• Journal of Ecology and Environment
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• v.41 no.11
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• pp.310-317
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• 2017

Background: Many studies about climate-related range shift of plants have focused on understanding the relationship between climatic factors and plant distributions. However, consideration of adaptation factors, such as dispersal and plant physiological processes, is necessary for a more accurate prediction. This study predicted the future distribution of marlberry (Ardisia japonica), a warm-adapted evergreen broadleaved shrub, under climate change in relation to the dispersal ability that is determined by elapsed time for the first seed production. Results: We introduced climate change data under four representative concentration pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios from five different global circulation models (GCMs) to simulate the future distributions (2041~2060) of marlberry. Using these 20 different climate data, ensemble forecasts were produced by averaging the future distributions of marlberry in order to minimize the model uncertainties. Then, a dispersal-limited function was applied to the ensemble forecast in order to exam the impact of dispersal capacity on future marlberry distributions. In the dispersal-limited function, elapsed time for the first seed production and possible dispersal distances define the dispersal capacity. The results showed that the current suitable habitats of marlberry expanded toward central coast and southern inland area from the current southern and mid-eastern coast area in Korea. However, given the dispersal-limited function, this experiment showed lower expansions to the central coast area and southern inland area. Conclusions: This study well explains the importance of dispersal capacity in the prediction of future marlberry distribution and can be used as basic information in understanding the climate change effects on the future distributions of Ardisia japonica.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.16-26
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• 2019

Wetlands that provide diverse ecosystem services, such as habitat provision and hydrological control of flora and fauna, constitute ecosystems through interaction between wetlands existing in a wetlandscape. Therefore, to evaluate the wetland functions such as resilience, it is necessary to analyze the ecological connectivity that is formed between wetlands which also show hydrologically dynamic behaviors. In this study, by defining wetlands as ecological nodes, we generated ecological networks through the connection of wetlands according to the dispersal model of wetland species. The characteristics of these networks were then analyzed using various network metrics. In the case of the dispersal based on a threshold distance, while a high local clustering is observed compared to the exponential dispersal kernel and heavy-tailed dispersal model, it showed a low efficiency in the movement between wetlands. On the other hand, in the case of the stochastic dispersion model, a low local clustering with high efficiency in the movement was observed. Our results confirmed that the ecological network characteristics are completely different depending on which dispersal model is chosen, and one should be careful on selecting the appropriate model for identifying network properties which highly affect the interpretation of network structure and function.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.1
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• pp.28-42
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• 2023

Seed dispersal supports community structure, maintains genetic connectivity across fragmented landscapes, and influences vegetation assemblages. In the Philippines, only two seed dispersal studies have compared different dispersal agents. We examined the seed dispersal patterns of water, wind, birds, and bats in the Caliraya Watershed, Philippines. We aimed to determine the floral species that were dispersed and how the forest characteristics influenced seed dispersal. By running seed rain traps and drift litter collection from March to June 2022, we analyzed 14,090 seeds in a privately owned study site within the watershed. Water did not exclusively disperse any species and acted as a secondary disperser. Seed density (seeds/trap) was significantly higher for bird-dispersed (n=166) and bat-dispersed (n=145) seeds than for wind-dispersed (n=79) seeds (One-way analysis of variance [ANOVA]: F_2,87=16.21, P<0.0001). Species number (species/trap) was significantly higher for bird-dispersed (n=3.7) and bat-dispersed (n=3.9) seeds than for wind-dispersed (n=0.2) seeds (One-way ANOVA: F_2,87 =16.67, P<0.0001). Birds dispersed more species because they are more diverse and access a wider variety of fruits, unlike bats. Birds and bats target different fruits and provide separate seed dispersal services. Generalized linear model analyses revealed that the number and basal area of fleshy fruit trees most strongly influenced the bird seed dispersal patterns. Therefore, we recommend a three-way approach to restoration efforts in the Caliraya Watershed: (1) ensure the presence of fleshy fruit trees in restoration zones, (2) assist the establishment of mid-successional and wind-dispersed trees, and (3) intensify the conservation efforts for both flora and faunal diversity.

• The Journal of the Petrological Society of Korea
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• v.22 no.4
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• pp.273-289
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• 2013

Fallout ash is a notorious hazard that can have a variety of damages on agriculture and infrastructure and, most notably to aviation and human health. This study discusses the design of a conceptual model to aid in modeling the dispersal and deposition of ash from Mt. Baekdu volcano. It includes a discussion of assumptions and boundary conditions of the model as well as a detailed diagram of the conceptual model, complete with input parameters, units and equations. The two main processes contained within the model are the dispersal and deposition of ash, the outputs obtained from running the model, if designed, would be the total amount of fine ash contained in the eruption column, distance travelled by ash and ash thickness at surface.

