2359 Silwood wood mice

2360 The field data collection was led by Sarah Knowles, and the data was cleaned and

2361 processed by Bryony Allen, Sarah Knowles, and Aura Raulo.

2362 Data were collected over a one-year period (Nov 2014–Dec 2015) from a wild population of

2363 rodents in a 2.47 ha mixed woodland plot (Nash's Copse) at Imperial College's Silwood Park

2364 campus, UK. Data for this study was collected as part of a longer-term rodent capture-mark-

2365 recapture study, where several rodent species were caught (*Apodemus sylvaticus*,

2366 *Apodemus sylvaticus*, *Apodemus flavicollis* and *Myodes glareolus*). Trapping was performed

2367 every 2-4 weeks, using 122 small folding Sherman traps (5.1 x 6.4 x 16.5cm, H. B

2368 Sherman). Traps baited with eight peanuts, a slice of apple and sterile cotton wool for

2369 bedding were set at dusk and collected at dawn, with all animals processed, sampled and

2370 then released inside the 100m2 grid cell they were captured in. As part of processing,

2371 captured individuals were identified to species, sexed, weighed, and aged (juvenile or adult)

2372 based on size and pelage characteristics. At first capture, all individuals were injected

2373 subcutaneously with a passive integrated transponder tag (PIT-tag) for permanent

2374 identification. Ear punches were collected from all mice and stored in ethanol at -20°C to

2375 provide genetic material for host genotyping. Live traps were set in an alternating

2376 checkerboard design, to ensure even coverage. Edges in the social network between

2377 individuals (nodes) were defined as unique mice trapped nearby (within one adjacent trap

2378 distance by Euclidean distance) in the same trapping night.
2380 Sleepy lizards

2381 The following description is adapted from Payne et al. (2022).

2382 We studied sleepy lizards (Tiliqua rugosa), a species of skink native to southern Australia.
2383 Sleepy lizards are large (adults are 400-950 g, with snout-vent length 25-35 cm), mainly
2384 herbivorous, and can live up to 50 years (Bull, 1995; Bull et al., 2017). Social network
2385 studies have shown that sleepy lizards are pair-living with strong male-female pair bonds
2386 (Leu et al., 2010, 2011), exhibiting a long-term socially monogamous mating system (Bull et
2387 al., 1998; Leu et al., 2015). Sleepy lizards are primarily active during the austral spring,
2388 September to December (Bull, 1987). Overnight and during periods of heat stress, they
2389 shelter in shaded refugia (i.e., large shrubs, logs, or burrows) (Kerr et al., 2003).

2390 Our field site was an ~ 1.2 km2 area near Bundey Bore Station (33.888240° S, 139.310718° E), South Australia (about 150 km north of Adelaide). The region has a semi-arid
2391 Mediterranean climate. The local site is dominated by chenopod shrubs (e.g., Maireana and
2392 Atriplex spp.) and patches of black oak trees (Casuarina spp.), with various annual plants
2393 growing between and under these shrubs and trees (e.g., the nonnative Ward's weed,
2394 Carrichtera annua, a preferred food item for sleepy lizards). In most years, food is more
2395 abundant in early spring when conditions are relatively cool and wet, becoming much less
2396 abundant later when conditions are hotter and drier.
2397

2398 As part of a long-term monitoring study, we used GPS units (horizontal precision +/- 6 m
2399 (Leu et al. 2010a)) to record adult lizard movement during their active season (i.e., the
2400 austral spring) from 2008 through 2017, excluding 2012. In 2008 through 2014, GPS units
2401 (Leu et al., 2010) took one GPS fix per 10 minutes, while in 2015 through 2017, GPS units
2402 took one fix per two minutes. To reduce autocorrelation in the GPS data and ensure
2403 consistency across years, following (Michelangeli et al., 2021), we thinned the GPS data
2404 from all years to one point per 20 minutes. We removed GPS errors according to fix
2405 accuracy (e.g., horizontal dilution greater than three), using an algorithm modified from
2406 Bjorneraas (2010) - which identifies errors via displacement, speed, and turning angle - and
2407 with manual inspection of GPS tracks for obvious errors.

