Biomass allometric models for Larix rupprechtii based on Kosak's taper curve equations and nonlinear seemingly unrelated regression

The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass model. Therefore, it is still an urgent scientific problem to build a high-precision biomass model system. A dataset of 114 trees was destructively sampled to obtain dry biomass components, including stems, branches, and foliage, and taper measurements to explore the applicability of biomass components to allometric scaling laws and develop a new system of additive models with the diameter in relative height (DRH) for each component of a Larch (Larix principis-rupprechtii Mayr) plantation in northern China. The variable exponential taper equations were modelled using nonlinear regression. In addition, applying nonlinear regression and nonlinear seemingly unrelated regression (NSUR) enabled the development of biomass allometric models and the system of additive models with DRH for each component. The results showed that the Kozak's (II) 2004 variable exponential taper equation could accurately describe the stem shape and diameter in any height of stem. When the diameters in relative height were D_0.2, D_0.5, and D_0.5 for branches, stems, and foliage, respectively, the allometric exponent of the stems and branches was the closest to the scaling relations predicted by the MST, and the allometric exponent of foliage was the most closely related to the scaling relations predicted by geometry theory. Compared with the nonlinear regression, the parameters of biomass components estimated by NSUR were lower, and it was close to the theoretical value and the most precise at forecasting. In the study of biomass process modelling, utilizing the DRH by a variable exponential taper equation can confirm the general biological significance more than the DBH of a fixed position.

A 3D approach to model the taper of irregular tree stems: making plots biomass estimates comparable in tropical forests

In tropical forests, the high proportion of trees showing irregularities at the stem base complicates forest monitoring. For example, in the presence of buttresses, the height of the point of measurement (H_POM ) of the stem diameter (D_POM ) is raised from 1.3 m, the standard breast height, up to a regular part of the stem. While D_POM is the most important predictor for tree aboveground biomass (AGB) estimates, the lack of harmonized H_POM for irregular trees in forest inventory increases the uncertainty in plot-level AGB stock and stock change estimates. In this study, we gathered an original non-destructive three-dimensional (3D) data set collected with terrestrial laser scanning and close range terrestrial photogrammetry tools in three sites in central Africa. For the 228 irregularly shaped stems sampled, we developed a set of taper models to harmonize H_POM by predicting the equivalent diameter at breast height (DBH') from a D_POM measured at any height. We analyzed the effect of using DBH' on tree-level and plot-level AGB estimates. To do so, we used destructive AGB data for 140 trees and forest inventory data from eight 1-ha plots in the Republic of Congo. Our results showed that our best simple taper model predicts DBH' with a relative mean absolute error of 3.7% (R²  = 0.98) over a wide D_POM range of 17-249 cm. Based on destructive AGB data, we found that the AGB allometric model calibrated with harmonized H_POM data was more accurate than the conventional local and pantropical models. At the plot level, the comparison of AGB stock estimates with and without H_POM harmonization showed an increasing divergence with the increasing share of irregular stems (up to -15%). The harmonization procedure developed in this study could be implemented as a standard practice for AGB monitoring in tropical forests as no additional forest inventory measurements is required. This would probably lead to important revisions of the AGB stock estimates in regions having a large number of irregular tree stems and increase their carbon sink estimates. The growing use of three-dimensional (3D) data offers new opportunities to extend our approach and further develop general taper models in other tropical regions.

Impact of rising temperatures on the biomass of humid old-growth forests of the world

BACKGROUND

Understanding how warming influence above-ground biomass in the world's forests is necessary for quantifying future global carbon budgets. A climate-driven decrease in future carbon stocks could dangerously strengthen climate change. Empirical methods for studying the temperature response of forests have important limitations, and modelling is needed to provide another perspective. Here we evaluate the impact of rising air temperature on the future above-ground biomass of old-growth forests using a model that explains well the observed current variation in the above-ground biomass over the humid lowland areas of the world based on monthly air temperature.

