Species Matter: Wood Density Influences Tropical Forest Biomass at Multiple Scales

Evolutionary history shapes variation of wood density of tree species across the world

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density.

Dataset about Mexico's forest diversity: Site locations of tree species, wood densities, and geographic database of forest-vegetation provinces

A dataset about three topics is provided, as a follow-up to the article "Mexico's forest diversity: common tree species and proposed forest-vegetation provinces" by Ricker et al. [1]. Firstly, 6927 site locations are provided for 22,532 trees of 1452 species. Secondly, measurements of basic wood-densities are reported for 779 tree species, obtained from 5256 trunk-core samples from Mexico's national forest inventory, and ranging from 0.05 to 0.93 g/cm3. Third, the data and maps of the forest-vegetation provinces from [1] were updated with the new cartography of Mexico's vegetation and land use (base year 2018). The maps are available now in an adjusted presentation as a shapefile-set for ArcGIS, as well as map-package and image files.

Sensing Forests Directly: The Power of Permanent Plots

The need to measure, monitor, and understand our living planet is greater than ever. Yet, while many technologies are applied to tackle this need, one developed in the 19th century is transforming tropical ecology. Permanent plots, in which forests are directly sensed tree-by-tree and species-by-species, already provide a global public good. They could make greater contributions still by unlocking our potential to understand future ecological change, as the more that computational and remote technologies are deployed the greater the need to ground them with direct observations and the physical, nature-based skills of those who make them. To achieve this requires building profound connections with forests and disadvantaged communities and sustaining these over time. Many of the greatest needs and opportunities in tropical forest science are therefore not to be found in space or in silico, but in vivo, with the people, places and plots who experience nature directly. These are fundamental to understanding the health, predicting the future, and exploring the potential of Earth's richest ecosystems. Now is the time to invest in the tropical field research communities who make so much possible.

Toward a forest biomass reference measurement system for remote sensing applications

Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA-ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation. A permanent, global, in situ, site-based forest biomass reference measurement system relying on ground data of the highest possible quality is therefore needed. Here, we have assembled a list of almost 200 high-quality sites through an in-depth review of the literature and expert knowledge. In this study, we explore how representative these sites are in terms of their coverage of environmental conditions, geographical space and biomass-related forest structure, compared to those experienced by forests worldwide. This work also aims at identifying which sites are the most representative, and where to invest to improve the representativeness of the proposed system. We show that the environmental coverage of the system does not seem to improve after at least the 175 most representative sites are included, but geographical and structural coverages continue to improve as more sites are added. We highlight the areas of poor environmental, geographical, or structural coverage, including, but not limited to, Canada, the western half of the USA, Mexico, Patagonia, Angola, Zambia, eastern Russia, and tropical and subtropical highlands (e.g. in Colombia, the Himalayas, Borneo, Papua). For the proposed system to succeed, we stress that (1) data must be collected and processed applying the same standards across all countries and continents; (2) system establishment and management must be inclusive and equitable, with careful consideration of working conditions; and (3) training and site partner involvement in downstream activities should be mandatory.

Soil geochemistry - and not topography - as a major driver of carbon allocation, stocks, and dynamics in forests and soils of African tropical montane ecosystems

The lack of field-based data in the tropics limits our mechanistic understanding of the drivers of net primary productivity (NPP) and allocation. Specifically, the role of local edaphic factors - such as soil parent material and topography controlling soil fertility as well as water and nutrient fluxes - remains unclear and introduces substantial uncertainty in understanding net ecosystem productivity and carbon (C) stocks. Using a combination of vegetation growth monitoring and soil geochemical properties, we found that soil fertility parameters reflecting the local parent material are the main drivers of NPP and C allocation patterns in tropical montane forests, resulting in significant differences in below- to aboveground biomass components across geochemical (soil) regions. Topography did not constrain the variability in C allocation and NPP. Soil organic C stocks showed no relation to C input in tropical forests. Instead, plant C input seemingly exceeded the maximum potential of these soils to stabilize C. We conclude that, even after many millennia of weathering and the presence of deeply developed soils, above- and belowground C allocation in tropical forests, as well as soil C stocks, vary substantially due to the geochemical properties that soils inherit from parent material.

