Introduction

Understanding the basis of phenotypic diversity is a key challenge in evolutionary ecology, and the study of the persistence of genetic-based color polymorphisms constitutes a key paradigm for its comprehension (Huxley 1955; White and Kemp 2016). Disruptive selection is a potential evolutionary mechanism explaining the persistence of polymorphisms (Mather 1955; Galeotti et al. 2003; Bond and Kamil 2006). This mechanism will act against individuals with intermediate colors, in favor of those with extreme color, which will increase in frequency over time because selection varies across space and time, leading to balance the fitness of the extreme phenotypes globally (Mather 1955; Galeotti et al. 2003; Bond and Kamil 2006).

Color polymorphism is phylogenetically widespread but rare (Hugall and Stuart-Fox 2012). Alternative color morphs are easily identifiable by researchers and could signal alternative strategies to cope with variation in environmental factors (Kassen 2002; Roulin 2004; Brommer et al. 2005; Emaresi et al. 2014; Svensson 2017). Color polymorphism has been extensively studied in birds, a group including 3.5% of polymorphic species (Roulin 2004). For example, color morphs may segregate temporally in relation to weather conditions as in tawny owls (Strix aluco) (Galeotti and Cesaris 1996; Roulin et al. 2003; Karell et al. 2011). Color morphs can spatially segregate based on social environments as well. For instance, white males in the white-throated sparrow (Zonotrichia albicollis) settle in areas with higher conspecific densities compared to tan males (Formica et al. 2004). Also, Eleonora’s falcons (Falco eleonorae) breed in morph-specific clusters where pale individuals group tightly and dark ones are territorial (Gangoso et al. 2015).

Light is among the most variable ecological conditions. It varies among different environments and daily, particularly so between day and night (Endler 1993). Variable luminal conditions might affect crypsis and, hence, determine morph detectability by prey and/or predators, which would act as the selective agents leading to morph-specific segregation in relation to light (Galeotti et al. 2003; Passarotto et al. 2018). In diurnal polymorphic birds, darker plumage colorations are less detectable in closed habitats, during dusk/dawn or in cloudy days, whereas lighter individuals are less detectable in open habitats, during midday or in sunny days. Accordingly, the different morphs adjust their habitat use and activity rhythms to light conditions (Preston 1980; Rohwer 1990; Tate et al. 2016; Tate and Amar 2017). In nocturnal polymorphic species, however, all the studies that have explored the link between light conditions and color-specific segregation have focused on nocturnal light conditions in relation to moonlight. Indeed, moon phases have been shown to determine hunting success in barn owls (Tyto alba) (San José et al. 2019) as a function of plumage coloration, so that the reddest barn owls had lower hunting success and provided less food to their owlets during moonlit nights. Meanwhile, the relationship between food provisioning to offspring and moon phases in scops owls was independent of plumage coloration (Avilés et al. 2022a).

Although daily activity patterns of most bird species are thought to be species-specific, there exist large intraspecific variability in circadian activity patterns under changing environmental conditions (Bunn 1972; Martin 1990; Mukhin et al. 2009). In nocturnal birds, individuals become more active during the day when food availability is low and demands are maximum, as during the breeding period (Endo and Sawara 2000), or when night length is short as in high latitudes (Zárybnická et al. 2012). Therefore, it is possible that color morphs change their circadian activity rhythms differently in relation to diel luminal conditions, switching between nocturnality and diurnality, to achieve a better background matching. Alternatively, but regardless of the crypsis of the morphs, different color morphs could use different habitats that differ in food availability and, hence, the color morphs occupying habitats with less food had to extend their hunting times into the day hours. These possibilities have not been investigated yet.

