Disentangling the effects of host resources, local, and landscape variables on the occurrence pattern of the dusky large blue butterfly (Phengaris nausithous) in upland grasslands
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Determining the effects of local and landscape drivers on endangered species and predicting potential suitable habitats for their persistence is crucial for effective conservation management. Here, we applied a multi-scale approach to disentangle the effects of host resources, local, and landscape variables on the occurrence pattern of Phengaris (= Maculinea) nausithous in semi-natural upland grasslands. Our approach comprised the assessment of host parameters (plant cover, density, height, flower heads density, ant nest density, ant colony size), local grassland management (pasture, meadow), site conditions (area, shape, terrain attributes), and landscape variables (landscape composition, connectivity). We used ensemble of small models based on bivariate generalized linear models for explaining and predicting the butterfly occurrence pattern. Bivariate models revealed that host ant nest density, plant cover and height, local grassland management type (pasture), slope and eastness, landscape forest cover and grassland connectivity had a positive effect on the occurrence of P. nausithous (average explained deviance 20.5%). Host ant density, host plant cover, and local grassland management were the most influential factors on the ensemble predictions. The presence of P. nausithous in upland grasslands is not only determined by host resources, but also by local and landscape factors. Such factors proved to be relevant for identifying and predicting suitable grassland sites for this endangered species. Consequently, we recommend that conservation actions should include a landscape perspective to promote connectivity by facilitating coherent grazing networks enabling dispersal between semi-natural upland grasslands and thus species persistence.
KeywordsButterfly conservation Connectivity Ensemble of small models Grazing Land use Site occupancy
We are grateful to Katja Steininger, Ute Petersen, Elke Tietz, Maren Darnauer, Gerd Kuna, and the land owners for their assistance in carrying out the fieldwork. We also thank Stefan Mecke, Antonia Ortmann, Clara van Waveren and Jan Thiele for their support with GIS analysis and valuable comments on the R appendix. Finally, the authors are grateful to Piotr Nowicki, Josef Settele and an anonymous reviewer for their constructive comments on an earlier draft which improved the manuscript considerably. This study was funded by a research Grant (Grant No. 91563454) from the German Academic Exchange Service (Deutscher Akademischer Austauschdienst, DAAD) to Antonio J. Pérez-Sánchez.
This study was funded by a research Grant (Grant No. 91563454) from the German Academic Exchange Service (Deutscher Akademischer Austauschdienst, DAAD) to Antonio J. Pérez-Sánchez.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Research involving human participants and/or animals
No specimens of P. nausithous or S. officinalis were collected in accordance with the Habitats Directive (Annex II + IV) and Bern Convention (Annex II) conservation actions, and standard methods were followed for ant data collection.
- Anton C, Musche M, Hula V, Settele J (2005) Which factors determine the population density of the predatory butterfly Maculinea nausithous? In: Settele J, Kühn E, Thomas J (eds) Studies on the ecology and conservation of European, butterflies in Europe. Species ecology along a gradient: Maculinea butterflies as a model, vol 2. Pensoft, Sofia, pp 57–59Google Scholar
- Beukema W, Martel A, Nguyen TT et al (2018) Environmental context and differences between native and invasive observed niches of Batrachochytrium salamandrivorans affect invasion risk assessments in the Western Palearctic. Divers Distrib 24:1788–1801. https://doi.org/10.1111/ddi.12795 CrossRefGoogle Scholar
- Broennimann O, Di Cola V, Guisan A (2018) ecospat: spatial ecology miscellaneous methods. R package version 3.0. https://cran.r-project.org/package=ecospat
