NEWS | R Documentation

## vegan News

### Changes in version 2.3-0

#### BUG FIXES

- 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.

#### WINDOWS

- `orditkplot` did not add file type identifier to saved graphics in Windows although that is required. The problem only concerned Windows OS.

#### NEW FEATURES AND FUNCTIONS

- `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.

### Changes in version 2.2-1

#### GENERAL

- This is a maintenance release to avoid warning messages caused by changes in CRAN repository. The namespace usage is also more stringent to avoid warnings and notes in development versions of R.

#### INSTALLATION

- vegan can be installed and loaded without tcltk package. The tcltk package is needed in `orditkplot` function for interactive editing of ordination graphics.

#### BUG FIXES

- `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.

#### NEW FEATURES

- `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), 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.

### Changes in version 2.2-0

#### GENERAL

- 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.

#### INSTALLATION

- 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.

#### NEW FUNCTIONS

- 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`.

#### BUG FIXES

- `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.

#### NEW FEATURES

- `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 online material 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 equation 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`.

#### DEPRECATED AND DEFUNCT

- `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.

### Changes in version 2.0-10

#### GENERAL

- This version is adapted to the changes in permute package version 0.8-0 and no more triggers NOTEs in package checks. This release may be the last of the 2.0 series, and the next vegan release is scheduled to be a major release with newly designed `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 R-Forge or GitHub and report the problems and user experience to us.

#### BUG FIXES

- `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.

#### NEW FEATURES

- The Kempton and Taylor algorithm was found unreliable in `fisherfit` and `fisher.alpha`, and now the estimation of Fisher alpha 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.

### Changes in version 2.0-9

- This version is released due to changes in programming interface and testing procedures in R 3.0.2. If you are using an older version of R, there is no need to upgrade vegan. There are no new features nor bug fixes. The only user-visible changes are in documentation and in output messages and formatting. Because of R changes, this version is dependent on R version 2.14.0 or newer and on lattice package.

### Changes in version 2.0-8

#### GENERAL

- This is a maintenance release that fixes some issues raised by changed in R toolset for processing vignettes. In the same we also fix some typographic issues in the vignettes.

#### NEW FEATURES

- `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.

### Changes in version 2.0-7

#### NEW FUNCTIONS

- `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.

#### BUG FIXES

- 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%).

#### NEW FEATURES

- 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`.

#### DEPRECATED

- The result objects of `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.

### Changes in version 2.0-6

#### BUG FIXES

- 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.

#### NEW FEATURES

- 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 R-squared 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 R-squared. 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.

### Changes in version 2.0-5

#### BUG FIXES

- `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.

#### NEW FUNCTIONS

- 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.

#### NEW FEATURES

- 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`.

#### INSTALLATION AND BUILDING

- 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.

### Changes in version 2.0-4

#### BUG FIXES

- `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.

#### NEW FEATURES

- 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.

### Changes in version 2.0-3

#### NEW FUNCTIONS

- 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).

#### BUG FIXES

- `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.

#### NEW FEATURES

- `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 R-squared 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 R-squared.

- 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).

### Changes in version 2.0-2

#### BUG FIXES

- 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.

#### NEW FEATURES

- `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.

### Changes in version 2.0-1

#### NEW FUNCTIONS

- `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.

#### BUG FIXES

- 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 2 by 2 submatrix if all cells were filled.

- The result from `permutest.cca` could not be `update`d because of a ‘NAMESPACE’ issue.

- R 2.14.0 changed so that it does not accept using `sd()` function for matrices (which was the behaviour at least since R 1.0-0), and several vegan functions were changed to adapt to this change (`rda`, `capscale`, `simulate` methods for `rda`, `cca` and `capscale`). The change in R 2.14.0 does not influence the results but you probably wish to upgrade vegan to avoid annoying warnings.

#### ANALYSES

- `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.

### Changes in version 2.0-0

#### GENERAL

- 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.

#### NEW FUNCTIONS

- `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).

#### NEW FEATURES

- `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.

#### DEPRECATED AND DEFUNCT

- `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.

#### ANALYSES

- `treeheight` uses much snappier code. The results should be unchanged.