Noise Pollution in the Center of the Iberian Peninsula: Diversity and Abundance on Urban Birds Breeding

Noise Pollution in the Center of the Iberian Peninsula: Diversity and Abundance on Urban Birds Breeding | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Noise Pollution in the Center of the Iberian Peninsula: Diversity and Abundance on Urban Birds Breeding Paula Almarza-Batuecas, Moisés Pescador This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5360841/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In an increasingly urbanized world, biodiversity, and more specifically birdlife located in urbanized ecosystems, faces several threats. Among these, noise pollution has proven to be one of the most significant, as it affects the effectiveness and efficiency of acoustic communication. We studied the relationship between noise and the diversity and abundance of birds breeding in urban areas in the central region of the Iberian Peninsula (Spain). We analyzed how species diversity and density varied across three levels of noise pollution (high, medium, and low). Species diversity decreased in areas with high noise pollution as compared to the sites with medium and low levels of noise. We analyzed the density of the most frequent species found within each category. We identified eight additional noise-tolerant species, whose density had significantly increased in environments with high levels of noise (e.g. Blackbird, Eurasian Tree Sparrow, and the Coal Tit). The ten most sensitive species, such as the Common Linnet, House Sparrow, and the European Greenfinch, had significantly decreased densities when the level of noise increased. Identifying the sensitivity (the effect) of urban bird species to acoustic pollution is vital for effective conservation management measures and for the sustainable planning and management of cities. Acoustic Pollution Biodiversity Conservation Noise Tolerance Urbanization Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Urbanized areas are becoming more abundant and expansive, often replacing other habitat types. Urban development forecasts have predicted that urban areas will continue to grow, and human populations will become increasingly concentrated in larger and larger cities (United Nations, Department of Economic and Social Affairs, 2018 ). This situation raises conservation concerns about urban change and its effect on wildlife (Lepczyk et al., 2017 ; Murgui & Hedblom, 2017 ), as urbanization brings many changes that can threaten wildlife, particularly birds (Díaz et al., 2022 ; Ditchkoff et al., 2006 ; Soifer et al., 2021 ). Urbanization brings with it many negative effects such as habitat fragmentation, increased stress, and contact with various sources of pollution (chemical, light, and acoustic pollution, even electromagnetic (Balmori & Hallberg, 2007 ; Chace & Walsh, 2006 ; Marzluff, 2016 ). However, urbanization can also be beneficial, leading to situations of a milder microclimate (heat island effect), increased food availability (which may be low quality), and a general decrease in predators (although the presence of cats remains a major threat) (Bernat-Ponce et al., 2022 ; Díaz et al., 2022 ). Despite the multiple negative effects of urbanization, some bird species are successful in cities, with large and successful populations in urban habitats (Jokimäki et al., 2016 ; Kark et al., 2007 ; Murgui & Hedblom, 2017 ; Slabbekoorn & Ripmeester, 2008 ). Nevertheless, it is also known that birds are particularly sensitive to noise pollution (Nemeth & Brumm, 2010 ; Slabbekoorn & Ripmeester, 2008 ). Anthropogenic noise pollution (also called noise in this paper) is closely linked to human activities, and its main source is road traffic (streets, avenues, roads, highways, etc.) and noise produced from other non-vehicle motors (Parris & Schneider, 2008 ; Slabbekoorn, 2004 , 2013 ; Warren et al., 2006 ). Generally, anthropogenic acoustic pollution is characterized by low-frequency noise, starting from 2 KHz and downwards (Slabbekoorn & Ripmeester, 2008 ; Warren et al., 2006 ). Birds use acoustic communication as one of the main communication routes to communicate with conspecifics and individuals of other species (Nemeth & Brumm, 2010 ; Slabbekoorn, 2004 ). This acoustic communication is extremely important to different activities of birds such as territory defense, mate attraction, parental care, and communication in cases of danger, among others (Patricelli & Blickley, 2006 ; Slabbekoorn, 2013 ). Noise can prevent proper and efficient acoustic communication between individuals by masking their vocalizations (Nemeth & Brumm, 2010 ; Oden et al., 2020 ; Slabbekoorn, 2004 ). This increase in noise leads to different negative effects for birds such as increased stress and predation, increased time spent on territory defense, mate attraction, feeding, and vigilance(Brumm, 2004 ; Eens et al., 2012 ; Gil et al., 2014 ; Sweet et al., 2022 ). Noise is an important stress factor for birds and can lead to a decline in their populations as their normal life cycles are hampered (Slabbekoorn, 2013 ; Warren et al., 2006 ). Noise can even produce a barrier effect, preventing some birds or bird species from accessing places with high noise pollution (Ghadiri Khanaposhtani et al., 2019 ; Patricelli & Blickley, 2006 ; Wiacek et al., 2015 ). Urban birdlife has declined in Spain in recent decades(SEO/BirdLife, 2013 , 2019 ), and a similar trend has been observed in other cities around the world(Balmori & Hallberg, 2007 ). Acoustic pollution (noise) can mask bird vocalizations, but it does not affect all bird species equally. It depends on the individual characteristics of each species (e.g. body size) and their song (vocal range, frequencies, etc.)(Francis et al., 2011 ; Mendes et al., 2010 ; Slabbekoorn, 2013 ; Warren et al., 2006 ). Alternatively, several studies have found that some species can adapt to noise; for example, with changes in their songs and vocalizations or their behaviour (Fuller et al., 2007 ; Mockford & Marshall, 2009 ; Nemeth & Brumm, 2010 ; Oden et al., 2020 ). The main objective of the present study is to assess the effects of noise on the diversity and density of bird species living and breeding in urban areas in the center of the Iberian Peninsula (Spain). We compare the diversity and density of birds between sites with three different levels of noise (high, medium, and low). We test whether noise has a negative effect on the urban bird population in our study areas. Moreover, we aim to identify which species populations are negatively or positively affected by noise and to study the effect of anthropogenic acoustic pollution on urban bird assemblages. Materials and Methods Study area Sampling was carried out in 9 cities and towns in the center of the Iberian Peninsula (Spain) (Fig. 1 ), in an area of approximately 1400 Km² and with a Mediterranean climate. The cities and towns were different in population and geographical size. The selected cities and towns were Madrid (324.7 Km², 3 332 035 inhabitants), Parla (9.1 Km², 133 004 inhabitants), Aranjuez (7.5 Km², 60 668 inhabitants), Pinto (10.7 Km², 55 208 inhabitants), Carranque (2.3 Km², 5 274 inhabitants), Casarrubuelos (0.79 Km², 4 062 inhabitants), Lominchar (1.1 Km², 2 639 inhabitants), Palomeque (0.26 Km², 1 143 inhabitants), and Batres (0.25 Km², 1 872 inhabitants). The study area included a wide variety of urban sites: small and large parks, ranging from squares to streets with minimal vegetation (to ensure a minimum number of bird recordings). We categorized the study area according to anthropogenic acoustic pollution (noise) (Barrigón Morillas et al., 2005 ; Mendes et al., 2011 ). For prior categorization, we used noise maps and decibel (dB) measurements during previous visits to each location. In addition, we made noise pollution measurements at each bird sampling visit. We measured noise decibels for 1 minute using an Extech Instruments sonometer model 407736 (with an A-weighted filter), one meter above the ground. Noise measurements were taken at each point and each visit, covering different times throughout the morning. These categories were validated by statistical analysis. The categories with their characteristics were: •High level of acoustic pollution, where noise pollution levels were high and continuous throughout the day. Mean 56.1 dB (range: 49–66 dB). •Medium level of acoustic pollution, where noise pollution levels were medium to low throughout the day, with peaks of high noise pollution corresponding to the start and end of work, schools, rush hours, etc. Mean 49.6 dB (range: 45–59 dB). •Low level of acoustic pollution, where noise pollution remained low throughout the day. Mean 43.3 dB (range: 39–48 dB). Bird sampling The sampling unit used was a point-count station with a 25 m fixed radius. This method was selected because it provides a standardized protocol, especially at sites with high environmental heterogeneity (Bibby et al., 2000 ). In this study, only a 25-m radius was used to avoid the problem of decreasing species detectability at farther away distances. We established 72 point-counts, divided into three categories of acoustic pollution: high, medium, and low, with 24 count points per category. The points counts were established according to town size, ranging from 22 (the biggest city, Madrid) to 3 (the smallest, Batres, Lominchar, and Palomeque). The 72 point-count stations were at least 250 m apart to avoid overlapping and duplicated point counts. The locations of the point-count stations were randomly selected, and the three groups of points had similar and comparable characteristics. The bird species, either heard or seen, and their abundance was recorded for 10 minutes. This sampling time frame was chosen because in previous studies this duration had proven to be optimal. Sampling was conducted early in the morning, before sunrise, until noon (or 10 am during the hottest months), in optimal weather conditions, with no or low wind and no rain (Bibby et al., 2000 ). Sampling was conducted during the breeding season, between March 2019 and August 2021. Sixteen sampling visits were made to each point-count station, and between 1 and 2 samplings were performed per month (a total of 8 visits in 2019, 6 in 2021, and only two visits in 2020 because of covid-19 shutdown). Statistical analysis We estimated the species diversity and density of each species for each noise level. To estimate species diversity, we calculated species richness using species accumulation curves. Species accumulation curves for each plot were constructed to measure the completeness of the sampling and to compare the species richness (Colwell & Coddington, 1994 ; Soberón & Llorente, 1993 ). These curves enabled us to establish a compromise to be made among the different plot surveys, such since as if they had been carried out exclusively based on the values of the number of species observed, without reference to the effort invested, would have been obtained false results (Gotelli & Colwell, 2001 ). The number of point counts was taken as a measure of the sampling effort and randomized 100 times to construct smoothed accumulation species curves (Gotelli & Colwell, 2001 ). We constructed and used 95% confidence intervals of the curves to compare species diversity among the three smoothed accumulation species curves (Gotelli & Colwell, 2010 ; Quesada & MacGregor-Fors, 2010 ). We used EstimateS v 9.1.0 software to construct the smoothed species accumulation curves (Colwell & Coddington, 1994 ). Moreover, we also calculated the density of the 33 most frequent species. We chose these most frequent species to ensure a sufficient data set for the analysis. To calculate the density (individuals per hectare) per species and point, we used the following equation proposed by Shiu & Lee (Shiu & Lee, 2003 ): $$\:D=\frac{n}{\pi\:{r}^{2}}\:10000$$ 1 , where D is the density, n is the number of individuals of a species and r is the sampling unit radius (in meters). We analyzed the density of each species for the three categories of acoustic pollution using a non-parametric Kruskal-Wallis test (Sokal & Rohlf, 1994). For species that showed significant differences, a pairwise Dunn test with Bonferroni correction was performed to detect which pairs of noise levels were significantly different. All statistical analyses were performed using IBM SPSS Statistics v 28.0.1.1 software. Results Species diversity A total of 29,934 individuals from 81 species, belongs to 37 families, were recorded (Tables 1 and A1 ). The comparison of species diversity for the three levels of noise produced smoothed species accumulation curves with a 95% confidence interval, as shown in Fig. 2 . Sites with a high noise level had fewer species and less diversity (49 bird species) than the sites with a medium or low level of noise (with 71 and 67 bird species respectively). In our analysis, the 95% confidence interval of the high noise level curve did not overlap with the confidence intervals of the other two curves. Of the 81 species, 17 species were not registered in the three noise categories, were not associated with any noise category, such as the Hawfinch ( Coccothraustes coccothraustes ) which was not registered in a high-noise sites. On the other hand, 19 species only were recorded in one of the categories. For example, the European Crested Tit ( Lophophanes cristatus ) was only recorded in sites with a low level of noise. The analysis of the trends in population size over the last decade showed that 21 species (Tables 1 and A1 ) were in decline in all Spanish territories such as the House Sparrow ( Passer domesticus ), Eurasian Magpie ( Pica pica ), European Serin ( Serinus serinus ), Common Linnet ( Linaria cannabina ), Eurasian Tree Sparrow ( Passer montanus ), White Wagtail ( Motacilla alba ), and the Iberian Green Woodpecker ( Picus sharpei ) (SEO/BirdLife, 2022 ). Although these species are experiencing a decrease in population size, they can be found in urban habitats. Of the 81 species, 15 species are listed in Spanish legislation as endangered or near endangered (Tables 1 and A1 ) such as the Barn Swallow ( Hirundo rustica ), which is classified as vulnerable (VU), and the Western Jackdaw ( Corvus monedula ), classified as endangered (EN) (SEO/BirdLife, 2021 ). We also found 2 rare species: Hawfinch and Pied Flycatcher ( Ficedula hypoleuca ) (SEO/BirdLife, 2013 ). Three allochthonous species were recorded, stand out Monk Parakeet ( Myiopsitta monachus ), which is one of the most frequent and abundant species found. Another species observed was the Common and Pallid Swift ( Apus apus and A. pallidus ). However, they were not included in the density analysis because of their biology, as they spend most of their lives away from the ground and noise. Table 1 The 33 most frequent and abundant bird species whose densities were analyzed. The table lists the common name of each species recorded, as well as its scientific name, conservation status (c. status), and the number of times it was recorded in each of the three noise categories (high, medium, and low) included in this study. The asterisk marks those species whose populations are in decline in Spain and ALLOC is the allochthonous species in Spain. English name Scientific name C. status High level Medium level Low level Total Common Wood Pigeon Columba palumbus LC 24 24 24 72 Common Blackbird Turdus merula LC 24 24 24 72 House Sparrow Passer domesticus LC* 24 24 24 72 Spotless Starling Sturnus unicolor LC 18 24 24 66 European Greenfinch Chloris chloris LC 21 23 22 66 Eurasian Magpie Pica pica LC* 23 23 18 64 European Goldfinch Carduelis carduelis LC 20 22 21 63 European Serin Serinus serinus LC* 19 20 22 61 Barn Swallow Hirundo rustica VU* 16 22 20 58 Eurasian Collared Dove Streptopelia decaocto LC 15 20 20 55 Rock Dove Columba livia LC* 21 19 13 53 Common House Martin Delichon urbicum LC 12 21 19 52 Common Linnet Linaria cannabina LC* 12 19 19 50 Eurasian Blue Tit Cyanistes caerueleus LC 19 16 8 43 Great Tit Parus major LC 16 14 10 40 Coal Tit Periparus ater LC 18 15 5 38 White Wagtail Motacilla alba LC* 12 15 7 34 Monk Parakeet Myiopsitta monachus ALLOC 19 11 3 33 European Robin Erithacus rubecula LC 12 12 8 32 Black Redstart Phoenicurus ochruros LC 6 11 12 29 Common Chaffinch Fringilla coelebs LC 8 12 8 28 Eurasian Blackcap Sylvia atricapilla LC 9 8 9 26 Short-toed Treecreeper Certhia brachydactyla LC 13 6 6 25 Stock Dove Columba oenas LC 9 6 7 22 Sardinian Warbler Sylvia melanocephala LC 7 8 7 22 Eurasian Tree Sparrow Passer montanus NT* 10 5 7 22 Iberian Green Woodpecker Picus sharpei LC* 9 5 2 16 European Pied Flycatcher Ficedula hypoleuca LC 4 7 5 16 Long-tailed Tit Aegithalos caudatus LC 3 4 4 11 Spotted Flycatcher Muscicapa striata LC 2 2 6 10 Western Jackdaw Corvus monedula EN* 2 3 3 8 Crested Lark Galerida cristata LC* 0 2 5 7 Mistle Thrush Turdus viscivorus LC 0 2 5 7 Response to noise In the density analysis, we observed that birds responded differently to the level of noise. Out of the 33 species studied, only 18 species showed a clear response. For the other 15 species, significant results were not obtained from the statistical analysis or the results did not clearly explain the response of these species to noise. Moreover, the species that did show a clear result could be divided into two groups or responses. One group or response consisted of species whose density responded negatively to noise. The density of these species was higher when the noise level was low than when it was high (Fig. 3 ). This group had statistically significant values and consisted of 10 bird species (Table 2 ): European Greenfinch ( Chloris chloris ), Common Chaffinch ( Fringilla coelebs ), Barn Swallow ( Hirundo rustica ), Common Linnet ( Linaria cannabina ), Spotted Flycatcher ( Muscicapa striata ), House Sparrow ( Passer domesticus ), Black Redstart ( Phoenicurus ochruros ), European Serin ( Serinus serinus ), Eurasian Collared Dove ( Streptopelia decaocto ), and the Spotless Starling ( Sturnus unicolor ). Table 2 shows the results of the pairwise analysis of noise levels for each species. Table 2 Results of the Kruskal-Wallis test for the species with the highest density at sites with a low level of noise. The table shows the results of the analysis among the three noise levels and the pairwise analysis. The species with a p-value of > 0.05 are indicated as ns. Species H p High-Low High-Medium Medium-Low H p H p H p Chloris chloris 41.242 < 0.001 -116.04 < 0.001 -121.268 < 0.001 5.228 ns Fringilla coelebs 12.965 0.002 -32.284 < 0.001 -6.079 ns -26.204 0.006 Hirundo rustica 103.128 < 0.001 -186.353 < 0.001 -32.721 ns -153.632 < 0.001 Linaria cannabina 48.4 < 0.001 -101.727 < 0.001 -40.32 0.006 -61.406 < 0.001 Muscicapa striata 9.351 0.009 -15.057 0.008 0.034 ns -15.091 0.008 Passer domesticus 17.486 < 0.001 -96.139 < 0.001 -23.732 ns -72.408 0.003 Phoenicurus ochruros 15.315 < 0.001 -37.286 < 0.001 -18.221 ns -19.065 0.045 Serinus serinus 9.603 0.008 -54.047 0.004 -8.738 ns -45.039 0.016 Streptopelia decaocto 34.98 < 0.001 -109.415 < 0.001 -77.382 < 0.001 -32.034 ns Sturnus unicolor 114.837 < 0.001 -230.449 < 0.001 -122.383 < 0.001 -108.066 < 0.001 The other group or response consisted of species whose density responded positively to noise. The density of these species was greater when the noise level was high than when it was low (Fig. 4 ). This group had statistically significant values and consisted of 8 bird species (Table 3 ): Rock Dove ( Columna livia ), Common Wood Pigeon ( Columba palumbus ), Monk Parakeet ( Myiopsitta monachus ), Eurasian Tree Sparrow ( Passer montanus ), Coal Tit ( Periparus ater ), Eurasian Magpie ( Pica pica ), Iberian Green Woodpecker ( Picus sharpei ), and the Common blackbird ( Turdus merula ). Table 3 shows the results of the pairwise analysis of noise levels for each species. Table 3 Results of the Kruskal-Wallis test for the species with the highest density at sites with a high level of noise. The table shows the results of the analysis among the three noise levels and the pairwise analysis. The species with a p-value of > 0.05 are indicated as ns. Species H p High-Low High-Medium Medium-Low H p H p H p Columba livia 104.682 < 0.001 201.109 < 0.001 132.379 < 0.001 68.73 < 0.001 Columba palumbus 7.883 0.019 63.723 0.005 38.488 ns 25.234 ns Myiopsitta monachus 155.597 < 0.001 207.849 < 0.001 110.104 < 0.001 97.745 < 0.001 Passer montanus 12.597 0,002 27.934 0.008 35.703 < 0.001 -7.77 ns Periparus ater 36.389 < 0.001 79.773 < 0.001 23.836 ns 55.938 < 0.001 Pica pica 65.316 < 0.001 154.809 < 0.001 37.082 ns 117.727 < 0.001 Picus sharpei 17.168 < 0.001 34.521 < 0.001 13.604 ns 20.917 0.013 Turdus merula 13.5 0.001 85.383 < 0.001 36.145 ns 49.238 0.035 Discussion A total of 81 breeding species belonging to 37 families were recorded. This diversity was to be expected based on similar studies on urban avifauna (Carral-Murrieta et al., 2020 ; Caula et al., 2010 ; Patón et al., 2012 ). Even though the urban habitat is one of the most altered with several sources of stress for birds (Díaz et al., 2022 ) we found bird species classified as being endangered, rare, or declining in population (SEO/BirdLife, 2013 , 2021 , 2022 ). These results were expected and are in line with other similar studies (Ives et al., 2016 ; Patón et al., 2012 ; Sorace & Gustin, 2017 ) and highlight the role of the urban ecosystem in maintaining bird diversity and conservation (Jokimäki et al., 2018 ; Villaseñor et al., 2020 ). The species that stand out because of their density and frequency are similar (Table 1 , Figs. 3 and 4 ) and are typically urban species (synanthropic species). Other similar studies highlight these species for their high frequency and abundance (Fernández-Juricic, 2001 ; Kontsiotis et al., 2019 ; Morelli et al., 2021 ; Sorace & Gustin, 2017 ). We see that the frequency and density of species decrease rapidly, a finding that is coherent with the effect of urbanization on the homogenization of biodiversity, with synanthropic species being the most abundant and frequent (McKinney, 2006 ; Slabbekoorn, 2013 ). One of the most abundant species found in this study was the invasive exotic species Monk Parakeet ( Myiopsitta monachus ). This and the other invasive exotic species found, despite not being in their natural habitat, have succeeded mainly due to changes caused by urbanization (Blair, 