Distribution of Estimated Stand Age Across Siberian Larch Forests, 1989-2012

Chen, D.; Loboda, Tatiana V.; Krylov, Alexander; Potapov, P.

doi:10.3334/ornldaac/1364

Cited by 3 publications

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“…Distribution of Estimated Stand Age Across Siberian Larch Forests (Chen et al 2017) is related to the former dataset, and is also mainly based on Landsat images with 30m resolution. It incorporates some more analysis to detect stand-replacing forest fires, but it only covers a part of eastern Siberia, including, however, 54 of our vegetation survey plots, and spans the years 1989-2012.…”

Section: Siberian Larch Stand Agementioning

confidence: 99%

Forest structure and individual tree inventories of north-eastern Siberia along climatic gradients

Miesner

Herzschuh

Pestryakova

et al. 2022

Preprint

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Abstract. We compile a data set of forest surveys from expeditions to the north-east of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia) and the Chukotka Autonomous Okrug (59-73° N, 97-169° E). The region is characterized by permafrost soils, and forests dominated by larch (Larix gmelinii RUPR., Larix cajanderi MAYR). Our dataset consists of a plot data base describing 226 georeferenced vegetation survey sites, and of a tree data base with information about all trees on these plots. The tree data base contains information on height, species and vitality of 40,289 trees. A subset of the trees was subject to a more detailed inventory, recording stem diameter at base and at breast height, crown diameter and height of the beginning of the crown. We recorded heights up to 28.5 m (median = 2.5 m) and stand densities up to 120,000 trees per ha (median = 1197 ha−1), both values tending to be higher in the more southerly areas. Observed taxa include Larix MILL., Pinus L., Picea A.DIETR., Abies MILL., Salix L., Betula L., Populus L., Alnus MILL. and Ulmus L.. In this study, we present the forest inventory data aggregated per site. Additionally, we connect it with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of ten species groups, allometries depend also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here. The data can be used for studying the forest structure of north-eastern Siberia, and for the calibration and validation of remotely sensed data.

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Section: Siberian Larch Stand Agementioning

confidence: 99%

Forest structure and individual tree inventories of north-eastern Siberia along climatic gradients

Miesner

Herzschuh

Pestryakova

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The Distribution of Estimated Stand Age Across Siberian Larch Forests (Chen et al, 2017) is related to the former data set and is also mainly based on Landsat images with 30 m resolution. It incorporates some more analysis to detect stand-replacing forest fires, but it only covers a part of eastern Siberia, including 54 of our vegetation survey plots, and spans the years 1989-2012.…”

Section: Siberian Larch Stand Agementioning

confidence: 99%

“…The data set for the Stand Age of Siberian Larch Forests by Chen et al (2017) has data for 54 of our vegetation plots and finds that 6 plots have experienced stand-replacing events between 1989 and 2012. The Hansen et al (2013) data set covers a wider area and different time range.…”

Section: Forest Lossmentioning

confidence: 99%

“…The Hansen et al (2013) data set covers a wider area and different time range. However, there are five plots for which they detect forest loss in times and places where Chen et al (2017) find that the stand age is at maximum. We encountered clear signs of recent disturbance in the vegetation at only 50 % of the plots where either of the data products detected forest loss.…”

Section: Forest Lossmentioning

confidence: 99%

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Forest structure and individual tree inventories of northeastern Siberia along climatic gradients

Miesner

Herzschuh

Pestryakova

et al. 2022

Earth Syst. Sci. Data

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Abstract. We compile a data set of forest surveys from expeditions to the northeast of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia), and the Chukotka Autonomous Okrug (59–73∘ N, 97–169∘ E), performed between the years 2011 and 2021. The region is characterized by permafrost soils and forests dominated by larch (Larix gmelinii Rupr. and Larix cajanderi Mayr). Our data set consists of a plot database describing 226 georeferenced vegetation survey plots and a tree database with information about all the trees on these plots. The tree database, consisting of two tables with the same column names, contains information on the height, species, and vitality of 40 289 trees. A subset of the trees was subject to a more detailed inventory, which recorded the stem diameter at base and at breast height, crown diameter, and height of the beginning of the crown. We recorded heights up to 28.5 m (median 2.5 m) and stand densities up to 120 000 trees per hectare (median 1197 ha−1), with both values tending to be higher in the more southerly areas. Observed taxa include Larix Mill., Pinus L., Picea A. Dietr., Abies Mill., Salix L., Betula L., Populus L., Alnus Mill., and Ulmus L. In this study, we present the forest inventory data aggregated per plot. Additionally, we connect the data with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of 10 species groups, allometries depended also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here. The data can be used for studying the forest structure of northeastern Siberia and for the calibration and validation of remotely sensed data. They are available at https://doi.org/10.1594/PANGAEA.943547 (Miesner et al., 2022).

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Long-Time Interval Satellite Image Analysis on Forest-Cover Changes and Disturbances around Protected Area, Zeya State Nature Reserve, in the Russian Far East

et al. 2021

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Boreal forest areas in the Russian Far East contained very large intact forests. This particular area is considered one of the most productive and diverse forests in the boreal biome of the world, and it is also home to many endangered species. Zeya State Nature Reserve is located at the southern margin of the boreal forest area in the Russian Far East and has rich fauna and flora. However, the forest in the region faced large-scale forest fires and clearcutting for timber recently. The information of disturbances is rarely understood. This study aimed to explore the effects of disturbance and forest dynamics around the reserve. Our study used two-year overlaid Landsat images from Landsat 5 Thematic Mapper (TM) and 8 Operational Land Imager (OLI), to generate forest-cover-change maps of 1988–1999, 1999–2010, and 2010–2016. In this paper, we analyze the direction of forest successional stages, to demonstrate the effectiveness of this protected area in terms of preventing human-based deforestation on the vegetation indices. The vegetation indices included the normalized burn ratio (NBR), the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI). The study provided information on the pattern of forest-cover change and disturbance area around the reserve. The NDWI was used to differentiate between water and non-water areas. The mean values of NBR and NDVI were calculated and determine the forest successional stages between burn, vegetation recovery, grass, mixed forest, oak forest, and birch and larch forest. The accuracy was assessed by using field measurements, field photos, and high-resolution images as references. Overall, our classification results have high accuracy for all three periods. The most disturbed area occurred during 2010–2016. The reserve was highly protected, with no human-disturbance activity. However, large areas from fire disturbance were found (137 km2) during 1999–2010. The findings also show a large area of disturbance, mostly located outside of the reserve. Mixed disturbance increased to almost 50 km2 during 2010–2016, in the buffer zone and outside of the reserve. We recommend future works to apply our methods to other ecosystems, to compare the forest dynamics and disturbance inside and outside the protected area.

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Distribution of Estimated Stand Age Across Siberian Larch Forests, 1989-2012

Cited by 3 publications

References 0 publications

Forest structure and individual tree inventories of north-eastern Siberia along climatic gradients

Forest structure and individual tree inventories of north-eastern Siberia along climatic gradients

Forest structure and individual tree inventories of northeastern Siberia along climatic gradients

Long-Time Interval Satellite Image Analysis on Forest-Cover Changes and Disturbances around Protected Area, Zeya State Nature Reserve, in the Russian Far East

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