From small-scale forest structure to Amazon-wide carbon estimates

Rödig, Edna; Knapp, Nikolai; Fischer, Rico; Bohn, Friedrich J.; Dubayah, Ralph; Tang, Hao; Huth, Andreas

doi:10.1038/s41467-019-13063-y

Cited by 31 publications

(30 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The importance of the Amazonian basin as one of the largest ecosystems on Earth is extensive, from being the richest region hosting 25% of global biodiversity to being a huge carbon sink that eliminates up to 20% of excess atmospheric carbon and contributes to the biogeochemical functioning of the Earth system 1 – 3 . The Amazon is exposed to different altering factors such as wind blow-downs 4 , droughts 5 , but also deforestation and intensive fires 6 .…”

Section: Introductionmentioning

confidence: 99%

Utilization of the zebrafish model to unravel the harmful effects of biomass burning during Amazonian wildfires

Babić

Čižmek

Maršavelski

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Amazonian wildfires in 2019 have raised awareness about rainforest burning due to increased emissions of particulate matter and carbon. In the context of these emissions, by-products of lignin thermal degradation (i.e. methoxyphenols) are often neglected. Methoxyphenols entering the atmosphere may form intermediates with currently unknown reaction mechanisms and toxicity. This study for the first time provides a comprehensive insight into the impact of lignin degradation products [guaiacol, catechol], and their nitrated intermediates [4-nitrocatechol, 4,6-dinitroguaiacol, 5-nitroguaiacol] on zebrafish Danio rerio. Results revealed 4-nitrocatechol and catechol as the most toxic, followed by 4,6DNG > 5NG > GUA. The whole-organism bioassay integrated with molecular modeling emphasized the potential of methoxyphenols to inhibit tyrosinase, lipoxygenase, and carbonic anhydrase, consequently altering embryonic development (i.e. affected sensorial, skeletal, and physiological parameters, pigmentation formation failure, and non-hatching of larvae). The whole-organism bioassay integrated with in silico approach confirmed the harmful effects of lignin degradation products and their intermediates on aquatic organisms, emphasizing the need for their evaluation within ecotoxicity studies focused on aquatic compartments.

show abstract

Section: Introductionmentioning

confidence: 99%

Utilization of the zebrafish model to unravel the harmful effects of biomass burning during Amazonian wildfires

Babić

Čižmek

Maršavelski

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Early studies used visual interpretation to identify different vegetation types [19], but increased data availability and improved analytical methods now make more sophisticated analyses possible. For example, functional and chemical traits of the forest canopy and carbon stocks of vegetation have been mapped in many parts of Amazonia using airborne and satellite sensors [9][10][11][12][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Mapping Floristic Patterns of Trees in Peruvian Amazonia Using Remote Sensing and Machine Learning

et al. 2020

View full text Add to dashboard Cite

Recognition of the spatial variation in tree species composition is a necessary precondition for wise management and conservation of forests. In the Peruvian Amazonia, this goal is not yet achieved mostly because adequate species inventory data has been lacking. The recently started Peruvian national forest inventory (INFFS) is expected to change the situation. Here, we analyzed genus-level variation, summarized through non-metric multidimensional scaling (NMDS), in a set of 157 INFFS inventory plots in lowland to low mountain rain forests (<2000 m above sea level) using Landsat satellite imagery and climatic, edaphic, and elevation data as predictor variables. Genus-level floristic patterns have earlier been found to be indicative of species-level patterns. In correlation tests, the floristic variation of tree genera was most strongly related to Landsat variables and secondly to climatic variables. We used random forest regression, under varying criteria of feature selection and cross-validation, to predict the floristic composition on the basis of Landsat and environmental data. The best model explained >60% of the variation along NMDS axes 1 and 2 and 40% of the variation along NMDS axis 3. We used this model to predict the three NMDS dimensions at a 450-m resolution over all of the Peruvian Amazonia and classified the pixels into 10 floristic classes using k-means classification. An indicator analysis identified statistically significant indicator genera for 8 out of the 10 classes. The results are congruent with earlier studies, suggesting that the approach is robust and can be applied to other tropical regions, which is useful for reducing research gaps and for identifying suitable areas for conservation.

show abstract

“…For example, one can analyse the influence of microclimate in a forest on carbon dynamics or the influence of speciesspecific water use strategies and how this might affect the water cycle due to changes in interception, precipitation or soil water content [27,67] Individual-based models based on forest inventories including tree size as well as species composition with a species-specific parametrisation enables a transfer to other sites. This approach could also facilitate largescale analysis of carbon flux dynamics on tree level by linking model simulations with remote sensing (e.g., Rödig et al [68]).…”

Section: The Benefit Of Modelling Forest Carbon Fluxesmentioning

confidence: 99%

Carbon Sequestration in Mixed Deciduous Forests: The Influence of Tree Size and Species Composition Derived from Model Experiments

Holtmann

Huth

Pohl

et al. 2021

Forests

Self Cite

View full text Add to dashboard Cite

Forests play an important role in climate regulation due to carbon sequestration. However, a deeper understanding of forest carbon flux dynamics is often missing due to a lack of information about forest structure and species composition, especially for non-even-aged and species-mixed forests. In this study, we integrated field inventory data of a species-mixed deciduous forest in Germany into an individual-based forest model to investigate daily carbon fluxes and to examine the role of tree size and species composition for stand productivity. This approach enables to reproduce daily carbon fluxes derived from eddy covariance measurements (R2 of 0.82 for gross primary productivity and 0.77 for ecosystem respiration). While medium-sized trees (stem diameter 30–60 cm) account for the largest share (66%) of total productivity at the study site, small (0–30 cm) and large trees (>60 cm) contribute less with 8.3% and 25.5% respectively. Simulation experiments indicate that vertical stand structure and shading influence forest productivity more than species composition. Hence, it is important to incorporate small-scale information about forest stand structure into modelling studies to decrease uncertainties of carbon dynamic predictions.

show abstract

From small-scale forest structure to Amazon-wide carbon estimates

Cited by 31 publications

References 53 publications

Utilization of the zebrafish model to unravel the harmful effects of biomass burning during Amazonian wildfires

Utilization of the zebrafish model to unravel the harmful effects of biomass burning during Amazonian wildfires

Mapping Floristic Patterns of Trees in Peruvian Amazonia Using Remote Sensing and Machine Learning

Carbon Sequestration in Mixed Deciduous Forests: The Influence of Tree Size and Species Composition Derived from Model Experiments

Contact Info

Product

Resources

About