Search

Forest regeneration is the process by which new tree seedlings become entrenched after forest trees have been harvested or destroyed by fire, insects, or diseases. The process is key to sustainable forestry and can be accomplished through natural regeneration, which occurs when new seedlings or sprouts are produced by trees left on or near the site. The study is to calculate the regeneration status of the tree species in community-managed forests. The sampling points were generated by using the random table. The sample quadrate size was taken 20m×20m for a tree, 5m×5m for a sapling, and 1m×1m for the seedling. In five community forests, altogether 30 quadrates were taken for a tree, 60 nested quadrates were taken for a sapling and 120 nested quadrates were taken for a seedling. The tree layer, sapling layer and seedling layer were differentiated by taking reference tothe Diameter at Breast Height (DBH) class. An individual having DBH ≥ 5cm is considered a tree, an individual having DBH value between 1cm to < 5cm is considered a sapling, and individuals having 1cm to < 5cm DBH are considered as a seedling. The DBH distribution curve was obtained by plotting diameter class in x- axis and density on y- axis. All studied community forests are mixed forest dominated by tree species Castanopsis indica, Diospyros embryopteris (Diospyros malabarica), Shorea robusta, and Schima wallichii (Schima wallichii choisy). The regeneration potential of the Tilahar community forest(CF) is found high despite high grazing and other human intervention. The DBH class distribution curve of tree species is found as inverse J-shape, indicating that the overall forest has a sustainable regeneration.

Monsoon floods are frequent in the Tarai region of Nepal and claim thousands of lives and substantial numbers of properties every year. Certain human activities are more affected than others in the case of the same hazard. This study analyzes vulnerability to flooding among Tharu households. Data were collected by employing household surveys, group discussions, and key informant interviews in the Thapapur Village Development Committee (VDC) of Kailali district, western Tarai, Nepal. The analysis presented in this study is based on the theory that underpins the pressure and release (PAR) and access models. The results show that Tharu people are the major inhabitants in the study area and they prefer to live within their community; many ex-bonded laborers (marginalized people) choose this location for residence. Human causalities have been reduced in recent years due to easy access to cell phones, which has facilitated effective flood warnings with suitable lead times, but agriculture production loss and other losses are still high. Agricultural land is not only an important natural asset but is also considered a financial asset due to its high price and private ownership. The study concludes that subsistence agriculture-based households with small landholding sizes and less income diversification are highly vulnerable to flooding. Improper resettlement of ex-bonded laborers and land fragmentation due to separation of family members are the most prominent factors resulting in small landholdings. The results can guide government authorities to develop proper flood management strategies for the people living in the lowlands (particularly the Tarai region) of Nepal.

Migration is one of the major factors affecting population distribution of Nepal. Job opportunity, education facility, medical facility and topographic situation are the key causes of migration. Human movement from mountain to hill; hill to Tarai; and rural to urban area migration are the major trend observed in Nepal. Migration has direct impact on various sectors including financial, social, demographic, and biological. All kind of services including educational, medical, transformational, and safety services should make equally accessible over the various parts of the country. This research helps to understand the trend of internal and international labor migration in Nepal. The study has used secondary data from Department of Foreign Employment (DoFE), Central Bureau of Statistics (CBS), Ministry of Finance (MoF). Remittance is playing a crucial role in the Nepalese economy. The highest foreign labor migration was found in the year 2013/14. The trend was continuously increased until 2013/14 and it has stated decreasing thereafter. International labor migration has mostly taken place to Malaysia, Qatar, Saudi Arabia, 110 UAE and other Southeast Asian countries and it is growing over the time that has shifted the agricultural based economy towards remittance-based economy.