2408

2409 References

2410 Bjorneraas, K., Van Moorter, B., Rolandsen, C. M., & Herfindal, I. (2010). Screening Global
2411 Positioning System Location Data for Errors Using Animal Movement Characteristics.
2412 Journal of Wildlife Management, 74(6), 1361-1366. https://doi.org/10.2193/2009-405

2413 Bull, C. M. (1987). A Population Study of the Viviparous Australian Lizard, Trachydosaurus rugosus (Scincidae). Copeia, 1987(3), 749-757.

2415 Bull, C. M. (1995). Population Ecology of the Sleepy Lizard, Tiliqua rugosa, at Mt-Mary, South-Australia. Australian Journal of Ecology, 20(3), 393-402.
2416
2417 https://doi.org/10.1111/j.1442-9993.1995.tb00555.x
2418 Bull, C. M., Cooper, S. J. B., & Baghurst, B. C. (1998). Social monogamy and extra-pair fertilization in an Australian lizard, Tiliqua rugosa. *Behavioral Ecology and Sociobiology*, 2419 44(1), 63-72. https://doi.org/10.1007/s002650050515

2421 Bull, C. M., Gardner, M. G., Sih, A., Spiegel, O., Godfrey, S. S., & Leu, S. T. (2017). Why Is Social Behavior Rare in Reptiles? Lessons From Sleepy Lizards. In M. Naguib, J. Podos, L. 2422 W. Simmons, L. Barrett, S. D. Healy, & M. Zuk (Eds.), *Advances in the Study of Behavior* 2423 (Vol. 49, pp. 1-26). Academic Press. https://doi.org/10.1016/bs.asb.2017.02.001

2425 Kerr, G. D., Bull, C. M., & Burzacott, D. (2003). Refuge sites used by the scincid lizard 2426 Tiliqua rugosa. *Austral Ecology*, 28(2), 152-160. https://doi.org/DOI 10.1046/j.1442-2427 9993.2003.01268.x

2428 Leu, S. T., Bashford, J., Kappeler, P. M., & Bull, C. M. (2010). Association networks reveal 2429 social organization in the sleepy lizard. *Animal Behaviour*, 79(1), 217-225. 2430 https://doi.org/10.1016/j.anbehav.2009.11.002

2431 Leu, S. T., Burzacott, D., Whiting, M. J., & Bull, C. M. (2015). Mate Familiarity Affects Pairing 2432 Behaviour in a Long-Term Monogamous Lizard: Evidence from Detailed Bio-Logging and a 2433 31-Year Field Study. *Ethology*, 121(8), 760-768. https://doi.org/10.1111/eth.12390

2434 Leu, S. T., Kappeler, P. M., & Bull, C. M. (2011). Pair-living in the Absence of Obligate 2435 Biparental Care in a Lizard: Trading-off Sex and Food? *Ethology*, 117(9), 758-768. 2436 https://doi.org/10.1111/j.1439-0310.2011.01934.x

2437 Michelangeli, M., Payne, E., Spiegel, O., Sinn, D. L., Leu, S. T., Gardner, M. G., & Sih, A. 2438 (2021). Personality, spatiotemporal ecological variation and resident/explorer movement 2439 syndromes in the sleepy lizard. *Journal of Animal Ecology*, 91(1), 210-223. 2440 https://doi.org/10.1111/1365-2656.13616

2441 Payne, E., Spiegel, O., Sinn, D. L., Leu, S. T., Gardner, M. G., Godfrey, S. S., Wohlfeil, C., & 2442 Sih, A. (2022). Intrinsic traits, social context, and local environment shape home range size 2443 and fidelity of sleepy lizards. *Ecological Monographs*, 92(3), e1519. 2444 https://doi.org/10.1002/ecm.1519
2446 Soay sheep

2447 This study was carried out on a long-term study population of Soay sheep (*Ovis aries*) on the
2448 St Kilda archipelago. The Soay sheep have lived wild on the archipelago for millennia, and
2449 have been monitored since 1985 in our study area in Village Bay on Hirta. The natural
2450 history and population dynamics of these sheep have been extensively documented
2451 (Clutton-Brock & Pemberton, 2004). Sheep are captured, marked at birth, and followed
2452 longitudinally across their lifespan to collect morphological, behavioural, parasitological, and
2453 immunological data.

