Probability Of Successful Dispersal Research Articles

Critical connectivity thresholds and the role of temperature in parasite metapopulations

Managing the spread of parasite populations is a ubiquitous challenge for managers of natural and farmed systems. A specific current example are “sea lice”, parasitic marine organisms that live on both wild and farmed Salmon sp., posing a persistent challenge to aquaculture operations in high latitude countries. Lice reproduce with pelagic larvae that spread in the water column, meaning that fish farm sites are connected to one another as a result of their relative location and the response of the organism to the environment. Much work has investigated population connectivity for specific systems, using computational models that link the physical and biological processes affecting larval transport. However, although probability and frequency of dispersal events may be calculated, the specific implications for outbreaks on sites is not entirely clear. We therefore used population models to describe the stage-structured dynamics of connected sea lice population networks, with the goal of establishing the critical connection strength (probability of successful dispersal) for occurrence of an outbreak. Our initial investigation deals with the case of “self-infection” of a single isolated population. Vital rates of life-cycle stages respond to temperature, and as a consequence so does critical connectivity. A dispersal success probability of around 0.01 is required for sea lice population development at the optimal temperature, although this is dependent on parameterisation. The analysis is extended to networks of sites interacting via dispersal, and we show how fallow sites can lead to substantial reductions in population growth rates. Our results provide an important, and to date, missing component in assessment of the environmental impact of marine aquaculture sites. They provide a basis upon which site operators and regional planners can appraise specific developments in the context of their surroundings, and may provide a means for future development of adaptive management strategies.

The role of spatial structure in the collapse of regional metapopulations.

Many wildlife populations are either naturally, or as a result of human land use, patchily distributed in space. The degree of fragmentation-specifically the remaining patch sizes and habitat configuration-is an important part of population dynamics. Demographic stochasticity is also likely to play an important role in patchy habitats that host small local populations. We develop a simulation model to evaluate the significance of demographic stochasticity and the role fragmentation plays in the determination of population dynamics and the risk of extinction of populations on habitat patches. Our model is formulated as a Markov-chain stochastic process on a finite, spatially explicit array of patches in which probability of successful dispersal is a function of interpatch distance. Unlike past work, we explicitly model local population dynamics and examine how these scale up to the entire population. As a test case, we apply the model to the American pika (Ochotona princeps) population living on the ore dumps in the ghost mining town of Bodie, California. This population has been studied nearly continuously for over four decades and has been of conservation concern as the southern half of the population declined precipitously beginning in 1989. Our model suggests that both the specific configuration of habitat and landscape heterogeneity are necessary and sufficient predictors of the eventual extinction of the southern constellation of patches. This example has important implications, as it suggests that fragmentation alone can lead to regional extinctions within metapopulations.

Patterns, causes, and consequences of marine larval dispersal

Quantifying the probability of larval exchange among marine populations is key to predicting local population dynamics and optimizing networks of marine protected areas. The pattern of connectivity among populations can be described by the measurement of a dispersal kernel. However, a statistically robust, empirical dispersal kernel has been lacking for any marine species. Here, we use genetic parentage analysis to quantify a dispersal kernel for the reef fish Elacatinus lori, demonstrating that dispersal declines exponentially with distance. The spatial scale of dispersal is an order of magnitude less than previous estimates-the median dispersal distance is just 1.7 km and no dispersal events exceed 16.4 km despite intensive sampling out to 30 km from source. Overlaid on this strong pattern is subtle spatial variation, but neither pelagic larval duration nor direction is associated with the probability of successful dispersal. Given the strong relationship between distance and dispersal, we show that distance-driven logistic models have strong power to predict dispersal probabilities. Moreover, connectivity matrices generated from these models are congruent with empirical estimates of spatial genetic structure, suggesting that the pattern of dispersal we uncovered reflects long-term patterns of gene flow. These results challenge assumptions regarding the spatial scale and presumed predictors of marine population connectivity. We conclude that if marine reserve networks aim to connect whole communities of fishes and conserve biodiversity broadly, then reserves that are close in space (<10 km) will accommodate those members of the community that are short-distance dispersers.

Modeling directional spatio-temporal processes in island biogeography.

A key challenge in island biogeography is to quantity the role of dispersal in shaping biodiversity patterns among the islands of a given archipelago. Here, we propose such a framework. Dispersal within oceanic archipelagos may be conceptualized as a spatio-temporal process dependent on: (1) the spatial distribution of islands, because the probability of successful dispersal is inversely related to the spatial distance between islands and (2) the chronological sequence of island formation that determines the directional asymmetry of dispersal (hypothesized to be predominantly from older to younger islands). From these premises, directional network models may be constructed, representing putative connections among islands. These models may be translated to eigenfunctions in order to be incorporated into statistical analysis. The framework was tested with 12 datasets from the Hawaii, Azores, and Canaries. The explanatory power of directional network models for explaining species composition patterns, assessed by the Jaccard dissimilarity index, was compared with simpler time-isolation models. The amount of variation explained by the network models ranged from 5.5% (for Coleoptera in Hawaii) to 60.2% (for Pteridophytes in Canary Islands). In relation to the four studied taxa, the variation explained by network models was higher for Pteridophytes in the three archipelagos. By the contrary, small fractions of explained variation were observed for Coleoptera (5.5%) and Araneae (8.6%) in Hawaii. Time-isolation models were, in general, not statistical significant and explained less variation than the equivalent directional network models for all the datasets. Directional network models provide a way for evaluating the spatio-temporal signature of species dispersal. The method allows building scenarios against which hypotheses about dispersal within archipelagos may be tested. The new framework may help to uncover the pathways via which species have colonized the islands of a given archipelago and to understand the origins of insular biodiversity.

