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23 results for “dispersal kernels”
Connectivity from a different perspective: comparing seed dispersal kernels in connected vs. unfragmented landscapes.
Habitat fragmentation can create significant impediments to dispersal. A technique to increase dispersal between otherwise isolated fragments is the use of corridors. Although previous studies have compared dispersal between connected fragments to dispersal between unconnected fragments, it remains unknown how dispersal between fragments connected by a corridor compares to dispersal in unfragmented landscapes. To assess the extent to which corridors can restore dispersal in fragmented landscapes to levels observed in unfragmented landscapes, we employed a stable-isotope marking technique to track seeds within four unfragmented landscapes and eight experimental landscapes with fragments connected by corridors. We studied two wind- and two bird-dispersed plant species, because previous community-based research showed that dispersal mode explains how connectivity effects vary among species. We constructed dispersal kernels for these species in unfragmented landscapes and connected fragments by marking seeds in the center of each landscape with 15N and then recovering marked seeds in seed traps at distances up to 200 m. For the two wind-dispersed plants, seed dispersal kernels were similar in unfragmented landscapes and connected fragments. In contrast, dispersal kernels of bird-dispersed seeds were both affected by fragmentation and differed in the direction of the impact: Morella cerifera experienced more and Rhus copallina experienced less long-distance dispersal in unfragmented than in connected landscapes. These results show that corridors can facilitate dispersal probabilities comparable to those observed in unfragmented landscapes. Although dispersal mode may provide useful broad predictions, we acknowledge that similar species may respond uniquely due to factors such as seasonality and disperser behavior. Our results further indicate that prior work has likely underestimated dispersal distances of wind-dispersed plants and that factors altering long-distance dis
Individual variation in marine larval-fish swimming speed and the emergence of dispersal kernels
<p>Dispersal emerges as a consequence of how an individual's phenotype interacts with the environment. Not all dispersing individuals have the same phenotype, and variation among individuals can generate complex variation in the distribution of dispersal distances and directions. While active locomotion performance is an obvious candidate for a dispersal phenotype, its effects on dispersal are difficult to measure or predict, especially in small organisms dispersing in wind or currents. Therefore, we analyzed the effects of larval swimming on dispersal and settlement of coral-reef fish larvae using a high-resolution biophysical model. The model is, to date, the only biophysical model of marine larval dispersal that has been statistically validated against genetic parentage estimates of larval origin and destination, and incorporates empirically-estimated larval behaviors and their ontogeny. Larval swimming, in combination with depth, orientation, and navigation behaviors, actually reduced dispersal distances compared to those of passive larvae. Swimming had no consistent effects on long distance dispersal, but increased the spread of settlement locations. Swimming speed, in contrast, did not consistently affect median dispersal distances, but faster swimming larvae had greater mean and maximum dispersal distances than slower swimming larvae. Finally, faster larval swimming speeds consistently increased the probability of settlement. Our analysis shows how larval swimming differentially affects multiple properties of dispersal kernels. In doing so, it indicates how selection could favor faster larval swimming to increase settlement, which may actually result in longer dispersal distances as a by-product of larvae trying to locate habitat rather than to disperse greater distances.</p>
Larval and adult traits coevolve in response to asymmetric coastal currents to shape marine dispersal kernels
<p>Dispersal emerges as an outcome of organismal traits and external forcings. However, it remains unclear how the emergent dispersal kernel evolves as a by-product of selection on the underlying traits. This question is particularly compelling in coastal marine systems where dispersal is tied to development and reproduction, and where directional currents bias larval dispersal downstream causing selection for retention. We modelled the dynamics of a metapopulation along a finite coastline using an integral projection model and adaptive dynamics to understand how asymmetric coastal currents influence the evolution of larval (pelagic larval duration) and adult (spawning frequency) life history traits, which indirectly shape the evolution of marine dispersal kernels. Selection induced by alongshore currents favors the release of larvae over multiple time periods, allowing long pelagic larval durations and long-distance dispersal to be maintained in marine life cycles in situations where they were previously predicted to be selected against. Two evolutionary stable strategies emerged: one with a long pelagic larval duration and many spawning events resulting in a dispersal kernel with a larger mean and variance, and another with a short pelagic larval duration and few spawning events resulting in a dispersal kernel with a smaller mean and variance. Our theory shows how coastal ocean flows are important agents of selection that can generate multiple, often co-occurring, evolutionary outcomes for marine life history traits that affect dispersal.</p>
Larval and adult traits coevolve in response to asymmetric coastal currents to shape marine dispersal kernels
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Individual variation in marine larval-fish swimming speed and the emergence of dispersal kernels
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Evolution of interspecific variation in marine larval dispersal kernels: The role of larval navigation ability