The scops owl is one such polymorphic nocturnal species. Its plumage coloration varies continuously from grey to brown in relation to the amount of phaeomelanin (Avilés et al. 2020); however, individuals can be categorized into three discrete color morphs (grey, intermediate and brown) based on a three-mode distribution (Parejo et al. 2018). The scops owl is mostly nocturnal but anecdotal reports suggest that it shows some diurnal activity as well (it sings and shows some activity by day, del Hoyo et al. 1999). However, variation in diurnal activity of scops owls has never been investigated in detail, raising the possibility that individuals tend to be more or less active at daytime depending on their coloration. In the south of Spain, insects, and particularly grasshoppers, are the main prey of scops owls during the breeding period (Cramp and Simmons 1988; Cruz-Miralles 2021). Some insects, particularly nocturnal ones, show impressive visual abilities including color discrimination during the night (Warrant 2017). Moreover, there is some experimental evidence showing that grasshoppers, which are mostly diurnal, discriminate among food sources with different coloration in both light and dark environments (Fadzly and Burns 2010) and are able to distinguish among predators with different coloration as well (Baird 2008). Therefore, the insectivorous scops owl is a potential suitable system to study simultaneously segregation of morphs and crypsis in relation to light conditions.

Here, we combined perceptual visual modeling, data from GPS tagged male and female scops owls during the nestling period and nest video recordings, to test the hypothesis that different plumage color phenotypes are adapted to different luminal conditions (day versus night). First, using a visual model approach, we assessed the degree of background matching of scops owl color variants from the perspective of typical prey and predators likely to act as selective agents on plumage color. Based on visual model calculations, we hypothesized that the color morph that will be more conspicuous during the day will perform better during the night. This expectation rests on theoretical work showing that visual color perception is impaired during the night due to a high noise ratio at the photoreceptors (Kelber et al. 2003), from which a lower negative selection against any color variant by prey and predators is deduced. We assessed whether adult activity (i.e., movements outside the core nesting area) differs among birds with different coloration depending on light conditions (as day versus night) to test color-dependent temporal segregation related to luminal conditions. In addition, we tested color-dependent owlets’ provisioning rate (as an indicator of success) as a function of luminal conditions. Patterns of temporal segregation driven by crypsis would predict (1) higher foraging activity during the night for the most diurnally conspicuous morph versus to more diurnally cryptic ones; and (2) higher provisioning rate during the night for the most diurnally conspicuous morph compared to more diurnally cryptic morphs.

Material and methods

Study system

The study was performed in a scops owl population breeding in nest-boxes in the province of Granada, southeast Spain (37° 18′ N, 3° 11′ W). The area is an extensive agricultural landscape with scattered holm oaks (Quercus ilex) where about 500 cork-made nest-boxes (measurements base of 24 × 24 cm, 40 cm height, and opening of 6 cm in diameter) were installed to attract medium-sized hole-nesting birds until 2018.

Scops owls are medium-sized migratory birds (Cramp and Simmons 1988) arriving to the study area from Africa in April (Avilés et al. 2022b). Scops owls begin reproduction throughout May (Parejo et al. 2012), producing one clutch of about 2–6 eggs that are laid every second day each. Incubation starts from the laying of the second egg, takes 24–25 days, and is performed by the female (del Hoyo et al.1999). Nestling rearing takes 21–29 days on average (Cramp and Simmons 1988). Both sexes participate in breeding tasks (Cramp and Simmons 1988), although just after hatching, females are mainly brooding the owlets and males are mainly in charge of hunting (DP et al., unpublished data). As the owlets grow, females increase their hunting activities. As a whole, for all the nestling period, males contribute 74.2% of the feeds brought to the nest (DP et al., unpublished data). Throughout the scops owl distribution range, the chicks in the nest are fed mostly with insects (Cramp and Simmons 1988; del Hoyo et al. 1999).

Each year, from the start of the breeding season (end of April), we visited nest-boxes every 7 days until their occupation by a scops owl pair. After occupation, we only visited nest-boxes once more after the end of laying and before the estimated hatching date to capture and ring the incubating female. After hatching, we visited nests every 3 days to record reproductive parameters and capture the male.