Lidar-Based Aboveground Biomass Estimations for the Maya Archaeological Site of Yaxnohcah, Campeche, Mexico

This study aims to provide a technique applied to archaeology to estimate lidar-based aboveground biomass (AGB) in contemporary tropical forests surrounding archaeological sites. Accurate AGB estimations are important to serve as a baseline to evaluate the wood resources that the ancient Maya could have used for the development of their cities. A lidar processing model is proposed to study the contemporary forest surrounding the Yaxnohcah archaeological site. As tropical forests are highly diverse environments where species are not uniformly distributed, it was necessary to consider the variation within the forest to obtain accurate AGB. Four vegetation communities were defined from a supervised classification of a Sentinel-2 satellite image. A stratified sample was then selected for the field survey that comprised 73 transects of 500 m2 each. To estimate the transect AGB, we used an allometric equation that requires diameter, height, and wood density measurements for identified species. Linear-derived models provided the relationship between field data with lidar statistics for each vegetation type. Predicted average AGB values agreed with those obtained in the field. However, they significantly differed between vegetation types, averaging 83 Mg/ha for lowland forest, 178 for transition forest, and 215 for upland forest communities. From those results, we created a map with wall-to-wall AGB estimates following the distribution of vegetation classes that could complement archaeological research of past land use. Vegetation classification also helped determine that there is a spatial relationship between vegetation communities and the distribution of archaeological settlement features for the ancient city of Yaxnohcah.

8000-year doubling of Midwestern forest biomass driven by population- and biome-scale processes

Changes in woody biomass over centuries to millennia are poorly known, leaving unclear the magnitude of terrestrial carbon fluxes before industrial-era disturbance. Here, we statistically reconstructed changes in woody biomass across the upper Midwestern region of the United States over the past 10,000 years using a Bayesian model calibrated to preindustrial forest biomass estimates and fossil pollen records. After an initial postglacial decline, woody biomass nearly doubled during the past 8000 years, sequestering 1800 teragrams. This steady accumulation of carbon was driven by two separate ecological responses to regionally changing climate: the spread of forested biomes and the population expansion of high-biomass tree species within forests. What took millennia to accumulate took less than two centuries to remove: Industrial-era logging and agriculture have erased this carbon accumulation.

Topography, Diversity, and Forest Structure Attributes Drive Aboveground Carbon Storage in Different Forest Types in Northeast China

Forests regulate air quality and respond to climate change by storing carbon. Assessing the driving factors of forest aboveground carbon (AGC) storage is of great importance for forest management. We assumed that different forest types would affect the relationship between species richness, stand density, individual tree size variation, and AGC. In order to test and verify it, we analyzed the inventory data of 206 fixed plots (20 m × 20 m) of Jingouling Forest Farm, taking advantage of the piecewise structural equation model (pSEM) to explore the effects of species diversity, stand structure attributes, and topography on the AGC storage in the Wangqing Forest in Jilin Province. In addition, in this study, we aimed to investigate whether the fixed factors (species diversity, stand structure attributes, and topography) influenced AGC storage more significantly than the random factor (forest type). According to the results of pSEM, the selected factors jointly explain the impact on 33% of AGC storage. The relationship between stand density and AGC is positive, and the impact of individual tree size variation on AGC storage is negative. Species richness has direct and indirect impacts on AGC storage, and the indirect impact is more significant through individual tree size variation. Both elevation and slope are significantly negatively associated with AGC storage. Forest type explains the impact on 12% of AGC storage, which means the relationship between AGC and predictors varies across forest types. The results provide a scientific basis for the protection and management decision of natural forests in northeastern China.

