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Modelling population dynamics in presence of hybridization

Abstract : Hybridization is the interbreeding of individuals from distinct populations. Anthropogenic hybridization is a significant threat that can cause species’ extinction. It is therefore fundamental to assess this threat and evaluate the effectiveness of management actions in an adaptive management loop. We developed demographic estimation and projection models to answer to these questions and showed their application.In the first chapter we: 1) developed a model to estimate prevalence in free‐ranging populations 2) carried out a simulation study to i) evaluate model performance, ii) compare it to naive quantifications of prevalence and iii) assess the accuracy of model-based estimates of prevalence under different sampling scenarios. The main results from this chapter were that i) the prevalence of hybrids could be estimated ii) model‐based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. Our results underline the importance of a model‐based approach to obtain unbiased estimates of prevalence of different population segments.In the second chapter we adopted targeted non-invasive genetic sampling and the capture-recapture estimation model developed in Chapter 1 to estimate the prevalence of wolf-dog hybrids in a local, protected wolf population in the northern Apennines, Italy. We discuss the results in the light of previous assessment of prevalence of wolf x dog admixed individuals in Western Europe and we illustrate the implications of the results for wolf conservation and for the management of wolf x dog hybridization in human-dominated landscapes. In particular, we estimated 64-78% recent hybrids occurring in 6 out of the 7 surveyed packs. Our findings underline that in human-modified landscapes wolf-dog hybridization may raise to unexpected levels if left unmanaged, and that reproductive barriers or dilution of dog genes through backcrossing should not be expected, per se, to prevent occurrence and the spread of introgression.In the third chapter we present a new matrix population model to project population dynamics of animal populations in presence of hybridization. We apply the model to two real-world case studies of terrestrial (wolf x dog) and marine mammal species (common dolphin Delphinus delphis x striped dolphin Stenella coeruleoalba). Our projections highlighted that i) hybridization leads to genomic extinction in the absence of reproductive isolation, ii) rare or depleted species are particularly vulnerable to genomic extinction, iii) genomic extinction depends mainly on demographic parameters of parental species, iiii) maintaining healthy and abundant populations prevents genomic extinction.In the fourth chapter we built an individual based model describing the life cycle of the gray wolf by contemplating social dynamics traits linked to hybridization rates. We applied this model to investigate the hybridization dynamics of wolves in a study population the Northern Apennines, Italy, in order to evaluate the effectiveness of different management scenarios aimed to reduce the abundance of admixed individuals during a ten-generation time. We showed that in presence of continuative immigration of admixed individuals any management action proved ineffective. In presence of immigration by pure wolves all management actions produced a decrease in prevalence, although their relative effectiveness changed depending on the mating choice scenario. In all the simulated scenarios, the impact of hybridization is predicted to extend at broad scales as large numbers of admixed dispersers are produced. Moreover, we identified demographic and social processes that need to be further investigated to more accurately project the outcomes of management alternatives.
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Submitted on : Wednesday, February 17, 2021 - 11:53:23 AM
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Nina Santostasi. Modelling population dynamics in presence of hybridization. Agricultural sciences. Université Montpellier; Università degli studi La Sapienza (Rome), 2020. English. ⟨NNT : 2020MONTG017⟩. ⟨tel-03144074⟩

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