Sandy beaches: state of the art of nematode ecology
In: Anais da Academia Brasileira de Ciencias. Academia Brasileira de Ciencias: Rio de Janeiro. ISSN 0001-3765; e-ISSN 1678-2690, more
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| Keywords |
Aquatic communities > Benthos
Biodiversity
Climatic changes
Food webs
Marine/Coastal |
| Author keywords |
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| Authors | | Top |
- Maria, T.F.
- Vanaverbeke, J., more
- Vanreusel, A., more
- Esteves, A.M.
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| Abstract |
In this review, we summarize existing knowledge of the ecology of sandy-beach nematodes, in relation to spatial distribution, food webs, pollution and climate change. We attempt to discuss spatial scale patterns (macro-, meso- and microscale) according to their degree of importance in structuring sandy-beach nematode assemblages. This review will provide a substantial background on current knowledge of sandy-beach nematodes, and can be used as a starting point to delineate further investigations in this field. Over decades, sandy beaches have been the scene of studies focusing on community and population ecology, both related to morphodynamic models. The combination of physical factors (e.g. grain size, tidal exposure) and biological interactions (e.g. trophic relationships) is responsible for the spatial distribution of nematodes. In other words, the physical factors are more important in structuring nematodes communities over large scale of distribution while biological interactions are largely important in finer-scale distributions. It has been accepted that biological interactions are assumed to be of minor importance because physical factors overshadow the biological interactions in sandy beach sediments; however, the most recent results from in-situ and ex-situ experimental investigations on behavior and biological factors on a microscale have shown promise for understanding the mechanisms underlying larger-scale patterns and processes. Besides nematodes are very promising organisms used to understand the effects of pollution and climate changes although these subjects are less studied in sandy beaches than distribution patterns. |
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