The use of socio-economy in species distribution modelling: Features of rural societies improve predictions of barn owl occurrence

https://doi.org/10.1016/j.scitotenv.2020.140407Get rights and content

Highlights

  • Barn owl prefers grasslands, fields, old churches and regions with mild climate.

  • Socio-economy (unemployment, income, etc.) also predicts barn owl occurrence.

  • Socio-economy may add overlooked information that links to farmland biodiversity.

Abstract

Variation of habitats and resources important for farmland birds seems to be only partly captured by ordinary statistics on land-use and agricultural production. For instance, densities of rodents being prey for owls and raptors or structures of rural architecture providing nesting sites for many species are central for bird diversity but are not reported in any official statistics. Thus, modelling species distributions, population abundance and trends of farmland birds may miss important predictive habitat elements. Here, we involve local socio-economy factors as a source of additional information on rural habitat to test whether it improves predictions of barn owl occurrence in 2768 churches across Poland. Barn owls occurred in 778 churches and seemed to prefer old churches made of brick located in regions with a milder climate, higher share of arable land and pastures, low road density and low levels of light pollution. Including data on local unemployment, the proportion of elder citizens, commune income per citizen, the share of citizens with high education and share of farmers among working population improved the model substantially and some of these variables predicted barn owl occurrence better than several land-use and climate data. Barn owls were more likely to occur in areas with high unemployment, a higher proportion of older citizens in a local population and higher share of farmers among working population. Importantly, the socio-economy variables were correlated with the barn owl occurrence despite all climatic, infrastructure and land-use data were present in the model. We conclude that the socio-economy of local societies may add important but overlooked information that links to spatial variation in farmland biodiversity.

Introduction

In the Anthropocene, the area of undisturbed natural environments has been considerably reduced across the whole globe. In many regions, vast areas of natural habitats (e.g. forests and grasslands) have been lost and replaced by new land-uses managed by humans such as farmland and urban areas (Antrop, 2004). Currently, farmlands are the most extensive habitat for biodiversity in Europe, harboring, for example, more than one half (250 species) of European bird species, of which 50% have suffered steep population declines (Krebs et al., 1999; Donald et al., 2001; Wretenberg et al., 2006). The important reason for this decline is believed to be driven by reduced amount of residual habitats at the field level (field verges, grasslands, rock outcrops, infield islands, wetlands) and a generally reduced habitat heterogeneity at the landscape level (e.g. Emmerson et al., 2016; Šálek et al., 2018b). Some recent studies also suggest additional influences of changes in human settlements as old farms and human settlements are important nesting habitats for many species but these are now renovated or replaced by new ones (Hiron et al., 2013; Rosin et al., 2016, Rosin et al., 2020; Šálek et al., 2016, Šálek et al., 2018a; see also Skórka et al., 2018).

Data on residual farmland habitats and habitat elements important for farmland birds are, however, not easily captured by ordinary statistics (e.g. the Corine Land Cover data, or national agricultural land-use statistics), as such habitats are generally not monitored because they are too small and play a marginal role in food production. Similarly, the age and structure of buildings and the availability of different microhabitats linked with rural architecture (see examples in Rosin et al., 2016, Rosin et al., 2020) are usually not covered by official statistics in an accessible way. Thus, current state and changes in the availability of these residual habitats in agricultural landscapes remain largely unknown, and thus making the protection and management of farmland birds difficult. However, one may consider social and economic characteristics at administrative level (e.g. commune or parish, continuously collected at such spatial scales in many countries) as a potential indicators of residual habitats, vegetation heterogeneity and habitat structures (e.g. Hope et al., 2003).

In theory, socio-economic statistics may give additional information on general levels of agricultural intensification, amount of residual farmland habitats and residual habitat elements, type and age of human settlements at the landscape scale, as socio-economy commonly varies between regions, and thus could be linked to corresponding variation in biodiversity (e.g. Rosin et al., 2020). Furthermore, local socio-economy (e.g. average age of citizens, wages, degree of unemployment, etc.) may also give additional information on general levels of landscape and habitat heterogeneity. For example, old farmers in poor regions may be more likely to continue small-scale extensive farming with traditional crops. Moreover, we expect more abandoned farms in poor regions (e.g. Wretenberg et al., 2007), which can partly increase landscape heterogeneity and furthermore be of direct use for wildlife (Mainwaring, 2015), including birds (Wretenberg et al., 2007). In rich regions, however, we expect a higher share of young farmers renovating their homesteads, modernising farming practices and implementing large-scale intensive farming. Therefore, we also expect a loss of residual habitats and habitat elements and, as a result, a loss in landscape heterogeneity. Such broad associations between socio-economy and agricultural intensification was already suggested in Donald et al. (2001) comparing bird population declines and level of agricultural intensification across European countries. However, empirical evidence linking socio-economy and biodiversity are lacking.

