The authors compile the Global Forest Database (ForC) to provide a macropscopic overview of the C cycle in the world’s forests. They compute the mean and standard deviation of 24 flux and stock variables (no soil variables) for mature and regrown (age < 100 years) forests. C cycling rates decrease from tropical to temperate to boreal forests. The majority of flux variables, together with most live biomass pools, increased significantly with the logarithm of stand age.

1. Introduction

  • forests photosynthesize 69 GtC/year, leading to being a C sink accounting for 29% of fossil fuel emissions (problem: deforestation)
  • regrowth (= secondary) forests become increasingly important
  • biomes: categories for different climate and vegetation
  • NEP = GPP - $R_{\text{eco}}$: net ecosystem production = gross primary production - total ecosystem respiration
  • biomass accumulation increases rapidly in young forests, followed by a slow decline to near zero in old forests

2. Methods and design

  • synthesis of many existing databases with the goal of understanding how C cycle varies depending on location and stand age
  • R scripts and manual edits
  • unit dry organic matter converted to C by C=0.47 OM (IPCC, 2018)
  • 4 biome types (tropical broadleaf, temperate broadleaf, temperate needleleaf, boreal needleleaf) and 2 age classes (young, mature)
  • C budget assumed closed if mean of components summed to within one standard deviation of the aggregate variable
  • effect of stand age tested by using mixed effects models
  • logarithmic fit also due to lack of sufficient data to use more parameters

3. Review results and synthesis

  • mature forests:
    • fluxes: tropical > temperate > boreal
    • NEP: no significant trend
    • mean stocks: tropical > temperate > boreal
    • max. stocks in temperate biomes
  • young forests:
    • fluxes and stocks increase with $\log_{10}$ of age
    • fluxes: tropical > temperate > boreal
    • NEP: temperate > boreal

4. Discussion

  • variation in NPP in mature forests less controlled by climate, more by moderate disturbance and $R_{\text{soil}}$ vs C inputs
  • organic layer (OL) highest in boreal forests due to slow decomposition
  • NEP increases for first 100 years
  • future forest C cycling will shape climate (Song et al. 2019, Schimel et al. 2015)
  • ForC contains ground data for variables that cannot be measured (at least directly) remotely, such as respiration fluxes

5. Conclusions

  • loss of biomass from mature forests cannot be recovered on time scales relevant for mitigating climate change
  • conservation of mature forests most important

Ideas

By definition, future projections extend our existing observations and understanding to conditions that do not currently exist on Earth (Bonan and Doney 2018, Gustafson et al 2018, McDowell et al 2018). To ensure that models are giving the right answers for the right reasons (Sulman et al 2018), it is important to benchmark against multiple components of the C cycle that are internally consistent with each other (Collier et al 2018, Wang et al 2018).

What about applying information partitioning to ForC?