Aquaculture is one of the fastest-growing food-producing sectors worldwide, making it desirable to assess the sustainability of aquaculture systems. The objective of this study was to develop a portfolio of quantitative indicators of economic, environmental and social sustainability to assess different aquaculture systems. The indicators were developed from 2003 to 2016, combining top-down and bottom-up methods, together with practical observations in experimental and commercial aquaculture facilities. A total of 56 economic (14), environmental (22) and social (20) indicators are proposed. Economic sustainability indicators reveal the degree of efficiency in using financial resources, the economic feasibility, resilience, and the capacity to absorb negative external costs and to generate funds for reinvestment. Environmental indicators reflect the use of natural resources, the efficiency in using resources, the release of pollutants and unused byproducts, and the risk of reducing biodiversity. Social sustainability indicators reflect the capacity to generate benefits for local communities, including jobs and food security, equitable income distribution, equality of opportunity, and inclusion of vulnerable populations. The indicators thus developed can be used on farm, regional, global or sectorial scales. They are quantitative, broad, scientifically sound, easy to understand and interpret, feasible to obtain on farms or on research stations, and permit comparison at different scales of space and time. Thus, they can be used to assess production systems and to compare different experimental treatments in research experiments. They also can be used by certifying organizations, investors, and policymakers. They allow performing diagnostics, identifying strengths and weaknesses, setting goals and determining actions, and assessing the effectiveness of actions and public policies.
The Amazon River prawn Macrobrachium amazonicum is widely distributed in lentic and lotic environments of South America, and shows different male morphotypes. In the present study, the effect of crowding on the general population structure of this species and its variation over time were evaluated. Prawns were reared in mesocosms consisting of 12 rectangular ~100 m 2 earthen ponds for ~160 d at densities of 10, 20, 40, and 80 prawns m -2 . Prawn density affected both individual and population development. Increased density reduced the size and frequency of the largest male morphotypes and reproductive females, delayed female maturation, and enhanced the asymmetry of the size distribution of individuals, increasing the frequency of smaller prawns. Although mortality was not affected up to 80 ind. m ). Therefore, the ontogeny and population development after metamorphosis are density-dependent processes. In conclusion, M. amazonicum has a dynamic and densitydependent population structure. This may be due to intrinsic regulatory mechanisms of the species and/or intraspecific competition. It seems that shifts in the sex ratio and the development pattern of male morphotypes are traits which evolved as part of the life strategy to decrease intraspecific competition in crowded conditions and to maintain a large population size. KEY WORDS: Intraspecific competition · Density-dependent factors · Sex ratio · Crustacean · Mesocosm · Macrobrachium amazonicum Resale or republication not permitted without written consent of the publisherAquat Biol 9: [291][292][293][294][295][296][297][298][299][300][301] 2010 ment plans for fisheries in order to guarantee longterm sustainability. M. amazonicum also has a high potential for aquaculture (Kutty 2005, New 2005. During the current decade, an intense research effort has been directed toward developing the technology for its commercial culture (Moraes-Valenti & Valenti 2010).Despite the high biological and economic importance of Macrobrachium amazonicum, its population biology is poorly understood. Natural populations inhabiting coastal areas show great variability in size, due to heterogeneous growth caused by the existence of 4 male morphotypes (Moraes- Riodades & Valenti 2004, Santos et al. 2006, da Silva et al. 2009). Some population studies have been performed in the eastern (KCA Silva et al. 2002a,b, 2005, MCN Silva et al. 2007) and central (Odinetz-Collart 1991a,b) Amazon basin. These studies suggest that reproduction, recruitment, and the size distribution of the prawn are site-dependent. However, the data presented did not cover other important ecological aspects, such as the population density, structure of the male morphotypes, mortality rates, reproductive capacity, intraspecific competition, and density-dependent processes. Therefore, more research is needed to fully understand the population biology of the Amazon River prawn.The aim of the present study was to evaluate the effect of density on population development of Macrobrachium amazonicum reare...
