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Considering landscape connectivity and gene flow in the Anthropocene using complementary landscape genetics and habitat modelling approaches

  • Peter KlingaEmail author
  • Martin Mikoláš
  • Peter Smolko
  • Martin Tejkal
  • Jacob Höglund
  • Ladislav Paule
Research Article

Abstract

Context

A comprehensive understanding of how rapidly changing environments affect species gene flow is critical for mitigating future biodiversity losses. While recent methodological developments in landscape ecology and genetics have greatly advanced our understanding of biodiversity conservation, they are rarely combined and applied in studies.

Objectives

We merged multifaceted landscape habitat modelling with genetics to detect and design biological corridors, and we evaluated the importance of habitat patches to test corridor efficacy for gene flow in a fragmented landscape. We examined an isolated population of an endangered umbrella species, the capercaillie (Tetrao urogallus), in the Western Carpathians; they have experienced habitat deterioration and accompanying population declines in recent decades.

Methods

To detect spatial patterns of genetic distances, we combined and optimized resistance surfaces using species distribution modelling, structural and functional connectivity analyses, multivariate regression approaches, and Moran’s eigenvector maps at hierarchical scales.

Results

Larger habitat patches had better gene flow among them, and we confirmed a broken metapopulation network characterised by a pattern of isolation by the environment. Distance to human settlements explained landscape genetic patterns better than other environmental and landscape features, MaxEnt resistance, Conefor resistance surfaces, and the pairwise Euclidean distances among individuals. The closer individuals were to settlements, the more pronounced were the effects of logging and other negative factors on their connectivity.

Conclusions

Merging multifaceted landscape habitat modelling with genetics can effectively test corridor efficacy for gene flow, and it represents a powerful tool for conservation of endangered species.

Keywords

Landscape genetics Fragmentation Isolation by environment Conservation Tetrao urogallus 

Notes

Acknowledgements

The authors wish to express thanks to numerous colleagues who assisted us with sampling, in particular F. Zięba and P. Krzan from Tatra National Park (Zakopane, Poland), P. Armatys from Górce National Park (Niedźwiedź, Poland), and conservationists, foresters, and volunteers from Slovakia. We are grateful to G. Baloghová and D. Krajmerová for assistance in the laboratory. The work was financially supported by the VEGA - Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic and Slovak Academy of Sciences [Grant Number 1/0303/12] and VEGA [Grant Number 2/0077/17]. M. Mikoláš was supported by the Czech University of Life Sciences, Prague (CIGA No. 20184304) and by the Institutional Project MSMT CZ.02.1.01/0.0/0.0/16_019/0000803. We are also grateful to Rob Morrissey (Branch Scientific Editing) for help with the language to strengthen our manuscript.

Supplementary material

10980_2019_789_MOESM1_ESM.docx (2.5 mb)
Supplementary material 1 (DOCX 2559 kb)

