A new lens on biodiversity assessment: The reliability of high-resolution remote sensing in investigating tree species diversity in old-growth forests

Describing and monitoring biodiversity in complex ecosystems is crucial for conservation and sustainable forest management. This study investigates the effectiveness of high-resolution remote sensing (RS) in assessing tree species diversity within the Białowieża Forest, one of the most natural lowla...

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Bibliographic Details
Published in:Forest ecology and management Vol. 595; p. 122987
Main Authors: Erfanifard, Yousef, Kraszewski, Bartłomiej, Lisiewicz, Maciej, Mielcarek, Miłosz, Czerepko, Janusz, Kuberski, Łukasz, Stereńczak, Krzysztof
Format: Journal Article
Language:English
Published: Elsevier B.V 01.11.2025
Subjects:
Airborne laser scanning (ALS)
Canopy and understory diversity
Color infrared (CIR) imagery
Management strategies
Species composition
XGBoost algorithm
XGBoost algorithm
Species composition
Canopy and understory diversity
Airborne laser scanning (ALS)
Management strategies
Color infrared (CIR) imagery
ISSN:0378-1127
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Summary:Describing and monitoring biodiversity in complex ecosystems is crucial for conservation and sustainable forest management. This study investigates the effectiveness of high-resolution remote sensing (RS) in assessing tree species diversity within the Białowieża Forest, one of the most natural lowland forests in Europe and a UNESCO World Heritage Site. The research aimed to evaluate two hypotheses: (H1) that RS can reliably assess canopy tree species diversity across different spatial contexts, and (H2) that there is a strong correlation between RS-derived biodiversity estimates and field measurements, with the correlation varying based on forest management and species composition. The study employed active (Airborne Laser Scanning - ALS) and passive (Color Infrared - CIR) RS data, along with XGBoost, to create species maps, which were compared with field measurements collected across three species compositions and three management categories. Findings suggest that RS is particularly reliable in stable environments with homogeneous species distributions, such as in mixed stands and managed forests, where RS closely aligned with field measurements. However, challenges emerged in capturing rare species and accurately estimating species densities in stands with complex vertical stratification, such as broadleaved stands and strict reserves. These limitations were identified as a critical determinant of the success of RS in biodiversity monitoring, whereas weaker correlations between canopy and understory diversity had a comparatively lesser impact. Overall, this study underscores the potential of RS in assessing tree species diversity, including both canopy and understory, and emphasizes its significance in supporting biodiversity monitoring and conservation. •RS assesses canopy diversity in stable forests but struggles with rare species.•RS performs best in balanced stands, with reduced accuracy in heterogeneous stands.•RS has difficulty distinguishing rare and less frequent species.•RS struggles in complex stands, often misestimating rare and understory species.
ISSN:0378-1127
DOI:10.1016/j.foreco.2025.122987