@article{fdi:010081109, title = {{S}patial management can significantly reduce d{FAD} beachings in {I}ndian and {A}tlantic {O}cean tropical tuna purse seine fisheries}, author = {{I}mzilen, {T}aha and {L}ett, {C}hristophe and {C}hassot, {E}mmanuel and {K}aplan, {D}avid}, editor = {}, language = {{ENG}}, abstract = {{D}ebris from fisheries pose significant threats to coastal marine ecosystems worldwide. {T}ropical tuna purse seine fisheries contribute to this problem via the construction and deployment of thousands of human-made drifting fish aggregating devices (d{FAD}s) annually, many of which end up beaching in coastal areas. {H}ere, we analyzed approximately 40,000 d{FAD} trajectories in the {I}ndian {O}cean and 12,000 d{FAD} trajectories in the {A}tlantic {O}cean deployed over the decade 2008-2017 to identify where and when beachings occur. {W}e find that there is tremendous promise for reducing beaching events by prohibiting deployments in areas most likely to lead to a beaching. {F}or example, our results indicate that 21% to 40% (depending on effort redistribution after closure) of beachings can be prevented if deployments are prohibited in areas in the south of 8 degrees {S} latitude, the {S}omali zone in winter, and the western {M}aldives in summer for the {I}ndian {O}cean, and in an elongated strip of areas adjacent to the western {A}frican coast for the {A}tlantic {O}cean. {I}n both oceans, the riskiest areas for beaching are not coincident with areas of high d{FAD} deployment activity, suggesting that these closures could be implemented with relatively minimal impact to fisheries. {F}urthermore, the existence of clear hotspots for beaching likelihood and the high rates of putative recovery of d{FAD} buoys by small-scale fishers in some areas suggests that early warning systems and d{FAD} recovery programs may be effective in areas that cannot be protected via closures if appropriate incentives can be provided to local partners for participating in these programs.}, keywords = {{M}arine pollution ; {F}ishing debris ; {C}oral reefs ; {F}ish aggregating device ({FAD}) ; {O}cean currents ; {ATLANTIQUE} ; {OCEAN} {INDIEN}}, booktitle = {}, journal = {{B}iological {C}onservation}, volume = {254}, numero = {}, pages = {108939 [9 ]}, ISSN = {0006-3207}, year = {2021}, DOI = {10.1016/j.biocon.2020.108939}, URL = {https://www.documentation.ird.fr/hor/fdi:010081109}, } @article{fdi:010077738, title = {{S}tability of the relationships among demersal fish assemblages and environmental-trawling drivers at large spatio-temporal scales in the northern {M}editerranean {S}ea}, author = {{M}erigot, {B}. and {G}aertner, {J}ean-{C}laude and {A}mour, {A}. {B}. and {C}arbonara, {P}. and {E}steban, {A}. and {G}arcia-{R}uiz, {C}. and {G}ristina, {M}. and {I}mzilen, {T}aha and {J}adaud, {A}. and {J}oksimovic, {A}. and {K}avadas, {S}. and {K}olitari, {J}. and {M}aina, {I}. and {M}aiorano, {P}. and {M}anfredi, {C}. and {M}icallef, {R}. and {P}eristeraki, {P}. and {R}elini, {G}. and {S}brana, {M}. and {S}pedicato, {M}. {T}. and {T}hasitis, {I}. and {V}ittori, {S}. and {V}rgoc, {N}.}, editor = {}, language = {{ENG}}, abstract = {{T}rawling pressure and environmental changes may affect the composition of fish assemblages. {O}ur knowledge on large spatio-temporal patterns of demersal fish composition remains incomplete for the {M}editerranean {S}ea. {W}e investigated (1) the spatio-temporal stability of demersal assemblages, (2) the relationships between these assemblages and potential structuring factors (trawling pressure and environmental conditions) in order to assess the dynamic of the assemblage structure at the scale of the northern {M}editerranean {S}ea. {W}e analysed a dataset of 18062 hauls from 10 to 800 m depth performed annually during the last two decades across 17 {G}eographical {S}ub-{A}reas ({GSA}s) ({MEDITS} program). {A} multi-table analysis ({STATICO}-{C}o{A}) evidenced a strong inter-{GSA}s stability in the organization of assemblages, with specificities for some {GSA}s. {T}he most stable structuring factors were linked to combined gradients of chlorophyll a, phytoplancton carbon biomass and temperature, inversely correlated with depth, salinity and nutrient gradients (axis 1 of the {STATICO}-{C}o{A} compromise, 93.74% of the total variability). {A} common pattern linking the distribution of species to these environmental gradients was evidenced for most of the 17 {GSA}s. {E}stimate of trawling pressure showed a minor role in the organization of the assemblages for the spatial scale and years investigated (axis 2. 4.67%).