Botanizing the Laiwangi Wanggameti region reveals new records from Sumba (Indonesia), an island with poorly accessible, scattered, and outdated floristic information

The implementation of Unmanned Aerial Vehicles (UAVs) and Structure-from-Motion (SfM) photogrammetry in assessing forest structures for forest inventory and biomass estimations has shown great promise in reducing costs and labour intensity while providing relative accuracy. Tree Height (TH) and Diameter at Breast Height (DBH) are two major variables in biomass assessment. UAV-based TH estimations depend on reliable Digital Terrain Models (DTMs), while UAV-based DBH estimations depend on reliable dense photogrammetric point cloud. The main aim of this study was to evaluate the performance of multi-rotor UAV photogrammetric point cloud in estimating homogeneous and heterogeneous forest structures, and their comparison to more accurate LiDAR data obtained from Aerial Laser Scanners (ALS), Terrestrial Laser Scanners (TLS), and more conventional means like manual field measurements. TH was assessed using UAVSfM and LiDAR point cloud derived DTMs, while DBH was assessed by comparing UAVSfM photogrammetric point cloud to LiDAR point cloud, as well as to manual measurements. The results obtained in the study indicated that there was a high correlation between UAVSfM TH and ALSLiDAR TH (R2 = 0.9258) for homogeneous forest structures, while a lower correlation between UAVSfM TH and TLSLiDAR TH (R2 = 0.8614) and UAVSfM TH and ALSLiDAR TH (R2 = 0.8850) was achieved for heterogeneous forest structures. A moderate correlation was obtained between UAVSfM DBH and field measurements (R2 = 0.5955) for homogenous forest structures, as well as between UAVSfM DBH and TLSLiDAR DBH (R2 = 0.5237), but a low correlation between UAVSfM DBH and UAVLiDAR DBH (R2 = 0.1114). The study demonstrated that UAV acquired imagery can be used to accurately estimate TH in both forest types, but has challenges estimating DBH. The research does not suggest that UAVSfM serves as a replacement for more high-cost and accurate LiDAR data, but rather as a cheaper adequate alternative in forestry management depending on accuracy requirements.

The explicit purpose of this study was to characterize climate and vegetation along the western slope of the El Sira Mountains (Peru) and evaluate radial tree growth in response to seasonal rainfall anomalies. From May 2011 until September 2015, we monitored radial stem growth of 67 trees using point dendrometers and measured climate within five sites along an altitudinal gradient. The transect extends from lowland terra firme forests, over submontane forests, late and mid successional montane cloud forests up to exposed elfin forests. Monthly rainfall estimates by the TRMM PR satellite (product 3B42) were highly correlated with our rain gauge observations but underestimate rainfall at high altitudes. Different intra-annual tree growth patterns could be identified within each elevational forest type, showing species with strictly seasonal growth, continuous growth or alternating growth patterns independent of the seasons. Stem growth at each site was generally larger during rainy seasons, except for the elfin forest. The rainy season from October 2013 to March 2014 was extraordinarily dry, with only 73% of long-term mean precipitation received, which resulted in reduced radial growth, again with the exception of the elfin forest. This indicates that montane tropical rain forests may suffer from prolonged droughts, while exposed ridges with elfin forests still receive plenty of precipitation and benefit from receiving more solar radiation for photosynthesis.

Biodiversity patterns along elevational gradients are generally characterised by monotonic decreases or mid-elevational peaks in species richness, while elevational zones may be characterised by distinct assemblages, or higher zones may be subsets of lowland assemblages. Elevational gradients in diversity have been less studied in the Afrotropical region. This study documents ant diversity patterns in three forest types associated with the tropical mountains of Udzungwa; we hypothesise that: (1) ant diversity and activity will show a monotonic decrease from mid-elevation with increasing elevation and (2) that forests associated with different elevations will have a distinct ant assemblage. Pitfall traps were deployed at three targeted elevations (650–800, 800–1400, and 1400–1500 m a.s.l.). Ant species richness declined with increasing elevation from 650 m a.s.l. and formed three elevational assemblages with lower elevation forests having almost twice as many species as sub-montane forests and three times as many as that of the montane forests. In contrast, overall ant activity peaked at 800–1400 m a.s.l. The ant assemblages associated with the lower elevation forest were very distinct, while assemblages associated with the sub-montane and montane forests shared species. Our study reveals valuable and relevant information for biodiversity monitoring and conservation planning as the species associated with each forest type may be used as indicator species for assessing biodiversity responses to climate change and anthropogenic activities on these mountains.

