Elsevier

Ecological Informatics

Volume 64, September 2021, 101375
Ecological Informatics

The effect of environmental variables on owl distribution in Central Europe: A case study from the Czech Republic

https://doi.org/10.1016/j.ecoinf.2021.101375Get rights and content

Highlights

  • The multivariate analysis of the owl community based on atlas data

  • Elevational and temperature distribution of Czech owls

  • Boreal Owl as a susceptible species to climate changes

  • Potential of Citizen Science data for species and habitat protection.

Abstract

Species distributional data from atlas projects collected by volunteers and professionals play an essential role in ecology and biodiversity conservation. Atlas data primarily allow evaluating longitudinal and latitudinal gradients in species distribution. However, the effects of additional factors such as elevation and associated climatic conditions and landscape structure are rarely assessed. We used the original data from the Atlas of birds breeding in the Czech Republic in terms of the presence and absence (0/1) of breeding occurrence of seven owl species in 604 mapping quadrates (each quadrate 12.0 × 11.1 km in size) to assess the effect of elevation (reaching from 100 to 1100 m a.s.l.) and temperature on the distributional patterns of the owls. Using a multivariate spatial analysis with latitude and longitude as space predictors and landscape structure as covariates, we found that elevation and temperature significantly affected owl distribution; the model explained 94.8% of the variability (p = 0.002). Only the boreal owl (Aegolius funereus) showed a clear preference for the highest elevation, and simultaneously, boreal and pygmy (Glaucidium passerinum) owls preferred the coldest environments. Eagle owl (Bubo bubo) and tawny owl (Strix aluco) most often occupied low and middle elevation of moderate temperatures. Barn owl (Tyto alba) and long-eared owl (Asio otus) inhabited the warmest areas in low elevations. Finally, little owl (Athene noctua) most often occurred in the lowest elevations of intermediate temperatures. We have documented that the elevation and associated climate conditions can work as an effective predictor to assess distributional preferences of owl species based on atlas data. The findings can be helpful when the management of owls' habitats is considered and implemented. For example, the results of our case study suggest that the boreal owl can be susceptible to global warming and intensive logging at high elevations.

Introduction

Broad-scale bird monitoring projects are the longest-running and largest citizen science programs (for review, see Gibbons et al., 2007) and play an important role in ecology and biodiversity conservation studies (Herrando et al., 2019; Robertson et al., 2010; Whittaker et al., 2005). Distributional data from breeding bird atlases usually provide reliable and high-quality datasets collected by standardized methods over regions (e.g., Atlas of Breeding Birds of Wallonia; Jacob et al., 2010), countries (e.g., Atlas of Breeding Birds in the Czech Republic; Šťastný et al., 2006), and continents (e.g., The EBCC Atlas of European Breeding Birds; Hagemeijer and Blair, 1997; eBIRD). However, the potential of atlas data is still undervalued (for review, see Donald and Fuller, 1998; Dunn and Weston, 2008). For example, atlas data used to be displayed as the 2D-maps, documenting geographical patterns in species distribution along latitude and longitude. Still, the effect of additional factors such as elevation and associated climatic conditions and land cover on species distribution is hidden in the maps. Although some atlases have included translucent plastic films to indicate the distributional patterns of individual species to additional effects (e.g., Kloubec et al., 2015; Šťastný et al., 2006), comprehensive analyses of other factors are scarce (Donald and Fuller, 1998; Dunn and Weston, 2008; Milanesi et al., 2017).

Geographical factors — especially latitude, longitude, and elevation — firmly control species distribution (Storch et al., 2003). While latitudinal effects work on a broad geographical (horizontal) scale, elevation effects can be evident on a small (vertical) scale as a result of temperature and habitat gradients (Barry, 2008; Chamberlain et al., 2016; Kolář et al., 2017; Londoño et al., 2017; McCain, 2009; Nagy and Grabherr, 2009). It has been shown that species diversity decreases with increasing distance from the equator in various animal taxa, including birds (Darwin, 1859; Hawkins et al., 2003). This effect has been explained, for example, by the decrease of primary productivity and habitat diversity towards northern latitude (Kerr and Packer, 1997; Rohde, 1992). Elevational diversity gradients have commonly been reported as decreasing in species diversity (e.g., Brown and Lomolino, 1998; Stevens, 1992; Terborgh, 1977). However, the effect of local environmental conditions can shift the peak of species diversity at any specific elevation, apart from the highest elevation (for details, see McCain, 2009; Rahbek, 2005). This effect can be explained by low temperature, habitat structure, short breeding season, low food availability, and higher predation risk at higher elevations (Boyle et al., 2016; Hawkins, 1999; Marchesi et al., 2006; McCain, 2009; Sergio et al., 2004, Sergio et al., 2009).

