Estimating Net Primary Productivity (NPP) and Debris-Fall in Forests Using Lidar Time Series
| Autor: | Tom Scott Smeltz, Mallory Allgeier, Roman J. Dial, Russell Wong, Pierre Chaussé, Thomas Day, Trevor S. Golden, Hans-Erik Andersen |
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| Rok vydání: | 2021 |
| Předmět: |
Canopy
Biomass (ecology) 010504 meteorology & atmospheric sciences Science Taiga 0211 other engineering and technologies Primary production 02 engineering and technology Atmospheric sciences 01 natural sciences Carbon cycle n/a Lidar Forest ecology General Earth and Planetary Sciences Environmental science Coarse woody debris 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
| Zdroj: | Remote Sensing, Vol 13, Iss 891, p 891 (2021) Remote Sensing Volume 13 Issue 5 |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs13050891 |
| Popis: | Temporal series of lidar, properly field-validated, can provide critical information allowing in-ferences about the dynamics of biomass and carbon in forest canopies. Forest canopies gain carbon through net primary production (NPP) and lose carbon through canopy component damage and death, such as fine and coarse woody debris and litterfall (collectively, debris-fall). We describe a statistical method to extract gamma distributions of NPP and debris-fall rates in forest canopies from lidar missions repeated through time and we show that the means of these distributions covary with ecologically meaningful variables: topography, canopy structure, and taxonomic composition. The method employed is the generalized method of moments that applies the R package gmm to uncover the distribution of latent variables. We present an example with eco-logical interpretations that support the method’s application to change in biomass estimated for a boreal forest in southcentral Alaska. The deconvolution of net change from remote sensing products as distributions of NPP and debris-fall rates can inform carbon cycling models of can-opy-level NPP and debris-fall rates. |
| Databáze: | OpenAIRE |
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