DOI: 10.5061/dryad.kd51c5bkh
title: Data from: Multi-species sensory networks and social foraging strategies: Implications for population decline in procellariiform seabirds

description: Multi-species sensory networks, where different species prioritize
 different sensory modalities and then use heterospecific information in a
 likely non-cooperative fashion, may allow animals to improve foraging over
 large areas for cryptic prey. We test this hypothesis in procellariiform
 seabirds that forage in mixed flocks, where both prey odors and visual
 cues provided by other foraging hetero- and con-specifics might improve
 success rates. Using agent-based models, we explored the impact of social
 strategies on olfactory foraging for Antarctic krill (Euphausia superba).
 Our results suggest that social foraging enables species with different
 sensory adaptations to achieve similar success rates. Additionally, our
 results indicate that foraging is more successful in mixed-species rather
 than single-species flocks, where individuals can monitor the activity of
 other birds that are using different sensory foraging strategies than
 themselves to find prey. These results suggest that sensory-based foraging
 networks may be more critical to their survival than previously assumed.
 Finally, we show that success rates decrease at low population densities.
 As seabird populations continue to decline, understanding and preserving
 these social foraging networks may be essential for their conservation and
 ecological success. Overall, our study provides insights into the critical
 role of multi-species sensory networks for foraging success, wherein
 different species have different sensory adaptations for locating prey.
 While we used empirical anatomical and behavioral data specific to
 procellariiforms to inform our models, our approach and results may have
 broader implications for other species as well.
description: # **Multi-species sensory networks and social foraging strategies:
 implications for population decline in procellariiform seabirds** Dataset
 DOI: [10.5061/dryad.kd51c5bkh](10.5061/dryad.kd51c5bkh) **Description of
 the data and file structure** These data are for the manuscript
 "Multi-species sensory networks and social foraging strategies:
 implications for population decline in procellariiform seabirds"  A
 description of every variable in the model can be found in the
 supplemental information, table S1. Additional information about the
 variables are listed here: For the files that contain the phrase “Fig_3,”
 or “Fig_4” the variables are described here: ·         Species1 or
 Species2: The “species” for the birds. In all cases “Set Manual” was used,
 and the bird’s body length and flight speed were set manually, rather than
 using the pre-selection. ·         N-Species1 or N-Species2: The number of
 birds in species 1 or species 2, respectively ·         S1-DR or S2-DR:
 The detection distance (or vision) that the agent can detect another agent
 in units of body-lengths. This value is multiplied by the agent’s body
 length to get the value in meters or patches. ·         S1-Olfaction or
 S2-Olfaction: The olfactory abilities of the agent. Can be either low,
 high, or none. These values are described in the main text. ·        
 Strategy: The movement strategy the animal used while foraging. These
 options are described in the main text. ·         S1-Flight-Speed-MpS or
 S2-Flight-Speed-MpS: The speed that the agents move, in meters per second
 ·         S1-Body-Length-Meters or S2-Body-Length-Meters: The agent’s body
 length, in meters ·         Seed: The model seed (controls the
 randomization of variables) ·         [step]: The tick, or step time, at
 which the model terminated. If this value is less than 3600 then the model
 terminated early, indicating that at this time all of the agents had
 either found the food or exited the map ·         (count turtles with
 [did-find-food = 1]): The number of agents that successfully found the
 food ·         (count turtles with [did-find-food = 1 and ever-find-odor =
 0]): The number of agents that successfully found the food, but never
 found the odor ·         (count turtles with [did-find-food = 1 and
 ever-find-odor = 1]): The number of agents that successfully found the
 food, and found the odor at some point in time ·         (allfoundodor):
 The number of agents that found the odor at some point in time ·        
 (count turtles): The number of agents still on the map at the time the
 model ended The files that contain the phrase “Parameterizing” contain
 some of the variables describes above, in addition to some of the
 following variables: ·         Rate-Of-Puff-Radius-Increase: The rate at
 which the puff’s radius increases over time (as a function of diffusion)
