Wrappers for the unconstrained ordination methods principal components
analysis (PCA), correspondence anslysis (CA), and principal coordinates
analysis (PCO) are now available via pca()
, ca()
, and pco()
respectively. The underlying methods used are rda()
, cca()
and dbrda()
respectively. See
#655.
The output from the ordination methods pca()
, pco()
, ca()
,
rda()
, cca()
, capscale
, and dbrda()
has changed slightly to
better separate the results from notifications to the user about
issues encountered with the data or the model. Related to changes in
#682.
The constrained ordination functions are now louder at informing users when one or more terms in a model are aliased (linearly dependent) and their effects cannot be estimated. See #682.
cca
and rda
return centroids for factor levels even when they
are called without formula, for instance, as cca(dune, dune.env)
.
plot.cca
retains default graphical settings also when only one set
of scores was displayed.
ordiplot
did not pass character size (cex
) to plot.cca
. Version
2.7-0 has more extensive changes, but this fixes the immediate issue
#656.
adonis2()
now defaults to running an omnibus test of the model
(by = NULL
) instead of a sequential test of model terms (by =
"terms"
). This makes adonis2()
more consistent with the default
for related ordination methods. See
#677.
decorana
checks now that input data are numeric instead of
confusing error message (see
https://stackoverflow.com/questions/78666646/).
make.cepnames
no longer splits names by hyphen: Capsella
bursa-pastoris used to be Capspast
but now is Capsburs
.
dbrda
failed in rare cases when an ordination component had only
negative eigenvalues. Issue
#670.
plot.cca
: biplot or regression arrows were not nicely scaled and
drew no arrows when displayed as the only item in graph.
ordipointlabel
failed with decorana
result. Bounding box for
text could be wrongly estimated with varying values of cex
.
vegdist
with argument na.rm = TRUE
still failed with missing
values. Dissimilarity methods "chisq"
(Chi-square distance) and
"mahalanobis"
did not implement na.rm = TRUE
. Even when missing
values are removed in calculation, dissimilarities may contain NA
depending on the number and pattern of missing values and
dissimilarity method.
decostand
standardization method "clr"
did not implement
na.rm = TRUE
(issue #661).
Standardization methods "rank"
and "rrank"
did not retain NA
values but changed them to 0. Original NA
values are kept in
decostand
, but with na.rm = TRUE
they are ignored when
transforming other data values.
metaMDS
: half-change scaling failed when maxdist
was fixed, but
was not 1.
summary.ordihull
(and hence ordiareatest
for convex hulls)
failed if input had more than two dimensions.
simulate.rda
failed with univariate response.
vegemite
returned only the last page of multi-page table in its
(invisible) return object.
do_wcentre
(weighted centring) can segfault due to a
protection error. The problem was found in automatic CRAN
checks. do_wcentre
is an internal function that is called from
envfit
(vectorfit
), wcmdscale
and varpart
(simpleCCA
)
Fixes bug #653.vegan depends on R version 4.1.0.
It is possible to build vegan with webR/wasm Fortran compiler. Issue #623.
Permutation tests for CCA were completely redesigned to follow C.J.F ter Braak & D.E. te Beest: Environ Ecol Stat 29, 849–868 (2022) (https://doi.org/10.1007/s10651-022-00545-4). The constraints are now re-weighted for the permuted response data, and in partial model they are also residualized by conditions (partial terms). In vegan (after release 2.4-6) the tests were identical to Canoco, but ter Braak & te Beest demonstrated that the results are biased. In old vegan (release 2.4-2 and earlier) the predictors were re-weighted but not residualized. Re-weighting was sufficient to remove bias with moderate variation of weights, but residualizing of predictors is necessary with strongly varying weights. See discussion in issue #542. The new scheme only concerns CCA which is a weighted method, and RDA and dbRDA permutation is unchanged.
summary
of ordination results no longer prints ordination scores
that often are so voluminous that they hide the real summary; see issue
#203. Ordination
scores should be extracted with scores
function. This breaks some
CRAN packages that use summary.cca
to extract scores. These should
switch to use scores
. The maintainers have been contacted and
patch files are suggested to adapt to this change. See
instructions
to fix the packages.
scores
function for constrained ordination (CCA, RDA,dbRDA)
default to return all types of scores (display = "all"
). Function
can optionally return a single type of scores as a list of one matrix
instead of returning a matrix (new argument droplist
).
Constrained ordination objects (cca
, rda
, dbrda
) fitted
without formula interface can have permutation tests (anova
) by
"axis"
and by "onedf"
. Models by "terms"
and "margin"
are only
possible with formula interface.
Permutation tests for constrained ordination objects (cca
, rda
,
dbrda
) with by = "axis"
stop permutations of later axis once the
cutoff
limit is reached. Earlier cutoff
had to be exceeded. The
default is to stop permutations once P-value 1 is reached. The
analysis takes care that P-values of axes are non-decreasing
similarly as in Canoco.
Coefficients of effects in prc
models are scaled similarly as they
were scaled in vegan pre 2.5-1. The change was suggested by
Cajo ter Braak.
Handling of negative eigenvalues was changed in the summary
of
eigenvals
. Negative eigenvalues are given as negative
"explanation", and the accumulated proportions add up over 1 for the
last non-negative eigenvalue, and 1 for the last negative
eigenvalue.
The printed output of capscale
shows proportions for real
components only and ignores imaginary dimensions. This is consistent
to summary
and other support methods. Issue
#636.
RsquareAdj
of capscale
is based only on positive eigenvalues,
and imaginary components are ignored.
stressplot.dbrda
refuses to handle partial models. Only the first
component of variation can be displayed because dbrda
internal
("working") data structures are not additive. For unconstrained
model "CA"
, for constrained "CCA"
and for partial none.
predict
for dbrda
will return the actual
type = "working"
. Earlier it returned "lc"
scores weighted by
eigenvalues. Both generated same distances and eigenvalues, though.
Parallel processing was inefficiently implemented and could be
slower than non-parallel in permutation tests for constrained
ordination and adonis2
.
plot
and scores
for cca
and rda
family of methods gave an
error when non-existing axes were requested. Now ignores requests to
axes numbers that are higher than in the result object.
summary
of prc
ignored extra parameters (such as const
).
Over-fitted models with high number of aliased variables caused a
rare failure in adonis2
and permutation tests of constrained
ordination methods (cca
, rda
, dbrda
, capscale
) with
arguments by = "margin"
or by = "axis"
. This also concerned
vif.cca
and intersetcor
. Typically this occurred with high-order
interactions of factor variables. See issues
#452 and
#622
Some methods accept rectangular raw data input as alternative to
distances, but did not pass all arguments to distance
functions. These arguments in vegdist
could be binary = TRUE
or
pseudocount
with Aitchison distance. This concerns dbrda
,
capscale
and bioenv
. See issue
#631
simper
gave arbitrary p-values for species that did not occur in
a subset. Now these are given as NA
. See
https://stackoverflow.com/questions/77881877/
Rsquare.adj
gave arbitrary p-values for over-fitted models with
no residual variation. Now returns NA
when R2 cannot
be adjusted. Automatic model building could proceed to such cases,
and this was fixed in ordiR2step
which returns R2 = 0
for overfitted cases. The constrained ordination methods issue a
warning if the model has no residual component. See issue
#610
inertcomp(..., display = "sites", proportional = TRUE)
gave wrong
values.
adonis
is deprecated: use adonis2
. There are several CRAN
packages that still use adonis
although we have contacted all
their authors in June 2022 and again in April 2024, and printed a
message of forthcoming deprecation since vegan 2.6-2. See issue
#523. See
instructions
to adapt your packages and functions to use adonis2
.
orditkplot
was moved to CRAN package vegan3d and is deprecated
in vegan. See issue
#585 and
announcement
#632
The use of summary
to extract ordination scores is deprecated: you
should use scores
to extract scores. This version still allows
extracting scores with summary
, but this will fail in next
versions. For summary.cca
see
instructions
to change your package.
Support was removed from ancient cca
objects (results of cca
,
rda
, dbrda
or capscale
) generated before CRAN release 2.5
(2016). If you still have such stray relics, use
newobject <- update(ancientobject)
to modernize the result.
as.mcmc.oecosimu
and as.mcmc.permat
are defunct: use toCoda
.
Code of defunct functions was completely removed.
Support of scores
for
ggplot2 graphics is
improved and extended for ordination functions. Suitable scores can be
requested with argument tidy = TRUE
, and in general all available
types of scores are returned in a data frame with variable score
labelling the type. The option was implemented in default method of
scores
and for structured wcmdscale
objects, and glitches were
fixed for rda
family and decorana
. Previously tidy
scores were
implemented for cca
, rda
, dbrda
family of methods, metaMDS
,
envfit
and rarecurve
.
adonis2
and anova
for constrained ordination results can perform a
sequential test of one-degree-of-freedom effects where multi-level
factors are split to their contrasts. Previously the test was
available only in permutest
.
New summary
function for varpart
for a brief overview. The summary
shows unique and overall contributed variation for each set of
variables. The fractions shared by several sets of variables are
divided equally with all contributing sets following Lai J, Zou Y,
Zhang J, Peres-Neto P (2022) Methods in Ecology and Evolution, 13:
782–788.
decorana
estimates orthogonalized eigenvalues and the total inertia
(scaled Chi-square). Orthogonalized eigenvalues can add up to the
total inertia. Together these enabled implementing eigenvals
,
bstick
and screeplot
methods for decorana
.
Axis lengths are reported for all decorana
methods.
Implemented tolerance
method for decorana
. This returns the
criterion that was used in rescaling DCA, and can be used to inspect
the success of rescaling: it should be constant 1 over the whole axis.
New toCoda
function to transform sequential null model results
from oecosimu
to an object that can be analysed with
coda for convergence
and independence as an MCMC model. Function replaces
as.mcmc.oecosimu
and as.mcmc.permat
.
metaMDS
is more informative about finding similar repeated results
with random starts and uses less confusing language when reporting the
results.