2454 Census data were collected for the years 1988-2018. Sheep are censused 30 times per year
2455 (10 each in spring, summer, and autumn). Experienced fieldworkers follow established
2456 routes noting the identity, spatial location (to nearest 100m OS grid square), behaviour and
2457 group membership of individual sheep. Fieldworkers assign individual sheep to groups using
2458 a 'chain rule', where individuals in close proximity are classed as associating (Castles et al.,
2459 2014). In total, census data comprises 357,283 total observations of 81,769 groups.
2460 Individuals were associated with a mean of 50 unique groups across our total dataset (range
2461 1-464). We used census records to construct annual social networks for each individual
2462 sheep, based on group membership in the same observation event.

2463

2464 References

2465 Castles, M., Heinsohn, R., Marshall, H. H., Lee, A. E. G., Cowlishaw, G., & Carter, A. J. (2014). Social networks created with different techniques are not comparable. Animal Behaviour, 96, 59–67.

2468 Clutton-Brock, T. H., & Pemberton, J. M. (2004). Soay Sheep: Dynamics and Selection in an Island Population. Cambridge University Press.

2470
## 2471 Vulturine guineafowl

2472 The vulturine guineafowl (Acryllium vulturinum) is a terrestrial bird species (body size: 60-72 cm) that lives in the arid and semi-arid savanna of East Africa. Vulturine guineafowl are gregarious and typically live in stable groups of 15-65 individuals ¹. Groups are highly cohesive throughout and across the day. Previous work has suggested that groups are non-territorial, establishing highly overlapped home ranges among neighbouring groups ²,³.

2473
2474
2475
2476
2477
2478
2479
2480
2481
2482
2483
2484
2485
2486
2487
2488
2489
2490
2491
2492
2493
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
2508
2509
2510

The vulturine guineafowl project was established in 2016 and collects data on up to 23 social groups (a total of 1189 birds) around the Mpala Research Centre in central Kenya. These data include fitting birds from each group with a global positioning system (GPS; 15g eObs solar) tag. These tags collect 1 data point per second (1 Hz), 10 consecutive data points every 5 minutes, or 1 data point every 15 minutes at the least, depending on the battery conditions (see ⁵ for more details). Here we used data from every 15th minute. In addition to the GPS tags, almost all individuals in our population have been fitted with a unique combination of colour bands for individual identification. Each day (morning and evening), a field team census groups in the area, recording the membership of each observed group and its location.

To obtain group size, we used the data from the group compositions for each month (see ⁶ for details) and combined the GPS data (where groups are) with group membership. In brief, we construct networks of robust co-observations among individuals ⁷, and then apply a community detection algorithm (walktrap community algorithm, using igraph package ⁸ in R) to identify groups. From these groups, we could quantify what GPS tags were in the same group and how many birds the group contained, thereby allowing us to estimate local densities.

The contact network was constructed based on the observation that meeting groups tend to mingle completely; each identified group-group contact event assumed that all individuals in one group were meeting all individuals in another group, with a threshold of 20 metres taken to represent a contact event.

## 2503 References

1. Papageorgiou, D. et al. The multilevel society of a small-brained bird. Current Biology 29, R1120–R1121 (2019).

2. Papageorgiou, D., Rozen-rechels, D., Nyaguthii, B. & Farine, D. R. Seasonality impacts collective movements in a wild group-living bird. 1–12 (2021).

