2015
DOI: 10.1016/j.dsr.2014.11.017
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Nonlinear ecological processes driving the distribution of marine decapod larvae

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Cited by 9 publications
(4 citation statements)
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“…g . temporal patterns of spawning, narrow ranges in pelagic larval duration, variations in reef-associated noise, wind direction, or local dynamism of the water column) [ 7 , 50 ]. The results of this study do not provide definitive evidence for either the ‘large larval patch’ or ‘dilution of a smaller larval patch at the time of settlement’ hypotheses [ 16 , 17 ].…”
Section: Discussionmentioning
confidence: 99%
“…g . temporal patterns of spawning, narrow ranges in pelagic larval duration, variations in reef-associated noise, wind direction, or local dynamism of the water column) [ 7 , 50 ]. The results of this study do not provide definitive evidence for either the ‘large larval patch’ or ‘dilution of a smaller larval patch at the time of settlement’ hypotheses [ 16 , 17 ].…”
Section: Discussionmentioning
confidence: 99%
“…To evaluate whether the dFAD moratorium's spatiotemporal strata may alter the detection of catch hotspots we ran our analyses on the With regards to the juvenile silky shark, we created an estimated abundance index from the quarterly heatmaps that summarize the European observer programme's data (Spain and France) collected between 2003 and 2015 (Lopez et al, 2020). We recreated the paper's sampling cells using the 'SpatialPolygons' function from the sp package (Pebesma & Bivand, 2012). We then overlapped these large sampling zones with the ICCAT1 × 1° grid to assign a shark abundance index value to each of the ICCAT cells.…”
Section: Case Studymentioning
confidence: 99%
“…Aspiring to develop a method for hotspot identification easier to implement and to transfer to different systems and fishery managers, we here propose self‐organizing maps (SOMs), an unsupervised artificial neural network (Kohonen, 1982). Their use is rising in ecological studies as they allow to explore patterns in large and complex datasets without a priori assumptions (Kalteh et al, 2008; Kangur et al, 2007; Park et al, 2006; Peña et al, 2015), yet they have been applied to few fisheries' studies until now (Conti et al, 2012; Hyun et al, 2005; Mendoza‐Carranza et al, 2018; Russo et al, 2016; Simić et al, 2014). Amongst their main characteristics, SOM smooth data by filtering out noise.…”
Section: Introductionmentioning
confidence: 99%
“…Decapods dominate slope communities in the BSB (Cartes & Sardà, 1993), and several studies exploring the distribution and the composition of larvae community have been carried at sub‐surface water layers (Olivar et al., 1998; Peña et al., 2015; Torres et al, 2014). Yet, larvae assemblages in deep waters remain virtually unknown.…”
Section: Introductionmentioning
confidence: 99%