RESULTS

Applying this model to the monthly air temperature data for 1970-2000 and monthly air temperature projections for 2081-2100, we found that the above-ground biomass of old-growth forests is expected to decrease everywhere in the humid lowland areas except boreal regions. The temperature-driven decrease is estimated at 41% in the tropics and at 29% globally.

CONCLUSIONS

Our findings suggest that rising temperatures impact the above-ground biomass of old-growth forests dramatically. However, this impact could be mitigated by fertilization effects of increasing carbon dioxide concentration in the atmosphere and nitrogen deposition.

Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass

Tropical forests vary widely in biomass carbon (C) stocks and fluxes even after controlling for forest age. A mechanistic understanding of this variation is critical to accurately predicting responses to global change. We review empirical studies of spatial variation in tropical forest biomass, productivity and woody residence time, focusing on mature forests. Woody productivity and biomass decrease from wet to dry forests and with elevation. Within lowland forests, productivity and biomass increase with temperature in wet forests, but decrease with temperature where water becomes limiting. Woody productivity increases with soil fertility, whereas residence time decreases, and biomass responses are variable, consistent with an overall unimodal relationship. Areas with higher disturbance rates and intensities have lower woody residence time and biomass. These environmental gradients all involve both direct effects of changing environments on forest C fluxes and shifts in functional composition - including changing abundances of lianas - that substantially mitigate or exacerbate direct effects. Biogeographic realms differ significantly and importantly in productivity and biomass, even after controlling for climate and biogeochemistry, further demonstrating the importance of plant species composition. Capturing these patterns in global vegetation models requires better mechanistic representation of water and nutrient limitation, plant compositional shifts and tree mortality.

Promoting sustainability education through hands-on approaches: a tree carbon sequestration exercise in a Singapore green space

During a university class project related to climate change mitigation strategies, we utilized a university green space as a "living laboratory" for collaborative learning exercise to estimate landscape-level carbon biomass storage. The key objective of the exercise was to foster sustainability awareness with regard to the effectiveness of tree-planting initiatives to offset carbon emissions. Collaborative learning is a process by which students work together in small groups to accomplish a common goal. As experiences are active, social and student-owned, the process leads to the development of a variety of cognitive and transferable skills that are beneficial in academia and the workplace. Through data collection/analysis, the carbon biomass exercise not only allowed students to assess critically the efficacy of a tree-planting initiative as a means to sequester carbon, but they became aware of the difficulties in performing research on complex environmental issues. The intention of the research was to give students an opportunity to practice data collection, data analysis, problem solving, teamwork, communication and scientific literacy skills, meanwhile utilizing the campus open green space to enhance the knowledge discovery process. Informal assessment and discussions with students demonstrated that the activity was successful in reaching a wide range of students with varying backgrounds and initial attitudes about climate change mitigating strategies, which was our objective. Our case study demonstrates how learning objectives can be integrated with university sustainability initiatives to improve learning and student engagement. Finally, we see green spaces as dynamic settings for learning about physical processes and issues related to environmental management and sustainability.

What Would a Tree Say About Its Size?

When developing theories, designing studies, and interpreting the results, researchers are influenced by their perception of tree size. For example, we may compare two trees of the same size belonging to different species, and attribute any differences to dissimilarities between the species. However, the meaning of “same size” depends on the measures of size used. Wood density influences certain measures, such as biomass, but does not influence e.g., trunk diameter. Therefore, the choice of the measure of size can reverse any conclusions. Hence, it is import to consider which measure of size should be used. I argue that the most common measure of size, i.e., trunk diameter, is often a bad choice when wood density varies, as diameter is then not directly related to processes important in evolution. When trees with equal diameters but differing wood densities are compared, the tree with denser wood is larger if the measure of size is related to construction cost or trunk strength, a proxy of leaf area. From this perspective, the comparison is then conducted between a biologically larger heavy-wooded tree and a smaller light-wooded tree, and the differences between the trees may be caused by size instead of wood density. Therefore, trunk biomass and strength may often be more suitable measures of size, as they reflect the construction cost and biomechanical potency linked to leaf area crown height, often too challenging to estimate more directly. To assess how commonly inadequate measures of tree size have been used, I reviewed 10 highly cited journal articles. None of these 10 articles discussed the impact of wood density on biological size, and instead based the analyses on diameters or basal areas. This led to conclusions that could change or even reverse in an analysis based on biomass or strength. Overall, I do not suggest avoiding the use of diameter, but I recommend considering result sensitivity to the measure of size, particularly in studies ones with variable wood densities.

