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Reef, R. and Gordon, C., 2024. Allometric equations for aboveground biomass estimation of temperate mangroves using uncrewed aerial vehicles. Journal of Coastal Research, 40(3), 474–484. Charlotte (North Carolina), ISSN 0749-0208. Temperate mangrove ecosystems face different stresses compared with their tropical counterparts, resulting in reduced extent, biodiversity, and productivity. Temperate mangroves represent less than 2% of global mangrove cover and are thus less studied, but where they occur, they provide distinct ecosystem services and are expanding. Avicennia marina subsp. australasica is the sole mangrove species found in Victoria, Australia, where mangroves reach their highest latitudinal limit globally. Estimating aboveground biomass (AGB) in temperate mangroves poses challenges because of their morphological differences from tropical forests. This study used uncrewed aerial vehicle (UAV)–derived measurements and ground inventory data to develop allometric equations for A. marina at its latitudinal limit. A hybrid allometric equation, incorporating both field- and UAV-derived metrics, provided the most accurate prediction of AGB (coefficient of determination [R2] = 0.93). An allometric equation using solely UAV-derived inputs (canopy area and canopy height) had high-fidelity prediction capacity (R2 = 0.85), although it overestimated AGB by 11%. A significant finding was the simplification of scaling from individual tree AGB to landscape-scale AGB by eliminating the need to segment individual tree canopies. Landscape-scale AGB estimates showed a stable underestimation of approximately 30%, which could be improved by segmenting the area into zones of similar height. AGB of mangroves in Western Port was estimated at 48 t ha–1, which is within the range measured for temperate mangroves around the world. The biomass density in this temperate region is significantly lower (40%) than the continental average. [ABSTRACT FROM AUTHOR]

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.

Stem taper models are helpful tools for predicting diameter of a tree at any height or volume of any stem section. In this study, traditional and artificial neural network (ANN) approaches were used to predict stem tapers of Scots pine individuals. The data used in this study correspond to destructively sampled trees in even-aged forest stands located in the three important locations where Scots pine grows naturally in northwestern Türkiye. In total, three regression type stem taper models from different categories and an ANN model were developed and evaluated both statistically and graphically. The best results were obtained by Kozak's taper model accounting for the 99% of the total variance in stem diameter predictions. [ABSTRACT FROM AUTHOR]

Pinang nut (Areca catechu L.) is a major agroforestry crops in Papua with high economic value. This study developed allometric equations for estimating Pinang biomass on the basis of stem diameter and height by destructive sampling inagroforestry systems. Aboveground biomass was measured and linked to plant stem diameter at various heights (0.13 and 130 cm above the ground) and plant height. The resultant equation was used for biomass estimates in various agroforestry systems with Pinang trees, with total of 18 plots differentiated in bottom, middle and upper slope positions. As expected for palm trees, plant height is a better predictor (Y = 0.816 H1.42; R2 = 0.89) of biomass than stem diameter, with equal results for diameter measurements at 13 or 130 cm height (Y = 0.0689 D2.59; R2 = 0.74). Best results were for an equation combining diameter and plant height: Y = 0.03883*H*D1.2; R2 = 0.96. Agroforestry systems on the upper slopes had the highest carbon stocks (38.8 Mg ha-1) than the middle and lower slopes (25.9 and 22.5 Mg ha-1, respectively). Aboveground carbon stocks of Pinang in study area ranged from 0.96 to 20.9 kg C tree-1 with an average of 10.1 kg C tree-1.

The early development of naturally regenerated forest stands is highly dynamic and includes rapid shifts in productivity and mortality. To characterise the growth dynamics in the initial decades, we assessed aboveground biomass stocks (S ab),aboveground biomass productivity (DP ab), and aboveground biomass mortality (DM ab) in five naturally regenerated European beech stands located in the Inner Western Carpathians. We developed allometric models for aboveground biomass compartments based on a sample of 262 trees. We also established five circular sampling plots within each stand and, for 15 years, carried out annual measurements of stem diameter at the base and height for all trees within the sampling plots. We then utilised the allometric models to calculate annual biomass accumulation in aboveground biomass compartments on an area basis. Our findings show that, despite the declining contribution of foliage to the total aboveground stock, about a quarter of annual net primary production in young beech stands enters the dead biomass pool due to leaf fall and tree mortality. The growth dynamics and biomass allocation patterns of young beech forests necessitate the development of specific allometric models to describe their growth and carbon capture processes. • Despite varying post-regeneration tree density, all studied forests reach a similar density of trees per hectare by age 20. • Biomass allocation shifts significantly with tree size in young, naturally regenerated European beech stands. • In young beech, the proportion of stem and branches increases rapidly at the expense of foliage. • Decennial assessement significantly underestimates productivity, using cumulative annual growth improves accuracy. [ABSTRACT FROM AUTHOR]

