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Rapid behavioural response of urban birds to COVID-19 lockdown

Citation

Gordo, Oscar; Brotons, Lluís; Herrando, Sergi; Gargallo, Gabriel (2021), Rapid behavioural response of urban birds to COVID-19 lockdown, Dryad, Dataset, https://doi.org/10.5061/dryad.8w9ghx3kc

Abstract

Biodiversity is threatened by the growth of urban areas. However, it is still poorly understood how animals can cope with and adapt to these rapid and dramatic transformations of natural environments. The COVID-19 pandemic provides us with a unique opportunity to unveil the mechanisms involved in this process. Lockdown measures imposed in most countries are causing an unprecedented reduction of human activities giving us an experimental setting to assess the effects of our lifestyle on biodiversity. We studied the birds’ response to the population lockdown by using more than 126,000 bird records collected by a citizen science project in north eastern Spain. We compared the occurrence and detectability of birds during the spring 2020 lockdown with baseline data from previous years in the same urban areas and dates. We found that birds did not increase their probability of occurrence in urban areas during the lockdown, refuting the hypothesis that nature has recovered its space in human emptied urban areas. However, we found an increase in bird detectability, especially during early morning, suggesting a rapid change in the birds’ daily routines in response to quieter and less crowded cities. In conclusion, urban birds showed high behavioural plasticity to rapidly adjust to novel environmental conditions, as those imposed by the COVID-19.

Methods

On March14th 2020, the Spanish Government declared the national emergency due to COVID-19 outbreak and imposed severe social restrictions. These restrictions included mandatory and permanent confinement of the population, borders closure, limitations in public transport, on-line education, working from home whenever possible, and closure of non-essential business and public services. One day later, we launched the project “#JoEmQuedoACasa” (I stay at home) within the citizen science on-line platform ornitho (www.ornitho.cat). This platform aims to collect wildlife records in Catalonia from birdwatchers and naturalists to improve knowledge of biodiversity in this region. The project launched during the lockdown aimed to collect information about wildlife responses to the new environmental conditions resulting from people confinement.

Lockdown surveys were conducted between March 15th and April 13th of 2020. During these four weeks, people were subjected to the most restrictive conditions of mobility and consequently this period showed the most drastic reduction of human activities. Therefore, lockdown checklists were carried out only from homes (e.g., balconies, rooftops or yards). To determine the effect of lockdown on bird behaviour, we also gathered all complete checklists available in ornitho recorded during the same dates between 2015 and 2019. A complete checklist is a checklist with all identified species during any survey. Surveyed sites were classified as urban or non-urban according to the 2017 land use/land cover map of Catalonia. All surveys during the lockdown were in urban environments, except a few observers living in the countryside, which were excluded from the analyses. Therefore, we obtained three groups of checklists: urban lockdown, historical urban, and historical non-urban.

All checklists had associated basic information about the survey: site (geographical coordinates), date, hour, time invested (which was used as a proxy for sampling effort) and observer identity. We excluded checklists lasting >3 h, as they might be discontinuous surveys. We also excluded those checklists started one hour earlier or later than sunrise or sunset, respectively, as they represented nocturnal surveys. To correct for the adjustment of daylight saving time at the end of March, we rescaled recorded hours in civil time to the relevant daily sun events: sunrise, noon and sunset, which were established as -1, 0 and 1, respectively. Sunrise, noon and sunset were calculated for every geographical coordinate and date by the ‘suncalc’ library (version 0.5.0) for R software. Rescaling was calculated as the quotient between the difference of noon and checklist hour and the difference of sunrise or sunset and checklist hour, depending on whether checklist started earlier or later than noon, respectively. This transformation allowed to fix the small bias caused by the longitudinal differences in sunrise and sunset across Catalonia as well as by the progressive day length increase during the study period. Not many observers recorded the number of individuals for each species. For this reason, we opted to work with presence/absence (1/0) data.

We selected data for the 16 most common sedentary urban species in Catalonia. We focused only on sedentary birds to avoid seasonal changes in occurrence and abundance associated with migration. Data from the common and the spotless starlings (Sturnus vulgaris and S. unicolor, respectively) were merged as Sturnus spp. as both were not usually identified at species level in most observations due to their high resemblance. Both species are common, well spread, sympatric and share similar habits and behaviour. Thus, we did not expect important differences in their occurrence or detectability.

Usage Notes

Variables

- spp: species. 6 letter code. Correspondence with scientific names: carcar Carduelis carduelis, chlchl Chloris chloris, colliv Columba livia, colpal Columba palumbus, cyacae Cyanistes caeruleus, larmic Larus michahellis, motalb Motacilla alba, myimon Myiopsitta monachus, parmaj Parus major, pasdom Passer domesticus, phooch Phoenicurus ochruros, picpic Pica pica, serser Serinus serinus, strdec Streptopelia decaocto, stuspp Sturnus spp., turmer Turdus merula.

- pres: 1 = recorded, 0 = not recorded.

- obs_utm: combination of observer identity and 1x1 km UTM cell where the survey was conducted.

- group: survey group. conf = urban lockdown 2020, no_urb_hist= historical non-urban 2015-2019, urb_hist = historical urban 2015-2019.

- time: invested time in the survey (decimal hours).

- hour_std: starting hour of the survey. -1 = sunrise, 0 = noon, 1 = sunset.