Evolution of density–and patch–size–dependent dispersal rates

Poethke, Hans Joachim; Hovestadt, Thomas

doi:10.1098/rspb.2001.1936

Cited by 211 publications

(265 citation statements)

References 76 publications

(118 reference statements)

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“…In this case, dispersing individuals profit not only from the chance to reach an empty habitat but also from the elevated chance to reach a patch with lower population density than their current patch. Thus, a positive correlation between ES dispersal rate and variance in population size is generally predicted (Poethke and Hovestadt 2002). In our simulations, variance in population size is also positively correlated with local extinction, either because externally caused catastrophes create such variance (environmental catastrophe scenario) or because this variance leads to random extinction events (fluctuating environment scenario).…”

Section: Discussionmentioning

confidence: 71%

“…The values for these alleles may change by mutation, thus allowing for the evolution of density-and patch-size-dependent dispersal strategies. To promote greater variability of genotypes in the first generations and to reduce the influence of mutations on the stability of the final result, we let mutation rates exponentially decrease from ∼0.1 to !0.001 over the course of the simulation experiments (10,000 generations; for details, see Poethke and Hovestadt 2002). For a broad range of parameters, we compared the results of this procedure with results generated by simulations with small constant mutation rates.…”

Section: The Modelmentioning

confidence: 99%

“…Offspring develop into mature individuals with a density-dependent survival probability s: After all individuals have reached maturity, they disperse in proportion to their individual dispersal probability d. We assume global dispersal; that is, a successful disperser reaches any patch in the landscape (except its home patch) with the same probability ( ). In our sim-1/[n patch Ϫ 1] ulations, dispersal probability is sensitive to local patch size and density according to the nonlinear model of Poethke and Hovestadt (2002): The individual values for p C and p K are determined by the mean value of the two corresponding alleles. At initiation, values for the alleles coding for p C and p K are set to 1 and 0, respectively.…”

Section: The Modelmentioning

confidence: 99%

“…cessional status (Ronce and Olivieri 1997), differences in patch capacity (McPeek and Holt 1992;Poethke and Hovestadt 2002), differences in population density (Ruxton 1996;Jánosi and Scheuring 1997;Saether et al 1999;Metz and Gyllenberg 2001;Poethke and Hovestadt 2002), and the occurrence of autocorrelated habitat distribution (Hovestadt et al 2001) are also factors promoting the evolution of dispersal.…”

mentioning

confidence: 99%

“…Our analysis builds on an individual-based model simulating the evolution of dispersal strategies in metapopulations, as presented in Poethke and Hovestadt (2002). In a number of simulation experiments, we will manipulate local extinction rates by alteration of the frequency of environmental catastrophes, the intensity of environmentally induced fluctuations in fertility, and dispersal mortality.…”

mentioning

confidence: 99%

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Local Extinction and the Evolution of Dispersal Rates: Causes and Correlations

Poethke

Hovestadt

Mitesser

2003

The American Naturalist

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105

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We present the results of individual-based simulation experiments on the evolution of dispersal rates of organisms living in metapopulations. We find conflicting results regarding the relationship between local extinction rate and evolutionarily stable (ES) dispersal rate depending on which principal mechanism causes extinction: if extinction is caused by environmental catastrophes eradicating local populations, we observe a positive correlation between extinction and ES dispersal rate; if extinction is a consequence of stochastic local dynamics and environmental fluctuations, the correlation becomes ambiguous; and in cases where extinction is caused by dispersal mortality, a negative correlation between local extinction rate and ES dispersal rate emerges. We conclude that extinction rate, which both affects and is affected by dispersal rates, is not an ideal predictor for optimal dispersal rates.

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Section: Discussionmentioning

confidence: 71%

Section: The Modelmentioning

confidence: 99%

Section: The Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Local Extinction and the Evolution of Dispersal Rates: Causes and Correlations

Poethke

Hovestadt

Mitesser

2003

The American Naturalist

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105

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Dispersal evolution in temporally variable environments: implications for plant range dynamics

Oldfather

Elzen

Heffernan

et al. 2021

American J of Botany

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Dispersal—the movement of an individual from the site of birth to a different site for reproduction—is an ecological and evolutionary driver of species ranges that shapes patterns of colonization, connectivity, gene flow, and adaptation. In plants, the traits that influence dispersal often vary within and among species, are heritable, and evolve in response to the fitness consequences of moving through heterogeneous landscapes. Spatial and temporal variation in the quality and quantity of habitat are important sources of selection on dispersal strategies across species ranges. While recent reviews have evaluated the interactions between spatial variation in habitat and dispersal dynamics, the extent to which geographic variation in temporal variability can also shape range‐wide patterns in dispersal traits has not been synthesized. In this paper, we summarize key predictions from metapopulation models that evaluate how dispersal evolves in response to spatial and temporal habitat variability. Next, we compile empirical data that quantify temporal variability in plant demography and patterns of dispersal trait variation across species ranges to evaluate the hypothesis that higher temporal variability favors increased dispersal at plant range limits. We found some suggestive evidence supporting this hypothesis while more generally identifying a major gap in empirical work evaluating plant metapopulation dynamics across species ranges and geographic variation in dispersal traits. To address this gap, we propose several future research directions that would advance our understanding of the interplay between spatiotemporal variability and dispersal trait variation in shaping the dynamics of current and future species ranges.

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Matrix quality and disturbance frequency drive evolution of species behavior at habitat boundaries

Martin

Fahrig

2015

Ecology and Evolution

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SummaryPrevious theoretical studies suggest that a species' landscape should influence the evolution of its dispersal characteristics, because landscape structure affects the costs and benefits of dispersal. However, these studies have not considered the evolution of boundary crossing, that is, the tendency of animals to cross from habitat to nonhabitat (“matrix”). It is important to understand this dispersal behavior, because of its effects on the probability of population persistence. Boundary‐crossing behavior drives the rate of interaction with matrix, and thus, it influences the rate of movement among populations and the risk of dispersal mortality. We used an individual‐based, spatially explicit model to simulate the evolution of boundary crossing in response to landscape structure. Our simulations predict higher evolved probabilities of boundary crossing in landscapes with more habitat, less fragmented habitat, higher‐quality matrix, and more frequent disturbances (i.e., fewer generations between local population extinction events). Unexpectedly, our simulations also suggest that matrix quality and disturbance frequency have much stronger effects on the evolution of boundary crossing than either habitat amount or habitat fragmentation. Our results suggest that boundary‐crossing responses are most affected by the costs of dispersal through matrix and the benefits of escaping local extinction events. Evolution of optimal behavior at habitat boundaries in response to the landscape may have implications for species in human‐altered landscapes, because this behavior may become suboptimal if the landscape changes faster than the species' evolutionary response to that change. Understanding how matrix quality and habitat disturbance drive evolution of behavior at boundaries, and how this in turn influences the extinction risk of species in human‐altered landscapes should help us identify species of conservation concern and target them for management.

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Evolution of density–and patch–size–dependent dispersal rates

Cited by 211 publications

References 76 publications

Local Extinction and the Evolution of Dispersal Rates: Causes and Correlations

Local Extinction and the Evolution of Dispersal Rates: Causes and Correlations

Dispersal evolution in temporally variable environments: implications for plant range dynamics

Matrix quality and disturbance frequency drive evolution of species behavior at habitat boundaries

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