Epsilon Archive for Student Projects

Abstract

Forest structural complexity plays a vital role in sustaining biodiversity and mitigating the climate through carbon sequestration, microclimate regulation and ecosystem resilience. The ecosystem services depend not only on forest structure itself, but also on our ability to measure that structure in a meaningful way. However, there is currently no single integrative measure that is widely accepted for measuring structural complexity, despite its ecological significance. Therefore, there is need for structural indices that can aggregate multidimensional stand attributes into a single, comparable measure. With the help of additional plot data from across Eurasia, this thesis investigates an integrated forest complexity index that incorporates α-diversity components of structural complexity and applies it to boreal forest stands in Svartberget, Northern Sweden. Several aggregation and weighting techniques were tested to synthesise these components into an aggregation index. The findings demonstrate that the aggregation technique has a greater impact on the resulting complexity metric than the weighting method. Compared to other aggregation methods, the weighted arithmetic‑geometric method was the least sensitive to high or low values and produced a balanced compromise neither overstating nor over-penalising the aggregation. This aggregation method in combination with inverse correlation-based weights achieved the most effective differentiation among plots. Plot ranking and index magnitude were only slightly impacted by weighting methods, indicating the robustness of the chosen structural complexity metrics. In general, the least structurally complex plots of the 17 total plots were the nine Svartberget plots. The aggregated structural complexity metric distinguished low-complexity plots in agreement with field assessments but did not clearly separate plots classified as medium and high complexity in the field. The research offers a potential methodology for measuring stand-level structural complexity for forest ecosystems but needs further assessment in medium and high complexity boreal forests.