The ELP encourages the use of a diverse range of evidence in project planning, in order to ensure that lessons from others are applied and actions are more likely to be effective.
The use of scientific evidence to support conservation and restoration decisions can increase the benefits gained and ensure cost effectiveness. However, conservation management actions are frequently based on anecdotal evidence rather than scientific data, potentially wasting limited resources on interventions that have previously been shown to be ineffective.
All ELP Implementation Projects go through a rigorous planning process, during which they are asked to consider the evidence on ecological and social restoration interventions. This involves integrating evidence from published scientific journals and reports with local knowledge and personal experience into decision making, in order to identify and implement the most effective actions for restoration in their target landscape.
There are some specific issues associated with making evidence-based decisions in landscape restoration. The large scale of these projects means that they are likely to be complex, with many interacting actions being undertaken across a range of habitats and species. The scale of some interventions, such as removing a dam or releasing a group of large herbivores, may make it difficult to gather evidence from replicated experiments. In addition, some restoration projects make use of innovative approaches, such as introducing novel species to replace those that have been lost or new applications of technology, which are as yet untested. Landscape restoration projects may also take place in remote locations where little historical data exists, meaning that evidence from less closely related systems may need to be considered.
Such issues may mean that evidence for actions to restore landscapes are scarce or challenging to apply. Therefore, it is especially important for such projects to generate new knowledge and understanding wherever possible, so that lessons can be learned, and experience shared. For more details, please see the section on generating evidence through testing interventions.