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Brydegaard M, Pedales RD, Feng V, Yamoa ASD, Kouakou B, Månefjord H, Wührl L, Pylatiuk C, Amorim DDS, Meier R. Towards global insect biomonitoring with frugal methods. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230103. [PMID: 38705174 PMCID: PMC11070255 DOI: 10.1098/rstb.2023.0103] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/24/2024] [Indexed: 05/07/2024] Open
Abstract
None of the global targets for protecting nature are currently met, although humanity is critically dependent on biodiversity. A significant issue is the lack of data for most biodiverse regions of the planet where the use of frugal methods for biomonitoring would be particularly important because the available funding for monitoring is insufficient, especially in low-income countries. We here discuss how three approaches to insect biomonitoring (computer vision, lidar, DNA sequences) could be made more frugal and urge that all biomonitoring techniques should be evaluated for global suitability before becoming the default in high-income countries. This requires that techniques popular in high-income countries should undergo a phase of 'innovation through simplification' before they are implemented more broadly. We predict that techniques that acquire raw data at low cost and are suitable for analysis with AI (e.g. images, lidar-signals) will be particularly suitable for global biomonitoring, while techniques that rely heavily on patented technologies may be less promising (e.g. DNA sequences). We conclude the opinion piece by pointing out that the widespread use of AI for data analysis will require a global strategy for providing the necessary computational resources and training. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.
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Affiliation(s)
- Mikkel Brydegaard
- Dept. Physics, Lund University, Sölvegatan 14c, 22362 Lund, Sweden
- Dept. Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
- Norsk Elektro Optikk, Østensjøveien 34, 0667 Oslo, Norge
- FaunaPhotonics, Støberi Støberigade 14, 2450 København, Denmark
| | - Ronniel D. Pedales
- Institute of Biology, University of the Philippines Diliman, Quezon City, Philippines 1101
- Center for Integrative Biodiversity Discovery, Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Invalidenstraße 43, 10115, Berlin, Germany
- Institute of Biology, Humboldt University, 10115 Berlin, Germany
| | - Vivian Feng
- Center for Integrative Biodiversity Discovery, Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Invalidenstraße 43, 10115, Berlin, Germany
- Institute of Biology, Humboldt University, 10115 Berlin, Germany
| | - Assoumou saint-doria Yamoa
- Instrumentation, Imaging and Spectroscopy Laboratory, Felix Houphouet-Boigny Institute, BP1093 Yamoussoukro, Ivory Coast
| | - Benoit Kouakou
- Instrumentation, Imaging and Spectroscopy Laboratory, Felix Houphouet-Boigny Institute, BP1093 Yamoussoukro, Ivory Coast
| | - Hampus Månefjord
- Dept. Physics, Lund University, Sölvegatan 14c, 22362 Lund, Sweden
| | - Lorenz Wührl
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - Christian Pylatiuk
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - Dalton de Souza Amorim
- Departamento de Biologia, FFCLRP, Universidade de São Paulo, Ribeirão Preto 14040-901, Brazil
| | - Rudolf Meier
- Center for Integrative Biodiversity Discovery, Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Invalidenstraße 43, 10115, Berlin, Germany
- Institute of Biology, Humboldt University, 10115 Berlin, Germany
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2
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Chen H, Li M, Månefjord H, Travers P, Salvador J, Müller L, Dreyer D, Alison J, Høye TT, Gao Hu, Warrant E, Brydegaard M. Lidar as a potential tool for monitoring migratory insects. iScience 2024; 27:109588. [PMID: 38646171 PMCID: PMC11031831 DOI: 10.1016/j.isci.2024.109588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 01/29/2024] [Accepted: 03/25/2024] [Indexed: 04/23/2024] Open
Abstract
The seasonal migrations of insects involve a substantial displacement of biomass with significant ecological and economic consequences for regions of departure and arrival. Remote sensors have played a pivotal role in revealing the magnitude and general direction of bioflows above 150 m. Nevertheless, the takeoff and descent activity of insects below this height is poorly understood. Our lidar observations elucidate the low-height dusk movements and detailed information of insects in southern Sweden from May to July, during the yearly northward migration period. Importantly, by filtering out moths from other insects based on optical information and wingbeat frequency, we have introduced a promising new method to monitor the flight activities of nocturnal moths near the ground, many of which participate in migration through the area. Lidar thus holds the potential to enhance the scientific understanding of insect migratory behavior and improve pest control strategies.
