Chemical composition and seasonal variation of the volatile oils from Siparuna guianensis Aubl. leaves collected from Monte do Carmo, Tocantins

Siparuna guianensis Aubl., known as “negramina”, “capitu”, is a small tree used for headaches, colds, fevers, as a healing agent, insect, and tick repellents. This study aimed to evaluate the chemical composition and seasonal variability of essential oils from the leaves of S. guianensis. Botanical material was collected in Monte do Carmo, Tocantins, Brazil. The powder from the leaves was submitted to hydrodistillation in a Clevenger apparatus, and the identification of the compounds was performed by GC-MS. In volatile oils, 21.32% to 55.44% of sesquiterpenes, 19.95 to 49.73% of oxygenated sesquiterpenes, 0.48 to 1.55% of oxygenated monoterpenes, 0 to 5.67% of monoterpene hydrocarbons were identified, 0 to 48.2% of other compounds. The major compounds were γ-muurolene (13.99 to 35.97%), Curzerene (7.22-19.15%), Curzerenone (7.3-18.13%), 2-undecanone (3.99- 10.63%). The presence of two clusters was verified: cluster I, discriminated by the compounds Curzerenone, β-selinene, δ-elemene, corresponding to the months with the lowest index, and cluster II, discriminated by the β-burbonene, corresponding to the months with the highest index rainfall index. Comparing the present study with data from the literature, it is concluded that S. guianensis presents great chemical variability, which can be explained by genetic factors, seasonality, light, temperature, which can alter the production of metabolites. As S. guianensis has broad therapeutic potential as an antimicrobial and promising larvicidal activity, there is a need for agronomic studies to obtain specimens that require more interesting chemical components for the pharmaceutical industry. This study is the first carried out with oils from leaves collected in Monte do Carmo, Tocantins, Brazil.

The role of morphology on the spatial distribution of short-duration rainfall extremes in Italy

The dependence of rainfall on elevation has frequently been documented in the scientific literature and may be relevant in Italy, due to the high degree of geographical and morphological heterogeneity of the country. However, a detailed analysis of the spatial variability of short-duration rainfall extremes and their connection to the landforms does not exist. Using a new, comprehensive and position-corrected rainfall extreme dataset (I2-RED), we present a systematic study of the relationship between geomorphological forms and the average of rainfall extremes (index rainfall) across the whole of Italy. We first investigated the dependence of sub-daily rainfall depths on elevation and other landscape indices through univariate and multivariate linear regressions. After analyzing the results, we repeated the analysis on geomorphological subdivisions of Italy. The results of the national-scale regression analysis did not confirm the assumption of elevation being the sole driver of the variability of rainfall extremes. The longitude, latitude, distance from the coastline, morphological obstructions and mean annual rainfall resulted to be significantly related to the index rainfall, and to play different roles for different durations (1- to 24-hours). However, when comparing the results of the best multivariate regression models with univariate regressions for morphological subdivisions, we found that “local” rainfall-topography relationships within the geomorphological subdivisions outperformed the country-wide multiple regressions and offered a reasonable representation of the effect of morphology on rainfall extremes.

The relationship between the normalized difference vegetation index, rainfall, and potential evapotranspiration in a banana plantation of Venezuela

<p>The water supply for rainfed crops such as bananas in the Aragua state of Venezuela is often uncertain, particularly towards the beginning of the rainy season (April-May). Where climatic conditions are seasonal, the temporal evolution of the NDVI (Normalized Difference Vegetation Index) closely accompanies the interannual variation of vegetation growth in response to thermal and hydric factors. The aim of the study is to assess the relationship between NDVI, rainfall and potential evapotranspiration during the period of January/2016 to December/2017 in a Venezuelan banana plantation. In this study, the NDVI derived from the GIMMS MODIS Terra product, the daily accumulated precipitation data (mm) and the daily mean air temperature (°C) were used as the only way to estimate the potential evapotranspiration. The results showed that the GMOD09Q1-based NDVI reflects reasonably well the spatiotemporal variation in biomass accumulation. Besides, this provides information on the water stress conditions in banana plants at the plot level. The influence of Precipitation and potential evapotranspiration on the NDVI was more evident when a lag of 1 month was considered in terms of the Spearman r, implying that there is a delay in the banana phonological response to rainfall changes and dryness conditions. However, due to its low spatial resolution (i.e. 250 m), it is not adequate for the identification of banana wilt disease. Therefore, future studies are needed to assess other satellite-derived spectral indices for monitoring the health of banana plants over different sites in Venezuela.</p>