Upon capture, all adults were photographed for color characterization (as in Parejo et al. 2018). We systematically took two standardized photos for each captured individual: one head-on, in which we could observe the head and breast plumage; and other to the back part in which we observed the back and wings. Photographs were taken using a digital camera (Canon EOS 1300D, Lens EF-S 18-55 IS II) mounted on a tripod at a constant distance of 50 cm and with a flash (aperture 4.5, shutter speed 1/200, ISO 800). We gently fixed owls with a harness inside a carton box that ensured stable light conditions and with the head placed next to a color chart (X-Rite ColorChecker® Passport). Photos were standardized using the Adobe® Photoshop Lightroom 6 plugin and used to determine coloration by focusing on redness extension at the head, breast, and wings-back. Each body part was scored by eye among 1 to 3 depending on if they were predominantly grey or brown (Parejo et al. 2018). At the end, scores of the three body parts were summed to get an individual score for every bird ranging from 3 to 9 (color score). Based on these scores, individuals can also be classified as grey (scores<5.5), intermediate (scores between 5.5 and 7, both included), and brown (scores >7) color morphs (Parejo et al. 2018). We used the color morph in all analyses to characterize plumage coloration. However, in the supplementary material (Tables S5, S6), we also provide analyses based on continuous color scores, reflecting the continuous nature of variation in plumage coloration in scops owls.

Each year, throughout scops owl reproduction, we also carried out 2–3 diurnal prey availability surveys in each territory. To do this, we walked at constant speed along longitudinal transects 50 m long and with a 5-m band and counted all the insects we detected (mainly flying insects as grasshoppers, butterflies, bumblebees, and beetles), either inactive or during their flights/jumps. This allowed us to assess whether territories of individuals with different morphs differed in food availability (measured as the mean number of insects counted in surveys of each territory). However, as these surveys were carried out during the day, in 2019, we also carried out nocturnal surveys in territories using the same methodology but with the help of flashlights. Based on surveys on 28 scops owls territories, we found that the mean number of insects counted during the day and at night in territories was significantly correlated (Pearson r = 0.45, P = 0.017, N = 28). Therefore, surveys of prey availability carried out during the day may be used to estimate prey availability in territories in general.

Estimation of crypsis

We used a visual modeling approach to estimate plumage crypsis. Briefly, vision models allow the calculation of perceptual differences between two color patches based on the ambient light (daytime irradiance) spectrum illuminating the bird, and the physiological properties of the receiver (i.e., the viewer’s ocular media transmission spectrum, and the absorption spectrum of the photoreceptors) (Endler 1990; Vorobyev and Osorio 1998). We thus calculated chromatic and achromatic contrasts of grey, intermediate, and brown morphs against the background (including the green foliage and branches) of holm-oak trees (i.e., the natural background where scops owls perch for resting or hunting). This was because the scops owl is a sit-and-wait predator that starts its hunting actions flying away usually from a perch tree (del Hoyo et al. 1999). Hence, insect preys are likely to detect scops owls against the background trees while perching and while approaching them. Using Avicol software v5, we performed model calculations from the perspective of different receivers: (1) a representative trichromat invertebrate receptor (i.e., potential prey), using photoreceptor spectral sensitivity of a bee; (2) a representative trichromat mammal receptor (i.e., potential prey and predator), using photoreceptor spectral sensitivity of a rodent; (3) a representative violet sensitive tetrachromat receptor (i.e., such as corvids and raptors, hence equivalent to an avian predator), using photoreceptor spectral sensitivity data from the peafowl (Pavo cristatus); and (4) a representative ultraviolet sensitive tetrachromat avian receptor (such as passerines, hence equivalent to avian prey), using photoreceptor spectral sensitivity data from the common starling (Sturnus vulgaris). We are aware that reliable sensory-based calculations require knowledge of photoreceptor spectral sensitivity of visual receiver species (Avilés 2020), which is currently lacking for all potential scops owls’ predators and prey species. Therefore, our analyses model calculations should be interpreted with caution, and are useful only in illustrating how large-scale variation on type, number, and distribution of different photoreceptors among major taxa with existing sensitivity data may influence scops owl plumage crypsis.

Spectral reflectance (300–700 nm) of typical grey (N = 16), intermediate (N = 47), and brown (N = 16) scops owls morphs used in the visual models were extracted from a previous work analyzing differences in spectrophotometric measures among discrete morphs in our population (Parejo et al. 2018). Background coloration of holm oak trees was measured by collecting a random sample of leaves and branches of ten holm oak trees from active nests where scops owls breed. In the laboratory, we measured background coloration in the dark with an Ocean Optics spectroradiometer using previously determined specifications for scops owl plumage (Parejo et al. 2018). For measurements, leaves and branches from each nest were disaggregated and laid flat on a black table. Ten readings were taken at random, and one mean background value was calculated based on mean values per nest. Irradiance spectra of the light in daylight in the surroundings of nest-boxes were extracted from Avilés et al. (2008).

