Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions 1-3 , but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear 4 . Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits-wood density, specific leaf area and maximum height-consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies 5 . Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our traitbased approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.Phenotypic traits are considered fundamental drivers of community assembly and thus species diversity 1,6 . The effects of traits on individual plant physiologies and functions are increasingly understood, and have been shown to be underpinned by well-known and globally consistent trade-offs 1-3 . For instance, traits such as wood density and specific leaf area capture trade-offs between the construction cost and longevity or strength of wood and leaf tissues 2,3 . By contrast, we still have a limited understanding of how such trait-based trade-offs translate into competitive interactions between species, particularly for long-lived organisms such as trees. Competition is a key filter through which ecological and evolutionary success is determined 4 . A long-standing hypothesis is that the intensity of competition decreases as two species diverge in trait values 7 (trait dissimilarity). The few studies [8][9][10][11][12][13] that have explored links between traits and competition have shown that linkages were more complex than this, as particular trait values may also confer competitive advantage independently from trait dissimilarity 9,13,14 . This distinction is fundamental for species coexistence and the local mixture of traits. If neighbourhood competition is driven mainly by trait dissimilarity, this will favour a wide spread of trait values at a local scale. By contrast, if neighbourhood interactions are mainly driven by the c...

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We surveyed the quantity and quality of dead Norway spruce (Picea abies (L.) Karst.) trees and wood-inhabiting cryptogams in a managed boreal forest landscape in northern Sweden. Size and decay of dead trees was related to substrate utilization by wood-inhabiting species. Coarse woody debris (CWD) was surveyed along 34 strip transects. CWD and wood-inhabiting cryptogams were surveyed in eight circular plots at each site. A total of 6195 spruce CWD units occurred along strip transects and 809 spruce CWD units in circular plots. On average 2.2 m3/ha spruce CWD was found on the plots. The majority (63%) of the transect CWD units were <10 cm diameter and in early to intermediate decay stages. Sixty-eight wood-specific species of fungi, lichens, mosses, and hepatics occurred on the plots. Of these, 13 occurred on [Formula: see text]5% of the 809 CWD units surveyed for wood-inhabiting species. Eight species occur on the Swedish red lists, indicating that such species are indeed uncommon in managed forests. Red-listed species showed strong preferences for large diameter CWD and CWD in late decay stages, i.e., substrates that are poorly represented in managed forests. Frequently occurring species, however, showed utilization patterns that correspond with the distribution of the substrate types.

Accurate estimates of below-ground biomass of trees are important when quantifying the amount of carbon sequestered in forests. Allometric single-tree below-ground biomass functions were developed for Pinus sylvestris , Picea abies and Betula pendula and Betula pubescens in Sweden. The idea was to calibrate an existing comprehensive data set of about 600 trees that only covered the stump and coarse roots against a new data set that covered roots down to 2 mm diameter. The new data set consisted of about 80 trees acquired using the same design as for the existing set, but complemented with a detailed inventory of the fine root fractions remaining in the ground. Checks were made to determine whether the density properties of the two data sets were comparable and it was concluded that they were. This was a prerequisite for calibrating the older data against the new information and further for merging the two data sets. The merged data set was used to derive regression functions for below-ground biomass. For all functions the adjusted R 2 values were always higher than 0.95 and the root mean square errors were always lower than 36% for P. sylvestris and P. abies. Below-ground biomass predicted with the new functions was approximately 11% higher than the values obtained using the existing biomass functions.

1 The United Nations Collaborative Program on Reduced Emissions from Deforestation and Forest 2Degradation in Developing Countries (UN REDD) was launched with the aim of contributing to 3 the development of capacity for reducing emissions from loss of forest carbon in developing 4 countries. It is understood that REDD mechanisms must be supported by forest assessment 5 programs that can monitor the carbon stocks by carbon pools and human activities. Reporting at a 6 national level will be required but many countries are likely to benefit from more local monitoring 7 programs within the countries as well, gauging the effects of national policies and local financial 8 mechanisms aimed at reaching goals for emission control for the nation as a whole. Field-based 9 forest sample surveys are typically used as support for national reporting purposes. However, 10 monitoring within the countries will require huge investments in field surveys to provide reliable 11 change estimates with high spatial and temporal resolution. Airborne scanning LiDAR has 12 emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of 13 above-ground tree biomass. The aim of this study was to demonstrate how "wall-to-wall" LiDAR 14 data can be used for change estimation. Estimators for areal changes of categories representing 15 human activities such as "deforestation", "degradation" and "untouched" were presented. 16Corresponding estimators for variance were also provided. Furthermore, it was shown how net 17 change in biomass for the defined activity categories and for the entire area of interest can be 18 estimated from a field sample survey with and without support of LiDAR remote sensing data and 19 how the uncertainty can be quantified by corresponding variance estimates. In a case study in a 20 small boreal forest area in southeastern Norway (852.6 ha) a probability sample of 176 field 21 sample plots distributed according to a stratified systematic design was measured twice over an 11 22 year period. Corresponding multi-temporal scanning LiDAR data were also available. A 23 multinomial logistic regression model was used to predict change category for every LiDAR grid 24 cell in the area, and areal changes were estimated from the pure field sample and with the support 25 of the LiDAR data applying model-assisted estimators. The standard errors of the areal change 26 estimates were reduced by 43-75% by adding LiDAR data to the estimation. The change categories 27 were used as post-strata in a subsequent estimation of net change in biomass. The standard errors 28 of the biomass change estimates for the respective change categories were reduced by 18-84% 29 compared to the pure field survey when using LiDAR data as auxiliary information in a model-30 assisted estimation procedure, which translates to a need for 1.5-38.7 times as many field plots 31 when relying only on the field data. For the entire area of interest, the standard error of the overall 32 net change in biomass was reduced by 57%...