Hellinger distance is directly available in vegdist
.
vegdist
, betadiver
and raupcrick
set attribute maxdist
giving
the numeric value of theoretical maximum of the dissimilarity index.
For many dissimilarities this is 1, but √2 for Chord and
Hellinger distances, for instance. The attribute is NA
for open
indices that do not have such a ceiling. betadiver
has three
similarity indices and these set maxdist
0.
metaMDS
defaults to halfchange scaling when the dissimilarities have
a numeric maxdist
attribute, and adapt the threshold to the ceiling
value. For open indices without ceiling, the threshold will be in the
scale of dissimilarities. metaMDS
used a simple test to detect index
ceiling 1, but the test is now more robust and can also find other
maximum values. If such inference is made, the function will broadcast
a message of assumed value of the ceiling.
Mountford index in vegdist
is now scaled to maximum value log(2).
Earlier Mountford distances were scaled to maximum 1.
hatvalues
of constrained ordination objects can sometimes be
practically 1 or above 1, but now these cases will be exactly 1. In
those cases rstandard
, rstudent
and cooks.distance
will be
NaN
. The behaviour is similar as in stats::lm.influence
functions.
as.rad
can handle multi-row data frames or matrices and return a
list of Rank-Abundance data for each row. Earlier only one site was
handled.
decostand
returns attribute parameters
of settings and variables
used in standardization. New function decobackstand
can use
parameters
to reconstruct original non-standardized data.
Back-transformation is not exact but has round-off errors, although
there is an attempt to keep original zeros exact. Back-transformation
is not possible for methods pa
, rank
and rrank
and it is not
implemented for alr
. Back-transformation queried in
https://stackoverflow.com/questions/73263526/
Rarefaction and rarefaction-based methods make sense only with
original observed counts and give misleading results if data are
multiplied or rare species are removed. Observed counts usually have
singletons (species with count one), and these method issue a
warning if minimum count is higher than one (which may be a false
positive, but inspect your data). Concerns functions rarefy
,
drarefy
, rrarefy
, rarecurve
,
specaccum(..., method="rarefy")
, rareslope
and avgdist
.
See github
discussion #537.
avgdist
exposes as.dist
arguments and can return "dist"
ance
objects that appear as lower triangles instead of appearing as
symmetric matrices.
betadisper
plots accept col
argument
(PR #300).
decorana
returned wrong results when Hill's piecewise transformation
(arguments before
/after
) were used, unless downweighting was also
used.
scores
failed when metaMDS
result had no species scores. Bug was
introduced in release 2.6-2. Issue raised in
https://stackoverflow.com/questions/72483924/
tolerance.cca
failed when only one axis (choice
) was requested.
decostand(..., method="alr")
did not accept name as a reference
,
and could fail in some cases.
CRAN package proxy interfered with simper
and caused an
obscure error (github issue
#528).
adonis
is on way to deprecation. Use adonis2
instead.
as.mcmc.oecosimu
and as.mcmc.permat
were deprecated: these could
not be used as S3 methods without depending on coda package. Use
toCoda
instead.
Compiled code is adapted to the changes in R 4.2.0. See issues #447, #507.
Cross-references to function in other packages were adapted to more stringent tests in CRAN
Aitchison and robust Aitchison distances were added to vegdist
.
Similar data transformations were added to decostand
.
Several functions can return “tidy” data structures that can be used
in ggplot2 graphics: rarecurve
, scores
functions for constrained
ordination (cca
etc.), decorana
, envfit
, metaMDS
.
scores.envfit
gained argument arrow.mul
. vegan plot
functions
used this automatically, but now it is easier to use envfit
in
non-vegan plotting.
Added function simpson.unb
for unbiased Simpson diversity that is
more robust to the variation in sample sizes.
diversity
gained argument group
to calculate indices for pooled
data. Discussed in issue
#393.
simper
is much faster even though parallel processing is not
implemented in the new code.
pairs
function was added to plot permustats
variables against each
other.
varpart
accepts dissimilarities given as a symmetric square matrix
instead of "dist"
object per wish of issue
#497.
metaMDS
adopted a more user-friendly policy, and trymax
will
always be the maximum number of tries. See dicussion in
https://stackoverflow.com/questions/66748605/.
adonis2
accepts strata
. adonis2
is the new main function that
replaces old adonis
. See issue
#427.
Fisher alpha (fisherfit
) is badly suited for extreme communities
that do not follow Fisher's model. Now fisherfit
returns NA
to
communities that have 0 or 1 species, and issues a warning with
communities consisting of singletons and having extreme Fisher alpha.
adipart
and multipart
formulae will automatically add unique id
and and constant. This will always sandwich the requested grouping
between alpha and gamma diversities, but not change the results for
requested groupings.
anova
function failed in marginal tests when constrained partial
ordination model (cca
, rda
etc.) had interaction terms. Issue
#463.
Constrained ordination (cca
etc.) gave misleading results when all
external variables (constraints, condition) were constant and
explained nothing.
decorana
could fail when some axes had zero eigenvalues. Issue
#401.
Species accumulation (specaccum
) failed when there was only one
species, but several “communities”. Issue
#501.
Parallel processing failed in Windows or with socket clusters in
permutest
of betadisper
. Issue
#369.
orditorp
failed if numeric labels were supplied. Reported in
https://stackoverflow.com/questions/69272366/.
Argument summarize
was accidentally dropped from goodness.cca
in
2017.
taxa2dist
failed if there was only one usable taxonomic level. See
https://stackoverflow.com/questions/67231431/.
Function adonis2
will replace adonis
.
humpfit
functions are defunct and removed. They are available in
non-CRAN package natto at https://github.com/jarioksa/natto.
commisimulator
is defunct. Use simulate
for nullmodel
objects.
permuted.index
is finally defunct (it was deprecated in vegan
2.2-0).
as.mlm
is defunct. Use functions documented with influence.cca
,
such as hatvalues.cca
, rstandard.cca
, rstudent.cca
,
cooks.distance.cca
and others.
Several distance-based functions failed if all distances were zero
(betadisper
, capscale
, isomap
, monoMDS
, pcnm
, wcmdscale
).
Reported in github issue
#372.
Non-linear self-starting regression models SSarrhenius
, SSgitay
,
SSgleason
and SSlomolino
failed in future R. The failure was
caused by internal changes in R-devel. Github issue
#382.
Arrow labels were in wrong position in plot.envfit(..., add =
FALSE)
.
rarecurve
added unnecessary names to the results. Github issue
#352.
permutest
for betadisper
failed in parallel processing in Windows
and in other systems when socket clusters were used. Github issue
#369.
Chi-square and Chord distances were added to vegdist
. Both of these
distances can be calculated as Euclidean distances of transformed
data, and actually were available earlier, but many users did not
notice this.
monoMDS
(and hence metaMDS
) uses stricter convergence criteria.
This improves possibilities to find stable solutions. However, users
may still need to tweak convergence criteria with their data. See
discussion in Github issue
#354.
text
functions for constrained ordination plots (cca
, rda
,
dbrda
, capscale
) accept now expression labels. This allows using
subscripts, superscripts and mathematical expressions. New support
function labels.cca
returns the current text labels so that authors
can change the desired ones. See github issue
#374.
vegemite
returns invisibly the final formatted table allowing
further processing.
ordiplot
passes cex
argument to linestack
and decorana
plots.
vegdist
silently accepted missing values (NA
) and removed them
from the analysis also with option na.rm = FALSE
. The behaviour was
introduced in vegan version 2.5-1. See GitHub issue
#319.
The labels were displaced when the bunch of arrows was not drawn at
the origin of the ordination graph in envfit
. See GitHub issue
#315.
Hill scale in coverscale
is open-ended and is not limited to percent
data, unlike most traditional cover class scales which are undefined
above 100% cover.
as.rad
no longer print the index attribute: the
attribute is still in the object, but printing made the output messy.vegan depends on R 3.4.0 or higher. The next vegan release may increase the dependence to R 3.6.0.
R 3.6.0 improved the method to find random indices for permuting
and sampling data. Vegan relies now on the R functions in its
ecological null models (functions nullmodel
, oecosimu
, commsim
,
permatfull
, permatswap
and others). Technically this change is
compatible with R 3.4.0 and later, but you can only gain the
benefits of improved code with a current release of R. The null
models may change due to this change, and most certainly they change
in R 3.6.0. See NEWS for the R 3.6.0 release and
discussion in github issue
#312.
Most vegan permutation routines rely on permute, and there you gain similar benefits of improved randomness when you upgrade R.
Thanks to the new R dependence, sigma
for constrained ordination
results works without workarounds of vegan 2.5-2. This fixes
completely the issue discussed in
#274.
Vegan test results cannot be reproduced in older versions than R 3.6.0. If you are worried about this, you should upgrade R.
metaMDS
failed in scaling results when other engine
than monoMDS
was used. However, we recommend you use monoMDS
. See github issue
#310.betadisper
changed interpretation of negative squared distances
which give complex-valued distances. Now they are regarded as
zero-distances whereas earlier we used their modulus. This will change
the results in cases where you had negative squared distances. For
further discussion, see github issue
#306.The code for interpreting formula will change in R 3.6.0, and
this makes constrained ordination methods (cca
, rda
, dbrda
,
capscale
) to fail. See github issue
#299.
R 3.6.0 introduces a new environment variable
_R_CHECK_LENGTH_1_LOGIC2_
, and several functions fail if this
variable is set. Changes concern ordiplot
, plot
and summary
for
constrained ordination objects, and ordixyplot
. See github issue
#305.
decorana
gave incorrect results when downweighting was used
(argument iweigh = 1
). The bug was introduced in vegan 2.5-1 and
reported as github issue
#303.
goodness
for constrained ordination methods failed when the
constraints had rank = 1 (only one constraining variable). Reported by
Pierre Legendre.
rda
and
dbrda
) and partial CCA models (function cca
) in function
RsquareAdj
. The feature was disabled in vegan 2.5-1 for both. For
RDA, the calculation is similar as in vegan 2.4-6 and earlier.