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Data from: Modelling unbiased dispersal kernels over continuous space by accounting for spatial heterogeneity in marking and observation efforts
1. Although a key demographic trait determining the spatial dynamics of wild populations, dispersal is notoriously difficult to estimate in the field. Indeed, dispersal distances obtained from the monitoring of marked individuals typically lead to biased estimations of dispersal kernels as a consequence of i) restricted spatial scale of the study areas compared to species potential dispersal and ii) heterogeneity in marking and observation efforts and therfore in detection probability across space. 2. Here we propose a novel method to circumvent these issues that does not require data on observation effort per se, to correct for the variability in detection of marked individuals across space. Observed dispersal events were weighted by the distribution of departure points and an eroded spatial window approach was applied so as to deal with border effect. We conducted a set of simulations which indicated that our method was successful in correcting the effect of spatially heterogeneous detectability and produce unbiased dispersal kernels. 3. We applied this method to a real dataset on Montagu's harrier (>5000 chicks tagged), providing ca. 6000 resightings collected in entire France by a network of 1200 volunteers within a citizen-science program. The median dispersal distance observed was 32 km (range: 0.1-627 km). Once corrected for spatial heterogeneity in marking and observation efforts and border effect, the modelled dispersal kernel indicated a median dispersal distance of 78-123 km depending on the spatial scale considered (constrained within French borders or not, respectively). 4. Synthesis and applications: The current rise of citizen-science programs is likely to stretch our estimate of the ecologically-relevant spatial scale at which dispersal takes place for many taxa. Our method is particularly suited for such large scale data that typically suffer from high spatial heterogeneity in marking and observation efforts and offers the possibility to derive unbiased dispersal kernels, a key component for modelling population dynamics and species distribution in a context of environmental change. Currently, our method assumes homogeneity in both habitat and dispersal behaviour across individuals. We discuss however how to relax these hypotheses to further investigate the effect of e.g. local conspecific density or habitat quality on dispersal propensity.
Data from: Exploring the interaction of avian frugivory and plant spatial heterogeneity and its effect on seed dispersal kernels using a simulation model
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Data from: Modelling unbiased dispersal kernels over continuous space by accounting for spatial heterogeneity in marking and observation efforts
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Data from: A synthesis of empirical plant dispersal kernels
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Data from: The pollen dispersal kernel and mating system of an insect-pollinated tropical palm, Oenocarpus bataua
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Data from: The evolution of marine larval dispersal kernels in spatially structured habitats: analytical models, individual-based simulations, and comparisons with empirical estimates
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Data from: Picky hitch-hikers: vector choice leads to directed dispersal and fat-tailed kernels in a passively dispersing mite
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Data from: Locomotion during digestion changes current estimates of seed dispersal kernels by fish
Dispersal of seeds by animals is an important mechanism regulating plant diversity, range expansions and invasions. Many birds, mammals, fish, and reptiles regularly ingest, transport and excrete viable seeds (known as endozoochory). The effectiveness of endozoochory is modelled in dispersal kernels: functions that describe seed shadows in the landscape by combining movement of animals with experimentally obtained seed retention times and survival. Currently, dispersal kernels use experimental data from resting animals, yet only moving animals disperse seeds. Although physical activity is known to affect digestive processes, little is known on how and to what extent this may influence current estimates of endozoochory. Activity may either prolong seed retention in the animal's gut (locomotion-priority mode hypothesis) or may not affect seed excretion rate (digestion-priority mode hypothesis), and may affect seed survival and germination positively or negatively. We tested how activity alters dispersal estimates in fish. We compared the seed dispersal potential of two riparian plant species (Carex acuta and C. riparia) by the common carp (Cyprinus carpio) subjected to three different activity levels: low (basal metabolic rate, BMR), medium (2×BMR), or high activity (3×BMR). Physical activity of the fish did not affect the number of intact retrieved seeds over 15 h of activity, but significantly affected seed retrieval patterns over time for both seed species. More active fish started seed excretion about 1 h later and kept excreting seeds at least 2 h longer. Effects of gut passage on germination could only be tested for C. acuta, where it reduced the percentage of germinating seeds by 22%, independent of the activity level. Seeds ingested by the fish germinated on average 3.5 days later than non-ingested control seeds. Seed retention times did not affect the timing of germination. Our results support the locomotion-priority mode hypothesis, and show that modelling dispersal kernels using parameters from inactive fish may underestimate potential dispersal distances. Because a trade-off between physical activity and digestive physiology is likely common in animals, it should be taken into account in future modelling of endozoochorous seed dispersal kernels.
