New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests.

Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based H:D allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based H:D allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from -1.6 m (-5.3%) to -7.5 m (-25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as -31.7 m (-41.3%). We propose a TLS-based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of -4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.

Trade-offs in biodiversity and ecosystem services between edges and interiors in European forests.

Forest biodiversity and ecosystem services are hitherto predominantly quantified in forest interiors, well away from edges. However, these edges also represent a substantial proportion of the global forest cover. Here we quantified plant biodiversity and ecosystem service indicators in 225 plots along forest edge-to-interior transects across Europe. We found strong trade-offs: phylogenetic diversity (evolutionary measure of biodiversity), proportion of forest specialists, decomposition and heatwave buffering increased towards the interior, whereas species richness, nectar production potential, stemwood biomass and tree regeneration decreased. These trade-offs were mainly driven by edge-to-interior structural differences. As fragmentation continues, recognizing the role of forest edges is crucial for integrating biodiversity and ecosystem service considerations into sustainable forest management and policy.

The drivers and impacts of Amazon forest degradation.

Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year-1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year-1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

StrucNet: a global network for automated vegetation structure monitoring.

Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large-scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three-dimensional vegetation structure at local scales. Here we demonstrate the potential of high-frequency ground-based laser scanning to systematically monitor structural changes in vegetation. We present a proof-of-concept high-temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high-temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.

Forest fragmentation impacts the seasonality of Amazonian evergreen canopies.

Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Here, we use terrestrial LiDAR surveys every two weeks spanning wet and dry seasons in Central Amazonia to show that plant phenology varies strongly across vertical strata in old-growth forests, but is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we find that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests lost plant material. In contrast, the understory greened up with increased light availability driven by the upper canopy loss, alongside increases in solar radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Our findings reveal a strong influence of edge effects on phenological controls in wet forests of Central Amazonia.

Forest above-ground volume assessments with terrestrial laser scanning: a ground-truth validation experiment in temperate, managed forests.

BACKGROUND AND AIMS: Quantifying the Earth's forest above-ground biomass (AGB) is indispensable for effective climate action and developing forest policy. Yet, current allometric scaling models (ASMs) to estimate AGB suffer several drawbacks related to model selection and uncertainties about calibration data traceability. Terrestrial laser scanning (TLS) offers a promising non-destructive alternative. Tree volume is reconstructed from TLS point clouds with quantitative structure models (QSMs) and converted to AGB with wood basic density. Earlier studies have found overall TLS-derived forest volume estimates to be accurate, but highlighted problems for reconstructing finer branches. Our objective was to evaluate TLS for estimating tree volumes by comparison with reference volumes and volumes from ASMs. METHODS: We quantified the woody volume of 65 trees in Belgium (from 77 to 2800 L; Pinus sylvestris, Fagus sylvatica, Larix decidua, and Fraxinus excelsior) with QSMs and destructive reference measurements. We tested a volume expansion factor (VEF) approach by multiplying the solid and merchantable volume from QSMs by literature VEF values. KEY RESULTS: Stem volume was reliably estimated with TLS. Total volume was overestimated by +21 % using original QSMs, by +9 % and -12 % using two sets of VEF-augmented QSMs, and by -7.3 % using best-available ASMs. The most accurate method differed per site, and the prediction errors for each method varied considerably between sites. CONCLUSIONS: VEF-augmented QSMs were only slightly better than original QSMs for estimating tree volume for common species in temperate forests. Despite satisfying estimates with ASMs, the model choice was a large source of uncertainty, and species-specific models did not always exist. Therefore, we advocate for further improving tree volume reconstructions with QSMs, especially for fine branches, instead of collecting more ground-truth data to calibrate VEF and allometric models. Promising developments such as improved co-registration and smarter filtering approaches are ongoing to further constrain volumetric errors in TLS-derived estimates.

High aboveground carbon stock of African tropical montane forests.

Tropical forests store 40-50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with lowland forests2. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane2,5,6 and lowland7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa8. We find that the low stem density and high abundance of large trees of African lowland forests4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse9,10 and carbon-rich ecosystems.

Understanding 3D structural complexity of individual Scots pine trees with different management history.

