4.7 Article

Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie-Ames-Stanford approach (CASA) model

Journal

ENVIRONMENTAL RESEARCH LETTERS
Volume 11, Issue 7, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/11/7/075004

Keywords

aboveground net primary productivity; CASA; secondary tropical dry forests

Funding

  1. Inter-American Institute for Global Change Research (IAI) by National Science Foundation of the United States [CRN3 025, GEO-1128040]
  2. National Science and Engineering Research Council of Canada (NSERC)

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Although tropical dry forests (TDFs) cover roughly 42% of all tropical ecosystems, extensive deforestation and habitat fragmentation pose important limitations for their conservation and restoration worldwide. In order to develop conservation policies for this endangered ecosystem, it is necessary to quantify their provision of ecosystems services such as carbon sequestration and primary production. In this paper we explore the potential of the Carnegie-Ames-Stanford approach (CASA) for estimating aboveground net primary productivity (ANPP) in a secondary TDF located at the Santa Rosa National Park (SRNP), Costa Rica. We calculated ANPP using the CASA model (ANPP(CASA)) in three successional stages (early, intermediate, and late). Each stage has a stand age of 21 years, 32 years, and 50+ years, respectively, estimated as the age since land abandonment. Our results showed that the ANPP(CASA) for early, intermediate, and late successional stages were 3.22 Mg C ha(-1) yr(-1), 8.90 Mg C ha(-1) yr(-1), and 7.59 Mg C ha(-1) yr(-1), respectively, which are comparable with rates of carbon uptake in other TDFs. Our results indicate that key variables that influence ANPP in our dry forest site were stand age and precipitation seasonality. Incident photosynthetically active radiation and temperature were not dominant in the ANPP(CASA). The results of this study highlight the potential of the use of remote sensing techniques and the importance of incorporating successional stage in accurate regional TDF ANPP estimation.

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