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Zhu M, Zhao Y, Li W, Han X, Wang Z, Yang X, Dang C, Liu Y, Xu S. Impact of carbon neutralization policy on the suitable habitat distribution of the North China leopard. Sci Rep 2024; 14:18821. [PMID: 39138239 PMCID: PMC11322554 DOI: 10.1038/s41598-024-69889-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 08/09/2024] [Indexed: 08/15/2024] Open
Abstract
The Chinese government has introduced a carbon neutral policy to cope with the rapid changes in the global climate. It is not clear what impact this policy will have on wildlife. Therefore, this study analyzed the suitable habitat distribution of China's unique leopard subspecies in northern Shaanxi, and simulated the potential suitable habitat distribution under different carbon emission scenarios at two time points of future carbon peak and carbon neutralization. We found that in the future SSPs 126 scenario, the suitable habitat area and the number of suitable habitat patches of North China leopard will continue to increase. With the increase of carbon emissions, it is expected that the suitable habitat of North China leopard will continue to be fragmented and shifted. When the annual average temperature is lower than 8 °C, the precipitation seasonality is 80-90 mm and the precipitation of the warmest quarter is greater than 260 mm, the probability of occurrence of North China leopard is higher. The increase in carbon emissions will lead to the reduction, migration, and fragmentation of the suitable habitat distribution of the North China leopard. Carbon neutrality policies can protect suitable wild habitats. In the future, the impact of carbon neutrality policies on future wildlife habitat protection should be carried out in depth to effectively promote the construction of wildlife protection projects.
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Affiliation(s)
- Mengyan Zhu
- Key Laboratory of Applied Ecology of Loess Plateau, Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China.
- Research and Development Centre of Ecological and Sustainable Application of Microbial Industry of the Loess Plateau in Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China.
- College of Life Sciences, Yan'an University, Yan'an, 716000, Shaanxi, China.
| | - Yue Zhao
- Key Laboratory of Applied Ecology of Loess Plateau, Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- Research and Development Centre of Ecological and Sustainable Application of Microbial Industry of the Loess Plateau in Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- College of Life Sciences, Yan'an University, Yan'an, 716000, Shaanxi, China
| | - Weiqiang Li
- Yan'an Laoshan State-Owned Forest Administration, Yan'an, 716000, China
| | - Xinghua Han
- Shaanxi Yan'an Huanglong Mountain Brown Eared Pheasant National Nature Reserve Management Bureau, Yan'an, 716000, China
| | - Zhen Wang
- Yan'an Laoshan State-Owned Forest Administration, Yan'an, 716000, China
| | - Xiaomei Yang
- Shaanxi Yan'an Huanglong Mountain Brown Eared Pheasant National Nature Reserve Management Bureau, Yan'an, 716000, China
| | - Cuiying Dang
- Key Laboratory of Applied Ecology of Loess Plateau, Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- Research and Development Centre of Ecological and Sustainable Application of Microbial Industry of the Loess Plateau in Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- College of Life Sciences, Yan'an University, Yan'an, 716000, Shaanxi, China
| | - Yaoguo Liu
- Key Laboratory of Applied Ecology of Loess Plateau, Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- Research and Development Centre of Ecological and Sustainable Application of Microbial Industry of the Loess Plateau in Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- College of Life Sciences, Yan'an University, Yan'an, 716000, Shaanxi, China
| | - Shicai Xu
- Key Laboratory of Applied Ecology of Loess Plateau, Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- Research and Development Centre of Ecological and Sustainable Application of Microbial Industry of the Loess Plateau in Shaanxi Province, Yan'an University, Yan'an, 716000, Shaanxi, China
- College of Life Sciences, Yan'an University, Yan'an, 716000, Shaanxi, China
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2
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Bauer S, Tielens EK, Haest B. Monitoring aerial insect biodiversity: a radar perspective. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230113. [PMID: 38705181 PMCID: PMC11070259 DOI: 10.1098/rstb.2023.0113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 03/21/2024] [Indexed: 05/07/2024] Open
Abstract
In the current biodiversity crisis, populations of many species have alarmingly declined, and insects are no exception to this general trend. Biodiversity monitoring has become an essential asset to detect biodiversity change but remains patchy and challenging for organisms that are small, inconspicuous or make (nocturnal) long-distance movements. Radars are powerful remote-sensing tools that can provide detailed information on intensity, timing, altitude and spatial scale of aerial movements and might therefore be particularly suited for monitoring aerial insects and their movements. Importantly, they can contribute to several essential biodiversity variables (EBVs) within a harmonized observation system. We review existing research using small-scale biological and weather surveillance radars for insect monitoring and outline how the derived measures and quantities can contribute to the EBVs 'species population', 'species traits', 'community composition' and 'ecosystem function'. Furthermore, we synthesize how ongoing and future methodological, analytical and technological advancements will greatly expand the use of radar for insect biodiversity monitoring and beyond. Owing to their long-term and regional-to-large-scale deployment, radar-based approaches can be a powerful asset in the biodiversity monitoring toolbox whose potential has yet to be fully tapped. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.
