Human-caused habitat loss and fragmentation disrupt contiguous natural areas, leading to low population sizes and isolation of populations. To avoid increased risk of extinction, conservation networks are created: clusters of connected protected areas, largely based on expert-opinion. In landscape ecology, models are used to increase ecological realism in network design in order to avoid misguided management actions. However, increasing the ecological complexity requires detailed ecological data. In this dissertation, I investigate the challenges and opportunities encountered applying such models for conservation network design. With remote-sensing and species detection data, I modelled potential connectivity for white-lipped peccaries Tayassu pecari in Belize. This species is an endangered forest ungulate that requires large forest areas and has a short dispersal range. The model identifed alternative corridor routes and areas that were particularly important for connectivity conservation. Satellite tracking of an individual in southern Belize showed that animal activity, and presumably forest cover and terrain ruggedness hampered data collection. Nevertheless, results showed an average home-range size and slow movement rates compared to other estimates, and confrmed the species' preference for forested habitats. A global evaluation of satellite telemetry in wildlife research, including over 3,000 telemetry units, provided insight into the relative in uence of the environment, topography, species, and unit characteristics on unit performance. Fix acquisition and data transfer rates were high, but close to half of the deployments failed prematurely, and half of these due to technical malfunction. Species and unit characteristics predicted unit performance better than environmental factors. Conservation network design based on moderately data-demanding models seems to be an achievable objective. However, modelling with high levels of ecological detail is still challenged by technological shortcomings. Ultimately, efective conservation network design depends on the continued collaboration between the modelling, empirical, and applied domains of connectivity conservation.