Assessing macroinvertebrate species composition in forest streams using LiDAR-based vegetation structure variables
The structure of terrestrial vegetation plays a crucial role in shaping stream habitats and macroinvertebrate communities. While previous studies examined the effects of catchment land-cover descriptors (usually coarse resolution) and riparian buffer characteristics (on-ground measures) on aquatic e...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25010209 |
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| Summary: | The structure of terrestrial vegetation plays a crucial role in shaping stream habitats and macroinvertebrate communities. While previous studies examined the effects of catchment land-cover descriptors (usually coarse resolution) and riparian buffer characteristics (on-ground measures) on aquatic ecosystems, the potential of high-resolution LiDAR-derived vegetation variables remains largely unexplored. This study investigates the potential application of LiDAR-based forest structure metrics for assessing macroinvertebrate communities in two mountain catchments in the core zones of two national parks in the Bohemian Forest Ecosystem. We analysed macroinvertebrate assemblages alongside in-stream environmental variables and LiDAR-derived parameters describing forest structure and land cover at three spatial scales: small (100 m buffer), medium (500 m buffer), and catchment-wide. Our results demonstrate significant effects of LiDAR variables on macroinvertebrate species composition, shaped by forest structure, the extent of non-forest biotopes, and forest disturbance history. Key predictors were the deciduous/coniferous cover, amount of deadwood, and living tree height and biomass, which were linked to in-stream habitat characteristics and water chemistry, but also showed some effects independent of in-stream variables. At smaller scales, LiDAR variables were primarily linked to in-stream habitat structure (organic debris, wood) and concentrations of dissolved organic carbon and phosphorus, whereas at the catchment scale, they were more closely associated with water chemistry (acidity, nutrients and ions concentrations). These findings highlight the utility of LiDAR data for stream assessment, offering a novel approach to understanding stream-catchment interactions in forested landscapes. By integrating remote sensing with traditional ecological monitoring, our study underscores the importance of multi-scale habitat assessments in assessing macroinvertebrate community structure and stream ecosystem dynamics. |
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| ISSN: | 1470-160X |