Abundant and refined structural information under forest canopy can be obtained by using terrestrial laser scanning (TLS) technology. This study explores the methods of using TLS to obtain point cloud data and estimate individual tree height and diameter at breast height (DBH) at plot level in regions with complex terrain. Octree segmentation, connected component labeling and random Hough transform (RHT) are comprehensively used to identify trunks and extract DBH of trees in sample plots, and tree height is extracted based on the growth direction of the trees. The results show that the topography, undergrowth shrubs, and forest density influence the scanning range of the plots and the accuracy of feature extraction. There are differences in the accuracy of the results for different morphological forest species. The extraction accuracy of Yunnan pine forest is the highest (DBH: Root Mean Square Error (RMSE) = 1.17 cm, Tree Height: RMSE = 0.54 m), and that of Quercus semecarpifolia Sm. forest is the lowest (DBH: RMSE = 1.22 cm, Tree Height: RMSE = 1.23 m). At plot scale, with the increase of the mean DBH or tree height in plots, the estimation errors show slight increases, and both DBH and height tend to be underestimated.

The relationship between tree height (h) and tree diameter at breast height (dbh) is an important element describing forest stands. In addition, h often is a required variable in volume and biomass models. Measurements of h are, however, more time consuming compared to those of dbh, and visual obstructions, rounded crown forms, leaning trees and terrain slopes represent additional error sources for h measurements. The aim of this study was therefore to develop h–dbh relationship models for natural tropical forest in Tanzania. Both general forest type specific models and models for tree species groups were developed. A comprehensive data set with 2 623 trees from 410 different tree species collected from a total of 1 191 plots and 38 sites covering the four main forest types of miombo woodland, acacia savanna, montane forest and lowland forests was applied. Tree species groups were constructed by using a k-means clustering procedure based on the h–dbh allometry, and a number of different non-linear model forms were tested. When considering the complexity of natural tropical forests in general and in particular variations of h–dbh relationships due to high species diversity in such forests, the model fit and performance were considered to be appropriate. Results also indicate that tree species group models perform better than forest type models. Despite the fact that the residual errors level associated with the models were relatively high, the models are still considered to be applicable for large parts of Tanzanian forests with an appropriate level of reliability.

Many studies analyzing the relative contribution of soil properties versus distance‐related processes on plant species composition have focused on lowland tropical forests. Very few have investigated two forest types simultaneously, to contrast ecological processes that assemble the communities. This study analyses—at the landscape scale—the relative contribution of soil and distance on lowland and submontane tropical forests, which co‐occur in two reserves of the Azuero peninsula (Panama). Floristic inventories and soil sampling were conducted in 81 0.1‐ha plots clustered in 27 sites, and data were analyzed using Mantel tests, variance partitioning and non‐metric multidimensional scaling. The largest differences in floristic composition occurred between reserves in both forest types. Soil variation and geographic distance were important determinants of floristic composition, but their effects were highly correlated; together they explained 7–25 percent and 46–50 percent of the variation in lowland and submontane forests, respectively. Soil variables that had the best correlations with floristic composition were iron, zinc, and silt content in lowland, and calcium, copper, iron, potassium, magnesium, phosphorus, zinc, and sand content in submontane forests. The studied forests showed a high beta diversity that seems to be related primarily with soils and, secondarily, with dispersal limitation and stochastic events. The results reveal a response of tree assemblages to environmental gradients, which are particularly conspicuous in Panama. The effects of limited dispersal seem to be more important in submontane than in lowland forests, probably as a result of higher isolation.

Primary hepatic tuberculosis masquerading as intrahepatic cholangiocarcinoma

An automatic approach for tree species detection and profile estimation of urban street trees using deep learning and Google street view images

BackgroundLarch (Larix Mill.) forests are widely distributed in the upper parts of mountainous areas in China, playing vital roles in constructing mountain landscapes and maintaining mountain environments. Despite their importance, our knowledges on the large-scale patterns of structure characteristics and the relationships between different structure variables are unclear. In this paper, we investigated 155 plots from 11 natural larch forest types across the country to explore the biogeographic patterns of the structure characteristics and the allometric relationships between different structure variables for Chinese larch forests.ResultsThe structure characteristics were significantly different among larch forest types. For different larch forest types, the power function fits the relationships between tree height and diameter at breast height (DBH), average DBH and stem density, and taper and stem density well, but with different exponents among larch forest types. The power exponents of the allometric relationships between tree height and DBH for different larch forest types varied from 0.61 to 0.93 (mean = 0.86) by standard major axis regression (SMA), and from 0.51 to 0.78 (mean = 0.56) by ordinary least square regression (OLS). The 50%, 75% and 95% quantile regression (QR) and OLS indicated that the average DBH and taper of the L. gmelinii forests, L. gmelinii var. principis-rupprechtii forests, and L. sibirica forests were significantly correlated with stem density.ConclusionsThe relationship between tree height and DBH showed a power function relationship for all larch forest types in China, but with different exponents. Overall, stem density was negatively correlated with average DBH and taper. The Sect. Larix forests exhibited stand density effect. Our findings provide an important basis for recognizing the biogeographic patterns of structure factors and for the management of larch forests in China.

Tree height, diameter, and grade were measured on 14 cattle grazing trial plots located on the Palustris Experimental Forest in Louisiana's Kisatchie National Forest. These plots had been established in the early 1960s. Mensurational data was gathered on 28 trees from grazed sites and another 28 from ungrazed plots. Increment cores were also taken from these trees. Statistical analyses showed no effect attributable to grazing on any of the variables measured: tree height, tree diameter at breast height, tree grade, growth rate, amount of latewood, unextracted specific gravity, or tracheid length.

Background: The Rumpi Hills Forest Reserve (RHFR) is a montane forest area in south-western Cameroon. Although RHFR is presumed to be rich in biodiversity and vegetation types, little information exists regarding its floristic composition and vegetation patterns.Objectives: Our goal was to characterise vegetation patterns in the reserve and to understand how elevation influences distributions and diversity of species. We aimed to provide a first detailed plant species inventory for this important forest area, as well as basic information on forest structure.Method: We characterised floristic composition and vegetation patterns of the reserve in 25 1-ha plots along an elevational gradient from 50 m to 1778 m. In each plot, trees and lianas of diameter at breast height (dbh) ≥ 10 cm were measured; shrubs 10 cm were measured in nested plots of 0.01 ha.Results: In all, 16 761 trees, shrubs and lianas with dbh ≥ 1 cm were censused, representing 71 families, 279 genera and 617 morphospecies. Floristic composition ranged from 94 to 132 species, with a mean of 117.5 species per hectare in lowland forest (50 m – 200 m) and 36–41 species, with a mean of 38.5 species per hectare in montane cloud forest (1600 m – 1778 m) near the summit of Mount Rata. Two-way indicator species analysis classified the 25 plots into six vegetation types corresponding to lowland evergreen rainforest, lowland evergreen rainforest on basalt rocks, middle-elevation evergreen forest, submontane forest, transitional submontane forest and montane cloud forest. In all, 0.006% of the reserve was included in our sample plots. Detrended correspondence analysis highlighted the importance of elevation in shaping vegetation patterns.Conclusion: The RHFR is composed of different vegetation types, which show impressive variation in terms of structure, species composition and diversity. The detailed, fine-scale inventory data obtained in this study could be useful in planning efficient management of this and other montane tropical forests.

