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

Poethke, Hans Joachim; Hovestadt, Thomas; Mitesser, Oliver

doi:10.1086/368224

Cited by 106 publications

(92 citation statements)

References 39 publications

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“…However, it remains a challenge to identify the mechanisms by which stable home ranges can emerge from unbounded movement paths, with a number of alternative modelling approaches in use [207]. In many of the existing IBMs of movement processes across complex landscapes the key questions being addressed have related to connectivity [208][209][210], emergent dispersal mortality [211,212], and home range formation [206,213,214], but in many cases these individual-based movement models have not been linked to models of population dynamics. When such links are made, it is possible to gain important new insights into the dynamics of species living on complex landscapes and into potential consequences of alternative management interventions [215].…”

Section: Process-based Modelsmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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Landscape ecological modelling provides a vital means for understanding the interactions between geographical, climatic, and socio-economic drivers of land-use and the dynamics of ecological systems. This growing field is playing an increasing role in informing landscape spatial planning and management. Here, we review the key modelling approaches that are used in landscape modelling and in ecological modelling. We identify an emerging theme of increasingly detailed representation of process in both landscape and ecological modelling, with complementary suites of modelling approaches ranging from correlative, through aggregated process based approaches to models with much greater structural realism that often represent behaviours at the level of agents or individuals. We provide examples of the considerable progress that has been made at the intersection of landscape modelling and ecological modelling, while also highlighting that the majority of this work has to date exploited a relatively small number of the possible combinations of model types from each discipline. We use this review to identify key gaps in existing landscape ecological modelling effort and highlight emerging opportunities, in particular for future work to progress in novel directions by combining classes of landscape models and ecological models that have rarely been used together.

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Section: Process-based Modelsmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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“…Simulation is terminated at the 30,000 th generation, since genetic parameters, p C, j and p K, j , are stable after 20,000 or more generations. It is difficult to interpret the absolute values of p C, j and p K, j , since individual d-values are determined by the interaction of both values with a local population density or sex ratio and relative carrying capacity, which fluctuate temporally (Poethke et al, 2003); therefore, mean d-values at 30,000th generation were used for statistical analysis. The simulation was replicated 10 times for each condition.…”

Section: Modelsmentioning

confidence: 99%

The evolution of sexual difference in dispersal strategy sensitive to population density

Hirota

2007

Appl. Entomol. Zool.

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Empirical studies reveal that dispersal behavior is dependent on local population density in different wild animals. Theoretical studies also pay much attention to modeling dispersal strategies sensitive to population density; however, the evolution of sex-biased dispersal has not been analyzed sufficiently by a model considering density-dependent dispersal. Therefore, a previous model where it is assumed that only genetic factors determine an individual's dispersal timing was thoroughly modified. The resultant model assumes that dispersal timing is determined by the interaction of genetic factors with local population density and local habitat size. This model demonstrates that when females copulate before dispersal, they evolve to emigrate from their natal habitat earlier than males. A model where dispersal timing is dependent on the local sex ratio instead of population density was also analyzed. This model also results in the evolution of female early dispersal, but the resultant dispersal timing of both sexes is slightly different from the model sensitive to population density. This difference is related to sexual difference in factors affecting reproductive success. Local population density is associated with the intensity of resource competition among females, whereas local sex ratio is informative for mate competition among males.

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“…On the one hand, these studies have shown that the evolution of high dispersal rates may be favoured by several mechanisms such as environmental fluctuations (e.g. to cope with temporal variability of resource availability [18][19][20]), local extinction probability [20] as well as individual and kin competition [9,17,[21][22][23]. On the other hand, the fitness benefits of dispersing can be reduced by the associated risks such as dispersal costs and mortality [24], thereby promoting the evolution of lower dispersal rates [15,25].…”

Section: Introductionmentioning

confidence: 99%

On the evolution of dispersal via heterogeneity in spatial connectivity

et al. 2015

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Dispersal has long been recognized as a mechanism that shapes many observed ecological and evolutionary processes. Thus, understanding the factors that promote its evolution remains a major goal in evolutionary ecology. Landscape connectivity may mediate the trade-off between the forces in favour of dispersal propensity (e.g. kin-competition, local extinction probability) and those against it (e.g. energetic or survival costs of dispersal). It remains, however, an open question how differing degrees of landscape connectivity may select for different dispersal strategies. We implemented an individual-based model to study the evolution of dispersal on landscapes that differed in the variance of connectivity across patches ranging from networks with all patches equally connected to highly heterogeneous networks. The parthenogenetic individuals dispersed based on a flexible logistic function of local abundance. Our results suggest, all else being equal, that landscapes differing in their connectivity patterns will select for different dispersal strategies and that these strategies confer a long-term fitness advantage to individuals at the regional scale. The strength of the selection will, however, vary across network types, being stronger on heterogeneous landscapes compared with the ones where all patches have equal connectivity. Our findings highlight how landscape connectivity can determine the evolution of dispersal strategies, which in turn affects how we think about important ecological dynamics such as metapopulation persistence and range expansion.

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

Cited by 106 publications

References 39 publications

Emerging Opportunities for Landscape Ecological Modelling

Emerging Opportunities for Landscape Ecological Modelling

The evolution of sexual difference in dispersal strategy sensitive to population density

On the evolution of dispersal via heterogeneity in spatial connectivity

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