# Use this to add a copy-code buttong klippy::klippy(position = c('top', 'right'), color = 'darkred')
knitr::opts_chunk$set(echo = TRUE)
library(emln) library(infomapecology)
Example 1
Data set
A binary directed marine food web from Ute et al. 2011. “The Role of Body Size in Complex Food Webs: A Cold Case.” In Advances in Ecological Research, edited by Andrea Belgrano, 45:181–223. Academic Press.. Kongsfjorden is a glacial fjord on the northwest corner of the Svalbard archipelago. It is a 30 km open fjord with no marked sill at the entrance, and with a maximum depth exceeding 300m. The network consists of 262 species with 1,544 feeding interactions. Data is available here.
Input
A link-list.
R Code
# Import data data("kongsfjorden_links") data("kongsfjorden_nodes") nodes <- kongsfjorden_nodes %>% select(node_name=Species, node_id_original=NodeID, everything()) interactions<- kongsfjorden_links %>% select(from=consumer, to=resource) %>% mutate_if(is.factor, as.character) %>% mutate(weight=1) # Prepare network objects network_object <- create_monolayer_network(x=interactions, directed = T, bipartite = F, node_metadata = nodes) # Run infomap, allow hierarchical modules # Some species will have only incoming or outgoing links, so the next line will result in a warning infomap_object <- run_infomap_monolayer(network_object, infomap_executable='Infomap', flow_model = 'directed', silent=T,trials=100, two_level=F, seed=123)
Infomap
Under the hood, the function run_infomap_monolayer runs:
./Infomap infomap.txt . -i link-list --tree --seed 123 -N 100 -f directed --silent
- Here, the most important feature is the lack of the argument
-2(or--two-level), which allows for hierarchical modules (the default in Infomap). -f directedindicates flow on a directed network.
Output
A tree file is produced by Infomap, but is parsed by run_infomap_monolayer from infomapecology. In Infomap's tree output, the path column has a tree-like format such as 1:3:2, which describes the path from the root of the tree to the leaf node. The first integer (1 in the 1:3:2 example) is the top module. The last integer after the colon (2 in the 1:3:2 example) indicates the ID of the leaf in the module, and not the ID of the node. In case a node has fewer levels because its module is not partitioned, the missing levels will show NA.
In the output excerpt below for the analysis of the Kongsfjorden food web, there are four nodes that belong to the 3rd submodule within top module 1. For these, module_level3 is the leaf id. Top modules 2 and 3 do not have sub-modules. Therefore, for these modules the second level (module_level2) is the leaf id and module_level3 shows an NA value. In addition, this data has node attributes, which are added to the final output. In this example: FeedingType, Mobility and Environment.
| node_id | node_name | module_level1 | module_level2 | module_level3 | FeedingType | Mobility | Environment |
|---|---|---|---|---|---|---|---|
| 54 | Laminaria saccharina | 1 | 1 | 1 | none | 1 | benthic |
| 55 | Laminaria digitata | 1 | 1 | 2 | none | 1 | benthic |
| 57 | Laminaria solidungula | 1 | 1 | 3 | none | 1 | benthic |
| 49 | Fucus distichus | 1 | 1 | 4 | none | 1 | benthic |
| 22 | Calanus finnmarchicus | 1 | 2 | 1 | predator | 4 | pelagic |
| 28 | Metridia lucens | 1 | 2 | 2 | predator | 4 | pelagic |
| 102 | Pandalus borealis | 2 | 2 | NA | predator | 3 | benthic |
| 40 | Thysanoessa inermis | 2 | 3 | NA | grazer | 4 | epipelagic/ice associated |
| 26 | Copepoda nauplii | 3 | 2 | NA | predator | 4 | pelagic |
| 34 | Clione limacina | 3 | 3 | NA | predator | 4 | pelagic |
Example 2
Data set
A binary directed food web from Mouritsen KN, Poulin R, McLaughlin JP, Thieltges DW. Food web including metazoan parasites for an intertidal ecosystem in New Zealand: Ecological Archives E092-173. Ecology. 2011;92: 2006–2006.
In infomapecology:
data(otago_nodes) data(otago_links)
Input
A link-list.
R Code
# Prepare data otago_nodes_2 <- otago_nodes %>% filter(StageID==1) %>% select(node_name=WorkingName, node_id_original=NodeID, WorkingName,StageID, everything()) anyDuplicated(otago_nodes_2$node_name) otago_links_2 <- otago_links %>% filter(LinkType=='Predation') %>% # Only include predation links filter(ConsumerSpecies.StageID==1) %>% filter(ResourceSpecies.StageID==1) %>% select(from=ResourceNodeID, to=ConsumerNodeID) %>% left_join(otago_nodes_2, by=c('from'='node_id_original')) %>% select(from, node_name, to) %>% left_join(otago_nodes_2, by=c('to'='node_id_original')) %>% select(from=node_name.x, to=node_name.y) %>% mutate(weight=1) # Prepare network objects # Some species will have only incoming or outgoing links, so the next line will result in a warning network_object <- create_monolayer_network(x=otago_links_2, directed = T, bipartite = F, node_metadata = otago_nodes_2) # Run infomap without hieararchy infomap_object <- run_infomap_monolayer(network_object, infomap_executable='Infomap', flow_model = 'directed', silent=T,trials=100, two_level=T, seed=123) infomap_object$modules %>% select(node_id, node_name, module=module_level1, OrganismalGroup, NodeType) %>% group_by(module, OrganismalGroup) %>% summarise(n=n_distinct(node_id)) %>% drop_na() %>% ggplot(aes(x=module, y=OrganismalGroup, size=n))+geom_point()+ scale_x_continuous(breaks = 1:infomap_object$m)+ theme_bw()+theme(panel.grid.minor = element_blank()) # Run infomap with hieararchy infomap_object <- run_infomap_monolayer(network_object, infomap_executable='Infomap', flow_model = 'directed', silent=T,trials=100, two_level=F, seed=123) infomap_object$modules %>% select(node_id, node_name, module=module_level1, OrganismalGroup, NodeType) %>% group_by(module, OrganismalGroup) %>% summarise(n=n_distinct(node_id)) %>% drop_na() %>% ggplot(aes(x=module, y=OrganismalGroup, size=n))+geom_point()+ scale_x_continuous(breaks = 1:infomap_object$m)+ theme_bw()+theme(panel.grid.minor = element_blank())
