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Abstract Due to the central role of landscape connectivity in many ecological processes, evaluating and accounting for it has gained attention in both theoretical and applied ecological sciences. To address this challenge, researchers often use generic species to simplify multi‐species connectivity assessments. Yet, this approach tends to oversimplify movement behaviour, likely reducing realism and precision of connectivity model outputs. Also, the most widely used methods and theories for assessing landscape connectivity, namely circuit and network theories, have strong limitations. Finally, uncertainty or robustness estimates are rarely integrated in connectivity assessments. Here, we propose a versatile framework, which, instead of using arbitrary defined generic species, first identifies species groups based on species' environmental niches and morphological, biological, and ecological traits. Second, it combines circuit and network theories to take the best of the two methods to assess landscape connectivity for those groups, while integrating uncertainties in modelling choices. Specifically, ecological continuities (i.e. landscape elements contributing to connectivity) are calculated for these groups and used together with group dispersal capacities to derive network‐based connectivity metrics for conservation areas. We detailed our framework through a case study where we assess the connectivity of 1619 protected areas in metropolitan France for 193 vertebrate species. Our study revealed that both the protection of ecological continuities and the connectivity of protected areas for 11 mammal and 19 bird groups, respectively, were quite low, with variations among groups. Different protection types (i.e. national parks, reserves or prefectural orders) contributed unequally to the overall connectivity of group‐specific suitable habitats. Considering uncertainty propagation was crucial, as many connectivity metrics varied among repetitions. The proposed framework combines different connectivity tools to provide a more relevant and comprehensive assessment of landscape connectivity. It can be used to inform the decision‐making process for spatial planning, particularly in the context of connectivity conservation and management, or support theoretical studies to better understand the ecological role of landscape connectivity. Its flexibility allows easy application under various environmental conditions, including future scenarios.

Abstract Landscape complexity can determine the population dynamics of interacting predators and prey. Yet, management plans are commonly developed from aspatial predictive models. This oversight may result in unexpected outcomes or the loss of opportunities to make spatial interventions that would increase a plan's effectiveness. The management of the threatened woodland caribou (Rangifer tarandus caribou), boreal population, provides an example of such shortcomings when using an aspatial approach. Currently, the most influential management recommendation is to maintain at least 65% of undisturbed forests in areas occupied by caribou populations, regardless of the spatial configuration of the forest cover. Using a spatially explicit individual‐based model (IBM), we evaluated the effects of the spatial configuration of cuts and roads on the mortality of boreal caribou living in sympatry with wolves (Canis lupus) and moose (Alces alces), an apparent competitor. Starting with a real forest landscape, we created forest management scenarios of the specific spatial distribution of cuts (mosaic, small, or large agglomeration) with increasing disturbance levels. We then ran the IBM with simulated agents, representing individuals of the three species, moving according to movement rules determined from radio‐collared individuals. We found that movement responses to land cover types and roads differed among species. For example, caribou and moose generally avoided areas close to roads, contrary to wolves. Those differences influenced the mortality of caribou agents, which not only depended on the levels of disturbance but also depended on the spatial distribution of cuts and roads. After controlling for disturbance level, wolves were more successful when forest management required an extensive road network resulting in relatively high habitat fragmentation. Caribou agents experienced lower mortality in landscapes with low densities of road and disturbance‐related edges. The effect remained much stronger, however, for the level than the spatial configuration of human disturbances. Still, our IBM demonstrated how landscape management could be used to manipulate species interactions, with the intent of either increasing or decreasing predation rates on specific populations, depending on management goals.