Distance-dependent Competition Indices Research Articles

Pinus halepensis and P. brutia provenances present similar resilience to drought despite contrasting survival, growth, cold tolerance and stem quality: Insights from a 45 year-old common garden experiment

To improve forest management strategies in the context of ongoing climate change, a better understanding of the inter- and intra-specific variability of tree performance is needed. Pinus halepensis and Pinus brutia, two major Mediterranean species providing crucial ecosystem services to human populations, have attracted increasing attention as potential candidates for assisted migration in the last decades for their growth performance and adaptation to drought. In this study, we compared 12 provenances of P. halepensis and 13 provenances of P. brutia originating from all around the Mediterranean basin in a common garden experiment established in 1976 in southeast France to identify the best species and provenances. Tree survival, circumference and height, as well as stem straightness and the presence of defects were measured and estimated based on forest inventories conducted in 1983, 1988, 1996 and 2021–22. In 2021, 427 trees were also cored and the resulting tree-ring width series were used to assess radial growth resistance, recovery and resilience to drought. Inter-individual variations in competition intensity were taken into account using a distance-dependent competition index, and did not show any significant relationship with tree resilience to drought, while it was negatively related with tree growth and positively with stem quality. We found only marginal differences among species and provenances in terms of growth response to drought. In contrast, there were strong inter- and intra-specific differences in terms of survival, cold tolerance, growth, and stem quality with P. brutia performing better than P. halepensis on average. Interestingly, provenances performances were not related to the climatic conditions at their origins suggesting that the observed inter- and intra-specific variability was not shaped by climatic gradients. This study is the first to compare P. halepensis and P. brutia resilience to drought and provides insights for the assisted migration of those species.

Select or Not? Comparing the Impact of Selective and Schematic Thinning on Scots Pine Tree Growth and Stand Structure

The first commercial thinning usually entails a high cost in harvest operations and a low resulting income. From a practical forestry perspective, a schematic spatial selection might be more efficient than a selective approach. Therefore, this study aimed to compare basal area, total and standing volumes, and periodic annual increment (PAI), as well as stand structure, between different thinning designs (selective and schematic thinning) and strategies (thinning once or more than once) over a long-term monitoring period of Scots pine (Pinus sylvestris) plantations in Sweden. We also evaluated the relevancy of distance-dependent competition indices (CIs) in individual tree growth models by comparing growth model predictions with the use of distance-dependent and distance-independent CIs. Despite higher heterogeneity in schematically thinned stands, there were no significant differences in standing and total volumes (m3·ha−1) among treatments in the short or long term. Although the inclusion of a distance-dependent CI improved the model slightly, distance-independent models predicted diameter growth just as effectively. Schematic thinning could be a viable option for a first commercial thinning or one-time thinning if, at least, one more thinning is included in the management plan, or if the motivating interest is mainly volume.

Do Distance-Dependent Competition Indices Contribute to Improve Diameter and Total Height Tree Growth Prediction in Juvenile Cork Oak Plantations?

Competition indices may improve tree growth modelling in high-density stands, found often in new cork oak plantations. Distance-dependent competition indices have hardly been considered for juvenile cork oak plantations since existing models were developed for low-density mature stands. This study aims at inspecting the potential of including distance-dependent competition indices into diameter at breast height (d) and total height (h) growth models for Quercus suber L., comparing several distance-dependent and distance-independent competition indices. Annual d and h growth were modelled with linear and non-linear growth functions, formulated as difference equations. Base models were initially fitted considering parameter estimates depending only on site index (S) and/or stand density (N). They were refitted, testing the significance of adding each competition index to the model parameters. Selected models included the best-performing distance-dependent or -independent competition indices as additional predictors. Best base d and h growth models showed a modelling efficiency (ef) of ef = 0.9833 and ef = 0.9900, respectively. Adding a distance-dependent competition index slightly improved growth models, to an ef = 0.9851 for d and ef = 0.9902 for h. Best distance-dependent competition indices slightly overperformed distance-independent ones in diameter growth models. Neither S nor N were included on best fitted models. If inter-tree competition is present in juvenile undebarked cork oak plantations, it does not yet strongly impact individual tree growth, which may diminish the importance of using, at this stage, more complex spatially explicit competition indices on predicting individual tree growth.