The studies dealing with the relationship between the elevational gradient and animal distribution have usually focused on particular species in specific environments. For example, the effect of elevation was studied in particular owl species, including Eurasian eagle owl Bubo bubo (Eifel region, Germany, Dalbeck and Heg, 2006; Trento region, Italy, Sergio et al., 2004), tawny owl Strix aluco (Trento region, Italy, Marchesi et al., 2006; Duna-Ipoly National Park, Hungary, Sasvári and Hegyi, 2011a), boreal owl Aegolius funereus (Šumava Mts., Czech Republic, Zárybnická et al., 2017a), little owl Athene noctua (catchment area of the Nidda River, Hesse, Germany, Gottschalk et al., 2011), barn owl Tyto alba (Province of León, Spain, Alegre et al., 1989), and Eurasian pygmy owl Glaucidium passerinum (Rila Mts., Bulgaria and Slovakia, Pačenovský and Shurulinkov, 2008). The rare studies have documented the differentiation of elevational distribution of two or three coexisting species. For example, it has been reported that tawny owl preferred to occupy lower elevations than boreal and Ural owls Strix uralensis (Mt. Krim, Slovenia Vrezec, 2003; Vrezec and Tome, 2004a). Similarly, tawny and Ural owls segregated their elevational distribution due to competitive exclusion (Slovenia Mts. Vrezec and Tome, 2004b). However, the studies assessing the elevational segregation of particular owl species within the whole community occupying a large geographical area are completely lacking.

The distribution of birds, including owls, also varies significantly with changes in habitat structure and heterogeneity, although particular species show different responses (Hanzelka and Reif, 2016; Morelli et al., 2019). One of the most sensitive groups to habitat changes is forest-dwelling animal species that usually suffer from the loss of forest area and intensive forest management (Schmiegelow and Monkkonen, 2002). For example, the population size and viability of boreal owl and pygmy owl are driven by the presence of old-growth coniferous forests (Barbaro et al., 2016; Hakkarainen et al., 2008; Zárybnická et al., 2017a; Zárybnická et al., 2017b). These habitats are necessary to provide suitable conditions for breeding and foraging these species; mainly, they provide safe shelters and a sufficient amount of tree cavities (Barbaro et al., 2016; Baroni et al., 2020; Hakkarainen et al., 2008). However, in Europe, the proportion of coniferous forests usually increases with increasing latitude and elevation (e.g., Kolář et al., 2017; Zárybnická et al., 2017a). Therefore, it is unclear if the effect of elevation separated from habitats still affects the distribution of owls.

We aimed to perform a multivariate spatial analysis of the data from the Atlas of breeding birds in the Czech Republic (Šťastný et al., 2006) as a case study to find the effect of elevation and climatic conditions on the distribution patterns of Czech owls. More specifically, we used the original data from the Atlas of breeding birds in terms of the presence and absence (0/1) of breeding occurrence of seven owl species in 604 mapping quadrates (each quadrate 12.0 × 11.1 km in size) to assess the effect of elevation (reaching from 100 to 1100 m a.s.l.), temperature, and rainfall on the owls' distribution. To remove the impact of additional factors, we included latitude and longitude as space predictors and landscape structure as covariates. We also aimed to discuss the biological results of our study to point the species that may be susceptible to habitat and clime changes.

Section snippets

Atlas data

We used the data from the Atlas of birds breeding in the Czech Republic in 2001–2003 (Šťastný et al., 2006). These data include the occurrence (presence/absence) of nine owl species in 628 mapping quadrates (each quadrate of 12.0 × 11.1 km in size) distributed between 100 and 1100 m a. s. l. (Fig. 1). We assessed the occupancy of quadrates only when the breeding of owl species was confirmed (i.e., we only included quadrates marked as “D”), as recommended by (Moudrý et al., 2017). We assessed

Results

Tawny and long-eared owls were the most frequent owl species breeding in 352 and 308 mapping quadrates (58.3% and 51.0% of all mapping quadrates, respectively), followed by the Eurasian eagle owl (n = 238, 39.4%), barn owl (n = 184, 30.5%), and boreal owl (n = 114, 18.9%). Eurasian pygmy and little owls were the most less frequent species breeding in 66 (10.9%) and 38 (6.3%) quadrates, respectively (Table 2). The distribution of owls covered the entire elevational range between 100 m and 1100 m

Discussion

Using the multivariate analysis with latitude and longitude included as space predictors and landscape structure as covariates, we found the distributional pattern of owl species along elevational and temperature gradients. Rainfall did not influence the owl distribution; however, it significantly correlated with temperature.

Conclusion

We found that elevation and temperature, controlled for habitat types, significantly influenced the owl distribution in the Czech Republic, but particular species showed different responses. Boreal and little owls were the most limited by elevation. While boreal owl preferred to occupy the highest elevations, little owl favored settling the lowest elevations. Boreal owl, pygmy owl, barn owl, and long-eared owl were the most limited by temperatures. While boreal and pygmy owls preferred to

Declaration of Competing Interest

None.

Acknowledgments

We are grateful to all field ornithologists who collected data on breeding owls for the Atlas of birds breeding in the Czech Republic during 2001–2003. We also appreciate the comments on the draft of the manuscript provided by W. M. Hochachka, Y. Benedetti, V. Moudrý, and an anonymous reviewer. This study was supported by the Internal Grant Agency of the Faculty of Environmental Sciences, Czech University of Life Sciences Prague (IGA No. 20184222; 42300/1312/3154).

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