Rainfall in the urban area and its impact on climatology and population growth

Due to the scarcity of studies linking the variability of rainfall and population growth in the capital cities of Northeastern Brazil (NEB), the purpose of this study is to evaluate the variability and multiscale interaction (annual and seasonal), and in addition, to detect their trends and the impact of urban growth. For this, monthly rainfall data between 1960 and 2020 were used. In addition, the detection of rainfall trends on annual and seasonal scales was performed using the Mann–Kendall (MK) test and compared with the phases of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The relationship between population growth data and rainfall data for different decades was established. Results indicate that the variability of multiscale urban rainfall is directly associated with the ENSO and PDO phases, followed by the performance of rain-producing meteorological systems in the NEB. In addition, the anthropic influence is shown in the relational pattern between population growth and the variability of decennial rainfall in the capitals of the NEB. However, no capital showed a significant trend of increasing annual rainfall (as in the case of Aracaju, Maceió, and Salvador). The observed population increase in the last decades in the capitals of the NEB and the notable decreasing trend of rainfall could compromise the region’s water security. Moreover, if there is no strategic planning about water bodies, these changes in the rainfall pattern could be compromising

Interactions of Environmental Variables and Water Use Efficiency in the Matopiba Region via Multivariate Analysis

This study aimed to evaluate the interaction of environmental variables and Water Use Efficiency (WUE) via multivariate analysis to understand the importance of each variable in the carbon–water balance in MATOPIBA. Principal Component Analysis (PCA) was applied to reduce spatial dimensionality and to identify patterns by using the following data: (i) LST (MOD11A2) and WUE (ratio between GPP-MOD17A2 and ET-MOD16A2), based on MODIS orbital products; (ii) Rainfall based on CHIRPS precipitation product; (iii) slope, roughness, and elevation from the GMTED and SRTM version 4.1 products; and (iv) geographic data, Latitude, and Longitude. All calculations were performed in R version 3.6.3 and Quantum GIS (QGIS) version 3.4.6. Eight variables were initially used. After applying the PCA, only four were suitable: Elevation, LST, Rainfall, and WUE, with values greater than 0.7. A positive correlation (≥0.78) between the variables (Elevation, LST, and Rainfall) and vegetation was identified. According to the KMO test, a series-considered medium was obtained (0.7 < KMO < 0.8), and it was explained by one PC (PC1). PC1 was explained by four variables (Elevation, LST, Rainfall, and WUE), among which WUE (0.8 < KMO < 0.9) was responsible for detailing 65.77% of the total explained variance. Positive scores were found in the states of Maranhão and Tocantins and negative scores in Piauí and Bahia. The positive scores show areas with greater Rainfall, GPP, and ET availability, while the negative scores show areas with greater water demand and LST. It was concluded that variations in variables such as Rainfall, LST, GPP, and ET can influence the local behavior of the carbon–water cycle of the vegetation, impacting the WUE in MATOPIBA

Interactions of Environmental Variables and Water Use Efficiency in the Matopiba Region via Multivariate Analysis

This study aimed to evaluate the interaction of environmental variables and Water Use Efficiency (WUE) via multivariate analysis to understand the importance of each variable in the carbon&ndash;water balance in MATOPIBA. Principal Component Analysis (PCA) was applied to reduce spatial dimensionality and to identify patterns by using the following data: (i) LST (MOD11A2) and WUE (ratio between GPP-MOD17A2 and ET-MOD16A2), based on MODIS orbital products; (ii) Rainfall based on CHIRPS precipitation product; (iii) slope, roughness, and elevation from the GMTED and SRTM version 4.1 products; and (iv) geographic data, Latitude, and Longitude. All calculations were performed in R version 3.6.3 and Quantum GIS (QGIS) version 3.4.6. Eight variables were initially used. After applying the PCA, only four were suitable: Elevation, LST, Rainfall, and WUE, with values greater than 0.7. A positive correlation (&ge;0.78) between the variables (Elevation, LST, and Rainfall) and vegetation was identified. According to the KMO test, a series-considered medium was obtained (0.7 &lt; KMO &lt; 0.8), and it was explained by one PC (PC1). PC1 was explained by four variables (Elevation, LST, Rainfall, and WUE), among which WUE (0.8 &lt; KMO &lt; 0.9) was responsible for detailing 65.77% of the total explained variance. Positive scores were found in the states of Maranh&atilde;o and Tocantins and negative scores in Piau&iacute; and Bahia. The positive scores show areas with greater Rainfall, GPP, and ET availability, while the negative scores show areas with greater water demand and LST. It was concluded that variations in variables such as Rainfall, LST, GPP, and ET can influence the local behavior of the carbon&ndash;water cycle of the vegetation, impacting the WUE in MATOPIBA

