Package 'cheddar'

Description

Functions that aggregate communities in a collection.

Usage

AggregateCommunities(collection, 
                     aggregate = names(collection), 
                     weight.by='N',
                     title = NULL)

AggregateCommunitiesBy(collection, aggregate.by, ...)

Arguments

Details

AggregateCommunities combines communities given in aggregate in to a single new Community.

Nodes that appear in one or more of the communities in aggregate are combined into a single node in the returned community. The way in which numeric node properties are aggregated is governed by the weight.by parameter. If weight.by is NULL or is not the name of a node property, the arithmetic mean is computed for each numeric node property. If weight.by is the name of a node property, that property is used to compute weighted means of the other numeric node properties; the arithmetic mean of weight.by is computed. This scheme means that if a community contains both N and M, aggregation using weight.by='N' results in the arithmetic mean of N and the N-weighted mean of M for each node. Node properties that are characters or logicals are aggregated by joining unique values with a ‘,’. Empty character strings are ignored. Species that are not present in some communities in the collection are assumed to have a value of 0 for all numeric node properties, an empty string ('') for all character node properties and a value of NA for all logical node properties.

The returned community contains the union of trophic links for each node. Community properties are aggregated by computing the arithmetic mean of numeric values and joining unique character and logical values with a ‘,’.

See the ‘Aggregating communities’ section of the ‘Collections’ vignette for a more detailed explanation and examples of how properties are aggregated.

AggregateCommunitiesBy aggregates by a property of the communities, either first-class or computed. If there is more than one unique value of the property across the contained communities, a new CommunityCollection object is returned. If there is just one unique value, a single Community is returned.

Value

A new object that is either of class Community or CommunityCollection.

Author(s)

Lawrence Hudson

See Also

CommunityCollection, CollectionCPS

Examples

data(pHWebs)

# An aggregate of 3 communities
AggregateCommunities(pHWebs, c('Old Lodge', 'Afon Hafren', 'Broadstone'))

# The Duddon Pike Beck and Mosedal Beck communities share the same 
# latitude and have pH values of 6.1 and 5.9 respectively.
CollectionCPS(pHWebs[c('Duddon Pike Beck', 'Mosedal Beck')])

# Aggregating by the 'lat' property therefore results in a new collection 
# of nine communities.
CollectionCPS(AggregateCommunitiesBy(pHWebs, 'lat'))

# Would produce an error
## Not run: AggregateCommunities(pHWebs, c('not a community', 'Afon Hafren'))

Description

Apply functions to a group of values given by a node property.

Usage

ApplyByClass(community, property, class, fn, ...)
SumMByClass(community, class, na.rm=FALSE)
SumNByClass(community, class, na.rm=FALSE)
SumBiomassByClass(community, class, na.rm=FALSE)

Arguments

Details

ApplyByClass applies fn to property by class. property and class should both be names that meet the criteria of the properties argument of NPS.

SumMByClass, SumNByClass and SumBiomassByClass are convenient wrapper around ApplyByClass.

Value

A vector or list of values, named by unique values of class.

Author(s)

Lawrence Hudson

See Also

Community, NPS

Examples

data(TL84)

# Sum body mass by category
ApplyByClass(TL84, 'M', 'category', sum)

# A more convenient way to sum body mass by category
SumMByClass(TL84)

# Sum body mass by kingdom. The 'Unclassified flagellates' node does not have a 
# kingdom, so we get a value labelled '<unnamed>'.
SumMByClass(TL84, 'kingdom')

# Maximum body mass by category
ApplyByClass(TL84, 'M', 'category', max)

# A list of min and max M
ApplyByClass(TL84, 'M', 'category', range)

# A list of min and max M by kingom
ApplyByClass(TL84, 'M', 'kingdom', range)

# The same values as a matrix
do.call('rbind', ApplyByClass(TL84, 'M', 'kingdom', range))

# Broadstone Stream has some nodes in every category without M so all returned 
# values are NA.
data(BroadstoneStream)
SumMByClass(BroadstoneStream)

# Get rid of the NA values
SumMByClass(BroadstoneStream, na.rm=TRUE)

Description

The food-web of the Benguela ecosystem.

Format

Community.

Source

Yodzis, 1988.

References

Yodzis, P. (1988) Local trophodynamics and the interaction of marine mammals and fisheries in the Benguela ecosystem. Journal of Animal Ecology 67, 4, 635–658.

Description

Convenience functions for accessing log10-transformed body mass, M, numerical abundance, N, and biomass abundance, B.

Usage

Log10M(community)
Log10N(community)
Biomass(community)
Log10Biomass(community)
Log10MNBiomass(community)

RCMRatio(community)
Log10RCMRatio(community)
CRMRatio(community)
Log10CRMRatio(community)

Arguments

Details

Log10M, Log10N, Biomass, Log10Biomass and each return a value per node. Log10MNBiomass returns a matrix with a row per node and columns ‘Log10M’, ‘Log10N’ and ‘Log10Biomass’. These functions are all suitable for use with NPS.

RCMRatio returns the ratio between the resource and consumer body mass for every trophic link. Log10RCMRatio returns the same data log10-transformed. CRMRatio and Log10CRMRatio are analagous functions that return the ratio between the consumer and resource body mass. These functions are all suitable for use with TLPS.

Value

A vector of length NumberOfNodes or a vector of length NumberOfTrophicLinks

Author(s)

Lawrence Hudson

See Also

NumberOfNodes, NPS, NumberOfTrophicLinks, TLPS

Examples

data(TL84)

NPS(TL84, c('M', 'Log10M', 'N', 'Log10N', 'Biomass', 'Log10Biomass'))

NPS(TL84, 'Log10MNBiomass')

TLPS(TL84, link.properties=c('Log10RCMRatio', 'Log10CRMRatio'))

Description

Function that assigns each node in a Community to a body-mass bin.

Usage

BodyMassBins(community, lower=min(NP(community,'M'), na.rm=TRUE), 
             upper=max(NP(community,'M'), na.rm=TRUE), n.bins=10)

Arguments

Details

Divides the range lower to upper in to n.bins equally-spaced log10(M) bins. Assigns each node in the community to one of these bins and returns the bins numbers. The returned vector has attributes bin.centres and breaks.

Value

A vector of length NumberOfNodes.

Author(s)

Lawrence Hudson

See Also

Community, NumberOfNodes

Examples

data(TL84)
BodyMassBins(TL84)

Description

The community of Broadstone Stream.

Taxonomic classification provided by Guy Woodward.

Format

Community.

Source

Woodward et al, 2005.

References

Woodward, G. and Speirs, D.C. and Hildrew, A.G. (2005) Quantification and resolution of a complex, size-structured food web. Advances in Ecological Research 36, 85–135.

Description

Cheddar provides a flexible, extendable representation of an ecological community and a range of functions for analysis and visualisation, focusing on food web, body mass and numerical abundance data. It also allows inter-web comparisons such as examining changes in community structure over environmental, temporal or spatial gradients.

Details of differences between versions of Cheddar are in the the online release history: https://github.com/quicklizard99/cheddar/blob/master/release_history.md.

Details

Author(s)

Maintainer: Lawrence Hudson <[email protected]>

Examples

# The dataset of Tuesday Lake sampled in 1984
data(TL84)

# Properties of the community
CPS(TL84)

# Properties of each node
head(NPS(TL84))

# Some computed node properties
head(NPS(TL84, c('Log10M', 'Log10N', 'Log10Biomass',
                 TL='PreyAveragedTrophicLevel', TS='TrophicSpecies')))

# Properties of each trophic link
head(TLPS(TL84))

# Computed properties of each node in each link
head(TLPS(TL84, node.properties=c('Log10M', 'Log10N', 'Log10Biomass',
                                  'PreyAveragedTrophicLevel')))


# A collection of 10 webs sampled across a wide pH gradient
data(pHWebs)

# A data.frame of predictors and responses
CollectionCPS(pHWebs, c('pH',
                        S='NumberOfNodes',
                        L='NumberOfTrophicLinks',
                        C='DirectedConnectance',
                        Slope='NvMSlope'))

Description

The community of Chesapeake Bay sampled in the years 1983 to 1986.

Format

Community.

Source

Baird and Ulanowicz, 1989; Bersier et al, 2002.

References

Bersier, L. and Banasek-Richter, C. and Cattin, M. (2002) Ecology 80 2394–2407.

Baird, D. and Ulanowicz. R. E. (1989) Ecological Monographs 59, 329–364.

Description

Apply a function to every Community in a CommunityCollection. Works the same as lapply but returns a CommunityCollection rather than a list.

Usage

CollectionApply(collection, f, ...)

Arguments

Value

A new object of class CommunityCollection.

Author(s)

Lawrence Hudson

See Also

CommunityCollection, lapply

Examples

data(pHWebs)

# Remove isolated nodes from each community
CollectionCPS(pHWebs, 'FractionIsolatedNodes')
pHWebs.no.iso <- CollectionApply(pHWebs, RemoveIsolatedNodes)
CollectionCPS(pHWebs.no.iso, 'FractionIsolatedNodes')


# Remove cannibalistic links from each community
sapply(pHWebs, function(community) length(Cannibals(community)))
pHWebs.no.can <- CollectionApply(pHWebs, RemoveCannibalisticLinks)
sapply(pHWebs.no.can, function(community) length(Cannibals(community)))


# Order the nodes each community by body mass
head(CollectionNPS(pHWebs))
pHWebs.by.M <- CollectionApply(pHWebs, OrderCommunity, 'M')
head(CollectionNPS(pHWebs.by.M))

Description

Returns a data.frame of first-class and computed properties of communities in a CommunityCollection.

Usage

CollectionCPS(collection, properties=NULL)

Arguments

Details

This function is named CollectionCPS for Collection Community PropertieS.

The properties argument is a vector whose entries are either names of first-class properties or names of functions which take as single required argument a CommunityCollection and return a single value. If properties is NULL, all first-class properties are included in the returned data.frame.

Value

A data.frame.