The aim of this study was to investigate whether socio-economic statistics add to explain observed spatial variation of a farmland breeding species. To answer that we focus on one iconic bird species of rural landscapes – the barn owl (Tyto alba). The barn owl is an avian predator specialising on small mammals in open farmlands and it is known to use buildings, especially churches, for nesting (Barn Owl Trust, 2012). Its population has declined dramatically in many European countries during the last decades (Toms et al., 2001; Martinez and Zuberogoitia, 2004; Poprach, 2017). The occurrence of barn owls was surveyed in nearly 2800 churches in Poland and we linked it to two categories of variables: ordinary climate and land-use (including infrastructure) variables and socio-economic statistics at the commune level. First, we investigated the importance of climate, land-use, church architecture and infrastructure-associated data for explaining variation in the presence of barn owls. Based on previous studies we hypothesized that this species prefers: regions with a less severe winter climate, churches located in agriculture-dominated landscape, and old churches over new ones (Altwegg et al., 2006). Second, we investigated the links between socio-economic statistics at the commune level (age structure of citizens, economy and education levels) as predictors of barn owl occurrence. We expected socio-economic variables to also be good predictors of barn owl occurrence, as we assumed that these statistics would cover the type of unmanaged grassland habitat mainly used by this species (i.e. tall grass habitats such as residual grasslands and abandoned grasslands). Finally, we tested whether adding socio-economy data into a model already containing climate, land-use, and infrastructure-associated variables improved the predictive power of the models. We hypothesize that socio-economy may contain additional information on habitat quality which is not reflected by land-use, climate or infrastructure that may improve model performance and the predictions of presence vs. absence.

Section snippets

Barn owl survey

The Polish population of the barn owl is estimated at 1000–1500 breeding pairs (Chodkiewicz et al., 2015) and has been declining for decades (Tomiałojć and Stawarczyk, 2003), most likely due to reduced amount of safe nesting places, changes of agricultural landscapes and increased mortality due to collisions with vehicles (Rivers, 1998; Gomes et al., 2009). The barn owl survey was performed as a part of the project “Conservation of barn owl in sacral buildings in Poland” led by the Wildlife

Univariate models

Barn owl presence was recorded in 778 out of 2768 churches, i.e. 28.1% of all surveyed churches. Generally, the barn owl occurrence was significantly univariately associated with all except two variables considered (Fig. 3A). The barn owl occurrence was associated with low elevation and short snow cover duration. Both type of material and age of the church were correlated with barn owl occurrence: the species preferred old churches over new ones and those made of bricks over those made of wood.

Discussion

Barn owl occurrence in Polish churches was associated not only with landscape, habitat and climate characteristics, but also with church type and age and socio-economy of the local societies. Importantly, some socio-economic factors were still significant predictors of barn owl occurrence when church characteristics, all remaining land-use and climate variables were simultaneously considered. Thus, data on local societies – their age structure and economy – seem to provide additional relevant

Conclusions

The present study shows that spatial distribution pattern of barn owls in Poland correlates with climate, land-use, road density and light pollution, which confirms numerous previous findings. Importantly, the barn owl distribution is also explained by local socio-economy factors: unemployment, the proportion of elder citizens, commune income per citizen, the share of citizens with high education and share of farmers among working population. We, therefore, conclude that social and economic

CRediT authorship contribution statement

Michał Żmihorski:Conceptualization, Methodology, Formal analysis, Writing - original draft, Writing - review & editing, Visualization.Marek Kowalski:Investigation.Jan Cichocki:Investigation.Sławomir Rubacha:Investigation.Dorota Kotowska:Writing - original draft, Visualization.Dominik Krupiński:Investigation.Zuzanna M. Rosin:Writing - original draft.Martin Šálek:Writing - original draft.Tomas Pärt:Conceptualization, Writing - original draft, Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We thank Marcin Bocheński, Paweł Czechowski, Grzegorz Jędro, Andrzej Wąsicki and tens of volunteers for their help in the field work. ZMR was supported by the Ministry of Science and Higher Education of Poland: program “Mobilność Plus” (no. 1654/MOB/V/2017/0), MŠ was supported by the research aim of the Czech Academy of Sciences (RVO 68081766).

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