• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.609-615
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• 2011

Forsythia saxatilis is a Korean endemic plant designated as rare and endangered by the Korea Forest Service (KFS). Growth and physiological characteristics of F. saxatilis were investigated under two different light intensities in order to figure out an appropriate growth environment for conservation and restoration of the species in its natural habitat. Shoot length, leaf size and weight, photosynthetic pigment content and photosynthetic parameters were measured for F. saxatilis grown at two experimental plots under relative light intensities (RLI) of 20% and 60% of the full sun, respectively. Fresh leaf weight of plants grown under high relative light intensities (RLI-60) exceeded that of plants grown at 20% RLI. The ratio of fresh leaf weight to leaf size at RLI-60 was 1.47 times superior comparing to that recorded at RLI-20. The content of photosynthetic pigments such as chlorophyll a, b and carotenoid were higher in plants grown at RLI-60, whereas the ratio of total chlorophyll to carotenoid content was higher in the leaves at RLI-20. Photosynthetic rate, stomatal conductance and transpiration rate at RLI-60 were, respectively, 2.5, 2.65 and 1.79 times higher comparing to those recorded at RLI-20. Water use efficiency, however, was higher at RLI-20. The chlorophyll/nitrogen ratio was 1.83 times higher at RLI-20 than at RLI-60. In contrast, the ratio of net photosynthesis to chlorophyll content at RLI-60 was 2.58 times higher than that of RLI-20. In conclusion, light intensity might be the major factor affecting growth and physiological characteristics of F. saxatilis grown under canopy of tall tree species.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.61-71
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• 2022

Data from an investigation of vulnerable conifer species in the subalpine zone in Korea obtained by the Korea Forest Service in 2017-2018 and monitoring research conducted by the National Institute of Forest Science since 2014 were used to analyze the status of distribution and growing condition of three major conifer species (Abies nephrolepis, Abies koreana, and Picea jezoensis) in the subalpine zone in the Baekdudaegan protected area. The distribution area of the studied species in the Baekdudaegan protected area was ca. 74% (8,035 ha) of the total distribution area in Korea, indicating that Baekdudaegan is a core area for conservation and restoration of subalpine conifer species. From decline index [A. nephrolepis in Mt. Taebaeksan and Mt. Deogyusan increased by 77.3% and 29.6%, respectively; A. koreana in Mt. Jirisan (Chunwangbong Peak) increased by 45.2% in four years; and P. jezoensis in Mt. Jirisan (Chunwangbong Peak) increased by 47.8% in two years] and seedling frequency (lower frequency of newly recruited seedlings than dead seedlings) results, the studied species are expected to face difficulties in sustainability. In contrast, at Mt. Seseoksan and Chunwangbong Peak in Mt. Jirisan, the health of trees and seedling frequency showed a partial tendency to recover and increase. In addition, we identified the relationship between the decline index and seedling frequency. These results will support the implementation of conservation strategies for vulnerable conifer species in the subalpine zone.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.