The importance of forest structure for carbon fluxes of the Amazon rainforest

Abstract

Precise descriptions of forest productivity, biomass, and structure are essential for understanding ecosystem responses to climatic and anthropogenic changes. However, relations between these components are complex, in particular for tropical forests.We developed an approach to simulate carbon dynamics in the Amazon rainforest including around 410 billion individual trees within 7.8 million km 2 . We integrated canopy height observations from space-borne LIDAR in order to quantify spatial variations in forest state and structure reflecting small-scale to large-scale natural and anthropogenic disturbances.Under current conditions, we identified the Amazon rainforest as a carbon sink, gaining 0.56 GtC per year. This carbon sink is driven by an estimated mean gross primary productivity (GPP) of 25.1 tC ha −1 a −1 , and a mean woody aboveground net primary productivity (wANPP) of 4.2 tC ha −1 a −1 . We found that successional states play an important role for the relations between productivity and biomass. Forests in early to intermediate successional states are the most productive, and woody above-ground carbon use efficiencies are non-linear. Simulated values can be compared to observed carbon fluxes at various spatial resolutions (>40 m). Notably, we found that our GPP corresponds to the values derived from MODIS. For NPP, spatial differences can be observed due to the consideration of forest successional states in our approach.We conclude that forest structure has a substantial impact on productivity and biomass. It is an essential factor that should be taken into account when estimating current carbon budgets or analyzing climate change scenarios for the Amazon rainforest.

Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model

“…The tropical evergreen forest of Amazonia holds 34% of terrestrial carbon stocks and makes up a significant fraction of the global carbon sink (Beer et al, 2010;Pan et al, 2011;Rödig et al, 2018). Improved model representation of the region's carbon and water fluxes is important if we are to assess their ongoing and future changes (Fu et al, 2013;Peñuelas & Filella, 2009;Wright et al, 2017).…”

The enigma of the Amazonian carbon balance

“…In most existing LSMs, a strong positive linear relation between NPP and AGB emerges in the forest of the Amazon basin that is not observed in the inventory plots (Johnson et al 2016). Rödig et al (2018) show that when successional stages and individual tree mortality from, for example self-thinning, are incorporated, the model is able to simulate a bell-shaped relation between ANPP and AGB with an optimum of potential ANPP at an AGB of 250 Mg C ha −1 , similar to what is observed in inventory plots.…”

“…Furthermore, other mechanisms that influence tree growth and survival such as soil phosphorus acquisition, storm damage, droughts, fires and deforestation, all deserve a place in future LSMs but have also proven to be notoriously difficult to incorporate into predictive models. This is the point where Rödig et al (2018) enter the stage. The authors incorporated a LIDAR derived canopy height map of the entire Amazon basin into a numerical model that simulates individual tree growth.…”

A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region

“…Recent efforts aiming at improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters (such as τ and Vcmax) have found that using single values for key parameters limits simulation 15 accuracy (Castanho et al, 2013). Thus, we conclude that a more mechanistic representation of the processes driving the spatial variability of carbon stocks and fluxes, forest structure and tree demographic dynamics is necessary to improve simulation accuracy (Rödig et al, 2018).…”