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

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 distribu...

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Autores principales: Virkkala, Raimo, Leikola, Niko, Kujala, Heini, Kivinen, Sonja, Hurskainen, Pekka, Kuusela, Saija, Valkama, Jari, Heikkinen, Risto K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285730/
https://www.ncbi.nlm.nih.gov/pubmed/34866270
http://dx.doi.org/10.1002/eap.2505
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author Virkkala, Raimo
Leikola, Niko
Kujala, Heini
Kivinen, Sonja
Hurskainen, Pekka
Kuusela, Saija
Valkama, Jari
Heikkinen, Risto K.
author_facet Virkkala, Raimo
Leikola, Niko
Kujala, Heini
Kivinen, Sonja
Hurskainen, Pekka
Kuusela, Saija
Valkama, Jari
Heikkinen, Risto K.
author_sort Virkkala, Raimo
collection PubMed
description 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.
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spelling pubmed-92857302022-07-18 Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species Virkkala, Raimo Leikola, Niko Kujala, Heini Kivinen, Sonja Hurskainen, Pekka Kuusela, Saija Valkama, Jari Heikkinen, Risto K. Ecol Appl Articles 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. John Wiley & Sons, Inc. 2022-01-28 2022-03 /pmc/articles/PMC9285730/ /pubmed/34866270 http://dx.doi.org/10.1002/eap.2505 Text en © 2021 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Articles
Virkkala, Raimo
Leikola, Niko
Kujala, Heini
Kivinen, Sonja
Hurskainen, Pekka
Kuusela, Saija
Valkama, Jari
Heikkinen, Risto K.
Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
title Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
title_full Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
title_fullStr Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
title_full_unstemmed Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
title_short Developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
title_sort developing fine‐grained nationwide predictions of valuable forests using biodiversity indicator bird species
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285730/
https://www.ncbi.nlm.nih.gov/pubmed/34866270
http://dx.doi.org/10.1002/eap.2505
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