Cite as:
Wallis, C. (2017): <b>Prediction map of ant species richness.</b> <i>Available online ( from DFG-FOR816dw.</i>

Resource Description

Title: Prediction map of ant species richness
Short Name: Ant species richness map
FOR816dw ID: 1655
Publication Date: 2017-09-03
Last Update Date: 2017-09-03
License and Usage Rights: PAK 823-825 data user agreement. (
Temporal Coverage:
Begin: 2014-03-01
End: 2014-12-20
Geographic Coverage:
Geographic Description: San francisco basin
Bounding Coordinates:
- lon/lat [degrees]
- WGS 84
North: Information not publicly available, please log in. Max: 2996.0 ( meter )
West: Information not publicly available, please log in. East: Information not publicly available, please log in. Elevation
South: Information not publicly available, please log in. Min: 1550.0 ( meter )
Dataset Owner(s):
Individual: Christine Wallis
Associated Person(s):
Individual: Jörg Bendix
Individual: David A. Donoso
Individual: Yvonne Tiede
The prediction map identifies the estimated richness of ant species in the mountain rainforest in the San Francisco Valley. The corresponding regression model explained 78% in variation of species richness. Further information about the model and sampled field data are published in Wallis et al. (2017): Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa. doi: 10.1016/j.ecolind.2017.01.022<br/>
| remote sensing | species richness estimate | Partial least-square regression | ants |
Associated entities to this dataset:
-------- 1 . spatial raster entity --------
Raster Name: Prediction map of estimated ant species richness
Tech. Details ...
Attribute(s) ...
Metadata Provider:
Individual: Christine Wallis
Contact Person:
Individual: Christine Wallis
Online Distribution:
Download File:
Data Publisher:
Organization: DFG-FOR816 Data Warehouse - University of Marburg, Department of Geography

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