Assessing larval dispersal is essential to understand the structure and dynamics of marine populations. However, knowledge about early-life dispersal is sparse, and so is our understanding of the spawning process, perhaps the most obscure component of biphasic life cycles. Indeed, the poorly known species-specific spawning modality and early-life traits, along with the high spatio-temporal variability of the oceanic circulation experienced during larval drift, hamper our ability to properly appraise the realized connectivity of coastal fishes. Here, we propose an analytical framework which combines Lagrangian modeling, network theory, otolith analyses and biogeographical information to pinpoint and characterize larval sources which are then grouped into discrete spawning areas. Such well-delineated sources and their predetermined settlement sites allow improving the quantitative evaluations of both dispersal scales and connectivity patterns. To illustrate its added value, our approach is applied to two case-studies focusing on D. sargus and D. vulgaris in the Adriatic sea. We evidence robust correlations between otolith geochemistry and modelled spawning areas to assess their relative importance for the larval replenishment of the Apulian coast. Our results show that, contrary to D. sargus, D. vulgaris larvae originate from both eastern and western Adriatic shorelines. Our findings also suggest that dispersal distances and dispersal surfaces scale differently with the pelagic larval duration. Furthermore, almost 30% of D. sargus larvae and 10% of D. vulgaris larvae of the Apulian populations come from Tremiti marine protected area (MPA), exemplifying larval spill-over from MPAs to surrounding unprotected areas. This flexible multidisciplinary framework, which can be adjusted to other coastal fish and oceanic system, exploits the explanatory power of a model tuned and backed-up by observations to provide more reliable scientific basis for the management and conservation of marine ecosystems.
Connectivity is a fundamental structural feature of a network that determines the outcome of any dynamics that happens on top of it. However, an analytical approach to obtain connection probabilities between nodes associated to paths of different lengths is still missing. Here, we derive exact expressions for random-walk connectivity probabilities across any range of numbers of steps in a generic temporal, directed and weighted network. This allows characterizing explicit connectivity realized by causal paths as well as implicit connectivity related to motifs of three nodes and two links called here pitchforks. We directly link such probabilities to the processes of tagging and sampling any quantity exchanged across the network, hence providing a natural framework to assess transport dynamics. Finally, we apply our theoretical framework to study ocean transport features in the Mediterranean Sea. We find that relevant transport structures, such as fluid barriers and corridors, can generate contrasting and counter-intuitive connectivity patterns bringing novel insights into how ocean currents drive seascape connectivity.
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