3. Papageorgiou, D., Cherono, W., Gall, G., Nyaguthii, B. & Farine, D. R. Testing the information centre hypothesis in a multilevel society. Journal of Animal Ecology (2024) doi:10.1111/1365-2656.14131.
2511 4. Klarevas-Irby, J. A., Nyaguthii, B. & Farine, D. R. Moving as a group imposes
2512 constraints on the energetic efficiency of movement. Proceedings B 292, (2025).

2513 5. He, P. et al. A guide to sampling design for GPS-based studies of animal societies.
2514 Methods Ecol Evol 14, 1887-1905 (2023).

2515 6. Ogino, M., Strauss, E. D. & Farine, D. R. Challenges of mismatching timescales in
2516 longitudinal studies of collective behaviour. Philosophical Transactions of the Royal Society
2517 B 378, (2023).

2518 7. Shizuka, D. & Farine, D. R. Measuring the robustness of network community
2519 structure using assortativity. Anim Behav 112, 237-246 (2016).

2520 8. Csardi, G. & Nepusz, T. The igraph software package for complex network research.
2521 InterJournal Complex Systems Complex Sy, 1695 (2006).

2522
2523 Water dragons

2524 Data were collected as part of an ongoing behavioural study of a population of eastern water dragons (*Intellagama lesueurii*) inhabiting an urban city park, Roma Street Parklands, Brisbane, Australia (27°27'46' S, 153°1'11' E). Consisting of approximately 336 individuals, the population inhabits a highly heterogenous, man-made, curated public garden (Strickland et al, 2014). Behavioural surveys were conducted twice daily (morning 7.30-10.30 and afternoon 13.00-16.00) approximately three days a week from November 2010 onwards.
2525
2526
2527
2528
2529 Data collection was restricted from September one year until April the following year,
2530
2531 representing the season in which dragons are active and not in brumation.

2532 For each individual encountered, a photo of their left and/or right facial profile, along with
2533 their GPS location was recorded. An individual's sex was assigned based on sexual
2534 dimorphism and dichromatism (Thompson, 1993). The individual's immediate behaviour at
2535 the time of the observation was recorded, which included a spectrum from resting to
2536 agonism (e.g. head bobbing, tail slapping, arm waving, chasing and physical combat).

2537 Profile photographs taken during surveys were used to identify individuals using a previously
2538 established method for this population (Gardiner et al, 2014). This method employed
2539 interactive identification software (I3S Spot, v. 4.0.2) which compared individual facial profile
2540 scale patterns from images taken during behavioural surveys to an existing photo library. We
2541 also took GPS locations of every observation; on each census, individuals with less than
2542 1.85m between them were taken to be in contact.

2543

2544 References

2545 Gardiner, R.Z., Doran, E., Strickland, K., Carpenter-Bundhoo, L. and Frère, C. A face in the crowd: a non-invasive and cost effective photo-identification methodology to understand the fine scale movement of eastern water dragons. PloS one 9, 96992 (2014).

2548 Strickland, K., Gardiner, R., Schultz, A.J. and Frere, C.H., 2014. The social life of eastern water dragons: sex differences, spatial overlap and genetic relatedness. Animal Behaviour
2549
2550 97, 53-61 (2014).

2551 Thompson, M.B. Estimate of the population structure of the eastern water dragon, Physignathus lesueurii (Reptilia: Agamidae), along riverside habitat. Wildlife Research 20,
2552
2553 613-619 (1993).

2554

2555
2556 Wild crickets

2557 The aim of the project was to monitor a wild population of field crickets (Gryllus campestris)
2558 living in a meadow in North Spain. This species is annual, and every individual spends most
2559 of its life inside or in the vicinity of burrows excavated in the ground. We monitored the
2560 natural population for 12 consecutive years. Every year, we found all the burrows in the
2561 meadow and marked them with a flag having a unique number. We trapped every individual
2562 in the population shortly after they emerged as adults and marked them with a plastic tag
2563 with a unique code for each individual. We used up to 140 infra-red video cameras to record
2564 24hrs a day at burrows and an area of about 20cm in diameter around the burrow from the
2565 date of first adult emergence to the date when the last adult in the population died. We then
2566 watched the video and extracted a number of relevant behaviours for each recorded
2567 individual, which were then used to form the social networks. A more detailed description of
2568 our methodology can be found in Rodríguez-Muñoz et al. (2019).