ESTUDO DA VARIABILIDADE PLUVIOMÉTRICA ESPAÇO-TEMPORAL NA MICRORREGIÃO DE SOUSA, PARAÍBA

<div class="WordSection1"><p>O Nordeste Brasileiro é uma das regiões mais problemáticas no que se refere à disponibilidade de água, portanto, se tem necessidade de atentar a práticas e métodos para desenvolvimento dessa região, visto que as condições climáticas, a hidrologia e sua vegetação são de extrema importância para compreender como esse ambiente se forma. O objetivo principal deste trabalho é verificar e avaliar a variabilidade climática da microrregião de Sousa, através da análise espaço-temporal mensal e anual da sua precipitação, identificando-se, assim, os períodos secos e chuvosos da área estudada com o auxílio do Índice de Anomalia de Chuva (IAC). Os dados pluviométricos utilizados na pesquisa correspondem às séries mensais de precipitação no período de 1994 a 2017 fornecidos pela AESA, para a avaliação temporal, espacial e para o cálculo do Índice de Anomalia de Chuva (IAC). A microrregião de Sousa apresenta dois períodos distintos, um período de cinco meses chuvosos e outro com sete meses secos. A distribuição espacial da precipitação da microrregião possui áreas bem distintas, onde a maior concentração de precipitação se localiza na parte sudoeste, em contrapartida, a região noroeste e em um ponto na parte central apresentaram valores baixos de precipitação.</p><p><strong>Palavras-chave:</strong> Períodos Secos, Períodos Chuvosos e Índice de Anomalia de Chuva.</p><p> </p><p align="center">STUDY OF SPACE-TIME PLUVIOMETRIC VARIABILITY IN THE SOUSA MICROREGION, PARAÍBA</p><p><strong>Abstract</strong></p><p>The Brazilian Northeast is one of the most problematic regions in terms of water availability. Therefore, it is necessary to consider the practices and methods for the development of this region, since climatic conditions, hydrology and vegetation are of extreme importance to understand how this environment is formed. The main objective of this work is to verify and evaluate the climatic variability of the Sousa microregion, through the monthly and annual space-time analysis of its precipitation, thus identifying the dry and rainy periods of the studied area with the aid of the Anomaly Index Rainfall (IAC). The rainfall data used in the research correspond to the monthly rainfall series from 1994 to 2017 provided by the EFSA for the temporal and spatial evaluation and for the calculation of the Rainfall Anomaly Index (IAC). The Sousa microregion has two distinct periods, one period of five rainy months and the other with seven dry months. This work has a relevance in the area of ecology, which through the results help to collaborate with the development of the microregion, which through its managers dominate the knowledge of the stations pointed to abundance and water scarcity for the anthropic activities.</p><p><strong>Key-words: </strong>Dry Periods, Rainy Periods, and Rain Anomaly Index.</p></div>

USING GLOBAL CLIMATE INDICES TO PREDICT RAINFALL AND SUGARCANE PRODUCTIVITY IN DRYLANDS OF BANYUWANGI, EAST JAVA, INDONESIA

