Abstract
Predictions from forest ecosystem models are limited in part by large uncertainties in the current state of the land surface, as previous disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect. Likewise, future disturbances also present a challenge to prediction as their dynamics are episodic and complex and occur across a range of spatial and temporal scales. While large extreme events such as tropical cyclones, fires, or pest outbreaks can produce dramatic consequences, small fine-scale disturbance events are typically much more common and may be as or even more important. This study focuses on the impacts of these smaller disturbance events on the predictability of vegetation dynamics and carbon flux. Using data on vegetation structure collected for the same domain at two different times, i.e. “repeat lidar data”, we test high-resolution model predictions of vegetation dynamics and carbon flux across a range of spatial scales at an important tropical forest site at La Selva Biological Station, Costa Rica. We found that predicted height change from a height-structured ecosystem model compared well to lidar measured height change at the domain scale (~150 ha), but that the model-data mismatch increased exponentially as the spatial scale of evaluation decreased below 20 ha. We demonstrate that such scale-dependent errors can be attributed to errors predicting the pattern of fine-scale forest disturbances. The results of this study illustrate the strong impact fine-scale forest disturbances have on forest dynamics, ultimately limiting the spatial resolution of accurate model predictions.
Highlights
Forest ecosystem dynamics are characterized by processes of disturbance and recovery across a range of spatial scales, from large catastrophic events including tropical cyclones, fires, and pest outbreaks, to fine-scale forest canopy gap dynamics [1,2,3,4,5,6]
Results of this study suggest that fine-scale forest disturbance events limit the spatial resolution of accurate model predictions
Forest disturbances occur across a wide range of spatial and temporal scales, and are known to influence both the structure and dynamics of forest ecosystems
Summary
Forest ecosystem dynamics are characterized by processes of disturbance and recovery across a range of spatial scales, from large catastrophic events including tropical cyclones, fires, and pest outbreaks, to fine-scale forest canopy gap dynamics [1,2,3,4,5,6]. The spatially and temporally heterogeneous patterns of vegetation structure and fluxes that result from these disturbances present a special challenge to interpretation and prediction [7]. Disturbances episodically alter vegetation structure and create important fluxes of carbon from vegetation to coarse woody. Predictability of Vegetation Dynamics debris, litter, and the atmosphere. Recovery following disturbances tends to restore vegetation structure and carbon over longer time scales (decades to centuries) as vegetation regrows and debris decomposes. The complex spatial pattern from a legacy of past events, together with ongoing and potentially changing future events, presents a challenge for understanding, and for prediction
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