DENDROECOLOGY OF NCRN TREES
Sector: Commercial • Location: United States of America
Source: Grants.gov
The National Capital Region Network (NCRN) monitors 425 permanent forest vegetation plots, distributed among 11 park units. Stand age is generally not known for these plots, which has complicated the interpretation of monitoring data. The measurement goals of this project are to (1) estimate stand age at each of the long-term monitoring plots and (2) generate a record of the historical pattern of
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | archived |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | The National Capital Region Network (NCRN) monitors 425 permanent forest vegetation plots, distributed among 11 park units. Stand age is generally not known for these plots, which has complicated the interpretation of monitoring data. The measurement goals of this project are to (1) estimate stand age at each of the long-term monitoring plots and (2) generate a record of the historical pattern of tree growth as recorded by tree rings. Analysis of these data will focus on building models of tree growth based on (1) community composition and estimates of competition, (2) climate variables related to growing season length and precipitation timing, and (3) remote sensing observations of vegetation cover. From these models, we expect to gain a better understanding of the sensitivity of tree growth to climate, disturbance, and long-term successional processes. Eight common species will be included in the study, affording the opportunity to compare across the most dominate species in the parks, and summarize their historic growth patterns and potential for future growth. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