Active restoration accelerates the carbon recovery of human-modified tropical forests

More than half of all tropical forests are degraded by human impacts, leaving them threatened with conversion to agricultural plantations and risking substantial biodiversity and carbon losses. Restoration could accelerate recovery of aboveground carbon density (ACD), but adoption of restoration is constrained by cost and uncertainties over effectiveness. We report a long-term comparison of ACD recovery rates between naturally regenerating and actively restored logged tropical forests. Restoration enhanced decadal ACD recovery by more than 50%, from 2.9 to 4.4 megagrams per hectare per year. This magnitude of response, coupled with modal values of restoration costs globally, would require higher carbon prices to justify investment in restoration. However, carbon prices required to fulfill the 2016 Paris climate agreement [$40 to $80 (USD) per tonne carbon dioxide equivalent] would provide an economic justification for tropical forest restoration.

Hurricane-Induced Rainfall is a Stronger Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds

Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems.

Testing for changes in biomass dynamics in large-scale forest datasets

Tropical forest responses to climate and atmospheric change are critical to the future of the global carbon budget. Recent studies have reported increases in estimated above-ground biomass (EAGB) stocks, productivity, and mortality in old-growth tropical forests. These increases could reflect a shift in forest functioning due to global change and/or long-lasting recovery from past disturbance. We introduce a novel approach to disentangle the relative contributions of these mechanisms by decomposing changes in whole-plot biomass fluxes into contributions from changes in the distribution of gap-successional stages and changes in fluxes for a given stage. Using 30 years of forest dynamic data at Barro Colorado Island, Panama, we investigated temporal variation in EAGB fluxes as a function of initial EAGB (EAGB_i ) in 10 × 10 m quadrats. Productivity and mortality fluxes both increased strongly with initial quadrat EAGB. The distribution of EAGB (and thus EAGB_i ) across quadrats hardly varied over 30 years (and seven censuses). EAGB fluxes as a function of EAGB_i varied largely and significantly among census intervals, with notably higher productivity in 1985-1990 associated with recovery from the 1982-1983 El Niño event. Variation in whole-plot fluxes among census intervals was explained overwhelmingly by variation in fluxes as a function of EAGB_i , with essentially no contribution from changes in EAGB_i distributions. The high observed temporal variation in productivity and mortality suggests that this forest is very sensitive to climate variability. There was no consistent long-term trend in productivity, mortality, or biomass in this forest over 30 years, although the temporal variability in productivity and mortality was so strong that it could well mask a substantial trend. Accurate prediction of future tropical forest carbon budgets will require accounting for disturbance-recovery dynamics and understanding temporal variability in productivity and mortality.

Estimating Urban Vegetation Biomass from Sentinel-2A Image Data

Urban vegetation biomass is a key indicator of the carbon storage and sequestration capacity and ecological effect of an urban ecosystem. Rapid and effective monitoring and measurement of urban vegetation biomass provide not only an understanding of urban carbon circulation and energy flow but also a basis for assessing the ecological function of urban forest and ecology. In this study, field observations and Sentinel-2A image data were used to construct models for estimating urban vegetation biomass in the case study of the east Chinese city of Xuzhou. Results show that (1) Sentinel-2A data can be used for urban vegetation biomass estimation; (2) compared with the Boruta based multiple linear regression models, the stepwise regression models—also multiple linear regression models—achieve better estimations (RMSE = 7.99 t/hm2 for low vegetation, 45.66 t/hm2 for broadleaved forest, and 6.89 t/hm2 for coniferous forest); (3) the models for specific vegetation types are superior to the models for all-type vegetation; and (4) vegetation biomass is generally lowest in September and highest in January and December. Our study demonstrates the potential of the free Sentinel-2A images for urban ecosystem studies and provides useful insights on urban vegetation biomass estimation with such satellite remote sensing data.

