Quantifying the influence of space on social group structure Series of networks based on individual connections collected from a population of free-ranging house mice (Mus musculus domesticus). Mice are tagged with a passive integrated transponder (PIT) when they reach a minimum weight of 18 grams. The mice use 40 artificial nest boxes, fitted with radio-frequency identification (RFID) antennae, to rest and rear litters. The antennae automatically record when mice equipped with a PIT enter and exit a box. Based on these antennae data, we can determine which individuals share nest boxes and for how long. (For further information on the study system refer to König et al. 2015). The series of networks is constructed based on the sharing of nest boxes. The series of networks consists of 14 days of antennae data over the duration of 2 years (population size during this time period ranged between 52 to 188 tagged adult house mice). Inactivity periods of the data collection system extended this time window, so that each time window consists of a similar period of active data collection (see also Liechti et al. 2020). We used total time spent sharing a nest box in seconds as our measure of association strength. Authors:
- Julian Evans^1†,
- Jonas I. Liechti^2†,
- Matthew J. Silk^3,4,
- Barbara König^1‡,
- Sebastian Bonhoeffer^{2‡ †}: Joint first author; ^‡: Joint last author; : Corresponding author: [email protected] 1: Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057 Zurich
2: Institute for Integrative Biology, ETH Zurich, Universitätsstrasse 16, 8092 Zurich, Switzerland
3: Centre for Ecology and Conservation, University of Exeter Penryn Campus, UK
4: Environment and Sustainability Institute, University of Exeter Penryn Campus, UK
Dataset
The raw data of the studied system is present in graphs folder in form of a
list of GraphML files.
The files containing the graphs are numbered according to their order of
appearance in the sequence of graphs. Each file contains a single graph the can be imported for example into
igraph. The following attributes are stored in the graphml files: Graph properties: - start (xml tag: g_start) gives the starting timepoint of
aggregation period. The format is 'YYYY-MM-DD HH:MM:SS'.
- stop (xml tag: g_stop) gives the ending timepoint of the
aggregation period. Node properties: - name (xml tag: v_name) a unique id for each individual that is consistent
across the sequence of graphs.
- x position( xml tag: v_x) is the x position [cm] of the barycentre from
all interactions of this individual.
- y position( xml tag: v_y) is the x position [cm] of the barycentre from
all interactions of this individual. Edge properties: - weight (xml tag: e_weight) is the weight [seconds] of an interaction.
The weight corresponds to the accumulated duration of interactions.

Quantifying the influence of space on social group structure Series of networks based on individual connections collected from a population of free-ranging house mice (Mus musculus domesticus). Mice are tagged with a passive integrated transponder (PIT) when they reach a minimum weight of 18 grams. The mice use 40 artificial nest boxes, fitted with radio-frequency identification (RFID) antennae, to rest and rear litters. The antennae automatically record when mice equipped with a PIT enter and exit a box. Based on these antennae data, we can determine which individuals share nest boxes and for how long. (For further information on the study system refer to König et al. 2015). The series of networks is constructed based on the sharing of nest boxes. The series of networks consists of 14 days of antennae data over the duration of 2 years (population size during this time period ranged between 52 to 188 tagged adult house mice). Inactivity periods of the data collection system extended this time window, so that each time window consists of a similar period of active data collection (see also Liechti et al. 2020). We used total time spent sharing a nest box in seconds as our measure of association strength. Authors:
- Julian Evans^1†,
- Jonas I. Liechti^2†,
- Matthew J. Silk^3,4,
- Barbara König^1‡,
- Sebastian Bonhoeffer^{2‡ †}: Joint first author; ^‡: Joint last author; : Corresponding author: [email protected] 1: Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057 Zurich
2: Institute for Integrative Biology, ETH Zurich, Universitätsstrasse 16, 8092 Zurich, Switzerland
3: Centre for Ecology and Conservation, University of Exeter Penryn Campus, UK
4: Environment and Sustainability Institute, University of Exeter Penryn Campus, UK
Dataset
The raw data of the studied system is present in graphs folder in form of a
list of GraphML files.
The files containing the graphs are numbered according to their order of
appearance in the sequence of graphs. Each file contains a single graph the can be imported for example into
igraph. The following attributes are stored in the graphml files: Graph properties: - start (xml tag: g_start) gives the starting timepoint of
aggregation period. The format is 'YYYY-MM-DD HH:MM:SS'.
- stop (xml tag: g_stop) gives the ending timepoint of the
aggregation period. Node properties: - name (xml tag: v_name) a unique id for each individual that is consistent
across the sequence of graphs.
- x position( xml tag: v_x) is the x position [cm] of the barycentre from
all interactions of this individual.
- y position( xml tag: v_y) is the x position [cm] of the barycentre from
all interactions of this individual. Edge properties: - weight (xml tag: e_weight) is the weight [seconds] of an interaction.
The weight corresponds to the accumulated duration of interactions.