DOI: 10.5061/dryad.7pvmcvf4s
title: Analysis of mixtures of birds and insects in weather radar profile data

description: Weather radars are increasingly used to study the spatial-temporal
 dynamics of airborne birds and insects. These two taxa often co-occur and
 separating their contributions is crucial for reliable interpretation of
 their movement patterns. Most studies have restricted analyses to
 locations, seasons, and periods in which one or the other taxa dominates.
 In this study, we describe an analytical method to estimate the proportion
 of birds and insects in cases where both taxa share the same airspace. Our
 approach partitions vertical profiles of biological reflectivity into bird
 and insect components, using assumptions of downwind heading selection by
 insects and information on expected airspeeds for birds and insects. We
 evaluated our method in regions, where existing approaches of studying
 bird migration with weather radars can be particularly challenging due to
 high airborne insect density: the tropics (Colombia) and the southern
 temperate zone (Southeast Australia). We found that bird and insect
 signals routinely reached similar magnitudes in these regions. Retrieved
 patterns of bird and insect occurrence across daily and annual cycles
 reflected expected biological patterns that are indicative of migratory
 and non-migratory movements in both climates and migration systems,
 particularly broad-front migration in birds. Contrary to fixed airspeed
 thresholding, we were able to partition birds along the full range of
 bird-insect proportions, retaining more spatial-temporal complexity that
 was crucial to revealing aerial habitat use of both taxa. Our analytical
 procedure readily extends existing vertical profiling approaches,
 empowering ecologists to explore complex aerial ecosystems across a
 diverse range of climates, as well as potential diurnal movements of birds
 and insects that remain heavily understudied. 
description: We obtained Colombian weather radar data including both single
 polarization moments (radial velocity and reflectivity) and dual
 polarization moments (correlation coefficient, differential reflectivity
 and differential phase) from the country's Institute for
 Hydrological, Meteorological, and Environmental Studies (IDEAM), focusing
 on the stations in San Jose del Guaviare, Guaviare department,
 south-central Colombia  (name: GUA, 2.53°N, longitude: 72.62°W, elevation:
 218 m a.s.l.) and Barrancabermeja, Santander department, north-central
 Colombia (name: BAR, latitude: 6.93°N, longitude: 73.76°W, elevation: 80 m
 a.s.l., Fig. 2A). Both radars are dual-polarization and operate at C-band
 (5.3 cm) with a beamwidth of 1°. The radar operated in dual-PRF mode with
 a low pulse repetition frequency (PRF) of 1266.667 Hz and high PRF of 1900
 Hz, corresponding to a Nyquist velocity of 50.6 m/s. For the Australian
 case study, we obtained the level-1 dataset from the Australian National
 Computational Infrastructure (NCI, Soderholm et al. 2019). We used data
 (radial velocity and reflectivity) from one radar in Captains Flat, New
 South Wales, southeast Australia (name: CapFlat, 35.66°S, longitude:
 149.51°E, elevation: 1382 m a.s.l., Fig. 2B) for the year 2018. This is an
 S-band (10.4 cm wavelength) single-polarization radar with a beamwidth of
 1.9°. Reflectivity data in the Australian dataset was calibrated by
 matching collocated information with the Tropical Rainfall Measuring
 Mission (TRMM) and Global Precipitation Measurement (GPM) satellite passes
 (Louf and Protat 2023) before further processing. The radar operated in
 dual-PRF mode with a low PRF of 500 Hz and a high PRF of 750 Hz,
 corresponding to a Nyquist velocity of 39.1 m/s. The
 Colombian radars are located in hot tropical lowlands, where seasonality
 is defined more by rainfall than temperature. The Barrancabermeja radar
 lies within the Magdalena River Valley but its beams reach the slopes of
 the Andes. San Jose del Guaviare sits at the junction between the Amazon
 and Orinoco River basins. We chose these Colombian radars based on their
 low elevations that maximize the volume of airspace captured by a single
 scan, the continuity of the available time series, and their strategic
 importance for regional migration, ensuring a sufficient volume of
 migration capturable by the radars (Bayly et al. 2018). The CapFlat radar
 is the highest radar in Australia in terms of elevation, with winter
 temperature (average low in July) reaching around 1.1 ℃ and summer
 temperature (average high in January) reaching around 27.9 ℃. Combined
 with its southerly latitude, it is most likely to record seasonal patterns
 in biological activity aloft in the temperate regions of Eastern
 Australia. We extracted vertical profiles of biological
 reflectivity (η, cm<sup>2</sup>⋅km<sup>-3</sup>)
 using the vol2bird algorithm from the <em>bioRad</em> R
