Abstract
Abstract. A significant proportion of the uncertainty in climate projections arises from uncertainty in the representation of land carbon uptake. Dynamic global vegetation models (DGVMs) vary in their representations of regrowth and competition for resources, which results in differing responses to changes in atmospheric CO2 and climate. More advanced cohort-based patch models are now becoming established in the latest DGVMs. These models typically attempt to simulate the size distribution of trees as a function of both tree size (mass or trunk diameter) and age (time since disturbance). This approach can capture the overall impact of stochastic disturbance events on the forest structure and biomass – but at the cost of increasing the number of parameters and ambiguity when updating the probability density function (pdf) in two dimensions. Here we present the Robust Ecosystem Demography (RED), in which the pdf is collapsed onto the single dimension of tree mass. RED is designed to retain the ability of more complex cohort DGVMs to represent forest demography, while also being parameter sparse and analytically solvable for the steady state. The population of each plant functional type (PFT) is partitioned into mass classes with a fixed baseline mortality along with an assumed power-law scaling of growth rate with mass. The analytical equilibrium solutions of RED allow the model to be calibrated against observed forest cover using a single parameter – the ratio of mortality to growth for a tree of a reference mass (μ0). We show that RED can thus be calibrated to the ESA LC_CCI (European Space Agency Land Cover Climate Change Initiative) coverage dataset for nine PFTs. Using net primary productivity and litter outputs from the UK Earth System Model (UKESM), we are able to diagnose the spatially varying disturbance rates consistent with this observed vegetation map. The analytical form for RED circumnavigates the need to spin up the numerical model, making it attractive for application in Earth system models (ESMs). This is especially so given that the model is also highly parameter sparse.
Highlights
A key requirement of Earth system science is to estimate how much carbon the land surface will take up in the decades ahead (Ciais et al, 2014)
This paper presents a simplified cohort model – Robust Ecosystem Demography (RED) – which updates the number of trees in each mass class but does not separately track tree age or patch age
In this paper we have presented a new intermediate complexity second-generation dynamic global vegetation model (DGVM), which captures important changes in forest demography
Summary
A key requirement of Earth system science is to estimate how much carbon the land surface will take up in the decades ahead (Ciais et al, 2014). The POP model (Haverd et al, 2014) uses stand-age cohorts as the dimension for population dynamics, every time step applying crowding and resource limited mortality rates. Another example is the ORCHIDEEMICT (Yue et al, 2018), which disaggregates the populations of a PFT into patch cohort functional types, with transitions between cohorts diagnosed when the average basal diameter passes a threshold. Where tree mortality rate can be assumed to be approximately independent of tree mass, the demographic equation yields equilibrium tree-size distributions which follow a Weibull distribution This is sometimes termed demographic equilibrium theory (DET) (see Appendix B). These simplifications significantly reduce the number of free parameters in RED but still enable it to fit forest inventory data in North America (Moore et al, 2018) and South America (Moore et al, 2020)
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