Modeling Tree Crown Ratio

Holdaway, Margaret R.

doi:10.5558/tfc62451-5

Cited by 44 publications

(25 citation statements)

References 2 publications

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“…This ontogenetic trend has already been reported for some tropical canopy species (O'Brien et al, 1995) and likely reflects changes in the pattern of resource allocation underlying crown edification in most forest canopy trees (Barthélémy and Caraglio, 2007;Hasenauer and Monserud, 1996;Holdaway, 1986;Moorby and Wareing, 1963;Perry, 1985). The overall increase in the carbon accumulation rate with tree size is a well-established trend (Stephenson et al, 2014), but the relative contribution of the trunk and the crown to that pattern has rarely been investigated, particularly for large trees for which branch growth monitoring involves a tremendous amount of work.…”

Section: Crown Mass Ratio and The Reference Biomass Model Errormentioning

confidence: 87%

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Ploton¹,

Barbier²,

Takoudjou³

et al. 2016

Biogeosciences

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Abstract. Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that Published by Copernicus Publications on behalf of the European Geosciences Union. P. Ploton et al.: Closing a gap in tropical forest biomass estimationthe proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥ 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

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Section: Crown Mass Ratio and The Reference Biomass Model Errormentioning

confidence: 87%

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Ploton¹,

Barbier²,

Takoudjou³

et al. 2016

Biogeosciences

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“…Coefficients α 1 to α 5 vary according to species groups defined in different variants of FVS (e.g., Bush and Brand 1995). If crown ratio information is not provided in the individual tree data, C is estimated using the equation derived by Holdaway (1986): (2) where BA is estimated stand basal area and β 1 to β 4 are coefficients specific to each species group.…”

Section: Main Components Of Ls-fvsmentioning

confidence: 99%

Testing the Lake States variant of FVS (Forest Vegetation Simulator) for the main forest types of northern Ontario

Lacerte¹,

Larocque²,

Woods³

et al. 2004

The Forestry Chronicle

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The Lake States variant of the FVS (Forest Vegetation Simulator) model (LS-FVS), also known as the LS-TWIGS variant of FVS, was validated for black spruce (Picea mariana (Mill.) BSP), white spruce (Picea glauca (Moench) Voss), jack pine (Pinus banksiana Lamb.) and trembling aspen (Populus tremuloides Michx.) forests in northern Ontario. Individual-tree data from 537 remeasured sample plots were used. This dataset included different combinations of site index, stand density and age. It was possible to compare observations and predictions for different projection length periods. The validation exercise included a biological consistency analysis, the computation of mean percent difference (MPD) for stand density, stand basal area, top height and quadratic mean diameter (QMD) and the comparison of observed and predicted individual-tree dbh. The biological consistency analysis indicated that LS-FVS logically predicted the effect of site index on top height, stand basal area and QMD for black spruce and jack pine. However, the decrease in stand basal area at young ages was inconsistent with the normal development pattern of the forest stands under study and was attributed to deficiencies in the prediction of mortality. LS-FVS was found to underpredict stand density, stand basal area and top height and to overpredict QMD. Even though there were large errors in the prediction of change in stand density, LS-FVS was nevertheless consistent in the prediction of the shape of the dbh size distribution. pour la densité, la surface terrière, la hauteur maximale et le diamètre moyen quadratique (QMD) et la comparaison des diamètres à hauteur de poitrine (dhp) observés et prédits d'arbres individuels. L'analyse de cohérence biologique a indiqué que LS-FVS a prédit de façon cohérente les effets de l'indice de site sur la hauteur maximale, la surface terrière et le QMD pour l'épinette noire et le pin gris. Cependant, la diminution en surface terrière en bas âge s'est avérée inconsistante avec la tendance normale de développement des types forestiers sous étude. Cette situation a été attribuée à une faiblesse de LS-FVS au niveau de la prédiction de la mortalité. Il a été trouvé que LS-FVS a sous-estimé la densité des peuplements, la surface terrière et la hauteur maximale et surestimé le QMD. Même s'il y avait de larges erreurs dans la prédiction du changement dans la densité des peuplements, LS-FVS était néanmoins cohérent dans la prédiction de la forme de la distribution des classes de dhp.

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“…For example, the Forest Vegetation Simulator (FVS) is a forest growth and yield model widely used in the US and parts of Canada (Crookston and Dixon 2005). The FVS-Northeastern variant (FVS-NE) uses the Holdaway (1986) equations for predicting CR. The parameters for the Holdaway (1986) equations are based on data available from the 1960s and 1970s inventories of the US Lake States, but little work has focused on validating these equations across the region where they are currently applied.…”

Section: Introductionmentioning

confidence: 99%

“…The FVS-Northeastern variant (FVS-NE) uses the Holdaway (1986) equations for predicting CR. The parameters for the Holdaway (1986) equations are based on data available from the 1960s and 1970s inventories of the US Lake States, but little work has focused on validating these equations across the region where they are currently applied. Furthermore, FVS-NE covers a wide geographic region, extending from Ohio east to New Jersey and north to Maine, encompassing an area with vastly different forest types, climatic zones, geology, and forest management strategies.…”

Section: Introductionmentioning

confidence: 99%

Development of height to crown base models for thirteen tree species of the North American Acadian Region

Rijal¹,

Weiskittel

Kershaw

2012

The Forestry Chronicle

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Height to live crown base (HCB) is an important input variable for several growth and yield models. Since HCB is rarely measured in the field, it is often predicted using static models. Instead of predicting HCB, the Forest Vegetation Simulator Northeastern Variant (FVS-NE) uses an equation that predicts crown ratio (CR), which has not been well validated. The main goal of the present study was to construct a regional HCB model for thirteen selected tree species of the Acadian Region of North America. The specific objectives were to: 1) evaluate FVS-NE model predictions, 2) compare suitable model forms, and 3) assess influence of various covariates to improve predictions. We evaluated three model forms, namely Holdaway (1986), logistic, and exponential. The findings indicated that FVS-NE models were significantly biased for all species as the overall mean bias and root mean square error (RMSE) were 0.11 m and 1.80 m, respectively. A logistic equation with size (diameter at breast height [DBH], total height [HT] and ratio of DBH to HT), and competition (crown competition factor [CCF] and basal area larger than subject tree [BAL]) gave the best predictions for all species in this analysis. This model had an overall mean bias <0.01 m and an RMSE of 1.59 m, which represents a significant improvement in predictions compared to FVS-NE. Despite the range of species and observed variation in the data, the equations worked well and can be easily calibrated to new stands with a few local observations.

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Modeling Tree Crown Ratio

Cited by 44 publications

References 2 publications

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Testing the Lake States variant of FVS (Forest Vegetation Simulator) for the main forest types of northern Ontario

Development of height to crown base models for thirteen tree species of the North American Acadian Region

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