DOI: 10.5061/dryad.pk0p2ngpc
title: Breeding in the pandemic: Short-term lockdown restrictions in a European capital city did not alter the life-history traits of two urban adapters

description: Humans are transforming natural habitats into managed urban green areas
 and impervious surfaces at an unprecedented pace. Yet the effects of human
 presence per se on animal life-history traits are rarely tested. This is
 particularly true in cities, where human presence is often indissociable
 from urbanisation itself. The onset of the SARS-CoV-2 outbreak, along with
 the resulting lockdown restrictions, offered a unique, “natural
 experiment” context to investigate wildlife responses to a sudden
 reduction of human activities. We analysed four years of avian breeding
 data collected in a European capital city to test whether lockdown
 measures altered nestbox occupancy and life-history traits in terms of
 egg-laying date, incubation duration, and clutch size in two urban
 adapters: great tits (Parus major) and blue tits (Cyanistes caeruleus).
 Lockdown measures, which modulated human presence, did not influence any
 of the life-history traits investigated. In contrast, tree cover, a
 distinct ecological attribute of the urban space, was positively
 associated with clutch size, a key avian life-history, and reproductive
 trait. This highlights the importance of habitat quality/ inter-year
 variation over human activity on the reproduction of urban wildlife. We
 discuss our results in light of other urban wildlife studies carried out
 during the pandemic, inviting the scientific community to carefully
 interpret all lockdown-associated shifts in biological traits.
description: <strong>Avian
 life-history traits data collection</strong>: From the end of March, we checked nestboxes
 weekly to identify those occupied by great tits and blue tits. A nestbox
 was considered “occupied” when at least one egg was laid on a completed
 nest. Weekly checks allowed to precisely record the date of the first egg
 laid (females usually lay 1 egg per day, and the laying date is recorded
 from the 1st of April, corresponding to the value of 1), incubation
 duration  (given in days and calculated as: hatch date – first egg laid
 date – clutch size – 1,
 though incubation occasionally starts earlier or later than clutch
 completion in tits) and
 clutch size (total number of eggs in the nest). Only the first broods were
 included in the analyses. <strong>Tree-cover
 measurements</strong>: We measured the percentage of tree cover in a
 100m radius around each nestbox following Szulkin et
 al. Briefly, we downloaded
 the raster-layer <em>Tree Cover Density</em> from Copernicus
 Land Monitoring Services (https://land.copernicus.eu/ sitemap;
 Forests/Tree Cover Density); this raster layer is defined as “the vertical
 projection of tree crowns to a horizontal earth’s surface”. The map of
 tree cover was generated in 2015 and contained a 20m-pixel resolution
 layer. After creating a 100m radius buffer around each nestbox, we
 obtained the averaged value of tree cover (in %) at the nestbox level
 using the function <em>Zonal Statistics</em> in
 qGIS. <strong>Statistical
 analyses</strong>: Statistical analyses were performed within the
 computing environment R (v.3.6.2), and jointly for great and blue tits
 (but for occupancy tests, where the two species were analysed separately).
 The parameter “<em>Species</em>” was fitted as a covariate in
 all the other models in order to directly assess species-specific trait
 variation. Because there was a significant association between the
 percentage of <em>Tree cover</em> and <em>Lockdown
 status</em> (LEA vs. LENA, see Table S2), we analysed these two
 parameters in separate models as indicated below. 
 To test associations between
 avian life-history traits and lockdown restrictions, all analyses were run
 using <em>Linear Models</em> or <em>Linear Mixed Effects
 Models</em>: note that the category <em>Site</em> was
 fitted as a random effect in the model only if the inter-group variance (n
 = 7 levels) was higher than zero, to control for pseudo-replication issues
 in occupancy analyses and because of site-related differences in avian
 fitness. All numeric predictors were mean-centred for clarity of
 parameters estimates. In addition, all interactions were tested and
 excluded from the models if not significant. 
 Note that, to investigate the
 effect of lockdown on avian life-history traits, we specifically focused
 on the interaction between <em>Year</em> and
 <em>lockdown status</em> (LEA - Lockdown Entrance Allowed vs.
 LENA - Lockdown Entrance Not Allowed sites), the latter explicitly
 reflecting a lack of outdoors human activity in LENA sites in 2020.
   To
 model nestbox <em>occupancy</em>, we fitted Generalised Linear
 Mixed Effects Models (GLMMs) with binomial distribution
 (“<em>glmer</em>” function in the R-package
 “<em>lme4</em>” v.1.1-21). A nestbox was considered occupied (1) only if
 a great tit or a blue tit (analysed separately) was breeding in the
 nestbox. Nestbox occupancy (0/1) was fitted as binomial-response variable
 in each model, while the interaction between the two categorical variables
 <em>Year</em> (four levels: 2017, 2018, 2019 and 2020) and
 <em>lockdown status</em> were fitted as predictors. For the
 analysis of nestboxes occupancy, we fitted the interaction between the two
 categorical variables <em>Year</em> and
 <em>Lockdown</em> status as explanatory variables.
 To
 model variation in egg <em>Lay date</em> (the egg laying date
 of a nest where the first egg was laid on the 1st of April would be coded
 with the value of 1), we log-transformed the response variable because the
 residuals of the models were not normally distributed. We consequently
 fitted a Linear Model (LM) with a Gaussian distribution
 (“<em>lm</em>” function). The same model structure was used to
 model incubation variation in days, <em>Incubation
 duration</em>, where we added <em>Lay date</em> as
 explanatory variable to control for the fact that earlier clutches in the
 season are characterized by longer incubation periods than those started
 later in the season. are often larger than those initiated
 later. For <em>clutch size</em>, we ran
 Linear Mixed Effect Models with Gaussian distribution
 (“<em>lmer</em>” function in R) with a model structure
 analogous to the one indicated above. Incubation duration -in days- was
 fitted as response variable while the interaction between
 <em>Year</em> and <em>Lockdown status</em>, and
 the continuous-variable <em>Lay date</em> (to control for
 seasonal differences in each breeding event, as incubation duration
 decreases later in the season) were fitted as predictors.
 To
 investigate the role of habitat quality on nestbox occupancy and avian
 life-history traits, we used analogous model structures to those described
 above, but the parameter <em>Lockdown</em> was replaced by the
 continuous variable <em>Tree cover</em> (here used as a proxy
 of optimal natural food resources, e.g. caterpillars, in great tits and
 blue tits).
description: Notes on databases: The excel file
 <strong>DataBTf1720S</strong> contains blue tit data. Missing
 data is indicated as empty cells. The excel file
 <strong>DataGT1720S</strong> contains great tit data. Missing
 data is indicated as empty cells. The excel file
 <strong>Occupdata</strong> contains data used for occupancy
 analyses on great tits and blue tits. Missing data is indicated as
 NA.