Extreme genetic depletion upon postglacial colonization hampers determining the provenance of introduced palmate newt populations

Abstract MtDNA barcoding is regularly applied to determine the provenance of invasive species. Variation in spatial genetic structuring across a species’ range, typically high within glacial refugia and low in postglacially colonized areas, influences the precision of this approach. The palmate newt (Lissotriton helveticus) has been introduced north of its native range inside the Netherlands. We conduct mtDNA barcoding to try and retrace the origin of the introduced localities. A large increase in sample size, particularly focusing on temperate Europe, emphasizes that the palmate newt shows practically no genetic variation outside the Iberian Peninsula glacial refugium. While we find a haplotype previously only known from the Iberian Peninsula inside the native range in Belgium, the haplotype present in the introduced Dutch populations occurs widely throughout the native range north of the Iberian Peninsula. Although mtDNA barcoding can be a powerful tool in invasion biology, the palmate newt case exposes its limitations

A family of process-based models to simulate landscape use by multiple taxa

Context Land-use change is a key driver of biodiversity loss. Models that accurately predict how biodiversity might be affected by land-use changes are urgently needed, to help avoid further negative impacts and inform landscape-scale restoration projects. To be effective, such models must balance model realism with computational tractability and must represent the different habitat and connectivity requirements of multiple species. Objectives We explored the extent to which process-based modelling might fulfil this role, examining feasibility for different taxa and potential for informing real-world decision-making. Methods We developed a family of process-based models (*4pop) that simulate landscape use by birds, bats, reptiles and amphibians, derived from the well-established poll4pop model (designed to simulate bee populations). Given landcover data, the models predict spatially-explicit relative abundance by simulating optimal home-range foraging, reproduction, dispersal of offspring and mortality. The models were co-developed by researchers, conservation NGOs and volunteer surveyors, parameterised using literature data and expert opinion, and validated against observational datasets collected across Great Britain. Results The models were able to simulate habitat specialists, generalists, and species requiring access to multiple habitats for different types of resources (e.g. breeding vs foraging). We identified model refinements required for some taxa and considerations for modelling further species/groups. Conclusions We suggest process-based models that integrate multiple forms of knowledge can assist biodiversity-inclusive decision-making by predicting habitat use throughout the year, expanding the range of species that can be modelled, and enabling decision-makers to better account for landscape context and habitat configuration effects on population persistence.</p

A family of process-based models to simulate landscape use by multiple taxa

Context: Land-use change is a key driver of biodiversity loss. Models that accurately predict how biodiversity might be affected by land-use changes are urgently needed, to help avoid further negative impacts and inform landscape-scale restoration projects. To be effective, such models must balance model realism with computational tractability and must represent the different habitat and connectivity requirements of multiple species. Objectives We explored the extent to which process-based modelling might fulfil this role, examining feasibility for different taxa and potential for informing real-world decision-making. Methods We developed a family of process-based models (*4pop) that simulate landscape use by birds, bats, reptiles and amphibians, derived from the well-established poll4pop model (designed to simulate bee populations). Given landcover data, the models predict spatially-explicit relative abundance by simulating optimal home-range foraging, reproduction, dispersal of offspring and mortality. The models were co-developed by researchers, conservation NGOs and volunteer surveyors, parameterised using literature data and expert opinion, and validated against observational datasets collected across Great Britain. Results The models were able to simulate habitat specialists, generalists, and species requiring access to multiple habitats for different types of resources (e.g. breeding vs foraging). We identified model refinements required for some taxa and considerations for modelling further species/groups. Conclusions We suggest process-based models that integrate multiple forms of knowledge can assist biodiversity-inclusive decision-making by predicting habitat use throughout the year, expanding the range of species that can be modelled, and enabling decision-makers to better account for landscape context and habitat configuration effects on population persistence.</p