References

  1. Aavik T, Holderegger R, Bolliger J (2014) The structural and functional connectivity of the grassland plant Lychnis flos-cuculi. Heredity 112:471–478CrossRefPubMedGoogle Scholar
  2. Adams RV, Lazerte SE, Otter KA, Burg TM (2016) Influence of landscape features on the microgeographic genetic structure of a resident songbird. Heredity 117:63–72CrossRefPubMedPubMedCentralGoogle Scholar
  3. Anderson DR, Burnham KP (2002) Avoiding pitfalls when using information-theoretic methods. J Wildl Manage 66:912–918CrossRefGoogle Scholar
  4. Bálint M, Ujvárosi L, Theissinger K, Lehrian S, Mészáros N, Pauls SU (2011) The Carpathians as a major diversity hotspot in Europe. In: Habel JC, Zachos FE (eds) Biodiversity hotspots. Springer, Berlin, pp 189–205CrossRefGoogle Scholar
  5. Bates D, Mächler M, Bolker B, Walker S (2015) fitting linear mixed-effects models using lme4. J Stat Softw 67:1–48CrossRefGoogle Scholar
  6. Bodenhofer U, Klawonn F (2008) Robust rank correlation coefficients on the basis of fuzzy orderings: initial steps. Mathware Soft Comput 15:5–20Google Scholar
  7. Bodenhofer U, Krone M, Klawonn F (2013) Testing noisy numerical data for monotonic association. Inf Sci 245:21–37CrossRefGoogle Scholar
  8. Bollmann K, Weibel P, Graf RF (2005) An analysis of central Alpine capercaillie spring habitat at the forest stand scale. For Ecol Manage 215:307–318CrossRefGoogle Scholar
  9. Bollmann K, Graf RF, Suter W (2011) Quantitative predictions for patch occupancy of capercaillie in fragmented habitats. Ecography 34:276–286CrossRefGoogle Scholar
  10. Braunisch V, Segelbacher G, Hirzel AH (2010) Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach. Mol Ecol 19:3664–3678CrossRefPubMedGoogle Scholar
  11. Braunisch V, Coppes J, Arlettaz R, Suchant R, Zellweger F, Bollmann K (2014) Temperate mountain forest biodiversity under climate change: compensating negative effects by increasing structural complexity. PLoS ONE 9:e97718CrossRefPubMedPubMedCentralGoogle Scholar
  12. Broeck AV, Maes D, Kelager A, Wynhoff I, WallisDeVries MF, Nash DR, Oostermeijer JG, Van Dyck H, Mergeay J (2017) Gene flow and effective population sizes of the butterfly Maculinea alcon in a highly fragmented, anthropogenic landscape. Biol Conserv 209:89–97CrossRefGoogle Scholar
  13. Coppes J, Nopp-Mayr U, Grünschachner-Berger V, Storch I, Suchant R, Braunisch V (2018) Habitat suitability modulates the response of wildlife to human recreation. Biol Conserv 227:56–64CrossRefGoogle Scholar
  14. Demographic Research Centre (2017) Main demographic data. http://www.infostat.sk/vdc/en/index.php?option=com_wrapper&view=wrapper&Itemid=35. Accessed 28 Dec 2017
  15. Di Minin E, Hunter LTB, Balme GA, Smith RJ, Goodman PS, Slotow R (2013) Creating larger and better connected protected areas enhances the persistence of big game species in the Maputaland–Pondoland–Albany biodiversity hotspot. PLoS ONE 8:e71788CrossRefPubMedPubMedCentralGoogle Scholar
  16. Doherty TS, Driscoll DA (2018) Coupling movement and landscape ecology for animal conservation in production landscapes. Proc Biol Sci 285:20172272CrossRefPubMedPubMedCentralGoogle Scholar
  17. Dutta T, Sharma S, McRae BH, Roy PS, DeFries R (2016) Connecting the dots: mapping habitat connectivity for tigers in central India. Reg Environ Chang 16:53–67CrossRefGoogle Scholar
  18. Ferianc O (1954) Rozšírenie lesných kúr na Slovensku. [Distribution of Galliformes in Slovakia]. Biológia 9:182–209Google Scholar