<p>In Indonesia, sugarcane (<em>Saccharum officinarum </em>L.) is mostly cultivated in drylands, thus depending on rainfall for crop growth and development. Rainfall is an essential factor affecting sugarcane productivity. The global climate indices can be used to investigate potential of rainfall within a given area and its relationship with crop productivity. This reserach aimed to analyze the relationship between the global climate index, rainfall, and sugarcane productivity in drylands near Glenmore sugar mill, i.e., Benculuk and Jolondoro, Banyuwangi, East Java, Indonesia. The global climate index data used were the Southern Oscillation Index (SOI) and Sea Surface Temperature (SST) between 1995 and 2014. Results of this research showed that SOI and SST can be used to predict the rainfall in both Benculuk and Jolondoro. Rainfall (y) can be predicted with SST data (x) using the equation of y = -352.49x + 7724.1 in Benculuk and y = -107.32 + 3443.4 in Jolondoro, as well as with SOI data (x) using the equation of y = 38.664x + 1555.1 in Benculuk and y = 10.541x + 1567.8 in Jolondoro. Sugarcane productivity (y) in Jolondoro can be predicted using data of total rainfall (x) between October and March with the following equation: y = -0.1672x + 1157.3. This equation can be used by sugar mills, sugarcane growers, and other sugarcane-relevant stakeholders for determining the appropriate growing season.</p>

Caracterização de eventos extremos e de suas causas climáticas com base no Índice Padronizado de Precipitação Para o Leste do Nordeste

Os eventos climáticos extremos demonstram um papel significativo das sociedades, seja por sua intensidade, pela frequência de ocorrência ou pela vulnerabilidade socioambiental. Objetiva-se classificar e quantificar as precipitações na porção leste da região Nordeste (NE) do Brasil através do índice SPI, como também detectar maiores déficits e/ou excesso de precipitação. O Standardized Precipitation Index (SPI) foi utilizado para quantificar déficits de precipitação e identificar eventos secos e chuvosos em diferentes escalas temporais, auxiliando no monitoramento da sua dinâmica temporal. No cálculo do SPI foi utilizado a distribuição gama, e estimados os limites de precipitação que representam a cada categoria do índice. Foram utilizados dados pluviométricos das capitais dos estados que compõem no leste do Nordeste do Brasil, no período de 1961 a 2014 provenientes da Agência Nacional das Águas (ANA). A análise de Ondeletas foi utilizada com objetivo de identificar ciclos de extremos pluviométricos e de suas causas através das escalas temporais detectadas em séries de precipitação para as capitais do leste do Nordeste do Brasil. Os resultados mostraram que as ocorrências de secas foram as maiores em todas as cidades, todavia na categoria extrema os eventos chuvosos revelaram-se mais frequentes. Os anos normais foram os mais persistentes em todas cidades analisadas. Recife apresentou máximas ocorrências de eventos chuvosos. Os eventos com intensidade extrema, seja chuvoso ou seco, ocorreram em boa parte da série em anos de ENOS. O SPI revelou-se uma excelente ferramenta na detecção e no monitoramento de seca/chuvas na região analisada. A presença de escalas temporais relacionadas com eventos ENOS, Dipolo do Atlântico, ciclo de manchas solares e Oscilação Decadal do Pacífico foram identificadas em todas as capitais do leste do NEB. Characterization of Drought Events Based on the Standardized of Precipitation Index for the East NortheastA B S T R A C TExtreme weather events demonstrate a significant role for societies, whether by their intensity, frequency of occurrence or socio-environmental vulnerability. Objective-classify and quantify as precipitation in the eastern portion of the Northeast (NE) of Brazil through the SPI index, as well as detect larger deficits and / or excess occurrence. The Standardized Precipitation Index (SPI) was used to quantify use deficits and to identify dry and rainy events in different temporal variations, helping to monitor their temporal utilization. No SPI calculations were used for gamma distribution, and estimated capture limits representing each category of the index. Rainfall data were used from the capitals of the states that make up the eastern Northeast of Brazil, with no period from 1961 to 2014, Registration of the National Water Agency (ANA). A wave analysis was used to identify extreme rainfall cycles and their causes caused by temporary variations detected in monitoring series for the eastern capitals of Brazil. The results shown as drought occurrences were the highest in all cities, however in the extreme category of rain events most frequently revealed. The normal years were the most persistent in all cities analyzed. Recife presents maximum occurrences of rain events. Extreme intensity events, whether rainy or dry, occur in much of the series in ENSO years. The SPI revealed an excellent tool for detection and monitoring of drought / gloves in the analyzed region. The presence of temporary variations related to ENOS, Atlantic Dipole, sunspot cycle and Pacific Oscillation events are identified in all eastern NEB capitals.Keywords: SPI; extreme rainfall; drought; Wavelet analysis.

