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Ecosystem carbon storage capacity as affected by disturbance regimes: A general theoretical model
Ist Teil von
Journal of Geophysical Research, 2012-09, Vol.117 (G3), p.n/a
Ort / Verlag
Washington, DC: Blackwell Publishing Ltd
Erscheinungsjahr
2012
Quelle
Wiley Online Library Journals Frontfile Complete
Beschreibungen/Notizen
Disturbances have been recognized as a key factor shaping terrestrial ecosystem states and dynamics. A general model that quantitatively describes the relationship between carbon storage and disturbance regime is critical for better understanding large scale terrestrial ecosystem carbon dynamics. We developed a model (REGIME) to quantify ecosystem carbon storage capacities (E[x]) under varying disturbance regimes with an analytical solution E[x] = U · τE · , where U is ecosystem carbon influx, τE is ecosystem carbon residence time, and τ1 is the residence time of the carbon pool affected by disturbances (biomass pool in this study). The disturbance regime is characterized by the mean disturbance interval (λ) and the mean disturbance severity (s). It is a Michaelis‐Menten‐type equation illustrating the saturation of carbon content with mean disturbance interval. This model analytically integrates the deterministic ecosystem carbon processes with stochastic disturbance events to reveal a general pattern of terrestrial carbon dynamics at large scales. The model allows us to get a sense of the sensitivity of ecosystems to future environmental changes just by a few calculations. According to the REGIME model, for example, approximately 1.8 Pg C will be lost in the high‐latitude regions of North America (>45°N) if fire disturbance intensity increases around 5.7 time the current intensity to the end of the twenty‐first century, which will require around 12% increases in net primary productivity (NPP) to maintain stable carbon stocks. If the residence time decreased 10% at the same time additional 12.5% increases in NPP are required to keep current C stocks. The REGIME model also lays the foundation for analytically modeling the interactions between deterministic biogeochemical processes and stochastic disturbance events.
Key Points
We developed an analytical model to quantify ecosystem carbon storage
It is a Michaelis‐Menten type equation
It integrates deterministic biogeochemical processes and stochastic disturbances