Spatio-Temporal Changes in Rook’s Assemblage Revealed by Thousands of Citizen Science Photos

doi:10.21203/rs.3.rs-3429378/v1

Citizen science data are increasingly being used to address ecological challenges. In our study, we utilized these data to analyze the urban invasion of rooks (Corvus frugilegus), which posed sanitary concerns and caused disruptions for residents. Although various strategies exist to contain rook invasions, effective mitigation relies on understanding their habitat preferences and daily movements—information hard to gather over extensive areas. To address this, we collected 4,523 geolocated observations from citizens who were monetarily incentivized to photograph the birds. These observations were categorized based on sunrise and sunset timings and further divided into 3-hour intervals. Our analysis revealed that rooks ventured to agricultural areas for foraging after sunrise but predominantly settled within the city post-sunset. During roosting, rooks displayed a preference for environments mimicking forested habitats, likely seeking protection from predators and adverse environmental elements like wind and extreme temperatures.

avian monitoring

rook invasion

species distribution model (SDM)

urban ecosystem

Urban areas can offer suitable habitats for synanthropic bird species, those that evolve and adapt alongside humans. These species often display increased breeding success and habitat density in urban settings (Moller et al., 2014; Jadczyk and Drzeniecka-Osiadacz, 2013). Challenges like low temperatures and scarce food resources during migration can elevate mortality rates among migrating birds (Newton, 2011). As a result, they gravitate towards urban areas, where food and a warmer microclimate are more consistent. In fact, the number of bird species in urban areas is increasing at a faster rate than in rural regions (Moller et al., 2014).

However, this rise in urban bird populations can lead to increased noise pollution and sanitary concerns due to bird excrement and potential disease transmission (Borges et al., 2017). This underscores the need for strategies to deter unwanted bird species from urban centers. The broad movement range of birds, both within and beyond urban confines, complicates their management. Despite the regular presence of wild animals in urban spaces and the acknowledged threats of urbanization to species conservation, there remains a significant gap in the systematic evaluation and management of urban wildlife. This includes a lack of quantitative assessment of environmental variables influencing bird habitats (Magle et al., 2003).

Previously, researchers relied on manual collection of localized or historical data (Whitfield, 2001). However, extrapolating these findings to larger areas is often restricted (Sanz, 2002; Crick, 2004). Ecological research often hinges on our grasp of diverse geographical concepts and spatiotemporal patterns, and large-scale studies can be logistically daunting (Dickinson et al., 2010). Citizen science offers a solution, aiding not only in broad-scale species conservation but also in identifying and monitoring invasive species over vast areas (Gallo and Waitt, 2011). For extensive studies like avian research, citizen science helps bypass spatial constraints, thereby reducing costs (Devitor et al., 2010; McCaffrey, 2005; Brashler, 2009).

Citizen science projects actively engage the public in collecting data for scientific research or policymaking. Empowered by technology, modern citizen science transcends many traditional barriers (Silvertown, 2009). It has proven invaluable in locating rare organisms, monitoring species invasions, and tracking bird populations (Hochachka et al., 1999), presenting a robust approach to address environmental challenges in conservation biology, natural resource manage, and environmental protection.

In this context, we examined the rook (C. frugilegus), an invasive species in South Korea now deemed harmful due to its nocturnal urban invasions and agricultural damage (Article 4 of the Enforcement Rules of the Wildlife Protection and Management Act, 2018). Altered by environmental changes, the migratory patterns of rooks have shifted (Sokolov and Gordienko, 2006). Since 2016, rooks have been observed seasonally in cities like Suwon from November to March, now spanning a vast geographical scope in and around the city.

To chart their movements, we initiated a three-month citizen science campaign from December 2021 to March 2022, gathering over 6,314 location data points on rooks. Using this participant-collected data, we aimed to: (1) chart the spatial and temporal patterns of dense rook congregations, (2) determine the most predictive environmental factors influencing rook distribution during daytime and nighttime, and (3) create detailed models of rook movements in 3-hour intervals. This large-scale urban study of rooks aspires to sidestep the constraints of traditional avian research methods, offering insights into their movements and potential management strategies.

2.1 Study area

We conducted our study in the city of Suwon, Gyeonggi Province, South Korea (37° 17’ 28” N; 127° 0’ 32” E). Suwon comprises four administrative divisions: Paldal-gu, Jangan-gu, Yeongtong-gu, and Gwonseon-gu, which include urban areas and surrounding agricultural and natural lands (Fig. 1). Rooks arrive in Suwon—the third most densely populated city in Gyeonggi Province with a population of 1.18 million people—in November, when the average temperature is 7.9°C and annual precipitation is 104.2 mm (Suwon, 2022).

The areas of each district are Yeongtong: 2.75 ha; Paldal: 1.29 ha; Jangan: 3.33 ha; and Gwonseon: 4.71 ha. In the study area, Gwonseon District exhibits the largest expanse of agricultural land, encompassing 0.97 hectares. Residential zones are most prevalent in Yeongtong and Paldal Districts, with areas of 0.64 hectares and 0.31 hectares, respectively. Jangan District, on the other hand, features the most extensive forested land, covering 1.51 hectares (Table S1).

2.2 Study species

The breeding season for rooks primarily spans May through June, with key breeding areas located in the Amur region, northeastern and southern China, and Mongolia. During the winter months, from November to March, rooks migrate to Korea, Japan, Taiwan, and eastern China. They frequently traverse Korea during the spring and autumn, acting as migratory birds in the country's southern regions.

Rooks favor habitats such as flatlands, open terrain, and forests in proximity to their roosting locations. As previously highlighted, rooks are classified as a harmful species under Article 4 of the Enforcement Rules of the Wildlife Protection and Management Act due to their tendency to cause prolonged crop damage in large groups. These birds typically gather in significant numbers, often in the hundreds or thousands (Madge and Burn, 1994), to roost post-sunset, commencing their foraging activities after sunrise (Hubalek, 2017). Consequently, we defined the preferred habitats of rooks based on the distinction between sunset and sunrise, utilizing data from December 2020 to February 2021 provided by the Meteorological Administration in Suwon.

2.3 Acquisition of citizen science data

We collected data on rook presence using the smartphone app CADA v.1.0.15 (Kim, 2020). Opting for a crowdsourcing approach, which is the most basic among the four levels of citizen science (Shum, 2012)—namely, level 1: crowdsourcing, level 2: distributed intelligence, level 3: participatory science, and level 4: extreme citizen science—we incentivized participation. Citizens, acting as sensors, were provided a financial reward of 0.35 USD for recording Corvus frugilegus sightings with their smartphones. Training sessions were not deemed necessary for this method.

The data acquired included the participant's address, age, geolocation (longitude and latitude), photograph of the rook, time of day, and the date of the observation. Once a participant's smartphone was registered, our database logged the location data along with the photos. The collection period spanned from December 2020 to March 2021. To prevent redundancy, we excluded data entries recorded within 20 minutes and a 200 m radius of a prior entry. Additionally, we filtered out irrelevant data, such as images not featuring rooks, both through a machine learning technique and manual visual inspection.

In total, we amassed 6,314 rook location records across Suwon's four districts through crowdsourcing. After refining the dataset, we used 4,522 valid location points (Table 1). Of these, 2,528 points (55%) were from Gwonseon, 1,023 (22%) from Yeongtong, 963 (22%) from Paldal, and 9 (0%) from Jangan.

Table 1

Citizen science data collected every 3 h
Counts of citizen science data
Hours	24–03	03–06	06–09	09–12	12–15	15–18	18–21	21–24
Count	182	47	626	574	496	685	1162	750

2.4 Acquisition of environmental variables

We referenced previous studies to select environmental variables favored by rooks appearing in urban areas; these were primarily artificial influences and structures such as food supply, mild temperatures, wind shields, and green spaces (Byrkjedal et al., 2012; Ciah et al., 2017; Clewley et al., 2016; Griffin et al., 2000). Among them, we combined 15 types of land use from the biotope map and five other variables were extracted—elevation, Euclidean distance from buildings with three different classes of floor numbers (1st ~ 5th, 6th ~ 20th, 30th and above), Euclidean distance from agricultural land, Euclidean distance from a utility pole, and Euclidean distance from streetlamp—which we selected as rook-favored variables (Table 2). As interest in landcover and land use maps increases as a practical measure that can consider specific natural environments and ecosystems in various urban development plans, the Ministry of the Environment of South Korea has prepared guidelines for creating “biotope” maps and distributed them to each local government.

The biotope map of Suwon city (Suwon City Government, 2019) was produced using the classification of the following: land use, land cover, green cover ratio, vegetation rate, and landscape data. Within the classifications, in this study, we utilized the land use and the height (number of floors) of the buildings provided by Suwon’s biotope map, which has a native resolution of 5 m². The distance from the utility pole was extracted by eliminating the areas of poles constructed underground provided by the Korea Electric Power Corporation. After extraction, the area poles were placed on top of transportation facilities at intervals of 30 m. Altitude was extracted with a resolution of 10x10 m using the digital topographic map provided by the National Territory Information Platform. The Euclidean distance from streetlamps was applied after acquiring the location data of streetlights in Suwon provided in 2021 from the public data portal (www.data.go.kr). We weighed these variables over 12-h periods at 3-h intervals according to our MaxENT results.