Partial CCA is now consistent with RDA and differs from the earlier
implementation. For both methods, the partial models are consistent
with varpart
. See github issue
#295.Constrained ordination gave misleading results when some constraints
or conditions had data with NULL variables. This rarely happens in
normal usage, but could happen in marginal anova
as reported in
github issue #291.
Several functions for numerical analysis wrongly accepted non-numeric
data (for instance, factors) and gave either meaningless results or
confusing error messages. Fixed functions include beals
,
designdist
, diversity
, gdispweight
, indpower
, spantree
,
specpool
, tsallis
, tsallisaccum
and vegdist
. See github issue
#292.
envfit
with vectors could fail with missing data.
The original data were not scaled and centred similarly as simulations
in simulate.rda
when several simulations were returned as a simmat
object (which is compatible with nullmodel
simulations and can be
used in oecosimu
).
anosim
checks its input to avoid confusing error messages like that
reported in StackOverflow question
52082743.
Broken-stick distribution (function bstick
) is no longer calculated
for distance-based Redundancy Analysis (dbrda
) with negative
eigenvalues, because it is not clear how this should be done. Now
dbrda
and capscale
are similar with this respect.
print
function for betadisper
results gained new argument neigen
to select the number of eigenvalues shown. The print
is more robust
when the number of eigenvalues is lower than the requested neigen
.
humpfit
was moved to the natto package and is still
available from https://github.com/jarioksa/natto. It is scheduled
for complete removal in vegan 2.6-0.Vegan declares dependence on R version 3.2.0. This dependence
was not yet noticed in the previous vegan release. However, the
generic sigma
function was only defined in R-3.3.0, and
therefore sigma.cca
of vegan must be spelt out completely when using
R-3.2.x. See discussion in issue
#274.
CRAN package klaR has
function rda
, and when loaded together with vegan this clashes with
vegan rda
for Redundancy Analysis. Vegan tries to mitigate the
problem. In most cases vegan functions will be used if vegan was
loaded after klaR, and an error message is issued if klaR objects are
handled with vegan functions. klaR is also tricked to print an
informative message if it handles vegan objects. However, vegan
namespace can be attached automatically at the start-up and then klaR
functions will take precedence. This was reported as issue
#277.
Bioconductor package phyloseq has a problem with vegdist
function
for dissimilarities. The problem can be fixed by re-installing
phyloseq from its source package. If you cannot do this, you must
either downgrade to vegan version 2.4-6 or wait till Bioconductor
binary packages are upgraded. This was reported in
Stackoverflow, and as
vegan issue #272,
and as phyloseq issues
#918 and
#921.
Plotting betadisper
failed if any of the groups
had only one
member. Reported in Stackoverflow as “Error: Incorrect no.of
dimensions” when plotting multivariate data in
Vegan.
Permutation tests for constrained ordination (anova.cca
,
permutest.cca
) could fail in parallel processing with socket
clusters. Socket clusters are always used in Windows and they can also
be used in other operating systems when created with makeCluster
.
See issue #276.
This is a major new release with changes all over the package: Nearly 40% of program files were changed from the previous release. Please report regressions and other issues in https://github.com/vegandevs/vegan/issues/.
Compiled code is used much more extensively, and most compiled
functions use .Call
interface. This gives smaller memory footprint
and is also faster. In wall clock time, the greatest gains are in
permutation tests for constrained ordination methods (anova.cca
) and
binary null models (nullmodel
).
Constrained ordination functions (cca
, rda
, dbrda
, capscale
)
are completely rewritten and share most of their code. This makes them
more consistent with each other and more robust. The internal
structure changed in constrained ordination objects, and scripts may
fail if they try to access the result object directly. There never was
a guarantee for unchanged internal structure, and such scripts should
be changed and they should use the provided support functions to
access the result object (see documentation of cca.object
and github
issue #262). Some
support and analysis functions may no longer work with result objects
created in previous vegan versions. You should use
update(old.result.object)
to fix these old result objects. See
github issues #218,
#227.
vegan includes some tests that are run when checking the package installation. See github issues #181, #271.
The informative messages (warnings, notes and error messages) are cleaned and unified which also makes possible to provide translations.
avgdist
: new function to find averaged dissimilarities from several
random rarefactions of communities. Code by Geoffrey Hannigan. See
github issues #242,
#243,
#246.
chaodist
: new function that is similar to designdist
, but uses
Chao terms that are supposed to take into account the effects of
unseen species (Chao et al., Ecology Letters 8, 148-159; 2005).
Earlier we had Jaccard-type Chao dissimilarity in vegdist
, but the
new code allows defining any kind of Chao dissimilarity.
New functions to find influence statistics of constrained ordination
objects: hatvalues
, sigma
, rstandard
, rstudent
,
cooks.distance
, SSD
, vcov
, df.residual
. Some of these could be
earlier found via as.mlm
function which is deprecated. See github
issue #234.
boxplot
was added for permustats
results to display the
(standardized) effect sizes.
sppscores
: new function to add or replace species scores in
distance-based ordination such as dbrda
, capscale
and metaMDS
.
Earlier dbrda
did not have species scores, and species scores in
capscale
and metaMDS
were based on raw input data which may not be
consistent with the used dissimilarity measure. See github issue
#254.
cutreeord
: new function that is similar to stats::cutree
, but
numbers the cluster in the order they appear in the dendrogram (left
to right) instead of labelling them in the order they appeared in the
data.
sipoo.map
: a new data set of locations and sizes of the islands in
the Sipoo archipelago bird data set sipoo
.
The inertia of Correspondence Analysis (cca
) is called “scaled
Chi-square” instead of using a name of a little known statistic.
If elements for Constraints and Conditions are data frames in
non-formula call of rda
or cca
, these are automatically expanded
to model matrices and can contain factor variables. Earlier they had
to be numerical model matrices and factors could only be used with the
formula interface.
Regression scores for constraints can be extracted and plotted for constrained ordination methods. See github issue #226.
Full model (model = "full"
) is again enabled in permutations tests
for constrained ordination results in anova.cca
and permutest.cca
.
permutest.cca
gained a new option by = "onedf"
to perform tests by
sequential one degree-of-freedom contrasts of factors. This option is
not (yet) enabled in anova.cca
.
The permutation tests are more robust, and most scoping issues should have been fixed.
Permutation tests use compiled C code and they are much faster. See github issue #211.
permutest
printed layout is similar to anova.cca
.
eigenvals
gained a new argument (model
) to select either
constrained or unconstrained scores. The old argument (constrained
)
is deprecated. See github issue
#207.
summary.eigenvals
returns a matrix instead of a list containing only
that matrix.
Adjusted R2 is not calculated for partial ordination, because it is
unclear how this should be done (function RsquareAdj
).
ordiresids
can display standardized and studentized residuals.
Function to construct model.frame
and model.matrix
for constrained
ordination are more robust and fail in fewer cases.
goodness
and inertcomp
for constrained ordination result object no
longer has an option to find distances: only explained variation is
available.
inertcomp
gained argument unity
. This will give “local
contributions to beta-diversity” (LCBD) and “species contribution to
beta-diversity” (SCBD) of Legendre & De Cáceres (Ecology Letters
16, 951-963; 2012).
goodness
is disabled for capscale
.
prc
gained argument const
for general scaling of results similarly
as in rda
.
prc
uses regression scores for Canoco-compatibility.
The C code for swap-based binary null models was made more efficients, and the models are all faster. Many of these models selected a 2 times 2 submatrix, and for this they generated four random numbers (two rows, two columns). Now we skip selecting third or fourth random number if it is obvious that the matrix cannot be swapped. Since most of time was used in generating random numbers in these functions, and most candidates were rejected, this speeds up functions. However, this also means that random number sequences change from previous vegan versions, and old binary model results cannot be replicated exactly. See github issues #197, #255 for details and timing.
Ecological null models (nullmodel
, simulate
, make.commsim
,
oecosimu
) gained new null model "greedyqswap"
which can radically
speed up quasi-swap models with minimal risk of introducing bias.
Backtracking is written in C and it is much faster. However, backtracking models are biased, and they are provided only because they are classic legacy models.
adonis2
gained a column of R2 similarly as old adonis
.
Great part of R code for decorana
is written in C which makes it
faster and reduces the memory footprint.
metaMDS
results gained new points
and text
methods.
ordiplot
and other ordination plot
functions can be chained with
their points
and text
functions allowing the use of
magrittr pipes. The
points
and text
functions gained argument to draw arrows allowing
their use in drawing biplots or adding vectors of environmental
variables with ordiplot
. Since many ordination plot
methods return
an invisible "ordiplot"
object, these points
and text
methods
also work with them. See github issue
#257.
Lattice graphics (ordixyplot
) for ordination can add polygons that
enclose all points in the panel and complete data.
ordicluster
gained option to suppress drawing in plots so that it
can be more easily embedded in other functions for calculations.
as.rad
returns the index of included taxa as an attribute.
Random rarefaction (function rrarefy
) uses compiled C code and is
much faster.
plot
of specaccum
can draw short horizontal bars to vertical error
bars. See StackOverflow question
45378751.
decostand
gained new standardization methods rank
and rrank
which replace abundance values by their ranks or relative ranks. See
github issue #225.
Clark dissimilarity was added to vegdist
(this cannot be calculated
with designdist
).
designdist
evaluates minimum terms in compiled code, and the
function is faster than vegdist
also for dissimilarities using
minimum terms. Although designdist
is usually faster than vegdist
,
it is numerically less stable, in particular with large data sets.
swan
passes type
argument to beals
.
tabasco
can use traditional cover scale values from function
coverscale
. Function coverscale
can return scaled values as
integers for numerical analysis instead of returning characters for
printing.
varpart
can partition Chi-squared inertia of correspondence
analysis with new argument chisquare
. The adjusted R2
is based on permutation tests, and the replicate analysis will have
random variation.
The explanatory tables can be data frames with factors or single
factors in varpart
and these will be automatically expanded to model
matrices. Earlier factors could only be used with one-sided model
formulae. Based on the code suggested by Daniel Borcard, Univ.
Montréal.
Very long Condition()
statements (> 500 characters) failed in
partial constrained ordination models (cca
, rda
, dbrda
,
capscale
). The problem was detected in StackOverflow question
49249816.
