The problem of (semi-)automatic treebank conversion arises when converting between different schemas, such as from a language specific schema to Universal Dependencies, or when converting from one Universal Dependencies version to the next. This thesis develops a formalism based on top-down tree transducers to convert dependency trees. Building on a well-defined mechanism yields a robust transformation system with clear semantics for rules and which guarantees that every transformation step results in a well formed tree, in contrast to previously proposed solutions. To exemplify the efficiency of the approach, a rule set to transform the Hamburg Dependency Treebank is created, which can already transform annotations with both coverage and precision of more than 90%.