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Affiliation(s)
- Hui Chen
- Department of Entomology, Nanjing Agricultural University, Nanjing 210095, China
- Lund Vision Group, Department Of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Meng Li
- Department Physics, Lund University, Sölvegatan 14c, 22363 Lund, Sweden
| | - Hampus Månefjord
- Department Physics, Lund University, Sölvegatan 14c, 22363 Lund, Sweden
| | - Paul Travers
- Department Biological Engineering, Polytech Clermont, 2 Av. Blaise Pascal, 63100 Aubière, France
| | - Jacobo Salvador
- Department Physics, Lund University, Sölvegatan 14c, 22363 Lund, Sweden
| | - Lauro Müller
- Department Physics, Lund University, Sölvegatan 14c, 22363 Lund, Sweden
| | - David Dreyer
- Lund Vision Group, Department Of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Jamie Alison
- Department Ecoscience, Aarhus University, C. F. Møllers Allé 8, 8000 Aarhus C, Denmark
| | - Toke T. Høye
- Department Ecoscience, Aarhus University, C. F. Møllers Allé 8, 8000 Aarhus C, Denmark
- Arctic Research Centre, Aarhus University, Ole Worms Allé 1, 8000 Aarhus C, Denmark
| | - Gao Hu
- Department of Entomology, Nanjing Agricultural University, Nanjing 210095, China
| | - Eric Warrant
- Lund Vision Group, Department Of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Mikkel Brydegaard
- Department Physics, Lund University, Sölvegatan 14c, 22363 Lund, Sweden
- Department Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
- FaunaPhotonics, Støberigade 14, 2450 Copenhagen, Denmark
- Norsk Elektro Optikk, Østensjøveien 34, 0667 Oslo, Norway
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Li M, Runemark A, Hernandez J, Rota J, Bygebjerg R, Brydegaard M. Discrimination of Hover Fly Species and Sexes by Wing Interference Signals. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304657. [PMID: 37847885 PMCID: PMC10700183 DOI: 10.1002/advs.202304657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 09/08/2023] [Indexed: 10/19/2023]
Abstract
Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin-film wing interference signals (WISs) can discriminate free-flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave-infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS-based surveillance is therefore a potent tool for remote insect identification and surveillance.
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Affiliation(s)
- Meng Li
- Department of PhysicsLund UniversitySölvegatan 14cLund22363Sweden
| | - Anna Runemark
- Department of BiologyLund UniversitySölvegatan 35Lund22362Sweden
| | | | - Jadranka Rota
- Biological Museum, Department of BiologyLund UniversitySölvegatan 37Lund22362Sweden
| | - Rune Bygebjerg
- Biological Museum, Department of BiologyLund UniversitySölvegatan 37Lund22362Sweden
| | - Mikkel Brydegaard
- Department of PhysicsLund UniversitySölvegatan 14cLund22363Sweden
- Department of BiologyLund UniversitySölvegatan 35Lund22362Sweden
- Norsk Elektro OptikkØstensjøveien 34Oslo0667Norway
- FaunaPhotonicsStøberigade 14Copenhagen2450Denmark
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Månefjord H, Li M, Brackmann C, Reistad N, Runemark A, Rota J, Anderson B, Zoueu JT, Merdasa A, Brydegaard M. A biophotonic platform for quantitative analysis in the spatial, spectral, polarimetric, and goniometric domains. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:113709. [PMID: 36461456 DOI: 10.1063/5.0095133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 10/21/2022] [Indexed: 06/17/2023]
Abstract
Advanced instrumentation and versatile setups are needed for understanding light interaction with biological targets. Such instruments include (1) microscopes and 3D scanners for detailed spatial analysis, (2) spectral instruments for deducing molecular composition, (3) polarimeters for assessing structural properties, and (4) goniometers probing the scattering phase function of, e.g., tissue slabs. While a large selection of commercial biophotonic instruments and laboratory equipment are available, they are often bulky and expensive. Therefore, they remain inaccessible for secondary education, hobbyists, and research groups in low-income countries. This lack of equipment impedes hands-on proficiency with basic biophotonic principles and the ability to solve local problems with applied physics. We have