  19. Ferraz G, Nichols JD, Hines JE, Stouffer PC, Bierregaard RO, Lovejoy TE (2007) A large-scale deforestation experiment: effects of patch area and isolation on Amazon birds. Science 315:238–241CrossRefPubMedGoogle Scholar
  20. Galpern P, Peres-Neto PR, Polfus J, Manseau M (2014) MEMGENE: spatial pattern detection in genetic distance data. Methods Ecol Evol 5:1116–1120CrossRefGoogle Scholar
  21. Graf RF, Kramer-Schadt S, Fernández N, Grimm V (2007) What you see is where you go? Modelling dispersal in mountainous landscapes. Landscape Ecol 22:853–866CrossRefGoogle Scholar
  22. Guillot G, Rousset F (2013) Dismantling the Mantel tests. Methods Ecol Evol 4:336–344CrossRefGoogle Scholar
  23. Hanski I, Ovaskainen O (2002) Extinction debt at extinction threshold. Conserv Biol 16:666–673CrossRefGoogle Scholar
  24. Harrisson KA, Pavlova A, Amos JN, Takeuchi N, Lill A, Radford JQ, Sunnucks P (2012) Fine-scale effects of habitat loss and fragmentation despite large-scale gene flow for some regionally declining woodland bird species. Landscape Ecol 27:813–827CrossRefGoogle Scholar
  25. Hedrick PW (2005) A standardized genetic differentiation measure. Evolution 59:1633–1638CrossRefPubMedGoogle Scholar
  26. Jost L (2008) GST and its relatives do not measure differentiation. Mol Ecol 17:4015–4026CrossRefPubMedGoogle Scholar
  27. Klinga P, Mikoláš M, Zhelev P, Höglund J, Paule L (2015) Genetic differentiation of western capercaillie in the Carpathian Mountains: the importance of post glacial expansions and habitat connectivity. Biol J Linn Soc 116:873–889CrossRefGoogle Scholar
  28. Klinga P, Smolko P, Krajmerová D, Paule L (2017) Landscape genetics highlight the importance of sustainable management in European mountain spruce forests: a case study on Western capercaillie. Eur J For Res 136:1041–1050CrossRefGoogle Scholar
  29. Kormann U, Gugerli F, Ray N, Excoffier L, Bollmann K (2012) Parsimony-based pedigree analysis and individual-based landscape genetics suggest topography to restrict dispersal and connectivity in the endangered capercaillie. Biol Conserv 152:241–252CrossRefGoogle Scholar
  30. Legendre P, Fortin MJ, Borcard D (2015) Should the Mantel test be used in spatial analysis? Methods Ecol Evol 6:1239–1247CrossRefGoogle Scholar
  31. Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. Trends Ecol Evol 18:189–197CrossRefGoogle Scholar
  32. Manicacci D, Olivieri I, Perrot V, Atlan A, Gouyon P-H, Prosperi J-M, Couvet D (1992) Landscape ecology: population genetics at the metapopulation level. Landscape Ecol 6:147–159CrossRefGoogle Scholar
  33. McRae BH, Kavanagh DM (2011) Linkage Mapper Connectivity Analysis Software. Seattle, WA: the nature conservancy. Comput Softw Progr Prod by Nat Conserv Seattle, WA, USA https://www.circuitscapeorg/linkagemapper Accessed 16 April 2016
  34. McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724CrossRefPubMedGoogle Scholar
  35. McRae BH, Hall SA, Beier P, Theobald DM (2012) Where to restore ecological connectivity? Detecting barriers and quantifying restoration benefits. PLoS ONE 7:e52604CrossRefPubMedPubMedCentralGoogle Scholar
  36. Meirmans PG, Hedrick PW (2011) Assessing population structure: F ST and related measures. Mol Ecol Resour 11:5–18CrossRefPubMedGoogle Scholar
  37. Mikoláš M, Svitok M, Tejkal M, Leitão PJ, Morrissey RC, Svoboda M, Seedre M, Fontaine JB (2015) Evaluating forest management intensity on an umbrella species: Capercaillie persistence in central Europe. For Ecol Manage 354:26–34CrossRefGoogle Scholar
