Indicspecies R package  Indicator species are species that are used as ecological indicators of community or habitat types, environmental conditions, or environmental changes. In order to determine indicator species, the characteristic to be predicted is represented in the form of a classification of the sites, which is compared to the patterns of distribution of the species found in that set of sites. 'Indicspecies' is an R package that contains a set of functions to assess the strength of relationship between species and a classification of sites. As such, it includes the well-known IndVal method (Dufrêne & Legendre 1997) and extends it by allowing the user to study combinations of site groups (De Cáceres et al. 2010). Apart from the IndVal index, the package allows computing many other indices suitable for this kind of associations (De Cáceres & Legendre 2009), such as the phi coefficient of association. It is also possible to check the statistical significance of such associations. Download indicspecies (ver. 1.6.0) from CRAN. Authors: Miquel De Cáceres, Florian Jansen Vegclust R package Classifications of vegetation provide a way of summarizing our knowledge of vegetation patterns. They are a necessary tool for nature conservation, landscape mapping and land-use planning. As the basis of vegetation classification is mainly conventional, many methodological options are possible. Functions for fuzzy or hard clustering of vegetation data. At least four tasks are necessary in the management of vegetation classifications: (1) Assigning a meaningful vegetation type to the plant community observed in a sampled site; (2) Updating the current definition of vegetation types according to the new vegetation information collected; (3) Defining new vegetation types with those relevés that are considered to be very different to any of the available types; (4) Reviewing classifications generated by other means. The 'vegclust' package provides functions for maintaining plot-based community classifications using fuzzy clustering methods (De Cáceres et al. 2010). Three models are available: Fuzzy C-means, Noise Clustering and Possibilistic C-means. Resniche R package The niche concept underlies most ecological questions, from population growth and geographic expansion to community dynamics and ecosystem functioning. There is not one niche concept, but many, each of which emphasizes a different aspect of a species’ ecological characteristics. The species resource niche refers to the set of resources used by the species, such as food types. Resniche provides functions to estimate resource niche metrics performed on species preference data for a set of qualitative resources (De Cáceres et al. 2011). R package resniche (ver. 1.3): [Source code] [Windows binary] [Mac OS X binary]. Authors: Miquel De Cáceres STI R package In order to test hypotheses about changes in the environment induced by man ecologists are sampling portions of the environment repeatedly across time. STI implements a method for testing a space–time interaction in repeated ecological survey data, when there is no replication at the level of individual sampling units (sites) (Legendre et al. 2010). This methodological development is important for the analysis of long-term monitoring data. In these systems, an interaction may indicate that the spatial structure of community composition has changed in the course of time or that the temporal evolution is not the same at all sites. The solution to the problem that we suggest is based on the representation of space and time by principal coordinates of neighbor matrices (PCNM eigenfunctions) in the ANOVA. Function 'STImodels' performs two-way ANOVA to test space-time interaction without replicates using one among a set of possible models. Function 'quickSTI' allows performing space-time ANOVA in a simplified way. In many models, degrees of freedom are saved by coding space and/or time parsimoniously using principal coordinates of neighbour matrices (PCNM). R package STI (ver. 1.0.2): [Source code] [Windows binary] [Mac OS X binary]. Authors: Pierre Legendre, Miquel De Cáceres, Daniel Borcard. Beals smoothing is a multivariate transformation specially designed for species presence/absence community data containing noise and/or a lot of zeros. This transformation replaces the observed values of the target species by predictions of occurrence on the basis of its co-occurrences with the remaining species. In many applications, the transformed values are used as input for multivariate analyses. As Beals smoothing values provide a sense of ‘‘probability of occurrence’’, they have also been used for inference. However, this transformation can produce spurious results, and it must be used with caution. We include here a set of functions to conduct the transformation and to test its validity.
Authors: Miquel De Cáceres, Jari Oksanen Vegana
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 The VEGANA (VEGetation edition ANAlysis tools) package is a set of programs, written in Java language, that provide a platform for editing and analyzing community data. It is being developed at the Plant Biology Department of the Universitat de Barcelona (UB). VEGANA website: http://biodiver.bio.ub.es/vegana ARAUCARIA, is a tool for the automatic classification of vegetation data: http://biodiver.bio.ub.es/vegana/araucaria Other
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Recodifying and extension of MIPSIM package (Molecular Interaction Potential SIMilarity analysis) using FORTRAN and Java. Developed at the Institut Municipal d'Investigacions Mèdiques (IMIM): MIPSIM 1.2 manual. Java servlet programmer in project SCHIP: Statistics for Chromosome Interphase Positioning. A collaboration between the Departament d'Estadística of the Universitat de Barcelona and the University of California at San Francisco (UCSF): http://cramer.stat.ub.es/schip/. Other web portals I've been involved as a Java applet programmer are:
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