Impact of the urbanization process on connectivity and genetic diversity - a spatially explicit simulation approach

Urbanization leads to fragmentation, degradation or loss of natural environments and reduces connectivity between remaining habitat patches. This affects dispersal and establishment of species and their genes and might have adverse effects on biodiversity in urban areas. Here we assess functional connectivity between green spaces for one plant (Plantago major) and one insect (Pieris rapae) model species in the Geneva urban area. We also estimate the impact of future urbanization projects planned until 2030 in Geneva (constructions and road projects) on the connectivity network. We show that the connectivity between small green spaces in the urban centres and larger ones in peripheral areas is fragile and unstable. Potential barriers to dispersal for the study species are mainly buildings, roads, but also large areas of forests, crops and vineyards. Furthermore and based on spatially explicit simulations of gene flow, we test how the distribution of genetic variation among populations along rural-urban gradients is affected by urban landscape elements. We compare these results to empirically observed population responses of the butterfly species P. rapae in the region of Marseille, France. For different dispersal scenarios and taking into account the effect of future intensification of urbanization, results show a decrease in genetic diversity in areas characterized by medium to high urban densities. In order to conserve and promote genetically stable and diverse populations, it is therefore important to maintain or increase landscape connectivity, especially between green spaces in dense urban centres and those in more natural peripheral areas.

Persistence of butterfly populations in fragmented habitats along urban density gradients: motility helps

Stéphane Joost, Estelle Rochat, Ivo Widmer

In a simulation study of genotypes conducted over 100 generations for more than 1600 butterfly’s individuals, we evaluate how the increase of anthropogenic fragmentation and reduction of habitat size along urbanisation gradients (from 7% to 59% of impervious land cover) influences genetic diversity and population persistence in butterfly species. We show that in areas characterised by a high urbanisation rate (> 56% impervious land cover), a large decrease of both genetic diversity (loss of 60-80% of initial observed heterozygosity) and population size (loss of 70-90% of individuals) is observed over time. This is confirmed by empirical data available for the mobile butterfly species Pieris rapae in a sub-part of the study area. Comparing simulated data for P. rapae with its normal dispersal ability and with a reduced dispersal ability, we also show that a higher dispersal ability can be an advantage to survive in an urban or highly fragmented environment. The results obtained here suggest that it is of high importance to account for population persistence, and confirm that it is crucial to maintain habitat size and connectivity in the context of land-use planning.

Nature Publishing Group2017

Species conservation in the face of global environmental changes: surface-based modelling of geo-environmental data to identify vulnerable populations

Estelle Rochat

Human activities are resulting in many land-use changes, particularly due to urbanisation and intensification of agricultural practices. Because of these changes, in addition to climate change, many species are facing habitat degradation. In order to avoid extinction under these conditions, they can either move to more favourable areas or adapt to their new environment. To develop appropriate conservation measures, it is essential to identify vulnerable populations that may not be able to disperse or adapt. In this context, modelling tools can be used to predict the potential impact of environmental changes on species and populations. However, to date, few approaches take into account the degree of exposure, the possibility of dispersal and the potential for adaptation. In this thesis, we present modelling approaches based on geo-environmental data to integrate these three elements. First, we use ecological niche models to estimate the distribution of suitable habitats for a given species as a function of environmental conditions. We propose an improvement of commonly used models by developing an approach to integrate spatio-temporal variability of environmental predictors. In addition, we develop a nested model to predict the distribution of vector-borne pathogens. This model can be used to identify populations that may be threatened by an increasing presence of pathogens in their habitat. We use it to model the evolution of the distribution of Ixodes ricinus ticks and their Chlamydiales bacterial pathogen. We then use landscape graphs to analyse the connectivity between habitats and estimate the possibilities for threatened species to move to more favourable areas. Connectivity is also essential for maintaining gene flow and genetic diversity, which is necessary for greater adaptive capacity. We propose here an approach combining landscape graphs, simulations and empirical genetic data to identify the impact of reduced connectivity on population persistence and genetic diversity. We use it to identify butterfly populations that are threatened by increasing fragmentation in an urban landscape. Finally, we develop the concept of "Spatial Areas of Genotypes Probability" (SPAG) to better analyse the adaptive potential of populations. SPAGs make it possible to model the probability of finding locally adapted genetic variants in a given territory, as well as to identify vulnerable populations lacking in genetic variants that would favour adaptation to future climate conditions. We use it to highlight populations of Moroccan and European goats that are poorly adapted to the climatic conditions predicted under a climate change scenario for 2070 (strong variations in precipitation or increased drought). To conclude, we show how the three modelling approaches presented can be combined and integrated into a more general conservation framework to identify vulnerable populations facing high exposure to environmental changes, low dispersal possibilities and reduced adaptive capacity.

