Abstract

The long timeframes involved in woodland regeneration and adaptation introduce considerable uncertainty into management and conservation planning as most ecological datasets span only a small part of ecosystem dynamics. This is a particular concern in vulnerable habitats, such as Atlantic birch-oak woods in north-western Britain, where range edge populations are at risk from herbivory and climate change. This study combines historical palaeoecology and stakeholder observations to assess how multiple perspectives can inform existing models, expectations and goals for Atlantic woodland management. Long-term evidence for changing woodland composition addresses stakeholder uncertainties over the currently restricted distribution of oak, alder and hazel. Oak has remained a secondary component of birch-dominated woods and habitat definitions based on oak are too narrow to ensure sustainability. Birch has survived numerous periods of climatic and biotic adversity and shows the strongest positive response to historic reductions in grazing pressure. This has led to a pulse of regeneration since c. AD 1900, so current restoration efforts are taking place within the strongest period of woodland expansion in the last c. 500 years. Positive and negative cultural legacies are evident and intervention is considered a necessary restoration tool. Managed grazing at key stages of habitat development can support continued recruitment and regeneration. A more flexible and integrated management approach is recommended. Long-term ecology can provide direction and address uncertainties, while ecological and stakeholder evidence provide the detail necessary to develop effective management that incorporates ecosystem perspectives. This can help shape management strategies that balance possible conflicts over perceived short-term ‘damage’ to secure longer-term processes. Learning based on multiple temporal perspectives has the potential to contribute to conservation and restoration planning and practice. These principles are more widely applicable in adaptive management.

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