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How nematode morphometric attributes integrate with taxonomy-based measures along an estuarine gradient
Sroczynska, K.; Conde, A.; Chainho, P.; Adão, H. (2021). How nematode morphometric attributes integrate with taxonomy-based measures along an estuarine gradient. Ecol. Indic. 124: 107384. https://dx.doi.org/10.1016/j.ecolind.2021.107384
In: Ecological Indicators. Elsevier: Shannon. ISSN 1470-160X; e-ISSN 1872-7034, more
Peer reviewed article  

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Author keywords
    Functional traits; Nematode assemblages; Spatial gradient; Sado estuary; Bio-assessment

Authors  Top 
  • Sroczynska, K.
  • Conde, A.
  • Chainho, P.
  • Adão, H.

Abstract
    Nematodes are highly susceptible to environmental change and possess a wide array of morphological and functional characteristics for the assessment of the “Good Environmental Status”, within Marine Strategy Framework Directive. However, while the taxonomic sufficiency of nematodes in detecting spatial gradients and related ecological niche conditions is well recognized, very little is known about nematodes functional morphometric attributes in response to environmental drivers. To explore this knowledge gap, we aimed to assess the efficacy and efficiency of nematode morphometric attributes (length, width, length/width ratio, biomass) in detecting spatial patterns along a Portuguese estuarine gradient, and compare it with the taxonomic approach. We hypothesized that abundance data weighted by the morphometric attributes will have a higher explanatory power in detecting spatial patterns than using abundance of morphometric data alone.Based on the recent recommendations regarding the time and cost related efficacy of methods in biomonitoring and ecological assessments we also hypothesized that a reduced dataset based on the most common genera will suffice to capture the same distributional patterns displayed by the whole assemblage.Our results demonstrated that dataset solely based on genera abundances had consistently better explanatory power than combined datasets or morphometric datasets alone, however, combined dataset provided different spatial patterns and performed better at discriminating estuary areas. The main gradients described by the taxonomy-based dataset were related to the sediment particle size and water depth. Considering combined datasets, spatial discrimination was mainly driven by the variation in dissolved oxygen % saturation, pointing out to the importance of this variable in determining estuarine conditions substantial for nematodes morphometric distributional patterns.The same analysis repeated for the most frequent genera resulted in similar distributional patterns as for the whole assemblage dataset, clearly demonstrating that spatial estuarine gradients can be sufficiently described by using only the most frequent genera. Such information may substantially increase the efficiency of bio-assessment surveys by reducing the cost and work associated with identification and measurements of all of the individual nematode genera.

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