}, keywords = {species composition ; stability ; demersal assemblages ; environment ; fishing pressure ; large scale ; co-inertia analysis ; {STATICO}-{C}o{A} ; {MEDITERRANEE}}, booktitle = {{M}editerranean demersal resources and ecosystems : 25 years of {MEDITS} trawl surveys}, journal = {{S}cientia {M}arina}, volume = {83}, numero = {1}, pages = {153--163}, ISSN = {0214-8358}, year = {2019}, DOI = {10.3989/scimar.04954.30{A}}, URL = {https://www.documentation.ird.fr/hor/fdi:010077738}, } @article{fdi:010075192, title = {{F}ish aggregating devices drift like oceanographic drifters in the near-surface currents of the {A}tlantic and {I}ndian {O}ceans}, author = {{I}mzilen, {T}aha and {C}hassot, {E}mmanuel and {B}arde, {J}ulien and {D}emarcq, {H}erv{\'e} and {M}aufroy, {A}. and {R}oa-{P}ascuali, {L}. and {T}ernon, {J}. {F}. and {L}ett, {C}hristophe}, editor = {}, language = {{ENG}}, abstract = {{K}nowledge of ocean surface dynamics is crucial for oceanographic and climate research. {T}he satellite-tracked movements of hundreds of drifters deployed by research and voluntary observing vessels provide high-frequency and high-resolution information on near-surface currents around the globe. {C}onsequently, they constitute a major component of the {G}lobal {O}cean {O}bserving {S}ystem ({GOOS}). {H}owever, maintaining this array is costly and in some oceanic regions such as the tropics, spatio-temporal coverage is limited. {H}ere, we demonstrate that the {GPS}-buoy equipped fish aggregating devices ({FAD}s) used in tropical tuna fisheries to increase fishing success are also capable of providing comparable near-surface current information. {W}e analyzed millions of position data collected between 2008 and 2014 from more than 15,000 {FAD}s and 2,000 drifters, and combined this information with remotely-sensed near-surface current data to demonstrate that the surface velocity components of {FAD}s and drifters are highly correlated in the {A}tlantic and {I}ndian {O}ceans. {W}hile it was noted that the subsurface structures of {FAD}s did slow them down relative to the drifters, particularly in the {A}tlantic {O}cean, this bias was measurable and could be accounted for in future studies. {O}ur findings show that the physical meteorological and oceanographic data collected by fishermen could provide an invaluable source of information to the {GOOS}. {F}urthermore, by forging closer collaborations with the fishing industry and ensuring their contributions to global ocean databases are properly acknowledged, there is significant scope to capture this data more effectively.}, keywords = {{D}rifter ; {F}ish aggregating device ; {F}isheries ; {L}agrangian transport ; {O}ceanography ; {S}urface currents ; {ATLANTIQUE} ; {OCEAN} {INDIEN}}, booktitle = {}, journal = {{P}rogress in {O}ceanography}, volume = {171}, numero = {}, pages = {108--127}, ISSN = {0079-6611}, year = {2019}, DOI = {10.1016/j.pocean.2018.11.007}, URL = {https://www.documentation.ird.fr/hor/fdi:010075192}, } @incollection{fdi:010079230, title = {{S}eychelles {VMS}/logbook comparison for tuna fisheries ({FAO} {A}rea 51)}, author = {{N}ieblas, {A}.{E}. and {B}arde, {J}ulien and {L}ouys, {J}. and {L}ucas, {J}. and {A}ssan, {C}. and {I}mzilen, {T}aha and {D}alleau, {C}. and {G}erry, {C}. and {C}hassot, {E}mmanuel}, editor = {}, language = {{ENG}}, abstract = {{S}eychelles high seas tuna fleets have a high {AIS} use with a transmission frequency considerably higher than that of {VMS}. {H}owever, {AIS} has far fewer transmissions than {VMS} and many more gaps in transmission longer than a few hours. {T}he spatial coverage of the {AIS} data is good for {S}eychelles longline vessels, with acceptable coverage over the core fishing grounds. {B}y contrast, {AIS} data are deficient for purse seiners and supply vessels with most data only present around ports due to the switch-off behavior linked to the piracy threat.{C}onsistent with data coverage, {AIS} seems to be very useful in describing the spatiotemporal patterns of the longline fishery and for identifying fishing hotspots. {T}he {GFW} neural net algorithm predicts well the fishing operations for longliners but predictions for purse seiners are not informative. {M}etrics for effort at the scale of 5° x 5° squares, such as those typically used by tuna regional fisheries management organizations ({RFMO}s) for longline fisheries, are well correlated between logbooks and {GFW} algorithms. {T}hus, {GFW} is able to accurately distinguish fishing from non-fishing activities for longliners. {H}owever, the frequent breaks in transmission, perhaps due to issues with {AIS} reception, lead to consistent underprediction by {AIS} and {GFW} algorithms of the "true" patterns shown using {VMS} and logbook data. {T}he increased satellite coverage observed between 2016 and 2017 resulted in improved {GFW} algorithm performance in deriving estimations of longline fishing effort.