Labels were not adjusted when arrows were rescaled in envfit
plots.
See StackOverflow question
49259747.
ordiArrowMul
failed if there was only one arrow to be plotted in
envfit
.
as.mlm
function for constrained correspondence analysis is
deprecated in favour of new functions that directly give the influence
statistics. See github issue
#234.
commsimulator
is now defunct: use simulate
for nullmodel
objects.
ade4 cca
objects are no
longer handled in vegan: ade4 has had no cca
since version 1.7-8
(August 9, 2017).
read.cep
function used FORTRAN format to read legacy CEP and Canoco
files. To avoid NOTEs and WARNINGs, the function was re-written in
R. The new read.cep
is less powerful and more fragile, and can
only read data in “condensed” format, and it can fail in several cases
that were successful with the old code. The old FORTRAN-based function
is still available in
cepreader. See github
issue #263. The
cepreader package is developed in
https://github.com/vegandevs/cepreader.rrarefy
), species abundance
distribution (preston
) and species pool (estimateR
) need exact
integer data, but the test allowed small fuzz. The functions worked
correctly with original data, but if data were transformed and then
back-transformed, they would pass the integer test with fuzz and give
wrong results. For instance, sqrt(3)^2
would pass the test as 3, but
was interpreted strictly as integer 2. See github issue
#259.ordiresids
uses now weighted residuals for cca
results.Several “Swap & Shuffle” null models generated wrong number of initial matrices. Usually they generated too many, which was not dangerous, but it was slow. However, random sequences will change with this fix.
Lattice graphics for ordination (ordixyplot
and friends) colour the
arrows by groups
instead of randomly mixed colours.
Information on constant or mirrored permutations was omitted when
reporting permutation tests (e.g., in anova
for constrained
ordination).
ordistep
has improved interpretation of scope
: if the lower scope
is missing, the formula of the starting solution is taken as the lower
scope instead of using an empty model. See Stackoverflow question
46985029.
fitspecaccum
gained new support functions nobs
and logLik
which
allow better co-operation with other packages and functions. See
GitHub issue #250.
The “backtracking” null model for community simulation is faster. However, “backtracking” is a biased legacy model that should not be used except in comparative studies.
orditkplot
should no longer give warnings in CRAN tests.anova(..., by = "axis")
for constrained ordination (cca
, rda
,
dbrda
) ignored partial terms in Condition()
.
inertcomp
and summary.cca
failed if the constrained component was
defined, but explained nothing and had zero rank. See StackOverflow:
R - Error message in doing RDA analysis - vegan
package.
Labels are no longer cropped in the meandist
plots.
The significance tests for the axes of constrained ordination use now forward testing strategy. More extensive analysis indicated that the previous marginal tests were biased. This is in conflict with Legendre, Oksanen & ter Braak, Methods Ecol Evol 2, 269–277 (2011) who regarded marginal tests as unbiased.
Canberra distance in vegdist
can now handle negative input entries
similarly as latest versions of R.
vegan registers native C and Fortran routines. This avoids warnings in model checking, and may also give a small gain in speed.
Future versions of vegan will deprecate and remove elements
pCCA$Fit
, CCA$Xbar
, and CA$Xbar
from cca
result objects. This
release provides a new function ordiYbar
which is able to construct
these elements both from the current and future releases. Scripts and
functions directly accessing these elements should switch to
ordiYbar
for smooth transition.
as.mlm
methods for constrained ordination include zero intercept to
give the correct residual degrees of freedom for derived statistics.
biplot
method for rda
passes correlation
argument to the scaling
algorithm.
Biplot scores were wrongly centred in cca
which caused a small error
in their values.
Weighting and centring were corrected in intersetcor
and spenvcor
.
The fix can make a small difference when analysing cca
results.
Partial models were not correctly handled in intersetcor
.
envfit
and ordisurf
functions failed when applied to species
scores.
Non-standard variable names can be used within Condition()
in
partial ordination. Partial models are used internally within several
functions, and a problem was reported by Albin Meyer (Univ Lorraine,
Metz, France) in ordiR2step
when using a variable name that
contained a hyphen (which was wrongly interpreted as a minus sign in
partial ordination).
ordispider
did not pass graphical arguments when used to show the
difference of LC and WA scores in constrained ordination.
ordiR2step
uses only forward
selection to avoid several problems
in model evaluation.
tolerance
function could return NaN
in some cases when it should
have returned 0
. Partial models were not correctly analysed.
Misleading (non-zero) tolerances were sometimes given for species that
occurred only once or sampling units that had only one species.
Permutation tests (permutests
, anova
) for the first axis failed in
constrained distance-based ordination (dbrda
, capscale
). Now
capscale
will also throw away negative eigenvalues when first
eigenvalues are tested. All permutation tests for the first axis are
now faster. The problem was reported by Cleo Tebby and the fixes are
discussed in GitHub issue
#198 and pull
request #199.
Some support functions for dbrda
or capscale
gave results or some
of their components in wrong scale. Fixes in stressplot
, simulate
,
predict
and fitted
functions.
intersetcor
did not use correct weighting for cca
and the results
were slightly off.
anova
and permutest
failed when betadisper
was fitted with
argument bias.adjust = TRUE
. Fixes Github issue
#219 reported by
Ross Cunning, O'ahu, Hawaii.
ordicluster
should return invisibly only the coordinates of internal
points (where clusters or points are joined), but last rows contained
coordinates of external points (ordination scores of points).
The cca
method of tolerance
was returning incorrect values for all
but the second axis for sample heterogeneities and species tolerances.
See issue #216 for
details.
Biplot scores are scaled similarly as site scores in constrained
ordination methods cca
, rda
, capscale
and dbrda
. Earlier they
were unscaled (or more technically, had equal scaling on all axes).
tabasco
adds argument to scale
the colours by rows or columns in
addition to the old equal scale over the whole plot. New arguments
labRow
and labCex
can be used to change the column or row labels.
Function also takes care that only above-zero observations are
coloured: earlier tiny observed values were merged to zeros and were
not distinct in the plots.
Sequential null models are somewhat faster (up to 10%). Non-sequential
null models may be marginally faster. These null models are generated
by function nullmodel
and also used in oecosimu
.
vegdist
is much faster. It used to be clearly slower than
stats::dist
, but now it is nearly equally fast for the same
dissimilarity measure.
Handling of data=
in formula interface is more robust, and messages
on user errors are improved. This fixes points raised in Github issue
#200.
The families and orders in dune.taxon
were updated to APG IV (Bot J
Linnean Soc 181, 1–20; 2016) and a corresponding classification
for higher levels (Chase & Reveal, Bot J Linnean Soc 161,
122-127; 2009).
Several support functions for ordination methods failed if the
solution had only one ordination axis, for instance, if there was only
one constraining variable in CCA, RDA and friends. This concerned
goodness
for constrained ordination, inertcomp
, fitted
for
capscale
, stressplot
for RDA, CCA (GitHub issue
#189).
goodness
for CCA & friends ignored choices
argument (GitHub issue
#190).
goodness
function did not consider negative eigenvalues of db-RDA
(function dbrda
).
Function meandist
failed in some cases when one of the groups had
only one observation.
linestack
could not handle expressions in labels
. This regression
is discussed in GitHub issue
#195.
Nestedness measures nestedbetajac
and nestedbetasor
expecting
binary data did not cope with quantitative input in evaluating
Baselga's matrix-wide Jaccard or Sørensen dissimilarity indices.
Function as.mcmc
to cast oecosimu
result to an MCMC object
(coda package) failed if
there was only one chain.
diversity
function returns now NA
if the observation had NA
values instead of returning 0
. The function also checks the input
and refuses to handle data with negative values. GitHub issue
#187.
rarefy
function will work more robustly in marginal case when the
user asks for only one individual which can only be one species with
zero variance.
Several functions are more robust if their factor arguments contain
missing values (NA
): betadisper
, adipart
, multipart
,
hiersimu
, envfit
and constrained ordination methods cca
, rda
,
capscale
and dbrda
. GitHub issues
#192 and
#193.
Distance-based methods were redesigned and made consistent for
ordination (capscale
, new dbrda
), permutational ANOVA (adonis
,
new adonis2
), multivariate dispersion (betadisper
) and variation
partitioning (varpart
). These methods can produce negative
eigenvalues with several popular semimetric dissimilarity indices, and
they were not handled similarly by all functions. Now all functions
are designed after McArdle & Anderson (Ecology 82, 290–297; 2001).
dbrda
is a new function for distance-based Redundancy Analysis
following McArdle & Anderson (Ecology 82, 290–297; 2001). With
metric dissimilarities, the function is equivalent to old capscale
,
but negative eigenvalues of semimetric indices are handled
differently. In dbrda
the dissimilarities are decomposed directly
into conditions, constraints and residuals with their negative
eigenvalues, and any of the components can have imaginary dimensions.
Function is mostly compatible with capscale
and other constrained
ordination methods, but full compatibility cannot be achieved (see
issue #140 in
Github). The function is based on the code by Pierre Legendre.
The old capscale
function for constrained ordination is still based
only on real components, but the total inertia of the components is
assessed similarly as in dbrda
.
The significance tests will differ from the previous version, but
function oldCapscale
will cast the capscale
result to a similar
form as previously.
adonis2
is a new function for permutational ANOVA of
dissimilarities. It is based on the same algorithm as the dbrda
. The
function can perform overall tests of all independent variables as
well as sequential and marginal tests of each term. The old adonis
is still available, but it can only perform sequential tests. With
same settings, adonis
and adonis2
give identical results (but see
Github issue #156
for differences).
Function varpart
can partition dissimilarities using the same
algorithm as dbrda
.
Argument sqrt.dist
takes square roots of dissimilarities and these
can change many popular semimetric indices to metric distances in
capscale
, dbrda
, wcmdscale
, adonis2
, varpart
and
betadisper
(issue
#179 in Github).
Lingoes and Cailliez adjustments change any dissimilarity into metric
distance in capscale
, dbrda
, adonis2
, varpart
, betadisper
and wcmdscale
. Earlier we had only Cailliez adjustment in capscale
(issue #179 in
Github).
RsquareAdj
works with capscale
and dbrda
and this allows using
ordiR2step
in model building.
specaccum
: plot
failed if line type (lty
) was given. Reported by
Lila Nath Sharma (Univ Bergen, Norway)ordibar
is a new function to draw crosses of standard deviations or
standard errors in ordination diagrams instead of corresponding
ellipses.
Several permustats
results can be combined with a new c()
function.
New function smbind
binds together null models by row, column or
replication. If sequential models are bound together, they can be
treated as parallel chains in subsequent analysis (e.g., after
as.mcmc
). See issue
#164 in Github.
New "curveball"
algorithm provides a fast null model with fixed row
and column sums for binary matrices after Strona et al. (Nature
Commun. 5: 4114; 2014).
The "quasiswap"
algorithm gained argument thin
which can reduce
the bias of null models.
"backtracking"
is now much faster, but it is still very slow, and
provided mainly to allow comparison against better and faster methods.
Compiled code can now be interrupted in null model simulations.
designdist
can now use beta diversity notation (gamma
, alpha
)
for easier definition of beta diversity indices.
metaMDS
has new iteration strategy: Argument try
gives the minimum
number of random starts, and trymax
the maximum number. Earlier we
only hand try
which gave the maximum number, but now we run at least
try
times. This reduces the risk of being trapped in a local optimum
(issue #154 in
Github).
If there were no convergent solutions, metaMDS
will now tabulate
stopping criteria (if trace = TRUE
). This can help in deciding if
any of the criteria should be made more stringent or the number of
iterations increased. The documentation for monoMDS
and metaMDS
give more detailed information on convergence criteria.
summary
of permustats
prints now P-values, and the test
direction (alternative
) can be changed.The qqmath
function of permustats
can now plot standardized
statistics. This is a partial solution to issue
#172 in Github.
MDSrotate
can rotate ordination to show maximum separation of factor
levels (classes) using linear discriminant analysis (lda
in
MASS package).
adipart
, hiersimu
and multipart
expose argument method
to
specify the null model.
RsquareAdj
works with cca
and this allows using ordiR2step
in
model building. The code was developed by Dan McGlinn (issue
#161 in Github).
However, cca
still cannot be used in varpart
.
ordiellipse
and ordihull
allow setting colours, line types and
other graphical parameters.
The alpha channel can now be given also as a real number in 0 ... 1 in addition to integer 0 ... 255.
ordiellipse
can now draw ellipsoid hulls that enclose points in a
group.
ordicluster
, ordisegments
, ordispider
and lines
and plot
functions for isomap
and spantree
can use a mixture of colours of
connected points. Their behaviour is similar as in analogous functions
in the the vegan3d
package.
plot
of betadisper
is more configurable. See issues
#128 and
#166 in Github for
details.
text
and points
methods for orditkplot
respect stored graphical
parameters.
Environmental data for the Barro Colorado Island forest plots gained new variables from Harms et al. (J. Ecol. 89, 947–959; 2001). Issue #178 in Github.
Function metaMDSrotate
was removed and replaced with MDSrotate
.
density
and densityplot
methods for various vegan objects were
deprecated and replaced with density
and densityplot
for
permustats
. Function permustats
can extract the permutation and
simulation results of vegan result objects.
eigenvals
fails with prcomp
results in R-devel. The next
version of prcomp
will have an argument to limit the number of
eigenvalues shown (rank.
), and this breaks eigenvals
in vegan.
calibrate
failed for cca
and friends if rank
was given.
betadiver
index 19
had wrong sign in one of its terms.
linestack
failed when the labels
were given, but the input scores
had no names. Reported by Jeff Wood (ANU, Canberra, ACT).
vegandocs
is deprecated. Current R provides better tools for
seeing extra documentation (news()
and browseVignettes()
).browseVignettes
. FAQ-vegan
and partitioning
were only
accessible with vegandocs
function.texi2dvi
was removed. Version 6.1
of texi2dvi
was incompatible with R and prevented building
vegan. The FAQ-vegan
that was earlier built with texi2dvi
uses now
knitr. Because of this,
vegan is now dependent on R-3.0.0. Fixes issue
#158 in Github.metaMDS
and monoMDS
could fail if input dissimilarities were huge:
in the reported case they were of magnitude 1E85. Fixes issue
#152 in Github.
Permutations failed if they were defined as
permute control
structures in estaccum
, ordiareatest
, renyiaccum
and
tsallisaccum
. Reported by Dan Gafta (Cluj-Napoca) for renyiaccum
.
rarefy
gave false warnings if input was a vector or a single
sampling unit.
Some extrapolated richness indices in specpool
needed the number of
doubletons (= number of species occurring in two sampling units), and
these failed when only one sampling unit was supplied. The
extrapolated richness cannot be estimated from a single sampling unit,
but now such cases are handled smoothly instead of failing: observed
non-extrapolated richness with zero standard error will be reported.
The issue was reported in
StackOverflow.
treedist
and treedive
refuse to handle trees with reversals, i.e,
higher levels are more homogeneous than lower levels. Function
treeheight
will estimate their total height with absolute values of
branch lengths. Function treedive
refuses to handle trees with
negative branch heights indicating negative dissimilarities. Function
treedive
is faster.
gdispweight
works when input data are in a matrix instead of a data
frame.
Input dissimilarities supplied in symmetric matrices or data frames
are more robustly recognized by anosim
, bioenv
and mrpp
.
Printing details of a gridded permutation design would fail when the grid was at the within-plot level.
ordicluster
joined the branches at wrong coordinates in some cases.
ordiellipse
ignored weights when calculating standard errors (kind
= "se"
). This influenced plots of cca
, and also influenced
ordiareatest
.
adonis
and capscale
functions recognize symmetric square matrices
as dissimilarities. Formerly dissimilarities had to be given as
"dist"
objects such as produced by dist
or vegdist
functions,
and data frames and matrices were regarded as observations x variables
data which could confuse users (e.g., issue
#147).
mso
accepts "dist"
objects for the distances among locations as an
alternative to coordinates of locations.
text
, points
and lines
functions for procrustes
analysis
gained new argument truemean
which allows adding procrustes
items
to the plots of original analysis.
rrarefy
returns observed non-rarefied communities (with a warning)
when users request subsamples that are larger than the observed
community instead of failing. Function drarefy
has been similar and
returned sampling probabilities of 1, but now it also issues a
warning. Fixes issue
#144 in Github.
Permutation tests did not always correctly recognize ties with the
observed statistic and this could result in too low P
-values. This
would happen in particular when all predictor variables were factors
(classes). The changes concern functions adonis
, anosim
, anova
and permutest
functions for cca
, rda
and capscale
, permutest
for betadisper
, envfit
, mantel
and mantel.partial
, mrpp
,
mso
, oecosimu
, ordiareatest
, protest
and simper
. This also
fixes issues #120
and #132 in GitHub.
Automated model building in constrained ordination (cca
, rda
,
capscale
) with step
, ordistep
and ordiR2step
could fail if
there were aliased candidate variables, or constraints that were
completely explained by other variables already in the model. This was
a regression introduced in vegan 2.2-0.
Constrained ordination methods cca
, rda
and capscale
treat
character variables as factors in analysis, but did not return their
centroids for plotting.
Recovery of original data in metaMDS
when computing WA scores for
species would fail if the expression supplied to argument comm
was
long & got deparsed to multiple strings. metaMDSdist
now returns the
(possibly modified) data frame of community data comm
as attribute
"comm"
of the returned dist
object. metaMDS
now uses this to
compute the WA species scores for the NMDS. In addition, the deparsed
expression for comm
is now robust to long expressions. Reported by
Richard Telford.
metaMDS
and monoMDS
rejected dissimilarities with missing values.
Function rarecurve
did not check its input and this could cause
confusing error messages. Now function checks that input data are
integers that can be interpreted as counts on individuals and all
sampling units have some species. Unchecked bad inputs were the reason
for problems reported in
Stackoverflow.
Scaling of ordination axes in cca
, rda
and capscale
can now be
expressed with descriptive strings "none"
, "sites"
, "species"
or
"symmetric"
to tell which kind of scores should be scaled by
eigenvalues. These can be further modified with arguments hill
in
cca
and correlation
in rda
. The old numeric scaling can still be
used.
The permutation data can be extracted from anova
results of
constrained ordination (cca
, rda
, capscale
) and further analysed
with permustats
function.
New data set BCI.env
of site information for the Barro Colorado
Island tree community data. Most useful variables are the UTM
coordinates of sample plots. Other variables are constant or nearly
constant and of little use in normal analysis.
Constrained ordination functions cca
, rda
and capscale
are now
more robust. Scoping of data set names and variable names is much
improved. This should fix numerous long-standing problems, for
instance those reported by Benedicte Bachelot (in email) and Richard
Telford (in Twitter), as well as issues
#16 and
#100 in GitHub.
Ordination functions cca
and rda
silently accepted dissimilarities
as input although their analysis makes no sense with these methods.
Dissimilarities should be analysed with distance-based redundancy
analysis (capscale
).
The variance of the conditional component was over-estimated in
goodness
of rda
results, and results were wrong for partial RDA.
The problems were reported in an
R-sig-ecology
message by Christoph von Redwitz.
orditkplot
did not add file type identifier to saved graphics in
Windows although that is required. The problem only concerned Windows
OS.goodness
function for constrained ordination (cca
, rda
,
capscale
) was redesigned. Function gained argument addprevious
to
add the variation explained by previous ordination components to axes
when statistic = "explained"
. With this option, model = "CCA"
will
include the variation explained by partialled-out conditions, and
model = "CA"
will include the accumulated variation explained by
conditions and constraints. The former behaviour was addprevious =
TRUE
for model = "CCA"
, and addprevious = FALSE
for model =
"CA"
. The argument will have no effect when statistic = "distance"
,
but this will always show the residual distance after all previous
components. Formerly it displayed the residual distance only for the
currently analysed model.
Functions ordiArrowMul
and ordiArrowTextXY
are exported and can be
used in normal interactive sessions. These functions are used to scale
a bunch arrows to fit ordination graphics, and formerly they were
internal functions used within other vegan functions.
orditkplot
can export graphics in SVG format. SVG is a vector
graphics format which can be edited with several external programs,
such as Illustrator and Inkscape.
Rarefaction curve (rarecurve
) and species accumulation models
(specaccum
, fitspecaccum
) gained new functions to estimate the
slope of curve at given location. Originally this was based on a
response to an
R-SIG-ecology
query. For rarefaction curves, the function is rareslope
, and for
species accumulation models it is specslope
.
The functions are based on analytic equations, and can also be
evaluated at interpolated non-integer values. In specaccum
models
the functions can be only evaluated for analytic models "exact"
,
"rarefaction"
and "coleman"
. With "random"
and "collector"
methods you can only use finite differences
(diff(fitted(<result.object>))
). Analytic functions for slope are
used for all non-linear regression models known to fitspecaccum
.
Species accumulation models (specaccum
) and non-liner regression
models for species accumulation (fitspecaccum
) work more
consistently with weights. In all cases, the models are defined using
the number of sites as independent variable, which with weights means
that observations can be non-integer numbers of virtual sites. The
predict
models also use the number of sites with newdata
, and for
analytic models they can estimate the expected values for non-integer
number of sites, and for non-analytic randomized or collector models
they can interpolate on non-integer values.
fitspecaccum
gained support functions AIC
and deviance
.
The varpart
plots of four-component models were redesigned following
Legendre, Borcard & Roberts Ecology 93, 1234–1240 (2012), and they
use now four ellipses instead of three circles and two rectangles. The
components are now labelled in plots, and the circles and ellipses can
be easily filled with transparent background colour.
orditkplot
function for interactive editing of
ordination graphics.ordisurf
failed if gam
package was loaded due to namespace issues: some support functions of
gam were used instead of
mgcv functions.
tolerance
function failed for unconstrained correspondence analysis.
estimateR
uses a more exact variance formula for bias-corrected Chao
estimate of extrapolated number of species. The new formula may be
unpublished, but it was derived following the guidelines of Chiu,
Wang, Walther & Chao, Biometrics 70, 671–682 (2014),
doi:10.1111/biom.12200, online
supplementary material.
Diversity accumulation functions specaccum
, renyiaccum
,
tsallisaccum
, poolaccum
and estaccumR
use now
permute package for
permutations of the order of sampling sites. Normally these functions
only need simple random permutation of sites, but restricted
permutation of the permute package and user-supplied permutation
matrices can be used.
estaccumR
function can use parallel processing.
linestack
accepts now expressions as labels. This allows using
mathematical symbols and formula given as mathematical expressions.
parallel
.
The argument can be an integer giving the number of parallel
processes. In unix-alikes (Mac OS, Linux) this will launch
"multicore"
processing and in Windows it will set up "snow"
clusters as desribed in the documentation of the parallel package. If
option
"mc.cores"
is set to an integer > 1, this will be used to
automatically start parallel processing. Finally, the argument can
also be a previously set up "snow"
cluster which will be used both
in Windows and in unix-alikes. Vegan vignette on Design decision
explains the implementation (use vegandocs("decission")
, and
parallel package has more extensive documentation on parallel
processing in R.The following function use parallel processing in analysing
permutation statistics: adonis
, anosim
, anova.cca
(and
permutest.cca
), mantel
(and mantel.partial
), mrpp
,
ordiareatest
, permutest.betadisper
and simper
. In addition,
bioenv
can compare several candidate sets of models in paralle,
metaMDS
can launch several random starts in parallel, and oecosimu
can evaluate test statistics for several null models in parallel.
permutations
. The default usage of simple
non-restricted permutations is achieved by giving a single integer
number. Restricted permutations can be defined using the how
function of the permute package. Finally, the argument can be a
permutation matrix where rows define permutations. It is possible to
use external or user constructed permutations.See help(permutations)
for a brief introduction on permutations in
vegan, and permute package for the full documention. The vignette of
the permute package can be read from vegan with command
vegandocs("permutations")
.
The following functions use the
permute package:
CCorA
, adonis
, anosim
, anova.cca
(plus associated
permutest.cca
, add1.cca
, drop1.cca
, ordistep
, ordiR2step
),
envfit
(plus associated factorfit
and vectorfit
), mantel
(and
mantel.partial
), mrpp
, mso
, ordiareatest
,
permutest.betadisper
, protest
and simper
.
nullmodel
function and defined in a low level commsim
function. The actual
null models are generated with a simulate
function that builds an
array of null models. The new null models include a wide array of
quantitative models in addition to the old binary models, and users
can plug in their own generating functions. The basic tool invoking
and analysing null models is oecosimu
. The null models are often
used only for the analysis of nestedness, but the implementation in
oecosimu
allows analysing any statistic, and null models are better
seen as an alternative to permutation tests.vegan package dependencies and namespace imports were adapted to changes in R, and no more trigger warnings and notes in package tests.
Three-dimensional ordination graphics using scatterplot3d for static plots and rgl for dynamic plots were removed from vegan and moved to a companion package vegan3d. The package is available in CRAN.
Function dispweight
implements dispersion weighting of Clarke et al.
(Marine Ecology Progress Series, 320, 11–27). In addition, we
implemented a new method for generalized dispersion weighting
gdispweight
. Both methods downweight species that are significantly
over-dispersed.
New hclust
support functions reorder
, rev
and scores
.
Functions reorder
and rev
are similar as these functions for
dendrogram
objects in base R. However, reorder
can use (and
defaults to) weighted mean. In weighted mean the node average is
always the mean of member leaves, whereas the dendrogram
uses always
unweighted means of joined branches.
Function ordiareatest
supplements ordihull
and ordiellipse
and
provides a randomization test for the one-sided alternative hypothesis
that convex hulls or ellipses in two-dimensional ordination space have
smaller areas than with randomized groups.
Function permustats
extracts and inspects permutation results with
support functions summary
, density
, densityplot
, qqnorm
and
qqmath
. The density
and qqnorm
are standard R tools that
only work with one statistic, and densityplot
and qqmath
are
lattice graphics that work with univariate and multivariate
statistics. The results of following functions can be extracted:
anosim
, adonis
, mantel
(and mantel.partial
), mrpp
,
oecosimu
, permustest.cca
(but not the corresponding anova
methods), permutest.betadisper
, and protest
.
stressplot
functions display the ordination distances at given
number of dimensions against original distances. The method functins
are similar to stressplot
for metaMDS
, and always use the inherent
distances of each ordination method. The functions are available for
the results capscale
, cca
, princomp
, prcomp
, rda
, and
wcmdscale
.
cascadeKM
of only one group will be NA
instead of a random value.
ordiellipse
can handle points exactly on a line, including only two
points (with a warning).
plotting radfit
results for several species failed if any of the
communities had no species or had only one species.
RsquareAdj
for capscale
with negative eigenvalues will now report
NA
instead of using biased method of rda
results.
simper
failed when a group had only a single member.
anova.cca
functions were re-written to use the permute package. Old
results may not be exactly reproduced, and models with missing data
may fail in several cases. There is a new option of analysing a
sequence of models against each other.
simulate
functions for cca
and rda
can return several
simulations in a nullmodel
compatible object. The functions can
produce simulations with correlated errors (also for capscale
) in
parametric simulation with Gaussian error.
bioenv
can use Manhattan, Gower and Mahalanobis distances in
addition to the default Euclidean. New helper function bioenvdist
can extract the dissimilarities applied in best model or any other
model.
metaMDS(..., trace = 2)
will show convergence information with the
default monoMDS
engine.
Function MDSrotate
can rotate a k
-dimensional ordination to k-1
variables. When these variables are correlated (like usually is the
case), the vectors can also be correlated to previously rotated
dimensions, but will be uncorrelated to all later ones.
vegan 2.0-10 changed the weighted nestednodf
so that weighted
analysis of binary data was equivalent to binary analysis. However,
this broke the equivalence to the original method. Now the function
has an argument wbinary
to select the method of analysis. The
problem was reported and a fix submitted by Vanderlei Debastiani
(Universidade Federal do Rio Grande do Sul, Brasil).
ordiellipse
, ordihull
and ordiellipse
can handle missing values
in groups
.
ordispider
can now use spatial medians instead of means.
rankindex
can use Manhattan, Gower and Mahalanobis distance in
addition to the default Euclidean.
User can set colours and line types in function rarecurve
for
plotting rarefaction curves.
spantree
gained a support function as.hclust
to change the minimum
spanning tree into an hclust
tree.
fitspecaccum
can do weighted analysis. Gained lines
method.
Functions for extrapolated number of species or for the size of species pool using Chao method were modified following Chiu et al., Biometrics 70, 671–682 (2014).
Incidence based specpool
can now use (and defaults to) small sample
correction with number of sites as the sample size. Function uses
basic Chao extrapolation based on the ratio of singletons and
doubletons, but switches now to bias corrected Chao extrapolation if
there are no doubletons (species found twice). The variance formula
for bias corrected Chao was derived following the supporting on line
material of
doi:10.1111/biom.12200 and
differs slightly from Chiu et al. (2014).
The poolaccum
function was changed similarly, but the small sample
correction is used always.
The abundance based estimateR
uses bias corrected Chao
extrapolation, but earlier it estimated its variance with classic Chao
model. Now we use the widespread approximate estimate from EstimateS
for variance.
With these changes these functions are more similar to EstimateS
tabasco
uses now reorder.hclust
for hclust
object for better
ordering than previously when it cast trees to dendrogram
objects.
treedive
and treedist
default now to match.force = TRUE
and can
be silenced with verbose = FALSE
.
vegdist
gained Mahalanobis distance.
Nomenclature updated in plant community data with the help of
Taxonstand and taxize packages. The taxonomy of the dune
data was
adapted to the same sources and APG III. varespec
and dune
use
8-character names (4 from genus + 4 from species epithet). New data
set on phylogenetic distances for dune
was extracted from Zanne et
al. (Nature 506, 89–92; 2014).
User configurable plots for rarecurve
.
strata
are deprecated in permutations. It is still accepted but will
be phased out in next releases. Use how
of permute package.
cca
, rda
and capscale
do not return scores scaled by
eigenvalues: use scores
function to extract scaled results.
commsimulator
is deprecated. Replace commsimulator(x, method)
with
simulate(nullmodel(x, method))
.
density
and densityplot
for permutation results are deprecated:
use permustats
with its density
and densityplot
method.
oecosimu
and
community pattern simulation, support for parallel processing, and
full support of the permute package. If you are interested in these
developments, you may try the development versions of vegan in
GitHub and report the problems
and user experience to us.envfit
function assumed that all external variables were either
numeric or factors, and failed if they were, say, character strings.
Now only numeric variables are taken as continuous vectors, and all
other variables (character strings, logical) are coerced to factors if
possible. The function also should work with degenerate data, like
only one level of a factor or a constant value of a continuous
environmental variable. The ties were wrongly in assessing permutation
P
-values in vectorfit
.
nestednodf
with quantitative data was not consistent with binary
models, and the fill was wrongly calculated with quantitative data.
oecosimu
now correctly adapts displayed quantiles of simulated
values to the alternative
test direction.
renyiaccum
plotting failed if only one level of diversity scale
was used.
The Kempton and Taylor algorithm was found unreliable in fisherfit
and fisher.alpha
, and now the estimation of Fisher α is only
based on the number of species and the number of individuals. The
estimation of standard errors and profile confidence intervals also
had to be scrapped.
renyiaccum
, specaccum
and tsallisaccum
functions gained subset
argument.
renyiaccum
can now add a collector
curve to to the analysis. The
collector curve is the diversity accumulation in the order of the
sampling units. With an interesting ordering or sampling units this
allows comparing actual species accumulations with the expected
randomized accumulation.
specaccum
can now perform weighted accumulation using the sampling
effort as weights.
ordisurf
gained new arguments for more flexible definition of fitted
models to better utilize the mgcv::gam
function.The linewidth of contours can now be set with the argument lwd
.
Labels to arrows are positioned in a better way in plot
functions
for the results of envfit
, cca
, rda
and capscale
. The labels
should no longer overlap the arrow tips.
The setting test direction is clearer in oecosimu
.
ordipointlabel
gained a plot
method that can be used to replot the
saved result.
tabasco()
is a new function for graphical display of community data
matrix. Technically it is an interface to R heatmap
, but its use
is closer to vegan function vegemite
. The function can reorder the
community data matrix similarly as vegemite
, for instance, by
ordination results. Unlike heatmap
, it only displays dendrograms if
supplied by the user, and it defaults to re-order the dendrograms by
correspondence analysis. Species are ordered to match site ordering or
like determined by the user.Function fitspecaccum(..., model = "asymp")
fitted logistic model
instead of asymptotic model (or the same as model = "logis"
).
nestedtemp()
failed with very sparse data (fill < 0.38
%).
The plot
function for constrained ordination results (cca
, rda
,
capscale
) gained argument axis.bp
(defaults TRUE
) which can be
used to suppress axis scale for biplot arrays.
Number of iterations in nonmetric multidimensional scaling (NMDS) can
be set with keyword maxit
(defaults 200
) in metaMDS
.
cca
, rda
and capscale
will no longer have
scores u.eig
, v.eig
and wa.eig
in the future versions of vegan.
This change does not influence normal usage, because vegan functions
do not need these items. However, external scripts and packages may
need changes in the future versions of vegan.The species scores were scaled wrongly in capscale()
. They were
scaled correctly only when Euclidean distances were used, but usually
capscale()
is used with non-Euclidean distances. Most graphics will
change and should be redone. The change of scaling mainly influences
the spread of species scores with respect to the site scores.
Function clamtest()
failed to set the minimum abundance threshold in
some cases. In addition, the output was wrong when some of the
possible species groups were missing. Both problems were reported by
Richard Telford (Bergen, Norway).
Plotting an object fitted by envfit()
would fail if p.max
was used
and there were unused levels for one or more factors. The unused
levels could result from deletion of observations with missing values
or simply as the result of supplying a subset of a larger data set to
envfit()
.
multipart()
printed wrong information about the analysis type (but
did the analysis correctly). Reported by Valerie Coudrain.
oecosimu()
failed if its nestedfun
returned a data frame. A more
fundamental fix will be in vegan 2.2-0, where the structure of the
oecosimu()
result will change.
The plot of two-dimensional procrustes()
solutions often draw
original axes in a wrong angle. The problem was reported by Elizabeth
Ottesen (MIT).
Function treedive()
for functional or phylogenetic diversity did not
correctly match the species names between the community data and
species tree when the tree contained species that did not occur in the
data. Related function treedist()
for phylogenetic distances did not
try to match the names at all.
The output of capscale()
displays the value of the additive constant
when argument add = TRUE
was used.
fitted()
functions for cca()
, rda()
and capscale()
can now
return conditioned (partial) component of the response: Argument
model
gained a new alternative model = "pCCA"
.
dispindmorisita()
output gained a new column for Chi-squared based
probabilities that the null hypothesis (random distribution) is true.
metaMDS()
and monoMDS()
have new default convergence criteria.
Most importantly, scale factor of the gradient (sfgrmin
) is
stricter. The former limit was too slack with large data sets and
iterations stopped early without getting close to the solution. In
addition, scores()
ignore now requests to dimensions beyond those
calculated instead of failing, and scores()
for metaMDS()
results
do not drop dimensions.
msoplot()
gained legend
argument for positioning the legend.
Nestedness function nestednodf()
gained a plot
method.
ordiR2step()
gained new argument R2scope
(defaults TRUE
) which
can be used to turn off the criterion of stopping when the adjusted
R2 of the current model exceeds that of the scope. This option
allows model building when the scope
would be overdetermined (number
of predictors higher than number of observations).
ordiR2step()
now handles partial redundancy analysis (pRDA).
orditorp()
gained argument select
to select the rows or columns of
the results to display.
protest()
prints the standardized residual statistic squared m12
in addition to the squared Procrustes correlation R2. Both
were calculated, but only the latter was displayed.
Permutation tests are much faster in protest()
. Instead of calling
repeatedly procrustes()
, the goodness of fit statistic is evaluated
within the function.
wcmdscale()
gained methods for print
, plot
etc. of the results.
These methods are only used if the full wcmdscale
result is returned
with, e.g., argument eig = TRUE
. The default is still to return only
a matrix of scores similarly as the standard R function
cmdscale()
, and in that case the new methods are not used.anova(<cca_object>, ...)
failed with by = "axis"
and by =
"term"
. The bug was reported by Dr Sven Neulinger (Christian Albrecht
University, Kiel, Germany).
radlattice
did not honour argument BIC = TRUE
, but always
displayed AIC.
density
method that can be used to find empirical probability distributions of
permutations. There is a new plot
method for these functions that
displays both the density and the observed statistic. The density
function is available for adonis
, anosim
, mantel
,
mantel.partial
, mrpp
, permutest.cca
and procrustes
.Function adonis
can return several statistics, and it has now a
densityplot
method (based on lattice).
Function oecosimu
already had density
and densityplot
, but they
are now similar to other vegan methods, and also work with adipart
,
hiersimu
and multipart
.
radfit
functions got a predict
method that also accepts arguments
newdata
and total
for new ranks and site totals for prediction.
The functions can also interpolate to non-integer “ranks”, and in some
models also extrapolate.Labels can now be set in the plot
of envfit
results. The labels
must be given in the same order that the function uses internally, and
new support function labels
can be used to display the default
labels in their correct order.
Mantel tests (functions mantel
and mantel.partial
) gained argument
na.rm
which can be used to remove missing values. This options
should be used with care: Permutation tests can be biased if the
missing values were originally in matching or fixed positions.
radfit
results can be consistently accessed with the same methods
whether they were a single model for a single site, all models for a
single site or all models for all sites in the data. All functions now
have methods AIC
, coef
, deviance
, logLik
, fitted
, predict
and residuals
.
Building of vegan vignettes failed with the latest version of LaTeX (TeXLive 2012).
R versions later than 2.15-1 (including development version)
report warnings and errors when installing and checking vegan, and you
must upgrade vegan to this version. The warnings concern functions
cIndexKM
and betadisper
, and the error occurs in betadisper
.
These errors and warnings were triggered by internal changes in R.
adipart
assumed constant gamma diversity in simulations when
assessing the P
-value. This could give biased results if the null
model produces variable gamma diversities and option weights =
"prop"
is used. The default null model ("r2dtable"
) and the default
option (weights = "unif"
) were analysed correctly.
anova(<prc-object>, by = "axis")
and other by
cases failed due to
‘NAMESPACE’ issues.
clamtest
wrongly used frequencies instead of the counts when
calculating sample coverage. No detectable differences were produced
when rerunning examples from Chazdon et al. 2011 and vegan help page.
envfit
failed with unused factor levels.
predict
for cca
results with type = "response"
or type =
"working"
failed with newdata
if the number of rows did not match
with the original data. Now the newdata
is ignored if it has a wrong
number of rows. The number of rows must match because the results in
cca
must be weighted by original row totals. The problem did not
concern rda
or capscale
results which do not need row weights.
Reported by Glenn De'ath.
adipart
, hiersimu
and
multipart
) have now formula
and default
methods. The formula
method is identical to the previous functions, but the default
method can take two matrices as input.Functions adipart
and multipart
can be used for fast and easy
overall partitioning to alpha, beta and gamma diversities by omitting
the argument describing the hierarchy.
The method in betadisper
is biased with small sample sizes. The
effects of the bias are strongest with unequal sample sizes. A bias
adjusted version was developed by Adrian Stier and Ben Bolker, and can
be invoked with argument bias.adjust
(defaults to FALSE
).
bioenv
accepts dissimilarities (or square matrices that can be
interpreted as dissimilarities) as an alternative to community data.
This allows using other dissimilarities than those available in
vegdist
.
plot
function for envfit
results gained new argument bg
that can
be used to set background colour for plotted labels.
msoplot
is more configurable, and allows, for instance, setting
y-axis limits.