  38. Mikoláš M, Svitok M, Bollmann K, Reif J, Bače R, Janda P, Trotsiuk V, Čada V, Vítková L, Teodosiu M, Coppes J, Schurman JS, Morrissey RC, Mrhalová H, Svoboda M (2017a) Mixed-severity natural disturbances promote the occurrence of an endangered umbrella species in primary forests. For Ecol Manage 405:210–218CrossRefGoogle Scholar
  39. Mikoláš M, Tejkal M, Kuemmerle T, Griffiths P, Svoboda M, Hlásny T, Leitão PJ, Morrissey RC (2017b) Forest management impacts on capercaillie (Tetrao urogallus) habitat distribution and connectivity in the Carpathians. Landscape Ecol 32:163–179CrossRefGoogle Scholar
  40. Mondol S, Bruford MW, Ramakrishnan U (2013) Demographic loss, genetic structure and the conservation implications for Indian tigers. Proc R Soc B Biol Sci 280:20130496CrossRefGoogle Scholar
  41. Nagel TA, Firm D, Pisek R, Mihelic T, Hladnik D, de Groot M, Rozenbergar D (2017) Evaluating the influence of integrative forest management on old-growth habitat structures in a temperate forest region. Biol Conserv 216:101–107CrossRefGoogle Scholar
  42. Olah G, Smith AL, Asner GP, Brightsmith DJ, Heinsohn RG, Peakall R (2017) Exploring dispersal barriers using landscape genetic resistance modelling in scarlet macaws of the Peruvian Amazon. Landscape Ecol 32:445–456CrossRefGoogle Scholar
  43. Oliveira EF, Martinez PA, São-Pedro VA, Gehara M, Burbrink FT, Mesquita DO, Garda AA, Colli GR, Costa GC (2017) Climatic suitability, isolation by distance and river resistance explain genetic variation in a Brazilian whiptail lizard. Heredity 120:251–265CrossRefPubMedGoogle Scholar
  44. Pakkala T, Pellikka J, Lindén H (2003) Capercaillie Tetrao urogallus—a good candidate for an umbrella species in taiga forests. Wildlife Biol 9:309–316CrossRefGoogle Scholar
  45. Pascual-Hortal L, Saura S (2006) Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Landscape Ecol 21:959–967CrossRefGoogle Scholar
  46. Pascual-Hortal L, Saura S (2008) Integrating landscape connectivity in broad-scale forest planning through a new graph-based habitat availability methodology: application to capercaillie (Tetrao urogallus) in Catalonia (NE Spain). Eur J For Res 127:23–31CrossRefGoogle Scholar
  47. Peterman WE, Ousterhout BH, Anderson TL, Drake DL, Semlitsch RD, Eggert LS (2016) Assessing modularity in genetic networks to manage spatially structured metapopulations. Ecosphere 7:1–16CrossRefGoogle Scholar
  48. Phillips SJ, Dudík M, Schapire RE (2004) A maximum entropy approach to species distribution modeling. Twenty-first Int Conf Mach Learn – ICML’04 83.  https://doi.org/10.1145/1015330.1015412
  49. Pisa G, Orioli V, Spilotros G, Fabbri E, Randi E, Bani L (2015) Detecting a hierarchical genetic population structure: the case study of the fire salamander (Salamandra salamandra) in Northern Italy. Ecol Evol 5:743–758CrossRefPubMedPubMedCentralGoogle Scholar
  50. Richardson JL, Brady SP, Wang IJ, Spear SF (2016) Navigating the pitfalls and promise of landscape genetics. Mol Ecol 25:849–863CrossRefPubMedGoogle Scholar
  51. Rösner S, Mussard-Forster E, Lorenc T, Müller J (2014) Recreation shapes a “landscape of fear” for a threatened forest bird species in Central Europe. Landscape Ecol 29:55–66CrossRefGoogle Scholar
  52. Sabatini FM, Burrascano S, Keeton WS, Levers C, Lindner M, Pötzschner F, Verkerk PJ, Bauhus J, Buchwald E, Chaskovsky O, Debaive N, Horváth F, Garbarino M, Grigoriadis N, Lombardi F, Duarte IM, Meyer P, Midteng R, Mikac S, Mikoláš M, Motta R, Mozgeris G, Nunes L, Panayotov M, Ódor P, Ruete A, Simovski B, Stillhard J, Svoboda M, Szwagrzyk J, Tikkanen O-P, Volosyanchuk R, Vrska T, Zlatanov T, Kuemmerle T (2018) Where are Europe’s last primary forests? Divers Distrib 24:1426–1439CrossRefGoogle Scholar
