958 resultados para Submerged aquatic vegetations


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The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

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This paper embodies details and method of operation of a mechanical device developed for eradication of submerged aquatic weeds. The economics of operation is also discussed.

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An experiment was conducted in brackish water ponds with transplanted aquatic weed (Najas sp.) to study the effect of submerged aquatic vegetation on culture of Penaeus monodon. Out of six ponds three were without any aquatic vegetation (T1) while in other three ponds weeds were planted covering 40% of the pond bottom (T2). Hatchery produced post larva of P. monodon (0.006 g) were stocked in all ponds at a density of 40,000/ha. Shrimps were fed twice daily with commercial and formulated feed prepared from locally available ingredients. After 105 days of rearing shrimp of highest average weight (63.18g) was obtained from T2 with a survival rate of 25.90% and the total production was obtained at 654.54 kg/ha. The average weight, survival and total production of shrimp in T1 were 35.0 g, 28.76% and 405.63 kg/ha, respectively.

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In aquatic ecosystems, macrophytes and phytoplankton are main primary producers, in which macrophyte plays an important role in maintaining clear water state, while phytoplankton often dominates in turbid waterbodies. In the present study, the growth and photosynthetic activity of the submerged aquatic plant Ceratophyllum oryzetorum Kom. in different cell densities of cyanobacterial bloom are studied. The results show that the plant length and fresh mass of C. oryzetorum are promoted by low cyanobacterial cell densities. Medium and high cyanobacterial cell densities, on the contrary, act as inhibitory. Furthermore, the photosynthetic activity of C. oryzetorum is strongly inhibited by high cyanobacterial cell densities. To a certain extent, the growth of cyanobacteria is inhibited by C. oryzetorum, but no significant effect is found in this study.

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Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This study aimed to evaluate feed preference and control efficacy of grass carp (Ctenopharyngodon idella) on the aquatic macrophytes Ceratophyllum demersum, Egeria densa and Egeria najas. An experiment was carried out at mesocosms conditions with 2,000 liters capacity and water residence time of 2.8 days. C. demersum, E. densa e E. najas biomasses were offered individually with sixty g and coupled in similar quantities of 30 g of each species, evaluated during 81 days, envolving 6 treatments. (1 - C. demersum, 2 - E. najas, 3 - E. densa, 4 - C. demersum + E. najas, 5 - C. demersum + E. densa and 6 - E. najas + E. densa). When offered individually, E. najas and C. demersum presented the same predation rate by grass carp, which was higher than E. densa predation rate. When plants were tested in pairs, the order of feed preference was C. demersum > E. najas > E. densa. E. najas and C. demersum percentage control ranged from 73 to 83%. No relation between biomass consumption and grass carp body weight gain was observed, probably due to differences in nutritional quality among macrophyte species according to fish necessities. Therefore, it is concluded that the use of grass carp is one excellent technique to control submersed macrophytes in Brazil.

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Lake Okeechobee, Florida, located in the middle of the larger Kissimmee River-Lake Okeechobee-Everglades ecosystem in South Florida, serves a variety of ecosystem and water management functions including fish and wildlife habitat, flood control, water supply, and source water for environmental restoration. As a result, the ecological status of Lake Okeechobee plays a significant role in defining the overall success of the greater Everglades ecosystem restoration initiative. One of the major ecological indicators of Lake Okeechobee condition focuses on the near-shore and littoral zone regions as characterized by the distribution and abundance of submerged aquatic vegetation (SAV) and giant bulrush (Scirpus californicus(C.A. Mey.) Steud.). The objective of this study is to present a stoplight restoration report card communication system, common to all 11 indicators noted in this special journal issue, as a means to convey the status of SAV and bulrush in Lake Okeechobee. The report card could be used by managers, policy makers, scientists and the public to effectively evaluate and distill information about the ecological status in South Florida. Our assessment of the areal distribution of SAV in Lake Okeechobee is based on a combination of empirical SAV monitoring and output from a SAV habitat suitability model. Bulrush status in the lake is related to a suitability index linked to adult survival and seedling establishment metrics. Overall, presentation of these performance metrics in a stoplight format enables an evaluation of how the status of two major components of Lake Okeechobee relates to the South Florida restoration program, and how the status of the lake influences restoration efforts in South Florida.

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The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

