DOI: 10.5061/dryad.jdfn2z3kn
title: Data from: home ranges, habitat selection, and energy expenditure of Strix varia (Barred Owls): understanding the full diel cycle matters for enhancing urban landscapes

description: We integrated GPS and accelerometer data to examine habitat selection and
 energy expenditure patterns across the diel cycle in Barred Owls (Strix
 varia), addressing a critical gap in wildlife research that often
 overlooks activity during the “inactive” phase. Owls in Baton Rouge,
 Louisiana, selected forests with tall canopies and open understories,
 particularly in affluent neighborhoods, supporting the “luxury effect” in
 urban biodiversity. Nocturnal home ranges were larger (31.8 ha) compared
 to diurnal home ranges (8.9 ha), indicating broader habitat use at night.
 The total area of preferred nocturnal habitat was 33% of the Baton Rouge
 study area, whereas preferred diurnal habitat comprised only 5%. Energy
 expenditure was inversely related to preference in nocturnal home ranges
 but increased with preference in diurnal home ranges. Our models were
 validated using independent data from Clemson, South Carolina, supporting
 the robustness of our analysis and revealing generalities in owl habitat
 selection across these regions. This research contributes to a deeper
 understanding of urban ecology, highlighting habitat components preferred
 by owls and possibly other forest-dwelling species. It emphasizes the
 difference in nocturnal and diurnal home range sizes, the scarcity of
 daytime refuges for Barred Owls in urban landscapes, and the variation in
 energy expenditure in preferred habitats. Our findings advocate for urban
 designs that accommodate wildlife activity throughout the day and night,
 and highlight the positive correlation between preferred owl habitat and
 affluent neighborhoods, underscoring the need for equitable distribution
 of green spaces to foster biodiversity across socioeconomic gradients.
 These insights will help develop strategies to enhance the ecological
 value of urban environments and the conservation of Barred Owls and
 associated forest-dwelling species in rapidly urbanizing areas.
description: Please see the associated publication.
description: # Data from: home ranges, habitat selection, and energy expenditure of
 Strix varia (Barred Owls): understanding the full diel cycle matters for
 enhancing urban landscapes
 [https://doi.org/10.5061/dryad.jdfn2z3kn](https://doi.org/10.5061/dryad.jdfn2z3kn) ## Description of the data and file structure ### Manuscript Reference: These data are associated with the manuscript titled "Home ranges, habitat selection, and energy expenditure of Barred Owls: Understanding the full diel cycle matters for enhancing urban landscapes," accepted for publication in the journal *Ornithological Applications* (Manuscript Number: ORNITH-APP-24-092R1). ### Corresponding Author: * **Name**: Vitek Jirinec, Ph.D. * **Affiliation**: Integral Ecology Research Center, Blue Lake, California, USA * **Email**: [vjirinec@iercecology.org](mailto:vjirinec@iercecology.org) ### Contributors: * Alessandra M. Bresnan * Marion Clément * Melanie R. Colón * Ashley M. Long * Garrett Rhyne * Patricia Rodrigues * Eliza Stein * Anna Pérez-Umphrey * Christina Varian * Steven Tyler Williams * Sabrina S. Taylor ### Abstract: These datasets include GPS location data, overall dynamic body acceleration (ODBA) data, and home range information for Barred Owls (*Strix varia*) collected in urban and suburban environments in Baton Rouge, Louisiana. The data were collected to study the habitat selection and energy expenditure patterns across the diel cycle of Barred Owls, with a particular focus on the impacts of urbanization and human affluence on these factors. ### Data Files: 1. **owl_GPS_data.csv**: This file contains GPS location data of Barred Owls collected during the study period in Baton Rouge. Each row represents a unique GPS point with associated timestamp, location coordinates, and owl ID. These data are also archived at Movebank ([https://www.movebank.org/cms/webapp?gwt_fragment=page=studies,path=study4341276830](https://www.movebank.org/cms/webapp?gwt_fragment=page=studies,path=study4341276830)). 2. **owl_ODBA_data.csv**: This file includes summarized ODBA data for each owl, which was originally measured at 5-second intervals. Each row represents the logarithm of the average ODBA sum for each period. Please see publication for more details. 3. **owl_range_data.csv**: This file contains data on home ranges calculated for the tagged Barred Owls, including home range area, area of forest and impervious surfaces, and the mean selection probability for each of the three home range types. ### Description of Experimental Efforts: The data was collected as part of a broader effort to understand how Barred Owls navigate and utilize urban and suburban landscapes. The study involved capturing and tagging owls with GPS and accelerometer loggers to monitor their movements and energy expenditure over time. Data collection took place from 2018 to 2021 in Baton Rouge, Louisiana. The study aims to reveal insights into habitat selection patterns across the diel cycle, with implications for urban planning and wildlife conservation. ### Funding: This research was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, McIntire Stennis program, and the Margaret H. Lloyd SmartState Endowment for Urban Ecology and Restoration. ### Files and variables #### File: owl\_ODBA\_data.csv **Description:** This file includes summarized ODBA data for each owl, which was originally measured at 5-second intervals. Each row represents the logarithm of the average ODBA sum for each period. Please see publication for more details. ##### Variables * ID: individual owl ID * agg_ODBA_log: logarithm of the average ODBA sum for the aggregate period (night, day, dusk, dawn) * night_ODBA_log: logarithm of the average ODBA sum for the night period * day_ODBA_log: logarithm of the average ODBA sum for the day period #### File: owl\_range\_data.csv **Description:** This file contains data on home ranges calculated for the tagged Barred Owls, including home range area, area of forest and impervious surfaces, and the mean selection probability for each of the three home range types. ##### Variables * ID: individual owl ID * agg_area_km2: aggregate home range area (km2) * day_area_km2: day home range area (km2) * night_area_km2: night home range area (km2) * agg_forest_km2: area of forest in the aggregate home range (km2) * agg_impervious_km2: area of impervious surfaces in the aggregate home range (km2) * day_forest_km2: area of forest in the day home range (km2) * day_impervious_km2: area of impervious surfaces in the day home range (km2) * night_forest_km2: area of forest in the night home range (km2) * night_impervious_km2: area of impervious surfaces in the night home range (km2) * agg_mean_selection: mean probability of selection in the aggregate home range * night_mean_selection: mean probability of selection in the night home range * day_mean_selection: mean probability of selection in the day home range #### File: owl\_GPS\_data.csv **Description:** This file contains GPS location data of Barred Owls collected during the study period in Baton Rouge. Each row represents a unique GPS point with associated timestamp, location coordinates, and owl ID. These data are also archived at Movebank ([https://www.movebank.org/cms/webapp?gwt_fragment=page=studies,path=study4341276830](https://www.movebank.org/cms/webapp?gwt_fragment=page=studies,path=study4341276830)). Variable names follow Movebank convention. ##### Variables * individual.local.identifier: individual owl ID * bn: USGS band number * timestamp: YYYY-DD-MM HH:MM:SS GMT * period: local time period (day or night) * location.lat: latitude * location.long: longitude * height.above.msl: height above sea level (m) * gps.hdop: HDOP * gps.satellite.count: number of satellites * duration: duration of GPS signal acquisition (s) * temperature: tag temperature (deg C) ## Code/software Please see publication for software details. Software used include R, ArcGIS Pro, and Google Earth Engine.