Author(s)

Lawrence Hudson

See Also

CPS, CommunityPropertyNames, CommunityCollection

Examples

data(pHWebs)

CollectionCPS(pHWebs)

# pH and a computed property
CollectionCPS(pHWebs, c('pH', 'NumberOfNodes'))

# A shorter name for the 'NumberOfNodes' column
CollectionCPS(pHWebs, c('pH', S='NumberOfNodes'))

# A function that returns more than one value. Some pHWebs communities contain 
# nodes (detritus and the like) that do not have a category. These appear in 
# <unnamed>.
CollectionCPS(pHWebs, 'SumBiomassByClass')

# Prefix columns with 'B'
CollectionCPS(pHWebs, c(B='SumBiomassByClass'))

# Remove biomasses of NA
CollectionCPS(pHWebs, list(B=list('SumBiomassByClass', na.rm=TRUE)))

Description

Returns a data.frame of first-class and computed node properties of communities in a CommunityCollection.

Usage

CollectionNPS(collection, properties=NULL)

Arguments

Details

This function is named CollectionNPS for Collection Node PropertieS. If properties is NULL, all first-class node properties are included in the returned data.frame.

Value

A data.frame.

Author(s)

Lawrence Hudson

See Also

NPS, CommunityCollection

Examples

data(pHWebs) 
head(CollectionNPS(pHWebs), 10)

head(CollectionNPS(pHWebs, 'M'), 10)

# Biomass is a function
head(CollectionNPS(pHWebs, 'Biomass'), 10)

head(CollectionNPS(pHWebs, c(B='Biomass')), 10)

# Several first-class and computed properties
head(CollectionNPS(pHWebs, c('M', 'N', B='Biomass', 'TrophicSpecies', 
                             TL='PreyAveragedTrophicLevel')), 10)

# Pass parameters to functions
head(CollectionNPS(pHWebs, 
                   list(TS1='TrophicSpecies', 
                        TS2=list('TrophicSpecies', include.isolated=FALSE), 
                        Iso='IsIsolatedNode')), 10)

Description

Returns a data.frame of first-class and computed trophic-link properties of communities in a CommunityCollection.

Usage

CollectionTLPS(collection, node.properties=NULL, link.properties=NULL)

Arguments

Details

This function is named CollectionTLPS for Collection Trophic Link PropertieS. It returns a data.frame containing the columns ‘resource’ and ‘consumer’ and any requested node and trophic-link properties. If node.properties and link.properties are both NULL then all first-class trophic-link properties are included in the returned data.frame.

Value

A data.frame.

Author(s)

Lawrence Hudson

See Also

TLPS, CommunityCollection

Examples

data(pHWebs)

# Just community, resource and consumer
head(CollectionTLPS(pHWebs), 10)

# The M of the resource and consumer in each link
head(CollectionTLPS(pHWebs, node.properties='M'), 10)

Description

Creates and returns a new object that represents an ecological community.

Usage

Community(nodes, properties, trophic.links = NULL)
## S3 method for class 'Community'
print(x, ...) 
## S3 method for class 'Community'
plot(x, ...) 
## S3 method for class 'Community'
summary(object, ...)

Arguments

Details

The most convenient way to import community data in to Cheddar is to put data in to CSV files and use the LoadCommunity function.

Many of Cheddar's plot and analysis functions make use of the ‘category’ node property by default, following previously-used metabolic groupings (Yodzis and Innes, 1992). The column nodes$category is optional but, if given, it should contain one of ‘producer’, ‘invertebrate’, ‘vert.ecto’, ‘vert.endo’ or should be an empty string.

Community supports standard generic functions plot, print, and summary.

Value

A new object of class Community.

Author(s)

Lawrence Hudson

References

Yodzis, P. and Innes, S. (1992) Body size and resource-consumer dynamics. The American Naturalist 139, 1151–1175.

See Also

CPS, NPS, TLPS, LoadCommunity SaveCommunity

Examples

data(TL84)
TL84

# Node properties
NPS(TL84)

# Trophic-link properties
TLPS(TL84)

# Eyeball the data
plot(TL84)

# A different plot function
PlotWebByLevel(TL84)

# Construct a new community.
# TL84.new is an exact copy of TL84
TL84.new <- Community(properties=CPS(TL84), 
                      nodes=NPS(TL84),
                      trophic.links=TLPS(TL84))
identical(TL84, TL84.new)

# A copy of TL84 without trophic links
TL84.no.links <- Community(properties=CPS(TL84), 
                           nodes=NPS(TL84))
NumberOfTrophicLinks(TL84.no.links)

# A community with 10 species and no properties
test <- Community(nodes=data.frame(node=paste('Species', 1:10)), 
                  properties=list(title='Test community'))
test
NPS(test)

Description

Functions that return whether or not a community has a particular property.

Usage

HasM(community)
HasN(community)
HasTrophicLinks(community)

Arguments

Value

A logical.

Author(s)

Lawrence Hudson

See Also

Community, CPS, NPS, TLPS

Examples

# Tuesday Lake 1984 has all three
data(TL84)
HasM(TL84)
HasN(TL84)
HasTrophicLinks(TL84)

# Skipwith Pond has trophic links but not M or N
data(SkipwithPond)
HasM(SkipwithPond)
HasN(SkipwithPond)
HasTrophicLinks(SkipwithPond)

Description

Collections of communities

Usage

CommunityCollection(communities)
## S3 method for class 'CommunityCollection'
print(x, ...) 
## S3 method for class 'CommunityCollection'
plot(x, ncol=min(length(x),5), by.col=TRUE, 
     plot.fn=plot, ...)
## S3 method for class 'CommunityCollection'
summary(object, ...)

Arguments

Details

Constructs a new CommunityCollection from a list of existing Community objects. CommunityCollection is a subclass of list. CommunityCollection objects can not be modified directly.

An error is raised if any Community objects in communities share the same ‘title’ community property. An error is also raised if the Community objects in communities do not all have the same value of the community properties ‘M.units’ and ‘N.units’. CommunityCollection places no restrictions on other properties. For example, all of the ten communities with the pHWebs collection has a valid pH property but this is not enforced by CommunityCollection - it would be possible for a Community within a collection to not have a pH property, to have a pH of NA or even to have an invalid pH, for example a negative value.

CommunityCollection supports standard generic functions plot, print, subset and summary.

Value

A new object of class CommunityCollection.

Author(s)

Lawrence Hudson

See Also

Community, CollectionCPS CollectionNPS CollectionTLPS, OrderCollection, subset.CommunityCollection, AggregateCommunitiesBy, AggregateCommunities, pHWebs

Examples

# 10 stream webs sampled over a wide pH gradient
data(pHWebs)
pHWebs


# Eyeball the webs
plot(pHWebs)

# Consistent axis limits
plot(pHWebs, xlim=c(-14,6), ylim=c(-3,13))

# Different plot function
plot(pHWebs, plot.fn=PlotWebByLevel, ylim=c(1,4.5))


# list-like operations
length(pHWebs)
sapply(pHWebs, 'NumberOfTrophicLinks')
pHWebs[['Broadstone']]  # Access the Community

# A new CommunityCollection containing every other ph web
pHWebs[seq(1, 10, by=2)]

# A new CommunityCollection containing two webs
pHWebs[c('Old Lodge','Bere Stream')]


# CollectionCPS gets community properties
CollectionCPS(pHWebs)   # Webs are sorted by increasing pH

# Order by decreasing pH
pHWebs.decreasing.pH <- OrderCollection(pHWebs, 'pH', decreasing=TRUE)
CollectionCPS(pHWebs.decreasing.pH)

# Order by name
pHWebs.name <- OrderCollection(pHWebs, 'title')
CollectionCPS(pHWebs.name, c('pH', 'NumberOfNodes'))

# The following will always be TRUE.
all(FALSE==duplicated(names(pHWebs)))


# A new collection of the two Tuesday Lake communities
data(TL84, TL86)
BothTL <- CommunityCollection(list(TL84, TL86))
CollectionCPS(BothTL)


# You can't modify CommunityCollections
## Not run: pHWebs[1] <- 'silly'

Description

Returns a vector of names of community properties.

Usage

CommunityPropertyNames(community)

Arguments

Value

A vector of names of community properties.

Author(s)

Lawrence Hudson

See Also

Community, CP, CPS

Examples

data(TL84)
CommunityPropertyNames(TL84)

Description

Returns a single community property or NA if property is not in CommunityPropertyNames.

Usage

CP(community, property)

Arguments

Details

This function is named CP for Community Property.

Value

A single community property.

Author(s)

Lawrence Hudson

See Also

Community, CPS, CommunityPropertyNames

Examples

data(TL84)
CP(TL84, 'title')

CP(TL84, 'lat')

CP(TL84, 'M.units')

# Returns a vector of NA
CP(TL84, 'not a property')

Description

Returns a list of first-class and computed community properties.

Usage

CPS(community, properties = NULL)

Arguments

Details

This function is named CPS for Community PropertieS. If properties is NULL, all properties are returned. If properties is not NULL then a list containing that subset of community properties is returned. Elements will be NA for values of property not in CommunityPropertyNames.

Value

A list.

Author(s)

Lawrence Hudson

See Also

Community, CP, CommunityPropertyNames

Examples

data(TL84)

# All properties
CPS(TL84)

# Just lat and long
CPS(TL84, c('lat', 'long'))

# lat and long and number of nodes
CPS(TL84, c('lat', 'long', 'NumberOfNodes'))

# lat and long and number of nodes, renamed
CPS(TL84, c('lat', 'long', S='NumberOfNodes'))

# 'not a property' is NA
CPS(TL84, c('lat', 'long', S='NumberOfNodes', 'not a property'))

Description

The number of trophic links in to and out of nodes in a Community.