2569

2570 References

2571 Rodríguez-Muñoz, R., Boonekamp, J. J., Liu, X. P., Skicko, I., Fisher, D. N., Hopwood, P., & Tregenza, T. (2019). Testing the effect of early-life reproductive effort on age-related decline in a wild insect. Evolution, 73, 317-328. doi: 10.1111/evo.13679

2574

2575
2576 Woodchester badgers

2577 The Woodchester Park badger study is conducted at Woodchester Park, Gloucestershire, UK (51.7°N,2.25°W), and has been ongoing since 1976 ¹,². For the purposes of this study 2578 co-trapping data were used to estimate both population density and social networks (note 2579 that co-trapping will only provide a proxy for social associations in this system;³). The study 2580 site is divided into three zones of approximately equal size, each of which is trapped four 2581 times per year from May to January inclusive (no captures occur in the intervening period to 2582 avoid catching dependent cubs and their mothers). Box traps constructed of steel mesh are 2583 set close to each active main and outlying sett (detected by sett activity surveys in the build- 2584 up to trapping) and baited with peanuts for up to 8 days. Traps are then set for two 2585 consecutive nights and checked the following mornings. At each active sett, more traps are 2586 deployed than expected to be required. On first capture badgers are permanently marked 2587 with a unique ID tattoo on the abdomen allowing them to be identified on future captures ⁴. 2588 Individuals are typically caught (on average) approximately two times per year². 2589

2590 Co-trapping networks can then be constructed based on individuals being caught at the 2591 same sett on the same day. Because these networks are constructed using co-trapping data 2592 only they can include all individuals regardless of their age or sex.

2593

2594 References

2595 1. McDonald, J. L., Robertson, A. & Silk, M. J. Wildlife disease ecology from the 2596 individual to the population: Insights from a long-term study of a naturally infected European 2597 badger population. Journal of Animal Ecology 87, 101–112 (2018).

2598 2. Delahay, R. J. et al. Long-term temporal trends and estimated transmission rates for 2599 Mycobacterium bovis infection in an undisturbed high-density badger (Meles meles) 2600 population. Epidemiol Infect 141, 1445–1456 (2013).

2601 3. Silk, M. J., McDonald, R. A., Delahay, R. J., Padfield, D. & Hodgson, D. J. CMRnet: 2602 An r package to derive networks of social interactions and movement from mark–recapture 2603 data. Methods Ecol Evol 12, 70–75 (2021).

2604 4. Cheeseman, C. L. & Harris, S. Methods of marking badgers (Meles meles). Journal 2605 of Zoology, Lond. 197, 289–292 (1982).

2606

2607
2608 Wytham badgers

2609 The Wytham Badger Project ran 1987 to 2019 and attempted to monitor all badgers resident
2610 in the Wytham Woods SSSI, a 4.24 km2 mixed woodland in southern England (51° 46' N,
2611 1° 20' W; for further information, see Macdonald & Newman 2022). The population is
2612 situated on a hill surrounded by the River Thames on three sides and the A34 motorway on
2613 the fourth, mimizing migration (immigration/emigration rate = 3%: Macdonald and
2614 Newman 2002). Over the study period, every active communal burrow system, termed a
2615 "sett", was trapped using string-trigger traps for two or (most commonly) three nights, three-
2616 four times per year, at regular seasonal intervals. Badgers were transferred to holding cages
2617 between 7:00 and 9:00 a.m., transported to a central feldstation, and sedated with 0.2 mL
2618 ketamine hydrochloride/kg body weight by intramuscular injection (McLaren et al. 2005). On
2619 first capture (typically as a cub or yearling), each badger received a unique numerical
2620 inguinal tattoo. The population divided into 23 social groups, established from frequent
2621 baitmarking surveys (Buesching et al. 2016), where each social group utilized several setts
2622 consisting of 1–10 holes, with on average 5.5 individuals cohabitating in the average sett
2623 (range 1 to 28).

