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Article ; Online: A Novel Method to Simultaneously Measure Leaf Gas Exchange and Water Content

Junttila, Samuli / Hölttä, Teemu / Salmon, Yann / Filella, Iolanda / Peñuelas, Josep

Remote Sensing. 2022 Aug. 02, v. 14, no. 15

2022

Abstract: Understanding the relationship between plant water status and productivity and between plant water status and plant mortality is required to effectively quantify and predict the effects of drought on plants. Plant water status is closely linked to leaf ... ...

Abstract	Understanding the relationship between plant water status and productivity and between plant water status and plant mortality is required to effectively quantify and predict the effects of drought on plants. Plant water status is closely linked to leaf water content that may be estimated using remote sensing technologies. Here, we used an inexpensive miniature hyperspectral spectrometer in the 1550–1950 nm wavelength domain to measure changes in silver birch (Betula pendula Roth) leaf water content combined with leaf gas exchange measurements at a sub-minute time resolution, under increasing vapor pressure deficit, CO₂ concentrations, and light intensity within the measurement cuvette; we also developed a novel methodology for calibrating reflectance measurements to predict leaf water content for individual leaves. Based on reflectance at 1550 nm, linear regression modeling explained 98–99% of the variation in leaf water content, with a root mean square error of 0.31–0.43 g cm⁻². The prediction accuracy of the model represents a c. ten-fold improvement compared to previous studies that have used destructive sampling measurements of several leaves. This novel methodology allows the study of interlinkages between leaf water content, transpiration, and assimilation at a high time resolution that will increase understanding of the movement of water within plants and between plants and the atmosphere.
Keywords	Betula pendula ; carbon dioxide ; drought ; gas exchange ; leaves ; light intensity ; models ; mortality ; prediction ; reflectance ; regression analysis ; spectrometers ; transpiration ; vapor pressure deficit ; water content ; wavelengths
Language	English
Dates of publication	2022-0802
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs14153693
Database	NAL-Catalogue (AGRICOLA)

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Article: Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season

Junttila, Samuli / Näsi, Roope / Koivumäki, Niko / Imangholiloo, Mohammad / Saarinen, Ninni / Raisio, Juha / Holopainen, Markus / Hyyppä, Hannu / Hyyppä, Juha / Lyytikäinen-Saarenmaa, Päivi / Vastaranta, Mikko / Honkavaara, Eija

Remote Sensing. 2022 Feb. 14, v. 14, no. 4

2022

Abstract: Climate change is increasing pest insects’ ability to reproduce as temperatures rise, resulting in vast tree mortality globally. Early information on pest infestation is urgently needed for timely decisions to mitigate the damage. We investigated the ... ...

Abstract	Climate change is increasing pest insects’ ability to reproduce as temperatures rise, resulting in vast tree mortality globally. Early information on pest infestation is urgently needed for timely decisions to mitigate the damage. We investigated the mapping of trees that were in decline due to European spruce bark beetle infestation using multispectral unmanned aerial vehicles (UAV)-based imagery collected in spring and fall in four study areas in Helsinki, Finland. We used the Random Forest machine learning to classify trees based on their symptoms during both occasions. Our approach achieved an overall classification accuracy of 78.2% and 84.5% for healthy, declined and dead trees for spring and fall datasets, respectively. The results suggest that fall or the end of summer provides the most accurate tree vitality classification results. We also investigated the transferability of Random Forest classifiers between different areas, resulting in overall classification accuracies ranging from 59.3% to 84.7%. The findings of this study indicate that multispectral UAV-based imagery is capable of classifying tree decline in Norway spruce trees during a bark beetle infestation.
Keywords	Picea abies ; Scolytidae ; bark beetle infestations ; climate change ; data collection ; decline ; forestry equipment ; multispectral imagery ; spring ; summer ; tree mortality ; trees ; unmanned aerial vehicles ; Finland
Language	English
Dates of publication	2022-0214
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs14040909
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale.

