Forest structure
View article: juliana7hl/R.pal_T.cruzi_Panama: Successional and native forest predict the occurrence and infection status of Chagas disease vectors in Panama
juliana7hl/R.pal_T.cruzi_Panama: Successional and native forest predict the occurrence and infection status of Chagas disease vectors in Panama Open
This code and data were used for the statistical analysis of the results presented in the work entitled "Successional and native forest predict the occurrence and infection status of Chagas disease vectors in Panama", by Hoyos et al., 2025
View article: FIGURE 8 in New species of Glossoscolex and Fimoscolex earthworms (Oligochaeta: Glossoscolecidae) from the Brazilian Atlantic Forest and Cerrado biomes
FIGURE 8 in New species of Glossoscolex and Fimoscolex earthworms (Oligochaeta: Glossoscolecidae) from the Brazilian Atlantic Forest and Cerrado biomes Open
FIGURE 8. Glossoscolex debortolii sp. nov. Holotype. A. View of the prostomium and clitellum in XIV–XIII. B. Setal arrangement, in the red rectangles, at the end of the worm, on the last segments. C. View of pair of male pores in XVII, in …
View article: Challenges for regeneration and stability of riparian forests under river regulation: lag effects and altered successional trajectory
Challenges for regeneration and stability of riparian forests under river regulation: lag effects and altered successional trajectory Open
This repository contains the scripts and associated data used for the analysis presented in the related study. The research examines the effects of dam regulation on riparian forest structure and woody plant regeneration in the Irati River…
View article: Foraging strategy of wood mice for undamaged and moth-infested Castanea crenata nuts on forest floor
Foraging strategy of wood mice for undamaged and moth-infested Castanea crenata nuts on forest floor Open
View article: FIGURE 8 in New species of Glossoscolex and Fimoscolex earthworms (Oligochaeta: Glossoscolecidae) from the Brazilian Atlantic Forest and Cerrado biomes
FIGURE 8 in New species of Glossoscolex and Fimoscolex earthworms (Oligochaeta: Glossoscolecidae) from the Brazilian Atlantic Forest and Cerrado biomes Open
FIGURE 8. Glossoscolex debortolii sp. nov. Holotype. A. View of the prostomium and clitellum in XIV–XIII. B. Setal arrangement, in the red rectangles, at the end of the worm, on the last segments. C. View of pair of male pores in XVII, in …
View article: Challenges for regeneration and stability of riparian forests under river regulation: lag effects and altered successional trajectory
Challenges for regeneration and stability of riparian forests under river regulation: lag effects and altered successional trajectory Open
This repository contains the scripts and associated data used for the analysis presented in the related study. The research examines the effects of dam regulation on riparian forest structure and woody plant regeneration in the Irati River…
View article: Guyafor network, permanent forest plots for long-term monitoring of French Guiana's forest ecosystems
Guyafor network, permanent forest plots for long-term monitoring of French Guiana's forest ecosystems Open
Guyafor is a network of permanent forestry plots installed in French Guiana, dedicated to the long-term study of forest dynamics and biodiversity. The main objectivs of this network, co-managed by research organizations (CIRAD and CNRS) an…
View article: Circumpolar Boreal Forest Aboveground Biomass Density and Vegetation Height, V3
Circumpolar Boreal Forest Aboveground Biomass Density and Vegetation Height, V3 Open
This dataset provides estimates of aboveground dry woody biomass density (AGBD) and vegetation height for high northern latitude forests at a 30-m spatial resolution for the year 2020, accounting for >30% of global forest area. The estimat…
View article: Unveiling Subcanopy Geographies: A Synergistic Multispectral, Hyperspectral, and SAR Paradigm for Forest Ecosystem Dynamics
Unveiling Subcanopy Geographies: A Synergistic Multispectral, Hyperspectral, and SAR Paradigm for Forest Ecosystem Dynamics Open
Forest ecosystems are vital for global biodiversity, carbon sequestration, and climate regulation, yet their intricate subcanopy structures remain challenging to accurately characterize using traditional remote sensing methods. This paper …
View article: Synergistic Hyperspectral-SAR Deep Fusion for Fine-Grained Forest Biodiversity Mapping
Synergistic Hyperspectral-SAR Deep Fusion for Fine-Grained Forest Biodiversity Mapping Open
Forest biodiversity is a critical indicator of ecosystem health and provides invaluable ecosystem services. However, accurate and fine-grained mapping of forest biodiversity at large scales remains a significant challenge due to the comple…
View article: Unveiling Subcanopy Geographies: A Synergistic Multispectral, Hyperspectral, and SAR Paradigm for Forest Ecosystem Dynamics
Unveiling Subcanopy Geographies: A Synergistic Multispectral, Hyperspectral, and SAR Paradigm for Forest Ecosystem Dynamics Open
