Hidden similarities in the dynamics of a weakly synchronous marine metapopulation

Populations of many marine species are only weakly synchronous, despite coupling through larval dispersal and exposure to synchronous environmental drivers. Although this is often attributed to observation noise, factors including local environmental differences, spatially variable dynamics, and chaos might also reduce or eliminate metapopulation synchrony. To differentiate spatially variable dynamics from similar dynamics driven by spatially variable environments, we applied hierarchical delay embedding. A unique output of this approach, the “dynamic correlation,” quantifies similarity in intrinsic dynamics of populations, independently of whether their abundance is correlated through time. We applied these methods to 17 populations of blue crab (Callinectes sapidus) along the US Atlantic coast and found that their intrinsic dynamics were broadly similar despite largely independent fluctuations in abundance. The weight of evidence suggests that the latitudinal gradient in temperature, filtered through a unimodal response curve, is sufficient to decouple crab populations. As unimodal thermal performance is ubiquitous in ectotherms, we suggest that this may be a general explanation for the weak synchrony observed at large distances in many marine species, although additional studies are needed to test this hypothesis.

Discrete stochastic marine metapopulation disease model

Some marine microparasitic pathogens can survive several months in the water column to make contact with or to be absorbed or filtered by hosts. Once inside, pathogens invade the host if they find suitable conditions for reproduction. This transmission from the environment occurs via pathogens released from infected and dead infected animals. Some recent modeling studies concentrated on the disease dynamic imposed by this complex interaction between population and water column at the host-pathogen level in single populations. However, only when a marine disease can be understood at the metapopulation scale effective approaches to management will become routinely achievable. The discrete-time disease model in this paper investigates both spatial and temporal dynamics of hosts and waterborne pathogens in a metapopulation system of three patches. This system with a patch providing infective particles and susceptible and infected individuals by dispersal tries to imitate the effect of current forces in the ocean on the passive dispersal of organisms. The model detects behaviours that are not present in single population continuous-time and deterministic models.

Discrete stochastic marine metapopulation disease model

Some marine microparasitic pathogens can survive several months in the water column to make contact with or to be absorbed or filtered by hosts. Once inside, pathogens invade the host if they find suitable conditions for reproduction. This transmission from the environment occurs via pathogens released from infected and dead infected animals. Some recent modeling studies concentrated on the disease dynamic imposed by this complex interaction between population and water column at the host-pathogen level in single populations. However, only when a marine disease can be understood at the metapopulation scale effective approaches to management will become routinely achievable. The discrete-time disease model in this paper investigates both spatial and temporal dynamics of hosts and waterborne pathogens in a metapopulation system of three patches. This system with a patch providing infective particles and susceptible and infected individuals by dispersal tries to imitate the effect of current forces in the ocean on the passive dispersal of organisms. The model detects behaviours that are not present in single population continuous-time and deterministic models.

Dispersal and population connectivity are phenotype dependent in a marine metapopulation

Larval dispersal is a key process determining population connectivity, metapopulation dynamics, and community structure in benthic marine ecosystems, yet the biophysical complexity of dispersal is not well understood. In this study, we investigate the interaction between disperser phenotype and hydrodynamics on larval dispersal pathways, using a temperate reef fish species, Trachinops caudimaculatus . We assessed the influence of larval traits on depth distribution and dispersal outcomes by: (i) using 24-h depth-stratified ichthyoplankton sampling, (ii) quantifying individual phenotypes using larval growth histories extracted from the sagittal otoliths of individual larvae, and (iii) simulating potential dispersal outcomes based on the empirical distribution of larval phenotypes and an advanced biological-physical ocean model. We found T. caudimaculatus larvae were vertically stratified with respect to phenotype, with high-quality phenotypes found in the bottom two depth strata, and poor-quality phenotypes found primarily at the surface. Our model showed high- and average-quality larvae experienced significantly higher local retention (more than double) and self-recruitment, and travelled shorter distances relative to poor-quality larvae. As populations are only connected when dispersers survive long enough to reproduce, determining how larval phenotype influences dispersal outcomes will be important for improving our understanding of marine population connectivity and persistence.

Discrete stochastic marine metapopulation disease model

Some marine microparasitic pathogens can survive several months outside the host in the water column to make contact with hosts or to be absorbed or filtered by hosts. Once inside, pathogens invade the host if they find suitable conditions for reproduction within the host. This transmission from the environment occurs via pathogens released from infected animals and dead infected animals. Some recent modeling studies concentrated on the disease dynamic imposed by this complex interaction between population and water column at the host-pathogen level in single populations. However, only when a marine disease can be understood at the metapopulation scale effective approaches to management will become routinely achievable. In this paper we explore the disease dynamics at the metapopulation applying a stochastic version. The discrete-time disease model in this paper investigates both spatial and temporal dynamics of hosts and waterborne pathogens in a three patch system. This metapopulation with a patch providing infective particles and susceptible and infected individuals by dispersal tries to imitate the effect of current forces in the ocean on the passive dispersal of organisms. The model detects system behaviors that are not present in single population continuous-time and deterministic models.

Insights from genetic and demographic connectivity for the management of rays and skates

Studying demographic and genetic connectivity can help assess marine metapopulation structure. Rays and skates have no larval phase; hence, population connectivity can only result from active movement of individuals. Using thornback ray (Raja clavata) in European waters as a case study, demographic and genetic connectivity were studied for 11 putative populations with unequal population abundances and two hypotheses of dispersal rates. Genetic simulation results highlighted three large metapopulations: in the Mediterranean, around the Azores, and on the Northeast Atlantic shelf. Demographic results highlighted a finer population structure indicating that several pairs of putative populations might be demographically linked. Results were highly sensitive to dispersal assumptions and relative population abundances, which provided insights into the potential magnitude of genetic and demographic connectivity differences. Accounting for demographic connectivity appears to be crucial for managing and conserving rays and skates, while genetic connectivity provides a longer-term perspective and less subtle spatial structures. Moreover, accounting for heterogeneity in population abundances is a key factor for determining or interpreting metapopulation connectivity.

Discrete stochastic marine metapopulation disease model

Some marine microparasitic pathogens can survive several months outside the host in the water column to make contact with hosts or to be absorbed or filtered by hosts. Once inside, pathogens invade the host if they find suitable conditions for reproduction within the host. This transmission from the environment occurs via pathogens released from infected animals and dead infected animals. Some recent modeling studies concentrated on the disease dynamic imposed by this complex interaction between population and water column at the host-pathogen level in single populations. However, only when a marine disease can be understood at the metapopulation scale effective approaches to management will become routinely achievable. In this paper we explore the disease dynamics at the metapopulation applying a stochastic version. The discrete-time disease model in this paper investigates both spatial and temporal dynamics of hosts and waterborne pathogens in a three patch system. This metapopulation with a patch providing infective particles and susceptible and infected individuals by dispersal tries to imitate the effect of current forces in the ocean on the passive dispersal of organisms. The model detects system behaviors that are not present in single population continuous-time and deterministic models.