syntable | R Documentation |
Synoptic tables summarize previously defined plant community groups, e.g., from cluster analysis, classification methods, or pre-defined strata, such as spatial distribution units. They help identify characteristic species patterns by calculating group-wise percentage/absolute frequencies, mean/median cover, fidelity indices or differential species character.
syntable
calculates synoptic tables from vegetation data and a vector of group identities.
The vegetation data can be provided as a species-sample matrix (default) or as long-format vegetation
data (one row per species occurrence) (long = TRUE
).
The unordered output table can be sorted with synsort
function.
syntable(
vegdata,
groups = NULL,
abund = "percentage",
type = "percfreq",
digits = NULL,
long = FALSE,
group_col = NULL,
phi_method = "default",
phi_standard = "none",
phi_target_size = NULL,
phi_alpha = NULL
)
vegdata |
A data-frame-like object. Either:
Missing values (NA) are converted to 0. If non-numeric abundance values are present, the matrix will be transformed to presence/absence with all non-zero values defined as 1. |
groups |
Group identities for samples. For wide data (default): a vector/factor of length
|
abund |
Type of abundances: percentage cover ( |
type |
Output type. One of |
digits |
Integer indicating the number of decimal places to be displayed in result tables (default 0; for phi 3) |
long |
Logical. If |
group_col |
(Long data only) Optional name of a column
in |
phi_method |
Fidelity measure when |
phi_standard |
Group-size equalization when |
phi_target_size |
Numeric percentage in |
phi_alpha |
Optional significance level for Fisher’s exact test when |
The function returns an (invisible) list of result components.
$syntable |
unordered synoptic table for given species and groups |
$samplesize |
total number of samples per group |
Additionally for differential species character calculation:
$onlydiff |
Synoptic table only with differential species |
$others |
List of non-differential species |
$differentials |
Lists differential species for each group |
For synoptic table calculation, six types are available.
type = "percfreq"
: percentage frequency of occurrence per group (default)
type = "totalfreq"
: absolute frequency (number of plots with presence) per group
type = "mean"
mean cover per group (abund = "percentage"
only)
type = "median"
median cover per group (abund = "percentage"
only)
type = "phi"
species fidelity. The default corresponds to the
binary phi coefficient (= \phi = \frac{u}{\sqrt{N - 1}}
; Sokal & Rohlf 1995, Bruelheide 2000) with values between -1 and 1, expressing the
avoidance or preference of a species for the target site group.
Alternatively, the hypergeometric u
-value (see Chytrý et al., 2002), or the Ochiai coefficient (see de Cáceres et al, 2008) can be selected via phi_method
.
Optional group-size equalization follows Tichý & Chytrý (2006) via phi_standard
and phi_target_size
. A significance level for an optional zero-out of
non-significant cells based on Fisher's exact test can be provided via phi_alpha
.
type = "diffspec"
differential character of species according to
Tsiripidis et al. 2009: p = positive, n = negative, pn = positive-
negative, or none (-). Consider that differential character is always
restricted to some and not necessarily all of the other units, thus considering percentage
frequency is essential for correct interpretation of the diagnostic species character.
Requires \ge 3
groups and is available for wide data only.
For sorting the output synoptic table, use synsort
function, providing several
options.
Friedemann von Lampe, Jenny Schellenberg
Bruelheide, H. (2000): A new measure of fidelity and its application to defining species groups. Journal of Vegetation Science 11: 167-178. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/3236796")}
Chytrý, M., Tichý, L., Holt, J., Botta-Dukat, Z. (2002): Determination of diagnostic species with statistical fidelity measures. Journal of Vegetation Science 13: 79-90. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1654-1103.2002.tb02025.x")}
de Cáceres, M., Font, X., & Oliva, F. (2008). Assessing species diagnostic value in large data sets: A comparison between phi‐coefficient and Ochiai index. Journal of Vegetation Science, 19(6), 779–788. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3170/2008-8-18446")}
Sokal, R.R. & Rohlf, F.J. (1995): Biometry. 3rd edition Freemann, New York.
Tichý, L., & Chytrý, M. (2006). Statistical determination of diagnostic species for site groups of unequal size. Journal of Vegetation Science, 17(6), 809–818. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1654-1103.2006.tb02504.x")}
Tsiripidis, I., Bergmeier, E., Fotiadis, G. & Dimopoulos, P. (2009): A new algorithm for the determination of differential taxa. Journal of Vegetation Science 20: 233-240. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1654-1103.2009.05273.x")}
synsort
## Synoptic table of Scheden vegetation data
library(cluster)
pam1 <- pam(schedenveg, 4) # PAM clustering with 4 clusters output
## 1) Unordered synoptic percentage frequency table
percfreq <- syntable(schedenveg, pam1$clustering, abund = "percentage",
type = "percfreq")
percfreq # view results
## 2) Differential species analysis
differential <- syntable(schedenveg, pam1$clustering, abund = "percentage",
type = "diffspec")
# show complete table with differential character of species
differential$syntable
# list differential species for second cluster
differential$differentials[2]
## 3) Synoptic table with phi fidelity
phitable <- syntable(schedenveg, pam1$clustering, abund = "percentage",
type = "phi")
phitable
## 3b) Hypergeometric u-value and standardisation of group sizes
phiu <- syntable(schedenveg, pam1$clustering, abund = "percentage",
type = "phi", phi_method = "uvalue", phi_standard = "all")
phiu
## 4) Synoptic percentage frequency table based on historical classification from 1997
percfreq <- syntable(schedenveg, schedenenv$comm, abund = "percentage",
type = "percfreq")
percfreq
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