2624 In total, the study amassed 11,488 captures of 1823 individuals, to which an enhanced
2625 Minimum Number Alive (eMNA; Bright Ross et al. 2002) enumeration procedure was
2626 applied. Population size averaged 242 adults ± 15.14 SD, range = 222–263) plus 66 cubs (±
2627 8.1 SD, range = 47–97) from 2005 to 2009. Thereafter, following high, and unexplained,
2628 mortality across age classes in 2010, the population settled to a slightly lower but stable
2629 phase through to 2015, comprising 195 adults (± 17.06 SD, range = 177–217) and 49 cubs
2630 (± 15.47 SD, range = 24–66; Bright Ross et al. 2020). In 2019, population density was 44.55
2631 ± 5.37 badgers km-2, where Wytham Woods has consistently had the highest density of
2632 European badgers ever recorded (Macdonald and Newman 2022). Co-trapping networks
2633 were then constructed based on individuals being caught at the same sett on the same day.

2634

2635

2636 References

2637 Buesching, C. D., Newman, C., Service, K., Macdonald, D. W., & Riordan, P. (2016). Latrine
2638 marking patterns of badgers (Meles meles) with respect to population density and range
2639 size. Ecosphere, 7(5), e01328.

2640 Bright Ross, J. G., Newman, C., Buesching, C. D., & Macdonald, D. W. (2022). Preserving
2641 identity in capture–mark–recapture studies: increasing the accuracy of minimum number
2642 alive (MNA) estimates by incorporating inter-census trapping efficiency variation. Mammalian
2643 Biology, 102(3), 567-580.

2644 Macdonald, D. W., & Newman, C. (2002). Population dynamics of badgers (Meles meles) in
2645 Oxfordshire, UK: numbers, density and cohort life histories, and a possible role of climate
2646 change in population growth. Journal of Zoology, 256(1), 121-138.
2647 Macdonald, D., & Newman, C. (2022). The Badgers of Wytham Woods: a model for behaviour, ecology, and evolution. Oxford University Press.

2649 McLaren, G. W., Thornton, P. D., Newman, C., Buesching, C. D., Baker, S. E., Mathews, F., & Macdonald, D. W. (2005). The use and assessment of ketamine–medetomidine–butorphanol combinations for field anaesthesia in wild European badgers (Meles meles). Veterinary anaesthesia and analgesia, 32(6), 367-372.

2653
2654 Wytham tits

2655 The study was conducted in Wytham Woods, Oxford, UK (51°46' N, 1°20' W), on a great tit (Parus major) population monitored using standardized protocols since the 1960s [1]. Great 2656 tits breed almost exclusively in nest boxes fixed at 1020 GPS-mapped locations across 2657 Wytham Woods [2]. Over 98% of breeding great tits occupy a single nest box per year, with 2658 breeding spanning April–July and comprising nest building, egg laying, incubation, and 2659 offspring rearing. Nestboxes were regularly checked to monitor breeding attempts, identify 2660 (or mark) adults (days 6–14 of the nestling phase), and mark nestlings (day 15) with unique 2661 British Trust for Ornithology (BTO) metal leg rings, alongside taking standard morphometric 2662 measurements [1-3]. 2663

2664 In winter (September–March), great tits form highly dynamic, fission-fusion feeding flocks 2665 with frequent turnover [3-5]. Since 2007, great tits captured during breeding or winter mist- 2666 netting have been fitted with plastic leg rings containing a unique RFID microchip, resulting 2667 in the RFID tagging of ~90% of the population [4]. RFID tags enable tracking of individuals at 2668 sunflower feeding stations equipped with two RFID antennae (Dorset ID, Aalten, 2669 Netherlands) at placed in 65 stratified-grid locations through in winters starting 2011, 2012, 2670 and 2013. During these winter seasons, these feeders were open every weekend from End- 2671 Nov to End-February (13 weekends), continuously scanning for RFID-tagged birds from pre- 2672 dawn to post-dusk.