EPFL2020

Dispersal modelling

Séverine Vuilleumier Varisco

In human-dominated landscapes, populations and species extinctions are directly related to habitat destruction and fragmentation. To provide genetic diversity as well as population viability, individual exchanges among isolated populations must be maintained. Therefore, animal dispersal processes in fragmented landscape become an important topic for ecologists, and ecological networks planning has become one of the major challenges for landscape planners. Identification of habitat patches as well as assessment of the effect of ecological networks is badly needed. Since little information on the effect of landscape heterogeneities on animal dispersal is available, simulation models are being developed. As dispersal pattern and success strongly depend on the spatial context, species' interactions with landscapes, species behaviour and species ability to disperse, these models must be able to simulate them explicitly. This research work therefore aims first at developing methods and models that allow realistic animal dispersal simulations in fragmented landscapes. Second it aims at evaluating the effect of landscape heterogeneities and animal behaviour on dispersal and on species persistence. Additionally, the ability of such a model to estimate gene flow is analysed. To carry on this research, the following fields have been explored: landscape ecology, metapopulation dynamic, animal behaviour, genetics, Geographical Information Systems, modelling approaches and programming. A method, based on properties provided by Geographical Information Systems software, is first proposed to generate ecological networks by simulating animal dispersal according to animal movement constraints induced by human infrastructures. The resulting maps provide a spatial identification of ecological networks, corridors and conflicting areas. This model has proved to be a useful and straightforward tool for landscape planning, even if this model, similar to other present-day models used in dispersal simulations, presents numerous technical and scientific limitations. To improve models for animal dispersal, a feature-oriented landscape model associated with an expert system has been developed. Its conceptualisation, its formalism, its data structure and its object-oriented design implementation provide a very accurate representation of landscape features and simulation of complex interactions between model entities (individuals and landscape features) based on simple rules. It allows the spatial identification of simulated processes. The ability of this model to incorporate states, relations and transition rules between entities makes it applicable to simulate large ranges of dispersal processes according to specific behaviour and/or landscape uses. To analyse the influence of landscape heterogeneities and species behaviour on dispersal and their incidence on metapopulation dynamics, the proposed feature-oriented model has been coupled with an animal model. The latter assigns different cognitive and dispersal abilities to individuals. Based on simulations according to three movement strategies (corresponding to the cognitive abilities of the simulated species), two measures evaluate the effect of cognitive abilities on dispersal: the colonisation probability between habitat patches and the ecological distance (due to landscape heterogeneities). These measures give an estimation of metapopulation structures (the habitat patches belonging to the metapopulation) and metapopulation dynamics induced by the landscape heterogeneities (for example, the habitat patches which release individuals). The complexity of dispersal processes, considering species behaviours and dispersal abilities, can therefore be reproduced and analysed at different levels. This application has shown the importance of animal behaviour on metapopulation dynamics and structure. Since tracking animals and providing sufficient data remain difficult, calibration and validation procedures of dispersal models are difficult to perform. One approach proposed here is to measure one of the consequences of dispersal: genetic differentiation among populations. Geographical distances are in general used to explain a part of the genetic differentiations. But as our fundamental assumption states that landscape heterogeneities and spatial arrangements of landscape features may strongly affect dispersal successes, genetic distance between populations must be better explained by the estimate of a model which considers these factors. We have tested this assumption with the greater white-toothed shrew (Crocidura russula). Scenarios considering various behaviours and dispersal abilities of C. russula have been performed. Relating measures of genetic, geographical and ecological distances (the latter emerge from scenario simulation results) highlights the model capability to reproduce dispersal of C. russula by explaining a greater part of the genetic differentiation than that explained by the geographical distances. This application has not only pointed out the ability of the model to quantify connectivity between habitat patches but also the difficulty to relate gene dispersal and individual dispersal.