Estudo das Rajadas de Vento no Semiárido Brasileiro

To qualify the wind it is necessary to know its direction and speed. It may have interference in direction and wind speed location, time of year, air temperature, pressure of the earth's atmosphere, humidity, atmosphere and reliefs. Their knowledge is of essential importance in various sectors of human activity, including aircraft safety, navigation, civil construction, agriculture, renewable energy, transport and etc. The focus of this work is the gusts of wind recorded in different regions of the semiarid state of Alagoas (Arapiraca and Palmeira dos Índios) and Pernambuco (Garanhuns and Petrolina) in the period 2014-2018. were analyzed the seasonal direction of the gusts, mean annual speed and gust distributions (seasonal and daily), Maximum annual bursts, monthly gust distributions, occurrences above 15 m/s  and the day of the highest gust on the surface, to observe how behaves  the gusts, temperature, pressure and direction at the time of winds peak.Para qualificar o vento é necessário conhecer sua direção e velocidade. Podem ter interferência na direção e velocidade do vento a localização, época do ano, temperatura do ar, a pressão da atmosfera terrestre, a umidade, a atmosfera e o relevo. O seu conhecimento é de essencial importância em vários setores da atividade humana, entre elas a segurança das aeronaves, navegação, na construção civil, na agricultura, energia renovável, transportes e etc. O foco deste trabalho são as ocorrências das rajadas de vento registradas em regiões distintas do semiárido no estado de Alagoas (Arapiraca e Palmeira dos Índios) e de Pernambuco (Garanhuns e Petrolina) no período 2014-2018. Foram analisadas a direção sazonal das rajadas, médias da velocidade anual, distribuições das rajadas (sazonal e diária), rajadas máximas anuais, distribuições mensais das rajadas, ocorrências acima de 15 m/s e o dia de ocorrência de maior rajada de vento na superfície, para observar como se comportam as rajadas, temperatura, pressão e direção no momento dos picos de vento

Variability of Water Use Efficiency Associated with Climate Change in the Extreme West of Bahia

Water has become more important in agricultural implementations over the years, as has the need for water management. Thus, Water Use Efficiency (WUE) has been used as an alternative form of detecting the variability of water management based on the carbon–water cycle. The study aimed to map and quantify the spatio-temporal distribution of WUE based on its interactions with environmental changes. It focused on an agricultural area in the westernmost region of Bahia, Northeast Brazil (NEB). For WUE estimation, data from Collection 6 MODIS Gross Primary Productivity (GPP) and Evapotranspiration (ET) products with a spatial resolution of 0.05° × 0.05° were obtained from the Earth Explorer website. Subsequently, annual WUE anomalies were calculated based on the 2001–2019 period. The results obtained indicated that the highest values of GPP (580 gC/m2), ET (3000 mm), and WUE (3.5 gC/mm·m2) occurred in agricultural areas, associated with cultural treatments and insertion of irrigation, which helped in the higher WUE values and consequently increased agricultural productivity in the study region. In addition, there was a marked influence of the phases of the climate variability mode—El Niño-Southern Oscillation (ENSO)—on the annual variability of the WUE, with a reduction of 96% during the La Niña of 2016 (an increase of 89% during El Niño of 2005). During El Niños, vegetation had greater efficiency resulting from the adaptation of vegetation in maintaining the carbon–water balance, using water more efficiently. However, unlike Las Niñas, with excessive precipitation there is an interference in the WUE, which interferes with the absorption of radiation and nutrients for the biophysical processes of vegetation and agriculture and, consequently, agricultural production. The use of WUE for agriculture is extremely important, especially for Brazil and countries with an economy based on primary production. This information on the way vegetation (native or agricultural) responds to interactions with the environment aids in decision-making about water management, possibly lowering losses or agricultural damage caused by a lack of water

The assessment of climatic, environmental, and socioeconomic aspects of the Brazilian Cerrado