Forest ecosystems are vital for global biodiversity, carbon sequestration, and climate regulation, yet their intricate subcanopy structures remain challenging to accurately characterize using traditional remote sensing methods. This paper …
View article: Synergistic Hyperspectral-SAR Deep Fusion for Fine-Grained Forest Biodiversity Mapping
Synergistic Hyperspectral-SAR Deep Fusion for Fine-Grained Forest Biodiversity Mapping Open
Forest biodiversity is a critical indicator of ecosystem health and provides invaluable ecosystem services. However, accurate and fine-grained mapping of forest biodiversity at large scales remains a significant challenge due to the comple…
View article: Forest reorganization after natural disturbance: a synthesis
Forest reorganization after natural disturbance: a synthesis Open
Forest reorganization after natural disturbance: a synthesis This repository contains all code and data required to reproduce the analyses for the manuscript “Forest reorganization after natural disturbance: a synthesis”, currently under r…
View article: Forest reorganization after natural disturbance: a synthesis
Forest reorganization after natural disturbance: a synthesis Open
Forest reorganization after natural disturbance: a synthesis This repository contains all code and data required to reproduce the analyses for the manuscript “Forest reorganization after natural disturbance: a synthesis”, currently under r…
View article: Challenges in Young Siberian Forest Height Estimation from Winter TerraSAR-X/TanDEM-X PolInSAR Observations
Challenges in Young Siberian Forest Height Estimation from Winter TerraSAR-X/TanDEM-X PolInSAR Observations Open
Accurate estimation of young forest height is essential for assessing the carbon sequestration potential of vast Siberian boreal forests recovering from wildfires. Satellite radar interferometry, particularly PolInSAR, is a promising tool …
View article: Characteristics (mean ± SD) of forest age classes corresponding to each successional stage of secondary tropical dry forest (SDF). Forest age and associated land-use activities were defined according to the multiple-use strategy practiced by Yucatecan Mayan families, as described in references [42,43]*.
Characteristics (mean ± SD) of forest age classes corresponding to each successional stage of secondary tropical dry forest (SDF). Forest age and associated land-use activities were defined according to the multiple-use strategy practiced by Yucatecan Mayan families, as described in references [42,43]*. Open
Characteristics (mean ± SD) of forest age classes corresponding to each successional stage of secondary tropical dry forest (SDF). Forest age and associated land-use activities were defined according to the multiple-use strategy practiced …
View article: S M Nazmuz Sakib Forest Spectral Diversity Index
S M Nazmuz Sakib Forest Spectral Diversity Index Open
Forest structural diversity underpins ecosystem function, resilience, and biodiversity, yet existing metrics often summarize only coarse stand-level attributes such as height distributions , basal area, or spatial point patterns. Recent ad…
View article: Image 2_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 2_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 4_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 4_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 10_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 10_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: S M Nazmuz Sakib Forest Spectral Diversity Index
S M Nazmuz Sakib Forest Spectral Diversity Index Open
Forest structural diversity underpins ecosystem function, resilience, and biodiversity, yet existing metrics often summarize only coarse stand-level attributes such as height distributions , basal area, or spatial point patterns. Recent ad…
View article: Image 5_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 5_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Table 2_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.docx
Table 2_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.docx Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 9_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 9_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Table 1_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.docx
Table 1_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.docx Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 3_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 3_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 7_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 7_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 6_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 6_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 1_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 1_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …
View article: Image 8_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Image 8_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg Open
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables …