TREE STRATIFICATION BASED ON ERUPTION DAMAGE LEVEL IN MOUNT MERAPI NATIONAL PARK YOGYAKARTA INDONESIA

Mount Merapi’s eruption has caused damage to the forests in the Mount Merapi National Park (MMNP). Nine years after the eruption, the vertical structure of vegetation can illustrate the progress of succession. This study aimed to analyze the tree composition and stratification in different forest damage levels after the 2010 Merapi eruption. The study was conducted in March 2019 at three stations, namely station A (heavy damage area), station B (moderate damage area), and station C (minor damage area). Vegetation parameters in each station were taken in a 10x100 plot and were processed using a tree profile diagram. Abiotic parameters were measured in each plot and analyzed using the correlation test. The results showed that the three stations were still dominated by the tree in Stratum C, but the tree density and tree height varied in proportion to the damage level. Station A in the heavy damage area has the lowest tree density (23 trees/0.1 ha) with a maximum tree height of 12 meters, in contrast to Station C in the minor damage area with tree density reaching 195 trees/0.1 ha and maximum tree height reaching 30 meters. Nine years after the Mount Merapi big eruption, the MMNP forests in Yogyakarta Province are still classified as young secondary forests. Key words: diagram, profile, succession, structure, vertical

Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

Mapping Maximum Tree Height of the Great Khingan Mountain, Inner Mongolia Using the Allometric Scaling and Resource Limitations Model

Maximum tree height is an important indicator of forest vegetation in understanding the properties of plant communities. In this paper, we estimated regional maximum tree heights across the forest of the Great Khingan Mountain in Inner Mongolia with the allometric scaling and resource limitations model. The model integrates metabolic scaling theory and the water–energy balance equation (Penman–Monteith equation) to predict maximum tree height constrained by local resource availability. Monthly climate data, including precipitation, wind speed, vapor pressure, air temperature, and solar radiation are inputs of this model. Ground measurements, such as tree heights, diameters at breast height, and crown heights, have been used to compute the parameters of the model. In addition, Geoscience Laser Altimeter System (GLAS) data is used to verify the results of model prediction. We found that the prediction of regional maximum tree heights is highly correlated with the GLAS tree heights (R2 = 0.64, RMSE = 2.87 m, MPSE = 12.45%). All trees are between 10 to 40 m in height, and trees in the north are taller than those in the south of the region of research. Furthermore, we analyzed the sensitivity of the input variables and found the model predictions are most sensitive to air temperature and vapor pressure.

Environmental harshness drives spatial heterogeneity in biotic resistance

Ecological communities often exhibit greater resistance to biological invasions when these communities consist of species that are not closely related. The effective size of this resistance, however, varies geographically. Here we investigate the drivers of this heterogeneity in the context of known contributions of native trees to the resistance of forests in the eastern United States of America to plant invasions. Using 42,626 spatially referenced forest community observations, we quantified spatial heterogeneity in relationships between evolutionary relatedness amongst native trees and both invasive plant species richness and cover. We then modelled the variability amongst the 91 ecological sections of our study area in the slopes of these relationships in response to three factors known to affect invasion and evolutionary relationships –environmental harshness (as estimated via tree height), relative tree density and environmental variability. Invasive species richness and cover declined in plots having less evolutionarily related native trees. The degree to which they did, however, varied considerably amongst ecological sections. This variability was explained by an ecological section’s mean maximum tree height and, to a lesser degree, SD in maximum tree height (R2GLMM = 0.47 to 0.63). In general, less evolutionarily related native tree communities better resisted overall plant invasions in less harsh forests and in forests where the degree of harshness was more homogenous. These findings can guide future investigations aimed at identifying the mechanisms by which evolutionary relatedness of native species affects exotic species invasions and the environmental conditions under which these effects are most pronounced.

Performance of some apricot (Prunus armeniaca L.) germplasm accessions for fruit quality traits in Himachal Pradesh

The present investigation was carried out in field gene bank of NBPGR Regional Station Phagli, Shimla during the year 2014-15. Twenty accessions of Prunus armeniaca L. namely St. Ambroise, Wenatchee, Nugget, Stirling, Nari, Harogem, Rakovslik, Viva Gold, IC-432145, Erevani, Safed Perchinar, KS-1, AS-1, AS-2, NJ-A96, Jordan Early, Vitillo, Shahib, Kalola and Anglo Arsani were evaluated for their tree, foliage, floral and fruit characters. St. Ambroise recorded maximum tree height (10.10 m) whereas minimum (2.47 m) was in Stirling. Shedding of leaf started from 29 th October (Nugget) and extended till 27 th November (Vitillo). Time of full bloom extended from 16 th March in Shahib to 23 rd March in Safed Perchinar. The longest duration (22 days) of flowering was recorded in Erevani and shortest (9 days) in Wenatchee. Time of fruit maturity was early (25 th May) in Shahib and late (26 th June) in Vitillo. Largest and heaviest fruits were observed in St. Ambroise (77.59 g) whereas smallest and lightest fruits were in Viva Gold (19.37 g). Maximum pulp to stone ratio was recorded in Safed Perchinar (33.21) and minimum in Nari (15.57). TSS content was maximum (19.56 °B) in Nari whereas minimum (10.73°B) in Anglo Arseni. Titratable acidity was recorded maximum (1.86 %) in AS-1 and minimum (0.76%) in IC 432145. Total sugar content ranged from 8.40 per cent in Anglo Arseni to 16.53 per cent in Nari. Total phenol content was maximum (89.57 mg/100 g) in AS-1 and minimum (70.41 mg/100 g) in IC432145. From the present investigation it may be concluded that St. Ambroise, Nari and Shahib can be used for gene source for developing new hybrid cultivars and St. Am-broise may be suggested for cultivation in wet temperate condition of Himachal Pradesh for its better quality.

Altitudinal filtering of large-tree species explains above-ground biomass variation in an Atlantic Central African rain forest

Patterns in above-ground biomass of tropical forests over short altitudinal gradients are poorly known. The aim of this study was to investigate the variation of above-ground biomass with altitude in old-growth forests and determine the importance of changes in floristic composition as a cause of this variation. We used a dataset from 15 1-ha permanent plots established from lowland (200 m asl) to submontane forests (900 m asl) in the Ngovayang Massif, south-western Cameroon. We analysed variation over altitude in two specific functional traits, the potential maximum tree height and the wood density. Forest above-ground biomass decreased from 500–600 Mg ha−1 in lowland plots to around 260 Mg ha−1 at the highest altitudes. The contribution to above-ground biomass of large-tree species (dbh ≥ 70 cm) decreased with altitude, while the contribution of smaller trees was constant. Contribution of the Fabaceae subfamily Caesalpinioideae decreased with altitude, while those of Clusiaceae, Phyllanthaceae and Burseraceae increased. While potential maximum tree height significantly decreased, wood specific gravity displayed no trend along the gradient. Finally, the decrease in above-ground biomass along the short altitudinal gradient can be at least partially explained by a shift in species composition, with large-tree species being filtered out at the highest altitudes. These results suggest that global change could lead to significant shifts in the properties of montane forests over time.