2001 ; Díaz et al., 2022 ; McKinney, 2006 ), which has caused problems for other bird species and even humans (Molina et al., 2016 ). We found lower bird diversity at sites with high noise levels. Noise seems to negatively affect bird diversity, rarefying some species, and even making them absent in places with a high level of noise (Francis et al., 2011 ; Marzluff, 2016 ; Wiacek et al., 2015 ). This rarefying of species with increasing noise was also observed by Herrera-Montes and Aide (Herrera-Montes & Aide, 2011 ), who found that some species disappeared in areas close to the noise source (road), and reappeared when the noise decreased. In this study, we obtained a similar species diversity at low level and medium noise levels. High species diversity has been related to medium and low disturbance levels in several studies (Kontsiotis et al., 2019 ; McKinney, 2006 ; Peris & Pescador, 2004 ; Wiacek et al., 2015 ). In this case, noise (anthropogenic acoustic pollution) is detrimental to birds because it masks their vocalizations, and this noise can be a barrier to their dispersion (Brumm & Slabbekoorn, 2005 ; Nemeth & Brumm, 2010 ; Slabbekoorn, 2013 ; Slabbekoorn & Ripmeester, 2008 ). However, this relationship between species richness and noise is not always clear, for example Ghadiri Khanaposhtani et al. ( 2019 ) show that avian richness could be decrease in some cases or increase in another ones in relation with noise increments. The response of the species to noise was not the same among them. These differential responses were expected based on the literature, which indicates that the response depends on many species-specific factors such as the vocalization characteristics of each species (Francis et al., 2011 ; Slabbekoorn, 2013 ; Warren et al., 2006 ). We found two main groups: species that at high noise levels decreased or increased in density. The species whose density was negatively affected by noise behaved as noise-sensitive species. For these species, it could be possible that acoustic pollution impedes their proper communication by masking their vocalizations and may produce a barrier effect on their distribution, making these areas with high noise pollution inaccessible (Marler & Slabbekoorn, 2004 ; Oden et al., 2020 ; Slabbekoorn & Ripmeester, 2008 ). The species whose density increased with increasing noise behaved as noise tolerant (or less sensitive) in this study. The increased density of some species may be explained by them occupying the niche space left by more sensitive species, increasing avian homogeneity (Brumm & Slabbekoorn, 2005 ; McKinney, 2006 ). We found results similar to this study for several species (Caula et al., 2010 ; Gil et al., 2014 ; Patón et al., 2012 ; Peris & Pescador, 2004 ; Wiacek et al., 2015 ). Despite similar results in the literature, we also found other studies with different, sometimes opposite, results for the same bird species (Patón et al., 2012 ; Peris & Pescador, 2004 ; Wiacek et al., 2015 ). On the other hand, we identified species with no clear relationship with noise, which is frequently reported in the literature (Herrera-Montes & Aide, 2011 ; Parris & Schneider, 2008 ; Peris & Pescador, 2004 ). These species seem not to be affected, either negatively or positively, but the reason behind this depends on each species, its characteristics, and its history (Brumm & Slabbekoorn, 2005 ; Murgui & Hedblom, 2017 ; Slabbekoorn, 2013 ). These results may change with a larger pool of data, or with specific or more concrete studies on these species without a clear relationship to noise. Discrepancies and species with no clear relationship may be due to a lack of knowledge about the song characteristics of some species and how noise affects them. Species may not be equally susceptible to masking by noise (anthropogenic acoustic pollution), and this will depend on their song characteristics (Hu & Cardoso, 2010 ; Nemeth & Brumm, 2010 ; Slabbekoorn, 2013 ), which may also be an explanation for some noise-tolerant species in this study. Another possible factor for these discrepancies may be the differences between road and city noise (more localized and continuous, and usually more intense). Another cause of discrepancies is the possible song adaptation of the species (Brumm & Slabbekoorn, 2005 ; Francis et al., 2011 ; Oden et al., 2020 ), which may blur the relationship with noise. This may be the case of the Great Tit. In our study, its density didn’t vary with the level of noise and several studies have found that Great Tits can adapt their vocalizations to avoid masking by noise (Dominoni et al., 2020 ; Slabbekoorn, 2013 ; Slabbekoorn & Ripmeester, 2008 ). The acoustic adaptation hypothesis (Patricelli & Blickley, 2006 ) may also be a reason for the increased density of tolerant species. These species can avoid the negative effects of noise and increase their population where other species cannot. Song adaptation has been described in different species by various authors; for example, for the great tit, the blackbird (Mendes et al., 2011 ; Nemeth & Brumm, 2010 ; Sierro et al., 2017 ), the European robin (Fuller et al., 2007 ; McMullen et al., 2014 ; Polak, 2014 ), and other species (Arroyo-Solís et al., 2013 ; Gil et al., 2014 ; Sheldon et al., 2020 ). What is not clear is whether these changes are permanent or not (De Framond & Brumm, 2022 ; Derryberry et al., 2020 ; Mockford & Marshall, 2009 ). These adaptations can be found in different song characteristics (Hu & Cardoso, 2010 ; Oden et al., 2020 ; Ripmeester et al., 2010 ), and these changes can give rise to various dialects in different populations (Moseley et al., 2019 ). Song adaptation to acoustic pollution is a broad topic, and although there are numerous studies on the subject, there is a need to further improve our knowledge. In this study, only noise pollution was considered by comparing three different noise categories (high, medium, and low). However, this research should be complemented using other multivariate studies where different characteristics of the urban habitat are evaluated simultaneously, as well as the effect of other collateral noise (stress, energy expenditure) (Gil et al., 2014 ; Raiter et al., 2014 ) on each species. The urban ecosystem is a heterogeneous environment, and many urban variables can affect birds. We randomly chose points with different characteristics to balance the urban characteristics and make the categories comparable. Although in our study, we think that chosen points along a representative sampling of urban ecosystems, we cannot rule out stochastic random effects. This point is a weakness of our study; however, we believe that the differences found are caused by differences in acoustic pollution. This type of study should be combined with other studies that analyze noise with other characteristics of the urban ecosystem and how it affects birds. Another important focus for urban bird conservation, aside from our study, is the quality of the populations regardless of abundance and how cities can become ecological traps (Raiter et al., 2014 ). Urban birds and their conservation are an important issue that can be addressed using various strategies, which underlines the need for further research and expanding our knowledge on this topic. Despite the dependency of birds on effective and efficient acoustic communication, only 54.5% of the species tested responded clearly to noise. Similar results can be found in different studies(Gil et al., 2014 ; Patón et al., 2012 ; Peris & Pescador, 2004 ) although other authors report a higher proportion (Ghadiri Khanaposhtani et al., 2019 ). This highlights the complexity of the relationship between noise and birds and the need for further research, to test whether these birds have adapted their songs or other factors important for their survival. Recently, urbanization efforts have shifted toward integrating cities into the natural environment, creating “greener” and more eco-friendly cities (Alberti et al., 2003 ; Dearborn & Kark, 2010 ) through structures and tools such as green roofs, vertical gardens, and biodiversity corridors (Fernández Calvo, 2019 ; Ikin et al., 2015 ; Savard et al., 2000 ). Part of the studies on urban biodiversity are focused on being a management tool for “ecofriendly” cities (Fernández-Juricic & Jokimäki, 2001 ; White et al., 2005 ). More eco-friendly management of cities, together with a general decrease in noise pollution linked to urbanized environments, promotes an increase in biodiversity and the role of cities in conservation(Dearborn & Kark, 2010 ; Ikin et al., 2015 ; Ives et al., 2016 ). These changes would also benefit city dwellers who would have a better quality of life both physically and mentally. This eco-friendly approach promotes the well-being of inhabitants (World Health Organization, 2016 ), connects them to nature, and produces benefits through various ecosystem services (temperature regulation and mitigation, cleaning up air pollution, etc.) (Dearborn & Kark, 2010 ; Swartz et al., 2023 ). Identifying the sensitivity (how it is affected) of bird species to acoustic pollution may allow urban birds to be used as bioindicators of noise. The use of birds as bioindicators of human health and quality of life and as a useful tool for urban management and biodiversity conservation (Pollack et al., 2017 ) is becoming increasingly used and studied. Conclusions Noise pollution seems to be a key factor for birds, as well as other animal species, that can lead to evolutionary pressure or increased energy expenditure. Noise decreased the diversity of birds, and increased their homogenization, and some species also experienced a decrease in density. The variety of responses to noise pollution may be due to several factors, the song characteristics of each species, their adaptive capacity, and other possible factors such as behaviour adaptation. The characteristics of urban environments are similar in many cities around the world, making the management of cities and their green spaces relevant to the adjacent landscape for the conservation of biodiversity in them (Lepczyk et al., 2017 ; McKinney, 2006 ). The effects of noise on birds need to be taken into account, especially when managing green spaces, planning cities, and how this could promote less noisy cities. Various actions can be taken to reduce the level of noise pollution, on several fronts, promoting less use of motor vehicles (mainly private), encouraging the use of other non-noisy transport (such as bicycles), pedestrianizing more streets, and better planning of infrastructure (main roads, etc.) are actions that reduce noise pollution. Noise barriers can also be palliative measures, for example, which can be artificial or natural such as lines of vegetation on the edges of large parks. These are just a few concrete examples, as more and more research is being carried out to reduce noise pollution and its propagation in urbanized environments with different and new focuses. Declarations Competing interests. The authors declare no competing interests. Funding This research was funded by the University of Salamanca, grant number R010 / 463AD04. Author Contribution Conceptualization, P.A.B and M.P.; methodology, P.A.B. and M.P.; software, P.A.B.; validation, M.P; formal analysis, P.A.B.; investigation, P.A.B.; resources, M.P.; data curation, P.A.B.; writing—original draft preparation, P.A.B.; writing—review and editing, M.P.; visualization, P.A.B.; supervision, M.P.; project administration, M.P.; funding acquisition, M.P. All authors have read and agreed to the manuscript. Acknowledgement We would like to acknowledge the University of Salamanca for funding and administrative support. Data Availability The raw data supporting the conclusions of this article will be made available by the authors upon request. References Alberti, M., Marzluff, J. M., Shulenberger, E., Bradley, G., Ryan, C., & Zumbrunnen, C. (2003). Integrating Humans into Ecology: Opportunities and Challenges for Studying Urban Ecosystems. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5360841","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":381439077,"identity":"d01ec1a2-b0af-4c3a-9575-35233a38e848","order_by":0,"name":"Paula Almarza-Batuecas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYHACxgNAIoGBvfngww8VQCYzcwNBPRAtPMeSjSXOgLQwEqtFIsdMgrcNbC1+LebsZwwO/GCwywPqMpOQnFcbzd8O1PKjYhtOLZY9OQYHexiSi4GWJVsUbjueO+MwYwNjz5nbOLUYHMgxOMDDwJzYwNhw8IbktmO5DUAtzIxteLScf2Nw8A9DfSJQWYME75xjufMJarmRY3CYh+FwYgMbM5MEb0NN7gZCWixnPCs4LGNwvJiNh43ZWOLYgdyNQC0H8fnFnD9548M3FdV5/PLvPz78UFOXO+/84YMPflTgcRiMZIPwD4PJAzjVw7UgQB0+xaNgFIyCUTBCAQAvT11JpeWW9QAAAABJRU5ErkJggg==","orcid":"","institution":"University of Salamanca","correspondingAuthor":true,"prefix":"","firstName":"Paula","middleName":"","lastName":"Almarza-Batuecas","suffix":""},{"id":381439078,"identity":"77cb92b8-5a99-45bd-925b-877ffad5cc0f","order_by":1,"name":"Moisés Pescador","email":"","orcid":"","institution":"University of Salamanca","correspondingAuthor":false,"prefix":"","firstName":"Moisés","middleName":"","lastName":"Pescador","suffix":""}],"badges":[],"createdAt":"2024-10-30 11:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5360841/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5360841/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70322539,"identity":"022e826b-b6ce-458a-87b3-33e1184757cf","added_by":"auto","created_at":"2024-12-02 06:55:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":634250,"visible":true,"origin":"","legend":"\u003cp\u003eA: Map of the study area in central Spain detailing the location of the cities and towns where the point-count stations were located. B: zoom in on the location of some point-count stations in one of the towns included in the study (Aranjuez): yellow stars (high-noise level); green circles (medium-noise level), and red squares (low-noise level). ArcGIS, Google Earth, and Eurostat maps were used to produce the maps.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5360841/v1/63fa4a5997933ba7f39be4a9.png"},{"id":70322538,"identity":"ca0bd031-b6ac-4131-9201-1c236154f0ac","added_by":"auto","created_at":"2024-12-02 06:55:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87917,"visible":true,"origin":"","legend":"\u003cp\u003eSmoothed species accumulation curves. The figure shows the smoothed species accumulation curves and their 95% confidence interval for each level noise: High (black), Medium (dark grey), and Low (light grey).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5360841/v1/32dda3f3165d34ccbeb4fb02.png"},{"id":70322765,"identity":"db280eb4-6a2e-4ba1-a5f9-021b3e2be625","added_by":"auto","created_at":"2024-12-02 07:03:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":28018,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies with the highest density (birds/ha) at sites with a low level of noise. Average density at sites with high (black), medium (dark grey), and low (light grey) levels of noise for each bird species. MUSSTR, \u003cem\u003eMuscicapa striata\u003c/em\u003e; PHOOCH, \u003cem\u003ePhoenicurus ochruros\u003c/em\u003e; FRICOE, \u003cem\u003eFringilla coelebs\u003c/em\u003e; LINCAN, \u003cem\u003eLinaria cannabina\u003c/em\u003e; STRDEC, \u003cem\u003eStreptopelia decaocto\u003c/em\u003e; SERSER, \u003cem\u003eSerinus serinus\u003c/em\u003e; HIRRUS, \u003cem\u003eHirundo rustica\u003c/em\u003e; CHLCHL, \u003cem\u003eChloris chloris\u003c/em\u003e; STUUNI; \u003cem\u003eSturnus unicolor\u003c/em\u003e and PASDOM, \u003cem\u003ePasser domesticus\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5360841/v1/93ad2c6028fa4d74e8037d74.png"},{"id":70322764,"identity":"3ea3a306-7c03-459b-9ecd-56c7bbc59c85","added_by":"auto","created_at":"2024-12-02 07:03:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":28031,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies with the highest density (birds/ha) at sites with a high level of noise. Average density at sites with high (black), medium (dark grey), and low (light grey) levels of noise for each bird species. PICSHA, \u003cem\u003ePicus sharpei\u003c/em\u003e; PERATE, \u003cem\u003ePeriparus ater\u003c/em\u003e; PASMON, \u003cem\u003ePasser montanus\u003c/em\u003e; PICPIC, \u003cem\u003ePica pica\u003c/em\u003e; MYIMON, \u003cem\u003eMyiopsitta monachus\u003c/em\u003e; COLPAL, \u003cem\u003eColumba palumbus\u003c/em\u003e; TURMER, \u003cem\u003eTurdus merula, \u003c/em\u003eand COLLIV, \u003cem\u003eColumba livia\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5360841/v1/5c71a59b818c3024c25fd420.png"},{"id":71542610,"identity":"5e7bb8ef-d3fa-4b6f-a593-97331e1746a6","added_by":"auto","created_at":"2024-12-16 14:47:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1629268,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5360841/v1/486a121d-31e8-4655-809e-b5aee5ca4ba4.pdf"},{"id":70322535,"identity":"79546797-d0af-42cb-9b93-ed0bad764a7f","added_by":"auto","created_at":"2024-12-02 06:55:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21814,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-5360841/v1/4d19287644b246e90ac7ddad.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Noise Pollution in the Center of the Iberian Peninsula: Diversity and Abundance on Urban Birds Breeding","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUrbanized areas are becoming more abundant and expansive, often replacing other habitat types. Urban development forecasts have predicted that urban areas will continue to grow, and human populations will become increasingly concentrated in larger and larger cities (United Nations, Department of Economic and Social Affairs, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This situation raises conservation concerns about urban change and its effect on wildlife (Lepczyk et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Murgui \u0026amp; Hedblom, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), as urbanization brings many changes that can threaten wildlife, particularly birds (D\u0026iacute;az et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ditchkoff et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Soifer et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Urbanization brings with it many negative effects such as habitat fragmentation, increased stress, and contact with various sources of pollution (chemical, light, and acoustic pollution, even electromagnetic (Balmori \u0026amp; Hallberg, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Chace \u0026amp; Walsh, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Marzluff, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, urbanization can also be beneficial, leading to situations of a milder microclimate (heat island effect), increased food availability (which may be low quality), and a general decrease in predators (although the presence of cats remains a major threat) (Bernat-Ponce et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; D\u0026iacute;az et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite the multiple negative effects of urbanization, some bird species are successful in cities, with large and successful populations in urban habitats (Jokim\u0026auml;ki et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kark et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Murgui \u0026amp; Hedblom, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Slabbekoorn \u0026amp; Ripmeester, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNevertheless, it is also known that birds are particularly sensitive to noise pollution (Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Slabbekoorn \u0026amp; Ripmeester, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Anthropogenic noise pollution (also called noise in this paper) is closely linked to human activities, and its main source is road traffic (streets, avenues, roads, highways, etc.) and noise produced from other non-vehicle motors (Parris \u0026amp; Schneider, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Generally, anthropogenic acoustic pollution is characterized by low-frequency noise, starting from 2 KHz and downwards (Slabbekoorn \u0026amp; Ripmeester, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Birds use acoustic communication as one of the main communication routes to communicate with conspecifics and individuals of other species (Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This acoustic communication is extremely important to different activities of birds such as territory defense, mate attraction, parental care, and communication in cases of danger, among others (Patricelli \u0026amp; Blickley, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Noise can prevent proper and efficient acoustic communication between individuals by masking their vocalizations (Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Oden et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This increase in noise leads to different negative effects for birds such as increased stress and predation, increased time spent on territory defense, mate attraction, feeding, and vigilance(Brumm, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Eens et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Gil et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sweet et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Noise is an important stress factor for birds and can lead to a decline in their populations as their normal life cycles are hampered (Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Noise can even produce a barrier effect, preventing some birds or bird species from accessing places with high noise pollution (Ghadiri Khanaposhtani et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Patricelli \u0026amp; Blickley, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Wiacek et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Urban birdlife has declined in Spain in recent decades(SEO/BirdLife, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and a similar trend has been observed in other cities around the world(Balmori \u0026amp; Hallberg, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Acoustic pollution (noise) can mask bird vocalizations, but it does not affect all bird species equally. It depends on the individual characteristics of each species (e.g. body size) and their song (vocal range, frequencies, etc.)