designed, prototyped, and evaluated the low-cost Biophotonics, Imaging, Optical, Spectral, Polarimetric, Angular, and Compact Equipment (BIOSPACE) for high-quality quantitative analysis. BIOSPACE uses multiplexed light-emitting diodes with emission wavelengths from ultraviolet to near-infrared, captured by a synchronized camera. The angles of the light source, the target, and the polarization filters are automated by low-cost mechanics and a microcomputer. This enables multi-dimensional scatter analysis of centimeter-sized biological targets. We present the construction, calibration, and evaluation of BIOSPACE. The diverse functions of BIOSPACE include small animal spectral imaging, measuring the nanometer thickness of a bark-beetle wing, acquiring the scattering phase function of a blood smear and estimating the anisotropic scattering and the extinction coefficients, and contrasting muscle fibers using polarization. We provide blueprints, component list, and software for replication by enthusiasts and educators to simplify the hands-on investigation of fundamental optical properties in biological samples.
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Affiliation(s)
- Hampus Månefjord
- Department of Physics, Lund University, Sölvegatan 14, SE-223 62 Lund, Sweden
| | - Meng Li
- Department of Physics, Lund University, Sölvegatan 14, SE-223 62 Lund, Sweden
| | - Christian Brackmann
- Department of Physics, Lund University, Sölvegatan 14, SE-223 62 Lund, Sweden
| | - Nina Reistad
- Department of Physics, Lund University, Sölvegatan 14, SE-223 62 Lund, Sweden
| | - Anna Runemark
- Department of Biology, Lund University, Sölvegatan 35, SE-223 63 Lund, Sweden
| | - Jadranka Rota
- Biological Museum, Department of Biology, Lund University, Sölvegatan 37, SE-223 62 Lund, Sweden
| | | | - Jeremie T Zoueu
- Laboratoire d'Instrumentation, Image et Spectroscopie, INP-HB, BP 1093 Yamoussoukro, Côte d'Ivoire
| | - Aboma Merdasa
- Department of Physics, Lund University, Sölvegatan 14, SE-223 62 Lund, Sweden
| | - Mikkel Brydegaard
- Department of Physics, Lund University, Sölvegatan 14, SE-223 62 Lund, Sweden
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Ellerstrand SJ, Choudhury S, Svensson K, Andersson MN, Kirkeby C, Powell D, Schlyter F, Jönsson AM, Brydegaard M, Hansson B, Runemark A. Weak population genetic structure in Eurasian spruce bark beetle over large regional scales in Sweden. Ecol Evol 2022; 12:e9078. [PMID: 35822111 PMCID: PMC9260063 DOI: 10.1002/ece3.9078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 05/10/2022] [Accepted: 05/16/2022] [Indexed: 01/05/2023] Open
Abstract
The Eurasian spruce bark beetle, Ips typographus, is a major pest, capable of killing spruce forests during large population outbreaks. Recorded dispersal distances of individual beetles are typically within hundreds of meters or a few kilometers. However, the connectivity between populations at larger distances and longer time spans and how this is affected by the habitat is less studied, despite its importance for understanding at which distances local outbreaks may spread. Previous population genetic studies in I. typographus typically used low resolution markers. Here, we use genome-wide data to assess population structure and connectivity of I. typographus in Sweden. We used 152 individuals from 19 population samples, distributed over 830 km from Strömsund (63° 46' 8″ N) in the north to Nyteboda (56° 8' 50″ N) in the south, to capture processes at a large regional scale, and a transect sampling design adjacent to a recent outbreak to capture processes at a smaller scale (76 km). Using restriction site-associated DNA sequencing (RADseq) markers capturing 1409-1997 SNPs throughout the genome, we document a weak genetic structure over the large scale, potentially indicative of high connectivity with extensive gene flow. No differentiation was detected at the smaller scale. We find indications of isolation-by-distance both for relative (F ST) and absolute divergence (Dxy). The two northernmost populations are most differentiated from the remaining populations, and diverge in parallel to the southern populations for a set of outlier loci. In conclusion, the population structure of I. typographus in Sweden is weak, suggesting a high capacity to disperse and establish outbreak populations in new territories.