- Dauber J, Wolters V (2004) Edge effects on ant community structure and species richness in an agricultural landscape. Biodivers Conserv 13:901–915. https://doi.org/10.1023/B:BIOC.0000014460.65462.2b CrossRefGoogle Scholar
- Della Rocca F, Bogliani G, Milanesi P (2017) Patterns of distribution and landscape connectivity of the stag beetle in a human-dominated landscape. Nat Conserv 19:19–37. https://doi.org/10.3897/natureconservation.19.12457 CrossRefGoogle Scholar
- Deutscher Wetterdienst (2017) Deutsche Klimaatlas, Klima und Welt, Thuringia. https://www.dwd.de/DE/klimaumwelt/klimaatlas/klimaatlas_node.html. Accessed 26 Apr 2019
- Kempe C, Nowicki P, Harpke A et al (2016) The importance of resource distribution: spatial co-occurrence of host plants and host ants coincides with increased egg densities of the Dusky Large Blue Maculinea nausithous (Lepidoptera: Lycaenidae). J Insect Conserv 20:1033–1045. https://doi.org/10.1007/s10841-016-9937-z CrossRefGoogle Scholar
- Loritz H, Settele J (2005) Effects of human land-use on availability and quality of habitats of the Large Blue butterfly. In: Settele J, Kühn E, Thomas JA (eds) Studies on the ecology and conservation of European, Butterflies in Europe. Species ecology along a gradient: Maculinea butterflies as a model, vol 2. Pensoft, Sofia, pp 225–227Google Scholar
- McRae B, Shah V, Mohapatra T (2013) Circuitscape user guide. Nat Conserv 28Google Scholar
- Moilanen A, Nieminen M (2002) Simple connectivity measures in spatial ecology. Ecology 83:1131–1145. https://doi.org/10.1890/0012-9658(2002)083%5b1131:scmise%5d2.0.co;2 CrossRefGoogle Scholar
- Munguira ML, Martín J (1999) Action plan for Maculinea butterflies in Europe. Nat Environ 97:1–72Google Scholar
- Musche M, Settele J (2005) Patterns of resource allocation and adaptive response to mowing in the plant Sanguisorba officinalis (Rosaceae). In: Settele J, Kühn E, Thomas J (eds) Studies on the ecology and conservation of butterflies in Europe: Species ecology along a European gradient: Maculinea butterflies as a model, vol 2. Pensoft, Sofia, p 228Google Scholar
- Pollard E, Yates TJ (1993) Monitoring butterflies for ecology and conservation. Chapman & Hall, LondonGoogle Scholar
- Schröder B, Richter O (2000) Are habitat models transferable in space and time? Zeitschrift für Ökologie und Naturschutz 8:195–205Google Scholar
- Schröder B, Strauss B, Biedermann R et al (2009) Predictive species distribution modelling in butterflies. In: Settele J, Shreeve TG, Konvicka M, van Dyck H (eds) Ecology of butterflies in Europe, 1st edn. Cambridge University Press, Cambridge, pp 62–78Google Scholar
- Science for Environment Policy, SEP (2017) Agri-environmental schemes: how to enhance the agriculture-environment relationship. Thematic Issue 57. Science Communication Unit, European Commission DG Environment, UWE, Bristol. http://ec.europa.eu/science-environmentpolicy
- Seifert B (2017) The ecology of Central European non-arboreal ants—37 years of a broad-spectrum analysis under permanent taxonomic control. Soil Org 89:1–67Google Scholar
- Seifert B (2018) The ants of Central and North Europe. lutra Verlags- und Vertriebsgesellschaft, Tauer, 408 ppGoogle Scholar
- Settele J, Henle K (2009) Grazing and cutting regimes for old grassland in temperate zones. In: Gherardi F, Corti C, Gualtieri M (eds) Biodiversity conservation and habitat management. Eolss Publishers, Oxford, pp 261–276Google Scholar
- Thuiller W, Georges D, Engler R, Breiner F (2019) biomod2: ensemble platform for species distribution modeling. R package version 3.3-7. https://cran.r-project.org/package=biomod2
- Thüringer Landesanstalt für Umwelt und Geologie, TLUG (2009) Schmetterlinge: Glaucopsyche nausithous. In: Artensteckbriefe Thüringen, pp 1–4Google Scholar
- Vrabec V, Kulma M, Bubová T, Nowicki P (2017) Long-term monitoring of Phengaris (Lepidoptera: Lycaenidae) butterflies in the Přelouč surroundings (Czech Republic): is the waterway construction a serious threat? J Insect Conserv 21:393–400. https://doi.org/10.1007/s10841-017-9982-2 CrossRefGoogle Scholar