We evaluated the water characteristics and particle sedimentation in Macrobrachium amazonicum (Heller 1862) grow-out ponds supplied with a high in£ow of nutrient-rich water. Prawns were subject to di¡erent stocking and harvesting strategies: upper-graded juveniles, lower-graded juveniles, non-graded juveni-les1selective harvesting and traditional farming (non-grading juveniles and total harvest only). Dissolved oxygen, afternoon N-ammonia and N-nitrate and soluble orthophosphate were lower in the ponds in comparison with in£ow water through the rearing cycle. Ponds stocked with the upper population fraction of graded prawns showed higher turbidity, total suspended solids and total Kjeldahl nitrogen than the remaining treatments. An increase in the chemical oxygen demand:biochemical oxygen demand ratio from inlet (4.9) to pond (7.1^8.0) waters indicated a non-readily biodegradable fraction enhancement in ponds. The sedimentation mean rate ranged from 0.08 to 0.16 mm day À 1 and sediment contained 480% of organic matter. The major factors a¡ecting pond ecosystem dynamic were the organic load (due to primary production and feed addition) and bioturbation caused by stocking larger animals. Data suggest that M. amazonicum grow-out in ponds subjected to a high in£ow of nutrient-rich water produce changes in the water properties, huge accumulation of organic sediment at the pond bottom and non-readily biodegradable material in the water column. However, the water quality remains suitable for aquaculture purposes. Therefore, nutrient-rich waters, when available, may represent a source of unpaid nutrients, which may be incorporated into economically valued biomass if managed properly.
The effects of artificial substrate and night-time aeration on the culture of Macrobrachium amazonicum were evaluated in 12 ponds stocked with 45 prawns m À2 . A completely randomized design in 2 9 2 factorial scheme with three replicates was used. The combination of factors resulted in four treatments: with substrate and aeration (SA), with substrate and without aeration (SWA), without substrate and with aeration (WSA) and without substrate and aeration (WSWA). The presence of substrate in SA and SWA treatments reduced suspended particles (seston) by~17.3% and P-orthophosphate by~50%. The use of aerator (WSA and SA treatments) significantly (P < 0.05) increased the concentration of dissolved oxygen, suspended particles and nutrients in the pond water. These results indicate that the effect of substrate on turbidity and total suspended solids (TSS) values is opposite to the effect of the aerator. The aerators in semiintensive grow-out M. amazonicum farming lower water quality because they increased the amount of detritus and nutrients in the pond water. On the other hand, the use of artificial substrate reduces turbidity values, chlorophyll a, TSS and P-orthophosphate concentrations. Therefore, the combination of substrate addition and night-time aeration is not interesting because they have opposite effects.
Todo o conteúdo deste livro está licenciado sob uma Licença de Atribuição Creative Commons. Atribuição 4.0 Internacional (CC BY 4.0). O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores. Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterá-la de nenhuma forma ou utilizá-la para fins comerciais.
Esse trabalho teve como objetivo avaliar a precisão e a acurácia do processamento de imagens digitais terrestres no monitoramento do desenvolvimento da macrófita aquática Lemna sp. Cerca de 1.281 plantas de lemna foram distribuídas em três delimitadores de área, no interior de um tanque de piscicultura, e tiveram seu desenvolvimento monitorado durante quinze dias consecutivos, por meio de imagens digitais capturadas em nível terrestre, com uma câmera digital Samsung, sensor 1/2,3", CCD com 12,3 megapíxels. As imagens digitais foram processadas em Sistema de Informação Geográfica, sendo utilizado como classificador digital o método da máxima verossimilhança. A avaliação da precisão foi realizada pela comparação das áreas mapeadas e a acurácia por meio do nível de reconhecimento dos pixels classificados. Os resultados revelam o potencial da técnica no monitoramento diário do desenvolvimento e da distribuição espacial da macrófita. Acrescenta-se que a técnica, além de ser de fácil realização, não afeta o desenvolvimento das plantas. Palavras-chave: Sensoriamento remoto terrestre. Processamento de imagens. Técnicas de medição. Ecologia aquática. 4 Conclusão Os resultados revelam o potencial da técnica para o monitoramento diário do desenvolvimento e da distribuição espacial de macrófitas. Trata-se de uma técnica de fácil aplicação, que não afeta o desenvolvimento das plantas.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.