Estimation of individual stem volume and diameter from segmented UAV laser scanning datasets in Pinus taeda L. plantations

ABSTRACT The competitive neighbourhood surrounding an individual tree can have a significant influence on its diameter at breast height (DBH) and individual tree stem volume (SV). Distance dependent competition index metrics are rarely recorded in traditional field campaigns because they are laborious to collect and are spatially limited. Remote sensing data could overcome these limitations while providing estimation of forest attributes over a large area. We used unoccupied aerial vehicle laser scanning data to delineate individual tree crowns (ITCs) and calculated crown size and distance-dependent competition indices to estimate DBH and SV. We contrasted two methods: (i) Random Forest (RF) and (ii) backwards-stepwise, linear multiple regression (LMR). We utilized an existing experiment in Pinus taeda L. plantations including multiple planting densities, genotypes and silvicultural levels. While the tree planting density did affect the correct delineation of ITCs, between 61% and 99% (mean 86%) were correctly linked to the planting location. The most accurate RF and LMR models all included metrics related to ITC size and competitive neighbourhood. The DBH estimates from RF and LMR were similar: RMSE 3.05 and 3.13 cm (R2 0.64 and 0.62), respectively. Estimates of SV from RF were slightly better than for LMR: RMSE 0.06 and 0.07 m3 (R2 0.77 and 0.70), respectively. Our results provide evidence that ITC size and competition index metrics may improve DBH and SV estimation accuracy when analysing laser-scanning data. The ability to provide accurate, and near-complete, forest inventories holds a great deal of potential for forest management planning.

Terrestrial Laser Scanning in Assessing the Effect of Different Thinning Treatments on the Competition of Scots Pine (Pinus sylvestris L.) Forests

Thinning is a forest management activity that regulates the competition between the trees within a forest. However, the effect of different thinning treatments on competition is largely unexplored, especially because of the difficulty in measuring crown characteristics. This study aimed to investigate how different type and intensity thinning treatments affect the stem- and crown-based competition of trees based on terrestrial laser scanning (TLS) point clouds. The research was conducted in three study sites in southern Finland where the Scots pine (Pinus sylvestris L.) is the dominant tree species. Nine rectangular sample plots of varying sizes (1000 m2 to 1200 m2) were established within each study site, resulting in 27 sample plots in total. The experimental design of each study site included two levels of thinning intensities and three thinning types, resulting in six different thinning treatments. To assess the competition between the trees, six distance-dependent competition indices were computed for each tree. The indices were based on diameter at breast height (DBH) (CIDBH), height (CIH), maximum crown diameter (CIMCD), crown projection area (CICA), crown volume (CICV), and crown surface area (CICS). The results showed that for both moderate and intensive intensities, the competition decrease was 45.5–82.5% for thinning from below, 15.6–73.6% for thinning from above, and 12.8–66.8% for systematic thinning when compared with control plots. In most cases, the crown- and stem-based metrics were affected by thinning treatments significantly when compared with control plots at a 95% confidence interval. Moreover, moderate from-below and from-above thinning showed no statistical difference with each other in both crown- and stem-based competition indices except for CIDBH (p-value ≤ 0.05). Our results confirm the great potential of TLS point clouds in quantifying stem- and crown-based competition between trees, which could be beneficial for enhancing ecological knowledge on how trees grow in response to competition.

