  We focus on connectivity methods used to understand and predict how
landscapes and habitats facilitate or impede the movement and dispersal of
species. Our objective is to compare the implication of methodological choices
at three stages of the modelling framework: landscape characterisation,
connectivity estimation, and connectivity assessment. What are the convergences
and divergences of different modelling approaches? What are the implications of
their combined results for landscape planning? We implemented two landscape
characterisation approaches: expert opinion and species distribution model
(SDM); four connectivity estimation models: Euclidean distance, least-cost
paths (LCP), circuit theory, and stochastic movement simulation (SMS); and two
connectivity indices: flux and area-weighted flux (dPCflux). We compared
outcomes such as movement maps and habitat prioritisation for a rural landscape
in southwestern France. Landscape characterisation is the main factor
influencing connectivity assessment. The movement maps reflect the models'
assumptions: LCP produced narrow beams reflecting the optimal pathways; whereas
circuit theory and SMS produced wider estimation reflecting movement
stochasticity, with SMS integrating behavioural drivers. The indices
highlighted different aspects: dPCflux the surface of suitable habitats and
flux their proximity. We recommend focusing on landscape characterisation
before engaging further in the modelling framework. We emphasise the importance
of stochasticity and behavioural drivers in connectivity, which can be
reflected using circuit theory, SMS or other stochastic individual-based
models. We stress the importance of using multiple indices to capture the
multi-factorial aspect of connectivity.
