Connectivity analysis as a tool for assessing restoration success

Context

Methods for measuring restoration success that include functional connectivity between species’ populations are rare in landscape ecology and restoration practices. We developed an approach that analyzes connectivity between populations of target species and their dispersal probabilities to assess restoration success based on easily accessible input data. Applying this method to landscape development scenarios can help optimize restoration planning.

Objectives

We developed an assessment for restoration success and restoration planning based on functional connectivity between species’ populations and spatially explicit scenarios. The method was used in a case study to test its applicability.

Methods

Based on data on available habitat, species’ occurrence and dispersal ranges, connectivity metrics and dispersal probabilities for target species are calculated using the software Conefor Sensinode. The metrics are calculated for scenarios that reflect possible changes in the landscape to provide a basis for future restoration planning. We applied this approach to floodplain meadows along the Upper Rhine for four plant species and three future scenarios.

Results

In the case study, habitats of the target species were poorly connected. Peucedanum officinale and Sanguisorba officinalis were more successful in recolonizing new habitats than Iris spuria and Serratula tinctoria. The scenarios showed that restoration of species-rich grassland was beneficial for dispersal of the target species. As expected in the agriculturally dominated study area, restoration of former arable land significantly increased dispersal probabilities.

Conclusions

In the case study, the developed approach was easily applicable and provided reasonable results. Its implementation will be helpful in decision-making for future restoration planning.