Volume equations for Khaya ivorensis A. Chev. plantations in Brazil

African mahogany (Khaya spp.) plantations are in expansion in Brazil and in the world. This fact justifies the need for studies related to its growth and yield. This paper aimed to evaluate the performance of single-entry and double-entry models for estimating merchantable and total volume for Khaya ivorensis plantations before the first thinning (7 years) and expected final cut (15 years). Volume data was from 100 and 46 trees in Minas Gerais and Pará states, respectively, by using an electronic dendrometer (Criterion RD 1000). Observed volumes were calculated by Smalian's formula. To validate the optical dendrometer, 10 trees were felled and had their volume measured, and compared with the volumes measured indirectly. The results showed that observed and estimated volumes were statistically equal, and that double-entry models were more precise than single-entry models. Schumacher and Hall model was the best equation to estimate merchantable volume for first thinning and for final cut in Minas Gerais stands. Spurr logarithmized model was the best equation to estimate total volume for first thinning and Spurr model for final cut in Pará stands. All chosen equations can be used to quantify merchantable and total volumes of Khaya ivorensis grown under similar conditions.

Role of tree size in moist tropical forest carbon cycling and water deficit responses

Drought disproportionately affects larger trees in tropical forests, but implications for forest composition and carbon (C) cycling in relation to dry season intensity remain poorly understood. In order to characterize how C cycling is shaped by tree size and drought adaptations and how these patterns relate to spatial and temporal variation in water deficit, we analyze data from three forest dynamics plots spanning a moisture gradient in Panama that have experienced El Niño droughts. At all sites, aboveground C cycle contributions peaked below 50-cm stem diameter, with stems ≥ 50 cm accounting for on average 59% of live aboveground biomass, 45% of woody productivity and 49% of woody mortality. The dominance of drought-avoidance strategies increased interactively with stem diameter and dry season intensity. Although size-related C cycle contributions did not vary systematically across the moisture gradient under nondrought conditions, woody mortality of larger trees was disproportionately elevated under El Niño drought stress. Thus, large (> 50 cm) stems, which strongly mediate but do not necessarily dominate C cycling, have drought adaptations that compensate for their more challenging hydraulic environment, particularly in drier climates. However, these adaptations do not fully buffer the effects of severe drought, and increased large tree mortality dominates ecosystem-level drought responses.

Trade-offs between carbon stocks and timber recovery in tropical forests are mediated by logging intensity

Forest degradation accounts for ~70% of total carbon losses from tropical forests. Substantial emissions are from selective logging, a land-use activity that decreases forest carbon density. To maintain carbon values in selectively logged forests, climate change mitigation policies and government agencies promote the adoption of reduced-impact logging (RIL) practices. However, whether RIL will maintain both carbon and timber values in managed tropical forests over time remains uncertain. In this study, we quantify the recovery of timber stocks and aboveground carbon at an experimental site where forests were subjected to different intensities of RIL (4, 8, and 16 trees/ha). Our census data span 20 years postlogging and 17 years after the liberation of future crop trees from competition in a tropical forest on the Guiana Shield, a globally important forest carbon reservoir. We model recovery of timber and carbon with a breakpoint regression that allowed us to capture elevated tree mortality immediately after logging. Recovery rates of timber and carbon were governed by the presence of residual trees (i.e., trees that persisted through the first harvest). The liberation treatment stimulated faster recovery of timber albeit at a carbon cost. Model results suggest a threshold logging intensity beyond which forests managed for timber and carbon derive few benefits from RIL, with recruitment and residual growth not sufficient to offset losses. Inclusion of the breakpoint at which carbon and timber gains outpaced postlogging mortality led to high predictive accuracy, including out-of-sample R² values >90%, and enabled inference on demographic changes postlogging. Our modeling framework is broadly applicable to studies that aim to quantify impacts of logging on forest recovery. Overall, we demonstrate that initial mortality drives variation in recovery rates, that the second harvest depends on old growth wood, and that timber intensification lowers carbon stocks.

Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9–12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China.

Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds

The estimation of tree biomass and the products that can be obtained from a tree stem have focused forest research for more than two centuries. Traditionally, measurements of the entire tree bole were expensive or inaccurate, even when sophisticated remote sensing techniques were used. We propose a fast and accurate procedure for measuring diameters along the merchantable portion of the stem at any given height. The procedure uses unreferenced photos captured with a consumer grade camera. A photogrammetric point cloud (PPC) is produced from the acquired images using structure from motion, which is a computer vision range imaging technique. A set of 18 loblolly pines (Pinus taeda Lindl.) from east Louisiana, USA, were photographed, subsequently cut, and the diameter measured every meter. The same diameters were measured on the point cloud with AutoCAD Civil3D. The ground point cloud reconstruction provided useful information for at most 13 m along the stem. The PPC measurements are biased, overestimating real diameters by 17.2 mm, but with a reduced standard deviation (8.2%). A linear equation with parameters of the error at a diameter at breast height (d1.3) and the error of photogrammetric rendering reduced the bias to 1.4 mm. The usability of the PPC measurements in taper modeling was assessed with four models: Max and Burkhart [1], Baldwin and Feduccia [2], Lenhart et al. [3], and Kozak [4]. The evaluation revealed that the data fit well with all the models (R2 ≥ 0.97), with the Kozak and the Baldwin and Feduccia performing the best. The results support the replacement of taper with PPC, as faster, and more accurate and precise product estimations are expected.

Socio-ecological costs of Amazon nut and timber production at community household forests in the Bolivian Amazon

The Bolivian Amazon holds a complex configuration of people and forested landscapes in which communities hold secure tenure rights over a rich ecosystem offering a range of livelihood income opportunities. A large share of this income is derived from Amazon nut (Bertholletia excelsa). Many communities also have long-standing experience with community timber management plans. However, livelihood needs and desires for better living conditions may continue to place these resources under considerable stress as income needs and opportunities intensify and diversify. We aim to identify the socioeconomic and biophysical factors determining the income from forests, husbandry, off-farm and two keystone forest products (i.e., Amazon nut and timber) in the Bolivian Amazon region. We used structural equation modelling tools to account for the complex inter-relationships between socioeconomic and biophysical factors in predicting each source of income. The potential exists to increase incomes from existing livelihood activities in ways that reduce dependency upon forest resources. For example, changes in off-farm income sources can act to increase or decrease forest incomes. Market accessibility, social, financial, and natural and physical assets determined the amount of income community households could derive from Amazon nut and timber. Factors related to community households' local ecological knowledge, such as the number of non-timber forest products harvested and the number of management practices applied to enhance Amazon nut production, defined the amount of income these households could derive from Amazon nut and timber, respectively. The (inter) relationships found among socioeconomic and biophysical factors over income shed light on ways to improve forest-dependent livelihoods in the Bolivian Amazon. We believe that our analysis could be applicable to other contexts throughout the tropics as well.