{T}he relationships between {GFW} predictions of longline fishing and effort could be useful in data-poor fisheries where poor collection and management systems may prevent the reporting of spatial effort to the {RFMO}. {I}n such cases, the availability of {AIS} or {VMS} data combined with information on the number of hooks deployed per operation may enable predictions of gridded effort, which would improve compliance with the {C}onservation and {M}anagement {M}easures.}, keywords = {{SEYCHELLES} ; {OCEAN} {INDIEN}}, booktitle = {{G}lobal atlas of {AIS}-based fishing activity : challenges and opportunities}, numero = {}, pages = {79--108}, address = {{R}ome}, publisher = {{FAO}}, series = {}, year = {2019}, ISBN = {978-92-5-131964-2}, URL = {https://www.documentation.ird.fr/hor/fdi:010079230}, } @inproceedings{fdi:010075958, title = {{E}nrichment of trajectories with environmental data, and standardization of tagging data using {N}et{CDF}}, author = {{N}ieblas, {A}.{E}. and {B}arde, {J}ulien and {B}ernard, {S}. and {I}mzilen, {T}aha and {K}erzerho, {V}. and {R}ouyer, {S}. and {B}onhommeau, {S}.}, editor = {}, language = {{ENG}}, abstract = {{G}eolocalisation and trajectory analysis can aid in understanding the ecological processes driving an organism. {B}y associating satellite-derived environmental data with individual trajectories of electronically-tagged organisms, it could be possible to define environmental characteristics of the tagged species' functional habitats (i.e., reproduction, nutrition). {T}hese data can also help identify biotic envelopes or predict the effects of climate change on marine species distributions. {T}he objective of the present work, undertaken as a collaboration between {IFREMER} and {IRD}, is to standardize electronic tag data files into network common data format ({N}et{CDF}) format, following the standards defined within the {POPSTAR} project for tag data (doi http://dx.doi.org/10.13155/34980), and enrich the positional data with satellite-derived surface environment data (e.g., sea surface temperature, salinity, sea level) and model-derived environment data at observed depths (e.g., temperature, salinity, currents). {W}e accounted for positional uncertainty using 95%, 75%, and 50% uncertainty polygons around the estimated positions of individuals. {W}e summarised environmental conditions within these uncertainty polygons using the mean, minimum, maximum, quantiles, and standard deviation of the selected enrichment parameter. {W}e generated generic codes to enable the automatic enrichment of position data from points and polygons. {F}urthermore, we developed algorithms to convert the enriched data into {N}et{CDF} format for subsequent visualisation and analysis.}, keywords = {{ATLANTIQUE} ; {OCEAN} {INDIEN}}, numero = {{IOTC}–2018–{WPDCS}14–25_{R}ev1}, pages = {12 multigr.}, booktitle = {}, year = {2018}, URL = {https://www.documentation.ird.fr/hor/fdi:010075958}, } @inproceedings{fdi:010075959, title = {{D}escribing and accessing biological and tagging data}, author = {{B}arde, {J}ulien and {N}ieblas, {A}.{E}. and {B}londel, {E}. and {B}odin, {N}athalie and {B}onhommeau, {S}. and {C}hassot, {E}mmanuel and {I}mzilen, {T}aha}, editor = {}, language = {{ENG}}, abstract = {}, keywords = {{OCEAN} {INDIEN}}, numero = {{IOTC}–2018–{WPDCS}14–25_{R}ev1}, pages = {12 multigr.}, booktitle = {}, year = {2018}, URL = {https://www.documentation.ird.fr/hor/fdi:010075959}, } @inproceedings{fdi:010069095, title = {{M}odeling trajectories of fish aggregating devices with satellite images : use cases related to fisheries}, author = {{I}mzilen, {T}aha and {L}ett, {C}hristophe and {C}hassot, {E}mmanuel and {B}arde, {J}ulien}, editor = {}, language = {{ENG}}, abstract = {{T}his note presents some work related to analysis of {FAD} trajectories (observed and simulated) by using additional observations of {D}rifters and related simulations with a model ({I}chthyop) driven by satellite products for sea surface currents ({OSCAR}). {W}e have different goals in mind: comparisons of {FAD}s and surface drifters trajectories (by comparing in situ observations and remote sensing data), predicting the areas where {FAD} could drift, prevent damages on coral reefs, check if some species are following {FAD}s. {H}owever to deal with these use cases, the execution of thousands of simulations is a prerequisite. {W}e propose to execute the runs of the model online with following benefits: all users can run the model remotely without having to configure anything and with additional machine resources, outputs of the model can be stored and shared online and are thus already available for the next steps (post processing). {W}e present and discuss some of the possible use cases and preliminary results.}, keywords = {{OCEAN} {INDIEN} ; {SEYCHELLES}}, numero = {{IOTC}–2016–{WPDCS}12–29}, pages = {11 multigr.}, booktitle = {}, year = {2016}, URL = {https://www.documentation.ird.fr/hor/fdi:010069095}, }