Plant Functional Diversity Is Linked to Carbon Storage in Deciduous Dipterocarp Forest Edges in Northern Thailand

Studies of carbon storage using functional traits have shown that it is strongly affected by functional diversity. We explored the effects of functional diversity on carbon storage at the edge of a deciduous dipterocarp forest (DDF) ecosystem in Thailand. Aboveground biomass carbon (AGBC), soil organic carbon (SOC), and total ecosystem carbon (TEC) were used as indicators of carbon storage. Five functional traits were measured in 49 plant species to calculate the community-weighted mean (CWM) and Rao’s quadratic diversity (FQ). We assessed which functional diversity metrics best-explained carbon storage. The results indicated that AGBC had a significant, positive relationship with the FQ of wood density, and a negative relationship with the CWM of leaf thickness. SOC had a significant, negative association with the FQ of leaf thickness and a positive relationship with the CWM of specific leaf area (SLA). TEC was best predicted by increases in the FQ of wood density and the CWM of SLA. These findings indicate that CWM and FQ are important for understanding how plant traits influence carbon storage in DDF edge ecosystems and suggest that promoting a high diversity of species with dissimilar wood density and high SLA may increase carbon storage in chronically disturbed DDF ecosystems.

Ecological legacies of past human activities in Amazonian forests

In Amazonia, human activities that occurred hundreds of years ago in the pre-European era can leave long-lasting effects on the forests - termed ecological legacies. These legacies include the intentional or nonintentional enrichment or depletion of certain species. The persistence of these legacies through time varies by species, and creates complex long-term trajectories of post-disturbance succession that affect ecosystem processes for hundreds of years. Most of our knowledge of Amazonian biodiversity and carbon storage comes from a series of several hundred forest plots, and we only know the disturbance history of four of them. More empirical data are needed to determine the degree to which past human activities and their ecological legacies affect our current understanding of Amazonian forest ecology.

New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar

A large portion of the terrestrial vegetation carbon stock is stored in the above-ground biomass (AGB) of tropical forests, but the exact amount remains uncertain, partly owing to the lack of measurements. To date, accessible peer-reviewed data are available for just 10 large tropical trees in the Amazon that have been harvested and directly measured entirely via weighing. Here, we harvested four large tropical rainforest trees (stem diameter: 0.6-1.2 m, height: 30-46 m, AGB: 3960-18 584 kg) in intact old-growth forest in East Amazonia, and measured above-ground green mass, moisture content and woody tissue density. We first present rare ecological insights provided by these data, including unsystematic intra-tree variations in density, with both height and radius. We also found the majority of AGB was usually found in the crown, but varied from 42 to 62%. We then compare non-destructive approaches for estimating the AGB of these trees, using both classical allometry and new lidar-based methods. Terrestrial lidar point clouds were collected pre-harvest, on which we fitted cylinders to model woody structure, enabling retrieval of volume-derived AGB. Estimates from this approach were more accurate than allometric counterparts (mean tree-scale relative error: 3% versus 15%), and error decreased when up-scaling to the cumulative AGB of the four trees (1% versus 15%). Furthermore, while allometric error increased fourfold with tree size over the diameter range, lidar error remained constant. This suggests error in these lidar-derived estimates is random and additive. Were these results transferable across forest scenes, terrestrial lidar methods would reduce uncertainty in stand-scale AGB estimates, and therefore advance our understanding of the role of tropical forests in the global carbon cycle.

Big trees drive forest structure patterns across a lowland Amazon regrowth gradient

Degraded Amazonian forests can take decades to recover and the ecological results of natural regeneration are still uncertain. Here we use field data collected across 15 lowland Amazon smallholder properties to examine the relationships between forest structure, mammal diversity, regrowth type, regrowth age, topography and hydrology. Forest structure was quantified together with mammal diversity in 30 paired regrowth-control plots. Forest regrowth stage was classified into three groups: late second-regrowth, early second-regrowth and abandoned pasture. Basal area in regrowth plots remained less than half that recorded in control plots even after 20–25 years. Although basal area did increase in sequence from pasture, early to late-regrowth plots, there was a significant decline in basal area of late-regrowth control plots associated with a decline in the proportion of large trees. Variation in different forest structure responses was explained by contrasting variables, with the proportion of small trees (DBH < 20 cm) most strongly explained by topography (altitude and slope) whereas the proportion of large trees (DBH > 60 cm) was explained by plot type (control vs. regrowth) and regrowth class. These findings support calls for increased efforts to actively conserve large trees to avoid retrogressive succession around edges of degraded Amazon forests.