Estimating height-diameter relations for structure groups in the natural forests of Northeastern China

Tree height-diameter (H-D) models are essential for estimating tree volume and forest production. The development of such models can be especially challenging in multi-species natural forests. We present new generalized mixed-effects models based on a set of 456 sample plots and 77,908 individual tree measurements. Tree species were assigned to one of four structure groups according to their life forms, regeneration modes and stand structure characteristics: (1) Understory tree species with an L-shaped D distribution (UL); (2) Sub-canopy tree species with an L-shaped D distribution (SL); (3) Sub-canopy tree species with a bell-shaped D distribution (SB); and (4) Canopy tree species with a bell-shaped D distribution (CB). A distance-dependent competition index (DCI) was included in the base model of the structure groups, and a mixed-effects model for each group with tree species as random-effect. The four models represent unique allometric relationships for the four structure groups. Model accuracy was improved for all groups after adding DCI. Two sets of mixed-effects H-D models (with or without DCI) are presented to improve the estimates of productivity and carbon stock in the temperate natural forests of Northeastern China. The general approach adopted in this study may serve as an example for similar studies in other multi-species and multi-layered forest stands.

Predicting crown width and length using nonlinear mixed-effects models: a test of competition measures using Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.)

Including individual-tree competition indices as predictor variables could significantly improve the performance of crown width and length models for Chinese fir ( Cunninghamia lanceolata (Lamb.) Hook.). Moreover, distance-dependent competition indices are superior to distance-independent ones when modeling crown width and length. Compared with crown width and length basic models with optimum competition indices, the performance of the two-level nonlinear mixed-effects models improved. Crown width (CW) and crown length (CL) are two important variables widely included as the predictors in growth and yield models that contribute to forest management strategies. Individual-tree crown width and length models were developed with data from 1498 Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) trees in 16 sample plots located at Jiangle County, Fujian Province, southeastern China. Two hypotheses were proposed: (1) including individual-tree competition indices as predictor variables could significantly improve performance of both the CW—DBH and CL—DBH models; and (2) the distance-dependent competition indices would perform better than distance-independent ones. The models were fitted using generalized linear least squares or generalized nonlinear least squares methods. In addition, to prevent correlations between observations from the same sampling unit, we introduced age classes and sample plots as random effects to develop the two-level nonlinear mixed-effects models. We found introduction of competition indices could significantly improve the performance of the CW—DBH and CL—DBH models. The distance-dependent competition index (i.e., competitor to subject tree distance) performed best in modeling the crown width and length models. Compared with crown width and length basic models with optimum competition indices, the performance of the two-level nonlinear mixed-effects models was significantly better. The two hypotheses were accepted. We hope these models will contribute to scientific management of Chinese fir plantations.

Effectiveness of competition indices for understanding growth in an overstocked stand

The objective of this study was to select and discuss indices to explain competition among trees in an unmanaged stand in order to support decision-making in forest management. The work was carried out in a plantation of Araucaria angustifolia (Bertol.) Kuntze located in a national forest in southern Brazil. The plantation was established in 1946 in 2 × 2 m spacing, with only one thinning that happened sometime between 1970 and 1980. Forty-six sample plots were established using an adaptation of the Prodan method. We tested distance-independent and distance-dependent competition indices that included or excluded crown area variables. An equation was generated to describe the relation between diameter at breast height and crown diameter, since these were highly correlated (r = 0.87); this permitted calculation of the growth space required for the trees in the stand. It is important to carefully choose the variables and competition indices to be tested in each study case. Including crown variables did not improve prediction ability to overcome the performance of the Stage distance-independent index. In general, the distance-independent indices performed better than the distance-dependent ones, even the stand arrangement in our study area was modified through thinning, mortality, and natural regeneration. When the goal is to better understand the ecological significance of a competition index and not only its statistical ability to predict short-term growth, simpler indices are recommended.

