Potira Meirelles Hermuche

Dynamics of Cattle Production in Brazil

Movement of livestock production within a country or region has implications for genetics, adaptation, well-being, nutrition, and production logistics, particularly in continental-sized countries, such as Brazil. Cattle production in Brazil from 1977 to 2011 was spatialized, and the annual midpoint of production was calculated. Changes in the relative production and acceleration of production were calculated and spatialized using ARCGIS®. Cluster and canonical discriminant analyses were performed to further highlight differences between regions in terms of cattle production. The mean production point has moved from the Center of Minas Gerais State (in the southeast region) to the North of Goiás State (in the Midwest region). This reflects changes in environmental factors, such as pasture type, temperature and humidity. Acceleration in production in the northern region of Brazil has remained strong over the years. More recently, “traditional” cattle-rearing regions, such as the south and southeast, showed a reduction in growth rates as well as a reduction in herd size or internal migration over the period studied. These maps showed that this movement tends to be gradual, with few regions showing high acceleration or deceleration rates.

Geographical distribution of sheep breeds in Brazil and their relationship with climatic and environmental factors as risk classification for conservation

BackgroundThe aim of this study was to evaluate the distribution of sheep breeds in Brazil, correlate their occurrence with environmental factors and determine their risk for extinction.MethodsThe localization of all flocks of purebred sheep (commerical and naturalised, hair and wool) in Brazil was spatialized in ARCGIS along with climatic (Thermal Humidity Index, precipitation, solar radiation, relative humidity) and physical environmental controls (altitude, pasture type). Data were analysed using analysis of variance, logisitic regression and cluster analyses. Distance matrices were constructed using longitude/latitude and those from environmental controls and these were correlated using Mantel test.ResultsSanta Ines and Dorper were the most popular breeds with a countrywide distribution. Over 80% of most breeds occurred within 500 km of their midpoint which has implications for their conservation and vulnerability as those breeds with few flocks and restricted geographical distribution are at higher risk. This was especially evident for the naturalised breeds. Spatial distribution of breeds was highly correlated with environmental controls and two distinct clusters were found. Spatial distribution of breeds was highly correlated with environmental controls. Naturalised sheep breeds in Brazil tend to be more localized than commercial breeds which may mean they are at greater risk. Hair and wool sheep tend to occur in specific environments.ConclusionsFlocks in the center west and northeast tend to further away from the midpoint for the breed, making germplasm exchange, and therefore avoidance of inbreeding and their conservation, more difficult.

Identificação regional da Floresta Estacional Decidual na bacia do Rio Paranã a partir da análise multitemporal de imagens MODIS

Parana river basin has one of the major fragments of Decidual Seasonal Forest in Brazil. This vegetation is widely fragmented due to the selective wood exploitation and the growth of pasture areas, what justifies the development of studies in order to understand its dynamics and preserve its diversity. Thus, the present study aimed at defining a method for regional identification of the Deciduous Forest in the Parana river basin. The deciduous forest has a typical phenological cycle in comparison with other savanna physiognomies. Due these characteristics, a temporal series of normalized difference vegetation index (NDVI) images of the MODIS sensor was used for its detection. The adopted methodology may be subdivided into the following steps: (a) elaboration of the 3D cube of NDVI images, where the z profile corresponding to temporal signature or NDVI spectrum, (b) noise elimination using the Minimum Noise Fraction (MNF) transformation, and (c) NDVI temporal variability examination of deciduous forest vegetation, with the establishment of the best NDVI band applied in the vegetation index differencing method. The Deciduous Forest presents a typical NDVI spectral behaviour, with higher values in the raining season and lower values in the dry season, what makes this kind of vegetation different from others. The employment of a changing detection algorithm between two images: one for the dry season and the other for the raining season enhances the localization of the Decidual Seasonal Forest. So, the methodology has proved to be effective for regional delimitation of Deciduous Forests considering the MODIS sensor. Considering the changing detection method, Deciduous Forest region is characterized by presenting NDVI alteration values.

Regional Identification of the Deciduous Forests of Brazil Central Using NDVI Seasonal Variations of the Sensor MODIS and Digital Elevation Model

Paranã river basin has one of the biggest fragments of Decidual Seasonal Forest in Brazil. This kind of vegetation is widely fragmented, mostly, due to the selective wood exploitation and the growth of pasture areas. Thus, many researches have been made in order to understand its dynamics and also to maintain its diversity, most of the times endemic. Thus, the present study aimed at defining a method for regional identification of the Deciduous Forest in the Paranã river basin. Due to the characteristics vegetation, a temporal sequence of MODIS images, over a period of one year, was used for its detection. The methodology adopted can be subdivided into the following steps: (a) NDVI temporal variability examination on deciduous forest vegetation, (b) the influence analysis of rainfall parameter by spatial interpolation, (c) elaboration of the geomorphology map using the DEM and terrain attributes, (d) spectral analysis of the relationships between the NDVI time series and precipitation, and (e) comparison between classified image of NDVI series and geomorphology/geology map. NDVI multi-temporal spectra had their noises treated by the MNF method, limited by the pluviometric data. The Deciduous Forest presents spectral behaviour of NDVI multi-temporal considered typical, with higher values in the raining season and lower values in the dry season, what makes this kind of vegetation different from others. So, the methodology has proved effective for regional delimitation of Deciduous Forests considering the MODIS sensor and SRTM data. Keywords-component; deciduous forest; remote sensing; MODIS; NDVI; changing detection; rainfal; DEM.