2020
DOI: 10.1016/j.marenvres.2020.105062
|View full text |Cite
|
Sign up to set email alerts
|

Long-term spatio-temporal changes of the muddy fine sand benthic community of the Bay of Seine (eastern English Channel)

Abstract: In the English Channel, the eastern Bay of Seine is exposed to numerous anthropogenic disturbances, in particular major changes in sediment dynamics, which are expected to greatly impact benthic communities. To assess the long-term effects of these stressors on the muddy fine sand benthic community, an original long-term monitoring program has been implemented since 1988. It is based on the sampling of a network of 60 stations during seven surveys over 28 years from 1988 to 2016. We investigate changes of spec… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

2
11
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
5
1
1

Relationship

1
6

Authors

Journals

citations
Cited by 17 publications
(13 citation statements)
references
References 59 publications
2
11
0
Order By: Relevance
“…In our study, the use of the station R dataset was essential to the better understanding of long‐term changes observed between only two sampling dates (1987 vs 2019). It confirms that the coupling of different spatial and temporal scales in any sampling strategy [few stations with high frequency sampling (Hewitt, Ellis & Thrush, 2016) vs low frequency larger sampling networks (Kröncke et al, 2011)] helps to track changes between long‐term sampling networks as suggested by Bacouillard et al (2020) and Callaway (2016) and that the development of such a monitoring strategy is important for the future.…”
Section: Discussionsupporting
confidence: 62%
See 2 more Smart Citations
“…In our study, the use of the station R dataset was essential to the better understanding of long‐term changes observed between only two sampling dates (1987 vs 2019). It confirms that the coupling of different spatial and temporal scales in any sampling strategy [few stations with high frequency sampling (Hewitt, Ellis & Thrush, 2016) vs low frequency larger sampling networks (Kröncke et al, 2011)] helps to track changes between long‐term sampling networks as suggested by Bacouillard et al (2020) and Callaway (2016) and that the development of such a monitoring strategy is important for the future.…”
Section: Discussionsupporting
confidence: 62%
“…The comparison to reference conditions based on pristine or slightly disturbed areas is recommended by the European WFD to track changes in environmental status, although it is generally recognized that non-disturbed marine and estuarine habitats are rare (Borja, Dauer & Grémare, 2012), and that historical data rarely constitute a pristine state (Callaway, 2016;Bacouillard et al, 2020). In this context, acceptable levels of disturbance can be used to define reference conditions (Borja, Dauer & Grémare, 2012).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…In fact, a closer look into the diversity found in this particular sample (03E/06) revealed the presence of three hydrozoans, three entoprocts, one nematode and one platyhelminth species in the metabarcoding dataset, which could have been easily unnoticed through the morphological inspection. Interestingly, although undetected through morphology, the DNA of Abra alba was also detected in this sample, a species that is often reported to live in close association with Lagis koreni (Thiébaut et al 1997, Bacouillard et al 2020). Similarly, Lagis koreni was detected only through metabarcoding in a sample (03D/06) where high densities of Abra alba were recorded by morphological inspection.…”
Section: Discussionmentioning
confidence: 75%
“…Benthic communities are commonly sampled via a network of stations and a sampling periodicity varying from seasonal to decadal. Such an approach allows detecting major changes in benthic macrofauna without being able to infer on the causes of changes (Bacouillard et al, 2020). The simultaneous sampling of several stations distributed in the area of interest makes possible to investigate temporal changes occurring at different inter-connected scales: (1) at the scale of a station, where local processes may drive the composition of communities (sedimentary changes, local anthropogenic pressures), and (2) at the scale of cluster of stations with similar composition (hereafter called assemblages), where processes operating at larger scale may drive the temporal variability (climate, diffuse and chronic anthropogenic disturbances).…”
Section: Introductionmentioning
confidence: 99%