Table 2

Predictor variables used in the study.
Variable	Definition
Land use type	Land use types 1: Residential area 2: Commercial and business area 3: Mixed residential and business area 4: Land for public use 5: Industrial area 6: Public manufacturing area 7: Transportation facilities area 8: Inaccessible area 9: River 10: Lakes and wetlands 11: Forest 12: Grassland 13: Agricultural land 14: Artificial area 15: Wasteland
Building (low, medium, high)	Euclidean distance from building floors low: 1–5 floors medium: 6–20 floors high: 21 floors and above
Farmland	Euclidean distance from agricultural land
Streetlamp	Euclidean distance from streetlamp
Utility pole	Euclidean distance from utility pole
Elevation	Elevation

2.5 Processing maximum entropy model

We developed two habitat models to differentiate between daylight and nighttime conditions. Using MaxENT version 3.4.4, we predicted the preferred rook habitats based on their occurrence data. We utilized k-fold cross-validation (k = 10) and designated a random test percentage of 25%. Pearson’s correlation analysis was performed to screen for environmental variables with high multicollinearity; however, none were identified. To adjust for uneven sampling bias, we transformed a bias file—capturing the density of Suwon’s population aged 18 and above within 5 x 5 m pixels—into a normal distribution. This ensured enhanced relative gain contributions and weighted areas with lower population densities appropriately (Stephanie et al., 2013).

The movements of rooks to foraging and roosting zones are influenced by light intensity (Swingland, 1976). Data from the Meteorological Administration in Suwon, spanning December 2020 to February 2021, indicated sunrise and sunset times as 7:35 and 17:41, respectively (Table 3). Considering civil twilight, which persists for 20–30 minutes post-sunset and pre-sunrise, noticeable changes in light intensity commence around 08:00 and 18:00 (Andre and Owens, 2021). After determining the daylight and nighttime weightings of the rook predictor variables, we applied these to the presence records. These records were segmented into eight 3-hour intervals, factoring in sunrise and sunset durations, allowing us to monitor the rook population's spatial distribution throughout the daily cycle.

Table 3

The average sunrise and sunset times in Suwon from December 2020 to February 2021.
Date	Sunrise time			Sunset time
Date	Min	Max	Mean	Min	Max	Mean
Dec/2020	07:27	07:46	07:38	17:14	17:24	17:17
Jan/2021	07:36	07:46	07:43	17:25	17:55	17:39
Feb/2021	07:05	07:35	07:21	17:56	18:25	18:11
Mean	07:35			17:41

3.1 Model performance

MaxENT AUC values of ≥ 0.70 are considered indicative of reliable models (Phillips and Dudik, 2008). The AUC values for rook distribution during the periods after sunrise (08:00–18:00) and after sunset (18:00–08:00) were both equal to or greater than 0.87. These values suggest that the models possess robust explanatory power (Figure S1).

3.2 Species distribution model results

The relative contributions of the top three environmental variables to the MaxENT model for rooks in the time zone after sunrise were Euclidean distance from agricultural land (31.5%), elevation (29.1%), and Euclidean distance from streetlamps (12.8%) (Table 4). According to the Euclidean distance from agricultural land, the probability of rook appearance was above 50% between the range of 0–100 m. According to elevation, the probability of rook appearance was 50–60% or more within a low range between 25 and 30 m (Fig. 3).

The relative contribution rates of the top four environmental variables to the MaxENT model for rooks in the time zone after sunset were Euclidean distance from buildings 6–20 floors tall (20.7%); land use (19.4%); elevation (19%); and Euclidean distance from a utility pole (14.5%) (Table 4). The environmental variable with the highest gain when used in isolation was land use. The environmental variable that, when omitted, most decreased the gain was the Euclidean distance from a utility pole. Among the 15 types of land use, mixed complex areas and the areas of lakes and wetlands contributed 50% or more. The probability of appearance within 0–10 m of a pole was found to be between 55–60% and dropped sharply to less than 50% beyond 20 m (Fig. 4).

Table 4

MaxENT percentage contribution and permutation importance for *Corvus frugilegus* after sunrise and sunset
After sunrise			After sunset
Variable	Percent contribution	Permutation importance	Variable	Percent contribution	Permutation importance
Farmland	31.5	31.1	Building (Medium)	20.7	12.2
Elevation	29.1	42	Land use type	19.4	11.7
Streetlamp	12.8	9.3	Elevation	19	34.3
Building (High)	10.9	5.1	Utility pole	14.5	15.8
Utility pole	5.2	6	Farmland	9.7	7.5
Building (Medium)	4.5	2.2	Building (High)	7.9	4.5
Land use type	3.7	3.9	Streetlamp	5.9	11.5
Building (low)	2.3	0.4	Building (low)	2.9	2.6

3.3 Differentiation in the assemblage locations by ‘real-time’ tracking using citizen science

Daily citizen science data from November to February indicated that rooks started to move to their foraging areas in the Gwonseon district after 06:00. In this region in western Suwon, agricultural land comprises 20.7% (Fig. 5c). After 09:00 presence probabilities above 0.8 were concentrated mainly in these agricultural lands where the rooks settled to forage until 18:00 (Fig. 5d–5f). Movement to the urban areas could be perceived after 18:00 in the Paldal and Yeongtong districts, located in eastern Suwon, where mixed residential and business land use comprises over 20% (Fig. 5g–5b).