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Seagrass communities are among the richest and most productive, photoautotrophic coastal systems in the world. They protect and improve water quality, provide shoreline stabilization, and are important habitats for an array of fish, birds, and other wildlife. Hence, much can be gained by protecting and restoring these important living resources. Human’s impact on these vital resources from population growth, pollution, and physical damage from boating and other activities can disrupt the growth of these seagrasses communities and have devastating effects on their health and vitality. Inventory and monitoring are required to determine the dynamics of seagrasses and devise better protection and restoration for these rich resources. The purpose of this seagrass workshop, sponsored by NOAA’s CSC , USGS, and FMRI, was to move toward greater objectivity and accuracy in seagrass mapping and monitoring. This workshop helped foster interaction and communication among seagrass professionals. In order to begin the process of determining the best uniform mapping process for the biological research community. Increasing such awareness among the seagrass and management communities, it is hoped that an improved understanding of the monitoring and mapping process will lead to more effective and efficient preservation os submerged aquatic vegetation. (PDF contains 20 pages)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Oxygen flux between aquatic ecosystems and the water column is a measure of ecosystem metabolism. However, the oxygen flux varies during the day in a “hysteretic” pattern: there is higher net oxygen production at a given irradiance in the morning than in the afternoon. In this study, we investigated the mechanism responsible for the hysteresis in oxygen flux by measuring the daily pattern of oxygen flux, light, and temperature in a seagrass ecosystem (Zostera muelleri in Swansea Shoals, Australia) at three depths. We hypothesised that the oxygen flux pattern could be due to diel variations in either gross primary production or respiration in response to light history or temperature. Hysteresis in oxygen flux was clearly observed at all three depths. We compared this data to mathematical models, and found that the modification of ecosystem respiration by light history is the best explanation for the hysteresis in oxygen flux. Light history-dependent respiration might be due to diel variations in seagrass respiration or the dependence of bacterial production on dissolved organic carbon exudates. Our results indicate that the daily variation in respiration rate may be as important as the daily changes of photosynthetic characteristics in determining the metabolic status of aquatic ecosystems.

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Executive Summary: The Estuary Restoration Act of 2000 (ERA), Title I of the Estuaries and Clean Waters Act of 2000, was created to promote the restoration of habitats along the coast of the United States (including the US protectorates and the Great Lakes). The NOAA National Centers for Coastal Ocean Science was charged with the development of a guidance manual for monitoring plans under this Act. This guidance manual, titled Science-Based Restoration Monitoring of Coastal Habitats, is written in two volumes. It provides technical assistance, outlines necessary steps, and provides useful tools for the development and implementation of sound scientific monitoring of coastal restoration efforts. In addition, this manual offers a means to detect early warnings that the restoration is on track or not, to gauge how well a restoration site is functioning, to coordinate projects and efforts for consistent and successful restoration, and to evaluate the ecological health of specific coastal habitats both before and after project completion (Galatowitsch et al. 1998). The following habitats have been selected for discussion in this manual: water column, rock bottom, coral reefs, oyster reefs, soft bottom, kelp and other macroalgae, rocky shoreline, soft shoreline, submerged aquatic vegetation, marshes, mangrove swamps, deepwater swamps, and riverine forests. The classification of habitats used in this document is generally based on that of Cowardin et al. (1979) in their Classification of Wetlands and Deepwater Habitats of the United States, as called for in the ERA Estuary Habitat Restoration Strategy. This manual is not intended to be a restoration monitoring “cookbook” that provides templates of monitoring plans for specific habitats. The interdependence of a large number of site-specific factors causes habitat types to vary in physical and biological structure within and between regions and geographic locations (Kusler and Kentula 1990). Monitoring approaches used should be tailored to these differences. However, even with the diversity of habitats that may need to be restored and the extreme geographic range across which these habitats occur, there are consistent principles and approaches that form a common basis for effective monitoring. Volume One, titled A Framework for Monitoring Plans under the Estuaries and Clean Waters Act of 2000, begins with definitions and background information. Topics such as restoration, restoration monitoring, estuaries, and the role of socioeconomics in restoration are discussed. In addition, the habitats selected for discussion in this manual are briefly described. (PDF contains 116 pages)

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As part of a multibeam and side scan sonar (SSS) benthic survey of the Marine Conservation District (MCD) south of St. Thomas, USVI and the seasonal closed areas in St. Croix—Lang Bank (LB) for red hind (Epinephelus guttatus) and the Mutton Snapper (MS) (Lutjanus analis) area—we extracted signals from water column targets that represent individual and aggregated fish over various benthic habitats encountered in the SSS imagery. The survey covered a total of 18 km2 throughout the federal jurisdiction fishery management areas. The complementary set of 28 habitat classification digital maps covered a total of 5,462.3 ha; MCDW (West) accounted for 45% of that area, and MCDE (East) 26%, LB 17%, and MS the remaining 13%. With the exception of MS, corals and gorgonians on consolidated habitats were significantly more abundant than submerged aquatic vegetation (SAV) on unconsolidated sediments or unconsolidated sediments. Continuous coral habitat was the most abundant consolidated habitat for both MCDW and MCDE (41% and 43% respectively). Consolidated habitats in LB and MS predominantly consisted of gorgonian plain habitat with 95% and 83% respectively. Coral limestone habitat was more abundant than coral patch habitat; it was found near the shelf break in MS, MCDW, and MCDE. Coral limestone and coral patch habitats only covered LB minimally. The high spatial resolution (0.15 m) of the acquired imagery allowed the detection of differing fish aggregation (FA) types. The largest FA densities were located at MCDW and MCDE over coral communities that occupy up to 70% of the bottom cover. Counts of unidentified swimming objects (USOs), likely representing individual fish, were similar among locations and occurred primarily over sand and shelf edge areas. Fish aggregation school sizes were significantly smaller at MS than the other three locations (MCDW, MCDE, and LB). This study shows the advantages of utilizing SSS in determining fish distributions and density.