Data from: Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

1.State-and-transition simulation models (STSMs) provide a general
framework for forecasting landscape dynamics, including projections of
both vegetation and land-use/land-cover (LULC) change. The STSM method
divides a landscape into spatially-referenced cells and then simulates the
state of each cell forward in time, as a discrete-time stochastic process
using a Monte Carlo approach, in response to any number of possible
transitions. A current limitation of the STSM method, however, is that all
of the state variables must be discrete. 2.Here we present a new approach
for extending a STSM, in order to account for continuous state variables,
called a state-and-transition simulation model with stocks and flows
(STSM-SF). The STSM-SF method allows for any number of continuous stocks
to be defined for every spatial cell in the STSM, along with a suite of
continuous flows specifying the rates at which stock levels change over
time. The change in the level of each stock is then simulated forward in
time, for each spatial cell, as a discrete-time stochastic process. The
method differs from the traditional systems dynamics approach to
stock-flow modelling in that the stocks and flows can be
spatially-explicit, and the flows can be expressed as a function of the
STSM states and transitions. 3.We demonstrate the STSM-SF method by
integrating a spatially-explicit carbon (C) budget model with a STSM of
LULC change for the state of Hawai'i, USA. In this example,
continuous stocks are pools of terrestrial C, while the flows are the
possible fluxes of C between these pools. Importantly, several of these C
fluxes are triggered by corresponding LULC transitions in the STSM. Model
outputs include changes in the spatial and temporal distribution of C
pools and fluxes across the landscape in response to projected future
changes in LULC over the next 50 years. 4.The new STSM-SF method allows
both discrete and continuous state variables to be integrated into a STSM,
including interactions between them. With the addition of stocks and
flows, STSMs provide a conceptually simple yet powerful approach for
characterizing uncertainties in projections of a wide range of questions
regarding landscape change.