• Journal of Forest and Environmental Science
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• v.39 no.2
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• pp.105-117
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• 2023

Climate change and invasive alien plant species (IAPs) are having a significant impact on mountain ecosystems. The combination of climate change and socio-economic development is exacerbating the invasion of IAPs, which are a major threat to biodiversity loss and ecosystem functioning. Species distribution modelling has become an important tool in predicting the invasion or suitability probability under climate change based on occurrence data and environmental variables. MaxEnt modelling was applied to predict the current suitable distribution of most noxious weed A. adenophora (Spreng) R. King and H. Robinson and analysed the changes in distribution with the use of current (year 2000) environmental variables and future (year 2050) climatic scenarios consisting of 3 representative concentration pathways (RCP 2.6, RCP 4.5 and RCP 8.5) in Bhutan. Species occurrence data was collected from the region of interest along the road side using GPS handset. The model performance of both current and future climatic scenario was moderate in performance with mean temperature of wettest quarter being the most important variable that contributed in model fit. The study shows that current climatic condition favours the A. adenophora for its invasion and RCP 2.6 climatic scenario would promote aggression of invasion as compared to RCP 4.5 and RCP 8.5 climatic scenarios. This can lead to characterization of the species as preferring moderate change in climatic conditions to be invasive, while extreme conditions can inhibit its invasiveness. This study can serve as reference point for the conservation and management strategies in control of this species and further research.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.185-198
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• 2001

This study was conducted to reveal the effects of local climatic conditions on reproductive growth in a mature stand of Korean white pine based on climatic estimates. For this, the reproductive growth such as production and characteristics of cone and seed were first measured and summarized for seven years from 1974 to 1980. The local climatic conditions in the study site were also estimated by both a topoclimatological method and a spatial statistical technique. The local climatic conditions were then correlated with and regressed on the growth factors to reveal the relationships between the climatic estimates and the reproductive growth. Average number of conelet formation per tree showed highly negative correlation with some climatic variables related to minimum temperature in the year of flower bud differentiation. Especially, the most significant negative correlation were found between average of the minimum temperature for June and July of flower bud differentiation year and the number of conelet formation. There was no significant correlation between the number of cone production and climatic variables. However, total precipitation from December of the flowering year to February of the cone production year showed the most high correlation (r=0.6036) with the number of cone production. It was found that significant climatic variables affecting the amount of cone drop and cone drop percentage were the sum of cloudy days from June of the flowering year to August of the cone production year. Positive correlation was significantly recognized between the average weight of empty seed per cone and total precipitation from December of the flowering year to February of the cone production year. For the percentage of empty seed, five climatic variables among 19 variables were significantly correlated at 10% level. The average weight of a cone showed negative correlation with total precipitation from June of the flowering year to August of the cone production year. It was also found that average weight of a seed had highly negative correlation with total precipitation from December of the flowering year to February of the cone production year. The average weight of cone coat was negatively correlated with two climatic variables derived from clear days, which are sum of clear days from November of the flowering year to March of the cone production year and sum of clear days from December of the flowering year to February of the cone production year. On the other hand, it showed positive correlation with mean temperature of May in the flowering year. The exactly same results were obtained in correlation analysis for the percentage of cone coat.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.1
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• pp.1-11
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• 2002

This study was conducted to reveal the effects of local climatic conditions on the early growth of Korean white pine progeny test stands. For this, stand variables such as mean DBH, mean height, basal area per hectare, and volume per hectare by stand age and locality were first measured and summarized for each stand. Based on these statistics, annual increments for 10 years from stand age 10 to 20 were calculated for each of stand variables. The effects of local climatic conditions as one of environmental factors on the growth were then analyzed by both a topoclimatological method and a spatial statistical technique. From yearly climatic estimates,30 climatic indices which affect the tree growth were computed for each of the progeny test stand. The annual increments were then correlated with and regressed on the climatic indices to examine effects of local climatic conditions on the growth. Gapyung area provided the best conditions for the early growth of Korean white pine and Kwangju area ranked second. On the other hand, the growth pattern in Youngdong ranked last overall as expected. It is also found that the local growth patterns of Korean white pine in juvenile stage were affected by typical weather conditions. The conditions such as low temperature and high relative humidity provide favor environment for the early growth of Korean white pine. Especially, it was concluded that the low temperature is a main factor influencing the early growth of Korean white pine based on the results of correlation analysis and regression equations developed far the prediction of annual increments of stand variables.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.41-51
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• 1999

This study was conducted to investigate the effects of local climatic conditions on the annual increment of Korean white pine planted in Gapyung and Yaungdong. For this, stand variables such as mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique which makes use of empirical relationships between the topography and the weather in study sites was applied to produce normal estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine. Then, the yearly climatic variables from 1990 to 1997 for each study site were derived from the spatial interpolation procedures based on inverse- distance weighting of the observed deviation from the climatic normals at the nearest 11 standard weather stations. From these estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc., which affect the tree growth, were computed on yearly base for each locality. The deviations of measured annual increments from the expected annual increments for 8 years based on yield table of Korean white pine were then correlated with and regressed on the yearly weather variables to examine effects of local climatic conditions on the growth. Gapyung area provides better conditions for the growth of Korean white pine in the early stage than Youngdong area. This indicates that the conditions such as low temperature, high relative humidity, and large amount of precipitation provide favor environment for the early growth of Korean white pine. A ccording to the correlation and regression an analysis using local climatic conditions and annual increments, the growth pattern of Gapyung area corresponds to this tendency. However, it was found that the relationship between annual increments and local climatic conditions in Youngdong area shows different tendency from Gapyung. These results mean that the yearly growth pattern could not sufficiently be explained by climatic conditions with high variance in yearly weather variables. In addition, the poor growth in Youngdong area might not only be affected by climatic conditions, but also by other environmental factors such as site quality.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.1
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• pp.89-96
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• 2014

