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Influence of different scales of forest structural complexity on ecosystem stability
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Disturbances such as extreme drought stress are becoming more frequent globally and pose a critical threat to boreal and temperate forests. Forest resistance to disturbances is influenced by multiple factors, including soil, climate, and structural complexity. Since a substantial portion of ecosystem functioning variability is related to maximum ecosystem productivity and water-use strategies, as part of WP2 of the CLIMB-FOREST EU project we calculated ecosystem functional properties (EFPs) that reflect these processes. Specifically, we used eddy covariance flux data to quantify photosynthetic capacity (NEPsat), underlying water-use efficiency (uWUE), and evaporative fraction (EFrac) for 71 forest sites across boreal and temperate regions of Europe and North America. To describe functional stability, we analyzed both mean EFPs and their inter-annual variability for each site. To examine which scales of structural complexity are associated with EFP stability, we used satellite-based indices describing vegetation structure and heterogeneity, including Rao’s Q of the Enhanced Vegetation Index (EVIRao), normalized near-infrared reflectance of vegetation (NIRvN), near-infrared entropy (NIRent), and maximum leaf area index (LAI). We applied generalized additive models (GAMs) combined with bootstrap-based variable importance analysis to evaluate associations between EFPs and structural complexity.We found that associations between EFPs and structural complexity metrics varied among ecosystem properties, with predictors more frequently meeting bootstrap-based importance criteria for mean EFPs than for their inter-annual variability. Maximum LAI and NIRvN were consistently retained as important predictors for mean NEPsat and mean EFrac, whereas no structural complexity metrics met the importance criteria for uWUE or for most variability metrics. Smooth-term estimates indicated directional partial associations, with higher LAI and NIRvN corresponding to higher modelled values of NEPsat and EFrac, while EVIRao and NIRent showed weaker or inconsistent partial trends. Overall, the results suggest that quantity of leaves and their spatial arrangement might be more important for EFPs than horizontal heterogeneity. Forests with denser and more organized canopies tended to function at higher levels of productivity and evaporation, without showing stronger inter-annual variability.
Copernicus GmbH
Title: Influence of different scales of forest structural complexity on ecosystem stability
Description:
Disturbances such as extreme drought stress are becoming more frequent globally and pose a critical threat to boreal and temperate forests.
Forest resistance to disturbances is influenced by multiple factors, including soil, climate, and structural complexity.
Since a substantial portion of ecosystem functioning variability is related to maximum ecosystem productivity and water-use strategies, as part of WP2 of the CLIMB-FOREST EU project we calculated ecosystem functional properties (EFPs) that reflect these processes.
Specifically, we used eddy covariance flux data to quantify photosynthetic capacity (NEPsat), underlying water-use efficiency (uWUE), and evaporative fraction (EFrac) for 71 forest sites across boreal and temperate regions of Europe and North America.
To describe functional stability, we analyzed both mean EFPs and their inter-annual variability for each site.
To examine which scales of structural complexity are associated with EFP stability, we used satellite-based indices describing vegetation structure and heterogeneity, including Rao’s Q of the Enhanced Vegetation Index (EVIRao), normalized near-infrared reflectance of vegetation (NIRvN), near-infrared entropy (NIRent), and maximum leaf area index (LAI).
We applied generalized additive models (GAMs) combined with bootstrap-based variable importance analysis to evaluate associations between EFPs and structural complexity.
We found that associations between EFPs and structural complexity metrics varied among ecosystem properties, with predictors more frequently meeting bootstrap-based importance criteria for mean EFPs than for their inter-annual variability.
Maximum LAI and NIRvN were consistently retained as important predictors for mean NEPsat and mean EFrac, whereas no structural complexity metrics met the importance criteria for uWUE or for most variability metrics.
Smooth-term estimates indicated directional partial associations, with higher LAI and NIRvN corresponding to higher modelled values of NEPsat and EFrac, while EVIRao and NIRent showed weaker or inconsistent partial trends.
Overall, the results suggest that quantity of leaves and their spatial arrangement might be more important for EFPs than horizontal heterogeneity.
Forests with denser and more organized canopies tended to function at higher levels of productivity and evaporation, without showing stronger inter-annual variability.
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