Annual, seasonal and spatial variation of abundance of the shrimp Artemesia longinaris (Decapoda : Penaeoidea) in south-eastern Brazil

The influence of several environmental factors oil the abundance and spatial-temporal distribution of the shrimp Artemesia longinaris were investigated from January 1998 to December 1999 in the Ubatuba region of São Paulo State, Brazil. Collections were performed monthly in the bays of Ubatumirim (UBM), Ubatuba (UBA) and Mar Virado (MV). Six sampling transects were estabilshed in each bay, four were parallel to the shore line, and two were next to the rocky shores. A commercial shrimp fishing boat equipped with two 'double-rig' nets was used. A total of 11,503 individuals was collected, including 1633 from UBM, 6344 from UBA and 3526 from MV the majority of the captured specimens came from the deeper areas (15 to 20 m) with high salinity (34 to 36 ppt). The highest abundance of A. longinaris in Ubatuba bay was recorded in areas where fine and very fine sand comprised more than 70% of the sediment. Moreover, the abundance of A. longinaris followed a seasonal trend, being higher during the summer, when intrusions of cold South Atlantic Coastal Waters (SACW) are frequent. Thus, type of sediment, temperature and salinity are determinant factors in the distribution of A. longinaris in the studied region.

Social organization of marine Tucuxi dolphins, Sotalia guianensis, in the Cananeia Estuary of southeastern Brazil

Social organization is an important component of the population biology of a species that influences gene flow, the spatial pattern and scale of movements, and the effects of predation or exploitation by humans. An important element of social structure in mammals is group fidelity, which can be quantified through association indices. To describe the social organization of marine tucuxi dolphins (Sotalia guianensis) found in the Cananeia estuary, southeastern Brazil, association indices were applied to photo-identification data to characterize the temporal stability of relationships among members of this population. Eighty-seven days of fieldwork were conducted from May 2000 to July 2003, resulting in direct observations of 374 distinct groups. A total of 138 dolphins were identified on 1-38 distinct field days. Lone dolphins were rarely seen, whereas groups were composed of up to 60 individuals (mean +/- 1 SD = 12.4 +/- 11.4 individuals per group). A total of 29,327 photographs were analyzed, of which 6,312 (21.5%) were considered useful for identifying individuals. Half-weight and simple ratio indices were used to investigate associations among S. guianensis as revealed by the entire data set, data from the core study site, and data from groups composed of <= 10 individuals. Monte Carlo methods indicated that only 3 (9.3%) of 32 association matrices differed significantly from expectations based on random association. Thus, our study suggests that stable associations are not characteristic of S. guianensis in the Cananeia estuary.

Multi-criteria spatial decision analysis for demarcation of greenway: A case study of the city of Rio Claro, São Paulo, Brazil

Concern regarding hydrological resources has been a theme of growing importance in Brazil, associating the development of new management policies and maintenance of natural areas related to rivers. An efficient way to maintain natural areas around rivers has been the development of greenways, and some cites have already adopted specific legislation in this respect. Following this growing evolution in the treatment of hydrological resources, this study was carried out to demarcate a greenway along the Corumbatai River in the state of São Paulo, Using multi-criteria analysis in a GIS environment. First, thematic maps were elaborated based on Landsat 7 satellite, aerial photographs and digital topographic base, Supported by field activities. With the use of multi-criteria analysis, for which ad hoe consultations were conducted to attribute weights to the thematic maps, a suitability map was elaborated for the allocation of the greenway. Sites that should be included in the greenway were also selected, such as areas appropriate for leisure activities, and ecologically important areas. Based on the suitability map, a pathway analysis was done, connecting the relevant points of interest, thus generating a greenway that runs along the Corumbatai River, with the aim of contributing to the conservation of this important hydrological resource. (c) 2007 Elsevier B.V. All rights reserved.