Probability of successful larval dispersal declines fivefold over 1 km in a coral reef fish

A central question of marine ecology is, how far do larvae disperse? Coupled biophysical models predict that the probability of successful dispersal declines as a function of distance between populations. Estimates of genetic isolation-by-distance and self-recruitment provide indirect support for this prediction. Here, we conduct the first direct test of this prediction, using data from the well-studied system of clown anemonefish (Amphiprion percula) at Kimbe Island, in Papua New Guinea. Amphiprion percula live in small breeding groups that inhabit sea anemones. These groups can be thought of as populations within a metapopulation. We use the x- and y-coordinates of each anemone to determine the expected distribution of dispersal distances (the distribution of distances between each and every population in the metapopulation). We use parentage analyses to trace recruits back to parents and determine the observed distribution of dispersal distances. Then, we employ a logistic model to (i) compare the observed and expected dispersal distance distributions and (ii) determine the relationship between the probability of successful dispersal and the distance between populations. The observed and expected dispersal distance distributions are significantly different (p < 0.0001). Remarkably, the probability of successful dispersal between populations decreases fivefold over 1 km. This study provides a framework for quantitative investigations of larval dispersal that can be applied to other species. Further, the approach facilitates testing biological and physical hypotheses for the factors influencing larval dispersal in unison, which will advance our understanding of marine population connectivity.

The influence of stage-dependent dispersal on the population dynamics of three amphipod species

In metapopulations, the maintenance of local populations can depend on source-sink dynamics, where populations with positive growth rate seed populations with negative growth rate. The pattern and probability of successful dispersal among habitats can therefore be crucial in determining whether local populations will become rare or increase in abundance. We present here data on the dispersal strategy and population dynamics of three marine amphipods living in pen shells (Atrina rigida) in the Gulf of Mexico. The three amphipod species in this study disperse at different life stages. Neomegamphopus hiatus and Melita nitida disperse as adults, while Bemlos unicornis disperses as juveniles. The two species that disperse as adults have the highest initial population sizes when a new shell becomes available, likely caused by the arriving females releasing their brood into these recently occupied shells. This dispersal pattern results in initially higher population growth, but fewer occupied shells, as noted by their clumped distribution. In contrast, the species that disperses as juveniles accumulates more slowly and more evenly across habitats, eventually dominating the other two in terms of numerical abundance. The metapopulation dynamics of the three species seems to be highly dependent on the life history stage involved in dispersal.

Effects of demographic parameters on metapopulation size and persistence: an analytical stochastic model

An analytical stochastic metapopulation model is developed. It describes how individuals will be distributed among patches as a function of density‐dependent birth, death and emigration rates, and the probability of successful dispersal. The model includes demographic stochasticity, but not catastrophes, environmental stochasticity or variation in patch size and suitability. All patches are equally likely to be colonized by migrants. The model predicts: (a) mean and variance of the number of individuals per patch; (b) probability distribution of individuals per patch; (c) mean number of individuals in transit; and (d) turn‐over rate and expected persistence time of a single patch. The model shows that (a) dispersal rates must be intermediate in order to ensure metapopulation persistence; (b) the mean number of individuals per patch is often well below the carrying capacity; (c) long transit times and/or high mortality during dispersal reduce the mean number of individuals per patch; (d) density‐dependent emigration responses will usually increase metapopulation size and persistence compared with density‐independent dispersal; (e) an increase in the per capita net growth rate can both increase and decrease metapopulation size and persistence depending on whether dispersal rates are high or low; (f) density‐independent birth, death, and emigration rates lead to a spatial pattern described by the negative binomial distribution.

Long-distance dispersal of a subantarctic brooding bivalve (Gaimardia trapesina) by kelp-rafting

The probability of successful dispersal by sessile benthic invertebrates is thought to strongly influence their geographic distribution and population genetics. Generally, species with long-lived planktonic larvae are expected to exhibit wider distribution patterns than those species which brood their young, due to their presumably greater potential for dispersal. In some cases, however, brooding species exhibit broad distributions and show evidence of genetic exchange with geographically distant populations. One potential factor that has been invoked as an expianation is dispersal by floating and rafting of adults and egg masses. Several studies have shown that it is possible for sessile adults to disperse on the order of several to many thousand kilometers by rafting on debris in ocean currents. With very few exceptions, however, direct evidence of rafting in the open ocean has been lacking. We present evidence of long-distance (1300 to 2000 km) dispersal of a brooding pelecypod,Gaimardia trapesina (Lamarck, 1819), in the Southern Ocean in the vicinity of Cape Horn, the Falkland Islands, and the antarctic island South Georgia (54°S; 37°W). Data on survival and fecundity rates ofG. trapesina and the prevalence of kelp rafts collected during the austral winter of 1993 indicate that dispersal by rafting can occur over ecologically relevant time scales and could potentially serve as a significant means of genetic exchange between populations.