For each scops owls’ body part, visual models were performed for each receptor separately, but we averaged the results from the three body parts (head, breast, and wings-back) for each receptor. The visual model establishes a color distance ΔS that describes the color contrasts between each individual color plumage and its background. In addition, it calculates achromatic (brightness) contrast distance ΔQ similar to the chromatic analysis. The units for ΔS and ΔQ are JNDs (just noticeable differences). We assumed that values below 1 JND are impossible to discriminate, and those with values below 3 JND would be difficult to distinguish even under favorable light conditions (Siddiqui et al. 2004; Cassey et al. 2009).

Tracking data

During the springs of 2018 and 2019, we trapped 24 different adult scops owls with different plumage coloration (15 females (2 grey, 8 intermediate and 5 brown) and 9 males (4 grey, 3 intermediate, 2 brown)) (Table S1) and deployed them with pinpoint GPS loggers (Microwave Telemetry Inc., Columbia, MD, USA) mounted on backpack harnesses made of Teflon. Both females and males were captured at the nests, females usually by hand while they were incubating and males with nest-traps during the chick-rearing period. We mounted 2g devices on females and 1.5g ones on males, which were below the restrictive recommended 2.5% of body weight (mean body weight of (1) females, mean ± SD 89.21 ± 15.28 g (N = 212), and (2) males, mean ± SD 70.11 ± 4.93 g (N = 108)), to maintain welfare of tagged individuals (Rodríguez-Ruiz et al. 2016). Loggers were deployed on birds several days (range 2–26 days, mean 11 days) before data recording (see Table S1 for GPS tracking details).

We deployed GPS loggers on different individuals breeding in different nests each year to avoid pseudoreplication. However, we sometimes marked with GPS the two members of a couple in the same year (both adults captured in 9 out of 15 target nests). As members of the same pair share environment (their offspring), we also investigated if the shared environment may have affected parental activities by performing analyses using the subsample of nests where we marked the two parents (9 nests). Results remained qualitatively identical to those reported in the manuscript and we do not find an effect of the nest_ID in any of the analyses, which decreases the possibility of a potential effect of territory/nest on the overall results (see supplementary material, Table S2, S4, S6). We marked adults of the two sexes because, although males undertake most of owlet provisioning early after hatching, females’ hunting responsibilities increase as the owlets’ growth, being responsible of more than 20% of the feedings (see above). In addition, the movements of adults during reproduction could be due to, apart from owlet provisioning, territorial defense or hunting for self-feeding. Hence, it is worth investigating whether there was morph-dependent temporal segregation in each sex.

Loggers were set to record GPS fixes every 45 min during two whole days (beginning at 23:30 h the first day) within the first half of the rearing period (i.e., first 16 days of owlets) (Table S1). We recaptured tagged birds before migrating to discharge data recorded. The number of positions obtained during these two days was optimized to guarantee loggers’ battery life for 1 year (our second related long-term objective was to study the owl migration, see Avilés et al. 2022b). GPS fix data were complemented with provisioning data that have higher temporal resolution to describe the general activity patterns of owls. We avoided studying the movement of owls for more than 2 days because breeding scops owls are more difficult to capture as chicks grow. Two days during the first 16 days of the rearing period is representative enough of the most sensitive period of owlets in the nest when owlets need to be continuously cared. Before any analysis, we initially filtered fixes obtained from each individual by discarding those ones with values of horizontal dilution of precision higher than 10. This led us to discard 51 out of 1474 initial fixes.

Activity rhythms and provisioning rate

We examined color-specific activity rhythms based on data provided by GPS devices. We calculated one variable to define activity patterns: “Foraging activity,” which classifies individuals as either active/foraging (coded as 1) when they are outside the core nesting area, or inactive/not foraging (coded as 0) when they are within the core area. Our analyses on foraging activity are based on the assumption that all individuals out of the nesting core area were actively foraging. This is clear for the nocturnal activity of parents during the nesting phase, when they are expected to be mainly hunting, but not so during daylight time and our GPS tracking data does not rule out the possibility that birds are sleeping when out of the nesting core area. Aiming to validate this assumption, we classified diurnal fixes of individuals outside the core nesting area (until now coded as active) as either inactive or active based on the distance from the immediately previous fix. Consecutive fixes that appeared together or separated by less than 10 m (the double of the average measurement error of GPS fixes) would be indicative of lack of movement of owls. We found that only 7% of the diurnal fixes outside the core nesting area were inactive, which suggests that owls outside the core nesting area are mostly active, likely hunting for themselves.