Pinang nut (Areca catechu L.) is a major agroforestry crops in Papua with high economic value. This study developed allometric equations for estimating Pinang biomass on the basis of stem diameter and height by destructive sampling inagroforestry systems. Aboveground biomass was measured and linked to plant stem diameter at various heights (0.13 and 130 cm above the ground) and plant height. The resultant equation was used for biomass estimates in various agroforestry systems with Pinang trees, with total of 18 plots differentiated in bottom, middle and upper slope positions. As expected for palm trees, plant height is a better predictor (Y = 0.816 H1.42; R2 = 0.89) of biomass than stem diameter, with equal results for diameter measurements at 13 or 130 cm height (Y = 0.0689 D2.59; R2 = 0.74). Best results were for an equation combining diameter and plant height: Y = 0.03883*H*D1.2; R2 = 0.96. Agroforestry systems on the upper slopes had the highest carbon stocks (38.8 Mg ha-1) than the middle and lower slopes (25.9 and 22.5 Mg ha-1, respectively). Aboveground carbon stocks of Pinang in study area ranged from 0.96 to 20.9 kg C tree-1 with an average of 10.1 kg C tree-1. [ABSTRACT FROM AUTHOR]

Terrestrial laser scanning is a promising technique for automatic measurements of tree stems. The objectives of the study were (1) to develop and validate a new method for the detection, classification and measurements of tree stems and canopies using the Hough transformation and the RANSAC algorithm and (2) assess the influence of distance to the scanner on the measurement accuracy. Tree detection and stem diameter estimates were validated for 16 circular plots with 20 m radius. The three dominating tree species were Norway spruce (Picea abies L. Karst.), Scots pine (Pinus sylvestris L.) and birch (Betula spp.). The proportion of detected trees decreased as the distance to the scanner increased and followed the trend of decreasing visible area. Within 10 m from the scanner, the proportion of detected trees was 87% on average for the plots and the diameter at breast height was estimated with a relative root-mean-square-error (RMSE) of 14%. The most accurate diameter measurements were obtained for pine, which had a RMSE of 7% for all the full 20 m radius plots. The RANSAC algorithm reduced noise and made it possible to obtain reliable estimates.

Background: The remaining forests in the extensive contact zone between southern Amazonia (seasonal rain forest) and the Cerrado (savanna) biomes are at risk due to intense land-use and climate change. Aims: To explore the vulnerability of these transitional forests to changes in land use and climate, we evaluated the effects of fragmentation and climatic variables on forest structure. Methods: We measured the diameter and height of 14,185 trees with diameter ≥10 cm at 24 forest plots distributed over an area of 25,000 km2. For each plot, we obtained data on contemporary fragmentation and climatic variables. Results: Forest structure variables (height, diameter, height:diameter allometry, biomass) varied significantly both within and among plots. The height, H:D and biomass of trees were positively correlated with annual precipitation and fragment area. Conclusions: The association between forest structure and precipitation indicates that these forests plots are likely to be vulnerable to dry season intensification anticipated for the southern edge of the Amazon. Additionally, the reduction in the fragment area may contribute to reductions in forest biomass and tree height, and consequently ecosystem carbon stocks. Given the likely susceptibility of these forests, urgent conservation action is needed to prevent further habitat degradation. [ABSTRACT FROM AUTHOR]

[Objective] This study aimed to clarify the quantitative relationships between growth parameters of sweet corn at different growth stages and canopy spectral indices, thus providing references for rapid monitoring of growth parameters of sweet corn. [Method] Based on field experiments of Zhengtian 68 under different potassium application levels, canopy spectral reflectance was collected using CGMD302 spectrometer at jointing stage, big bell mouth stage and tasseling stage, respectively; plant height, stem diameter, and leaf area index (LAI) were measured, to investigate the relationships between various growth parameters and spectral indices. [Result] Normalized difference vegetation index (NDVI) was positively correlated with stem diameter and LAI; ratio vegetation index (RVI) was negatively correlated with stem diameter and LAI. The single-stage monitoring models established based on NDVI and RVI could retrieve effectively stem diameter and LAI of sweet corn with the prediction accuracy of higher than 0.9, root mean square error (RMSE) of less than 10%, average relative error (RE) of less than 5%. [Conclusion] This study provided a technical basis for rapid monitoring of growth parameters of sweet corn. [ABSTRACT FROM AUTHOR]

Terrestrial laser scanning is a promising technique for automatic measurements of tree stems. The objectives of the study were (1) to develop and validate a new method for the detection, classification and measurements of tree stems and canopies using the Hough transformation and the RANSAC algorithm and (2) assess the influence of distance to the scanner on the measurement accuracy. Tree detection and stem diameter estimates were validated for 16 circular plots with 20 m radius. The three dominating tree species were Norway spruce (Picea abies L. Karst.), Scots pine (Pinus sylvestris L.) and birch (Betula spp.). The proportion of detected trees decreased as the distance to the scanner increased and followed the trend of decreasing visible area. Within 10 m from the scanner, the proportion of detected trees was 87% on average for the plots and the diameter at breast height was estimated with a relative root-mean-square-error (RMSE) of 14%. The most accurate diameter measurements were obtained for pine, which had a RMSE of 7% for all the full 20 m radius plots. The RANSAC algorithm reduced noise and made it possible to obtain reliable estimates. [ABSTRACT FROM AUTHOR]

