An index for tracking old-growth value in disturbance-prone forest landscapes

Forests in their later stages of development attain attributes that support biodiversity and provide a variety of ecological benefits (e.g. clean water and carbon storage). Despite their values, old-growth forests are declining worldwide in part due to anthropogenic pressures. A persistent challenge...

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Autores principales:	Luizmar de Assis Barros, Ché Elkin
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Community forest Conservation Ecosystem service Old-growth management area (OGMA) Aerial Laser scanning (ALS, LiDAR) Remote sensing Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/1e6a25a2b98643edaeacada52b43205e
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id	oai:doaj.org-article:1e6a25a2b98643edaeacada52b43205e
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spelling	oai:doaj.org-article:1e6a25a2b98643edaeacada52b43205e2021-12-01T04:37:27ZAn index for tracking old-growth value in disturbance-prone forest landscapes1470-160X10.1016/j.ecolind.2020.107175https://doaj.org/article/1e6a25a2b98643edaeacada52b43205e2021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20311146https://doaj.org/toc/1470-160XForests in their later stages of development attain attributes that support biodiversity and provide a variety of ecological benefits (e.g. clean water and carbon storage). Despite their values, old-growth forests are declining worldwide in part due to anthropogenic pressures. A persistent challenge to managing and conserving old-growth forest has been establishing a reliable method for measuring old-growth values across large landscapes at an appropriately fine ecological and spatial scale. Using data from a community-managed forest in central British Columbia, Canada, an Aerial Laser Scanning (ALS) based metric was developed, using a random forest modeling framework, to predict an old-growth index across the forest. Using this old-growth index, we estimated that forests with “Very-high” old-growth values cover 14.7% of the study area (18,183.2 ha), and that only 25% (4,545.9 ha) of this “very-high” old growth value areas are current inside designated old-growth management areas (OGMAs). Additionally, the forests with “very-high” old-growth values that are currently inside OGMAs are fragmented, as only 1 out of 40 OGMAs have more than 50% of its area covered by forests with “Very-high” old-growth value. This research provides a clear ecological indicator that uses fine-scale remotely sensed data to measure old-growth and assess its conservation status within reserves. While the index developed is specific to the study site, the framework, is generic enough to be adapted to other forest types and ecosystems. More importantly, the identification of the amount and location of old-growth forests over the landscape can aid in the management and conservation of this rare resource and its services.Luizmar de Assis BarrosChé ElkinElsevierarticleCommunity forestConservationEcosystem serviceOld-growth management area (OGMA)Aerial Laser scanning (ALS, LiDAR)Remote sensingEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107175- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Community forest Conservation Ecosystem service Old-growth management area (OGMA) Aerial Laser scanning (ALS, LiDAR) Remote sensing Ecology QH540-549.5
spellingShingle	Community forest Conservation Ecosystem service Old-growth management area (OGMA) Aerial Laser scanning (ALS, LiDAR) Remote sensing Ecology QH540-549.5 Luizmar de Assis Barros Ché Elkin An index for tracking old-growth value in disturbance-prone forest landscapes
description	Forests in their later stages of development attain attributes that support biodiversity and provide a variety of ecological benefits (e.g. clean water and carbon storage). Despite their values, old-growth forests are declining worldwide in part due to anthropogenic pressures. A persistent challenge to managing and conserving old-growth forest has been establishing a reliable method for measuring old-growth values across large landscapes at an appropriately fine ecological and spatial scale. Using data from a community-managed forest in central British Columbia, Canada, an Aerial Laser Scanning (ALS) based metric was developed, using a random forest modeling framework, to predict an old-growth index across the forest. Using this old-growth index, we estimated that forests with “Very-high” old-growth values cover 14.7% of the study area (18,183.2 ha), and that only 25% (4,545.9 ha) of this “very-high” old growth value areas are current inside designated old-growth management areas (OGMAs). Additionally, the forests with “very-high” old-growth values that are currently inside OGMAs are fragmented, as only 1 out of 40 OGMAs have more than 50% of its area covered by forests with “Very-high” old-growth value. This research provides a clear ecological indicator that uses fine-scale remotely sensed data to measure old-growth and assess its conservation status within reserves. While the index developed is specific to the study site, the framework, is generic enough to be adapted to other forest types and ecosystems. More importantly, the identification of the amount and location of old-growth forests over the landscape can aid in the management and conservation of this rare resource and its services.
format	article
author	Luizmar de Assis Barros Ché Elkin
author_facet	Luizmar de Assis Barros Ché Elkin
author_sort	Luizmar de Assis Barros
title	An index for tracking old-growth value in disturbance-prone forest landscapes
title_short	An index for tracking old-growth value in disturbance-prone forest landscapes
title_full	An index for tracking old-growth value in disturbance-prone forest landscapes
title_fullStr	An index for tracking old-growth value in disturbance-prone forest landscapes
title_full_unstemmed	An index for tracking old-growth value in disturbance-prone forest landscapes
title_sort	index for tracking old-growth value in disturbance-prone forest landscapes
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/1e6a25a2b98643edaeacada52b43205e
work_keys_str_mv	AT luizmardeassisbarros anindexfortrackingoldgrowthvalueindisturbanceproneforestlandscapes AT cheelkin anindexfortrackingoldgrowthvalueindisturbanceproneforestlandscapes AT luizmardeassisbarros indexfortrackingoldgrowthvalueindisturbanceproneforestlandscapes AT cheelkin indexfortrackingoldgrowthvalueindisturbanceproneforestlandscapes
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An index for tracking old-growth value in disturbance-prone forest landscapes

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