A data frame of 72 woody and herbaceous plant species recorded across 92 sample plots in a Mediterranean forest / maquis ecosystem. Species abundances follow a cover-abundance scale (1–9). Taxonomic classification includes seven ranks from species to kingdom.
Format
A data frame with 1545 rows and 9 columns:
- Site
Sample plot identifier,
plot_01–plot_92(character)- Species
Binomial species name with underscore separator (character)
- Genus
Genus (character)
- Family
Family (character)
- Order
Order (character)
- Class
Class (character)
- Phylum
Phylum / Division (character)
- Kingdom
Kingdom (character)
- Abundance
Cover-abundance value, integer 1–9 (numeric)
Details
The data originate from a plot-based vegetation survey. Each of the
92 plots (plot_01–plot_92) records the cover-abundance
of the species present, yielding 1545 species-by-plot observations.
Per-plot richness ranges from 7 to 30 species (mean approximately 17).
Taxonomic coverage: 92 plots, 72 species, 66 genera, 32 families, 20 orders, 4 classes (Magnoliopsida, Liliopsida, Pinopsida, Polypodiopsida), all within Tracheophyta (Plantae).
This dataset can be used directly with batch_analysis
for multi-site analysis:
batch_analysis(med_forest)To extract a single plot for use with ozkan_pto or
compare_indices:
See also
batch_analysis for multi-site analysis,
anatolian_trees for a smaller multi-site example,
campus_comm and campus_gytk for a
single-community example.
Examples
data(med_forest)
head(med_forest)
#> Site Species Genus Family Order
#> 1 plot_01 Arbutus_andrachne Arbutus Ericaceae Ericales
#> 2 plot_01 Asparagus_acutifolius Asparagus Asparagaceae Asparagales
#> 3 plot_01 Ceratonia_siliqua Ceratonia Fabaceae Fabales
#> 4 plot_01 Cistus_creticus Cistus Cistaceae Malvales
#> 5 plot_01 Cotinus_coggygria Cotinus Anacardiaceae Sapindales
#> 6 plot_01 Crataegus_monogyna Crataegus Rosaceae Rosales
#> Class Phylum Kingdom Abundance
#> 1 Magnoliopsida Tracheophyta Plantae 4
#> 2 Liliopsida Tracheophyta Plantae 4
#> 3 Magnoliopsida Tracheophyta Plantae 5
#> 4 Magnoliopsida Tracheophyta Plantae 5
#> 5 Magnoliopsida Tracheophyta Plantae 4
#> 6 Magnoliopsida Tracheophyta Plantae 4
length(unique(med_forest$Site)) # 92 plots
#> [1] 92
length(unique(med_forest$Species)) # 72 species
#> [1] 72
# Single plot extraction
plot1 <- med_forest[med_forest$Site == "plot_01", ]
comm <- setNames(plot1$Abundance, plot1$Species)
tax <- plot1[, c("Species", "Genus", "Family", "Order",
"Class", "Phylum", "Kingdom")]
ozkan_pto(comm, tax)
#> taxdiv -- Ozkan pTO Result
#>
#> All levels:
#> uTO : 11.42649
#> TO : 16.21376
#> uTO+ : 11.62039
#> TO+ : 16.40788
#>
#> Max informative level (level 4):
#> uTO_max : 11.42649
#> TO_max : 16.21376
#> uTO+_max : 11.62039
#> TO+_max : 16.40788
#>
#> Deng entropy by level:
#> Species: 3.091042
#> Genus: 3.091042
#> Family: 3.354025
#> Order: 3.810515
#> Class: 11.95889
#> Phylum: 0
#> Kingdom: 0
# \donttest{
# Multi-site analysis (reduce n_iter for a quick run)
batch_analysis(med_forest, n_iter = 100)
#> taxdiv -- Batch Analysis
#> Sites: 92
#> Indices: 14
#>
#> Site N_Species Shannon Simpson Delta Delta_star AvTD VarTD
#> plot_01 22 3.048622 0.950311 4.005360 4.172214 4.147186 0.402579
#> plot_02 22 2.969729 0.943577 4.032364 4.230320 4.147186 0.402579
#> plot_03 30 3.248865 0.956706 4.111555 4.262678 4.252874 0.450997
#> plot_04 16 2.649498 0.923704 4.037203 4.322106 4.208333 0.548264
#> plot_05 20 2.803143 0.931855 3.960876 4.201103 4.047368 0.413546
#> plot_06 19 2.784268 0.932742 4.023740 4.268472 4.175439 0.682672
#> plot_07 20 2.847504 0.935402 4.107951 4.345416 4.257895 0.454543
#> plot_08 26 3.088315 0.948624 3.994431 4.172827 4.036923 0.509406
#> plot_09 25 3.020219 0.944515 4.078507 4.279541 4.060000 0.489733
#> plot_10 22 2.924331 0.940329 4.086189 4.305252 4.277056 0.486010
#> uTO TO uTO_plus TO_plus uTO_max TO_max uTO_plus_max TO_plus_max
#> 11.42649 16.21376 11.62039 16.40788 11.42649 16.21376 11.62039 16.40788
#> 11.04168 15.82918 11.62039 16.40788 11.04168 15.82918 11.62039 16.40788
#> 11.63946 16.42695 12.45736 17.24486 11.63946 16.42695 12.45736 17.24486
#> 10.27902 15.06652 10.63379 15.42128 10.27902 15.06652 10.63379 15.42128
#> 10.40382 15.19131 11.06113 15.84862 10.42505 15.21254 11.13597 15.92346
#> 10.30577 15.09326 10.50537 15.29286 10.50143 15.28892 10.86950 15.65699
#> 10.77870 15.56619 11.42499 16.21248 10.82023 15.60773 11.47943 16.26693
#> 10.50674 15.29423 11.21123 15.99872 10.66086 15.44836 11.38966 16.17715
#> 10.72225 15.50975 11.29581 16.08330 10.77619 15.56369 11.34324 16.13073
#> 10.79208 15.57957 11.53628 16.32377 10.79208 15.57957 11.53628 16.32377
#> ... ( 92 sites total)
# }