  53. Saura S, Pascual-Hortal L (2007) A new habitat availability index to integrate connectivity in landscape conservation planning: comparison with existing indices and application to a case study. Landsc Urban Plan 83:91–103CrossRefGoogle Scholar
  54. Saura S, Torné J (2009) Conefor Sensinode 2.2: a software package for quantifying the importance of habitat patches for landscape connectivity. Environ Model Softw 24:135–139CrossRefGoogle Scholar
  55. Segelbacher G, Storch I, Tomiuk J (2003) Genetic evidence of capercaillie Tetrao urogallus dispersal sources and sinks in the Alps. Wildlife Biol 9:267–273CrossRefGoogle Scholar
  56. Segelbacher G, Manel S, Tomiuk J (2008) Temporal and spatial analyses disclose consequences of habitat fragmentation on the genetic diversity in capercaillie (Tetrao urogallus). Mol Ecol 17:2356–2367CrossRefPubMedGoogle Scholar
  57. Sexton JP, Hangartner SB, Hoffmann AA (2013) Genetic isolation by environment or distance: which pattern of gene flow is most common? Evolution 68:1–15CrossRefPubMedGoogle Scholar
  58. Steven R, Castley JG (2013) Tourism as a threat to critically endangered and endangered birds: global patterns and trends in conservation hotspots. Biodivers Conserv 22:1063–1082CrossRefGoogle Scholar
  59. Straka M, Paule L, Ionescu O, Štofík J, Adamec M (2012) Microsatellite diversity and structure of Carpathian brown bears (Ursus arctos): consequences of human caused fragmentation. Conserv Genet 13:153–164CrossRefGoogle Scholar
  60. Suter W, Graf RF, Hess R (2002) Capercaillie (Tetrao urogallus) and avian biodiversity: testing the umbrella-species concept. Conserv Biol 16:778–788CrossRefGoogle Scholar
  61. Thompson PL, Rayfield B, Gonzalez A (2014) Robustness of the spatial insurance effects of biodiversity to habitat loss. Evol Ecol Res 16:445–460Google Scholar
  62. Titus VR, Bell RC, Becker CG, Zamudio KR (2014) Connectivity and gene flow among Eastern tiger salamander (Ambystoma tigrinum) populations in highly modified anthropogenic landscapes. Conserv Genet 15:1447–1462CrossRefGoogle Scholar
  63. van Strien MJ, Holderegger R, Van Heck HJ (2015) Isolation-by-distance in landscapes: considerations for landscape genetics. Heredity 114:27–37CrossRefPubMedGoogle Scholar
  64. Wang W, Qiao Y, Li S, Pan W, Yao M (2017) Low genetic diversity and strong population structure shaped by anthropogenic habitat fragmentation in a critically endangered primate, Trachypithecus leucocephalus. Heredity 118:542–553CrossRefPubMedPubMedCentralGoogle Scholar
  65. Wegge P, Kastdalen L (2007) Pattern and causes of natural mortality of capercaille, Tetrao urogallus, chicks in a fragmented boreal forest. Ann Zool Fenn 44:141–151Google Scholar
  66. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358PubMedGoogle Scholar
  67. Wielstra B (2015) The crested newt Triturus cristatus recolonized temperate Eurasia from an extra-Mediterranean glacial refugium. Biol J Linn Soc 114:574–587CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Faculty of ForestryTechnical University in ZvolenZvolenSlovakia
  2. 2.Faculty of Forestry and Wood SciencesCzech University of Life SciencesPraha 6 – SuchdolCzech Republic
  3. 3.PRALESRosinaSlovakia
  4. 4.DIANABanská BystricaSlovakia
  5. 5.Department of Ecology and Genetics, Evolutionary Biology CentreUppsala UniversityUppsalaSweden
  6. 6.Department of Biological SciencesUniversity of AlbertaEdmontonCanada

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