 package (Dokter et al. 2019) to a temporal resolution of 6 min and 10 min
 and an altitudinal resolution of 200 m and 100 m in the Australian and
 Colombian datasets, respectively. Precipitation in the Australian dataset
 was removed using MistNet, a convolutional neural network and screened
 manually by visually checking time-altitude plots of reflectivity factor
 and removing time-altitude ranges with meteorological contamination (Lin
 et al. 2019, Dokter et al. 2019). Precipitation in the Colombian dataset
 was removed using the correlation coefficient ρ<sub>HV</sub>
 (pixels with ρ<sub>HV</sub> &gt; 0.95 were removed,
 Stepanian et al. 2016). To reduce the risk of precipitation contamination,
 an additional 5 km margin was removed around identified precipitation
 areas for all radars. The vertical profile includes the reflectivity and
 the associated U (east-west) and V (south-north) components of ground
 speed. We retrieved the U and V components of wind speed from the ERA5
 reanalysis for Australia (Hersbach et al. 2023) and the North American
 Regional Reanalysis for Colombia (Mesinger et al. 2006). We downloaded the
 hourly (Australia) and 3-hourly (Colombia) data at pressure levels from
 1000 to 750 hPa, spatially interpolated to the radar location, and further
 interpolated to the altitudinal and temporal resolution of the vertical
 profiles. Airspeed was determined by subtracting the wind speed vector
 from the ground speed vector. We found airspeeds in our case studies were
 skewed heavily towards lower values (Supplementary Material Fig. S1 and
 S2), even during heavy bird migration, because of the strong background of
 aerial insects. To summarize daily and seasonal
 patterns, we calculated the mean bird proportion , bird reflectivity  and
 insect reflectivity  at each time-altitude bin of the vertical profile
 spanning a data set of four years from the BAR radar in Colombia
 (<em>n = </em>171,986 scans), and one year at the CapFlat
 radar in Australia (<em>n = </em>105,120 scans). We chose the
 BAR radar because time series from this radar was more complete, and the
 quality of velocity data was higher. To illustrate the seasonal patterns,
 we created yearly trends of bird proportions, bird and insect reflectivity
 by fitting Generalized Additive Models (GAM, Wood 2017) using a
 quasi-Poisson distributional family and cyclic cubic regression splines,
 using bird proportions and the densities as response and day of year as
 predictor.
description: # Analysis of mixtures of birds and insects in weather radar profile data
 [https://doi.org/10.5061/dryad.7pvmcvf4s](https://doi.org/10.5061/dryad.7pvmcvf4s) ## Description of the data and file structure This dataset contains the data and code required to replicate bird-insect mixture analysis from Australian and Colombian weather radar data. Data includes daily vertical profiles and their seasonal summaries of one Australian radar and two Colombian radars. Codes include R markdown files that can be used to reproduce Figure3-5 in the associated paper. This README describes only the variables relevant to the analysis. Other variables included in the dataset are standard outputs from the R function `biorad::calculate_vp`. For details on these additional variables, please refer to the R documentation for `calculate_vp`: [biorad documentation](https://www.rdocumentation.org/packages/bioRad/versions/0.5.1/topics/calculate_vp). ### Files and variables #### File: mixture\_code.zip **Description:** code used to generate figure 3-5 in this study. R is required to run the following script; the script was created using R version 4.4.1. Annotations are provided throughout the script through 1) library loading, 2) dataset loading and cleaning, 3) analyses, and 4) figure creation. 1. **daily_pattern_final.Rmd** * **Description**: R code used to summarize the mixture patterns in the example dates in Figure 3. 2\. **seasonal_pattern_final.Rmd** * **Description**: R code used to summarize the seasonal bird-insect patterns in the entire year in Figure 4. 3. **sensitivity_test.Rmd** * **Description**: R code used to conduct sensitivity test analysis in Figure 5. #### File: mixture\_data.zip **Description:** **data used to generate figure 3-5 in this study.** 1\. **australia_complete_df_mixtures.rds** * **Description**: This dataset contains a comprehensive compilation of vertical profiles generated using the vol2bird algorithm from the R package "bioRad" for the Australian site.  * *u_wind*: wind speed component west to east in m/s. * *v_wind*: wind speed component south to north in m/s. * *ff*: Horizontal ground speed in m/s. * *dd*: Ground speed direction in degrees clockwise from north. * *eta*: Animal reflectivity in cm^2/km^3. * *dens*: Animal density in animals/km^3. 2\. **colombia_complete_df_mixtures.rds** * **Description**: This dataset contains a comprehensive compilation of vertical profiles generated using the vol2bird algorithm from the R package "bioRad" for the Colombian sites.  * *u_wind*: wind speed component west to east in m/s. * *v_wind*: wind speed component south to north in m/s. * *ff*: Horizontal ground speed in m/s. * *dd*: Ground speed direction in degrees clockwise from north. * *eta*: Animal reflectivity in cm^2/km^3. * *dens*: Animal density in animals/km^3. 3\. **BAR_seasonal_new.rds** * **Description**: Seasonal dataset for the BAR site, containing modelled bird and insect reflectivity (eta) for each day of a year. used to generate Figure 4 * *jday*: day of the year, 1 to 365 * *mean_bird_prop*: mean bird proportion calculated using method proposed in this paper. * *bird_eta*: Animal reflectivity attributed to birds * *insect_eta*: Animal reflectivity attributed to insects 4\. **Capflat_seasonal_new.rds** * **Description**: Seasonal dataset for the Capflat (Australian) site, containing modelled bird and insect reflectivity (eta) for each day of a year. used to generate Figure 4. * *jday*: day of the year, 1 to 365 * *mean_bird_prop*: mean bird proportion calculated using method proposed in this paper. * *bird_eta*: Animal reflectivity attributed to birds * *insect_eta*: Animal reflectivity attributed to insects 5\. **Capflat_vpts_example.rds** * **Description**: Vertical Profile Time Series (VPTS) dataset for the Capflat site for the examplar date in Figure 3 * u: Ground speed component of the mixture west to east in m/s. NA indicates that ground speed values could not be resolved using the vol2bird algorithm. * v: Ground speed component of the mixture south to north in m/s. NA indicates that ground speed values could not be resolved using the vol2bird algorithm. * *Uwind*: wind speed component west to east in m/s. *Vwind*: wind speed component south to north in m/s. * *ff*: Horizontal ground speed in m/s. * *dd*: Ground speed direction in degrees clockwise from north. * *eta*: Animal reflectivity in cm^2/km^3. * *bird_dens*: Animal density in animals/km^3. * *bird_dens*: Animal density in animals/km^3. * *radar*: name of the radar * *datetime_local*: local date time of the animal movement. * *height_above_radar*: altitudinal band of animal movement above the height of the radar. 6\. **BAR_vpts_example.rds** * **Description**: Vertical Profile Time Series (VPTS) dataset for the BAR site for the examplar date in Figure 3 * u: Ground speed component of the mixture west to east in m/s. NA indicates that ground speed values could not be resolved using the vol2bird algorithm, and excluded from the subsequent analysis. * v: Ground speed component of the mixture south to north in m/s. NA indicates that ground speed values could not be resolved using the vol2bird algorithm, and excluded from the subsequent analysis. * *u_wind*: wind speed component west to east in m/s. * *v_wind*: wind speed component south to north in m/s. * *ff*: Horizontal ground speed in m/s. * *dd*: Ground speed direction in degrees clockwise from north. * *eta*: Animal reflectivity in cm^2/km^3. * *bird_dens*: Animal density in animals/km^3. * *bird_dens*: Animal density in animals/km^3. * *radar*: name of the radar * *datetime_local*: local date time of the animal movement. * *height_above_radar*: altitudinal band of animal movement above the height of the radar. 7\. **GUA_vpts_example.rds** * **Description**: Vertical Profile Time Series (VPTS) dataset for the GUA site for the examplar date in Figure 3 * u: Ground speed component of the mixture west to east in m/s. NA indicates that ground speed values could not be resolved using the vol2bird algorithm, and excluded from the subsequent analysis. * v: Ground speed component of the mixture south to north in m/s. NA indicates that ground speed values could not be resolved using the vol2bird algorithm, and excluded from the subsequent analysis. * *u_wind*: wind speed component west to east in m/s. * *v_wind*: wind speed component south to north in m/s. * *ff*: Horizontal ground speed in m/s. * *dd*: Ground speed direction in degrees clockwise from north. * *eta*: Animal reflectivity in cm^2/km^3. * *bird_dens*: Animal density in animals/km^3. * *bird_dens*: Animal density in animals/km^3. * *radar*: name of the radar * *datetime_local*: local date time of the animal movement. * *height_above_radar*: altitudinal band of animal movement above the height of the radar. #### 3. Key Data Fields * u: Ground speed component west to east in m/s. * v: Ground speed component south to north in m/s. * ff: Horizontal ground speed in m/s. * dd: Ground speed direction in degrees clockwise from north. * eta: Animal reflectivity in cm^2/km^3. * dens: Animal density in animals/km^3. * uwind: wind speed component west to east in m/s. interpolated to the time-altitude bin using ERA5 data. * vwind: wind speed component south to north in m/s. interpolated to the time-altitude bin using ERA5 data.