Evidence map›Paper›PMID 34866270›Full record

ArticleEcological applications : a publication of the Ecological Society of America2022

Developing fine-grained nationwide predictions of valuable forests using biodiversity indicator bird species.

Raimo Virkkala, Niko Leikola, Heini Kujala, Sonja Kivinen, Pekka Hurskainen, Saija Kuusela, Jari Valkama, Risto K Heikkinen

Abstract read
In one paragraph

Article in Ecological applications : a publication of the Ecological Society of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  4. Reeve's Muntjac (Animals : an open access journal from MDPI · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
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  10. Article
  11. Developing fine-grained nationwide predictions of valuable forests using biodiversity indicator bird species.Ecological applications : a publication of the Ecological Society of America · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Raimo VirkkalaFinnish Environment Institute, Biodiversity Centre, Helsinki, Finland.
Niko LeikolaFinnish Environment Institute, Biodiversity Centre, Helsinki, Finland.
Heini KujalaFinnish Museum of Natural History, University of Helsinki, Helsinki, Finland.
Sonja KivinenFinnish Environment Institute, Biodiversity Centre, Helsinki, Finland.
Pekka HurskainenFinnish Environment Institute, Biodiversity Centre, Helsinki, Finland.
Saija KuuselaFinnish Environment Institute, Biodiversity Centre, Helsinki, Finland.
Jari ValkamaFinnish Museum of Natural History, University of Helsinki, Helsinki, Finland.
Risto K HeikkinenFinnish Environment Institute, Biodiversity Centre, Helsinki, Finland.ORCID 0000-0003-4190-5108

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of indicator species in forest conservation and management planning can facilitate enhanced preservation of biodiversity from the negative effects of forestry and other uses of land. However, this requires detailed and spatially comprehensive knowledge of the habitat preferences and distributions of selected focal indicator species. Unfortunately, due to limited resources for field surveys, only a small proportion of the occurrences of focal species is usually known. This shortcoming can be circumvented by using modeling techniques to predict the spatial distribution of suitable sites for the target species. Airborne laser scanning (ALS) and other remote sensing (RS) techniques have the potential to provide useful environmental data covering systematically large areas for these purposes. Here, we focused on six bird of prey and woodpecker species known to be good indicators of boreal forest biodiversity values. We used known nest sites of the six indicator species based on nestling ringing records. Thus, the most suitable nesting sites of these species provide important information for biodiversity-friendly forest management and conservation planning. We developed fine-grained, that is, 96 × 96 m grid cell resolution, predictive maps across the whole of Finland of the suitable nesting habitats based on ALS and other RS data and spatial information on the distribution of important forest stands for the six studied biodiversity indicator bird species based on nesting-habitat suitability modeling, that is, the MaxEnt model. Habitat preferences of the study species, as determined by MaxEnt, were in line with the previous knowledge of species-habitat relations. The proportion of suitable habitats of these species in protected areas (PAs) was considerable, but our analysis also revealed many potentially high-quality forest stands outside PAs. However, many of these sites are increasingly threatened by logging because of increased pressures for using forests for bioeconomy and forest industry based on National Forest Strategy. Predicting habitat suitability based on information on the nest sites of indicator species provides a new tool for systematic conservation planning over large areas in boreal forests in Europe, and a corresponding approach would also be feasible and recommendable elsewhere where similar data are available.

Indexed as

Conservation of Natural ResourcesForestsAnimalsBiodiversityBirdsEcosystemForestrybiodiversity indicatorbird speciesborealforest conservation and managementhabitat suitabilitynest sitepredictingspecies distribution modelingsystematic conservation planning

Identifiers

PMID34866270
PMCPMC9285730

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.