A keystone species, European aspen (Populus tremula L.), in boreal forests: Ecological role, knowledge needs and mapping using remote sensing

Sustainable forest management increasingly highlights the maintenance of biological diversity and requires up-to-date information on the occurrence and distribution of key ecological features in forest environments. Different proxy variables indicating species richness and quality of the sites are essential for efficient detecting and monitoring forest biodiversity. European aspen (Populus tremula L.) is a minor deciduous tree species with a high importance in maintaining biodiversity in boreal forests. Large aspen trees host hundreds of species, many of them classified as threatened. However, accurate fine-scale spatial data on aspen occurrence remains scarce and incomprehensive.&#160;We studied detection of aspen using different remote sensing techniques in Evo, southern Finland. Our study area of 83 km2 contains both managed and protected southern boreal forests characterized by Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst), and birch (Betula pendula and pubescens L.), whereas European aspen has a relatively sparse and scattered occurrence in the area. We collected high-resolution airborne hyperspectral and airborne laser scanning data covering the whole study area and ultra-high resolution unmanned aerial vehicle (UAV) data with RGB and multispectral sensors from selected parts of the area. We tested the discrimination of aspen from other species at tree level using different machine learning methods (Support Vector Machines, Random Forest, Gradient Boosting Machine) and deep learning methods (3D convolutional neural networks).&#160;Airborne hyperspectral and lidar data gave excellent results with machine learning and deep learning classification methods The highest classification accuracies for aspen varied between 91-92% (F1-score). The most important wavelengths for discriminating aspen from other species included reflectance bands of red edge range (724&#8211;727 nm) and shortwave infrared (1520&#8211;1564 nm and 1684&#8211;1706 nm) (Viinikka et al. 2020; M&#228;yr&#228; et al 2021). Aspen detection using RGB and multispectral data also gave good results (highest F1-score of aspen = 87%) (Kuzmin et al 2021). Different remote sensing data enabled production of a spatially explicit map of aspen occurrence in the study area. Information on aspen occurrence and abundance can significantly contribute to biodiversity management and conservation efforts in boreal forests. Our results can be further utilized in upscaling efforts aiming at aspen detection over larger geographical areas using satellite images.

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The demographic structure of European aspen (Populus tremula) populations in managed and old-growth boreal forests in eastern Finland

Canadian Journal of Forest Research ◽

10.1139/x06-289 ◽

2007 ◽

Vol 37 (6) ◽

pp. 1070-1081 ◽

Cited By ~ 30

Author(s):

Tarja Latva-Karjanmaa ◽

Reijo Penttilä ◽

Juha Siitonen

Keyword(s):

Protected Areas ◽

Boreal Forests ◽

Large Scale ◽

Populus Tremula ◽

Managed Forests ◽

Mature Trees ◽

Old Growth ◽

European Aspen ◽

Eastern Finland

European aspen ( Populus tremula L.) is a keystone species for biodiversity in boreal forests. However, large aspen have largely been removed from managed forests, whereas regeneration and the long-term persistence of mature trees in protected areas are matters of concern. We recorded the numbers of mature (≥20 cm diameter) aspen in old-growth and managed forests in eastern Finland, based on a large-scale inventory (11 400 ha, 36 000 living and dead trees). In addition, saplings and small aspen trees were surveyed on thirty-six 1 ha sample plots. The average volumes of mature living and dead aspen were 4.0 and 1.3 m3/ha in continuous old-growth forests and 0.2 and 0.6 m3/ha in managed forests, respectively. These results indicate that large aspen trees in managed forests are a legacy of the past, when forest landscapes were less intensively managed. We conclude that the long-term persistence of aspen in protected areas can only be secured by means of restoration measures that create gaps large enough for regeneration to occur. More emphasis should be given to sparing aspen during thinning and to retaining mature aspen during regeneration cutting in managed forests.

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Detection of European Aspen (Populus tremula L.) Based on an Unmanned Aerial Vehicle Approach in Boreal Forests

Remote Sensing ◽

10.3390/rs13091723 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1723

Author(s):

Anton Kuzmin ◽

Lauri Korhonen ◽

Sonja Kivinen ◽

Pekka Hurskainen ◽

Pasi Korpelainen ◽

...

Keyword(s):

Forest Management ◽

Unmanned Aerial Vehicle ◽

Classification Accuracy ◽

Boreal Forests ◽

Populus Tremula ◽

Tree Level ◽

Tree Crown ◽

Individual Tree ◽

European Aspen ◽

Aerial Vehicle

European aspen (Populus tremula L.) is a keystone species for biodiversity of boreal forests. Large-diameter aspens maintain the diversity of hundreds of species, many of which are threatened in Fennoscandia. Due to a low economic value and relatively sparse and scattered occurrence of aspen in boreal forests, there is a lack of information of the spatial and temporal distribution of aspen, which hampers efficient planning and implementation of sustainable forest management practices and conservation efforts. Our objective was to assess identification of European aspen at the individual tree level in a southern boreal forest using high-resolution photogrammetric point cloud (PPC) and multispectral (MSP) orthomosaics acquired with an unmanned aerial vehicle (UAV). The structure-from-motion approach was applied to generate RGB imagery-based PPC to be used for individual tree-crown delineation. Multispectral data were collected using two UAV cameras: Parrot Sequoia and MicaSense RedEdge-M. Tree-crown outlines were obtained from watershed segmentation of PPC data and intersected with multispectral mosaics to extract and calculate spectral metrics for individual trees. We assessed the role of spectral data features extracted from PPC and multispectral mosaics and a combination of it, using a machine learning classifier—Support Vector Machine (SVM) to perform two different classifications: discrimination of aspen from the other species combined into one class and classification of all four species (aspen, birch, pine, spruce) simultaneously. In the first scenario, the highest classification accuracy of 84% (F1-score) for aspen and overall accuracy of 90.1% was achieved using only RGB features from PPC, whereas in the second scenario, the highest classification accuracy of 86 % (F1-score) for aspen and overall accuracy of 83.3% was achieved using the combination of RGB and MSP features. The proposed method provides a new possibility for the rapid assessment of aspen occurrence to enable more efficient forest management as well as contribute to biodiversity monitoring and conservation efforts in boreal forests.