Usage

Degree(community)
InDegree(community)
TrophicGenerality(community)
NumberOfResources(community)
OutDegree(community)
TrophicVulnerability(community)
NumberOfConsumers(community)

NormalisedTrophicGenerality(community)
NormalisedTrophicVulnerability(community)

Arguments

Details

InDegree and OutDegree return the number of trophic links in-to and out-of each node. Degree returns InDegree + OutDegree. TrophicGenerality and NumberOfResources are synonyms for InDegree. TrophicVulnerability and NumberOfResources are synonyms for OutDegree.

NormalisedTrophicGenerality and NormalisedTrophicVulnerability return the containing the number of resources and consumer of each node, normalised with respect to LinkageDensity. The mean of the values returned by both NormalisedTrophicGenerality and NormalisedTrophicVulnerability is 1, making their standard deviations comparable across different food webs.

Value

A vector of length NumberOfNodes.

Author(s)

Lawrence Hudson

References

Williams, R.J. and Martinez, N.D. (2000) Simple rules yield complex food webs. Nature 404, 180–183.

See Also

Community, NumberOfNodes, LinkageDensity, DirectedConnectance, DegreeDistribution

Examples

data(TL84)

d <- Degree(TL84)
i <- InDegree(TL84)
o <- OutDegree(TL84)

# This equality is always TRUE for all food webs
all(d == i+o)

ntg <- NormalisedTrophicGenerality(TL84)
mean(ntg)    # Equals 1
ntv <- NormalisedTrophicVulnerability(TL84)
mean(ntv)    # Equals 1

Description

Node degree distribution.

Usage

DegreeDistribution(community, cumulative=FALSE)

Arguments

Details

Returns a vector of proportions of nodes with 0:max(Degree(community)) trophic links.

Value

A vector of numbers.

Author(s)

Lawrence Hudson

See Also

Degree, PlotDegreeDistribution

Examples

data(TL84)
DegreeDistribution(TL84)
DegreeDistribution(TL84, cumulative=TRUE)

Description

Functions for computing the sum diet/consumer gaps of each species in a Community and for minimising the sum diet/consumer gaps using a simulated annealing learning method.

Usage

SumDietGaps(community)
SumConsumerGaps(community)

MinimiseSumDietGaps(community, T.start = 10, T.stop = 0.1, c = 0.9, 
                    swaps.per.T = 1000, trace.anneal = FALSE, n = 1, 
                    best = TRUE)
MinimiseSumConsumerGaps(community, T.start = 10, T.stop = 0.1, c = 0.9, 
                        swaps.per.T = 1000, trace.anneal = FALSE, n = 1, 
                    best = TRUE)

Arguments

Details

SumDietGaps and SumConsumerGaps return the total number of gaps in each species' diet (Stouffer et al 2006) and each species' consumers (Zook et al 2011) respectively.

MinimiseSumDietGaps and MinimiseSumConsumerGaps use the simulated annealing learning method described by Stouffer et al (2006) to minimise either SumDietGaps or SumConsumerGaps. Simulated annealing learning is a stochastic method so several optimisations might be required to find the global minimum. Use a value of n greater than 1 to perform several optimisations.

Value

For SumDietGaps and SumConsumerGaps, a single number. For the two minimisation functions, if n is 1 or best is TRUE, a list containing the values

If n is greater than 1 and best is FALSE then a list of n lists, each list containing the above three values, sorted by increasing sum.gaps.

Author(s)

Lawrence Hudson

References

Stouffer, D.B. and Camacho, J. and Amaral, L.A.N. (2006) Proceedings of the National Academy of Sciences of the United States of America 103, 50, 19015–19020.

Zook, A.E. and Eklof, A. and Jacob, U. and Allesina, S. (2011) Journal of Theoretical Biology 271, 1 106–113.

See Also

Community, OrderCommunity, PredationMatrix, PlotPredationMatrix

Examples

data(TL84)
# Perform 5 independent optimisations
res <- MinimiseSumDietGaps(TL84, n=5)

# Compare the original, ordered by body mass and minimised predation matrices
par(mfrow=c(1,3))
PlotPredationMatrix(TL84, main=paste('Sum diet gap', SumDietGaps(TL84)))
TL84.by.M <- OrderCommunity(TL84, 'M')
PlotPredationMatrix(TL84.by.M, 
                    main=paste('Sum diet gap', SumDietGaps(TL84.by.M)))
PlotPredationMatrix(res$reordered, main=paste('Sum diet gap', res$sum.gaps))

# The same comparison but retaining the original column ordering
par(mfrow=c(1,3))
PlotPredationMatrix(TL84)
PlotPredationMatrix(TL84, resource.order=NP(TL84.by.M, 'node'))
PlotPredationMatrix(TL84, resource.order=res$order)

Description

Nodes that consume themselves in the food web.

Usage

IsCannibal(community)
Cannibals(community)
FractionCannibalistic(community)

Arguments

Details

IsCannibal returns a vector of logical of length NumberOfNodes; values are TRUE for nodes consume themselves. Cannibals returns the names of nodes for which IsCannibals returns TRUE. FractionCannibalistic returns the proportion of nodes for which IsCannibal returns TRUE

Value

Either a logical vector of length NumberOfNodes or a vector of names.

Author(s)

Lawrence Hudson

See Also

RemoveCannibalisticLinks, NumberOfNodes, PredationMatrix, Degree, InDegree, OutDegree, ResourcesByNode, ConsumersByNode, ResourcesOfNodes, ConsumersOfNodes

Examples

data(TL84)

IsCannibal(TL84)
Cannibals(TL84)
FractionCannibalistic(TL84)

Description

Fit linear regressions to node data by class.

Usage

LinearRegressionByClass(community, X, Y, class)

Arguments

Details

A linear model is fitted through all data points and through each subset of the data given by class. A list of lm objects is returned. The list will contain NULL if it is not possible to fit a linear regression to that class; this will happen for classes that contain just a single node or that contain all or all but one nodes where X and/or Y is NA.

Value

A list of lm objects.

Author(s)

Lawrence Hudson

See Also

Community, ApplyByClass, NPS, NvMLinearRegressions, lm

Examples

data(TL84)

# Regressions fitted to log10(Biomass) versus log10(M) data.
models <- LinearRegressionByClass(TL84, 'Log10M', 'Log10Biomass', 
                                  'category')

# 'all', 'producer', 'invertebrate', 'vert.ecto'
names(models)

# Extract slopes and intercepts
sapply(models, coef)

Description

LoadCollection and SaveCollection are functions for loading and saving CommunityCollection objects to text files.

Usage

LoadCollection(dir, ...)
SaveCollection(collection, dir, ...)

Arguments

Details

The Community objects in collection are saved to a directory named communities inside dir. The order of the collection is not saved. Any existing data in dir is ignored.

Value

LoadCollection returns a new CommunityCollection.

Author(s)

Lawrence Hudson

See Also

CommunityCollection, OrderCollection, LoadCommunity, SaveCommunity

Examples

data(pHWebs)
temp.path <- tempfile()
SaveCollection(pHWebs, temp.path)
pHWebs.loaded <- LoadCollection(temp.path)
pHWebs.loaded <- OrderCollection(pHWebs.loaded, 'pH')
unlink(temp.path, recursive=TRUE)
identical(pHWebs, pHWebs.loaded)    # TRUE

Description

LoadCommunity and SaveCommunity are functions for loading and saving Community objects to CSV files.

Usage

LoadCommunity(dir, fn='read.csv', ...)
SaveCommunity(community, dir, fn='write.csv', na='', ...)

Arguments

Details

Data are stored in CSV (Comma-Separated Value) files in dir. Properties of any aspect of the community (nodes, links or the whole community) can be added simply by adding columns to the relevant CSV file. The data-quality checks defined by Community are applied by LoadCommunity. The fn and dots arguments can be used to read/write files in a range of formats.

properties.csv defines items applicable to the community as a whole, such as sampling date, lat & long or altitude and environmental variables such as temperature or pH. This file must contain a column called ‘title’.

nodes.csv should contain the list of nodes and together with any associated properties such as mean body mass, mean numerical abundance and classification. This file must contain a column called ‘node’ that must contain node names. Many of Cheddar's plot and analysis functions make use of the ‘category’ node property by default, following previously-used metabolic groupings (Yodzis & Innes, 1992). The ‘category’ column of nodes.csv is optional but, if given, it should contain one of ‘producer’, ‘invertebrate’, ‘vert.ecto’, ‘vert.endo’ or should be an empty string.

trophic.links.csv is optional. It defines trophic links in columns ‘resource’ and ‘consumer’, which should be names of nodes. Properties of trophic links such as evidence for the presence of the link (e.g. empirically observed or inferred from literature) can be added to this file.

Value

LoadCommunity returns a new Community.

Author(s)

Lawrence Hudson

References

Yodzis, P. and Innes, S. (1992) Body size and resource-consumer dynamics. The American Naturalist 139, 1151–1175.

See Also

Community, read.csv, write.csv

Examples

data(TL84)
temp.path <- tempfile()
SaveCommunity(TL84, temp.path)
TL84.loaded <- LoadCommunity(temp.path)
unlink(temp.path, recursive=TRUE)
identical(TL84, TL84.loaded)    # TRUE

Description

A function that lumps together nodes in a Community.

Usage

LumpNodes(community, 
          lump, 
          title = NULL, 
          weight.by = 'N')

Arguments

Details

If weight.by is not NULL and it is the name of a node property, it is used to compute weighted means of all the other numeric node properties. The arithmetic mean of weight.by is computed. If weight.by is NULL or is not the name of a node property, the arithmetic mean is computed for each numeric node property. Node properties that are characters or logicals are aggregated by joining unique values with a ‘,’. Empty character strings are ignored.

Value

A new object of class Community.