2673 Winter Population Social Structure

2674 RFID detections generated a spatiotemporal datastream reflecting the bursts of activity as 2675 flocks arrived and fed. A machine-learning algorithm (Gaussian mixture model) assigned 2676 detections to the most likely flock or ‘gathering event’, providing a robust and effective 2677 method for determining flock co-membership [5]. From the resulting group-by-individual 2678 matrices, social networks (association matrices) were constructed using the Simple Ratio 2679 Index [5,6].

2680 For this analysis, non-directional weighted networks were built from the yearly (i.e. whole 2681 winter season GBI matrix) to measure dyadic association propensity, and the extensive 2682 sampling here reduces the typical limitations of the ‘gambit of the group’ approach [7]. 2683 Networks included all RFID-detected individuals linked to a unique BTO ring number. Due to 2684 high turnover and movement, kin structure was weak, with only ~1.5% of winter social 2685 connections occurring between first-order relatives [7]; therefore, relatedness was not 2686 considered a key structuring factor. Nevertheless, this social network dataset is known to be 2687 biologically meaningful, and forms part of a broader investigation into great tit social ecology, 2688 contributing insights into individual sociality [8,9], social structure and demography [7,10], 2689 and links to ecological processes such as information transmission [11,12], foraging [13, 14], 2690 breeding settlement and mating behavior [7,14,15].

2691 All work was approved by the University of Oxford, Department of Zoology, Animal Welfare 2692 and Ethical Review Board (Approval: APA/1/5/ZOO/NASPA/Sheldon/TitBreedingEcology) 2693 and adhered to local animal research guidelines. All birds were caught, tagged, and ringed 2694 by licensed BTO ringers.
2696 References

2697 Perrins CM. 1965 Population fluctuations and clutch-size in the great tit, Parus major L. J

2698 Anim Ecol 34, 601–647. (doi:10.2307/2405301)

2699 Wilkin TA, Perrins CM, Sheldon BC. 2007 The use of GIS in estimating spatial variation in habitat quality: a case study of lay-date in the Great Tit Parus major. Ibis 149, 110–118.

2700 (doi:10.1111/j.1474-919X.2006.00627.x)

2702 Farine DR, Firth JA, Aplin LM, Crates RA, Culina A, Garroway CJ, Hinde CA, Kidd LR, Milligan ND, Psorakis I, et al. 2015 The role of social and ecological processes in structuring

2704 animal populations: a case study from automated tracking of wild birds. R Soc Open Sci 2,

2705 150057. (doi:10.1098/rsos.150057)

2706 Aplin LM, Farine DR, Morand-Ferron J, Cole EF, Cockburn A, Sheldon BC. 2013 Individual

2707 personalities predict social behaviour in wild networks of great tits (Parus major). Ecol Lett

2708 16, 1365–1372. (doi:10.1111/ele.12181)

2709 Psorakis I, Voelkl B, Garroway CJ, Radersma R, Aplin LM, Crates RA, Culina A, Farine DR,

2710 Firth JA, Hinde CA, et al. 2015 Inferring social structure from temporal data. Behav Ecol

2711 Sociobiol 69, 857–866. (doi:10.1007/s00265-015-1906-0)

2712 Cairns SJ, Schwager SJ. 1987 A comparison of association indices. Anim Behav 35, 1454–

2713 1469. (doi:10.1016/S0003-3472(87)80018-0)

2714 Firth JA, Sheldon BC. 2016 Social carry-over effects underpin trans-seasonally linked

2715 structure in a wild bird population. Ecol Lett 19, 1324–1332. (doi:10.1111/ele.12669)

2716 Aplin LM, Firth JA, Farine DR, Voelkl B, Crates RA, Culina A, Garroway CJ, Hinde CA, Kidd

2717 LR, Psorakis I, et al. 2015 Consistent individual differences in the social phenotypes of wild

2718 great tits, Parus major. Anim Behav 108, 117–127. (doi:10.1016/j.anbehav.2015.07.016)

2719 Firth JA, Voelkl B, Crates RA, Aplin LM, Biro D, Croft DP, Sheldon BC. 2017 Wild birds

2720 respond to flockmate loss by increasing their social network associations to others. Proc. R.