Abstract Background The Cerrado is the most biodiverse savanna and maintains other biomes. Aware of its significance, this paper evaluated the Brazilian Cerrado’s climatic, environmental, and socioeconomic aspects using remote sensing data and spatial statistics (correlation analysis and principal components analysis—PCA). Following the measures of sample adequacy (MSA) and Kaiser–Meyer–Olkin (KMO) tests, seventeen variables were evaluated. Results The MSA revealed that the dataset had a good quality (0.76), and nine variables were selected: elevation, evapotranspiration, active fires, Human Development Index (HDI), land use and land cover (LULC; shrubland and cropland/rainfed), rainfall (spring and autumn), and livestock. The correlation matrix indicated a positive (negative) association between HDI and autumn rainfall (HDI and active fires) with a value of 0.77 (− 0.55). The PCA results determined which three principal components (PC) were adequate for extracting spatial patterns, accounting for 68.02% of the total variance with respective values of 38.59%, 16.89%, and 12.5%. Due to economic development and agribusiness, Cerrado’s northern (central, western, and southern) areas had negative (positive) score HDI values, as shown in PC1. Climatic (rainfall—spring and fall) and environmental (cropland/rainfed and shrubland) aspects dominated the PC2, with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability. On the other hand, environmental aspects (LULC-shrubland and elevation) influenced the PC3; areas with high altitudes (> 500 m) received a higher score. Conclusion Agricultural expansion substantially affected LULC, leading to deforestation-caused suppression of native vegetation

Spatiotemporal Analysis of Fire Foci and Environmental Degradation in the Biomes of Northeastern Brazil

Forest fires destroy productive land throughout the world. In Brazil, mainly the Northeast of Brazil (NEB) is strongly affected by forest fires and bush fires. Similarly, there is no adequate study of long-term data from ground and satellite-based estimation of fire foci in NEB. The objectives of this study are: (i) to evaluate the spatiotemporal estimation of fires in NEB biomes via environmental satellites during the long term over 1998–2018, and (ii) to characterize the environmental degradation in the NEB biomes via orbital products during 1998–2018, obtained from the Burn Database (BDQueimadas) for 1794 municipalities. The spatiotemporal variation is estimated statistically (descriptive, exploratory and multivariate statistics) from the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Standardized Precipitation Index (SPI) through the Climate Hazards Group InfraRed Precipitation Station (CHIRPS). Moreover, we identify 10 homogeneous groups of fire foci (G1–G10) with a total variance of 76.5%. The G1 group is the most extended group, along with the G2 group, the exception being the G3 group. Similarly, the G4–G10 groups have a high percentage of hotspots, with more values in the municipality of Grajaú, which belongs to the agricultural consortium. The gradient of fire foci from the coast to the interior of the NEB is directly associated with land use/land cover (LULC) changes, where the sparse vegetation category and areas without vegetation are mainly involved. The Caatinga and Cerrado biomes lose vegetation, unlike the Amazon and Atlantic Forest biomes. The fires detected in the Cerrado and Atlantic Forest biomes are the result of agricultural consortia. Additionally, the two periods 2003–2006 and 2013–2018 show periods of severe and prolonged drought due to the action of El Niño

Spatiotemporal Analysis of Fire Foci and Environmental Degradation in the Biomes of Northeastern Brazil

Forest fires destroy productive land throughout the world. In Brazil, mainly the Northeast of Brazil (NEB) is strongly affected by forest fires and bush fires. Similarly, there is no adequate study of long-term data from ground and satellite-based estimation of fire foci in NEB. The objectives of this study are: (i) to evaluate the spatiotemporal estimation of fires in NEB biomes via environmental satellites during the long term over 1998&ndash;2018, and (ii) to characterize the environmental degradation in the NEB biomes via orbital products during 1998&ndash;2018, obtained from the Burn Database (BDQueimadas) for 1794 municipalities. The spatiotemporal variation is estimated statistically (descriptive, exploratory and multivariate statistics) from the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Standardized Precipitation Index (SPI) through the Climate Hazards Group InfraRed Precipitation Station (CHIRPS). Moreover, we identify 10 homogeneous groups of fire foci (G1&ndash;G10) with a total variance of 76.5%. The G1 group is the most extended group, along with the G2 group, the exception being the G3 group. Similarly, the G4&ndash;G10 groups have a high percentage of hotspots, with more values in the municipality of Graja&uacute;, which belongs to the agricultural consortium. The gradient of fire foci from the coast to the interior of the NEB is directly associated with land use/land cover (LULC) changes, where the sparse vegetation category and areas without vegetation are mainly involved. The Caatinga and Cerrado biomes lose vegetation, unlike the Amazon and Atlantic Forest biomes. The fires detected in the Cerrado and Atlantic Forest biomes are the result of agricultural consortia. Additionally, the two periods 2003&ndash;2006 and 2013&ndash;2018 show periods of severe and prolonged drought due to the action of El Ni&ntilde;o

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora