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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.
Null model analysis was upgraded:
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.
The 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.
Several vegan functions can now use parallel processing for slow
and repeating calculations. All these functions have argument
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.
All permutation tests are based on the permute package
which offers strong tools for restricted permutation. All these
functions have argument 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.
Community null model generation has been completely redesigned
and rewritten. The communities are constructed with new
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.
Most vegan functions with permutation tests have now a
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.
Functions for diversity partitioning (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.
Function 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
updated 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.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.