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Ecological theory predicts that demographic connectivity structures the dynamics of local populations within metapopulation systems, but empirical support has been constrained by major limitations in data and methodology. We tested this prediction for giant kelp Macrocystis pyrifera, a key habitat-forming species in temperate coastal ecosystems worldwide, in southern California, USA. We combined a long-term (22 years), large-scale (~500 km coastline), high-resolution census of abundance with novel patch delineation methods and an innovative connectivity measure incorporating oceanographic transport and source fecundity. Connectivity strongly predicted local dynamics (well-connected patches had lower probabilities of extinction and higher probabilities of colonization, leading to greater likelihoods of occupancy) but this relationship was mediated by patch size. Moreover, the relationship between connectivity and local population dynamics varied over time, possibly due to temporal variation in oceanographic transport processes. Surprisingly, connectivity had a smaller influence on colonization relative to extinction, possibly because local ecological factors differ greatly between extinct and extant patches. Our results provide the first comprehensive evidence that southern California giant kelp populations function as a metapopulation system, challenging the view that populations of this important foundation species are governed exclusively by self-replenishment.

At small spatial and temporal scales, genetic differentiation is largely controlled by constraints on gene flow, while genetic diversity across a species' distribution is shaped on longer temporal and spatial scales. We assess the hypothesis that oceanographic transport and other seascape features explain different scales of genetic structure of giant kelp, Macrocystis pyrifera. We followed a hierarchical approach to perform a microsatellite-based analysis of genetic differentiation in Macrocystis across its distribution in the northeast Pacific. We used seascape genetic approaches to identify large-scale biogeographic population clusters and investigate whether they could be explained by oceanographic transport and other environmental drivers. We then modelled population genetic differentiation within clusters as a function of oceanographic transport and other environmental factors. Five geographic clusters were identified: Alaska/Canada, central California, continental Santa Barbara, California Channel Islands and mainland southern California/Baja California peninsula. The strongest break occurred between central and southern California, with mainland Santa Barbara sites forming a transition zone between the two. Breaks between clusters corresponded approximately to previously identified biogeographic breaks, but were not solely explained by oceanographic transport. An isolation-by-environment (IBE) pattern was observed where the northern and southern Channel Islands clustered together, but not with closer mainland sites, despite the greater distance between them. The strongest environmental association with this IBE pattern was observed with light extinction coefficient, which extends suitable habitat to deeper areas. Within clusters, we found support for previous results showing that oceanographic connectivity plays an important role in the population genetic structure of Macrocystis in the Northern hemisphere., (© 2015 John Wiley & Sons Ltd.)

The manner in which patches are delineated in spatially realistic metapopulation models will influence the size, connectivity, and extinction and recolonization dynamics of those patches. Most commonly used patch-definition methods focus on identifying discrete, contiguous patches of habitat from a single temporal observation of species occurrence or from a model of habitat suitability. However, these approaches are not suitable for many metapopulation systems where entire patches may not be fully colonized at a given time. For these metapopulation systems, a single large patch of habitat may actually support multiple, interacting subpopulations. The interactions among these subpopulations will be ignored if the patch is treated as a single unit, a situation we term the "mega-patch problem." Mega-patches are characterized by variable intra-patch synchrony, artificially low inter-patch connectivity, and low extinction rates. One way to detect this problem is by using time series data to calculate demographic synchrony within mega-patches. We present a framework for identifying subpopulations in mega-patches using a combination of spatial autocorrelation and graph theory analyses. We apply our approach to southern California giant kelp (Macrocystis pyrifera) forests using a new, long-term (27 years), satellite-based data set of giant kelp canopy biomass. We define metapopulation patches using our method as well as several other commonly used patch delineation methodologies and examine the colonization and extinction dynamics of the metapopulation under each approach. We find that the relationships between patch characteristics such as area and connectivity and the demographic processes of colonizations and extinctions vary among the different patch-definition methods. Our spatial-analysis/graph-theoretic framework produces results that match theoretical expectations better than the other methods. This approach can be used to identify subpopulations in metapopulations where the distributions of organisms do not always reflect the distribution of suitable habitat.