Author(s)

Lawrence Hudson

See Also

LumpTrophicSpecies, IsIsolatedNode, IsolatedNodes, NPS, weighted.mean

Examples

data(TL84)

# Lump together isolated nodes in TL84
length(which(IsIsolatedNode(TL84)))  # 6 isolated species
IsolatedNodes(TL84)                  # Names of isolated nodes

lump <- NP(TL84, 'node')             # Existing node names

# Give isolated nodes the same lump value
lump[IsolatedNodes(TL84)] <- 'Isolated nodes lumped together'
TL84.lumped <- LumpNodes(TL84, lump)

NumberOfNodes(TL84)         # 56 nodes in unlumped web
NumberOfNodes(TL84.lumped)  # 51 nodes in lumped web

IsolatedNodes(TL84.lumped)  # A single node


# This trivial example shows that no nodes are lumped if values in lump are 
# unique to each node
lump <- NP(TL84, 'node')
identical(TL84, LumpNodes(TL84, lump, title=CP(TL84, 'title')))


# Ythan Estuary contains two species that are split in to adult and 
# juvenile forms. The example below lumps these in to single species.
data(YthanEstuary)

# The names of nodes in YthanEstuary
lump <- NP(YthanEstuary, 'node')

# European flounder:
# "Platichthys flesus" and "Platichthys flesus (juvenile)"
# Lump these in to one node
lump["Platichthys flesus (juvenile)"==lump] <- "Platichthys flesus"

# Common eider:
# "Somateria mollissima" and "Somateria mollissima (juvenile)"
# Lump these in to one node
lump["Somateria mollissima (juvenile)"==lump] <- "Somateria mollissima"
YthanEstuary.lumped <- LumpNodes(YthanEstuary, lump)


# Examine the computed means for Somateria mollissima
# Arithmetic mean of N is 2592
NP(YthanEstuary.lumped, 'N')['Somateria mollissima']
mean(NP(YthanEstuary, 'N')[c("Somateria mollissima (juvenile)", 
                             "Somateria mollissima")])

# N-weighted mean of M is 1637.018
NP(YthanEstuary.lumped, 'M')['Somateria mollissima']
weighted.mean(NP(YthanEstuary, 'M')[c("Somateria mollissima (juvenile)", 
                                    "Somateria mollissima")], 
              NP(YthanEstuary, 'N')[c("Somateria mollissima (juvenile)", 
                                    "Somateria mollissima")], )


# Plot the original community and the community with lumped nodes
par(mfrow=c(1,2))
plot(YthanEstuary, highlight.nodes=c("Platichthys flesus", 
                                     "Platichthys flesus (juvenile)", 
                                     "Somateria mollissima", 
                                     "Somateria mollissima (juvenile)"))
plot(YthanEstuary.lumped, highlight.nodes=c("Platichthys flesus", 
                                            "Somateria mollissima"))

Description

Lump trophic species.

Usage

LumpTrophicSpecies(community, include.isolated=TRUE, title=NULL, ...)

Arguments

Details

Aggregates nodes that share identical sets of prey and predators.

Value

A Community.

Author(s)

Lawrence Hudson

References

Briand, F and Cohen, J.E. 1984 Community food webs have scale-invariant structure Nature 307, 264–267.

Jonsson, T. and Cohen, J.E. and Carpenter, S. R. 2005 Food webs, body size, and species abundance in ecological community description. Advances in Ecological Research 36, 1–84.

Pimm, S.L. and Lawton, J.H. and Cohen, J.E. 1991 Food web patterns and their consequences Nature 350, 669–674.

Williams, R.J. and Martinez, N.D. 2000 Simple rules yield complex food webs 404, 180–183.

See Also

TrophicSpecies, LumpNodes, IsIsolatedNode

Examples

data(TL84)
NumberOfNodes(TL84)

TL84.lumped <- LumpTrophicSpecies(TL84)

length(unique(TrophicSpecies(TL84)))    # 22 trophic species in TL84...
NumberOfNodes(TL84.lumped)              # ... and 22 nodes in the lumped web

Description

The control and drought treatments from one of the four replicates from a long-running study of the effects of drought on community structure.

Taxonomic classification provided by Mark Ledger.

Format

CommunityCollection.

Source

Ledger et al, 2011; Ledger et al, 2012; Woodward et al 2012.

References

Ledger, M.E. and Edwards, F.K. and Brown, L.E. and Milner, A.M. and Woodward, G. (2011) Impact of simulated drought on ecosystem biomass production: an experimental test in stream mesocosms. Global Change Biology 17, 7, 2288–2297.

Ledger, M.E., and Brown, L.E., and Edwards, F.K. and Milner, A.M. and Woodward, G. (2012) Drought alters the structure and functioning of complex food webs. Nature Climate Change 2, 9, 1–5.

Woodward, G. and Brown, L.E and Edwards, F. and Hudson, L.N. and Milner, A.M. and Reuman, D.C. and Mark E.L. (2012) Climate change impacts in multispecies systems: drought alters food web size-structure in a field experiment. Philosophical Transactions of the Royal Society B: Biological Sciences.

Description

Functions that report the connectivity of nodes in a food web.

Usage

IsBasalNode(community)
IsTopLevelNode(community) 
IsIntermediateNode(community) 
IsIsolatedNode(community) 
IsConnectedNode(community) 
IsNonBasalNode(community) 
IsNonTopLevelNode(community) 

BasalNodes(community)
TopLevelNodes(community) 
IntermediateNodes(community) 
IsolatedNodes(community) 
ConnectedNodes(community)
NonTopLevelNodes(community) 
NonBasalNodes(community)

FractionBasalNodes(community)
FractionIntermediateNodes(community)
FractionTopLevelNodes(community)
FractionIsolatedNodes(community)
FractionNonBasalNodes(community)
FractionConnectedNodes(community)
FractionNonTopLevelNodes(community)

Arguments

Details

Each node in a community is defined as:

These definitions allow the following additional definitions:

For each of the above seven definitions, ‘X’, there are three functions: IsX, X and FractionX. The first returns a vector of logical of length NumberOfNodes; values are TRUE for nodes that fit the definition of ‘X’. The second returns the names of nodes for which IsX returns TRUE. The third returns the proportion of nodes in the community that fit the definition of ‘X’.

Value

Either a logical vector of length NumberOfNodes or a vector of names.

Author(s)

Lawrence Hudson

See Also

NumberOfNodes, Cannibals, IsCannibal, NumberOfTrophicLinks, PredationMatrix, Degree, InDegree, OutDegree, ResourcesByNode, ConsumersByNode, ResourcesOfNodes, ConsumersOfNodes

Examples

data(TL84)

# Assemble a table of node connectivity. Only one of each of the following 
# four properties is TRUE for each node.
connectivity <- NPS(TL84, c('IsBasalNode', 'IsIsolatedNode', 
                            'IsIntermediateNode', 'IsTopLevelNode'))
connectivity

# Each row sums to 1, confirming that exactly one of the columns in each row 
# is TRUE.
all(1==rowSums(connectivity))

# These summations are 1
sum(FractionBasalNodes(TL84), 
    FractionIntermediateNodes(TL84), 
    FractionTopLevelNodes(TL84), 
    FractionIsolatedNodes(TL84))

sum(FractionConnectedNodes(TL84), 
    FractionIsolatedNodes(TL84))

sum(FractionBasalNodes(TL84), 
    FractionNonBasalNodes(TL84))

sum(FractionTopLevelNodes(TL84), 
    FractionNonTopLevelNodes(TL84))

Description

Node name indices.

Usage

NodeNameIndices(community, nodes)

Arguments

Details

Returns integer indices of names in nodes.

Value

A vector of integers

Author(s)

Lawrence Hudson

See Also

Community

Examples

data(TL84)

NodeNameIndices(TL84, 'Umbra limi')
NodeNameIndices(TL84, c('Nostoc sp.','Umbra limi'))

Description

Returns a vector of names of node properties.

Usage

NodePropertyNames(community)

Arguments

Value

A vector of the names of node properties.

Author(s)

Lawrence Hudson

See Also

NP, NPS

Examples

data(TL84) 
NodePropertyNames(TL84)

Description

Returns a node property.

Usage

NP(community, property)

Arguments

Details

This function is named NP for Node Property. It returns a vector containing the value of property for every node. The returned vector is named by node. If the name is not a property, a vector of NA is returned.

Value

A vector of length NumberOfNodes.

Author(s)

Lawrence Hudson

See Also

NPS, NumberOfNodes

Examples

data(TL84)

NP(TL84, 'M')

# Returns a vector of NA
NP(TL84, 'not a property')

Description

Returns a data.frame of first-class and computed node properties.

Usage

NPS(community, properties = NULL)

Arguments

Details

This function is named NPS for Node Properties. It returns a data.frame containing the column ‘node’ and any requested properties. If properties is NULL, all first-class node properties are included in the returned data.frame.

properties should be either a vector or a list that contains either names of first class properties, names of functions that take only a community or lists in which the first element is the name of a function that takes a community and subsequent elements are named arguments to that function. Names of properties are column names in the returned data.frame.

Value

A data.frame with NumberOfNodes rows.

Author(s)

Lawrence Hudson

See Also

NP, NumberOfNodes

Examples

data(TL84) 
NPS(TL84) 

NPS(TL84, 'M') 

# Biomass is a function
NPS(TL84, 'Biomass') 

NPS(TL84, c(B='Biomass'))

# Several first-class and computed properties
NPS(TL84, c('M', 'N', B='Biomass', 'TrophicSpecies', 
            TL='PreyAveragedTrophicLevel'))

# Pass parameters to functions
NPS(TL84, list(TS1='TrophicSpecies', 
               TS2=list('TrophicSpecies', include.isolated=FALSE), 
               Iso='IsIsolatedNode'))

Description

Functions that return the number of nodes in the community.

Usage

NumberOfNodes(community)
NumberOfNodesByClass(community, class)
FractionOfNodesByClass(community, class)

Arguments

Value

NumberOfNodes returns a single number. NumberOfNodesByClass and FractionOfNodesByClass both return a value for each class.

Author(s)

Lawrence Hudson

See Also

Community, NPS

Examples

data(TL84)
NumberOfNodes(TL84)
NumberOfNodesByClass(TL84)
FractionOfNodesByClass(TL84)

Description

The number of trophic links in Community.

Usage

NumberOfTrophicLinks(community) 
LinkageDensity(community) 
DirectedConnectance(community)

Arguments

Details

NumberOfTrophicLinks returns the total number of links in the web, including cannibalistic links.