Li, Sizhuo / Brandt, Martin / Fensholt, Rasmus / Kariryaa, Ankit / Igel, Christian / Gieseke, Fabian / Nord-Larsen, Thomas / Oehmcke, Stefan / Carlsen, Ask Holm / Junttila, Samuli / Tong, Xiaoye / d'Aspremont, Alexandre / Ciais, Philippe

PNAS nexus

2023 Volume 2, Issue 4, Page(s) pgad076

Abstract: Sustainable tree resource management is the key to mitigating climate warming, fostering a green economy, and protecting valuable habitats. Detailed knowledge about tree resources is a prerequisite for such management but is conventionally based on plot- ... ...

Abstract	Sustainable tree resource management is the key to mitigating climate warming, fostering a green economy, and protecting valuable habitats. Detailed knowledge about tree resources is a prerequisite for such management but is conventionally based on plot-scale data, which often neglects trees outside forests. Here, we present a deep learning-based framework that provides location, crown area, and height for individual overstory trees from aerial images at country scale. We apply the framework on data covering Denmark and show that large trees (stem diameter >10 cm) can be identified with a low bias (12.5%) and that trees outside forests contribute to 30% of the total tree cover, which is typically unrecognized in national inventories. The bias is high (46.6%) when our results are evaluated against all trees taller than 1.3 m, which involve undetectable small or understory trees. Furthermore, we demonstrate that only marginal effort is needed to transfer our framework to data from Finland, despite markedly dissimilar data sources. Our work lays the foundation for digitalized national databases, where large trees are spatially traceable and manageable.
Language	English
Publishing date	2023-03-09
Publishing country	England
Document type	Journal Article
ISSN	2752-6542
ISSN (online)	2752-6542
DOI	10.1093/pnasnexus/pgad076
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: StrucNet: a global network for automated vegetation structure monitoring.

Calders, Kim / Brede, Benjamin / Newnham, Glenn / Culvenor, Darius / Armston, John / Bartholomeus, Harm / Griebel, Anne / Hayward, Jodie / Junttila, Samuli / Lau, Alvaro / Levick, Shaun / Morrone, Rosalinda / Origo, Niall / Pfeifer, Marion / Verbesselt, Jan / Herold, Martin

Remote sensing in ecology and conservation

2023 Volume 9, Issue 5, Page(s) 587–598

Abstract: Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and ... ...

Abstract	Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large-scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three-dimensional vegetation structure at local scales. Here we demonstrate the potential of high-frequency ground-based laser scanning to systematically monitor structural changes in vegetation. We present a proof-of-concept high-temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high-temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.
Language	English
Publishing date	2023-04-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2825232-9
ISSN	2056-3485
ISSN	2056-3485
DOI	10.1002/rse2.333
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Article: Understanding 3D structural complexity of individual Scots pine trees with different management history.

Saarinen, Ninni / Calders, Kim / Kankare, Ville / Yrttimaa, Tuomas / Junttila, Samuli / Luoma, Ville / Huuskonen, Saija / Hynynen, Jari / Verbeeck, Hans

Ecology and evolution

2021 Volume 11, Issue 6, Page(s) 2561–2572

Abstract: Tree functional traits together with processes such as forest regeneration, growth, and mortality affect forest and tree structure. Forest management inherently impacts these processes. Moreover, forest structure, biodiversity, resilience, and carbon ... ...

Abstract	Tree functional traits together with processes such as forest regeneration, growth, and mortality affect forest and tree structure. Forest management inherently impacts these processes. Moreover, forest structure, biodiversity, resilience, and carbon uptake can be sustained and enhanced with forest management activities. To assess structural complexity of individual trees, comprehensive and quantitative measures are needed, and they are often lacking for current forest management practices. Here, we utilized 3D information from individual Scots pine (
Language	English
Publishing date	2021-01-31
Publishing country	England
Document type	Journal Article
ZDB-ID	2635675-2
ISSN	2045-7758
ISSN	2045-7758
DOI	10.1002/ece3.7216
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Article: Effects of Stem Density on Crown Architecture of Scots Pine Trees.