Spatial electric load forecasting using an evolutionary heuristic

A method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules' representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evolutionary heuristic, which considers a stochastic behavior by crossing over similar rules. The method considers development of new zones and also redevelopment of existing ones. The results are presented in future preference maps. The tests in a real system from a midsized city show a high rate of success when results are compared with information gathered from the utility planning department. The most important features of this method are the need for few data and the simplicity of the algorithm, allowing for future scalability.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multi-Agent Framework for Spatial Load Forecasting

A multi-agent framework for spatial electric load forecasting, especially suited to simulate the different dynamics involved on distribution systems, is presented. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented as development probabilities. With this setting, different kind of agents can be developed to simulate the growth pattern of the loads in distribution systems. This paper presents two different kinds of agents to simulate different situations, presenting some promissory results.

Spatial and temporal distribution of the shrimp nematopalaemon schmitti (Decapoda: Caridea: Palaemonidae) at a subtropical enclosed bay in South America

The spatio-temporal distribution of the soft bottom dwelling shrimp Nematopalaemon schmitti and the effect of environmental conditions (sediment characteristics, temperature, salinity and dissolved oxygen) on its abundance were studied at Ubatuba Bay, south-eastern coast of Brazil. Surveys were conducted monthly from September 1995 to August 1996. Each sampling set comprised eight different transects distributed within the bay. Comparisons of CPUE of shrimp among sampling stations demonstrated that the abundance of N. schmitti was the greatest during winter, when average water temperature within the bay was considerably lower than during the rest of the year. Most shrimps (more than 95%) were collected at a single transect located at the northernmost side of the bay, demonstrating the extremely patchy distribution of this species. A multiple regression analysis using data only from this northernmost transect indicated that temperature was the most relevant factor affecting the abundance of N. schmitti during the year. Copyright © 2009 Marine Biological Association of the United Kingdom.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

Spatial load forecasting using a demand propagation approach

A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance. © 2011 IEEE.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

Considering Urban Dynamics in spatial electric load forecasting

When dealing with spatio-temporal simulations of load growth inside a service zone, one of the most important problems faced by a Distribution Utility is how to represent the different relationships among different areas. A new load in a certain part of the city could modify the load growth in other parts of the city, even outside of its radius of influence. These interactions are called Urban Dynamics. This work aims to discuss how to implement Urban Dynamics considerations into the spatial electric load forecasting simulations using multi-agent simulations. To explain the approach, three examples are introduced, including the effect of an attraction load, the effect of a repulsive load, and the effect of several attraction/repulsive loads at the same time when considering the natural load growth. © 2012 IEEE.

Caracterização fisiográfica e pedológica da região norte do estado do Ceará

Pós-graduação em Geociências e Meio Ambiente - IGCE

Temporal and spatial distribution of the commercial shrimp Litopenaeus schmitti (Dendrobranchiata: Penaeidae) in the south-eastern Brazilian coast

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Determining spatial resolution in spatial load forecasting using a grid-based model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

How marine upwelling influences the distribution of Artemesia longinaris (Decapoda: Penaeoidea)?

Upwelling events can occur in most of the oceans altering the water physical, chemical and sediment conditions and consequently the species communities dwelling the areas. For better understanding the behavior of populations inhabiting upwelling regions, the spatial and temporal distribution of a Penaeoidea shrimp was studied correlating it with the abiotic factors that vary during upwelling and non-upwelling periods in an area under influence of Cabo Frio upwelling. Bottom salinity and temperature, organic matter and sediment type from each station were sampled from March 2008 to February 2010, in six stations located between 5 and 45 m depth. The lowest temperatures were recorded during spring and summer for both years with temperature values lower than 19 degrees C. A total of 26,466 Artemesia longinaris shrimps were captured mainly in 10-35 m depth. Upwelling periods showed significant differences in abundance in relation to non-upwelling periods. The spatial distribution among stations varied according to the temperature with higher abundance in stations with values between 19 and 21 degrees C. The highest abundance of A. longinaris was recorded in spring and summer when intrusions of the cold waters of South Atlantic Central Waters (SACW) were frequent. Thus, the effect of cold water of SACW boosted by the upwelling was a determinant factor in the spatial and temporal distribution of A. longinaris in the studied region.