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Using multilevel remote sensing and ground data to estimate forest biomass resources in remote regions: a case study in the boreal forests of interior Alaska

Canadian Journal of Remote Sensing ◽

10.5589/m12-003 ◽

2011 ◽

Vol 37 (6) ◽

pp. 596-611 ◽

Cited By ~ 42

Author(s):

Hans-Erik Andersen ◽

Jacob Strunk ◽

Hailemariam Temesgen ◽

Donald Atwood ◽

Ken Winterberger

Keyword(s):

Remote Sensing ◽

Boreal Forests ◽

Forest Biomass ◽

Interior Alaska ◽

Biomass Resources

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Development of F1 hybrid population and the high-density linkage map for European aspen (Populus tremula L.) using RADseq technology

BMC Plant Biology ◽

10.1186/s12870-017-1127-y ◽

2017 ◽

Vol 17 (S1) ◽

Cited By ~ 13

Author(s):

Anatoly V. Zhigunov ◽

Pavel S. Ulianich ◽

Marina V. Lebedeva ◽

Peter L. Chang ◽

Sergey V. Nuzhdin ◽

...

Keyword(s):

Linkage Map ◽

High Density ◽

Populus Tremula ◽

Hybrid Population ◽

F1 Hybrid ◽

European Aspen ◽

High Density Linkage Map

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Variant Calling Using NGS Data in European Aspen (Populus tremula)

Advances in the Understanding of Biological Sciences Using Next Generation Sequencing (NGS) Approaches ◽

10.1007/978-3-319-17157-9_4 ◽

2015 ◽

pp. 43-61 ◽

Cited By ~ 5

Author(s):

Jing Wang ◽

Douglas Scofield ◽

Nathaniel R. Street ◽

Pär K. Ingvarsson

Keyword(s):

Variant Calling ◽

Populus Tremula ◽

European Aspen ◽

Ngs Data

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Predictive mapping of bryophyte richness patterns in boreal forests using species distribution models and remote sensing data

Ecological Indicators ◽

10.1016/j.ecolind.2020.106826 ◽

2020 ◽

Vol 119 ◽

pp. 106826 ◽

Cited By ~ 1

Author(s):

Carlos Cerrejón ◽

Osvaldo Valeria ◽

Nicolas Mansuy ◽

Marion Barbé ◽

Nicole J. Fenton

Keyword(s):

Remote Sensing ◽

Species Distribution ◽

Boreal Forests ◽

Species Distribution Models ◽

Remote Sensing Data ◽

Distribution Models ◽

Predictive Mapping ◽

Sensing Data ◽

Richness Patterns

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Variation of wood density and shrinkage in European aspen ( Populus tremula )

European Journal of Wood and Wood Products ◽

10.1007/s001070050479 ◽

2001 ◽

Vol 59 (1-2) ◽

pp. 79-84 ◽

Cited By ~ 15

Author(s):

T. Kärki

Keyword(s):

Wood Density ◽

Populus Tremula ◽

European Aspen

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Inferring the Genomic Landscape of Recombination Rate Variation in European Aspen (Populus tremula)

G3 Genes|Genome|Genetics ◽

10.1534/g3.119.400504 ◽

2019 ◽

Vol 10 (1) ◽

pp. 299-309 ◽

Cited By ~ 2

Author(s):

Rami-Petteri Apuli ◽

Carolina Bernhardsson ◽

Bastian Schiffthaler ◽

Kathryn M. Robinson ◽

Stefan Jansson ◽

...

Keyword(s):

Linkage Disequilibrium ◽

Linkage Map ◽

Recombination Rate ◽

Gene Density ◽

Populus Tremula ◽

Rate Variation ◽

Recombination Rates ◽

Genomic Features ◽

European Aspen ◽

Recombination Rate Variation

The rate of meiotic recombination is one of the central factors determining genome-wide levels of linkage disequilibrium which has important consequences for the efficiency of natural selection and for the dissection of quantitative traits. Here we present a new, high-resolution linkage map for Populus tremula that we use to anchor approximately two thirds of the P. tremula draft genome assembly on to the expected 19 chromosomes, providing us with the first chromosome-scale assembly for P. tremula (Table 2). We then use this resource to estimate variation in recombination rates across the P. tremula genome and compare these results to recombination rates based on linkage disequilibrium in a large number of unrelated individuals. We also assess how variation in recombination rates is associated with a number of genomic features, such as gene density, repeat density and methylation levels. We find that recombination rates obtained from the two methods largely agree, although the LD-based method identifies a number of genomic regions with very high recombination rates that the map-based method fails to detect. Linkage map and LD-based estimates of recombination rates are positively correlated and show similar correlations with other genomic features, showing that both methods can accurately infer recombination rate variation across the genome. Recombination rates are positively correlated with gene density and negatively correlated with repeat density and methylation levels, suggesting that recombination is largely directed toward gene regions in P. tremula.

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