Saarinen, Ninni / Kankare, Ville / Huuskonen, Saija / Hynynen, Jari / Bianchi, Simone / Yrttimaa, Tuomas / Luoma, Ville / Junttila, Samuli / Holopainen, Markus / Hyyppä, Juha / Vastaranta, Mikko

Frontiers in plant science

2022 Volume 13, Page(s) 817792

Abstract: Trees adapt to their growing conditions by regulating the sizes of their parts and their relationships. For example, removal or death of adjacent trees increases the growing space and the amount of light received by the remaining trees enabling their ... ...

Abstract	Trees adapt to their growing conditions by regulating the sizes of their parts and their relationships. For example, removal or death of adjacent trees increases the growing space and the amount of light received by the remaining trees enabling their crowns to expand. Knowledge about the effects of silvicultural practices on crown size and shape and also about the quality of branches affecting the shape of a crown is, however, still limited. Thus, the aim was to study the crown structure of individual Scots pine trees in forest stands with varying stem densities due to past forest management practices. Furthermore, we wanted to understand how crown and stem attributes and also tree growth affect stem area at the height of maximum crown diameter (SAHMC), which could be used as a proxy for tree growth potential. We used terrestrial laser scanning (TLS) to generate attributes characterizing crown size and shape. The results showed that increasing stem density decreased Scots pine crown size. TLS provided more detailed attributes for crown characterization compared with traditional field measurements. Furthermore, decreasing stem density increased SAHMC, and strong relationships (Spearman's correlations > 0.5) were found between SAHMC and crown and stem size and also stem growth. Thus, this study provided quantitative and more comprehensive characterization of Scots pine crowns and their growth potential. The combination of a traditional growth and yield study design and 3D characterization of crown architecture and growth potential can open up new research possibilities.
Language	English
Publishing date	2022-03-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2613694-6
ISSN	1664-462X
ISSN	1664-462X
DOI	10.3389/fpls.2022.817792
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Article ; Online: StrucNet

Remote Sensing in Ecology and Conservation (2023) ; ISSN: 2056-3485

A global network for automated vegetation structure monitoring

2023

Abstract: Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables(EBV) and essential climate variables are used to monitor biodiversity and car-bon dynamics and ... ...

Abstract	Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables(EBV) and essential climate variables are used to monitor biodiversity and car-bon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Space borne measurements can provide large-scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three-dimensional vegetation structure at local scales. Here we demonstrate the potential of high-frequency ground-based laser scanning to systematically monitor structural changes in vegetation. We present a proof of concept high-temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high-temporal laser scanning that can allow up scaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.
Keywords	Life Science
Subject code	333
Language	English
Publishing country	nl
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effects of water availability on a forestry pathosystem: fungal strain-specific variation in disease severity.

Linnakoski, Riikka / Sugano, Junko / Junttila, Samuli / Pulkkinen, Pertti / Asiegbu, Fred O / Forbes, Kristian M

Scientific reports

2017 Volume 7, Issue 1, Page(s) 13501

Abstract: Norway spruce is one of the most important commercial forestry species in Europe, and is commonly infected by the bark beetle-vectored necrotrophic fungus, Endoconidiophora polonica. Spruce trees display a restricted capacity to respond to environmental ... ...

Abstract	Norway spruce is one of the most important commercial forestry species in Europe, and is commonly infected by the bark beetle-vectored necrotrophic fungus, Endoconidiophora polonica. Spruce trees display a restricted capacity to respond to environmental perturbations, and we hypothesized that water limitation will increase disease severity in this pathosystem. To test this prediction, 737 seedlings were randomized to high (W+) or low (W-) water availability treatment groups, and experimentally inoculated with one of three E. polonica strains or mock-inoculated. Seedling mortality was monitored throughout an annual growing season, and total seedling growth and lesion length indices were measured at the experiment conclusion. Seedling growth was greater in the W+ than W- treatment group, demonstrating limitation due to water availability. For seedlings infected with two of the fungal strains, no differences in disease severity occurred in response to water availability. For the third fungal strain, however, greater disease severity (mortality and lesion lengths) occurred in W- than W+ seedlings. While the co-circulation in nature of multiple E. polonica strains of varying virulence is known, this is the first experimental evidence that water availability can alter strain-specific disease severity.
MeSH term(s)	Forests ; Fungi/pathogenicity ; Germination ; Picea/immunology ; Picea/microbiology ; Picea/physiology ; Plant Immunity ; Seeds/metabolism ; Seeds/physiology ; Water Cycle
Language	English
Publishing date	2017-10-18
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-017-13512-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Vertical plant profiles for Dassenbos (NL, 2014-2018, TLS); Wytham Woods (UK, 2022, LEAF) & Northern Australia (2021-2022, LEAF)