Drought is a very complex natural hazard and has a negative impact on the global ecosystem as a whole. Recently Bangladesh has been experiencing by different degree of dryness as a consequence of high climate variability, affecting the crop production to a great extent in the last couple of decades. In this context, the present study was made an effort to assess and analyse drought characteristics based on two drought indices, i.e., Standardized Precipitation Index (SPI) and Vegetation Condition Index (VCI), and model agricultural drought risk with Fast-and-frugal decision tree (FFT) model in Bangladesh from 2001 to 2016. We identified drought occurrence and its dynamics with three-time scale, i.e., SPI3J (November-January), SPI3A (February-April) and SPI6A (November-April), and three rice-growing seasons, i.e., Aus (March-July), Aman (June-November), and Boro (November-May) from TRMM (Tropical Rainfall Measuring Mission) and MODIS (Moderate Resolution Imaging Spectroradiometer) data. The results demonstrate that TRMM had good consistency with rain gauge measurement compared to CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record) data to derive SPI3J, SPI3A and SPI6A. Overall results confirmed that more drought frequency observed in SPI6A than SPI3J and SPI3A time scale, representing moderate to severe drought throughout the country. Regarding agricultural drought resulting from VCI demonstrated Boro rice-growing season as more vulnerable crop growing season affected by severe to extreme drought event. Validation results of VCI exhibited a high correlation with rice yield data than in-situ soil moisture data. Results of the FFT model show that out of ten predictor variables SPI3J and SPI6A caused agricultural drought with SPI value less than -1.08 and -1.21 respectively. Additionally, the model characterized SPI3J and SPI6A as the most critical driving factors with the highest balanced accuracy triggering agricultural drought risk in Bangladesh.

Urbanization is an increasing phenomenon around the world, causing many adverse effects in urban areas. Urban heat island is are of the most well-known phenomena. In the present study, surface urban heat islands (SUHI) were studied for seven megacities of the South Asian countries from 2000–2019. The urban thermal environment and relationship between land surface temperature (LST), land use landcover (LULC) and vegetation were examined. The connection was explored with remote-sensing indices such as urban thermal field variance (UTFVI), surface urban heat island intensity (SUHII) and normal difference vegetation index (NDVI). LULC maps are classified using a CART machine learning classifier, and an accuracy table was generated. The LULC change matrix shows that the vegetated areas of all the cities decreased with an increase in the urban areas during the 20 years. The average LST in the rural areas is increasing compared to the urban core, and the difference is in the range of 1–2 (°C). The SUHII linear trend is increasing in Delhi, Karachi, Kathmandu, and Thimphu, while decreasing in Colombo, Dhaka, and Kabul from 2000–2019. UTFVI has shown the poor ecological conditions in all urban buffers due to high LST and urban infrastructures. In addition, a strong negative correlation between LST and NDVI can be seen in a range of −0.1 to −0.6.

Drought has devastating impacts on agriculture and other ecosystems, and its occurrence is expected to increase in the future. However, its spatiotemporal impacts on net primary productivity (NPP) in Mongolia have remained uncertain. Hence, this paper focuses on the impact of drought on NPP in Mongolia. The drought events in Mongolia during 2003–2018 were identified using the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The Boreal Ecosystem Productivity Simulator (BEPS)-derived NPP was computed to assess changes in NPP during the 16 years, and the impacts of drought on the NPP of Mongolian terrestrial ecosystems was quantitatively analyzed. The results showed a slightly increasing trend of the growing season NPP during 2003–2018. However, a decreasing trend of NPP was observed during the six major drought events. A total of 60.55–87.75% of land in the entire country experienced drought, leading to a 75% drop in NPP. More specifically, NPP decline was prominent in severe drought areas than in mild and moderate drought areas. Moreover, this study revealed that drought had mostly affected the sparse vegetation NPP. In contrast, forest and shrubland were the least affected vegetation types.

Drought, a climate-related disaster impacting a variety of sectors, poses challenges for millions of people in South Asia. Accurate and complete drought information with a proper monitoring system is very important in revealing the complex nature of drought and its associated factors. In this regard, deep learning is a very promising approach for delineating the non-linear characteristics of drought factors. Therefore, this study aims to monitor drought by employing a deep learning approach with remote sensing data over South Asia from 2001–2016. We considered the precipitation, vegetation, and soil factors for the deep forwarded neural network (DFNN) as model input parameters. The study evaluated agricultural drought using the soil moisture deficit index (SMDI) as a response variable during three crop phenology stages. For a better comparison of deep learning model performance, we adopted two machine learning models, distributed random forest (DRF) and gradient boosting machine (GBM). Results show that the DFNN model outperformed the other two models for SMDI prediction. Furthermore, the results indicated that DFNN captured the drought pattern with high spatial variability across three penology stages. Additionally, the DFNN model showed good stability with its cross-validated data in the training phase, and the estimated SMDI had high correlation coefficient R2 ranges from 0.57~0.90, 0.52~0.94, and 0.49~0.82 during the start of the season (SOS), length of the season (LOS), and end of the season (EOS) respectively. The comparison between inter-annual variability of estimated SMDI and in-situ SPEI (standardized precipitation evapotranspiration index) showed that the estimated SMDI was almost similar to in-situ SPEI. The DFNN model provides comprehensive drought information by producing a consistent spatial distribution of SMDI which establishes the applicability of the DFNN model for drought monitoring.