LinkageDensity returns the NumberOfTrophicLinks / NumberOfNodes, including cannibalistic links and isolated nodes.

DirectedConnectance returns NumberOfTrophicLinks / NumberOfNodes^2, including cannibalistic links and isolated nodes.

Value

A single number.

Author(s)

Lawrence Hudson

References

Martinez, N. D. 1991 Artifacts or attributes? Effects of resolution on the Little Rock Lake food web. Ecological Monographs 61, 367–392.

See Also

NumberOfNodes

Examples

data(TL84)

NumberOfTrophicLinks(TL84)
LinkageDensity(TL84)
DirectedConnectance(TL84)

Description

Compute the convex hull around log-transformed $N$ versus $M$ data.

Usage

NvMConvexHull(community)

Arguments

Details

Returns the points and area of the minimum convex hull (a polygon in log10-transformed numerical abundance versus log10-transformed body mass space) that bounds all the species within the community.

Value

A list containing the values

Author(s)

Lawrence Hudson

References

Leaper, R. and Raffaelli, D. (1999) Defining the abundance body-size constraint space: data from a real food web. Ecology Letters 2, 3, 191–199.

See Also

Community, PlotNvM, chull

Examples

data(TL84)

# Compute convex hull
convex.hull <- NvMConvexHull(TL84)

# The nodes that form the hull
convex.hull$nodes

# The area of the hull
convex.hull$area

# Plot the hull in red around the nodes
PlotNvM(TL84)
polygon(convex.hull$points, lwd=2, border='red')

Description

Creation and analysis of linear regressions fitted to log10- transformed numerical abundance versus log10-transformed body mass.

Usage

NvMLinearRegressions(community, class)

NvMSlope(community)
NvMIntercept(community)
NvMSlopeAndIntercept(community)

NvMSlopeByClass(community, class)
NvMInterceptByClass(community, class)
NvMSlopeAndInterceptByClass(community, class)

Arguments

Value

NvMLinearRegressions returns a list of lm objects, one for each class and one fitted to all data. The list will contain NULL if it is not possible to fit a linear regression to that class; this will happen for classes that contain just a single node or that contain all or all but one nodes where X and/or Y is NA.

NvMSlope, NvMIntercept and NvMSlopeAndIntercept return the slope, intercept and both, respectively, of a single linear regression fitted to all data. NvMSlopeByClass, NvMInterceptByClass and NvMSlopeAndInterceptByClass return the slope, intercept and both, respectively, of linear regressions fitteed to each class and one to all data. For classes where it is not possible to fit a linear regression (for the reasons given above), NvMSlopeByClass, NvMInterceptByClass and NvMSlopeAndInterceptByClass will return NA.

Author(s)

Lawrence Hudson

See Also

Community, CommunityCollection ApplyByClass

Examples

data(TL84)

models <- NvMLinearRegressions(TL84)

# 'all', 'producer', 'invertebrate', 'vert.ecto'
names(models)

# Extract slopes and intercepts
sapply(models, coef)


# Slopes and intercepts through all data for each web in the pHWebs 
# collection
data(pHWebs)
CollectionCPS(pHWebs, properties=c('NvMSlope'))
CollectionCPS(pHWebs, properties=c('NvMIntercept'))
CollectionCPS(pHWebs, properties=c('NvMSlopeAndIntercept'))

# Slopes and intercepts through each category for each web in pHWebs
CollectionCPS(pHWebs, properties=c('NvMSlopeAndInterceptByClass'))

Description

Tri-trophic statistics.

Usage

NvMTriTrophicStatistics(community)

Arguments

Details

Tri-trophic statistics as described by Cohen et al 2009 PNAS.

Value

A list containing

Author(s)

Lawrence Hudson

References

Cohen, J.E. and Schittler, D.N. and Raffaelli, D.G. and Reuman, D.C. (2009) Food webs are more than the sum of their tritrophic parts. Proceedings of the National Academy of Sciences of the United States of America 106, 52, 22335–22340.

See Also

TLPS, ThreeNodeChains, TrophicChains, PlotAuppervAlower, NvMTriTrophicTable

Examples

data(TL84)
tts <- NvMTriTrophicStatistics(TL84)
nrow(tts$links)
head(tts$links)

nrow(tts$three.node.chains)
head(tts$three.node.chains)

nrow(tts$trophic.chains)
head(tts$trophic.chains)

Description

Tri-trophic statistics.

Usage

NvMTriTrophicTable(collection)

Arguments

Details

Returns a data.frame that contains the same statistics presented in Table 1 on Cohen et al 2009 PNAS. The function removes nodes lacking body mass (M) and/or numerical abundance (N), cannibalistic links and isolated nodes from each community. The last eight rows of the table contain four network statistics both with and without these removals.

Value

A data.frame with a column per community and the rows

Author(s)

Lawrence Hudson

References

Cohen, J.E. and Schittler, D.N. and Raffaelli, D.G. and Reuman, D.C. (2009) Food webs are more than the sum of their tritrophic parts. Proceedings of the National Academy of Sciences of the United States of America 106, 52, 22335–22340.

See Also

NvMTriTrophicStatistics, CommunityCollection

Examples

data(TL84, TL86, YthanEstuary)
collection <- CommunityCollection(list(TL84, TL86, YthanEstuary))
table <- NvMTriTrophicTable(collection)
print(round(table, 2))

Description

Nodes that consume two or more species and have a non-integer trophic level.

Usage

IsOmnivore(community, level=PreyAveragedTrophicLevel)
Omnivores(community, ...)
FractionOmnivorous(community, ...)
Omnivory(community, ...)

Arguments

Details

Omnivores are those nodes that consume two or more species and have a non-integer trophic level (Polis 1991). IsOmnivore returns a vector of logical of length NumberOfNodes; values are TRUE for nodes that are omnivorous. Omnivores returns the names of nodes for which IsOmnivore returns TRUE. FractionOmnivorous and Omnivory both return the proportion of nodes for which IsOmnivore returns TRUE.

Many researchers have used chain-averaged trophic level when computing omnivory (Polis, 1991; Bersier et al 2002). Computing chain-averaged trophic level requires enumerating every unique food chain - this can be lengthy for complex food webs so the default function used by IsOmnivore is PreyAveragedTrophicLevel. Omnivory values obtained using these two methods might differ slightly.

Value

Either a logical vector of length NumberOfNodes or a vector of names.

Author(s)

Lawrence Hudson

References

Polis, G. A. (1991) Complex desert food webs: an empirical critique of food web theory. American Naturalist 138, 123–155.

Bersier, L. and Banasek-Richter, C. and Cattin, M. (2002) Ecology 80 2394–2407.

See Also

NumberOfNodes, PreyAveragedTrophicLevel, ChainAveragedTrophicLevel

Examples

data(TL84)

IsOmnivore(TL84)
Omnivores(TL84)
Omnivory(TL84)

# Omnivory values found using PreyAveragedTrophicLevel and 
# ChainAveragedTrophicLevel differ for ChesapeakeBay
data(ChesapeakeBay)
Omnivory(ChesapeakeBay)
Omnivory(ChesapeakeBay, level=ChainAveragedTrophicLevel)

Description

Order a CommunityCollection

Usage

OrderCollection(collection, ..., decreasing=FALSE)

Arguments

Value

A CommunityCollection.

Author(s)

Lawrence Hudson

See Also

CommunityCollection, order, CollectionCPS

Examples

data(pHWebs)
CollectionCPS(pHWebs, c('pH', 'NumberOfNodes'))

# Order by name
pHWebs.name <- OrderCollection(pHWebs, 'title')
CollectionCPS(pHWebs.name, c('pH', 'NumberOfNodes'))

# Order by decreasing pH
pHWebs.decreasing.pH <- OrderCollection(pHWebs, 'pH', decreasing=TRUE)
CollectionCPS(pHWebs.decreasing.pH, c('pH', 'NumberOfNodes'))

# Order by increasing diversity
pHWebs.increasing.S <- OrderCollection(pHWebs, 'NumberOfNodes')
CollectionCPS(pHWebs.increasing.S, c('pH', 'NumberOfNodes'))

Description

Order a Community.

Usage

OrderCommunity(community, ..., decreasing=FALSE, na.last = TRUE, 
               new.order=NULL, title=NULL)

Arguments

Details

Returns a new Community object. dots can contain any name that meets the criteria of the properties parameter of NPS. If new.order is NULL then ... and optionally decreasing are used to compute the new node ordering.

Different node orders will yield different SumDietGaps and SumConsumerGaps (e.g. Stouffer et al 2006, Zook et al 2011).

Value

A Community.

Author(s)

Lawrence Hudson

References

Stouffer, D.B. and Camacho, J. and Amaral, L.A.N. (2006) Proceedings of the National Academy of Sciences of the United States of America 103, 50, 19015–19020.

Zook, A.E. and Eklof, A. and Jacob, U. and Allesina, S. (2011) Journal of Theoretical Biology 271, 1 106–113.

See Also

Community, order, Intervality, CollectionNPS, PreyAveragedTrophicLevel, PlotPredationMatrix

Examples

data(TL84)
NPS(TL84)

# Order by increasing M
TL84.increasing.M <- OrderCommunity(TL84, 'M', title='Increasing M')
NPS(TL84.increasing.M)

# Order by decreasing M
TL84.decreasing.M <- OrderCommunity(TL84, 'M', decreasing=TRUE)
NPS(TL84.decreasing.M)

# Order by increasing M and N
TL84.increasing.MN <- OrderCommunity(TL84, 'M', 'N')
NPS(TL84.increasing.MN)

# Reverse existing order
TL84.reversed <- OrderCommunity(TL84, new.order=56:1)
NPS(TL84.reversed)

# Sort alphabetically by category and by increasing M within each category
TL84.category <- OrderCommunity(TL84, 'category', 'M')

# Increasing trophic level, then randomly sorted within trophic level
new.order <- order(PreyAveragedTrophicLevel(TL84), sample(1:56))
TL84.increasing.TL <- OrderCommunity(TL84, new.order=new.order, 
                                     title='Increasing TL')
NPS(TL84.increasing.TL)

# Graphically show the effect of different orders
par(mfrow=c(1,2))
PlotPredationMatrix(TL84.increasing.M)
PlotPredationMatrix(TL84.increasing.TL)

Description

Ten stream food webs sampled across a large pH gradient.

