PREDICTION OF SUSCEPTIBILITY FOR OLD TREES (> 100 YEARS OLD) TO FALL IN BOGOR BOTANICAL GARDEN

Since the establishment of the Bogor Botanical Garden (BBG) in 1817, the protection of the tree collections, even the loss of aging trees (> 100 years old), has been one of its most important tasks. Abiotic factors such as intense extreme events, i.e., heavy rainfall and strong winds, as well as biotic factors from human activities, pests and diseases, and the deterioration of the health of the plant collection with age, has threatened the survival of the old tree collections. As the BBG has many functions for conservation and human ecological activities, tree fall accidents have become a primary concern in preventing the loss of biodiversity and human life. Therefore, disaster map zonation is required to prevent and minimize such accident together with a prediction of which individual specimen is likely to fall. We examined the health of 154 to determine the falling probability of 1106 aged trees based on several factors that might cause the fall in the past and to make model predictions generated by nine supervised machine learning algorithms to get a binary value of falling probability and then classified into four categories (neglectable, low, moderate, and high probability of falling). Inverse Distance Weighted interpolation method was used to depict a zone map of trees prone to fall in BBG. We found 885 susceptible trees, of which 358 individual trees were highly susceptible to fall (red zone color), dominated by families from Fabaceae, Lauraceae, Moraceae, Meliaceae, Dipterocarpaceae, Sapindaceae, Rubiaceae, Myrtaceae, Araucariaceae, Malvaceae, and Anacardiaceae. This result was based on Random Forest model due to its highest accuracy among algorithms and its lowest false negative (FN) value. The FN value was important to minimize error calculation on aged trees that were not prone to fall but turned out to be prone to fall. The dominant factor contributing to high falling intensity was hollow and brittle on the tree trunks where many were found to have pests inside damaged parts such as termites, wood-borers, and bark-eaters. Several trees were found to have combined damages with more than a single causative factor that exacerbated tree’s health and increased falling probability

Decay Tree Detection in Bogor Botanic Gardens Collection Using Sonic Tomograph Technology

Bogor Botanic Gardens is an ex-situ plant conservation area in Indonesia. Since BBG is 103 years old, many collections are 100 years old or older. These antique collections may sustain damage, such as broken or collapsing, endangering visitors and employees. As a result, monitoring tree health at BBG is a critical task. According to the tree health monitoring data, 73 of 244 trees were further checked using the PiCUS Sonic Tomograph. Trees from the Fabaceae (31%) and Myrtaceae (10%) families were the most frequently checked. Walnuts trees from the Burseraceae family had the most specimens (47,94%). The PST effectively provides an immediate picture of the stem condition by calculating solid and decaying wood percentage values

Decay Tree Detection in Bogor Botanic Gardens Collection Using Sonic Tomograph Technology

Bogor Botanic Gardens is an ex-situ plant conservation area in Indonesia. Since BBG is 103 years old, many collections are 100 years old or older. These antique collections may sustain damage, such as broken or collapsing, endangering visitors and employees. As a result, monitoring tree health at BBG is a critical task. According to the tree health monitoring data, 73 of 244 trees were further checked using the PiCUS Sonic Tomograph. Trees from the Fabaceae (31%) and Myrtaceae (10%) families were the most frequently checked. Walnuts trees from the Burseraceae family had the most specimens (47,94%). The PST effectively provides an immediate picture of the stem condition by calculating solid and decaying wood percentage values

Effect of Pyroclastic Cloud from Merapi Volcano to the Survival of Uromycladium Tepperianum on Falcataria Moluccana in Yogyakarta, Indonesia

AbstractGroup of rust fungi have strong mechanism for adaptation and changed their pathogenecity under critical condition, includ characteristics, survival and pathogenecity of U. tepperianum in Falcataria moluccana. Inoculums of U. tepperianum were taken from sengon trees in the Southern hill of Merapi volcano which showed symptoms of gall on 3 different distance of area affected by pyroclastic cloud, i.e. danger (3-7km), alert (>7-11km) and warning (>11-15km) from the top of Merapi. Three locations from each distance were randomly chosen, namely fire (directly affected), border (indirectly affected) and green (completely uninfluenced) by pyroclastic cloud. Based on artificial inoculation test, pathogenecity of each inoculum was observed. The color, size and shape of teliospore as well as texture and color of gall were observed using qualitative and quantitative assessment. Survival and aggressiveness of U. tepperianum in the fire were lower than in the border or green location in all distances. However, in the border location itself, the spores of U. tepperianum is more pathogenic, represent by higher percentage of germination, penetration, and infection than in the both locations. This result was also supported by the characteristic of teliospores that were bigger, brighter, had better integrity shape (round) in the border location. One of obvious case due to local environmental changing caused by Merapi eruption was the increasing of aggressiveness of the gall rust disease caused by U. tepperianum on F. moluccana