This paper tried to highlights impact of flood disaster on local livelihood in Kandra river basin, Kailali District. The study also examined coping strategies of the members of flood affected village community. In so doing, required data and information were collected and generated through household survey, semi-structured interviews as well as focus group discussions, key informant interview and observations. There are almost 50 settlements in the river basin; whereas 15 settlements are along with Kandra River. Three settlements: Kanhaiyapur, Thengarpuruwa and Lalbojhi; are most frequently affected from flood disaster that were selected for the study purpose. Thirty households from each settlement have been selected for household questionnaire. Satellite images and aerial photos are used to analyze terrain, channel course. The study finds that all communities living in the low-lying area and along the riverbank are affected from flood disaster. However, not all people are vulnerable equally. To cope with this problem, local people have designed and practicing various adaptation techniques. The adaptation strategy differs based on their socio-economic condition, such as education, income, occupations and living conditions. Establishment of early warning system and capacity building of flood victims will help to cope with disasters.

Global warming threatens ecosystem functions, biodiversity, and rangeland productivity in Mongolia. The study analyzes the spatial and temporal distributions of the Net Primary Production (NPP) and its response to climatic parameters. The study also highlights how various land cover types respond to climatic fluctuations from 2003 to 2018. The Boreal Ecosystem Productivity Simulator (BEPS) model was used to simulate the rangeland NPP of the last 16 years. Satellite remote sensing data products were mainly used as input for the model, where ground-based and MODIS NPP were used to validate the model result. The results indicated that the BEPS model was moderately effective (R2 = 0.59, the Root Mean Square Error (RMSE) = 13.22 g C m−2) to estimate NPP for Mongolian rangelands (e.g., grassland and sparse vegetation). The validation results also showed good agreement between the BEPS and MODIS estimates for all vegetation types, including forest, shrubland, and wetland (R2 = 0.65). The annual total NPP of Mongolia showed a slight increment with an annual increase of 0.0007 Pg (0.68 g C per meter square) from 2003 to 2018 (p = 0.82) due to the changes in climatic parameters and land cover change. Likewise, high increments per unit area found in forest NPP, while decreased NPP trend was observed in the shrubland. In conclusion, among the three climatic parameters, temperature was the factor with the largest influence on NPP variations (r = 0.917) followed precipitation (r = 0.825), and net radiation (r = 0.787). Forest and wetland NPP had a low response to precipitation, while inter-annual NPP variation shows grassland, shrubland, and sparse vegetation were highly sensitive rangeland types to climate fluctuations.

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches&mdash, Crichton&rsquo, s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton&rsquo, s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman&rsquo, s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

Basin geomorphology is a complete system of landforms and topographic features that play a crucial role in the basin-scale flood risk evaluation. Nepal is a country characterized by several rivers and under the influence of frequent floods. Therefore, identifying flood risk areas is of paramount importance. The East Rapti River, a tributary of the Ganga River, is one of the flood-affected basins, where two major cities are located, making it crucial to assess and mitigate flood risk in this river basin. A morphometric calculation was made based on the Shuttle Radar Topographic Mission (SRTM) 30-m Digital Elevation Model (DEM) in the Geographic Information System (GIS) environment. The watershed, covering 3037.29 km2 of the area has 14 sub-basins (named as basin A up to N), where twenty morphometric parameters were used to identify flash flood potential sub-basins. The resulting flash flood potential maps were categorized into five classes ranging from very low to very high-risk. The result shows that the drainage density, topographic relief, and rainfall intensity have mainly contributed to flash floods in the study area. Hence, flood risk was analyzed pixel-wise based on slope, drainage density, and precipitation. Existing landcover types extracted from the potential risk area indicated that flash flood is more frequent along the major Tribhuvan Rajpath highway. The landcover data shows that human activities are highly concentrated along the west (Eastern part of Bharatpur) and the east (Hetauda) sections. The study concludes that the high human concentrated sub-basin “B” has been categorized as a high flood risk sub-basin, hence, a flood-resilient city planning should be prioritized in the basin.

