bipartite (version 0.74)

bipartite-package: Analysis of bipartite ecological webs.

Description

Bipartite provides functions to viualise webs and calculate a series of indices commonly used to describe pattern in ecological webs. It focusses on webs consisting of only two trophic levels, e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the webs topology.

encoding

latin1

versionlog

0.74 (release date: 24-Oct-2008) functional specialisation (functspec) bug fix{Paths were double the true length, hence minimum was 2, rather than 1.} H2fun bug fix{Since the search for H2min is heuristic, H2uncorr can sometimes be lower than H2min; in that case, H2fun returned a value greater 1, while it should be one exactly.} new function nestedness.corso{Calculates (weighted) nestedness according to Corso et al. (2008) and Galeano et al. (2008).} new function discrepancy{Calculates discrepancy according to Brualdi & Sanderson (1999), deemed to be best ever measure of nestedness; also gives an example for a binary null model analysis based on vegan's commsimulator.} other{Correction of several minor typos on the help pages; removal of "~" in help files; same citation style throughout; new cross references (especially for the nestedness functions); in networklevel, nestedness is now calculated using vegan's nestedtemp due to matrix inversion problems reported for binmatnest.} 0.73 (release date: 1-Sept-2008) new feature{plotweb}{Named abundance-vector for each level can be used.} new function plotweb2 (not debugged!){For plotting tripartite networks.} 0.72 (release date: 12-June-2008) new function: functional specialisation with functspec{See Dalgaard et al. (2008).} new function: interface to sna through as.one.mode{Allows calculation of path lengths, centrality, betweenness and other indices developed for one-mode networks.} bug-fix{Error in plotweb when no species labels were given.}

Details

We only had three types of bipartite webs in mind when writing this package: seed-disperser, plant-pollinator and predator-prey systems. In how far it makes sense to use these functionalities for other systems (or indeed for these systems) lies in the hands of the user. Please refer to the literature cited for details on the theory behind the indices. Input for most analyses is an interaction matrix of m higher level species with n lower level species, i.e. an n x m matrix, where higher trophic level species are in columns, lower level in rows. Column and row names can be provided. This is fundamentally different from multi-dimensional webs, which are organised as k x k matrix, i.e. each species against each other. Such a format is incompatible with the functions we provide here. The first step is to visualise the interaction web. Two functions are on offer here: one (visweb) simply plots the matrix in colours depicting the strength of an interaction and options for re-arranging columns and rows (e.g. to identify compartments or nesting). The other function (plotweb) plots the actual web with participants (as two rows of rectangles) connected by lines (proportional to interaction strength). The second step is to calculate various indices describing network topography. There are two different levels this can be achieved at: the entire web (using function networklevel) or the individual species (using function specieslevel). All other functions in the package are helpers, although some can be called on their own and return the respective result (dfun, H2fun and second.extinct with slope.bipartite). See function description for details and examples. ll{ Package: bipartite Type: Package Version: 0.73 Date: 2008-10-24 License: GPL }

References

Bascompte, J., Jordano, P. and Olesen, J. M. (2006) Asymmetric coevolutionary networks facilitate biodiversity maintenance. Science 312, 431--433 Bersier, L. F., Banasek-Richter, C. and Cattin, M. F. (2002) Quantitative descriptors of food-web matrices. Ecology 83, 2394--2407 Bl�thgen, N., Menzel, F. and Bl�thgen, N. (2006) Measuring specialization in species interaction networks. BMC Ecology 6, 12 Bl�thgen, N., Menzel, F., Hovestadt, T., Fiala, B. and Bl�thgen, N. (2007) Specialization, constraints, and conflicting interests in mutualistic networks. Current Biology 17, 1--6 Corso G., de Ara�jo A.I.L. and de Almeida A.M. (2008) A new nestedness estimator in community networks. arXiv, 0803.0007v1 [physics.bio-ph] Dalsgaard, B., A. M. Mart�n Gonz�lez, J. M. Olesen, A. Timmermann, L. H. Andersen, and J. Ollerton. (2008) Pollination networks and functional specialization: a test using Lesser Antillean plant-hummingbird assemblages. Oikos 117, 789--793 Galeano J., Pastor J.M. and Iriondo J.M. (2008) Weighted-Interaction Nestedness Estimator (WINE): A new estimator to calculate over frequency matrices. arXiv 0808.3397v1 [physics.bio-ph] Memmott, J., Waser, N. M. and Price, M. V. (2004) Tolerance of pollination networks to species extinctions. Proceedings of the Royal Society B 271, 2605--2611 Tylianakis, J. M., Tscharntke, T. and Lewis, O. T. (2007) Habitat modification alters the structure of tropical host-parasitoid food webs. Nature 445, 202--205 Vazquez, D. P. and Aizen, M. A. (2004) Asymmetric specialization: A pervasive feature of plant-pollinator interactions. Ecology 85, 1251--1257

Examples

data(Safariland)
plotweb(Safariland)
visweb(Safariland)
networklevel(Safariland)
specieslevel(Safariland)