Understanding disturbance regimes from patterns in biomass and primary
productivity
Abstract
Natural and anthropogenic disturbances act as important drivers of tree
mortality, shaping the structure, composition and biomass distribution
of forests. Disturbance regimes may emerge from different
characteristics of disturbance events over time and space. We design a
model- based experiment to investigate the links between disturbance
regimes at the landscape scale and spatial features of biomass patterns.
The effects on biomass of a wide range of disturbance regimes are
simulated by varying three different parameters, i.e. μ (probability
scale), α (clustering degree), and β (intensity slope) that shape the
extent, frequency, and intensity of disturbance events, respectively. A
simple dynamic carbon cycle model is used to simulate 200 years of plant
biomass dynamics in response to circa +2000 different disturbance
regimes, depending on the different combinations of μ, α, and β. Each
parameter combination yields a spatially explicit estimate of plant
biomass for which sixteen synthesis statistics are estimated on the
spatial distributions of biomass, including information-based and
texture features. Based on a multi-output regression approach we link
these synthesis statistics with additional gross primary production
(GPP) constraints to retrieve the three disturbance parameters. In doing
so we evaluate the confidence in inferring disturbance regimes from
spatial distributions of biomass. Our results show that all three
parameters can be confidently retrieved. The Nash-Sutcliffe efficiency
for the prediction of the μ, α, and β is 97.3%, 96.6%, and 97.9%,
respectively. A feature importance analysis reveals that the
distribution statistics dominate the prediction of μ and β, while
features quantifying texture have a stronger connection with α. Overall,
this study clarifies the association between biomass patterns emerging
from different underlying disturbance regimes, while overcoming the
previously found equifinality between mortality rates and total biomass.
Given the links between decadal vegetation dynamics and the
uncertainties in the role of terrestrial ecosystems in the global
biogeochemical cycles, a better understanding and the quantification of
disturbance regimes would improve our current understanding of controls
and feedback at the biosphere-atmosphere interface in the current Earth
system models.