Information content in time series of litter decomposition studies and the transit time of litter in arid lands
Authors: Sarquis Agustín , Sierra Carlos A. 
Published: May 2023

Abstract. Plant litter decomposition stands at the intersection between
carbon (C) loss and sequestration in terrestrial ecosystems. During this
process organic matter experiences chemical and physical transformations
that affect decomposition rates of distinct components with different
transformation fates. However, most decomposition studies only fit one-pool
models that consider organic matter in litter as a single homogenous pool
and do not incorporate the dynamics of litter transformations and transfers
into their framework. As an alternative, compartmental dynamical systems are
sets of differential equations that serve to represent both the
heterogeneity in decomposition rates of organic matter and the
transformations it can undergo. This is achieved by including parameters for the initial proportion of mass in each compartment, their respective
decomposition rates, and mass transfer coefficients between compartments.
The number of compartments as well as their interactions, in turn,
determine the model structure. For instance, a one-pool model can be considered
a compartmental model with only one compartment. Models with two or more
parameters, in turn, can have different structures, such as a parallel one if each
compartment decomposes independently or in a series if there is mass transfer
from one compartment to another. However because of these differences in
model parameters, comparisons in model performance can be complicated. In
this context we introduce the concept of transit time, a random variable
defined as the age distribution of particles when they are released from a
system, which can be used to compare models with different structures. In
this study, we first asked what model structures are more appropriate to
represent decomposition from a publicly available database of decomposition
studies in arid lands: aridec. For this purpose, we fit one- and two-pool
decomposition models with parallel and series structures, compared their
performance using the bias-corrected Akaike information criterion (AICc) and
used model averaging as a multi-model inference approach. We then asked what
the potential ranges of the median transit times of litter mass in arid lands
are and what their relationships with environmental variables are. Hence, we
calculated a median transit time for those models and explored patterns in the
data with respect to mean annual temperature and precipitation, solar
radiation, and the global aridity index. The median transit time was 1.9 years
for the one- and two-pool models with a parallel structure and 5 years for
the two-pool series model. The information in our datasets supported all
three models in a relatively similar way and thus our decision to use a
multi-model inference approach. After model averaging, the median transit time
had values of around 3 years for all datasets. Exploring patterns of
transit time in relation to environmental variables yielded weak correlation
coefficients, except for mean annual temperature, which was moderate and
negative. Overall, our analysis suggests that current and historical litter
decomposition studies often do not contain information on how litter quality
changes over time or do not last long enough for litter to entirely
decompose. This makes fitting accurate mechanistic models very difficult.
Nevertheless, the multi-model inference framework proposed here can help to
reconcile theoretical expectations with the information content from field
studies and can further help to design field experiments that better
represent the complexity of the litter decomposition process.