Same Viewpoint Different Perspectives—A Comparison of Expert Ratings with a TLS Derived Forest Stand Structural Complexity Index

Forests are one of the most important terrestrial ecosystems for the protection of biodiversity, but at the same time they are under heavy production pressures. In many cases, management optimized for timber production leads to a simplification of forest structures, which is associated with species loss. In recent decades, the concept of retention forestry has been implemented in many parts of the world to mitigate this loss, by increasing structure in managed stands. Although this concept is widely adapted, our understanding what forest structure is and how to reliably measure and quantify it is still lacking. Thus, more insights into the assessment of biodiversity-relevant structures are needed, when aiming to implement retention practices in forest management to reach ambitious conservation goals. In this study we compare expert ratings on forest structural richness with a modern light detection and ranging (LiDAR) -based index, based on 52 research sites, where terrestrial laser scanning (TLS) data and 360° photos have been taken. Using an online survey (n = 444) with interactive 360° panoramic image viewers, we sought to investigate expert opinions on forest structure and learn to what degree measures of structure from terrestrial laser scans mirror experts’ estimates. We found that the experts’ ratings have large standard deviance and therefore little agreement. Nevertheless, when averaging the large number of participants, they distinguish stands according to their structural richness significantly. The stand structural complexity index (SSCI) was computed for each site from the LiDAR scan data, and this was shown to reflect some of the variation of expert ratings (p = 0.02). Together with covariates describing participants’ personal background, image properties and terrain variables, we reached a conditional R2 of 0.44 using a linear mixed effect model. The education of the participants had no influence on their ratings, but practical experience showed a clear effect. Because the SSCI and expert opinion align to a significant degree, we conclude that the SSCI is a valuable tool to support forest managers in the selection of retention patches

Improving decision-making on wild land conservation in Europe through analysis of human perceptions of wild spaces and species

The conservation and restoration of wild spaces and species has become popular as a cost-effective, nature-based solution, to address biodiversity loss, landscape fragmentation and flood risk. Effective conservation requires a comprehensive evidence base, and there is a clear need for integrated methods to map remaining wilderness areas in support of decision-making on their protection for future generations. This PhD focuses spatially on wild spaces and species within upland areas in France and Scotland. It explores participatory, place-based methods, for capturing human perceptions of wild spaces that could be used to improve the quality of the maps that we make of wildness. It analyses public perceptions towards wild spaces and species in situ at the local level, and examines how they relate to current wildness mapping. It explores the impact of immersion in wild spaces and exposure to historical landscape conditions on attitudes to possible landscape futures and species reintroductions. As an answer to the challenges of better capturing local ecological knowledge, and the subjective nature of our experience of wild spaces, it tests novel methods for including ecoacoustics in the mapping of wildness, which capture more than just the visual attributes of wild spaces. Significant correlations were found between existing maps of wildness, human perceptions of wildness, and ecoacoustic indices captured along the same transect. The results of the different methodological approaches showed a high level of agreement and together reveal details of key attributes of wildness excluded under current methods. An important next step is to develop these methods, improve how the results can be integrated, and explore how additional knowledge types and data could be included. Taken together, the results suggest that future wildness mapping could benefit from the potential of the methods tested here to support more effective conservation of wild spaces and wild species within Europe