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Affiliation(s)
| | - Shruti Choudhury
- Department of BiologyLund UniversityLundSweden
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science CentreSwedish University of Agricultural SciencesUmeåSweden
| | | | | | - Carsten Kirkeby
- Excellent Team for Mitigation, Faculty of Forestry & Wood SciencesCzech University of Life Sciences PragueSuchdolCzech Republic
| | - Daniel Powell
- Animal Welfare and Disease ControlCopenhagen UniversityFrederiksberg CDenmark
| | - Fredrik Schlyter
- Global Change Ecology Research GroupUniversity of the Sunshine CoastSippy DownsQueenslandAustralia
- Department of Plant Protection BiologySwedish University of Agricultural SciencesLommaSweden
| | - Anna Maria Jönsson
- Department of Physical Geography and Ecosystem ScienceLund UniversityLundSweden
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Automating insect monitoring using unsupervised near-infrared sensors. Sci Rep 2022; 12:2603. [PMID: 35173221 PMCID: PMC8850605 DOI: 10.1038/s41598-022-06439-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 01/28/2022] [Indexed: 11/09/2022] Open
Abstract
Insect monitoring is critical to improve our understanding and ability to preserve and restore biodiversity, sustainably produce crops, and reduce vectors of human and livestock disease. Conventional monitoring methods of trapping and identification are time consuming and thus expensive. Automation would significantly improve the state of the art. Here, we present a network of distributed wireless sensors that moves the field towards automation by recording backscattered near-infrared modulation signatures from insects. The instrument is a compact sensor based on dual-wavelength infrared light emitting diodes and is capable of unsupervised, autonomous long-term insect monitoring over weather and seasons. The sensor records the backscattered light at kHz pace from each insect transiting the measurement volume. Insect observations are automatically extracted and transmitted with environmental metadata over cellular connection to a cloud-based database. The recorded features include wing beat harmonics, melanisation and flight direction. To validate the sensor’s capabilities, we tested the correlation between daily insect counts from an oil seed rape field measured with six yellow water traps and six sensors during a 4-week period. A comparison of the methods found a Spearman’s rank correlation coefficient of 0.61 and a p-value = 0.0065, with the sensors recording approximately 19 times more insect observations and demonstrating a larger temporal dynamic than conventional yellow water trap monitoring.
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Identification of Flying Insects in the Spatial, Spectral, and Time Domains with Focus on Mosquito Imaging. SENSORS 2021; 21:s21103329. [PMID: 34064829 PMCID: PMC8151584 DOI: 10.3390/s21103329] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/04/2021] [Accepted: 05/07/2021] [Indexed: 11/17/2022]
Abstract
Insects constitute a very important part of the global ecosystem and include pollinators, disease vectors, and agricultural pests, all with pivotal influence on society. Monitoring and control of such insects has high priority, and automatic systems are highly desirable. While capture and analysis by biologists constitute the gold standard in insect identification, optical and laser techniques have the potential for high-speed detection and automatic identification based on shape, spectroscopic properties such as reflectance and fluorescence, as well as wing-beat frequency analysis. The present paper discusses these approaches, and in particular presents a novel method for automatic identification of mosquitos based on image analysis, as the insects enter a trap based on a combination of chemical and suction attraction. Details of the analysis procedure are presented, and selectivity is discussed. An accuracy of 93% is achieved by our proposed method from a data set containing 122 insect images (mosquitoes and bees). As a powerful and cost-effective method, we finally propose the combination of imaging and wing-beat frequency analysis in an integrated instrument.
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