Ecosystem science increasingly relies on highly derived metrics to synthesize across large datasets. However, full uncertainty associated with these metrics is seldom quantified. Our objective was to evaluate measurement error and model uncertainty in plot-based estimates of carbon stock and carbon change. We quantified the measurement error associated with live stems, deadwood and plot-level variables in temperate rainforest in New Zealand. We also quantified model uncertainty for height-diameter allometry, stem volume equations and wood-density estimates. We used Monte Carlo simulation to assess the net effects on carbon stock and carbon change estimated using data from 227 plots from throughout New Zealand. Plot-to-plot variation was the greatest source of uncertainty, amounting to 9.1% of mean aboveground carbon stock estimates (201.11 MgC ha). Propagation of the measurement error and model uncertainty resulted in a 1% increase in uncertainty (0.1% of mean stock estimate). Carbon change estimates (mean −0.86 MgC ha y) were more uncertain, with sampling error equating to 56% of the mean, and when measurement error and model uncertainty were included this uncertainty increased by 35% (22.1% of the mean change estimate). For carbon change, the largest sources of measurement error were missed/double counted stems and fallen coarse woody debris. Overall, our findings show that national-scale plot-based estimates of carbon stock and carbon change in New Zealand are robust to measurement error and model uncertainty. We recommend that calculations of carbon stock and carbon change incorporate both these sources of uncertainty so that management implications and policy decisions can be assessed with the appropriate level of confidence. [ABSTRACT FROM AUTHOR]

In the Sahelian and Sudanian ecozones of West Africa, the rainy season lasts only 3-4 months per year, there are steep rainfall gradients with latitude and longitude, the climate is becoming increasingly hotter and drier with more variable rainfall, some fuelwood species are disappearing locally, demand for fuelwood is increasing, and we expect that fuelwood production will be increasingly limited to drier sites in the future. We need a methodology, therefore, to identify the best species for fuelwood production in drier sites. We used a methodology that could be used to identify the best fuelwood species for drier and wetter sites in regions where there are steep rainfall gradients. We investigated variation in growth and fuelwood properties of five species ( Balanites aegyptiaca, Combretum glutinosum, Guiera senegalensis, Piliostigma reticulatum, Ziziphus mauritiana) along rainfall gradients. Growth parameters (tree height, stem diameter under bark, mean ring width) and fuelwood properties (basic density, volatile matter, fixed carbon, ash content, moisture content, gross calorific value, gross calorific value per cubic meter, fuel value index) were adjusted for tree age. For each species, linear regressions were used to determine the effects of mean annual rainfall and geographical coordinates, which were correlated with rainfall, on tree growth and fuelwood properties; and the effects of tree growth on fuelwood properties in lower, intermediate and higher rainfall zones. Geographical coordinates explained more variation than rainfall, and relationships with rainfall differed among species. Larger trees had wood with higher basic density, fixed carbon, ash content, moisture content, gross calorific value and/or gross calorific value per cubic meter, but lower volatile matter and/or fuel value index. Relationships between growth and fuelwood properties were not significant in all species and rainfall zones. Based on this study, we recommend producing fuelwood of C. glutinosum and G. senegalensis. [ABSTRACT FROM AUTHOR]

Abstract: The objectives of this study were to quantify and analyze differences in laser height and laser intensity distributions of individual trees obtained from airborne laser scanner (ALS) data for different canopy conditions (leaf-on vs. leaf-off) and sensors. It was also assessed how estimated tree height, stem diameter, and tree species were influenced by these differences. The study was based on 412 trees from a boreal forest reserve in Norway. Three different ALS acquisitions were carried out. Leaf-on and leaf-off data were acquired with the Optech ALTM 3100 sensor, and an additional leaf-on dataset was acquired using the Optech ALTM 1233 sensor. Laser echoes located within the vertical projection of the tree crowns were attributed to different echo categories (“first echoes of many”, “single echoes”, “last echoes of many”) and analyzed. The most pronounced changes in laser height distribution from leaf-on to leaf-off were found for the echo categories denoted as “single” and “last echoes of many” where the distributions were shifted towards the ground under leaf-off conditions. The most pronounced change in the intensity distribution was found for “first echoes of many” where the distribution was extremely skewed towards the lower values under leaf-off conditions compared to leaf-on. Furthermore, the echo height and intensity distributions obtained for the two different sensors also differed significantly. Individual tree properties were estimated fairly accurately in all acquisitions with RMSE ranging from 0.76 to 0.84m for tree height and from 3.10 to 3.17cm for stem diameter. It was revealed that tree species was an important model term in both and tree height and stem diameter models. A significantly higher overall accuracy of tree species classification was obtained using the leaf-off acquisition (90 vs. 98%) whereas classification accuracy did not differ much between sensors (90 vs. 93%). [Copyright &y& Elsevier]