  Relating forest productivity to local variations in forest structure has been
a long-standing challenge. Previous studies often focused on the connection
between forest structure and stand-level photosynthesis (GPP). However, biomass
production (NPP) and net ecosystem exchange (NEE) are also subject to
respiration and other carbon losses, which vary with local conditions and life
history traits. Here, we use a simulation approach to study how these losses
impact forest productivity and reveal themselves in forest structure. We fit
the process-based forest model Formind to a 25ha inventory of an old-growth
temperate forest in China and classify trees as "mature" (full-grown) or
"immature" based on their intrinsic carbon use efficiency. Our results reveal a
strong negative connection between the stand-level carbon use efficiency and
the prevalence of mature trees: GPP increases with the total basal area,
whereas NPP and NEE are driven by the basal area of immature trees.
Accordingly, the basal area entropy - a structural proxy for the prevalence of
immature trees - correlated well with NPP and NEE and had higher predictive
power than other structural characteristics such as Shannon diversity and
height standard deviation. Our results were robust across spatial scales
(0.04-1ha) and yield promising hypotheses field studies and new theoretical
work.