This study was carried out in a 23-year plantation, divided into three slope (S) groups (S < 15%, 15% ≤ S < 35%, and S ≥ 35%), sampled from southern Türkiye in Taurus cedar (Cedrus libani A. Rich.). Tree height and diameter at breast height were studied to examine effect of slope on the characteristics in the plantation established 2 × 2.5 m. Third slope (S ≥ 35%) showed the highest tree height (5.9 m) and diameter at breast height (8.8 cm) performances, while they were the lowest in first slope (S < 15%) (5.1 m and 8.1 cm). There were significant (p < 0.05) differences among slope groups for tree height opposite to diameter at breast height according to results of analysis of variance. Diameter at breast height had higher variation than tree height in all slope groups based on coefficient variation. Positive and significant (p < 0.05) relations between tree height and diameter at breast height in all slope groups according to results of correlation analysis. Results of the study were discussed for afforestation and other forestry practices of the species.

Understanding the relationship between diameter breast height (dbh), tree height and volume helps in optimizing log selection for different purposes based on required timber volume. The purpose of the study was to create a modified model for diameter breast height, tree height and volume for Pinus caribaea to adequately fit all relevant variations in the data using R programme. Dbh is better predictor variable compared to tree height when volume is considered as a response variable. But this alone could not meet the assumptions of linear regression model. This therefore prompted the use of all data collected where by the tree height was considered as random effect. This was useful in the fitting of all data of the collected variables to a more useful relation in estimation of their linear regression relationship. The accuracy of this model was improved by addition of log function. Data of Pinus caribaea tree volume, dbh and height was collected. One hundred (100) trees were sampled in 1 hectare of pinus plantation with a range of corresponding tree dbh and height across the plantation in to a data set known as “mypinedata”. We wanted to know how dhb and height of Pinus caribaea as predictor variables affected its volume as a response variable. Comparison of dbh and height for best predictor variable for volume as a response in the linear regression model showed dbh as a preferred variable. However to meet the assumptions the linear relationship of volume, dbh and height was modified to fit all relevant data to improve on the model. The modified model for dbh- volume linear relationship was consequently created to cater for the adequate fit of the data or relevant variations using height as a random effect. Therefore modified model proved better fit for volume, dbh and height relationship in Pinus caribaea stand as deduced from its data summary and the assumptions when the log function was added. The assumptions for the modified model were met for the plot of residua

A comprehension of the effects planting density and nitrogen (N) fertilization have on the physiological and morphological characteristics of trees is critical for optimizing the require size and characteristics of wood products. We evaluated the growth traits and the leaf and wood characteristics of three clone poplars including Populus simonii × P. nigra ‘Xiaohei’, ‘Xiaohei-14’ and ‘Bailin-3’ under five planting densities (1666, 1111, 833, 666, and 555 tree ha−1) and four N fertilization rates (0, 100, 160, and 220 g tree−1 year−1). The results show that the clone type significantly affected all observed indicators, while planting density and N fertilization treatments had a significant effect on growth traits and leaf characteristics, but not on wood characteristics. Specifically, the clone ‘Bailin-3’ exhibited the largest annual increments in tree height and diameter at breast height (DBH), leaf width, N content, and soluble protein content. A decrease in initial planting density (from 1666 to 555 tree ha−1) led to an increased annual incremental tree height and DBH, regardless of clone type and N fertilization treatment. N fertilization treatment significantly impacted the annual increment in DBH, but not that of tree height. Further, the annual increments in tree height and DBH were positively correlated with leaf width, N content, chlorophyll content, and soluble protein content, and negatively correlated with hemicellulose content. In addition, the chlorophyll and soluble protein contents were identified as the most reliable predictors of the annual increments in tree height and DBH. Our results demonstrate the clone ‘Bailin-3’ with 555 tree ha−1 under 160 g N tree−1 yr−1 showed superior growth traits and leaf characteristics. Thus, it is recommended for future poplar silviculture of larger diameter timber production at similar sites. The results contribute to understanding of the effects of planting density and fertilization on the growth traits and the leaf and wood characteristics of three poplar clones, offering valuable guidance for the sustainable development and long-term productivity of poplar plantations.

Estimating diameter at breast height and basal diameter of trees from stump measurements in Nepal's lower temperate broad-leaved forests