Today?s large-scale distributed systems consist of collections of nodes that have highly variable availability - a phenomenon sometimes called churn. This availability variation is often a hindrance to achieving reliability and performance for distributed applications such as multicast. This paper looks into utilizing and leveraging availability information in order to provide availability-dependent message reliability for multicast receivers. An application (e.g., a publish-subscribe system) may want to scale the multicast message reliability at each receiver according to that receiver?s availability (in terms of the fraction of time that receiver is online) - different options are that the reliability is independent of the availability, or proportional to it.. We propose several gossip-based algorithms to support several such predicates. These techniques rely on each node?s availability being monitored in a distributed manner by a small group of other nodes in such a way that the monitoring load is evenly distributed in the system. Our techniques are light-weight, scalable, and are space- and timeefficient. We analyze our algorithms and evaluate them experimentally by injecting availability traces collected from real peer-to-peer systems.