2023

Abstract: This dataset was described and used for the analysis of the following publication: StrucNet: A global network for automated vegetation structure monitoring. Brede, B., Newnham, G., Culvenor, D., Armston, J., Bartholomeus, H., Griebel, A., Hayward, J., ... ...

Abstract	This dataset was described and used for the analysis of the following publication: StrucNet: A global network for automated vegetation structure monitoring. Brede, B., Newnham, G., Culvenor, D., Armston, J., Bartholomeus, H., Griebel, A., Hayward, J., Junttila, S., Lau, A., Levick, S., Morrone, R., Origo, N., Pfeifer, M., Verbesselt, J. & Herold, M. Remote Sensing in Ecology and Conservation (accepted) Any use of this dataset should cite the paper above (Creative Commons Attribution 4.0 International Public License). Contact: kim.calders@ugent.be ================================================ Dataset ================================================ 1) TLS vertical plant profiles Dassenbos. Five-year dynamics of forest structure for the four sampling locations in Dassenbos. Data were collected using the same measurement protocol and data analysis using https://www.pylidar.org/ as described in Calders et al. (2015) using a zenith range of 35-70 degrees for 184-186 (some scans were discarded for quality purposes) measurement days during the period from February 2014 to November 2018. The data repository contains the vertical plant profiles and plotting code (Fig 1 in paper) 2) One-year dynamics of vegetation structure for a tropical savanna site in Northern Australia (Fig 2 in paper) and Wytham Woods (Fig 3 in paper). The data repository contains the vertical plant profiles derived from LEAF data and plotting code.
Keywords	Life Science
Subject code	580
Publisher	University Ghent
Publishing country	nl
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Can Leaf Water Content Be Estimated Using Multispectral Terrestrial Laser Scanning? A Case Study With Norway Spruce Seedlings.

Junttila, Samuli / Sugano, Junko / Vastaranta, Mikko / Linnakoski, Riikka / Kaartinen, Harri / Kukko, Antero / Holopainen, Markus / Hyyppä, Hannu / Hyyppä, Juha

Frontiers in plant science

2018 Volume 9, Page(s) 299

Abstract: Changing climate is increasing the amount and intensity of forest stress agents, such as drought, pest insects, and pathogens. Leaf water content, measured here in terms of equivalent water thickness (EWT), is an early indicator of tree stress that ... ...

Abstract	Changing climate is increasing the amount and intensity of forest stress agents, such as drought, pest insects, and pathogens. Leaf water content, measured here in terms of equivalent water thickness (EWT), is an early indicator of tree stress that provides timely information about the health status of forests. Multispectral terrestrial laser scanning (MS-TLS) measures target geometry and reflectance simultaneously, providing spatially explicit reflectance information at several wavelengths. EWT and leaf internal structure affect leaf reflectance in the shortwave infrared region that can be used to predict EWT with MS-TLS. A second wavelength that is sensitive to leaf internal structure but not affected by EWT can be used to normalize leaf internal effects on the shortwave infrared region and improve the prediction of EWT. Here we investigated the relationship between EWT and laser intensity features using multisensor MS-TLS at 690, 905, and 1,550 nm wavelengths with both drought-treated and
Language	English
Publishing date	2018-03-08
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2711035-7
ISSN	1664-462X
ISSN	1664-462X
DOI	10.3389/fpls.2018.00299
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