Understanding the response of terrestrial ecosystems to future climate changes would substantially contribute to the scientific assessment of vegetation–climate interactions. Here, the spatiotemporal distribution and dynamics of vegetation in China were projected and compared based on comprehensive sequential classification system (CSCS) model under representative concentration pathway (RCP) RCP2.6, RCP4.5, and RCP8.5 scenarios, and five sensitivity levels were proposed. The results show that the CSCS model performs well in simulating vegetation distribution. The number of vegetation types would increase from 36 to 40. Frigid–perhumid rain tundra and alpine meadow are the most distributed vegetation types, with an area of more than 78.45 × 104 km2, whereas there are no climate conditions suitable for tropical–extra-arid tropical desert in China. Some plants would benefit from climate changes to a certain extent. Warm temperate–arid warm temperate zone semidesert would expand by more than 1.82% by the 2080s. A continuous expansion of more than 18.81 × 104 km2 and northward shift of more than 124.93 km in tropical forest would occur across all three scenarios. However, some ecosystems would experience inevitable changes. More than 1.33% of cool temperate–extra-arid temperate zone desert would continuously shrink. Five sensitivity levels present an interphase distribution. More extreme scenarios would result in wider ecosystem responses. The evolutionary trend from cold–arid vegetation to warm–wet vegetation is a prominent feature despite the variability in ecosystem responses to climate changes.

Landslide susceptibility assessment along the Araniko highway was done using the relationship between the landslide causative factor and presence/absence of landslide using linear discriminant analysis, and divided into Low, Medium, High, and Very High susceptibility zone. The spatial analysis of landslide distribution with its conditioning factors depicts 40°-60° of the slope, South-east and South direction of aspect, 0–5 km North from MCT, 10–20 km of distance from the epicentre, where barren land and forest area are found most susceptible to a landslide. This research can help undertake the proper mitigation and adaptation measures for the landslide risk along the Araniko highway. Keywords: Landslides, Linear discriminant analysis, Susceptibility, Araniko Highway, Factors

Nepal has been facing different kind of hazards especially water induced disaster in summer season. Many people have been affecting from disaster every year. Flood is a frequent disaster in Tarai region because of intense rainfall within a short period (June to September). Flood disaster mainly affects land- farming activities; on the other hand, many Nepalese rural people are depending on land farming as their major livelihood activities. Therefore, agriculture based human livelihoods highly vulnerable to flood disaster in Nepal. In addition to that, such disaster has a differential impact on human livelihood. The focus of the study is to find condition of livelihood vulnerability and coping strategy to flood disaster from western Nepal. Ninety-nine frequently hazard affected households were interviewed from Thapapur Village Development Committee (VDC) of Kailali district (western Tarai of Nepal) by using purposive sampling method, eight key informant interviews and two group discussions were done from three and half months' fieldwork. Livelihood framework has used to study the condition of livelihood. In addition, concept of Pressure and Release (PAR), and access model have used to analyse household vulnerability. Although there are no human causalities for seven years, the disaster has high impacts on agriculture production especially paddy cultivation, which is the major livelihood activities of the VDC. In addition to that the flood destroys house wall, enter into house and swept food grain are seasonal disaster impact in the VDC. The financial asset of household livelihood is poor in Thapapur VDC and playing negative role in livelihood building process. Diversification on income source and structural changes are major coping strategy observed in the area buts its effectiveness is differ with their economic condition. Household income dependency on agriculture has been reduced and new buildings are built flood resistant (use tall timber). The finding suggests that landholding size is the major determinant household livelihood vulnerability. When I traced back the present unsafe livelihood condition to the root cause, it is found that the main reasons of household vulnerability are improper government resettlement scheme for ex- bounded labourer, population growth and fragmentation of land, and unequal land distribution. Having poor financial asset, the household has fragile self-protection measures. In addition to that, the VDC has poor social protection measure to flood disaster and has weak structure of domination too that lead high disaster loss. Mostly people are using indigenous disaster management activities that are not sufficient to reduce the flood effect on livelihood in future. GEO350 MASV-GEOG

Two recent indigenous cases of tinea capitis in children due to pale isolates of Trichophyton violaceum are reported herein for the first time from South-East Europe (Greece). Pale isolates of Trichophyton violaceum, reported in the past as Trichophyton glabrum, are thus far sporadically reported only from African or Asian countries. The cases reported herein raise the awareness of its existence in the community, assigning special importance to its accurate identification in the clinical laboratory.