Format

CommunityCollection.

Source

Layer et al 2010.

References

Layer, K. and Riede, J.O. and Hildrew, A.G. and Woodward, G. (2010) Food web structure and stability in 20 streams across a wide pH gradient. Advances in Ecological Research 42, 265–299.

Description

High-level function for plotting upper-versus-lower link angles.

Usage

PlotAuppervAlower(community, 
                  main=CPS(community)$title,
                  xlab=~A[lower], 
                  ylab=~A[upper], 
                  xlim=c(-180, 180),
                  ylim=c(-180, 180), 
                  pch=19, 
                  ...)

Arguments

Author(s)

Lawrence Hudson

References

Cohen, J.E. and Schittler, D.N. and Raffaelli, D.G. and Reuman, D.C. (2009) Food webs are more than the sum of their tritrophic parts. Proceedings of the National Academy of Sciences of the United States of America 106, 52, 22335–22340.

See Also

NvMTriTrophicStatistics

Examples

data(TL84)
PlotAuppervAlower(TL84)

Description

High-level function for plotting nodes in a circle.

Usage

PlotCircularWeb(community, 
                clockwise = TRUE, 
                origin.degrees = 0, 
                proportional.radius = 1, 
                frame.plot = FALSE,
                xlim = c(-1,1), 
                ylim = c(-1,1), 
                ...)

Arguments

Author(s)

Lawrence Hudson

See Also

Community, PlotBSpectrum, PlotWagonWheel, PlotNPS, PlotNPSDistribution, PlotNSpectrum, PlotRankNPS, PlotTLPS, PlotWebByLevel

Examples

data(TL84)
PlotCircularWeb(TL84)

# Plot the first node at the 6 o'clock position
PlotCircularWeb(TL84, origin.degrees=180)

# Plot the first node at the 6 o'clock position and plot nodes 
# counter-clockwise
PlotCircularWeb(TL84, origin.degrees=180, clockwise=FALSE)

Description

Functions that are useful for customising plots and for creating your own plot functions.

Usage

Log10BLabel(community, name = "italic(B)", units = with(CPS(community), 
            paste(M.units, "~", N.units)))
Log10MLabel(community, name = "italic(M)", units = CPS(community)$M.units)
Log10NLabel(community, name = "italic(N)", units = CPS(community)$N.units)

DefaultCategoryColours()
DefaultCategoryLabelColours()
DefaultCategorySymbols()
DefaultLinkColour()

PlaceMissingPoints(x, xlim, y, ylim)

LMabline(model, ...)
PlotLinearModels(models, colour.spec, col, ...)
FormatLM(model, slope.95.ci = FALSE, ci.plus.minus.style = FALSE, 
         r = FALSE, r.squared = TRUE, model.var.names = TRUE, dp = 2)

Arguments

Author(s)

Lawrence Hudson

See Also

Community, DefaultCategoryColours, NvMLinearRegressions, LinearRegressionByClass, lm

Description

High-level functions for plotting node properties.

Usage

PlotNPS(community, 
        X,
        Y,
        main = CPS(community)$title, 
        xlab, 
        ylab, 
        xlim = NULL, 
        ylim = NULL, 
        colour.by, 
        colour.spec, 
        col = NULL, 
        symbol.by, 
        symbol.spec, 
        pch = NULL, 
        bg.by, 
        bg.spec, 
        bg = NULL, 
        cex.by = NULL, 
        cex.spec = NULL, 
        cex = NULL, 
        label.colour.by = NULL, 
        label.colour.spec = NULL, 
        label.colour = NULL, 
        link.colour.by = NULL, 
        link.colour.spec = NULL, 
        link.col = NULL, 
        link.line.type.by = NULL, 
        link.line.type.spec = NULL, 
        link.lty = NULL, 
        link.lwd = NULL, 
        highlight.links = NULL, 
        highlight.nodes = Cannibals, 
        lowlight.nodes, 
        show.na = FALSE,
        show.web = TRUE, 
        show.nodes.as = "points", 
        node.labels = NULL, 
        label.cex = 0.6, 
        are.values = FALSE, 
        frame.plot = TRUE,
        ...)

PlotMvN(community, 
        xlab = Log10NLabel(community), 
        ylab = Log10MLabel(community), 
        ...)

PlotNvM(community, 
        xlab = Log10MLabel(community), 
        ylab = Log10NLabel(community), 
        ...)

PlotBvM(community, 
        xlab = Log10MLabel(community), 
        ylab = Log10BLabel(community), 
        ...)

PlotMvB(community, 
        xlab = Log10BLabel(community), 
        ylab = Log10MLabel(community), 
        ...)

Arguments

Details

The general-purpose function PlotNPS plots one node property against another.

For colour.by, symbol.by, bg.by, cex.by and label.colour.by, if X.by is not NULL and a relevant X.spec is not given, the X.by values are converted to a factor, the levels of which are used as the plot parameter. An error is raised if X.by contains any values not present in X.spec.

If colour.by/bg.by/symbol.by is NULL and community has a node property named ‘category’ then node colours/background colours/symbols are given by ‘category’ using the colour.spec/bg.spec/symbol.spec given by DefaultCategoryColours/DefaultCategorySymbols.

label.colour.by, node.labels and label.cex are used only if show.nodes.as is equal to "points".

The convenience functions PlotMvN, PlotNvM, PlotBvM and PlotMvB are ‘wrappers’ around PlotNPS that plot log10-transformed body mass (M), numerical abundance (N) or biomass (B). All of the parameters of PlotNPS, with the exception of X, Y and are.values, can be used with these four functions.

If show.nodes.as is equal to "points" then labels are plotted using label.cex and label.colour.

Author(s)

Lawrence Hudson

See Also

Community, NPS, DefaultCategoryColours, DefaultCategorySymbols, PlotBSpectrum, PlotCircularWeb, PlotNPSDistribution, PlotNSpectrum, PlotRankNPS, PlotTLPS, PlotWebByLevel PlaceMissingPoints

Examples

data(TL84)
PlotNvM(TL84)

# Set colours and plot symbols directly
PlotNvM(TL84, col=1, pch=19, highlight.nodes=NULL)

# Plot each level of taxonomic resolution in a different colour
PlotNvM(TL84, colour.by='resolved.to', pch=19, highlight.nodes=NULL)

# Plot each level of taxonomic resolution in a specific colour
colour.spec <- c(Species='purple3', Genus='green3', 'red3')
PlotNvM(TL84, colour.by='resolved.to', colour.spec=colour.spec, pch=19, 
        highlight.nodes=NULL)
legend("topright", legend=names(colour.spec), pch=19, col=colour.spec)

# Use PlotNPS to plot trophic height against log10 body mass
PlotNPS(TL84, 'Log10M', 'TrophicHeight', xlab=Log10MLabel(TL84), 
        ylab='Trophic height')


# The 'POM (detritus)' node in the Ythan Estuary dataset lacks both body mass 
# and numerical abundance.
par(mfrow=c(1,2))
data(YthanEstuary)
PlotNvM(YthanEstuary)
PlotNvM(YthanEstuary, show.na=TRUE)

Description

High-level functions for plotting distributions of node properties.

Usage

PlotNPSDistribution(community, 
                    property, 
                    main = CPS(community)$title, 
                    density.args = list(), 
                    ...)

PlotBDistribution(community, 
                  xlab = Log10BLabel(community), 
                  ...)

PlotMDistribution(community, 
                  xlab = Log10MLabel(community), 
                  ...)

PlotNDistribution(community, 
                  xlab = Log10NLabel(community), 
                  ...)

PlotDegreeDistribution(community, 
                       xlab = "Number of links", 
                       ...)

Arguments

Details

The convenience functions PlotBDistribution, PlotMDistribution and PlotNDistribution are wrappers around PlotNPSDistribution.

Author(s)

Lawrence Hudson

See Also

Community, NPS, DegreeDistribution, PlotCircularWeb, PlotNPS, PlotNPSDistribution, PlotRankNPS, PlotTLPS, PlotWebByLevel

Examples

data(TL84)

PlotMDistribution(TL84)

# A bandwidth of 3
PlotMDistribution(TL84, density.args=list(bw=3))

PlotDegreeDistribution(TL84)

Description

High-level functions for plotting value-versus-rank of node properties.

Usage

PlotRankNPS(community, 
            property, 
            rank.by=property, 
            log10.rank = FALSE, 
            xlab, 
            ylab, 
            show.web=FALSE, 
            ...)

PlotMvRankM(community, 
            log10.rank = FALSE, 
            xlab, 
            ylab, 
            ...)

PlotNvRankN(community, 
            log10.rank = FALSE, 
            xlab, 
            ylab, 
            ...)

PlotBvRankB(community, 
            log10.rank = FALSE, 
            xlab, 
            ylab, 
            ...)

Arguments

Details

The convenience functions PlotMvRankM, PlotNvRankN and PlotBvRankB are ‘wrappers’ around PlotRankNPS that plot rank log10-transformed body mass (M), numerical abundance (N) or biomass (B).

Author(s)

Lawrence Hudson

See Also

Community, NPS, PlotBSpectrum, PlotCircularWeb, PlotNPS, PlotNPSDistribution, PlotNSpectrum, PlotTLPS, PlotWebByLevel

Examples

data(TL84)
PlotNvRankN(TL84)

# log10(N) against log10(rank of M)
PlotRankNPS(TL84, property='Log10N', rank.by='M', log10.rank=TRUE)


# The 'POM (detritus)' node in the Ythan Estuary dataset lacks body mass.
par(mfrow=c(1,2))
data(YthanEstuary)
PlotMvRankM(YthanEstuary)
PlotMvRankM(YthanEstuary, show.na=TRUE)

Description

High-level functions for plotting trophic link properties.

