An interdisciplinary approach to achieve consensus for evidence-based management of red deer (Cervus elaphus) in the Lake District

Human-wildlife conflict (HWC) is a global conservation problem and a significant driver of species extinction risk. HWC is commonly associated with human-human conflicts that increase the complexity of creating lasting solutions. Resolving both the human-wildlife and human-human elements of these conflicts requires an interdisciplinary approach to evaluate the ecological impacts of the target species and engage key stakeholders. Red deer (Cervus elaphus) are managed by humans to mitigate perceived negative impacts to human land-use objectives. The aim of this PhD was to develop a new best practice process by synthesising natural- and social- science methods to achieve collaborative, landscape-scale adaptive deer impact management in the Lake District National Park. The PhD aim was achieved through the engagement of key stakeholders, evaluating the habitat impacts of deer across the landscape, and estimating the population abundance of deer to inform impact management actions.

Key stakeholders across Borrowdale and Thirlmere were engaged in a bottom-up approach, using a modified Delphi process. The Delphi process was employed to evaluate how stakeholders value a cultural rural landscape and native deer populations within it, and to enable equitable discussion to build consensus in co-created adaptive impact management. Crucially, consensus was achieved through a holistic approach in which participants defined the nature of the conflict, articulated shared values and objectives, and collaboratively constructed an adaptive management decision making framework, demonstrating that value led facilitation can reconcile divergent land use priorities in a contested landscape.

To inform adaptive impact management decision-making, the red deer population size was estimated using four different methods: two census and two sampling methods. The Random Encounter Model (REM) was demonstrably the most cost-effective and precise approach for informing deer management actions. From REM estimates, mean red deer density showed a suggested decline of approximately 5.7% per year over the three-year study period, but statistical support of this trend was marginal.

The impacts of deer were estimated across the landscape using index methods; Deer Activity and Impact (DAI) method for woodlands, and Putman Method for open range habitats. From 2022 to 2024 in Borrowdale and Thirlmere, average impacts in open range habitats remained moderate to low moderate and did not change significantly over time, nor did woodland impacts, which remained low moderate to moderate. Additionally, the DAI and Putman Methods were evaluated against independent assessments of impact to validate their effectiveness in informing impact management. Both the DAI (rs(18) = 0.809, p <0.05) and the Putman Method (rs(38) = 0.893, p <0.001) demonstrated strong positive correlations with independently derived impact estimates. Taken together, the population and impact assessments demonstrate that robust, low complexity ecological monitoring methods can be aligned with stakeholder defined objectives to inform adaptive impact management at landscape scale.

This thesis demonstrated that integrating participatory consensus-building with validated, practitioner-friendly ecological monitoring provides a viable and transferable framework for mitigating long-standing HWC. By embedding population and impact monitoring within a socially legitimate decision-making process, adaptive management becomes both technically defensible and politically durable. Facilitated consensus building was critical to the co creation of shared objectives, monitoring actions, and deer population control methods, embedding technical decision making within a socially legitimate governance structure. This approach has direct implications for deer management and conservation policy, indicating that socially legitimate, adaptive management can be operationalised where ecological evidence and stakeholder values are jointly incorporated into decision making.

Future research should focus on refining key ecological parameters to support practitioner uptake of monitoring methods and evaluating whether the adaptive management framework can be sustained through self management. Periodic stakeholder re-engagement will be essential to reassess and adapt the framework, ensuring it continues to underpin management policy and contributes to the long term mitigation of human–red deer conflict in this multi user landscape.