Plant traits controlling growth change in response to a drier climate

Plant traits are increasingly being used to improve prediction of plant function, including plant demography. However, the capability of plant traits to predict demographic rates remains uncertain, particularly in the context of trees experiencing a changing climate. Here we present data combining 17 plant traits associated with plant structure, metabolism and hydraulic status, with measurements of long-term mean, maximum and relative growth rates for 176 trees from the world's longest running tropical forest drought experiment. We demonstrate that plant traits can predict mean annual tree growth rates with moderate explanatory power. However, only combinations of traits associated more directly with plant functional processes, rather than more commonly employed traits like wood density or leaf mass per area, yield the power to predict growth. Critically, we observe a shift from growth being controlled by traits related to carbon cycling (assimilation and respiration) in well-watered trees, to traits relating to plant hydraulic stress in drought-stressed trees. We also demonstrate that even with a very comprehensive set of plant traits and growth data on large numbers of tropical trees, considerable uncertainty remains in directly interpreting the mechanisms through which traits influence performance in tropical forests.

Development of formaldehyde-free bio-board produced from mushroom mycelium and substrate waste

Synthetic adhesives in the plywood industry are usually volatile compounds such as formaldehyde-based chemical which are costly and hazardous to health and the environment. This phenomenon promotes an interest in developing bio-boards without synthetic adhesives. This study proposed a novel application of natural mycelium produced during mushroom cultivation as natural bio-adhesive material that convert spent mushroom substrate (SMS) into high-performance bio-board material. Different types of spent mushroom substrates were compressed with specific designed mould with optimal temperature at 160 °C and 10 mPa for 20 min. The bio-board made from Ganoderma lucidum SMS had the highest internal bonding strength up to 2.51 mPa. This is far above the 0.4-0.8 range of China and US national standards. In addition, the material had high water and fire resistance, high bonding and densified structures despite free of any adhesive chemicals. These properties and the low cost one step procedure show the potential as a zero-waste economy chain for sustainable agricultural practice for waste and remediation.

Diversity, distribution and dynamics of large trees across an old-growth lowland tropical rain forest landscape

Large trees, here defined as ≥60 cm trunk diameter, are the most massive organisms in tropical rain forest, and are important in forest structure, dynamics and carbon cycling. The status of large trees in tropical forest is unclear, with both increasing and decreasing trends reported. We sampled across an old-growth tropical rain forest landscape at the La Selva Biological Station in Costa Rica to study the distribution and performance of large trees and their contribution to forest structure and dynamics. We censused all large trees in 238 0.50 ha plots, and also identified and measured all stems ≥10 cm diameter in 18 0.50 ha plots annually for 20 years (1997–2017). We assessed abundance, species diversity, and crown conditions of large trees in relation to soil type and topography, measured the contribution of large trees to stand structure, productivity, and dynamics, and analyzed the decadal population trends of large trees. Large trees accounted for 2.5% of stems and ~25% of mean basal area and Estimated Above-Ground Biomass, and produced ~10% of the estimated wood production. Crown exposure increased with stem diameter but predictability was low. Large tree density was about twice as high on more-fertile flat sites compared to less fertile sites on slopes and plateaus. Density of large trees increased 27% over the study interval, but the increase was restricted to the flat more-fertile sites. Mortality and recruitment differed between large trees and smaller stems, and strongly suggested that large tree density was affected by past climatic disturbances such as large El Niño events. Our results generally do not support the hypothesis of increasing biomass and turnover rates in tropical forest. We suggest that additional landscape-scale studies of large trees are needed to determine the generality of disturbance legacies in tropical forest study sites.

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.