Effect of competition on individual white spruce production in young boreal mixedwood forests

Increasing the production of wood fibre from conifer species such as white spruce (Picea glauca (Moench) Voss) is one of many challenges in the management of boreal mixedwood forests. The effects of various competition measures on relative growth and relative growth rate variables were calculated for individual white spruce subject trees. Correlation analysis was used to explore relationships with competitor structural features, including the ratio of competitor basal area to subject tree basal area (CBAS), the ratio of competitor height to subject tree height (AHCS), and the proportion of softwood (FSW). Regression analysis was used to explore relationships with three distance-dependent competition indices. The ratio of subject tree height to diameter at breast height (DBH) (HDR), crown ratio (CR), and crown relative increment rate (CRIR) were significantly correlated with CBAS and AHCS. HDR, CR, CRIR, and DBH relative growth rate were all statistically significantly related to the competition indices. Results indicated that (i) relative growth and relative growth rate measures successfully captured a range of competition, (ii) crowns of trees with larger diameters used their horizontal growing space more efficiently to produce stemwood, and (iii) the proportion of softwood contributing to competition did not appear to influence subject tree production efficiency. Growth efficiency variables have the potential to improve our understanding of boreal mixedwood dynamics.

HOW COMPETITION INDICES BEHAVE AT DIFFERENT NEIGHBORHOOD COVERAGES AND MODIFICATIONS IN A NATURAL ARAUCARIA FOREST IN SOUTHERN BRAZIL

Tree-level growth models are being more used in heterogeneous forests, for they can take underlying processes, such as competition, into account. Although it is common in the forest literature to test several indices in order to define the most suitable for each study, the evaluation of plot sizes or competition radii is poorly addressed in competition studies. The objective of this work was to assess the effect of different plot sizes and competitor selection radii on distance-independent and distance-dependent competition indices, as well as test several modifications in previously created indices. We used data of diameter, canopy stratum and crown quality from two stem mapped measurements carried out in a six-year period. Both distance-dependent and independent indices were calculated for different plot sizes and competitor selection radii. The performance of plot sizes and neighborhood radii was evaluated via Spearman’s rank correlation with the annual growth in diameter, and those with the largest correlation coefficient were included in a stepwise regression to estimate diameter growth. For almost all the indices the correlation increased as the plot size or radius increased. A 50 m x 50 m square plot generated the strongest correlation for distance-independent indices. A 20 m radius resulted the largest correlation for the distancedependent indices. Modifications in some of the indices also improved their performance. The stepwise regression selected BAL and Hegyi indices to describe the diameter growth, which means that using only one competition index might not be enough to fully explain the overall competition.

The impact of intraspecific competition on tree growth in planted Korean pine forest

The aim of this study was to explore the correlation of competition indices (CIs) on individual tree growth for Korean pine (Pinus koraiensis) plantation using partial correlation analysis and generalized linear models. The data were collected from 15 permanent plots in Mengjiagang forestry farm, Northeast China. The results showed that the distance dependent CIs have a higher predictive capacity for individual growth of pine trees. The control index of competitive trees number (CI1) combined with the selection fixed competitor trees (M2) was found to be the most well correlated competition measure with five - years diameter increment. Thus, the competition index (CI1- M2) was recommended for developing individual tree growth models. The subject tree diameter at breast height, crown width, height to crown base, tree volume and basal area all showed a significantly linear correlation with tree competition intensity (P < 0,05). Diameter at breast height, crown width, tree volume and basal area all decreased with increasing competition intensity, whereas the height to crown base increased. There was no significant relationship between competition intensity and tree height (P > 0,05). The optimal model of predicting individual growth with logarithm of diameter at breast height and CIs as the independent variables due to the best fitting performance. This results also showed considerable improvement in predicting individual tree periodic growth when including competition indices that the mean absolute error is reduced in the range of 22−25%.