The in vivo effect of sodium valproate (SV) on the activity of uridine diphosphate glucuronosyltransferase (UDP-GT) and hepatotoxicity in the mouse liver was studied. Mice were injected intraperitoneally (IP) with SV at doses varying from 50 to 800 mg/kg per day, for six consecutive days (dose-response group) or at a standard dose of 300 mg/g per day for 2-10 days (time-response group), whereas the controls were injected with normal saline. Valproic acid levels had a positive correlation to the dose (P < 0.001) and duration of drug administration (P = 0.006). A gradual increase in UDP-GT activity was observed in doses of up to approximately 400 mg/kg per day, whereas in higher doses the enzyme activity gradually decreased. The time course of UDP-GT activity at the standard dose of 300 mg/kg per day increased progressively, with a maximum up to the sixth day and then had a gradual reduction. Hepatic necrosis (which was unrelated to the dose or the duration of drug administration) was found in 13% of the SV-treated animals and in none of the controls. We conclude that at an optimal dose (300-400 mg/kg per day) and at a time course of 6 days, SV causes liver UDP-GT induction, whereas in higher doses and longer duration of administration, UDP-GT activity is gradually reduced. SV also causes hepatotoxicity unrelated to dose and time course.

Two recent indigenous cases of tinea capitis in children due to pale isolates of Trichophyton violaceum are reported herein for the first time from South-East Europe (Greece). Pale isolates of Trichophyton violaceum, reported in the past as Trichophyton glabrum, are thus far sporadically reported only from African or Asian countries. The cases reported herein raise the awareness of its existence in the community, assigning special importance to its accurate identification in the clinical laboratory. © 2012 International Society for Human and Animal Mycology

A total of 140 non-replicate Streptococcus pneumoniae community isolates from Greek children collected during the period 1995-1997 were studied. Combined intermediate and high penicillin resistance rates were 23% in 1995, 29% in 1996, and 27% in 1997. The proportion of highly resistant isolates steadily increased from 2% in 1995 to 12% in 1997. There was no significant difference in penicillin resistance rates among colonizing and infecting isolates (23 and 27%, respectively). Over the study period, a clear shift towards higher penicillin MIC was observed among both the susceptible and resistant groups. Thus, penicillin resistance rates were equally high among colonizing and infecting isolates and resistance levels appeared to be gradually increasing throughout the entire S. pneumoniae population. (C) 1999 Elsevier Science B.V. and International Society of Chemotherapy. All rights reserved.

The in vivo effect of sodium valproate (SV) on the activity of uridine diphosphate glucuronosyltransferase (UDP-GT) and hepatotoxicity in the mouse liver was studied. Mice were injected intraperitoneally (IP) with SV at doses varying from 50 to 800 mg/kg per day, for six consecutive days (dose-response group) or at a standard dose of 300 mg/g per day for 2-10 days (time-response group), whereas the controls were injected with normal saline. Valproic acid levels had a positive correlation to the dose (P < 0.001) and duration of drug administration (P = 0.006). A gradual increase in UDP-GT activity was observed in doses of up to approximately 400 mg/kg per day, whereas in higher doses the enzyme activity gradually decreased. The time course of UDP-GT activity at the standard dose of 300 mg/kg per day increased progressively, with a maximum up to the sixth day and then had a gradual reduction. Hepatic necrosis (which was unrelated to the dose or the duration of drug administration) was found in 13% of the SV-treated animals and in none of the controls. We conclude that at an optimal dose (300-400 mg/kg per day) and at a time course of 6 days, SV causes liver UDP-GT induction, whereas in higher doses and longer duration of administration, UDP-GT activity is gradually reduced. SV also causes hepatotoxicity unrelated to dose and time course.

We prospectively examined the epidemiology of invasive Haemophilus influenzae type b (Hib) infections among children under 5 y of age in the Greater Athens area before the introduction of immunization. The annual incidence of systemic Hib infections was 12/10000. Meningitis was the most common clinical entity and accounted for 69% of the cares. In the prevaccine era, the incidence of systemic Hib disease, particularly that of meningitis, was much lower in Greece compared to rates reported from Northern and Central Europe.