 in meters/s ·         Odor-Source-Release-Rate: The rate at which puffs
 are being generated by the food source, in puffs/s ·        
 Eddy-Diffusivity: The exponent which sets the small-scale eddy diffusion
 coefficient. This value is the exponent X in 10^X (for example, a value of
 -1 results in 0.1 m2/s, while a value of 1 results in 10 m2/s) ·        
 weight-flocking: The amount to which the agents prioritize moving towards
 flockmates versus moving crosswind (the weighting for the flocking
 heading) where 1 = only flocking, and 0 = only moving crosswind ·        
 Time-Per-Turn: The total amount of time that elapses in between
 directional changes once the odor plume has been lost (i.e. the amount of
 time they continue to move upwind, and then the amount of time they
 maintain each heading before turning in the opposite direction during the
 zigzags) ·         zig-zag-heading-offset: The angle relative to “upwind”
 that the birds take during the zigzag headings (i.e. the direction they
 face during the zigzags, where 0 = upwind, and 90 = crosswind) ·        
 max-turning-radius-degrees-per-second: The maximum angle the birds are
 ever able to turn per second (their “roll angle”) ·        
 max-align-cohere-turn-degrees-per-second: The maximum angle the birds turn
 when aligning and cohering per second. Should not exceed the maximum
 turning radius ·         max-separate-turn-degrees-per-second: The maximum
 angle the birds turn when separating per second. Should be very small, as
 this is only a slight adjustment to prevent collisions ·        
 Denominator-For-Relationship-Between-DR-and-MinSep: The denominator which
 controls the relationship between DR and the minimum separation between
 birds (i.e. the minimum spacing between birds in a group) which is set as
 minimum separation = DR / denominator. The minimum separation value in
 meters as a function of this denominator is shown in the corresponding S1
 or S2 Minimum Separation monitors **Files and variables** **File:
 Netlogo_Model_v16.nlogo** The Netlogo model used to generate all data.
 **File: Code_for_Publication_Combined_Main_and_Supp_for_Dryad.Rmd** The
 code for analyzing all models and generating all figures **File:
 Fig_3A_BBA_v1.csv** The data used to generate figure 3A for the
 Black-browed Albatross (BBA) for seeds 1:100. **File: Fig_3A_BBA_v2.csv**
 The data used to generate figure 3A for the Black-browed Albatross (BBA)
 for seeds 101:500. **File: Fig_3A_WSP.csv** The data used to generate
 figure S5A, which is equivalent to figure 3A but for the Wilson's
 storm petrel (WSP). **File: Fig_3A_WCP.csv** The data used to generate
 figure S6A, which is equivalent to figure 3A but for the White-chinned
 petrel (WCP). **File: Fig_3A_Wandering_Albatross.csv** The data used to
 generate figure S7A, which is equivalent to figure 3A for the Wandering
 Albatross (WA). **File: Fig_3B_BBA_pop_5.csv** The data used to generate
 figure 3B for the BBA for a population of 5 birds. **File:
 Fig_3B_BBA_pop_10.csv** The data used to generate figure 3B for the BBA
 for a population of 10 birds. **File: Fig_3B_BBA_pop_20.csv** The data
 used to generate figure 3B for the BBA for a population of 20 birds.
 **File: Fig_3B_WSP.csv** The data used to generate figure S5B, which is
 equivalent to figure 3B but for the WSP. **File: Fig_3B_WCP.csv** The data
 used to generate figure S6B, which is equivalent to figure 3B but for the
 WCP. **File: Fig_3B_Wandering_Albatross.csv** The data used to generate
 figure S7B, which is equivalent to figure 3B but for the WA. **File:
 Fig_4_BBA_and_WCP.csv** The data used to generate figure 4 for the BBA and
 WCP. **File: Fig_4_WSP.csv** The data used to generate figure S5C, which
 is equivalent to figure 4 but for the WSP. **File: Fig_4_WCP.csv** The
 data used to generate figure S6C, which is equivalent to figure 4 but for
 the WCP. **File: Fig_4_Wandering_Albatross.csv** The data used to generate
 figure S7C, which is equivalent to figure 4 but for the WA. **File:
 Fig_4_BBA.csv** The data used to generate figure S8, which is equivalent
 to figure 4 but all of the birds are BBA. **File:
 Parameterizing_Sensitivity_Analysis.csv** The data used to generate table
 S2. **File: Parameterizing_Odor_Plume.csv** The data used to generate
 figures S1 and S2. **File: Parameterizing_MinSep.csv** The data used to
 generate figure S3. **File: Parameterizing_ZigZag.csv** The data used to
 generate figure S4. **Code/software** Modeling was done using the
 agent-based software, Netlogo, version 6.2.2. Results were analyzed and
 plotted in R, version 4.3.1. **Access information** Other publicly
 accessible locations of the data: * [Github
 Repo](https://github.com/jngranger/Multi-species-sensory-networks-and-social-foraging-strategies-implications-for-population-decline)