Tallo: A global tree allometry and crown architecture database.

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research-from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology-from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

Slow rate of secondary forest carbon accumulation in the Guianas compared with the rest of the Neotropics.

Secondary forests are a prominent component of tropical landscapes, and they constitute a major atmospheric carbon sink. Rates of carbon accumulation are usually inferred from chronosequence studies, but direct estimates of carbon accumulation based on long-term monitoring of stands are rarely reported. Recent compilations on secondary forest carbon accumulation in the Neotropics are heavily biased geographically as they do not include estimates from the Guiana Shield. We analysed the temporal trajectory of aboveground carbon accumulation and floristic composition at one 25-ha secondary forest site in French Guiana. The site was clear-cut in 1976, abandoned thereafter, and one large plot (6.25 ha) has been monitored continuously since. We used Bayesian modeling to assimilate inventory data and simulate the long-term carbon accumulation trajectory. Canopy change was monitored using two aerial lidar surveys conducted in 2009 and 2017. We compared the dynamics of this site with that of a surrounding old-growth forest. Finally, we compared our results with that from secondary forests in Costa Rica, which is one of the rare long-term monitoring programs reaching a duration comparable to our study. Twenty years after abandonment, aboveground carbon stock was 64.2 (95% credibility interval 46.4, 89.0) Mg C/ha, and this stock increased to 101.3 (78.7, 128.5) Mg C/ha 20 yr later. The time to accumulate one-half of the mean aboveground carbon stored in the nearby old-growth forest (185.6 [155.9, 200.2] Mg C/ha) was estimated at 35.0 [20.9, 55.9] yr. During the first 40 yr, the contribution of the long-lived pioneer species Xylopia nitida, Goupia glabra, and Laetia procera to the aboveground carbon stock increased continuously. Secondary forest mean-canopy height measured by lidar increased by 1.14 m in 8 yr, a canopy-height increase consistent with an aboveground carbon accumulation of 7.1 Mg C/ha (or 0.89 Mg C·ha-1 ·yr-1 ) during this period. Long-term AGC accumulation rate in Costa Rica was almost twice as fast as at our site in French Guiana. This may reflect higher fertility of Central American forest communities or a better adaptation of the forest tree community to intense and frequent disturbances. This finding may have important consequences for scaling-up carbon uptake estimates to continental scales.

Improving plant allometry by fusing forest models and remote sensing.

Allometry determines how tree shape and function scale with each other, related through size. Allometric relationships help scale processes from the individual to the global scale and constitute a core component of vegetation models. Allometric relationships have been expected to emerge from optimisation theory, yet this does not suitably predict empirical data. Here we argue that the fusion of high-resolution data, such as those derived from airborne laser scanning, with individual-based forest modelling offers insight into how plant size contributes to large-scale biogeochemical processes. We review the challenges in allometric scaling, how they can be tackled by advances in data-model fusion, and how individual-based models can serve as data integrators for dynamic global vegetation models.

New formula and conversion factor to compute basic wood density of tree species using a global wood technology database.

PREMISE OF THE STUDY: Basic wood density is an important ecological trait for woody plants. It is used to characterize species performance and fitness in community ecology and to compute tree and forest biomass in carbon cycle studies. While wood density has been historically measured at 12% moisture, it is convenient for ecological purposes to convert this measure to basic wood density, i.e., the ratio of dry mass over green volume. Basic wood density can then be used to compute tree dry biomass from living tree volume. METHODS: Here, we derive a new exact formula to compute the basic wood density Db from the density at moisture content w denoted Dw , the fiber saturation point S, and the volumetric shrinkage coefficient R. We estimated a new conversion factor using a global wood technology database where values to use this formula are available for 4022 trees collected in 64 countries (mostly tropical) and representing 872 species. KEY RESULTS: We show that previous conversion factors used to convert densities at 12% moisture into basic wood densities are inconsistent. Based on theory and data, we found that basic wood density could be inferred from the density at 12% moisture using the following formula: Db = 0.828D12 . This value of 0.828 provides basic wood density estimates 4-5% smaller than values inferred from previous conversion factors. CONCLUSIONS: This new conversion factor should be used to derive basic wood densities in global wood density databases. Its use would prevent overestimating global forest carbon stocks and allow predicting better tree species community dynamics from wood density.