The nesting area was defined using the utilization distribution around the nest of each tracked owl, with a 95% confidence region. For this, we used the Autocorrelated Kernel Density Estimation (AKDE) by means of the R package ctmm (Calabrese et al. 2016). This method is the most suitable for autocorrelated tracking data as those collected for scops owls (Fleming and Calabrese 2017). Additionally, to allow comparisons with other studies, we performed and provided calculations of the kernel density estimation (KDE), and the minimum convex polygons (MCP) (Table S1), using the adehabitatHR R package. These measurements were all highly correlated (r > 0.69, P < 0.001) and, hence, analyses were based on AKDE (Fig. S1). The core nesting area of each individual was calculated as the 10% AKDE.

We classified fixes in relation to light conditions for day and night (hereafter “Nocturnality” as nocturnal = 1 versus diurnal = 0). We considered that a fix takes place in night light conditions when it was recorded within the period between 30 min after sunset and 30 min before sunrise of the following day based on daily data extracted from the site https://www.timeanddate.com/sun/. Nocturnality, thus, reflects large-scale variations in luminal conditions during a 24-h cycle likely to influence plumage crypsis in scops owls.

We complemented the study of foraging behavior with video-recordings of parental provisioning rate in nest-boxes. Parental provisioning rates extracted from video recordings allowed us to investigate success of each color phenotype in relation to nocturnality (as in Tate et al. 2016). We monitored parental provisioning during 1 day per nest in 17 nests at the beginning of the chick-rearing period (8 days after the hatching of the first egg) using infrared micro-cameras (KPC- S500, black and white CCD camera, Esentia Systems Inc.) installed in the ceiling of nestboxes in 2018. We video-recorded the same nests where adults were tagged with GPS in 2018 but, due to limitations in video camera availability, we recorded parental provisioning (on day 8 of the oldest chick in each nest) and collected GPS data (on average on day 11 of the oldest chick in each nest) in different days. Recordings began around sunset (16 min after the sunset on average) and finished some hours after sunrise (186 min after the sunrise on average), hence including different light conditions. From the recordings, we calculated hourly parental provisioning rates of each parent defining 60-min periods that were fully associated either to day or night conditions (i.e., nocturnality) as a function of sunset and sunrise time each day (see above). When a recording began in the meantime between day and night, we defined a period shorter than 60-min and calculated the hourly provisioning rate relative to that time. To facilitate sex identification in the videos, before recording parental behavior, we captured and marked on the forehead females with a liquid corrector Typp-Ex dot.

Additionally, to assess if the assumption that provisioning rates are an indicator of foraging success (Tate et al. 2016) holds for scops owls, we obtained parental number of feeds and total mass gain of owlets for each nest throughout the recording time. For this purpose, we obtained an only estimation of prey provisioning for the two parents. Moreover, each nest owlets was weighted to the nearest 0.5g with a Pesola spring balance just before and after the recording of parental behavior to measure total mass gain of owlets per nest. We found a strong positive relationship between parental number of feeds and weight gain of owlets (F1,15 = 6.20, P = 0.02, estimate ± SE = 0.15 ± 0.06, N=17 nests), indicating that individuals with higher provisioning rates are more efficient than those with lower provisioning rates.

We were interested in circadian activity of color morphs in relation to large-scale light variation between day and night. We disregarded a possible effect of night luminosity on scops owls’ activity because the nocturnal provisioning pattern of grey and brown morphs is not differently affected by moonlight variation in our population (Avilés et al. 2022a, b).

