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Climatic Change

, Volume 140, Issue 3–4, pp 549–562 | Cite as

The sea level rise impact on four seashore breeding birds: the key study of Sečovlje Salina Nature Park

  • Danijel IvajnšičEmail author
  • Lovrenc Lipej
  • Iztok Škornik
  • Mitja Kaligarič
Article
First Online:

Abstract

Climate change is expected to result in an acceleration of current rates of sea level rise, inundating many low-lying coastal and intertidal landscapes. This could have important implications for many coastal habitat types and related organisms that depend on these habitats, including shorebirds that rely on them for feeding, overwintering and breeding. Potential change in the availability of suitable breeding area according to linear and model-based sea level rise scenarios was modeled for four breeding birds (Kentish Plover, Little Tern, Common Tern and Black-winged Stilt) in Sečovlje Salina Nature Park, based on precise mapping of nests over a period of 10 years and on present environmental predictors. Different breeding niches for the studied bird species in SSNP were identified, which indirectly indicates different responses to environmental change, in this case triggered by climate change induced sea level rise. Future breeding suitability maps indicate that the Little Tern and the Common Tern could potentially face a drastic decrease of adequate breeding grounds in SSNP later than the Kentish Plover and the Black-winged Stilt. However, these individual species responses to sea level rise, as a climate change driver, is a step forward for conservation biologists and landscape planners in protected areas, as they prepare cost-effective plans for mitigating negative impact on these ecosystems. This study also illustrates an important general point about the likely effects of climate change on ecological resources, which is that climate change does not happen in a vacuum; its impact will interact with pre-existing stress factors.

Keywords

Normalize Difference Vegetation Index Digital Elevation Model Bird Species Bird Breeding Environmental Predictor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Danijel Ivajnšič
    • 1
    Email author
  • Lovrenc Lipej
    • 3
  • Iztok Škornik
    • 4
  • Mitja Kaligarič
    • 1
    • 2
  1. 1.Faculty of Natural Sciences and MathematicsUniversity of MariborMariborSlovenia
  2. 2.Faculty of Agriculture and Life SciencesUniversity of MariborHočeSlovenia
  3. 3.National Institute of Biology, Marine Biology StationPiranSlovenia
  4. 4.Sečovlje Salina Nature Park, Soline Pridelava Soli d.o.o.PortorožSlovenia

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