Patterns of spatial genetic structure (SGS), typically estimated by genotyping adults, integrate migration over multiple generations and measure the effective gene flow of populations. SGS results can be compared with direct ecological studies of dispersal or mating system to gain additional insights. When mismatches occur, simulations can be used to illuminate the causes of these mismatches. Here, we report a SGS and simulation-based study of self-fertilization in Macrocystis pyrifera, the giant kelp. We found that SGS is weaker than expected in M. pyrifera and used computer simulations to identify selfing and early mortality rates for which the individual heterozygosity distribution fits that of the observed data. Only one (of three) population showed both elevated kinship in the smallest distance class and a significant negative slope between kinship and geographical distance. All simulations had poor fit to the observed data unless mortality due to inbreeding depression was imposed. This mortality could only be imposed for selfing, as these were the only simulations to show an excess of homozygous individuals relative to the observed data. Thus, the expected data consistently achieved nonsignificant differences from the observed data only under models of selfing with mortality, with best fits between 32% and 42% selfing. Inbreeding depression ranged from 0.70 to 0.73. The results suggest that density-dependent mortality of early life stages is a significant force in structuring Macrocystis populations, with few highly homozygous individuals surviving. The success of these results should help to validate simulation approaches even in data-poor systems, as a means to estimate otherwise difficult-to-measure life cycle parameters., (© 2013 John Wiley & Sons Ltd.)

Ocean currents are expected to be the predominant environmental factor influencing the dispersal of planktonic larvae or spores; yet, their characterization as predictors of marine connectivity has been hindered by a lack of understanding of how best to use oceanographic data. We used a high-resolution oceanographic model output and Lagrangian particle simulations to derive oceanographic distances (hereafter called transport times) between sites studied for Macrocystis pyrifera genetic differentiation. We build upon the classical isolation-by-distance regression model by asking how much additional variability in genetic differentiation is explained when adding transport time as predictor. We explored the extent to which gene flow is dependent upon seasonal changes in ocean circulation. Because oceanographic transport between two sites is inherently asymmetric, we also compare the explanatory power of models using the minimum or the mean transport times. Finally, we compare the direction of connectivity as estimated by the oceanographic model and genetic assignment tests. We show that the minimum transport time had higher explanatory power than the mean transport time, revealing the importance of considering asymmetry in ocean currents when modelling gene flow. Genetic assignment tests were much less effective in determining asymmetry in gene flow. Summer-derived transport times, in particular for the month of June, which had the strongest current speed, greatest asymmetry and highest spore production, resulted in the best-fit model explaining twice the variability in genetic differentiation relative to models that use geographic distance or habitat continuity. The best overall model also included habitat continuity and explained 65% of the variation in genetic differentiation among sites., (© 2011 Blackwell Publishing Ltd.)

Isolation by distance (IBD) models are widely used to predict levels of genetic connectivity as a function of Euclidean distance, and although recent studies have used GIS-landscape ecological approaches to improve the predictability of spatial genetic structure, few if any have addressed the effect of habitat continuity on gene flow. Landscape effects on genetic connectivity are even less understood in marine populations, where habitat mapping is particularly challenging. In this study, we model spatial genetic structure of a habitat-structuring species, the giant kelp Macrocystis pyrifera, using highly variable microsatellite markers. GIS mapping was used to characterize habitat continuity and distance between sampling sites along the mainland coast of the Santa Barbara Channel, and their roles as predictors of genetic differentiation were evaluated. Mean dispersal distance (sigma) and effective population size (Ne) were estimated by comparing our IBD slope with those from simulations incorporating habitat continuity and spore dispersal characteristics of the study area. We found an allelic richness of 7-50 alleles/locus, which to our knowledge is the highest reported for macroalgae. The best regression model relating genetic distance to habitat variables included both geographic distance and habitat continuity, which were respectively, positively and negatively related to genetic distance. Our results provide strong support for a dependence of gene flow on both distance and habitat continuity and elucidate the combination of Ne and a that explained genetic differentiation.