Statistical analyses

Temporal segregation of male and female scops owls was analyzed separately. We analyzed factors affecting foraging activity by performing GLMMs (generalized linear mixed models, proc GLIMMIX in SAS) with a binomial error structure. In the models, nocturnality (coded as day versus night light conditions), individual plumage color morph (discrete variable with grey, intermediate, and brown categories), and the interactions among these terms were introduced as explanatory fixed variables and the individual ID as a random intercept to take into account that observations from each tracked birds are not independent. In addition, to account for environmental effects, we introduced in models the observation date as a covariate and the year as a fixed factor. Finally, the age of owlets and brood size were included as further covariates to account for potential behavioral differences in parents due to nestling needs.

We run LMMs (linear mixed model, proc MIXED in SAS) with a Gaussian distribution to analyze factors affecting hourly provisioning rates to nests by male and female parents separately. In these two models, nocturnality (coded as day versus night light conditions) during each hour, individual plumage color morph, and the interaction among these terms were introduced as explanatory fixed variables and the nest ID as a random factor to take into account that observations from each parent throughout the recording time are not independent. Furthermore, we included brood size as a covariate in the models to account for potential behavioral differences in parents due to nestling needs.

Neither females (linear model, proc GLM in SAS F2,1.90 = 0.73, P = 0.50, N = 15) nor males (linear model, proc GLM in SAS F2,1.33 = 0.32, P = 0.74, N = 9) with different color morphs varied in brood size.

These analyses were performed separately for each sex aiming to minimize the risk of model over-parameterization given that we sampled a limited number of nests and because we were interested in the study of temporal color-specific segregation of males and females separately in relation to daily light conditions.

Pairwise differences in significant models were checked by comparisons of least-squared means of each treatment with the Tukey-Kramer test.

To analyze the relationship between provisioning rate per nest with total weight gain of owlets, we run a LM (linear model, proc GLM in SAS) with a Gaussian distribution.

Finally, we performed LMMs (linear mixed model, proc MIXED in SAS) with a Gaussian distribution to look for differences in insect availability at the territories in relation to males and females’ plumage color morph. In these two models, individual plumage color morph and the year were introduced as explanatory fixed variables and the nest ID as a random factor to take into account that prey availability samplings for each territory each year are not independent.

Standard model validation graphs (Zuur 2009) revealed that model assumptions of homogeneity of variance and normality of residuals were fulfilled.

Results

Color-specific plumage crypsis

Model calculations revealed that the grey, intermediate, and brown morphs show a low level of background matching as perceived by typical mammal and bird receivers, as both chromatic and achromatic contrasts against the vegetation are far above the limits for visual detection (JNDs > 3) (Fig. 1). However, the three morphs show chromatic contrasts lower than 3 JNDs for insect prey, indicating that they are nearly undetectable for insects, even under favorable light condition. Interestingly, when considering achromatic contrasts, insects might be able to detect grey individuals but not more brownish ones, which showed higher matching with the background (Fig. 1). These patterns remained qualitatively identical when we compared detectability for the different body parts (head, back, and chest) separately.

Fig. 1
figure 1

Chromatic (A) and achromatic (B) contrast in JNDs (just noticeable differences) of the average plumage coloration (± standard error) of grey, intermediate, and brown scops owls against holm-oak tree foliage in average daylight conditions from the perspective of different receivers. The threshold (>3) indicating that the bird are likely discriminable is showed with a dashed line

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Activity rhythm and provisioning rates

Forty-four percent of the activity of scops owls in our population occurs during the day, this value oscillating between 15 and 72% depending on the individuals. This diurnal activity mainly occurs in the final hours of the day, before sunset, and a part also in the early morning (Fig. S2). Accordingly, diurnal chick provisioning activity occurred mainly before sunset (recorded in 75% of monitored nests) and also in the early morning (recorded in 40% of monitored nests and always during the first hour after sunrise).

In males, foraging activity was unrelated to coloration, either alone or in interaction with nocturnality (Tables 1, S3), but was affected by nocturnality, so that males were all more active at night than during the day (Fig. 2a). Interestingly, however, we found a significant effect of the interaction between color morph and light conditions on the provisioning rate of males (Tables 1, S4). Males with different color morph did not differ in their provisioning rates during the day, but during the night, grey males performed more provisioning trips compared to intermediate males, and, to a lesser extent, compared to brown males (Fig. 3a).