Citizen science-derived data often correlates with ecological challenges manifesting within urban settings, directly affecting residents and thereby spurring their participation (Gallo and Waitt, 2011). Through our project's incorporation of citizen science, we accumulated 4,523 rook occurrences. Such data collection presents a unique opportunity for residents to engage with ecological issues firsthand. Our findings elucidated rook-favored urban environmental variables mirroring their forested preferences, which offer protection from external threats. Notably, we mapped rook spatial distribution over a 24-hour cycle with citizen science data, a feat traditionally achieved using invasive techniques such as GPS devices (Byrkjedal et al., 2012; Ciach et al., 2017; Griffin et al., 2000).

Post-sunrise, rook assemblages predominantly occurred within 50–100 m of agricultural land, reflecting their known proclivity for daytime foraging near such terrains, influenced by resource size and abundance (Griffin et al., 2000). They also exhibited a preference for areas proximate to streetlamps (at distances of 50 ~ 100 m). Artificial lighting impacts their foraging area choices, making illuminated regions more attractive due to enhanced visibility and extended foraging durations (Clewley, 2016). Urban regions, particularly those combining commercial and residential zones, present warmer climates favored by rooks. For instance, Paldal in southeast Suwon, characterized by its residential dominance, exhibited high rook appearance likelihood (Fig. 2) (Dwyer et al., 2014). While proximity to utility poles emerged as a significant variable post-sunrise, more so than streetlamps, rooks and other urban-venturing species like owls gravitate towards these structures, especially in areas featuring extensive open spaces and limited forestry (Dwyer et al., 2014). Moreover, rooks favored areas adjacent to buildings ranging from 6 to 20 stories, likely due to the wind protection they afford (Gorenzel and Salmon, 1995). Recognizably, rooks typically establish their rookeries near foraging territories, with the most significant foraging zones detected within a 0.5–1.5 km radius from their rookeries.

Our 24-hour habitat suitability mapping uncovered nuanced shifts in rook locations. They predominantly congregated around the agricultural expanse west of Suwon as the residual civil twilight glow dimmed (Fig. 5). Their movements to and from foraging and roosting zones were predominantly modulated by light intensity, particularly during winter months (Andre and Owens, 2021). Diminished afternoon light prompted rooks to gravitate towards primary congregation areas, while decreased morning light intensity expedited their departure from feeding territories, compelling them to adjust their positions post-sunrise.

Our study delineates the daily congregation patterns of rooks derived from non-invasively procured citizen science data. This knowledge can underpin strategies to either curtail or harmoniously coexist with urban-invading corvids. Presently, Suwon is trialing the laser pointer technique to deter rooks from city roosting—an approach similarly employed in Sunnyvale, California to manage rook invasions (Kim, 2019; Picon, 2022). This method relies on laser beams mimicking the eye color (green) of rook predators to scatter them. In Rochester, Minnesota, USA, a composite technique featuring laser pointers, recorded crow calls, and starter guns has been deployed to discourage American crows (Corvus brachyrhynchos) from downtown roosting (Richert, 2019). Other locales, including Sacramento and Hanford in California, have introduced trained Harris’s hawks (Parabuteo unicinctus) guided by lasers to disband crow congregations. As we expand our scope beyond Suwon City, leveraging citizen science tools akin to eBird will prove invaluable in discerning rook habitat predilections. By judiciously analyzing time-segmented citizen science datasets, we aspire to evaluate both immediate and enduring outcomes of laser interventions and to monitor rook adaptive responses to varied laser intervention frequencies.

Ethical Approval

Not applicable.

Funding

“This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Urban Ecological Health Promotion Technology Development Project, funded by Korea Ministry of Environment (MOE) (2020002770002)”

Acknowledgements

“This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Urban Ecological Health Promotion Technology Development Project, funded by Korea Ministry of Environment (MOE) (2020002770002)”

“This work was financially supported by Korea Ministry of Land, Infrastructure and Transport(MOLIT) as 「Innovative Talent Education Program for Smart City」”

Availability of data and materials

The authors confirm that the data supporting the findings of this study are available within the article and its Supplementary material. Raw data that support the findings of this study are available from the corresponding author, upon reasonable request.

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No competing interests reported.

SupplementaryMaterial.pdf

Spatio-Temporal Changes in Rook’s Assemblage Revealed by Thousands of Citizen Science Photos

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Abstract

Figures

Introduction

Materials and methods

Results

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1