Data from: Extended dispersal kernels in a changing world: insights from statistics of extremes
Dispersal ecology is a topical discipline that involves understanding and predicting plant community responses to multiple drivers of global change. Propagule movements that entail long-distance dispersal (LDD) events are crucial for plants to reach and colonize suitable sites across fragmented landscapes. Yet, LDD events are extremely rare, and thus, obtaining reliable estimates of the maximum distances that propagules move across and of their frequency has been a long-lasting challenge in plant ecology. Recent advances in dispersal ecology have provided reliable records of dispersal distances, but they remain confined to focal populations, limiting our ability to infer the frequency and actual extent of LDD events across landscapes. In this study, we view LDD events as extreme values of a dispersal function, and we apply statistics of extremes to derive the frequency and extent of LDD events of simulated and empirical data sets. We first briefly explain the rationale behind statistics of extremes, and we then illustrate how dispersal ecology can benefit conceptually and analytically from applying extreme value analyses. We apply the block maxima approach to simulated seed shadows, and we apply the peak over a threshold method to empirical data sets that contain pollen and seed dispersal distances recorded for a population of Prunus mahaleb, an insect-pollinated and vertebrate-dispersed tree species. Diagnostic plots reveal a distance threshold of υ = 80 m for pollen grains and of υ = 170 m for dispersed seeds. Values that exceed the threshold fit a light-tailed distribution function for pollen and fit a fat-tailed Pareto distribution for seed dispersal distances. Both distribution functions estimate a low (but nonzero) conditional probability of reaching distant locations, extending well beyond the borders of our focal population as follows: Pr (X ≥ 1 km) = 9 × 10−5 for pollen grains and Pr (X ≥ 10 km) = 7 × 10−5 for dispersed seeds. Synthesis. Dispersal ecologists can take the most of their dispersal distance records by applying statistics of extremes to infer the probability of occurrence of extremely rare, but crucial, long distance dispersal events that reach locations well beyond focal populations.
Data from: Self-recruitment in a Caribbean reef fish: a method for approximating dispersal kernels accounting for seascape
Characterizing patterns of larval dispersal is essential to understanding the ecological and evolutionary dynamics of marine metapopulations. Recent research has measured local dispersal within populations, but the development of marine dispersal kernels from empirical data remains a challenge. We propose a framework to move beyond point estimates of dispersal towards the approximation of a simple dispersal kernel, based on the hypothesis that the structure of the seascape is a primary predictor of realized dispersal patterns. Using the coral reef fish Elacatinus lori as a study organism, we use genetic parentage analysis to estimate self-recruitment at a small spatial scale (<1 km). Next, we determine which simple kernel explains the observed self-recruitment, given the influx of larvae from reef habitat patches in the seascape at a large spatial scale (up to 35 km). Finally, we complete parentage analyses at six additional sites to test for export from the focal site and compare these observed dispersal data within the metapopulation to the predicted dispersal kernel. We find 4.6% self-recruitment (CI95%: ±3.0%) in the focal population, which is explained by the exponential kernel y = 0.915x (CI95%: y = 0.865x, y = 0.965x), given the seascape. Additional parentage analyses showed low levels of export to nearby sites, and the best-fit line through the observed dispersal proportions also revealed a declining function y = 0.77x. This study lends direct support to the hypothesis that the probability of larval dispersal declines rapidly with distance in Atlantic gobies in continuously distributed habitat, just as it does in the Indo-Pacific damselfishes in patchily distributed habitat.
Data from: Locomotion during digestion changes current estimates of seed dispersal kernels by fish
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Data from: Self-recruitment in a Caribbean reef fish: a method for approximating dispersal kernels accounting for seascape
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Data from: Extended dispersal kernels in a changing world: insights from statistics of extremes
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Data from: High-frequency sampling and piecewise models reshape dispersal kernels of a common reef coral
Models of dispersal potential are required to predict connectivity between populations of sessile organisms. However, to date, such models do not allow for time‐varying rates of acquisition and loss of competence to settle and metamorphose, and permit only a limited range of possible survivorship curves. We collect high‐resolution observations of coral larval survival and metamorphosis, and apply a piecewise modeling approach that incorporates a broad range of temporally‐varying rates of mortality and loss of competence. Our analysis identified marked changes in competence loss and mortality rates, whose timing implicates developmental failure and depletion of energy reserves. Asymmetric demographic rates suggest more intermediate‐range dispersal, less local retention, and less long‐distance dispersal than predicted by previously‐employed non‐piecewise models. Because vital rates are likely temporally asymmetric, at least for non‐feeding broadcast‐spawned larvae, piecewise analysis of demographic rates will likely yield more reliable predictions of dispersal potential.
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