Table 1 Model outputs of GLMMs and LMMs analyzing the effect of nocturnality (day versus night light conditions), color morph (as grey, intermediate, or brown), and their interaction on parental (15 females, 9 males) foraging activity and provisioning rate. Sample size and degrees of freedom are given in respective columns. See Tables S3–S4 in the supplementary material for full model outputs. Significant effects (P<0.05) are shown in bold type
Full size table
Fig. 2
figure 2

Mean estimated foraging activity (+ standard error), measured as presence or absence from the core nesting area (10% AKDE, autocorrelated kernel density estimation) of male (a, left) and female (b, right) scops owls during day and night light conditions in relation to their color morph (as grey, intermediate or brown). Values are LS-means obtained from the models including nocturnality, color-morph, and the interaction between these two terms as explanatory variables and the individual ID as a random term. Asterisks indicate statistically significant pairwise differences checked with the Tukey-Kramer test within each light condition

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Fig. 3
figure 3

Mean estimated hourly provisioning rate (+ standard error) of male (a, left) and female (b, right) scops owls during day and night light conditions in relation to their color morph (as grey, intermediate, or brown). Values are LS-means obtained from the models including nocturnality, color-morph, and the interaction between these two terms as explanatory variables and the individual ID as a random term. Asterisks indicate statistically significant pairwise differences checked with the Tukey-Kramer test within each light condition

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In females, foraging activity was determined by the individual color morph in interaction with nocturnality (Tables 1, S3), so that nocturnal foraging activity, but not diurnal activity, decreased from grey to intermediate to brown females (Fig. 2b). On the other hand, females’ provisioning rate (Tables 1, S4) was only related to nocturnality, being higher during the night than during the daytime (Fig. 3b).

We did not find an effect of the date or year of observation, nor of the age of the owlets on any of the response variables, neither in males nor in females (Tables S3, S4). Brood size, however, had a significant positive effect on female provisioning rate so that females with larger broods had higher provisioning rates (Table S4).

Insect availability did not differ among territories of males (F2,26 = 0.14, P = 0.87, N = 30 territories with known male morph) or females (F2,15 = 0.19, P = 0.83, N = 44 territories in with known female morph) with different coloration. However, insect availability differed among territories of males (females Z = 0.95, P = 0.17; males Z = 1.65, P = 0.05) and years (females F1,14 = 11.81, P < 0.01; males F1,26 = 4.71, P = 0.04).

Discussion

Our results show that a considerable amount of activity occurs during daylight conditions, mainly in the first few hours after sunrise and before sunset, in breeding scops owls. In addition, we have shown that scops owls of alternative color morphs differ in circadian activity rhythms during the nestling period. We found that activity at night, but not during the day, was higher for grey and intermediate females than for brown females. Therefore, as diurnal activity did not vary with coloration in scops owls, grey females, by being more active than brown females during the night, seem to be more nocturnal than the other females. Also, we found that grey males had higher provisioning rates than intermediate and brown males during the night. Hence, grey males were more efficient at night than the others. But whether these findings are suggesting that grey scops owl phenotypes are better adapted to forage during night light than more brownish ones remains to be elucidated. Grey owls could benefit for intensively hunting during the night, when they are less conspicuous to prey. However, how light differences between day and night might affect success of more brownish owls remains elusive. One possibility is that selection was acting on a larger spatial or temporal scale than the one considered here, when/where the advantage obtained by brown individuals in daylight could be detected.

There are several possible explanations for the differences in activity and hunting success of scops owl morphs. First, the degree of background matching of differently colored individuals may vary with light conditions (Ducrest et al. 2008), so that foraging and anti-predator success might vary with coloration (e.g., Boerner and Krueger 2009; Tate et al. 2016; San José et al. 2019). Visual model calculations revealed that detectability of the different morphs was far over the discrimination threshold for detection by birds and mammals, suggesting that potential predators and prey in these two clades would be unlikely drivers of variation in color and activity rhythms in scops owls. However, calculations also revealed that insect prey would show many difficulties to discriminate any of the owl morphs among the surrounding vegetation at day light when relying on chromatic contrasts, but that they might potentially distinguish the grey morph when relying on achromatic contrasts. Grasshoppers are known to modify their behavior (for instance being less active or modifying habitat selection) to avoid detection by different predators (Pitt 1999; Civantos et al. 2004). Hence, grey individuals would show a general poorer crypsis at day light and could potentially be perceived by grasshoppers, which are the main prey of scops owls during the breeding period (Cramp and Simmons 1988; del Hoyo et al. 1999). In the study area, we have previously shown that insects constituted 89.9% of biomass delivered to nests during nighttime, being grasshoppers the most abundant prey whichever parental coloration (Avilés et al. 2022a, b). Therefore, it is unlikely that the owls switched to alternative prey during the night because grasshoppers are primarily diurnal.

