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The Impact of Fine-Scale Disturbances on the Predictability of Vegetation Dynamics and Carbon Flux.

Hurtt GC, Thomas RQ, Fisk JP, Dubayah RO, Sheldon SL - PLoS ONE (2016)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Geographical Sciences, University of Maryland, College Park, MD, United States of America.

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.

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La Selva gridded (1 ha) land-use history classification.Primary denotes natural old-growth vegetation. Secondary denotes vegetation recovering from prior land-use (Organization for Tropical Studies, unpublished data).
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pone.0152883.g001: La Selva gridded (1 ha) land-use history classification.Primary denotes natural old-growth vegetation. Secondary denotes vegetation recovering from prior land-use (Organization for Tropical Studies, unpublished data).

Mentions: A total of 1036 ha were classified as forest, 732 old growth (primary) and 304 recovering (secondary) (Fig 1). The mean CTH across the entire domain (primary and secondary) for 1998 and 2005 was 30.6 ± 0.15 m and 31.4 ± 0.14, respectively (1 SE). The mean CTH for primary and secondary forest in 1998 was 32.6 ± 0.11 m and 25.4 ± 0.30 m (1 SE), respectively. Fig 2 shows a map of mean CTH in 1998 at 1 ha resolution. Fig 3 shows a map of LVIS mean canopy top height change (2005–1998) at 1 ha resolution.


The Impact of Fine-Scale Disturbances on the Predictability of Vegetation Dynamics and Carbon Flux.

Hurtt GC, Thomas RQ, Fisk JP, Dubayah RO, Sheldon SL - PLoS ONE (2016)

La Selva gridded (1 ha) land-use history classification.Primary denotes natural old-growth vegetation. Secondary denotes vegetation recovering from prior land-use (Organization for Tropical Studies, unpublished data).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4836756&req=5

pone.0152883.g001: La Selva gridded (1 ha) land-use history classification.Primary denotes natural old-growth vegetation. Secondary denotes vegetation recovering from prior land-use (Organization for Tropical Studies, unpublished data).
Mentions: A total of 1036 ha were classified as forest, 732 old growth (primary) and 304 recovering (secondary) (Fig 1). The mean CTH across the entire domain (primary and secondary) for 1998 and 2005 was 30.6 ± 0.15 m and 31.4 ± 0.14, respectively (1 SE). The mean CTH for primary and secondary forest in 1998 was 32.6 ± 0.11 m and 25.4 ± 0.30 m (1 SE), respectively. Fig 2 shows a map of mean CTH in 1998 at 1 ha resolution. Fig 3 shows a map of LVIS mean canopy top height change (2005–1998) at 1 ha resolution.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Geographical Sciences, University of Maryland, College Park, MD, United States of America.

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.

Show MeSH
Related in: MedlinePlus