Guild Structure Cody (1975) demonstrated that the division of available resources amongst sets of insectivorous birds in shrub grasslands results in the projection upon each resource dimension of almost identical niches within Californian chaparral, Chilean matorall and South African machia

Guild Structure While a set of resources may be divided by consumers in an infinite number of ways, in reality the realized niches of each species showed a remarkable similarity in these three shrubland systems – despite the fact each is colonized by a taxonomically distinct set of species

Guild Structure The match is so close that the different species of the analogous communities even display morphological convergence in their adaptations to apparently parallel niches

Guild Structure Similar constancy of niche structure in parallel communities is recorded among assemblages of montane lizards in Chile and California (Fuentes 1976), coral reef fish assemblages of the Atlantic and Pacific (Gladfelter et al. 1980) and ‘finch’ communities (Schluter 1986)

Guild Structure What is a guild? “Any group of species that exploit the same class of environmental resources in a similar way”

Guild Structure Many guilds have been documented –e.g. nectar feeders, desert lizards, terrestrial salamanders, insectivorous birds However, one can subdivide groups –E.g. Insectivorous birds become: foliage gleaners, flycatchers, bark gleaners, or ground gleaners

Guild Structure Furthermore, you do not have to group species together in terms taxonomic positions, but rather on their niche requirements

Guild Structure: evidence The basic idea is that within a community there are clusters of species interacting among themselves more strongly than with other species in the community

Guild Structure: problems There are problems with the guild concept There is no objective criteria for assigning guild membership Limits on membership not clearly defined Causes of guild structure unresolved Most studies do restrict analysis to a single taxonomic assemblage

Guild Structure: evidence Inger and Colwell (1977) made the first attempt at objective identification of guild structure within community matrices by seeking sharp discontinuities in the arrangement of resource use curves along resource axes (e.g. sudden increases in the variance of mean overlap)

Guild Structure objective grouping Joern and Lawlor (1981; Oikos) determined group membership of guilds through use of a clustering technique, progressively linking together (in unidimensional space) pairs and then clusters of species with highest overlap

Guild Structure Guild structure (of grasshoppers) based upon resource use Guild structure is ascribed from cluster analysis of species in relation to expressed overlap in resource use

Guild Structure Joern and Lawlor’s analysis clusters together groups of species whose competitive interactions with others are strongest with that same guild (greater overlap) This approach can be extended to multidimensional space using a range of clustering techniques (e.g. PCA or FA)

Guild Structure While this approach effectively defines groups and identifies species, it does provide statistical significance to the clusters identified (but see Jaksic and Medel 1990)

Guild Structure: null model The null model for guild structure is that the relative frequency of guilds in the assemblage represents a random sample of species from the colonizing source pool

Guild Structure: null model Two deviations from the null model are possible: the difference in guild frequencies between the source pool and the assemblage might be unusually small or large

Guild Structure: null model When the deviations are large, certain guilds are over- or under-represented in local assemblages For example, in many land-bridge islands, there is a consistent absence of some bird families (MacArthur et al. 1972; Ecology) Why?

Guild Structure: null model When the variation is unusually small, that would indicate the guilds are similar to one another in the level of co-occurrence observed

Guild Structure: null model How to achieve a correct null model? Solution: drawing species randomly from an appropriate source pool to evaluating the ‘expected’ amount of variation in such island (or small) assemblages

Guild Structure: null model Gotelli and Abele (1982; J of Biogeography) used the hypergeometric distribution to test for deviations in species richness of West Indian landbird families

Guild Structure: null model For each island, the observed number of species in each family was compared to the expected number if species were drawn equiprobably from the archipelago list

Guild Structure: null model Results: the number of coexisting species of parrots (Psittacidae) was less than expected but the number of coexisting pigeons and doves (Columbidae) and mockingbirds (Mimidae) was greater than expected Can you think of what characteristics might contribute to over-representation?

Guild Structure: EcoSim null model The guild structure works within the co- occurrence analysis option One could create a separate presence- absence matrix for each guild in the assemblage and analyze each matrix separately

Guild Structure: EcoSim null model However, there are also times when one might want to test for patterns among the guilds as a group

Guild Structure: EcoSim null model All species are assigned to a single guild (user-defined and therefore subject to biologists biases) This module does not test for classification or recognition of guilds, but rather hypotheses about them that have been designated a-priori by YOU Tests for differences among different guilds

Guild Structure: EcoSim null model Species Site1 Site2 Site3 Site4 SpeciesA1100 SpeciesB0010 SpeciesC0001 SpeciesD1111 SpeciesE0110 SpeciesF0100 SpeciesG1110 SpeciesH0001 SpeciesI1101 SpeciesJ1011 SpeciesK1001

Guild Structure: EcoSim null model Species GuildSite1 Site2 Site3 Site4 SpeciesAX1100 SpeciesBX0010 SpeciesCY0001 SpeciesDX1111 SpeciesEY0110 SpeciesFY0100 SpeciesGZ1110 SpeciesHZ0001 SpeciesIY1101 SpeciesJX1011 SpeciesKY1001

Guild Structure: EcoSim null model Another form of analysis in the co- occurrence module is rather than analyze for differences among guilds, one can compare among regions (or any other type of ‘site’ grouping)

Guild Structure: EcoSim null model SpeciesSite1 Site2 Site3 Site4 Regions Intact Intact Invaded Invaded SpeciesA1100 SpeciesB0010 SpeciesC0001 SpeciesD1111 SpeciesE0110

Guild Structure: EcoSim null model Generates similar indices as the standard co-occurrence analysis (e.g. C-score, the number of checkerboard species pairs, the number of species combinations, and the variance ratio)

Guild Structure: EcoSim null model In addition to grouping by guild or region, there is a ‘favored states’ analysis (based upon the hypothesis of Fox’s assembly rules)

Guild Structure: EcoSim null model Fox suggested that species are added sequentially to a community such that different ‘functional groups’ (or guilds) are represented as evenly as possible. Communities can then be classified as to whether they are in a ‘favored’ or an ‘unfavored’ state

Guild Structure: EcoSim null model For example, if a community had 7 species and 4 guilds, a favored state would have the guilds filled with (1,2,2,2) species However, an unfavored state would be (1,0,3,3)

Guild Structure: EcoSim null model EcoSim reshuffles the guild labels, then examines each column of the matrix and designates it as a favored or unfavored state. The number of favored states in a matrix is an integer that can range from 0 to a maximum of C, the number of columns in the data matrix