Dataset on Woody Aboveground Biomass, Disturbance Losses, and Wood Density from an African Savanna Ecosystem
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| Title: | Main Title: Dataset on Woody Aboveground Biomass, Disturbance Losses, and Wood Density from an African Savanna Ecosystem |
| Descriptions: | Abstract: This dataset comprises raw and processed data from two tree inventories in savanna and savanna woodland vegetation along elephant disturbance gradients in Zambezi Region, Namibia. The recorded individuals represent all age classes and damage levels (including gullivers) and were classified accordingly into nine growth classes. The raw data contains allometric/dendrometric proxies (height, canopy diameters, and stem circumferences for stems > 15cm at the base) which were recorded for n = 6,179 woody individuals in 60 plots (each 0.1 ha). Wood samples were taken to measure specific wood density (SWD) for each recorded species. SWD measurements and raw data have been used to estimate aboveground biomass (AGB) per individual via allometric models.
Existing methodologies and workflows had to be improved to account for damages and diverse vegetation structure as shaped by disturbance impacts. In addition to standing biomass, our proposed method also delivered data on biomass losses to respective disturbance agents (elephants, fire, and others) for each individual. For a subset of tree individuals (n = 288), which fulfilled the minimum requirements to be assessed with conventional methods, the aboveground biomass was re-estimated with a standard procedure to allow for a method comparison.
The processed data comprises living AGB on individual and unit per area basis as determined with two competing methods (conventional vs our proposed). The proposed method further delivered data on pre-disturbance AGB and AGB losses to major disturbance agents. For a description of biomass partitions also see detailed legend within the Data file.
Our research hypothesis was that increasing elephant densities decrease woody aboveground biomass (AGB) and increase elephant-mediated AGB losses along the disturbance gradient. Findings from the data presented here support this hypothesis. Furthermore, increasing elephant densities seem to decrease fire disturbance impacts along the same gradient. These trends can be demonstrated for two different vegetation types (savanna & savanna woodland). A comparison between the conventional standard method and our improved proposed methodology highlights the importance of suitable sampling strategies and protocols for determining biomass and carbon storage in highly disturbed dryland ecosystems. The conventional method over-estimated biomass in large but disturbed trees, while simultaneously under-estimating total biomass on a unit per area basis through omission of all smaller trees, shrubs, and highly damaged woody individuals (gullivers). Table Of Contents: The .xlsx file contains several spreadsheets with the following data tables: - data prop: Data on AGB and AGB losses of n=6,179 individual trees and shrubs as estimated by our proposed method - data conv: Data on AGB as estimated by a conventional method; subset of n=288 trees which were assessable to a conventional method of AGB estimation - specific wood density: Data on SWD measures taken for n=65 species in the dataset - data raw: Raw data of field measurements for n=6,179 individual trees and shrubs - plot coordinates: Geographic location (Lat & Lon) of all 60 plots surveyed |
| Identifier: | 10.17632/3cs85wd3gb.1 (DOI) |
| Related Resource: | Is Previous Version Of Dataset 10.17632/3cs85wd3gb.4 (DOI) |
| Citation Advice: | Kindermann, Liana; Dobler, Magnus; Niedeggen, Daniela; Fabiano, Ezequiel Chimbioputo; Linstädter, Anja (2021), “Dataset on Woody Aboveground Biomass, Disturbance Losses, and Wood Density from an African Savanna Ecosystem”, Mendeley Data, V1, doi: 10.17632/3cs85wd3gb.1 |
Responsible Party
| Creators: | Liana Kindermann (Author), Magnus Dobler (Author), Daniela Niedeggen (Author), Ezequiel Chimbioputo Fabiano (Author), Anja Linstädter (Principal Investigator) |
| Contributors: | Salvation Mahulilo (Data Collector), Jasmin Frietsch (Data Collector), Ekkehard Klingelhoeffer (Contact Person) |
| Funding Reference: | Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 228: Future Rural Africa: Future-making and social-ecological transformation |
| Publisher: | CRC/TRR228 Database (TRR228DB) |
| Publication Year: | 2021 |
Topic
| TRR228 Topic: | Ecology |
| Related Subproject: | A1 |
| Subjects: | Keywords: Biomass, Carbon, Carbon Storage Dynamics, Conservation, Ecology, National Park, Vegetation, Vegetation Structure, Wildlife |
| Geogr. Information Topic: | Biota |
File Details
| Filename: | Data_DiB_final.xlsx |
| Data Type: | Dataset - Dataset |
| File Size: | 1.8 MB |
| Dates: | Available: 27.02.2021 Created: 01.09.2018 (beginning of fieldwork) Other: 31.05.2019 (end of fieldwork) |
| Mime Type: | application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |
| Data Format: | MS Excel (1) |
| Language: | English |
| Status: | Raw Data |
Constraints
| Download Permission: | Free |
| Download Information: | Data can also be downloaded from Mendeley data repository. |
| General Access and Use Conditions: | According to the TRR228DB data policy agreement. |
| Access Limitations: | According to the TRR228DB data policy agreement. |
| Licence: | [Creative Commons] Attribution 4.0 International (CC BY 4.0) |
Geographic
Specific Information - Data
| Temporal Extent: | 01.09.2018, 08:54:00 - 31.05.2019, 08:54:00 |
| Lineage: | This dataset is a subset of the data collected in A01 (Ecology Division) as has been prepared for and used within a publication. Processed biomass data and dendrometric raw data are given on an individual tree level. From raw data presented in one spreadsheet of this file, biomass estimations with two different methods have been calculated (find results in two additional spreadsheets of this same file). Data on specific wood density is given as per-species mean. |
| Subtype: | Natural Science Data |
Metadata Details
| Metadata Creator: | Liana Kindermann |
| Metadata Created: | 02.03.2021 |
| Metadata Last Updated: | 18.01.2022 |
| Subproject: | A1 |
| Funding Phase: | 1 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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Dataset Statistics
| Page Visits: | 128 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 4 |
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Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