• Journal of Environmental Impact Assessment
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• v.27 no.3
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• pp.291-306
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• 2018

This study was designed to predict potential habitat of Japanese evergreen oak (Quercus acuta Thunb.) in Korean Peninsula considering its dispersal ability under climate change. We used a species distribution model (SDM) based on the current species distribution and climatic variables. To reduce the uncertainty of the SDM, we applied nine single-model algorithms and the pre-evaluation weighted ensemble method. Two representative concentration pathways (RCP 4.5 and 8.5) were used to simulate the distribution of Japanese evergreen oak in 2050 and 2070. The final future potential habitat was determined by considering whether it will be dispersed from the current habitat. The dispersal ability was determined using the Migclim by applying three coefficient values (${\theta}=-0.005$, ${\theta}=-0.001$ and ${\theta}=-0.0005$) to the dispersal-limited function and unlimited case. All the projections revealed potential habitat of Japanese evergreen oak will be increased in Korean Peninsula except the RCP 4.5 in 2050. However, the future potential habitat of Japanese evergreen oak was found to be limited considering the dispersal ability of this species. Therefore, estimation of dispersal ability is required to understand the effect of climate change and habitat distribution of the species.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.365-370
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• 2010

The pollen dispersal by wind can make an important to understanding the viability and evolution of plants in ecological and agricultural science. Modelling can be applied to evaluate concerns about the spread of engineered pollens from genetically modified (GM) crops. Here, we are using gamma model to estimate the level of dispersal distance of pollen in the cross-pollination between two different maize (Zea mays L.) cultivars in GMO field of Korea University during the year 2010. The result of estimation of model indicates maximum pollen dispersal distance of estimated proportion of cross-pollination of maize was reached to 0.1% in 525 meter northwest due to the wind. We identify further measurements necessary to improve the accuracy of the model predictions.

• Journal of the Korea Institute of Building Construction
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• v.16 no.1
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• pp.77-85
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• 2016

This study provides the numerical model to assess retrofit and strengthen levels in the dispersal and combat facilities. First of all, it is verified that direct-hitting projectiles are more destructive to the structures rather than close-falling bombs with explosion tests. The protective capacity of dispersal and combat facilities, which are modeled with soil uncertainty and structural field data, is analyzed through finite element method. With structural survivability and facility data, the logistic regression model is drawn. This model could be used to determine the level of the retrofit and strengthen in the dispersal and combat facilities of contact areas. For more reliable model, it could be better to identify more significant factors and adapt non-linear model. In addition, for adapting this model on the spot, appropriate strengthen levels should be determined by hands on staffs associated with military facilities.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.15 no.4
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• pp.291-306
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• 2011

We consider the second order Strang splitting method to approximate the solution to the KdV equation. The model equation is split into three sets of initial value problems containing convection and dispersal terms separately. TVD MUSCL or MUSCL scheme is applied to approximate the convection term and the second order centered difference method to approximate the dispersal term. In time stepping, explicit third order Runge-Kutta method is used to the equation containing convection term and implicit Crank-Nicolson method to the equation containing dispersal term to reduce the CFL restriction. Several numerical examples of weakly and strongly dispersive problems, which produce solitons or dispersive shock waves, or may show instabilities of the solution, are presented.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.4
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• pp.15-27
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• 2024

Ecosystem-disturbing plant species pose a significant threat to native ecosystems due to their high reproductive capacity, making it essential to monitor their distribution and develop effective mitigation strategies. Consequently, it is crucial to enhance the evaluation of the impacts of these species in environmental impact assessments by incorporating scientific evidence alongside qualitative assessments. This study introduces a dispersal model into the species distribution model to simulate the potential spread of ecosystem-disturbing plant species, reflecting their ecological characteristics. Additionally, we developed mitigation scenarios and quantitatively calculated reduction rates to propose effective mitigation strategies. The species distribution model showed a reliable AUC (Area Under the Curve) of at least 0.890. The dispersal model's results were also credible, with 31 out of 34 validation coordinates falling within the predicted spread range. Simulating the impact of the spread of ecosystem-disturbing plant species over the next five years revealed that one project site had potential habitats for Ambrosia artemisiifolia, necessitating robust mitigation measures such as seed removal. Another project site, with potential habitats for Symphyotrichum pilosum, indicated that physical removal methods within the site were effective due to the species' relatively short dispersal distance. These findings can serve as fundamental data for project executors and reviewers in evaluating the impact of the spread of ecosystem-disturbing plant species during the planning stages of projects.

• International Journal of Industrial Entomology and Biomaterials
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• v.6 no.2
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• pp.163-169
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• 2003

Studies were conducted on the effect of pruning time, host age, conidial dispersal and weather parameters on the incidence and severity of mulberry leaf spot (Myrothecium roridum). The disease severity (%) increased with increase in shoot age irrespective of pruning date. Maximum disease severity was observed in plants pruned during first week of April and minimum disease severity in plants pruned during first week of March. Significant (P ＜ 0.01) influence of date of pruning, shoot age and their interaction was observed on severity of the disease. Apparent infection rate (r) was significantly higher during the plant growth period from day 48 to day 55. Average apparent yale was higher in plants pruned during first week of April and least in plants pruned during first week of July. The disease infection was negatively correlated to distance from the inoculum source. Leaf spot severity (%) was influenced by weather parameters. Multiple regression analysis revealed contribution of various combinations of weather parameters on the disease severity. Linear prediction model $(Y ＝ －81.803＋1.176x_2＋0.765x_3) with significant $R^2$ was developed for prediction of the disease under natural epiphytotic condition.