Hulls and ellipses are now filled using semitransparent colours in
ordihull
and ordiellipse
, and the user can set the degree of
transparency with a new argument alpha
. The filled shapes are used
when these functions are called with argument draw = "polygon"
.
Function ordihull
puts labels (with argument label = TRUE
) now in
the real polygon centre.
ordiplot3d
returns function envfit.convert
and the projected
location of the origin
. Together these can be used to add envfit
results to existing ordiplot3d
plots.
Equal aspect ratio cannot be set exactly in ordiplot3d
because
underlying core routines do not allow this. Now ordiplot3d
sets
equal axis ranges, and the documents urge users to verify that the
aspect ratio is reasonably equal and the graph looks like a cube. If
the problems cannot be solved in the future, ordiplot3d
may be
removed from next releases of vegan.
ordipointlabel
gained argument to select
only some of the
items for plotting. The argument can be used only with one set of
points.Added new nestedness functions nestedbetasor
and nestedbetajac
that implement multiple-site dissimilarity indices and their
decomposition into turnover and nestedness components following
Baselga (Global Ecology and Biogeography 19, 134–143; 2010).
Added function rarecurve
to draw rarefaction curves for each row
(sampling unit) of the input data, optionally with lines showing
rarefied species richness with given sample size for each curve.
Added function simper
that implements “similarity percentages” of
Clarke (Australian Journal of Ecology 18, 117–143; 1993). The
method compares two or more groups and decomposes the average
between-group Bray-Curtis dissimilarity index to contributions by
individual species. The code was developed in
GitHub by Eduard Szöcs (Uni
Landau, Germany).
betadisper()
failed when the groups
was a factor with empty
levels.
Some constrained ordination methods and their support functions are
more robust in border cases (completely aliased effects, saturated
models, user requests for non-existng scores etc). Concerns
capscale
, ordistep
, varpart
, plot
function for constrained
ordination, and anova(<cca.object>, by = "margin")
.
The scores
function for monoMDS
did not honour choices
argument
and hence dimensions could not be chosen in plot
.
The default scores
method failed if the number of requested axes was
higher than the ordination object had. This was reported as an error
in ordiplot
in
R-sig-ecology
mailing list.
metaMDS
argument noshare = 0
is now regarded as a numeric
threshold that always triggers extended dissimilarities
(stepacross
), instead of being treated as synonymous with noshare =
FALSE
which always suppresses extended dissimilarities.
Nestedness discrepancy index nesteddisc
gained a new argument that
allows user to set the number of iterations in optimizing the index.
oecosimu
displays the mean of simulations and describes alternative
hypothesis more clearly in the printed output.
Implemented adjusted R2 for partial RDA. For partial model rda(Y ~
X1 + Condition(X2))
this is the same as the component [a] = X1|X2
in variance partition in varpart
and describes the marginal (unique)
effect of constraining term to adjusted R2.
Added Cao dissimilarity (CYd) as a new dissimilarity method in
vegdist
following Cao et al., Water Envir Res 69, 95–106 (1997).
The index should be good for data with high beta diversity and
variable sampling intensity. Thanks to consultation to Yong Cao (Univ
Illinois, USA).
Function capscale
failed if constrained component had zero rank.
This happened most likely in partial models when the conditions
aliased constraints. The problem was observed in anova(..., by
="margin")
which uses partial models to analyses the marginal
effects, and was reported in an email message to R-News mailing
list.
stressplot
and goodness
sometimes failed when metaMDS
was based
on isoMDS
(MASS package) because metaMDSdist
did not use the same
defaults for step-across (extended) dissimilarities as metaMDS(...,
engine = "isoMDS")
. The change of defaults can also influence
triggering of step-across in capscale(..., metaMDSdist = TRUE)
.
adonis
contained a minor bug resulting from incomplete
implementation of a speed-up that did not affect the results. In
fixing this bug, a further bug was identified in transposing the hat
matrices. This second bug was only active following fixing of the
first bug. In fixing both bugs, a speed-up in the internal f.test()
function is fully realised. Reported by Nicholas Lewin-Koh.
ordiarrows
and ordisegments
gained argument order.by
that gives
a variable to sort points within groups
. Earlier the points were
assumed to be in order.
Function ordispider
invisibly returns the coordinates to which the
points were connected. Typically these are class centroids of each
point, but for constrained ordination with no groups
they are the LC
scores.
clamtest
: new function to classify species as generalists and
specialists in two distinct habitats (CLAM test of Chazdon et al.,
Ecology 92, 1332–1343; 2011). The test is based on multinomial
distribution of individuals in two habitat types or sampling units,
and it is applicable only to count data with no over-dispersion.
as.preston
gained plot
and lines
methods, and as.fisher
gained
plot
method (which also can add items to existing plots). These are
similar as plot
and lines
for prestonfit
and fisherfit
, but
display only data without the fitted lines.
raupcrick
: new function to implement Raup-Crick dissimilarity as a
probability of number of co-occurring species with occurrence
probabilities proportional to species frequencies. Vegan has
Raup-Crick index as a choice in vegdist
, but that uses equal
sampling probabilities for species and analytic equations. The new
raupcrick
function uses simulation with oecosimu
. The function
follows Chase et al. (2011) Ecosphere 2:art24
[doi:10.1890/ES10-00117.1],
and was developed with the consultation of Brian Inouye.
Function meandist
could scramble items and give wrong results,
especially when the grouping
was numerical. The problem was reported
by Dr Miguel Alvarez (Univ. Bonn).
metaMDS
did not reset tries
when a new model was started with a
previous.best
solution from a different model.
Function permatswap
for community null models using quantitative
swap never swapped items in a 2x2 submatrix if all cells were
filled.
The result from permutest.cca
could not be update
d because of a
‘NAMESPACE’ issue.
R 2.14.0 changed so that it does not accept using sd()
function for matrices (which was the behaviour at least since R
1.0-0), and several vegan functions were changed to adapt to this
change (rda
, capscale
, simulate
methods for rda
, cca
and
capscale
). The change in R 2.14.0 does not influence the
results but you probably wish to upgrade vegan to avoid annoying
warnings.
nesteddisc
is slacker and hence faster when trying to optimize the
statistic for tied column frequencies. Tracing showed that in most
cases an improved ordering was found rather early in tries, and the
results are equally good in most cases.Peter Minchin joins the vegan team.
vegan implements standard R ‘NAMESPACE’. In general, S3
methods
are not exported which means that you cannot directly use or see
contents of functions like cca.default
, plot.cca
or
anova.ccabyterm
. To use these functions you should rely on R
delegation and simply use cca
and for its result objects use plot
and anova
without suffix .cca
. To see the contents of the function
you can use :::
, such as vegan:::cca.default
. This change may
break packages, documents or scripts that rely on non-exported names.
vegan depends on the permute package. This package provides powerful
tools for restricted permutation schemes. All vegan permutation will
gradually move to use permute, but currently only betadisper
uses
the new feature.
monoMDS
: a new function for non-metric multidimensional scaling
(NMDS). This function replaces MASS::isoMDS
as the default method in
metaMDS
. Major advantages of monoMDS
are that it has ‘weak’
(‘primary’) tie treatment which means that it can split tied
observed dissimilarities. ‘Weak’ tie treatment improves ordination of
heterogeneous data sets, because maximum dissimilarities of 1
can be
split. In addition to global NMDS, monoMDS
can perform local and
hybrid NMDS and metric MDS. It can also handle missing and zero
dissimilarities. Moreover, monoMDS
is faster than previous
alternatives. The function uses Fortran
code written by Peter
Minchin.
MDSrotate
a new function to replace metaMDSrotate
. This function
can rotate both metaMDS
and monoMDS
results so that the first axis
is parallel to an environmental vector.
eventstar
finds the minimum of the evenness profile on the Tsallis
entropy, and uses this to find the corresponding values of diversity,
evenness and numbers equivalent following Mendes et al. (Ecography
31, 450-456; 2008). The code was contributed by Eduardo Ribeira Cunha
and Heloisa Beatriz Antoniazi Evangelista and adapted to vegan by
Peter Solymos.
fitspecaccum
fits non-linear regression models to the species
accumulation results from specaccum
. The function can use new
self-starting species accumulation models in vegan or other
self-starting non-linear regression models in R. The function can
fit Arrhenius, Gleason, Gitay, Lomolino (in vegan), asymptotic,
Gompertz, Michaelis-Menten, logistic and Weibull (in base R)
models. The function has plot
and predict
methods.
Self-starting non-linear species accumulation models SSarrhenius
,
SSgleason
, SSgitay
and SSlomolino
. These can be used with
fitspecaccum
or directly in non-linear regression with nls
. These
functions were implemented because they were found good for
species-area models by Dengler (J. Biogeogr. 36, 728-744; 2009).
adonis
, anosim
, meandist
and mrpp
warn on negative
dissimilarities, and betadisper
refuses to analyse them. All these
functions expect dissimilarities, and giving something else (like
correlations) probably is a user error.
betadisper
uses restricted permutation of the permute package.
metaMDS
uses monoMDS
as its default ordination engine. Function
gains new argument engine
that can be used to alternatively select
MASS::isoMDS
. The default is not to use stepacross
with monoMDS
because its ‘weak’ tie treatment can cope with tied maximum
dissimilarities of one. However, stepacross
is the default with
isoMDS
because it cannot handle adequately these tied maximum
dissimilarities.
specaccum
gained predict
method which uses either linear or spline
interpolation for data between observed points. Extrapolation is
possible with spline interpolation, but may make little sense.
specpool
can handle missing values or empty factor levels in the
grouping factor pool
. Now also checks that the length of the pool
matches the number of observations.
metaMDSrotate
was replaced with MDSrotate
that can also handle the
results of monoMDS
.
permuted.index2
and other “new” permutation code was removed in
favour of the permute package. This code was not intended for normal
use, but packages depending on that code in vegan should instead
depend on permute.
treeheight
uses much snappier code. The results should be unchanged.Any scripts or data that you put into this service are public.
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