Skip to main content

Constraining rooting depths in tropical rainforests using satellite data and ecosystem modeling for accurate simulation of gross primary production seasonality

Buy Article:

$48.00 plus tax (Refund Policy)

Abstract:

Abstract

Accurate parameterization of rooting depth is difficult but important for capturing the spatio-temporal dynamics of carbon, water and energy cycles in tropical forests. In this study, we adopted a new approach to constrain rooting depth in terrestrial ecosystem models over the Amazon using satellite data [moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI)] and Biome-BGC terrestrial ecosystem model. We simulated seasonal variations in gross primary production (GPP) using different rooting depths (1, 3, 5, and 10 m) at point and spatial scales to investigate how rooting depth affects modeled seasonal GPP variations and to determine which rooting depth simulates GPP consistent with satellite-based observations. First, we confirmed that rooting depth strongly controls modeled GPP seasonal variations and that only deep rooting systems can successfully track flux-based GPP seasonality at the Tapajos km67 flux site. Second, spatial analysis showed that the model can reproduce the seasonal variations in satellite-based EVI seasonality, however, with required rooting depths strongly dependent on precipitation and the dry season length. For example, a shallow rooting depth (1–3 m) is sufficient in regions with a short dry season (e.g. 0–2 months), and deeper roots are required in regions with a longer dry season (e.g. 3–5 and 5–10 m for the regions with 3–4 and 5–6 months dry season, respectively). Our analysis suggests that setting of proper rooting depths is important to simulating GPP seasonality in tropical forests, and the use of satellite data can help to constrain the spatial variability of rooting depth.

Keywords: Amazon; Biome-BGC; MODIS; carbon cycle; gross primary production; remote sensing; rooting depth; seasonal cycle; terrestrial biosphere model; tropical forest; vegetation index

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-2486.2006.01277.x

Affiliations: 1: Ecosystem Science and Technology Branch, NASA Ames Research Center, San Jose State University, Mail Stop 242-4, Moffett Field, CA 94035, USA, 2: Ecosystem Science and Technology Branch, NASA Ames Research Center, California State University at Monterey Bay, Mail Stop 242-4, Moffett Field, CA 94035, USA, 3: Department of Watershed Science, Utah State University, Logan, UT 84322-5210, USA, 4: Ecosystem Science and Technology Branch, NASA Ames Research Center, Mail Stop 242-4, Moffett Field, CA 94035, USA, 5: Department of Earth and Planetary Sciences and Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA, 6: Department of Soil, Water, and Environmental Science, University of Arizona, Tuscon, AZ 85721, USA, 7: Department of Geography and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA

Publication date: January 1, 2007

bsc/gcb/2007/00000013/00000001/art00006
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more