The ecology, distribution, conservation and management of large old trees

Large old trees are some of the most iconic biota on earth and are integral parts of many terrestrial ecosystems including those in tropical, temperate and boreal forests, deserts, savannas, agro-ecological areas, and urban environments. In this review, we provide new insights into the ecology, function, evolution and management of large old trees through broad cross-disciplinary perspectives from literatures in plant physiology, growth and development, evolution, habitat value for fauna and flora, and conservation management. Our review reveals that the diameter, height and longevity of large old trees varies greatly on an inter-specific basis, thereby creating serious challenges in defining large old trees and demanding an ecosystem- and species-specific definition that will only rarely be readily transferable to other species or ecosystems. Such variation is also manifested by marked inter-specific differences in the key attributes of large old trees (beyond diameter and height) such as the extent of buttressing, canopy architecture, the extent of bark micro-environments and the prevalence of cavities. We found that large old trees play an extraordinary range of critical ecological roles including in hydrological regimes, nutrient cycles and numerous ecosystem processes. Large old trees strongly influence the spatial and temporal distribution and abundance of individuals of the same species and populations of numerous other plant and animal species. We suggest many key characteristics of large old trees such as extreme height, prolonged lifespans, and the presence of cavities - which confer competitive and evolutionary advantages in undisturbed environments - can render such trees highly susceptible to a range of human influences. Large old trees are vulnerable to threats ranging from droughts, fire, pests and pathogens, to logging, land clearing, landscape fragmentation and climate change. Tackling such diverse threats is challenging because they often interact and manifest in different ways in different ecosystems, demanding targeted species- or ecosystem-specific responses. We argue that novel management actions will often be required to protect existing large old trees and ensure the recruitment of new cohorts of such trees. For example, fine-scale tree-level conservation such as buffering individual stems will be required in many environments such as in agricultural areas and urban environments. Landscape-level approaches like protecting places where large old trees are most likely to occur will be needed. However, this brings challenges associated with likely changes in tree distributions associated with climate change, because long-lived trees may presently exist in places unsuitable for the development of new cohorts of the same species. Appropriate future environmental domains for a species could exist in new locations where it has never previously occurred. The future distribution and persistence of large old trees may require controversial responses including assisted migration via seed or seedling establishment in new locales. However, the effectiveness of such approaches may be limited where key ecological features of large old trees (such as cavity presence) depend on other species such as termites, fungi and bacteria. Unless other species with similar ecological roles are present to fulfil these functions, these taxa might need to be moved concurrently with the target tree species.

Drivers of aboveground wood production in a lowland tropical forest of West Africa: teasing apart the roles of tree density, tree diversity, soil phosphorus, and historical logging

Tropical forests currently play a key role in regulating the terrestrial carbon cycle and abating climate change by storing carbon in wood. However, there remains considerable uncertainty as to whether tropical forests will continue to act as carbon sinks in the face of increased pressure from expanding human activities. Consequently, understanding what drives productivity in tropical forests is critical. We used permanent forest plot data from the Gola Rainforest National Park (Sierra Leone) – one of the largest tracts of intact tropical moist forest in West Africa – to explore how (1) stand basal area and tree diversity, (2) past disturbance associated with past logging, and (3) underlying soil nutrient gradients interact to determine rates of aboveground wood production (AWP). We started by statistically modeling the diameter growth of individual trees and used these models to estimate AWP for 142 permanent forest plots. We then used structural equation modeling to explore the direct and indirect pathways which shape rates of AWP. Across the plot network, stand basal area emerged as the strongest determinant of AWP, with densely packed stands exhibiting the fastest rates of AWP. In addition to stand packing density, both tree diversity and soil phosphorus content were also positively related to productivity. By contrast, historical logging activities negatively impacted AWP through the removal of large trees, which contributed disproportionately to productivity. Understanding what determines variation in wood production across tropical forest landscapes requires accounting for multiple interacting drivers – with stand structure, tree diversity, and soil nutrients all playing a key role. Importantly, our results also indicate that logging activities can have a long‐lasting impact on a forest's ability to sequester and store carbon, emphasizing the importance of safeguarding old‐growth tropical forests.

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil

Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approaches can be useful techniques in minimizing estimation errors within complex variations of vegetation. We evaluated the performance of Random Forest® regression tree and Artificial Neural Network procedures in modelling stem taper. Diameters and volume outside bark were compared to a traditional taper-based equation across a tropical Brazilian savanna, a seasonal semi-deciduous forest and a rainforest. Neural network models were found to be more accurate than the traditional taper equation. Random forest showed trends in the residuals from the diameter prediction and provided the least precise and accurate estimations for all forest types. This study provides insights into the superiority of a neural network, which provided advantages regarding the handling of local effects.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25 ha), all stems ≥ 1 cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 °S-61 °N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 °C), changes in precipitation (up to ± 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8 g N m(-2) yr(-1) and 3.1 g S m(-2) yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5 km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.