(Francis et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Mendes et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Alternatively, several studies have found that some species can adapt to noise; for example, with changes in their songs and vocalizations or their behaviour (Fuller et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Mockford \u0026amp; Marshall, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Oden et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main objective of the present study is to assess the effects of noise on the diversity and density of bird species living and breeding in urban areas in the center of the Iberian Peninsula (Spain). We compare the diversity and density of birds between sites with three different levels of noise (high, medium, and low). We test whether noise has a negative effect on the urban bird population in our study areas. Moreover, we aim to identify which species populations are negatively or positively affected by noise and to study the effect of anthropogenic acoustic pollution on urban bird assemblages.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eStudy area\u003c/p\u003e \u003cp\u003eSampling was carried out in 9 cities and towns in the center of the Iberian Peninsula (Spain) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), in an area of approximately 1400 Km\u0026sup2; and with a Mediterranean climate. The cities and towns were different in population and geographical size. The selected cities and towns were Madrid (324.7 Km\u0026sup2;, 3 332 035 inhabitants), Parla (9.1 Km\u0026sup2;, 133 004 inhabitants), Aranjuez (7.5 Km\u0026sup2;, 60 668 inhabitants), Pinto (10.7 Km\u0026sup2;, 55 208 inhabitants), Carranque (2.3 Km\u0026sup2;, 5 274 inhabitants), Casarrubuelos (0.79 Km\u0026sup2;, 4 062 inhabitants), Lominchar (1.1 Km\u0026sup2;, 2 639 inhabitants), Palomeque (0.26 Km\u0026sup2;, 1 143 inhabitants), and Batres (0.25 Km\u0026sup2;, 1 872 inhabitants). The study area included a wide variety of urban sites: small and large parks, ranging from squares to streets with minimal vegetation (to ensure a minimum number of bird recordings). We categorized the study area according to anthropogenic acoustic pollution (noise) (Barrig\u0026oacute;n Morillas et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Mendes et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). For prior categorization, we used noise maps and decibel (dB) measurements during previous visits to each location. In addition, we made noise pollution measurements at each bird sampling visit. We measured noise decibels for 1 minute using an Extech Instruments sonometer model 407736 (with an A-weighted filter), one meter above the ground. Noise measurements were taken at each point and each visit, covering different times throughout the morning. These categories were validated by statistical analysis. The categories with their characteristics were:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e\u0026bull;High level of acoustic pollution, where noise pollution levels were high and continuous throughout the day. Mean 56.1 dB (range: 49\u0026ndash;66 dB).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e\u0026bull;Medium level of acoustic pollution, where noise pollution levels were medium to low throughout the day, with peaks of high noise pollution corresponding to the start and end of work, schools, rush hours, etc. Mean 49.6 dB (range: 45\u0026ndash;59 dB).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e\u0026bull;Low level of acoustic pollution, where noise pollution remained low throughout the day. Mean 43.3 dB (range: 39\u0026ndash;48 dB).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBird sampling\u003c/p\u003e \u003cp\u003eThe sampling unit used was a point-count station with a 25 m fixed radius. This method was selected because it provides a standardized protocol, especially at sites with high environmental heterogeneity (Bibby et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In this study, only a 25-m radius was used to avoid the problem of decreasing species detectability at farther away distances. We established 72 point-counts, divided into three categories of acoustic pollution: high, medium, and low, with 24 count points per category. The points counts were established according to town size, ranging from 22 (the biggest city, Madrid) to 3 (the smallest, Batres, Lominchar, and Palomeque). The 72 point-count stations were at least 250 m apart to avoid overlapping and duplicated point counts. The locations of the point-count stations were randomly selected, and the three groups of points had similar and comparable characteristics. The bird species, either heard or seen, and their abundance was recorded for 10 minutes. This sampling time frame was chosen because in previous studies this duration had proven to be optimal. Sampling was conducted early in the morning, before sunrise, until noon (or 10 am during the hottest months), in optimal weather conditions, with no or low wind and no rain (Bibby et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Sampling was conducted during the breeding season, between March 2019 and August 2021. Sixteen sampling visits were made to each point-count station, and between 1 and 2 samplings were performed per month (a total of 8 visits in 2019, 6 in 2021, and only two visits in 2020 because of covid-19 shutdown).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe estimated the species diversity and density of each species for each noise level. To estimate species diversity, we calculated species richness using species accumulation curves. Species accumulation curves for each plot were constructed to measure the completeness of the sampling and to compare the species richness (Colwell \u0026amp; Coddington, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Sober\u0026oacute;n \u0026amp; Llorente, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). These curves enabled us to establish a compromise to be made among the different plot surveys, such since as if they had been carried out exclusively based on the values of the number of species observed, without reference to the effort invested, would have been obtained false results (Gotelli \u0026amp; Colwell, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The number of point counts was taken as a measure of the sampling effort and randomized 100 times to construct smoothed accumulation species curves (Gotelli \u0026amp; Colwell, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). We constructed and used 95% confidence intervals of the curves to compare species diversity among the three smoothed accumulation species curves (Gotelli \u0026amp; Colwell, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Quesada \u0026amp; MacGregor-Fors, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). We used EstimateS v 9.1.0 software to construct the smoothed species accumulation curves (Colwell \u0026amp; Coddington, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, we also calculated the density of the 33 most frequent species. We chose these most frequent species to ensure a sufficient data set for the analysis. To calculate the density (individuals per hectare) per species and point, we used the following equation proposed by Shiu \u0026amp; Lee (Shiu \u0026amp; Lee, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:D=\\frac{n}{\\pi\\:{r}^{2}}\\:10000$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e,\u003c/p\u003e \u003cp\u003ewhere D is the density, n is the number of individuals of a species and r is the sampling unit radius (in meters).\u003c/p\u003e \u003cp\u003eWe analyzed the density of each species for the three categories of acoustic pollution using a non-parametric Kruskal-Wallis test (Sokal \u0026amp; Rohlf, 1994). For species that showed significant differences, a pairwise Dunn test with Bonferroni correction was performed to detect which pairs of noise levels were significantly different. All statistical analyses were performed using IBM SPSS Statistics v 28.0.1.1 software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eSpecies diversity\u003c/p\u003e \u003cp\u003eA total of 29,934 individuals from 81 species, belongs to 37 families, were recorded (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003eA1\u003c/span\u003e). The comparison of species diversity for the three levels of noise produced smoothed species accumulation curves with a 95% confidence interval, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Sites with a high noise level had fewer species and less diversity (49 bird species) than the sites with a medium or low level of noise (with 71 and 67 bird species respectively). In our analysis, the 95% confidence interval of the high noise level curve did not overlap with the confidence intervals of the other two curves. Of the 81 species, 17 species were not registered in the three noise categories, were not associated with any noise category, such as the Hawfinch (\u003cem\u003eCoccothraustes coccothraustes\u003c/em\u003e) which was not registered in a high-noise sites. On the other hand, 19 species only were recorded in one of the categories. For example, the European Crested Tit (\u003cem\u003eLophophanes cristatus\u003c/em\u003e) was only recorded in sites with a low level of noise. The analysis of the trends in population size over the last decade showed that 21 species (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003eA1\u003c/span\u003e) were in decline in all Spanish territories such as the House Sparrow (\u003cem\u003ePasser domesticus\u003c/em\u003e), Eurasian Magpie (\u003cem\u003ePica pica\u003c/em\u003e), European Serin (\u003cem\u003eSerinus serinus\u003c/em\u003e), Common Linnet (\u003cem\u003eLinaria cannabina\u003c/em\u003e), Eurasian Tree Sparrow (\u003cem\u003ePasser montanus\u003c/em\u003e), White Wagtail (\u003cem\u003eMotacilla alba\u003c/em\u003e), and the Iberian Green Woodpecker (\u003cem\u003ePicus sharpei\u003c/em\u003e) (SEO/BirdLife, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although these species are experiencing a decrease in population size, they can be found in urban habitats. Of the 81 species, 15 species are listed in Spanish legislation as endangered or near endangered (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003eA1\u003c/span\u003e) such as the Barn Swallow (\u003cem\u003eHirundo rustica\u003c/em\u003e), which is classified as vulnerable (VU), and the Western Jackdaw (\u003cem\u003eCorvus monedula\u003c/em\u003e), classified as endangered (EN) (SEO/BirdLife, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We also found 2 rare species: Hawfinch and Pied Flycatcher (\u003cem\u003eFicedula hypoleuca\u003c/em\u003e) (SEO/BirdLife, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Three allochthonous species were recorded, stand out Monk Parakeet (\u003cem\u003eMyiopsitta monachus\u003c/em\u003e), which is one of the most frequent and abundant species found. Another species observed was the Common and Pallid Swift (\u003cem\u003eApus apus and A. pallidus\u003c/em\u003e). However, they were not included in the density analysis because of their biology, as they spend most of their lives away from the ground and noise.