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Title

Sensitivity and robustness of larval connectivity diagnostics obtained from Lagrangian Flow Networks

AuthorsMonroy Pérez, Pedro; Rossi, Vincent ; Ser-Giacomi, Enrico ; López, Cristóbal ; Hernández-García, Emilio
KeywordsBio-physical model
Connectivity
Lagrangian Flow Network
Larval dispersion and transport
Particle-tracking model
Robustness
Sensitivity analysis
Issue Date12-Jan-2017
PublisherOxford University Press
CitationICES Journal of Marine Science 74(6): 1763-1779 (2017)
AbstractLagrangian Flow Network (LFN) is a modelling framework in which ocean sub-areas are represented as nodes in a network interconnected by links representing transport of propagules (eggs and larvae) by currents. We asses the sensitivity and robustness of four LFN-derived connectivity metrics measuring retention and exchange. The most relevant parameters are tested over large ranges and a wide region with contrasting hydrodynamics: density of released particles, node size (spatial scale of discretization), Pelagic Larval Duration (PLD) and spawning modality. We find a minimum density of released particles that guarantees reliable values for most of the metrics examined. We also find that node size has a nontrivial influence on them. Connectivity estimates for long PLDs are more robust against biological uncertainties (PLD and spawning date) than for short PLDs. For mass-spawners releasing propagules over short periods (≈ 2-10 days), daily release must be simulated to properly consider connectivity fluctuations due to variable currents. In contrast, average connectivity estimates for species that spawn repeatedly over longer durations (few weeks to few months) remain robust even using longer periodicity (5-10 days). Our results have implications to design connectivity experiments with particle-tracking models and to evaluate the reliability of their results.
Publisher version (URL)https://doi.org/10.1093/icesjms/fsw235
URIhttp://hdl.handle.net/10261/173514
DOI10.1093/icesjms/fsw235
ISSN1054-3139
E-ISSN1095-9289
Appears in Collections:(IFIC) Artículos
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