Patterns of activity and hunting efficiency were in part congruent with a poor background matching of grey phenotypes during day light, which would increase their activity during the night when they are not so disadvantaged. First, grey males showed higher provisioning rates during night light illumination, and second, grey females seem to be more active during the night than intermediate or brown individuals. This could indicate that grey scops owl phenotypes are less successful at hunting during daylight compared to brown or intermediate phenotypes. Background matching at daytime may be particularly relevant in nocturnal species such as scops owls, because around half of their hunting activity during the breeding period occurs during day light. It is worth stressing that visual model predictions are only applicable in daylight conditions and not at night and, hence, that we cannot accurately predict the adaptive value of different morphs in terms of detectability during the night. Future studies might assess this by performing behavioral experiments using prey and predators in captivity in day and night light (e.g., San José et al. 2019). In addition, the possibility that different color morphs occupy different habitats differing in food availability is not very likely as we found that insect availability did not differ among territories with owners of different color morphs.

Finally, plumage coloration may covary with other phenotypic traits so that differently colored individuals behave differently and/or show a different susceptibility to stress (Almasi et al. 2008; Karell et al. 2011; Cruz-Miralles et al. 2020; Parejo and Avilés 2020), inducing differently colored individuals to perform alternative strategies and/or to exploit alternative habitats (reviewed in Roulin 2004). This opens the possibility that differently colored scops owls have different activity rhythms because of different behavioral traits. There is recent evidence supporting the existence of a sex-specific phaeomelanic integrated phenotype in male but not in female scops owls. Brownish males are shier and show less resistance to stress than greyish ones (Cruz-Miralles et al. 2020). Additionally, brownish females were found to be more sensitive to social information on predation risk during the breeding period than more greyish ones (Parejo and Avilés 2020). Therefore, one explanation to higher activity and efficiency of grey individuals in night light conditions could be related to these behavioral differences related to coloration. Indeed, grey individuals get higher provisioning rate than more brown ones during the night, probably due to their higher boldness that leads them to get the more successful luminal niche given their personality. In addition, differently colored scops owls might have different activity rhythms because they specialize on different prey (Karell et al. 2021). This possibility has not been tested for scops owls yet, so that it cannot be discarded that morph-specific prey specialization was behind the different activity patterns of morphs.

It should be noted that the found movement patterns of color morphs were based on a relatively low number of tracked individuals, which may suggest that they arose by chance. However, we deployed the available tags randomly in the population aiming to reduce any biased in collected data. Moreover, results on provisioning behavior confirmed the patterns detected with GPS tags. Hence, it seems likely that the found activity patterns are reflecting the real segregation among individuals during the nesting period.

Other studies have previously found an ecological segregation across morphs in polymorphic species from different taxonomical groups. In many instances, the preference for certain conditions has been linked to foraging or antipredatory benefits due to the enhancement of crypsis in these conditions (Dreiss et al. 2012; Tate et al. 2016; Tate and Amar 2017; Fulgione et al. 2019; San José et al. 2019; Koskenpato et al. 2020). In other cases, segregation has been related to thermoregulation (Hetem et al. 2009; Galván et al. 2018) or physiological constraints (Pérez i de Lanuza and Carretero 2018) induced by melanins, and in others to the covariation among melanin-based coloration and other phenotypic traits that could determine the preference (Formica et al. 2004; Boerner and Krueger 2009; Gangoso et al. 2015). In scops owls, our results would support the idea that poor crypsis under daylight may drive selection for more nocturnal behavior in grey owls. We do not find, however, evidence that brown morphs were better adapted to forage during the day. Hence, persistence of color polymorphism in scops owls cannot be exclusively achieved through day-night morph segregation, suggesting the action of either this mechanism but on a different spatial or temporal scale or another different mechanism.