Landscape Ecology

, Volume 30, Issue 3, pp 501–516 | Cite as

How to integrate remotely sensed data and biodiversity for ecosystem assessments at landscape scale

  • Petteri Vihervaara
  • Laura Mononen
  • Ari-Pekka Auvinen
  • Raimo Virkkala
  • Yihe Lü
  • Inka Pippuri
  • Petteri Packalen
  • Ruben Valbuena
  • Jari Valkama
Research Article

Abstract

Context

Biodiversity and ecosystem functioning underpins the delivery of all ecosystem services and should be accounted for in all decision-making related to the use of natural resources and areas. However, biodiversity and ecosystem services are often inadequately accounted for in land use management decisions.

Objective

We studied a boreal forest ecosystem by linking citizen-science bird data with detailed information on forest characteristics from airborne laser scanning (ALS). In this paper, we describe this method, and evaluate how similar kinds of biological data sets combined with remote sensing can be used for ecosystem assessments at landscape scale.

Methods

We analysed data for 41 boreal forest bird species and for 14 structural ALS-based forest parameters.

Results

The results support the use of the selected method as a basis for quantifying spatially-explicit biodiversity indicators for ecosystem assessments, while suggestions for improvements are also reported. Finally, we evaluate the capacity of those indicators to describe biodiversity-ecosystem service relationships, for example with carbon trade-offs. The results showed clear distinctions between the different species as measured, for example, by above-ground forest biomass at the observation sites. We also assess how the available data sources can be developed to be compatible with the concept of essential biodiversity variables (EBV), which has been put forward as a solution to cover the most important aspects of biodiversity and ecosystem functioning.

Conclusions

We suggest that EBVs should be integrated into environmental monitoring programmes in the future, and citizen science and remote sensing methods need to be an important part of them.

Keywords

Ecosystem service Habitat LiDAR Essential biodiversity variable Citizen science Forest 

Supplementary material

10980_2014_137_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 17 kb)
10980_2014_137_MOESM2_ESM.docx (242 kb)
Supplementary material 2 (DOCX 242 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Petteri Vihervaara
    • 1
  • Laura Mononen
    • 1
    • 2
  • Ari-Pekka Auvinen
    • 1
  • Raimo Virkkala
    • 1
  • Yihe Lü
    • 3
  • Inka Pippuri
    • 4
  • Petteri Packalen
    • 4
  • Ruben Valbuena
    • 4
  • Jari Valkama
    • 5
  1. 1.Finnish Environment Institute (SYKE)HelsinkiFinland
  2. 2.Department of Geographical and Historical StudiesUniversity of Eastern Finland (UEF)JoensuuFinland
  3. 3.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences (RCEES)Chinese Academy of SciencesBeijingChina
  4. 4.School of Forest SciencesUniversity of Eastern Finland (UEF)JoensuuFinland
  5. 5.Finnish Museum of Natural History (FMNH), Zoological Museum, Monitoring CentreUniversity of HelsinkiHelsinkiFinland

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