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe 33 most frequent and abundant bird species whose densities were analyzed. The table lists the common name of each species recorded, as well as its scientific name, conservation status (c. status), and the number of times it was recorded in each of the three noise categories (high, medium, and low) included in this study. The asterisk marks those species whose populations are in decline in Spain and ALLOC is the allochthonous species in Spain.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnglish name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScientific name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC. status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedium level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon Wood Pigeon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eColumba palumbus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon Blackbird\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTurdus merula\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHouse Sparrow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePasser domesticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpotless Starling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSturnus unicolor\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEuropean Greenfinch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eChloris chloris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEurasian Magpie\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePica pica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEuropean Goldfinch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCarduelis carduelis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEuropean Serin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSerinus serinus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarn Swallow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHirundo rustica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVU*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEurasian Collared Dove\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStreptopelia decaocto\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRock Dove\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eColumba livia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon House Martin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDelichon urbicum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon Linnet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eLinaria cannabina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEurasian Blue Tit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCyanistes caerueleus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreat Tit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eParus major\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoal Tit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePeriparus ater\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite Wagtail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMotacilla alba\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonk Parakeet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMyiopsitta monachus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eALLOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEuropean Robin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eErithacus rubecula\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack Redstart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePhoenicurus ochruros\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon Chaffinch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFringilla coelebs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEurasian Blackcap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSylvia atricapilla\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShort-toed Treecreeper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCerthia brachydactyla\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStock Dove\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eColumba oenas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSardinian Warbler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSylvia melanocephala\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEurasian Tree Sparrow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePasser montanus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNT*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIberian Green Woodpecker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePicus sharpei\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEuropean Pied Flycatcher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFicedula hypoleuca\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong-tailed Tit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAegithalos caudatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpotted Flycatcher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMuscicapa striata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern Jackdaw\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCorvus monedula\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEN*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrested Lark\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eGalerida cristata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMistle Thrush\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTurdus viscivorus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eResponse to noise\u003c/p\u003e \u003cp\u003eIn the density analysis, we observed that birds responded differently to the level of noise. Out of the 33 species studied, only 18 species showed a clear response. For the other 15 species, significant results were not obtained from the statistical analysis or the results did not clearly explain the response of these species to noise. Moreover, the species that did show a clear result could be divided into two groups or responses. One group or response consisted of species whose density responded negatively to noise. The density of these species was higher when the noise level was low than when it was high (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This group had statistically significant values and consisted of 10 bird species (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e): European Greenfinch (\u003cem\u003eChloris chloris\u003c/em\u003e), Common Chaffinch (\u003cem\u003eFringilla coelebs\u003c/em\u003e), Barn Swallow (\u003cem\u003eHirundo rustica\u003c/em\u003e), Common Linnet (\u003cem\u003eLinaria cannabina\u003c/em\u003e), Spotted Flycatcher (\u003cem\u003eMuscicapa striata\u003c/em\u003e), House Sparrow (\u003cem\u003ePasser domesticus\u003c/em\u003e), Black Redstart (\u003cem\u003ePhoenicurus ochruros\u003c/em\u003e), European Serin (\u003cem\u003eSerinus serinus\u003c/em\u003e), Eurasian Collared Dove (\u003cem\u003eStreptopelia decaocto\u003c/em\u003e), and the Spotless Starling (\u003cem\u003eSturnus unicolor\u003c/em\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the results of the pairwise analysis of noise levels for each species.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the Kruskal-Wallis test for the species with the highest density at sites with a low level of noise. The table shows the results of the analysis among the three noise levels and the pairwise analysis. The species with a p-value of \u0026gt;\u0026thinsp;0.05 are indicated as ns.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHigh-Low\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eHigh-Medium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMedium-Low\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChloris chloris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-116.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-121.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFringilla coelebs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-32.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-6.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-26.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHirundo rustica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-186.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-32.721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-153.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLinaria cannabina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-101.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-40.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-61.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMuscicapa striata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-15.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-15.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePasser domesticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-96.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-23.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-72.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePhoenicurus ochruros\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-37.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-18.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-19.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSerinus serinus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-54.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-8.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-45.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptopelia decaocto\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-109.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-77.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-32.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSturnus unicolor\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-230.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-122.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-108.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe other group or response consisted of species whose density responded positively to noise. The density of these species was greater when the noise level was high than when it was low (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This group had statistically significant values and consisted of 8 bird species (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e): Rock Dove (\u003cem\u003eColumna livia\u003c/em\u003e), Common Wood Pigeon (\u003cem\u003eColumba palumbus\u003c/em\u003e), Monk Parakeet (\u003cem\u003eMyiopsitta monachus\u003c/em\u003e), Eurasian Tree Sparrow (\u003cem\u003ePasser montanus\u003c/em\u003e), Coal Tit (\u003cem\u003ePeriparus ater\u003c/em\u003e), Eurasian Magpie (\u003cem\u003ePica pica\u003c/em\u003e), Iberian Green Woodpecker (\u003cem\u003ePicus sharpei\u003c/em\u003e), and the Common blackbird (\u003cem\u003eTurdus merula\u003c/em\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results of the pairwise analysis of noise levels for each species.