Competition and water stress indices as predictors of Pinus halepensis Mill. radial growth under drought

The frequency, duration, and severity of drought events are expected to increase in the Mediterranean area as a result of climate change, with strong impacts on forest ecosystems and in particular individual tree growth. Tree growth response to drought is strongly influenced by local site and stand characteristics that can be quantified using competition indices (CIs) and water stress indices (WSIs). These indices have been widely used to predict tree growth; however, they are numerous, and few studies have investigated them jointly. In this context, we investigated the potential of using CIs and WSIs to investigate tree behaviour under drought. The main objective of this study was to quantify P. halepensis Mill. annual radial growth using tree size from the previous year, CIs and WSIs.We studied twelve 50-year-old Pinus halepensis plots located in the South-East of France distributed in different density treatments (light, medium and dense). At each plot, all trees were measured (height, circumference), spatialized and the ring-widths were measured for ~15 trees. We also developed a two-strata (over- and understorey) forest water balance model to simulate soil water content at a daily resolution based on stand characteristics (LAI values in particular) and soil properties. A mixed modelling approach was eventually used to investigate the drivers of P. halepensis annual radial growth and to test the performance of five CIs and four WSIs.The best growth model included tree size, the sum of Basal Area of Larger trees in a 5 m-radius (BAL; as CI), and the number of days that trees experienced water stress in a year (as WSI) as predictors. This model explained up to 56% of the variance in observed pine tree growth, which increased up to 77% when the individual tree was included as a random effect on the intercept. We found that distance-independent CIs can perform as well as distance-dependent CIs in our study site. The duration of drought alone appeared to better predict tree growth than drought intensity and duration, or drought timing. The selected model led us to reaffirm the positive effect of thinning on tree secondary growth when facing long and intense drought.

Prediction of Competition Indices in a Norway Spruce and Silver Fir-Dominated Forest Using Lidar Data

Competitive interactions are important predictors of tree growth. Spatial and temporal changes in resource availability, and variation in species and spatial patterning of trees alter competitive interactions, thus affecting tree growth and, hence, biomass. Competition indices are used to quantify the level of competition among trees. As these indices are normally computed only over small areas, where field measurements are done, it would be useful to have a tool to predict them over large areas. On this regard, remote sensing, and in particular light detection and ranging (lidar) data, could be the perfect tool. The objective of this study was to use lidar metrics to predict competition (on the basis of distance-dependent competition indices) of individual trees and to relate them with tree aboveground biomass (AGB). The selected study area was a mountain forest area located in the Italian Alps. The analyses focused on the two dominant species of the area: Silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) H. Karst). The results showed that lidar metrics could be used to predict competition indices of individual trees (R2 above 0.66). Moreover, AGB decreased as competition increased, suggesting that variations in the availability of resources in the soil, and the ability of plants to withstand competition for light may influence the partitioning of biomass.

Effects of red alder on growth of Douglas-fir and western redcedar in southwestern British Columbia

Red alder (Alnus rubra [Bong.]), is the most common broadleaf species in the Pacific Northwest, and is widely distributed as a component of mixed stands with conifers. It rapidly overtops associated juvenile conifers and is a strong competitor. However, red alder is also a symbiotic nitrogen fixer and can contribute to improvement in soil nitrogen, as well as serving other roles such as improving biodiversity and forest health.We examined data collected in mixed red alder-conifer plantations established between 1992 and 1999 to examine the effects of red alder on the growth of Douglas-fir (Pseudotsuga menziessi (Mirb.) Franco, Fd) and western redcedar (Thuja plicata Donn., Cw). Results suggest that densities of up to 400 alder trees per hectare may be acceptable and possibly desirable on nitrogen deficient sites. The growth of Fd may be enhanced when red alder density is relatively low at older ages. We found that the competitive effects of red alder on conifer growth were consistently lower than that of the conifers (Fd and Cw) while alder had stronger effects on light availability. The relationship between volume growth and competition indices varied between the two conifer species: (1) for Fd the highest correlations were obtained using a distance-dependent competition index based on the height differences, and (2) for Cw the highest correlations were with distance-independent Lorimer’s index. As also expected due to Cw’s greater shade tolerance, its volume growth showed less sensitivity to the presence of red alder than Fd.

