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Search results for: "keyword:"species richness estimate""

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1-2 of 2 datasets.

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» Tree species - estimated species diversity (Matrix plots) created by: Christine Wallis, Jürgen Homeier (last update: 2017-01-06)

» Prediction map of ant species richness created by: Christine Wallis (last update: 2017-09-03)

Detailed view

Tree species - estimated species diversity (Matrix plots)

Dataset ID:	1545
Last updated:	2017-01-06
Dataset creators:	Christine Wallis Jürgen Homeier
Contact:	Christine Wallis
Temporal coverage:	2007-01-06 00:00:00 - 2008-12-31 00:00:00 - time zone: -5
Geographic coverage:	South Ecuador
Abstract:	All woody plants (including palms and arborescent ... Abstract: All woody plants (including palms and arborescent ferns) with a diameter at breast height (dbh) > 5 cm and a height > 1.3 m were sampled on 50 permanent plots each covering 20 m × 20 m between 2007 and 2008. Species richness was estimated at a coverage of 70% of the expected total species richness using rarefaction and extrapolation. The site scores for the first two dimensions of NMDS ordination analysis were based on Bray-Curtis dissimilarity (presence/absence).
Additional info:	--- Additional info:
Keywords:	\| biodiversity \| species richness estimate \| species turnover \| Community composition \|
DOI:	10.5678/LCRS/PAK823-825.DAT.1545
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

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Entity name:	Tree species diversity matrix plots
Entity type:	dataTable
Attributes:	ID of the plot (PlotID) (Unitless) Total number of species (N_Spec) [Unitless] Total Number of trees (tree_n) [Count] Specified level of sample coverage (sample_coverage) [Percent] Estimated species richness (estimated_N_spec) [Unitless] First axis of NMDS (NMDS1) [Unitless] Second axis of NMDS (NMDS2) [Unitless] Height above mean sea level (geocoordinate_amsl) [Meter] slope (Slope) [Degree] Minimum geographic latitude (geocoordinate_latitude_min) [Degree] Maximum geographic latitude (geocoordinate_latitude_max) [Degree] Minimum geographic longitude (geocoordinate_longitude_min) [Degree] Maximum geographic longitude (geocoordinate_longitude_max) [Degree]

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Prediction map of ant species richness

Dataset ID:	1655
Last updated:	2017-09-03
Dataset creators:	Christine Wallis
Contact:	Christine Wallis
Temporal coverage:	2014-03-01 00:00:00 - 2014-12-20 00:00:00 - time zone: -5
Geographic coverage:	San francisco basin
Abstract:	The prediction map identifies the estimated richne... Abstract: 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
Additional info:	--- Additional info:
Keywords:	\| remote sensing \| species richness estimate \| Partial least-square regression \| ants \|
Intellectual rights:	PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)

Entity name:	Prediction map of estimated ant species richness
Entity type:	spatialRaster (701 x 693)
Attributes:	Species richness (specrich) [Count]

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