Supply Response Analysis Of Paddy In Kediri : Managerial Implications

Research of farmer’s response analysis to price is important to increase paddy production in Kediri. Farmers are conducted as the object of the research because they are the decision maker on all of farming activities. This study is aimed to know the effect of harvest area response, productivity response, supply response paddy, and managerial implications in Kediri. The analysis method used the Nerlove approach through harvest area response and productivity response. Data were collected annually from 1992 to 2015. The result showed that harvest area in previous year was the significant factor to the harvest area. Grain price, fertilizer price index, rainfall, harvest area in previous 2 years and 3 years had no significant effect. Factors which had significant impact for the productivity were grain price and productivity in the previous year, but fertilizer price index, harvest area, and rainfall had no significant effect. Paddy supply-elasticity in short term and long term was inelastic so that supply paddy was unresponsive on grain price changing. Managerial implication formulation consists of procedural implications and policy implications. Procedural implications included the use of a transplanter, jajar legowo system, use of fertilizer in 6 right-ways completed with a demonstration plot. The policy implication is was composed by price and non-price policies. Price policies were showed by costs of good sold which was supported by coopertaion between farmers and BULOG and the use of combine harvester. Non-price policies were embodied with the increasing of cropping index and wetland transformation into settlements.

Regional frequency analysis of daily rainfall extremes using L-moments approach

Daily extreme precipitation values are among environmental events with the most disastrous consequences for human society. Information on the magnitudes and frequencies of extreme precipitations is essential for sustainable water resources management, planning for weather-related emergencies, and design of hydraulic structures. In the present study, regional frequency analysis of maximum daily rainfalls was investigated for Golestan province located in the northeastern Iran. This study aimed to find appropriate regional frequency distributions for maximum daily rainfalls and predict the return values of extreme rainfall events (design rainfall depths) for the future. L-moment regionalization procedures coupled with an index rainfall methodwere applied to maximum rainfall records of 47 stations across the study area. Due to complex geographicand hydro-climatological characteristics of the region, an important research issue focused on breaking downthe large area into homogeneous and coherent sub-regions. The study area was divided into five homogeneousregions, based on the cluster analysis of site characteristics and tests for the regional homogeneity.The goodness-of-fit results indicated that the best fitting distribution is different for individual homogeneousregions. The difference may be a result of the distinctive climatic and geographic conditions. The estimatedregional quantiles and their accuracy measures produced by Monte Carlo simulations demonstrate that theestimation uncertainty as measured by the RMSE values and 90% error bounds is relatively low when returnperiods are less than 100 years. But, for higher return periods, rainfall estimates should be treated withcaution. More station years, either from longer records or more stations in the regions, would be required forrainfall estimates above T=100 years. It was found from the analyses that, the index rainfall (at-site averagemaximum rainfall) can be estimated reasonably well as a function of mean annual precipitation in Golestanprovince. Index rainfalls combined with the regional growth curves, can be used to estimate design rainfallsat ungauged sites. Overall, it was found that cluster analysis together with the L-moments based regional frequencyanalysis technique could be applied successfully in deriving design rainfall estimates for northeasternIran. The approach utilized in this study and the findings are of great scientific and practical merit, particularlyfor the purpose of planning for weather-related emergencies and design of hydraulic engineering structures