A novel approach to selecting a competition index: the effect of competition on individual-tree diameter growth of Calabrian pine

In this study, we evaluated the performance of 18 competition indices composed of nine distance-dependent and nine distance-independent indices in explaining the variation in individual-tree diameter growth of Calabrian pine (Pinus brutia Ten.) in the central Mediterranean region of Turkey. The data were obtained from 432 sample plots with varying stand age, site index, and stand density. To evaluate the performance of each competition index, the mean square error reduction approach was used relative to the noncompetition. Also, this study compared fixed and mixed effects models to analyze diameter growth. Statistical analyses showed that the best distance-independent competition indices performed as well as the best distance-dependent competition indices. The distance-independent competition index of Schröder and Gadow (1999; Can. J. For. Res. 29(2): 280–283, doi: 10.1139/x98-199) performed best and is recommended for use in future growth and yield models to be used in the central Mediterranean region of Turkey. Also, the best selection of competitive neighbors was achieved using the area of influence overlap method, whereas the fixed-radius and angle count sampling methods had no significant improvement in quantifying the competition effects. On the other hand, all mixed effects models provided much better fits than their fixed model counterparts.

Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil

Models to predict tree survival and mortality can help to understand vegetation dynamics and to predict effects of climate change on native forests. The objective of the present study was to use Artificial Neural Networks, based on the competition index and climatic and categorical variables, to predict tree survival and mortality in Semideciduous Seasonal Forests in the Atlantic Forest biome. Numerical and categorical trees variables, in permanent plots, were used. The Agricultural Reference Index for Drought (ARID) and the distance-dependent competition index were the variables used. The overall efficiency of classification by ANNs was higher than 92% and 93% in the training and test, respectively. The accuracy for classification and number of surviving trees was above 99% in the test and in training for all ANNs. The classification accuracy of the number of dead trees was low. The mortality accuracy rate (10.96% for training and 13.76% for the test) was higher with the ANN 4, which considers the climatic variable and the competition index. The individual tree-level model integrates dendrometric and meteorological variables, representing a new step for modeling tree survival in the Atlantic Forest biome.

Competition and dominance between angiosperms and Araucaria angustifolia (Bert.) O. Kuntze in the Atlantic Forest in southern Brazil

The dominance relationship between angiosperms and gymnosperms in natural forests has long been widely discussed, with some researchers believing that angiosperms tend to displace conifers due to competitive processes between the two species groups. The Lozenge or “temporal stand replacement” model states that a cohort of conifers is first established after a disturbance, while angiosperms establish themselves under the conifer canopy in a secondary stage that thereafter hinders conifer regeneration. This causes a drastic decline in conifer recruitment, restricting them to filling in gaps opportunistically. The objective of this study was to evaluate the competition for growth and survival between a conifer (Araucaria angustifolia) and two groups of angiosperms (shade-tolerant and light-demanding) in a species-rich forest using a distance-dependent competition index. We also investigated dominance among the three species groups by projecting the aboveground biomass of the groups for 50 years using an individual-tree distance-dependent growth model. We used data collected from 25 1-ha permanent plots located in the National Forest (FLONA) of Irati in southern Brazil, where all trees with more than a 10-cm diameter at breast height were identified for species and tagged, mapped, and measured. These plots have been measured every 3 years since their establishment in 2002. For diameter growth, the results indicated the araucarias were subject to severe intraspecific competition, while the light-demanding species suffered only moderate competition from the araucarias. The shade-tolerant species experienced little competition from any species group. No empirical evidence was found to support the hypothesis that competition estimates improve mortality predictions in a simple model based on stem diameter. Regarding the long-term dominance of the Araucaria, light-demanding, and shade-tolerant groups, the growth model indicated that araucarias will tend to dominate over the two angiosperm groups in aboveground biomass within 50 years, suggesting that this forest type follows the Lozenge model.

