision-making and planning. With the biogeoclimatic ecosystem classification in place, silvicultural management in British Columbia has been given an ecological foundation; however, relationships between growth and site have not yet been fully investigated. The purpose of this study was to determine how height growth of Douglas-fir within the drier portion of the CWH zone varies with site. We adopted site index (m @ 50 yr bh) as a species-specific measure of forest productivity, recognizing that it indicates height growth performance at a selected point in time. If forest productivity is correlated with ecological measures of site quality, what site factors should be used to quantify the relationships? Because of compensating effects, the numerous site factors can be reduced to four primary (synoptic) factors that directly affect plant establishment and growth: climate (light and temperature), soil moisture, soil nutrients, and soil aeration (not used in this study).

I april 2022 presenterade Riksskogstaxeringen (RT) preliminära digitaliserade data om provträd, inklusive åldersbestämningar, från den första Riksskogstaxeringen 1923–1929. Motsvarande data har tidigare funnits tillgängliga digitalt för provträd från inventeringarna efter 1983. Tillsammans med de nya preliminära uppgifterna finns därför nu möjlighet att studera trädpopulationens utveckling i Sverige under de senaste 90 åren. Syftet med denna studie var att analysera hur den svenska trädpopulationen har utvecklats baserat på de tre mätperioderna 1926, 1985 och 2018. Det gjordes genom en kvantitativ analys av RT:s data med fokus på variablerna trädslag, brösthöjdsålder och diameter. Resultaten visar att störst förändringar skedde mellan 1985 och 2018. 2018 var tall för första gången det vanligaste trädslaget. Mellan 1926 och 2018 ökar antalet barrträd i varje diameterklass. De gamla och grova träden blir fler både i avseende på barr och löv. För lövträden ses en markant ökning av bok och ek mellan 1985 och 2018.

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