Raw species count data file with the following columns; 1)TimePoint is a factor indicating the sequential sampling time point 2)LandscapeType is a factor indicating the microcosm network type (linear or dendritic) 3)LandscapeID is a factor indicating the unique microcosm ID 4)NetworkPair is a factor indicating the Linear/Dendritic network pair - please refer to the publication for details. 5)PatchNumber is a factor indicating the sampling location within the microcosm network - please refer to the publication for details. 6)DateSampled is the date the sampling occurred in dd.mm.yy format 7-21) are the species count numbers for each sampling event with the names corresponding to Table A1 in the publication appendix. (http://www.oikosjournal...
These data represent the observed abundance in 32 reintroduced populations of two native forb specie...
This compiled (zip) file consists of 7 matrices of data: one species data matrix, with abundance obs...
This is the accompanying data and code for the publication [Markovitch & Krasnogor: Predicting Speci...
The BioTIME database contains raw data on species identities and abundances in ecological assemblage...
The table contains 469 variables (columns) recorded and calculated in 32 plots (rows). Column 1: co...
Data on survival of seedlings collected in the field (Müller et al. 2016). Columns: Individual (Iden...
This dataset is in a single Excel file that contains information on the richness and abundance of in...
<p>(a) Number of human observation and preserved specimen records of each species. Species are plott...
<h2>File List</h2><div> <p><a href="morpho_pa.csv">morpho_pa.csv</a> (MD5: ...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
Richness over the study period (1979 to 2008) of colonizing species (see Appendix A for species clas...
species-by-site-matrix-for-cooccurrence-analysis.csv contains the presence-absence forest metacommun...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
These data represent the observed abundance in 32 reintroduced populations of two native forb specie...
This compiled (zip) file consists of 7 matrices of data: one species data matrix, with abundance obs...
This is the accompanying data and code for the publication [Markovitch & Krasnogor: Predicting Speci...
The BioTIME database contains raw data on species identities and abundances in ecological assemblage...
The table contains 469 variables (columns) recorded and calculated in 32 plots (rows). Column 1: co...
Data on survival of seedlings collected in the field (Müller et al. 2016). Columns: Individual (Iden...
This dataset is in a single Excel file that contains information on the richness and abundance of in...
<p>(a) Number of human observation and preserved specimen records of each species. Species are plott...
<h2>File List</h2><div> <p><a href="morpho_pa.csv">morpho_pa.csv</a> (MD5: ...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
Richness over the study period (1979 to 2008) of colonizing species (see Appendix A for species clas...
species-by-site-matrix-for-cooccurrence-analysis.csv contains the presence-absence forest metacommun...
Motivation: The BioTIME database contains raw data on species identities and abundances in ecologica...
These data represent the observed abundance in 32 reintroduced populations of two native forb specie...
This compiled (zip) file consists of 7 matrices of data: one species data matrix, with abundance obs...
This is the accompanying data and code for the publication [Markovitch & Krasnogor: Predicting Speci...