Context Landscape complementation, or how landscapes that contain two or more non-substitutable and spatially separated resources facilitate resource use, is critical for many populations. Implicit to the problem of landscape complementation is the movement of individuals to access multiple resources. Conventional measures of complementation, such as habitat area or distance between habitats, do not consider the spatial configuration of resources or how landscape features impede movement. Objectives We advanced a bipartite network approach to capture the spatial configuration and connectivity of two habitat types and contrasted this framework to conventional approaches in a habitat selection model. Methods Using satellite-telemetry of the Florida manatee (Trichechus manatus latirostris), a marine mammal that relies on two distinct, spatially separate habitats for foraging and thermoregulating, we parameterized and compared mixed conditional logistic models with covariates describing classic habitat selection metrics, conventional measures of landscape complementation, and bipartite network metrics. Results The models best supported included habitat area, resistance distance between habitats, and the bipartite network metric eigenvector centrality. The connectivity between habitats and the spatial configuration of one habitat type relative to other types better described habitat selection than conventional measures of landscape complementation alone. The type of habitat, i.e. seagrass or thermal refuge, influenced both the direction and magnitude of the response. Conclusions Landscape complementation is an important predictor of selection and thus classic complementation measures are not sufficient in describing the process. Formalization of complementation with bipartite network can therefor reveal effects potentially missed with conventional measures.