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the Kruskal-Wallis test for the species with the highest density at sites with a high level of noise. The table shows the results of the analysis among the three noise levels and the pairwise analysis. The species with a p-value of \u0026gt;\u0026thinsp;0.05 are indicated as ns.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHigh-Low\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eHigh-Medium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMedium-Low\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eColumba livia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e201.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e132.379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e68.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eColumba palumbus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e25.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMyiopsitta monachus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e155.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e207.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e110.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e97.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePasser montanus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-7.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePeriparus ater\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e79.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55.938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePica pica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e154.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e37.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e117.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePicus sharpei\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTurdus merula\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e49.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA total of 81 breeding species belonging to 37 families were recorded. This diversity was to be expected based on similar studies on urban avifauna (Carral-Murrieta et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Caula et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pat\u0026oacute;n et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Even though the urban habitat is one of the most altered with several sources of stress for birds (D\u0026iacute;az et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) we found bird species classified as being endangered, rare, or declining in population (SEO/BirdLife, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These results were expected and are in line with other similar studies (Ives et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pat\u0026oacute;n et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Sorace \u0026amp; Gustin, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and highlight the role of the urban ecosystem in maintaining bird diversity and conservation (Jokim\u0026auml;ki et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Villase\u0026ntilde;or et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The species that stand out because of their density and frequency are similar (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and are typically urban species (synanthropic species). Other similar studies highlight these species for their high frequency and abundance (Fern\u0026aacute;ndez-Juricic, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Kontsiotis et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Morelli et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sorace \u0026amp; Gustin, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We see that the frequency and density of species decrease rapidly, a finding that is coherent with the effect of urbanization on the homogenization of biodiversity, with synanthropic species being the most abundant and frequent (McKinney, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). One of the most abundant species found in this study was the invasive exotic species Monk Parakeet (\u003cem\u003eMyiopsitta monachus\u003c/em\u003e). This and the other invasive exotic species found, despite not being in their natural habitat, have succeeded mainly due to changes caused by urbanization (Blair, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; D\u0026iacute;az et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; McKinney, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), which has caused problems for other bird species and even humans (Molina et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe found lower bird diversity at sites with high noise levels. Noise seems to negatively affect bird diversity, rarefying some species, and even making them absent in places with a high level of noise (Francis et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Marzluff, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wiacek et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This rarefying of species with increasing noise was also observed by Herrera-Montes and Aide (Herrera-Montes \u0026amp; Aide, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), who found that some species disappeared in areas close to the noise source (road), and reappeared when the noise decreased. In this study, we obtained a similar species diversity at low level and medium noise levels. High species diversity has been related to medium and low disturbance levels in several studies (Kontsiotis et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; McKinney, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Peris \u0026amp; Pescador, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wiacek et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In this case, noise (anthropogenic acoustic pollution) is detrimental to birds because it masks their vocalizations, and this noise can be a barrier to their dispersion (Brumm \u0026amp; Slabbekoorn, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Slabbekoorn \u0026amp; Ripmeester, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). However, this relationship between species richness and noise is not always clear, for example Ghadiri Khanaposhtani et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) show that avian richness could be decrease in some cases or increase in another ones in relation with noise increments.\u003c/p\u003e \u003cp\u003eThe response of the species to noise was not the same among them. These differential responses were expected based on the literature, which indicates that the response depends on many species-specific factors such as the vocalization characteristics of each species (Francis et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). We found two main groups: species that at high noise levels decreased or increased in density. The species whose density was negatively affected by noise behaved as noise-sensitive species. For these species, it could be possible that acoustic pollution impedes their proper communication by masking their vocalizations and may produce a barrier effect on their distribution, making these areas with high noise pollution inaccessible (Marler \u0026amp; Slabbekoorn, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Oden et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Slabbekoorn \u0026amp; Ripmeester, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The species whose density increased with increasing noise behaved as noise tolerant (or less sensitive) in this study. The increased density of some species may be explained by them occupying the niche space left by more sensitive species, increasing avian homogeneity (Brumm \u0026amp; Slabbekoorn, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; McKinney, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). We found results similar to this study for several species (Caula et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gil et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pat\u0026oacute;n et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Peris \u0026amp; Pescador, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wiacek et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Despite similar results in the literature, we also found other studies with different, sometimes opposite, results for the same bird species (Pat\u0026oacute;n et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Peris \u0026amp; Pescador, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wiacek et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the other hand, we identified species with no clear relationship with noise, which is frequently reported in the literature (Herrera-Montes \u0026amp; Aide, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Parris \u0026amp; Schneider, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Peris \u0026amp; Pescador, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). These species seem not to be affected, either negatively or positively, but the reason behind this depends on each species, its characteristics, and its history (Brumm \u0026amp; Slabbekoorn, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Murgui \u0026amp; Hedblom, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These results may change with a larger pool of data, or with specific or more concrete studies on these species without a clear relationship to noise. Discrepancies and species with no clear relationship may be due to a lack of knowledge about the song characteristics of some species and how noise affects them. Species may not be equally susceptible to masking by noise (anthropogenic acoustic pollution), and this will depend on their song characteristics (Hu \u0026amp; Cardoso, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), which may also be an explanation for some noise-tolerant species in this study. Another possible factor for these discrepancies may be the differences between road and city noise (more localized and continuous, and usually more intense). Another cause of discrepancies is the possible song adaptation of the species (Brumm \u0026amp; Slabbekoorn, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Francis et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Oden et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which may blur the relationship with noise. This may be the case of the Great Tit. In our study, its density didn\u0026rsquo;t vary with the level of noise and several studies have found that Great Tits can adapt their vocalizations to avoid masking by noise (Dominoni et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Slabbekoorn, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Slabbekoorn \u0026amp; Ripmeester, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The acoustic adaptation hypothesis (Patricelli \u0026amp; Blickley, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) may also be a reason for the increased density of tolerant species. These species can avoid the negative effects of noise and increase their population where other species cannot. Song adaptation has been described in different species by various authors; for example, for the great tit, the blackbird (Mendes et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Nemeth \u0026amp; Brumm, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sierro et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the European robin (Fuller et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; McMullen et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Polak, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and other species (Arroyo-Sol\u0026iacute;s et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gil et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sheldon et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). What is not clear is whether these changes are permanent or not (De Framond \u0026amp; Brumm, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Derryberry et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mockford \u0026amp; Marshall, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These adaptations can be found in different song characteristics (Hu \u0026amp; Cardoso, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Oden et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ripmeester et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and these changes can give rise to various dialects in different populations (Moseley et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Song adaptation to acoustic pollution is a broad topic, and although there are numerous studies on the subject, there is a need to further improve our knowledge.