Usage

PlotTLPS(community, 
         X, 
         Y,
         xlab, 
         ylab, 
         axes.limits.equal = FALSE,
         xlim = NULL, 
         ylim = NULL, 
         main = CPS(community)$title, 
         highlight.links = NULL, 
         lowlight.links = NULL, 
         colour.by, 
         colour.spec, 
         col = NULL, 
         symbol.by, 
         symbol.spec, 
         pch = NULL, 
         bg.by, 
         bg.spec, 
         bg = NULL, 
         cex.by = NULL, 
         cex.spec = NULL, 
         cex = NULL, 
         are.values = FALSE,
         ...)

PlotPredationMatrix(community, 
                    xlab='Consumer', 
                    ylab='Resource', 
                    resource.order,
                    consumer.order,
                    ...)

PlotMRvMC(community, 
          xlab=Log10MLabel(community, name='italic(M)[consumer]'),
          ylab=Log10MLabel(community, name='italic(M)[resource]'),
          axes.limits.equal = TRUE,
          ...)

PlotMCvMR(community, 
          xlab=Log10MLabel(community, name='italic(M)[resource]'),
          ylab=Log10MLabel(community, name='italic(M)[consumer]'),
          axes.limits.equal = TRUE,
          ...)

PlotNRvNC(community, 
          xlab=Log10NLabel(community, name='italic(N)[consumer]'),
          ylab=Log10NLabel(community, name='italic(N)[resource]'),
          axes.limits.equal = TRUE,
          ...)

PlotNCvNR(community, 
          xlab=Log10NLabel(community, name='italic(N)[resource]'),
          ylab=Log10NLabel(community, name='italic(N)[consumer]'),
          axes.limits.equal = TRUE,
          ...)

PlotBRvBC(community, 
          xlab=Log10BLabel(community, name='italic(B)[consumer]'),
          ylab=Log10BLabel(community, name='italic(B)[resource]'),
          axes.limits.equal = TRUE,
          ...)

PlotBCvBR(community, 
          xlab=Log10BLabel(community, name='italic(B)[resource]'),
          ylab=Log10BLabel(community, name='italic(B)[consumer]'),
          axes.limits.equal = TRUE,
          ...)

Arguments

Details

The general-purpose function PlotTLPS plots one trophic-link property against another.

If colour.by/bg.by/symbol.by is NULL and community has a node property named ‘category’ then trophic-link colours/background colours/symbols are given by ‘resource.category’ using colour.spec/bg.spec/symbol.spec given by DefaultCategoryColours/DefaultCategorySymbols.

PlotPredationMatrix shows trophic links as a binary matrix with species shown in node order, starting at the top-left. If row.node and col.order are both missing (the default) or are the same, then a dashed diagonal line is drawn. Points on the dashed line indicate cannibalistic trophic links.

The convenience functions PlotMRvMC, PlotMCvMR, PlotNRvNC, PlotNCvNR, PlotBRvBC, PlotBCvBR are ‘wrappers’ around PlotRankNPS that plot a log10-transformed body mass, M, numerical abundance, N, or biomass abundance, B.

Author(s)

Lawrence Hudson

See Also

Community, TLPS, PlotBSpectrum, PlotCircularWeb, PlotNPS, PlotNPSDistribution, PlotNSpectrum, PlotRankNPS, PlotWebByLevel

Examples

data(TL84)

# The predation matrix
PlotPredationMatrix(TL84)

# The predation matrix with rows ordered by body mass
PlotPredationMatrix(TL84, resource.order='M')

# Colours and symbols by resource.category
PlotMCvMR(TL84)

# Colours and symbols by consumer.category
PlotMCvMR(TL84, bg.by='consumer.category', symbol.by='consumer.category', 
          colour.by='consumer.category')

# Consumer trophic height against resource log10(M)
PlotTLPS(TL84, 'resource.Log10M', 'consumer.TrophicHeight')

# Log10(M of resource / M of consumer) against consumer log10(M)
PlotTLPS(TL84, 'consumer.Log10M', 'Log10RCMRatio')

Description

Plot a nodes as concentric circles around a focal node.

Usage

PlotWagonWheel(community,
               focus,
               clockwise=TRUE,
               origin.degrees=0,
               frame.plot=FALSE,
               main=NULL,
               ...)

Arguments

Details

The node given in focus is plotted at the centre of the wagon wheel. Other nodes in the community are plotted in concentric circles that are one, two, three etc trophic links away from the focus. Isolated nodes - those with no resources or consumers, other than possibly themselves - are not shown.

Author(s)

Lawrence Hudson

See Also

Community, Degree, IsolatedNodes, OrderCommunity, PlotCircularWeb, PlotNPS, PlotWebByLevel, rgb, ShortestPaths

Examples

data(TL84)
# Ploesoma sp. is the focal species
PlotWagonWheel(TL84, 'Ploesoma sp.')

# Show nodes as numbers
PlotWagonWheel(TL84, 'Ploesoma sp.', show.nodes.as='labels')

# 'Daphnia pulex' is the focus, nodes ordered by degree (total number of
# trophic links), lines partially transparent
PlotWagonWheel(OrderCommunity(TL84, 'Degree'), 'Daphnia pulex',
               show.nodes.as='labels', link.col=rgb(0.8,0.8,0.8,0.5))

Description

A high-level function for plotting a food-web by vertically with the lowest trophic-level nodes at the bottom.

Usage

PlotWebByLevel(community, 
               level='PreyAveragedTrophicLevel', 
               max.nodes.per.row=20,
               round.levels.to.nearest=0.2,
               stagger=0.1, 
               x.layout='wide', 
               y.layout='compress', 
               show.level.labels=TRUE,
               show.level.lines=FALSE, 
               xaxt='n', 
               yaxt='n', 
               xlab='', 
               ylab='', 
               frame.plot=FALSE,
               ylim=NULL,
               ...)

Arguments

Details

If round.levels.to.nearest is greater than 0, values in level are rounded to the nearest round.levels.to.nearest. Rounded values are used by the x.layout and y.layout engines.

If x.layout is 'skinny' then nodes are spaced one x unit apart and max.nodes.per.row is ignored. If x.layout is 'narrow', nodes are spaced one x unit apart if fewer than max.nodes.per.row on that row, otherwise nodes are squashed in to the available x space. If x.layout is 'wide', nodes are spaced widely.

If y.layout is 'compress', then nodes are always shown at the values in level. If y.layout is 'stagger' and there are more than max.nodes.per.row on a level then the plotted levels are staggered by the values in stagger.

Author(s)

Lawrence Hudson

See Also

Community, PlotBSpectrum, PlotCircularWeb, PlotNPS, PlotNPSDistribution, PlotNSpectrum, PlotRankNPS, PlotTLPS

Examples

# Compare prey-averaged and chain-averaged trophic level
data(TL84)
par(mfrow=c(1,2))
PlotWebByLevel(TL84, ylim=c(1,5.8), main='Prey-averaged')
PlotWebByLevel(TL84, ylim=c(1,5.8), level='ChainAveragedTrophicLevel', 
               main='Chain-averaged')

# Compare the three different x layouts
par(mfrow=c(1,3))
for(x.layout in c('skinny', 'narrow', 'wide'))
{
    PlotWebByLevel(TL84, x.layout=x.layout, main=x.layout)
}

# Compare the effect of round levels before plotting
# Different x-spacing of the four nodes around level 3
par(mfrow=c(1,2))
PlotWebByLevel(TL84, round.levels.to.nearest=0.2)
PlotWebByLevel(TL84, round.levels.to.nearest=0)

# Compare the effect of staggering levels
# Primary producers are staggered in the second plot
par(mfrow=c(1,2))
# No staggering - stagger and max.nodes.per.row are ignored
PlotWebByLevel(TL84, y.layout='compress')
# Stagger
PlotWebByLevel(TL84, y.layout='stagger', stagger=0.1, 
               max.nodes.per.row=20)

Description

Returns a predation matrix.

Usage

PredationMatrix(community, weight=NULL)

Arguments

Details

Returns a square matrix with NumberOfNodes rows and columns. If weight is NULL then a binary matrix, in which elements are either 0 or 1, is returned; 1 indicates a trophic link from a resource (row) to a consumer (column). If weight is not NULL then elements of the returned matrix will be set to the values given by weight. Row names and column names of the returned matrix are node names.

Value

A square matrix.

Author(s)

Lawrence Hudson

See Also

PlotPredationMatrix, TLPS, NumberOfNodes, NumberOfTrophicLinks, ResourcesByNode, ConsumersByNode, PredationMatrixToLinks

Examples

data(TL84)

# A square matrix of NumberOfNodes rows and columns
dim(PredationMatrix(TL84))
NumberOfNodes(TL84)

# Should contain NumberOfTrophicLinks links
sum(PredationMatrix(TL84))
NumberOfTrophicLinks(TL84)

# Compare an unweighted matrix and a matrix weighted by diet fraction
data(Benguela)

PredationMatrix(Benguela)
PredationMatrix(Benguela, weight='diet.fraction')

Description

A function that converts a predation matrix to a data.frame with the columns ‘resource’ and ‘consumer’.

Usage

PredationMatrixToLinks(pm, link.property=NULL)

Arguments

Details

Returns a data.frame of trophic links contained within pm. Non-zero and non-NA values indicate a trophic link between a resource (row) and consumer (column). pm should have both row names and column names. The returned data.frame will contain the columns ‘resource’ and ‘consumer’. If pm contains quantitative information such as diet fractions or number of observations then you can set link.property to the name of the quantity and the returned data.frame will include a column with that name, that contains link strength values extracted from pm.

If you have existing food-web data in predation-matrix form then this function can help to import your data in to Cheddar.