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Affiliation(s)
- Silke Bauer
- Swiss Federal Institute for Forest, Snow and Landscape Research, 8903 Birmensdorf, Switzerland
- Swiss Ornithological Institute, Sempach, LU 6204, Switzerland
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, 1090 GE Amsterdam, Noord-Holland, The Netherlands
- Department of Environmental System Science, Federal Institute of Technology (ETH), 8092 Zürich, Switzerland
| | - Elske K. Tielens
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019-0390, USA
| | - Birgen Haest
- Swiss Ornithological Institute, Sempach, LU 6204, Switzerland
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3
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Chen C, Granados A, Brodie JF, Kays R, Davies TJ, Liu R, Fisher JT, Ahumada J, McShea W, Sheil D, Mohd-Azlan J, Agwanda B, Andrianarisoa MH, Appleton RD, Bitariho R, Espinosa S, Grigione MM, Helgen KM, Hubbard A, Hurtado CM, Jansen PA, Jiang X, Jones A, Kalies EL, Kiebou-Opepa C, Li X, Lima MGM, Meyer E, Miller AB, Murphy T, Piana R, Quan RC, Rota CT, Rovero F, Santos F, Schuttler S, Uduman A, van Bommel JK, Young H, Burton AC. Combining camera trap surveys and IUCN range maps to improve knowledge of species distributions. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14221. [PMID: 37937455 DOI: 10.1111/cobi.14221] [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: 12/05/2022] [Revised: 10/05/2023] [Accepted: 10/31/2023] [Indexed: 11/09/2023]
Abstract
Reliable maps of species distributions are fundamental for biodiversity research and conservation. The International Union for Conservation of Nature (IUCN) range maps are widely recognized as authoritative representations of species' geographic limits, yet they might not always align with actual occurrence data. In recent area of habitat (AOH) maps, areas that are not habitat have been removed from IUCN ranges to reduce commission errors, but their concordance with actual species occurrence also remains untested. We tested concordance between occurrences recorded in camera trap surveys and predicted occurrences from the IUCN and AOH maps for 510 medium- to large-bodied mammalian species in 80 camera trap sampling areas. Across all areas, cameras detected only 39% of species expected to occur based on IUCN ranges and AOH maps; 85% of the IUCN only mismatches occurred within 200 km of range edges. Only 4% of species occurrences were detected by cameras outside IUCN ranges. The probability of mismatches between cameras and the IUCN range was significantly higher for smaller-bodied mammals and habitat specialists in the Neotropics and Indomalaya and in areas with shorter canopy forests. Our findings suggest that range and AOH maps rarely underrepresent areas where species occur, but they may more often overrepresent ranges by including areas where a species may be absent, particularly at range edges. We suggest that combining range maps with data from ground-based biodiversity sensors, such as camera traps, provides a richer knowledge base for conservation mapping and planning.
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Affiliation(s)
- Cheng Chen
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alys Granados
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
- Felidae Conservation Fund, Mill Valley, California, USA
| | - Jedediah F Brodie
- Division of Biological Sciences and Wildlife Biology Program, University of Montana, Missoula, Montana, USA
| | - Roland Kays
- North Carolina Museum of Natural Sciences, Raleigh, North Carolina, USA
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, North Carolina, USA
| | - T Jonathan Davies
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Botany, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Runzhe Liu
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biology Department, Lund University, Lund, Sweden
| | - Jason T Fisher
- School of Environmental Studies, University of Victoria, Victoria, British Columbia, Canada
| | - Jorge Ahumada
- Moore Center for Science, Conservation International, Arlington, Virginia, USA
| | - William McShea
- Conservation Ecology Center, Smithsonian's National Zoo & Conservation Biology Institute, Front Royal, