Dataset Information

Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates.

ABSTRACT: We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets of airborne light detection and ranging (lidar), including five multi-temporal and 610 single-date lidar datasets. Specifically, we (1) compared the fixed height and relative height methods for gap delineation and established a relationship between static and dynamic gaps (newly created gaps); (2) explored potential environmental/climate drivers explaining gap occurrence using generalized linear models; and (3) cross-related our findings to mortality estimates from 181 field plots. Our findings suggest that static gaps are significantly correlated to dynamic gaps and can inform about structural changes in the forest canopy. Moreover, the relative height outperformed the fixed height method for gap delineation. Well-defined and consistent spatial patterns of dynamic gaps were found over the Amazon, while also revealing the dynamics of areas never sampled in the field. The predominant pattern indicates 20-35% higher gap dynamics at the west and southeast than at the central-east and north. These estimates were notably consistent with field mortality patterns, but they showed 60% lower magnitude likely due to the predominant detection of the broken/uprooted mode of death. While topographic predictors did not explain gap occurrence, the water deficit, soil fertility, forest flooding and degradation were key drivers of gap variability at the regional scale. These findings highlight the importance of lidar in providing opportunities for large-scale gap dynamics and tree mortality monitoring over the Amazon.

SUBMITTER: Dalagnol R

PROVIDER: S-EPMC7809196 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates.

Dalagnol Ricardo R Wagner Fabien H FH Galvão Lênio S LS Streher Annia S AS Phillips Oliver L OL Gloor Emanuel E Pugh Thomas A M TAM Ometto Jean P H B JPHB Aragão Luiz E O C LEOC

Scientific reports 20210114 1

We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets of airborne light detection and ranging (lidar), including five multi-temporal and 610 single-date lidar datasets. Specifically, we (1) compared the fixed height and relative height methods for gap delineation and established a relationship between static and dynamic gaps (newly created gaps); (2) explored potential environmental/climate drivers explaining gap occurrence using generalized linear ...[more]

PMID: 33446809

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Project description:Landscape-scale deforestation poses a major threat to global biodiversity, not only because it limits habitat availability, but also because it can drive the degradation of the remaining habitat. However, the multiple pathways by which deforestation directly and indirectly affects wildlife remain poorly understood, especially for elusive forest-dependent species such as arboreal mammals. Using structural equation models, we assessed the direct and indirect effects of landscape forest loss on arboreal mammal assemblages in the Lacandona rainforest, Mexico. We placed camera traps in 100 canopy trees, and assessed the direct effect of forest cover and their indirect effects via changes in tree basal area and canopy openness on the abundance and diversity (i.e., species richness and exponential of Shannon entropy) of arboreal mammals. We found that forest loss had negative indirect effects on mammal richness through the increase of tree canopy openness. This could be related to the fact that canopy openness is usually inversely related to resource availability and canopy connectivity for arboreal mammals. Furthermore, independently of forest loss, the abundance and richness of arboreal mammals was positively related to tree basal area, which is typically higher in old-growth forests. Thus, our findings suggest that arboreal mammals generally prefer old-growth vegetation with relatively low canopy openness and high tree basal area. However, unexpectedly, forest loss was directly and positively related to the abundance and richness of mammals, probably due to a crowding effect, a reasonable possibility given the relatively short history (~40 years) of deforestation in the study region. Conversely, the Shannon diversity was not affected by the predictors we evaluated, suggesting that rare mammals (not the common species) are the ones most affected by these changes. All in all, our findings emphasize that conservation measures ought to focus on increasing forest cover in the landscape, and preventing the loss of large trees in the remaining forest patches.

Dataset Information

Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates.

Publications

Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates.

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