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Due to advances in low power sensors, energy harvesting, and disruption tolerant networking, we can now build mobile systems that operate perpetually, sensing and streaming data directly to scientists. However, factors such as energy harvesting variability and unpredictable network connectivity make building robust and perpetual systems difficult. In this paper, we present a system, Tula, that balances sensing with data delivery, to allow perpetual and robust operation across highly dynamic and mobile networks. This balance is especially important in unpredictable environments; sensing more data than can be delivered by the network is not useful, while gathering less underutilizes the system's potential. Tula is decentralized, fair and automatically adapts across different mobility patterns. We evaluate Tula using mobility and energy traces from TurtleNet-a mobile sensor network we deployed to study Gopher tortoises-and publicly available traces from the UMass DieselNet testbed. Our evaluations show that Tula senses and delivers data at up to 85 percent of an optimal, oracular system that perfectly replicates data and has foreknowledge of future energy harvesting. We also demonstrate that Tula can be implemented on a small microcontroller with modest code, memory, and processing requirements.