Value

A data.frame

Author(s)

Lawrence Hudson

See Also

Community, PredationMatrix, TLPS

Examples

data(TL84)

links <- PredationMatrixToLinks(PredationMatrix(TL84))
identical(links, TLPS(TL84))    # TRUE

# Create a Cheddar community from an existing square predation matrix
node <- c('Leaf', 'Caterpillar', 'Bluetit')
pm <- matrix( c(0, 1, 0,
                0, 0, 1,
                0, 0, 0), 
             ncol=3, byrow=TRUE, dimnames=list(node, node))

community1 <- Community(nodes=data.frame(node=node),
                        trophic.links=PredationMatrixToLinks(pm),
                        properties=list(title='Test community'))
TLPS(community1)

# The same set of trophic links could be represented by a non-square predation 
# matrix
pm <- matrix( c(1, 0,
                0, 1), 
             ncol=2, byrow=TRUE, 
             dimnames=list(node[1:2], node[2:3]))

community2 <- Community(nodes=data.frame(node=node),
                        trophic.links=PredationMatrixToLinks(pm),
                        properties=list(title='Test community'))
TLPS(community2)

all.equal(community1, community2)    # TRUE

# Extract quantitative information
node <- c('Leaf 1', 'Leaf 2', 'Caterpillar 1', 'Caterpillar 2')
pm <- matrix( c(0, 0, 0.4, 0.8, 
                0, 0, 0.6, 0.2, 
                0, 0, 0,   0, 
                0, 0, 0,   0), 
             ncol=4, byrow=TRUE, dimnames=list(node, node))

# A data.frame that has a column called diet.fraction
PredationMatrixToLinks(pm, link.property='diet.fraction')

Description

High-level functions that create pyramid plots.

Usage

PlotBPyramid(community, 
             level = floor(PreyAveragedTrophicLevel(community)),
             expected.levels,
             fill.missing.levels = TRUE,
             order.by.expected = TRUE,
             show.level.labels = TRUE, 
             xlab = Log10BLabel(community, name=expression(~sum(italic(B)))), 
             ylab = "", 
             xlim = NULL, 
             col = NULL, 
             text.col = 'black',
             main = CPS(community)$title,
             ...)

PlotNPyramid(community, 
             level = floor(PreyAveragedTrophicLevel(community)),
             expected.levels,
             fill.missing.levels = TRUE,
             order.by.expected = TRUE,
             show.level.labels = TRUE, 
             xlab = Log10NLabel(community, name=expression(~sum(italic(N)))),
             ylab = "", 
             xlim = NULL, 
             col = NULL, 
             text.col = 'black',
             main = CPS(community)$title,
             ...)

Arguments

Details

PlotBPyramid plots log10-transformed sum biomass abundance in each level and PlotNPyramid plots log10-transformed sum numerical abundance in each level.

expected.levels provides two behaviours. First, it provides error checking: an error is raised if values are in level that are not in expected.levels. Second, it interacts with fill.missing.levels and order.by.expected to control which levels are drawn and how. If fill.missing.levels is TRUE then values in expected.levels that are not present in level are shown on the pyramid plot. If order.by.level is TRUE then the levels are plotted in the order given in expected.levels. If level contains numbers then expected.levels defaults to a sequence of integers floor(min(level)):ceiling(max(level)). If level is ‘category’ then expected.levels defaults to the intersection of values of ‘category’ that are present in community and the usual Cheddar default values: ‘<unnamed>’, ‘producer’, ‘invertebrate’, ‘vert.ecto’, ‘vert.endo’.

Author(s)

Lawrence Hudson

See Also

Community, SumBiomassByClass, SumNByClass, Log10BLabel, Log10NLabel, floor, ceiling

Examples

data(TL84)

# Use a large left-hand margin to show level text
reset.par <- par(mar=c(5,8,1,1))

# Using prey-averaged trophic level
PlotNPyramid(TL84)

# Using chain-averaged of trophic level
PlotNPyramid(TL84, level=floor(ChainAveragedTrophicLevel(TL84)))

# Show by category
PlotNPyramid(TL84, level='category')

# Taxonomic kingdoms as levels
PlotNPyramid(TL84, level='kingdom')

# Taxonomic kingdoms as levels, with a defined order
PlotNPyramid(TL84, level='kingdom', expected.levels=c("<unnamed>", "Plantae", 
             "Chromista","Bacteria","Protozoa","Animalia"))


# Compare the YthanEstuary and the TL84 datasets. YthanEstuary has nodes in 
# each of the categories whereas TL84 only has producer, invertebrate and 
# vert.ecto nodes. Show categories that are not present in TL84
par(mfrow=c(1,2))
data(YthanEstuary)
xlim <- range(c(Log10N(TL84), Log10N(YthanEstuary)), na.rm=TRUE)
PlotNPyramid(TL84, level='category', xlim=xlim, 
             expected.levels=c('<unnamed>', 'producer', 'invertebrate', 
                               'vert.ecto', 'vert.endo'))
PlotNPyramid(YthanEstuary, level='category',  xlim=xlim)
par(mfrow=c(1,1))


# For the BroadstoneStream dataset, the LongestTrophicLevel function returns 
# nodes in levels 1 and 7 to 10 but no nodes in levels 2 to 6. 
# By default all levels between the minimum and maximum are shown, so levels 
# 2 to 6 appear with no boxes.
data(BroadstoneStream)
PlotNPyramid(BroadstoneStream, 
             level=floor(LongestTrophicLevel(BroadstoneStream)))

# Set fill.missing.levels to FALSE to prevent levels 2 to 6 from being drawn.
PlotNPyramid(BroadstoneStream, 
             level=floor(LongestTrophicLevel(BroadstoneStream)), 
             fill.missing.levels=FALSE)

par(reset.par)

Description

Quantitative descriptors after Bersier at al Ecology 2002.

Usage

NodeQuantitativeDescriptors(community, weight)
QuantitativeDescriptors(community, weight, top.level.threshold=0.99)

Arguments

Details

Quantitative food-web descriptors as described by Bersier et al 2002 Ecology.

NodeQuantitativeDescriptors computes a table of node-level quantitative descripttors, as presented in Bersier et al 2002, Table 1. It returns a matrix with columns NResources, NConsumers, bIn, bOut, nN, nP, d.prime, d, o.prime, o, g.prime, g, v.prime, v.

QuantitativeDescriptors computes values presented in Bersier et al 2002 Table 2. It returns a matrix with columns Qualitative, Unweighted and Weighted and rows Fraction top level, Fraction intermediate, Fraction basal, Ratio resources:consumers, Link density, Connectance, Fraction links top:intermediate, Fraction links top:basal, Fraction links intermediate:intermediate, Fraction links intermediate:basal, Mean chain length, Median chain length, SD chain length, Max chain length, Degree of omnivory, Generality, Vulnerability, SD standardised generality, SD standardised vulnerability.

Value

A matrix.

Author(s)

Lawrence Hudson

References

Bersier, L. and Banasek-Richter, C. and Cattin, M. (2002) Ecology 80 2394–2407.

See Also

TrophicLinkPropertyNames, NumberOfTrophicLinks, NumberOfNodes

Examples

data(ChesapeakeBay)
QuantitativeDescriptors(ChesapeakeBay, 'biomass.flow')
NodeQuantitativeDescriptors(ChesapeakeBay, 'biomass.flow')

Description

Remove cannibalistic trophic links.

Usage

RemoveCannibalisticLinks(community, title)

Arguments

Details

Returns a new Community with any cannibalistic trophic links removed.

Value

A new object of class Community.

Author(s)

Lawrence Hudson

See Also

Community

Examples

data(TL84)
NumberOfTrophicLinks(TL84)

TL84.no.cannibal <- RemoveCannibalisticLinks(TL84)
NumberOfTrophicLinks(TL84.no.cannibal)

Description

Remove isolated nodes.

Usage

RemoveIsolatedNodes(community, title)

Arguments

Details

Returns a new Community with isolated nodes removed.

Value

A new object of class Community.

Author(s)

Lawrence Hudson

See Also

Community, IsIsolatedNode

Examples

data(TL84)
IsolatedNodes(TL84)

TL84.no.isolated <- RemoveIsolatedNodes(TL84)
IsolatedNodes(TL84.no.isolated)

Description

Remove one or more nodes.

Usage

RemoveNodes(community, remove, title, 
                   method=c('direct','secondary','cascade'))

Arguments

Details

Returns a new Community with nodes in remove removed. An error is raised if remove refers to nodes not in the community of if remove refers to all nodes in the community.

If method is ‘direct’, only the nodes in remove are removed. If method is ‘secondary’, secondarily extinct nodes - those that directly consume one or more nodes in ‘remove’ and that no longer have any resources (except themselves) after the removal - are also removed. If method is ‘cascade’, a multistep version of ‘secondary’ is applied. This has the effect of propogating extinctions though the community - all consumers that are ultimately dependent upon all species in ‘remove’, and upon no other nodes (except themselves), will be removed.

Value

A new object of class Community.

Author(s)

Lawrence Hudson

See Also

Community, BasalNodes, IsolatedNodes, NumberOfNodes

Examples

data(TL84)

# Three different ways of removing node 56 (Umbra limi)
a <- RemoveNodes(TL84, 56)
b <- RemoveNodes(TL84, 'Umbra limi')
c <- RemoveNodes(TL84, c(rep(FALSE,55), TRUE))

identical(a,b)  # TRUE
identical(a,c)  # TRUE

# The behaviours of the different methods
NumberOfNodes(TL84)         # 56 nodes in total
length(BasalNodes(TL84))    # 25 basal nodes
length(IsolatedNodes(TL84)) #  6 isolated nodes

RemoveNodes(TL84, BasalNodes(TL84)) # 56 - 25 = 31 nodes remain
RemoveNodes(TL84, BasalNodes(TL84), method='secondary') # 14 nodes remain
RemoveNodes(TL84, BasalNodes(TL84), method='cascade')   # 6 isolated nodes remain

# Results in an error
## Not run: RemoveNodes(TL84, 1:NumberOfNodes(TL84))