Influencia de la competencia en el crecimiento diamétrico de Pinus durangensis Martínez en Durango, México

En esta investigación se analizó la influencia de la competencia sobre el crecimiento en diámetro normal en árboles de Pinus durangensis en bosques mixtos e irregulares del estado de Durango. Se utilizaron datos de dos inventarios realizados en 2009 y 2014, en 16 Sitios Permanentes de Investigación Forestal y de Suelos (SPIFyS) de 2 500 m2, dentro de los cuales, Pinus durangensis fue la especie dominante del estrato arbóreo, con 39.44 % del valor de importancia, y crece de manera mezclada con otras 18 especies arbóreas. El efecto de la competencia fue analizado mediante 14 índices de competencia independientes de la distancia y 11 dependientes de la distancia; para ello, se evaluaron 11 criterios de selección de árboles competidores. Los índices independientes de la distancia explicaron ligeramente mejor que los índices dependientes de la distancia el crecimiento en diámetro normal de la especie estudiada. El índice de competencia independiente de la distancia que se deriva de la razón entre el área basal del árbol objetivo y el área basal por hectárea describió mejor el efecto deseado, por lo que se recomienda para su posible inclusión en futuros modelos de crecimiento en diámetro normal desarrollados para P. durangensis.

Allometric modelling of crown width for white spruce by fixed- and mixed-effects models

Crown width is an important predictor for tree growth, crown surface area, forest canopy cover, tree-crown profiles and wildlife habitat indices. This paper developed crown width models for white spruce (Picea glauca (Moench) Voss) in Alberta using allometric fixed and mixed models with varying degrees of model complexity. Diameter at breast height was the most important predictor and was used in the base model. Crown ratio, height-diameter ratio and two competition indices (CIs) were additional predictors added to the base model to form four expanded models. At each level of complexity, a fixed model and a mixed model were fitted. Improved fits were achieved for both model types as model complexity increased, and all mixed models provided much better fits than their fixed model counterparts. Population-averaged (PA) predictions by fixed models, and typical mean (TM), PA and plot-specific (PS) predictions by mixed models were compared on both model fitting and validation data. TM and PA predictions by each mixed model were almost identical, and they were less accurate than PA predictions by the fixed model counterpart, especially for simpler models. Much better PS predictions by mixed models were observed on both datasets. Although the distancedependent CI was slightly better than the distance-independent CI, both were not recommended due to their marginal contributions to crown width predictions.

Separating effects of crown structure and competition for light on trunk growth of Sequoia sempervirens

Tree-level productivity is largely determined by crown size and aboveground vigor, but light availability ultimately controls growth. Competition indices are typically used in modeling instead of actual measurements of light. Our goals were to determine which measure of light best predicts trunk growth increments of Sequoia sempervirens, to quantify the amount of growth variation explained by light after accounting for effects of tree structure, and to compare model fitness of various competition indices. Twenty-four trees spanning a wide range of light environments were randomly selected from stands of different ages, including trees 23–72m tall and 20–560years old. Tree structure and trunk growth increments were quantified via direct measurements of all branches and coring main trunks at multiple heights. Light availability was quantified via hemispherical photography throughout tree crowns. Competition indices were computed by measuring the size and distribution of neighboring trees. The largest tree had 69m3 of wood and bark, 3208m2 of leaf area, and produced 1.04m3yr−1 of wood in the main trunk, whereas the smallest tree had less than 1m3 of wood and bark, 134m2 of leaf area, and produced 0.04m3yr−1 of wood in the main trunk. After accounting for tree structure, light availability explained an additional 10% of variation in trunk wood volume increment. Light availability alone explained 49% of the variation in wood volume increment, while tree size alone explained 41%. The growth model with average mid-crown openness as the measure of light availability was 19 times more likely than the model without a term for light. A distance-dependent competition index computing neighboring tree crown volume (DDCV) was >1200 times more likely than any other competition index in the best growth model. Together with tree size and aboveground vigor, DDCV explained 91% of variation in trunk wood volume increment.