2721 Soc. B Biol. Sci. 284. (doi:10.1098/rspb.2017.0299)

2722 Beck, K. B., Farine, D. R., Firth, J. A., & Sheldon, B. C. (2023). Variation in local population

2723 size predicts social network structure in wild songbirds. Journal of Animal Ecology, 92(12),

2724 2348–2362. https://doi.org/10.1111/1365-2656.14015

2725 Aplin LM, Farine DR, Morand-Ferron J, Sheldon BC. 2012 Social networks predict patch

2726 discovery in a wild population of songbirds. Proc Biol Sci 279, 4199–4205.

2727 (doi:10.1098/rspb.2012.1591)

2728 Firth JA, Sheldon BC, Farine DR. 2016 Pathways of information transmission among wild

2729 songbirds follow experimentally imposed changes in social foraging structure. Biol Lett 12,

2730 20160144. (doi:10.1098/rsbl.2016.0144)
2731 McMahon K, Marples NM, Spurgin LG, Rowland HM, Sheldon BC, Firth JA. 2024 Social network centrality predicts dietary decisions in a wild bird population. iScience 27, 109581. (doi:10.1016/j.isci.2024.109581)

2734 Firth JA, Voelkl B, Farine DR, Sheldon BC. 2015 Experimental evidence that social relationships determine individual foraging behavior. Curr Biol 25, 3138-3143. (doi:10.1016/j.cub.2015.09.075)

2737 Firth JA, Cole EF, Ioannou CC, Quinn JL, Aplin LM, Culina A, McMahon K, Sheldon BC. 2018 Personality shapes pair bonding in a wild bird social system. Nat Ecol Evol, 1696-1704. (doi:10.1038/s41559-018-0670-8)

2740

2741
2742 Wytham wood mice

2743 This data set is a trapping data set of wild rodents caught in Holly Hill, Wytham Woods 2018-
2744 2019. Rodents were trapped approximately fortnightly and new individuals tagged with a
2745 PIT-tag for permanent identification. Individuals were then released back to their point of
2746 capture. Data were collected over a 1-year period (Nov 2018–Nov 2019) from a wild
2747 population of rodents in a 4 ha (200 x 200 meters square) mixed woodland plot. Data for this
2748 study was collected as part of a longer-term rodent capture-mark-recapture study, where
2749 several rodent species were caught (*Apodemus sylvaticus*, *Apodemus flavicollis* and
2750 *Myodes glareolus*). Trapping was performed every 2-4 weeks, using 200 small folding
2751 Sherman traps (5.1 x 6.4 x 16.5cm, H. B Sherman). To ensure even trapping coverage, live
2752 traps were set with an alternating checkerboard design in every other 10 x 10 meter "Grid
cell" of the 200 x 200 meters study area. Traps baited with 6 peanuts, a slice of apple and
2753 sterile cotton wool for bedding were set at dusk and collected at dawn, with all animals
2754 processed, sampled and then released inside the 100m2 grid cell they were captured in. As
2755 part of processing, captured individuals were identified to species, sexed, weighed, and
2756 aged (to juvenile or adult) based on size and pelage characteristics. At first capture, all
2757 individuals were injected subcutaneously with a passive integrated transponder tag (PIT-tag)
2758 for permanent identification. There were a few cases (~2% of captures) where the animal
2759 died during trapping and thus was not released. This was most often due to animal being
2760 found dead in the trap (which can happen due to epidemics or other poor health especially in
2761 the spring) and in a couple of cases due to animal being put down following Schedule 1 due
2762 to extreme poor health or injury. Edges in the social network between individuals (nodes)
2763 were defined as unique mice trapped nearby (within one adjacent trap distance by Euclidean
distance) in the same trapping night.
2764
2765

2766

2767