\u003c/p\u003e \u003cp\u003eIn this study, only noise pollution was considered by comparing three different noise categories (high, medium, and low). However, this research should be complemented using other multivariate studies where different characteristics of the urban habitat are evaluated simultaneously, as well as the effect of other collateral noise (stress, energy expenditure) (Gil et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Raiter et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) on each species. The urban ecosystem is a heterogeneous environment, and many urban variables can affect birds. We randomly chose points with different characteristics to balance the urban characteristics and make the categories comparable. Although in our study, we think that chosen points along a representative sampling of urban ecosystems, we cannot rule out stochastic random effects. This point is a weakness of our study; however, we believe that the differences found are caused by differences in acoustic pollution. This type of study should be combined with other studies that analyze noise with other characteristics of the urban ecosystem and how it affects birds. Another important focus for urban bird conservation, aside from our study, is the quality of the populations regardless of abundance and how cities can become ecological traps (Raiter et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Urban birds and their conservation are an important issue that can be addressed using various strategies, which underlines the need for further research and expanding our knowledge on this topic.\u003c/p\u003e \u003cp\u003eDespite the dependency of birds on effective and efficient acoustic communication, only 54.5% of the species tested responded clearly to noise. Similar results can be found in different studies(Gil et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pat\u0026oacute;n et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Peris \u0026amp; Pescador, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) although other authors report a higher proportion (Ghadiri Khanaposhtani et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This highlights the complexity of the relationship between noise and birds and the need for further research, to test whether these birds have adapted their songs or other factors important for their survival.\u003c/p\u003e \u003cp\u003eRecently, urbanization efforts have shifted toward integrating cities into the natural environment, creating \u0026ldquo;greener\u0026rdquo; and more eco-friendly cities (Alberti et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Dearborn \u0026amp; Kark, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) through structures and tools such as green roofs, vertical gardens, and biodiversity corridors (Fern\u0026aacute;ndez Calvo, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ikin et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Savard et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Part of the studies on urban biodiversity are focused on being a management tool for \u0026ldquo;ecofriendly\u0026rdquo; cities (Fern\u0026aacute;ndez-Juricic \u0026amp; Jokim\u0026auml;ki, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; White et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). More eco-friendly management of cities, together with a general decrease in noise pollution linked to urbanized environments, promotes an increase in biodiversity and the role of cities in conservation(Dearborn \u0026amp; Kark, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Ikin et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ives et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These changes would also benefit city dwellers who would have a better quality of life both physically and mentally. This eco-friendly approach promotes the well-being of inhabitants (World Health Organization, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), connects them to nature, and produces benefits through various ecosystem services (temperature regulation and mitigation, cleaning up air pollution, etc.) (Dearborn \u0026amp; Kark, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Swartz et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Identifying the sensitivity (how it is affected) of bird species to acoustic pollution may allow urban birds to be used as bioindicators of noise. The use of birds as bioindicators of human health and quality of life and as a useful tool for urban management and biodiversity conservation (Pollack et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) is becoming increasingly used and studied.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eNoise pollution seems to be a key factor for birds, as well as other animal species, that can lead to evolutionary pressure or increased energy expenditure. Noise decreased the diversity of birds, and increased their homogenization, and some species also experienced a decrease in density. The variety of responses to noise pollution may be due to several factors, the song characteristics of each species, their adaptive capacity, and other possible factors such as behaviour adaptation. The characteristics of urban environments are similar in many cities around the world, making the management of cities and their green spaces relevant to the adjacent landscape for the conservation of biodiversity in them (Lepczyk et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; McKinney, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effects of noise on birds need to be taken into account, especially when managing green spaces, planning cities, and how this could promote less noisy cities. Various actions can be taken to reduce the level of noise pollution, on several fronts, promoting less use of motor vehicles (mainly private), encouraging the use of other non-noisy transport (such as bicycles), pedestrianizing more streets, and better planning of infrastructure (main roads, etc.) are actions that reduce noise pollution. Noise barriers can also be palliative measures, for example, which can be artificial or natural such as lines of vegetation on the edges of large parks. These are just a few concrete examples, as more and more research is being carried out to reduce noise pollution and its propagation in urbanized environments with different and new focuses.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests.\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was funded by the University of Salamanca, grant number R010 / 463AD04.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, P.A.B and M.P.; methodology, P.A.B. and M.P.; software, P.A.B.; validation, M.P; formal analysis, P.A.B.; investigation, P.A.B.; resources, M.P.; data curation, P.A.B.; writing\u0026mdash;original draft preparation, P.A.B.; writing\u0026mdash;review and editing, M.P.; visualization, P.A.B.; supervision, M.P.; project administration, M.P.; funding acquisition, M.P. All authors have read and agreed to the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to acknowledge the University of Salamanca for funding and administrative support.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlberti, M., Marzluff, J. M., Shulenberger, E., Bradley, G., Ryan, C., \u0026amp; Zumbrunnen, C. (2003). Integrating Humans into Ecology: Opportunities and Challenges for Studying Urban Ecosystems. 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In \u003cem\u003eWHO Regional Office for Europe\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acoustic Pollution, Biodiversity, Conservation, Noise Tolerance, Urbanization","lastPublishedDoi":"10.21203/rs.3.rs-5360841/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5360841/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn an increasingly urbanized world, biodiversity, and more specifically birdlife located in urbanized ecosystems, faces several threats. Among these, noise pollution has proven to be one of the most significant, as it affects the effectiveness and efficiency of acoustic communication. We studied the relationship between noise and the diversity and abundance of birds breeding in urban areas in the central region of the Iberian Peninsula (Spain). We analyzed how species diversity and density varied across three levels of noise pollution (high, medium, and low). Species diversity decreased in areas with high noise pollution as compared to the sites with medium and low levels of noise. We analyzed the density of the most frequent species found within each category. We identified eight additional noise-tolerant species, whose density had significantly increased in environments with high levels of noise (e.g. Blackbird, Eurasian Tree Sparrow, and the Coal Tit). The ten most sensitive species, such as the Common Linnet, House Sparrow, and the European Greenfinch, had significantly decreased densities when the level of noise increased. Identifying the sensitivity (the effect) of urban bird species to acoustic pollution is vital for effective conservation management measures and for the sustainable planning and management of cities.\u003c/p\u003e","manuscriptTitle":"Noise Pollution in the Center of the Iberian Peninsula: Diversity and Abundance on Urban Birds Breeding","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-02 06:55:07","doi":"10.21203/rs.3.rs-5360841/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0602f756-f4c5-4afa-a5e5-6bf4b40abdf6","owner":[],"postedDate":"December 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-16T14:39:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-02 06:55:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5360841","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5360841","identity":"rs-5360841","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}