We aimed to evaluate the effects of climatic elements on potato yield and create a model with climatic elements for estimating the potato yield, using the results of the regional adjustment tests of potato. We used 86 data of the yield data of a potato variety, Sumi, from 17 regions over 11 years. According to the results, the climatic elements showed significant level of correlation coefficient with marketable yield appeared to be almost every climatic elements except wind velocity, which was daily average air temperature (Tave), daily minimum air temperature (Tmin), daily maximum air temperature(Tmax), daily range of air temperature (Tm-m), precipitation (Prec.), relative humidity (R.H.), sunshine hours (S.H.) and days of rain over 0.1 mm (D.R.) depending on the periods of days after planting or before harvest. The correlations between these climatic elements and marketable yield of potato were stepwised using SAS, statistical program, and we selected a model to predict the yield of marketable potato, which was $y=7.820{\times}Tmax_-1-6.315{\times}Prec_-4+128.214{\times}DR_-8+91.762{\times}DR_-3+643.965$. The correlation coefficient between the yield derived from the model and the real yield of marketable yield was 0.588 (DF 85).

• Korean Journal of Soil Science and Fertilizer
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• v.20 no.1
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• pp.17-22
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• 1987

An analysis was made on optimal N fertilizer for high yielding and ordinary rice varieties and their dependence upon the climatic conditions during growth stage in 1971-1979. The results obtained were summarized as follows; 1. The coefficient of variation for optimum N rates were 19.1% for high yielding varieties and 21.9% for ordinary varieties. And the those of yields at optimum N levels were 7.0% for high yielding varieties and 9.9% for ordinary varieties. 2. Optimum N fertilizer rates for high yielding varieties were 22.4kg/10a in favorable climatic years and 16.1kg/10a in unfavorable climatic years. As for ordinary varieties, optimum N levels were 19.2kg/10a in favorable climatic years and 13.0kg/10a in unfavorable climatic years. Accordingly, more N should be applied in favorable climatic years regardless of varieties. 3. This difference was derived from sunshine hours, rainfall, and relative humidity. Optimum N rates were correlated positively with sunshine hours, and negatively with rainfall and relative humidity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.102-107
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• 2015

This study was conducted to classify agro-climatic zones in Northeast district of China. For agro-climatic zoning, monthly mean temperature and precipitation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1979 and 2010 (http://disc.sci.gsfc.nasa.gov/) were collected. Altitude and vegetation fraction of East Asia from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were altitude (200 m, between 200-800 m, 800 m), vegetation fraction (60%), annual mean temperature ($0^{\circ}C$), temperature in the hottest month ($22^{\circ}C$), and annual precipitation (700 mm). In Northeast district of China, mean annual temperature, annual precipitation, and solar radiation were $3.4^{\circ}C$, 613.2 mm, and $4,414.2MJ/m^2$ between 2009 and 2013, respectively. Twenty-two agro-climatic zones identified in Northeast district of China by metrics classification method, from which the map of agro-climatic zones for Northeast district of China was derived. The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield of Northeast district of China as well as those of North Korea.

• Ecology and Resilient Infrastructure
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• v.4 no.4
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• pp.187-192
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• 2017

This study evaluated the reduction performance of ambient temperature and the amount of evaporation that takes place depends on the temperature difference of paving blocks which are used in the sidewalk, roadway, parking lot, park, plaza, and etc. The water-retentive block of the LID (Low Impact Development) practice was compared with the conventional concrete block. For the quantitative performance evaluation, experiments were performed in a climatic environment chamber capable of controlling the climatic environment (solar radiation, temperature, humidity, rainfall, and snowfall). The method for performance evaluation was proposed using temperature, humidity, and ambient air of paving blocks which changes according to the solar radiation and the wind speed after the rainfall. As a result, the evaporation amount of the water-retentive block was 2.6 times higher than that of the concrete block, the surface temperature of water-retentive block was $10^{\circ}C$ lower than the concrete block, and the air temperature of water-retentive block was $4.6^{\circ}C$ lower than the concrete block. Therefore, it is analyzed that the water-retentive block with a large amount of evaporation is more effective in reducing the urban heat island phenomenon as compared with the concrete block.

• Korean Journal of Environmental Agriculture
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• v.38 no.1
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• pp.34-37
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• 2019

BACKGROUND: A region can be divided into agroclimatic zones based on homogeneity in weather variables that have greatest influence on crop growth and yield. The agro-climatic zone has been used to identify yield variability and limiting factors for crop growth. This study was conducted to classify agro-climatic zones in the state of Mato Grosso in Brazil for predicting crop productivity and assessing crop suitability etc. METHODS AND RESULTS: For agro-climatic zonation, monthly mean temperature, precipitation, and solar radiation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1980 and 2010 were collected. Altitude and vegetation fraction of Brazil from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were temperature in the hottest month ($30^{\circ}C$), annual precipitation (600 mm and 1000 mm), and altitude (200 m and 500 m). The state of Mato Gross in Brazil was divided into 9 agro-climatic zones according to these criteria by using matrix classification method. CONCLUSION: The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield in the state of Mato Grosso in Brazil.