Tree functional traits together with processes such as forest regeneration, growth, and mortality affect forest and tree structure. Forest management inherently impacts these processes. Moreover, forest structure, biodiversity, resilience, and carbon uptake can be sustained and enhanced with forest management activities. To assess structural complexity of individual trees, comprehensive and quantitative measures are needed, and they are often lacking for current forest management practices. Here, we utilized 3D information from individual Scots pine (Pinus sylvestris L.) trees obtained with terrestrial laser scanning to, first, assess effects of forest management on structural complexity of individual trees and, second, understand relationship between several tree attributes and structural complexity. We studied structural complexity of individual trees represented by a single scale-independent metric called "box dimension." This study aimed at identifying drivers affecting structural complexity of individual Scots pine trees in boreal forest conditions. The results showed that thinning increased structural complexity of individual Scots pine trees. Furthermore, we found a relationship between structural complexity and stem and crown size and shape as well as tree growth. Thus, it can be concluded that forest management affected structural complexity of individual Scots pine trees in managed boreal forests, and stem, crown, and growth attributes were identified as drivers of it.

Drivers of carbon stocks in forest edges across Europe.

Forests play a key role in global carbon cycling and sequestration. However, the potential for carbon drawdown is affected by forest fragmentation and resulting changes in microclimate, nutrient inputs, disturbance and productivity near edges. Up to 20% of the global forested area lies within 100 m of an edge and, even in temperate forests, knowledge on how edge conditions affect carbon stocks and how far this influence penetrates into forest interiors is scarce. Here we studied carbon stocks in the aboveground biomass, forest floor and the mineral topsoil in 225 plots in deciduous forest edges across Europe and tested the impact of macroclimate, nitrogen deposition and smaller-grained drivers (e.g. microclimate) on these stocks. Total carbon and carbon in the aboveground biomass stock were on average 39% and 95% higher at the forest edge than 100 m into the interior. The increase in the aboveground biomass stock close to the edge was mainly related to enhanced nitrogen deposition. No edge influence was found for stocks in the mineral topsoil. Edge-to-interior gradients in forest floor carbon changed across latitude: carbon stocks in the forest floor were higher near the edge in southern Europe. Forest floor carbon decreased with increasing litter quality (i.e. high decomposition rate) and decreasing plant area index, whereas higher soil temperatures negatively affected the mineral topsoil carbon. Based on high-resolution forest fragmentation maps, we estimate that the additional carbon stored in deciduous forest edges across Europe amounts to not less than 183 Tg carbon, which is equivalent to the storage capacity of 1 million ha of additional forest. This study underpins the importance of including edge influences when quantifying the carbon stocks in temperate forests and stresses the importance of preserving natural forest edges and small forest patches with a high edge-to-interior surface area.

The effects of seaward distance on above and below ground carbon stocks in estuarine mangrove ecosystems.

BACKGROUND: Mangrove forests have gained recognition for their potential role in climate change mitigation due to carbon sequestration in live trees, and carbon storage in the sediments trapped by mangrove tree roots and pneumatophores. Africa hosts about 19% of the world's mangroves, yet relatively few studies have examined the carbon stocks of African mangroves. The available studies report considerable differences among sites and amongst the different pools of carbon stocks. None considered the effects of seaward distance. We present details of AGC and SOC carbon stocks for Lindi in Tanzania, and focus on how these values differ with increasing seaward distance and, how our results compare to those reported elsewhere across Africa. RESULTS: AGC ranged between 11 and 55 Mg C ha-1, but was not significantly affected by seaward distance. SOC for 0-1 m depth ranged from 154 to 484, with a mean of 302 Mg C ha-1. SOC was significantly negatively correlated with seaward distance. Mangrove type (estuarine/oceanic), soil erosion, soil depth may explain these differences We note important methodological differences in previous studies on carbon stocks in mangroves in Africa. CONCLUSION: This study indicates that seaward distance has an important effect on SOC stocks in the Lindi region of Tanzania. SOC should be fully incorporated into national climate change mitigation policies. Studies should report seaward distance and to describe the type of mangrove stand to make results easily comparable across sites and to assess the true value of Blue Carbon in Africa. We recommend focusing on trees > 10 cm diameter for AGC, and sampling soils to at least 1 m depth for SOC, which would provide a more complete assessment of the potentially considerable mangrove carbon store.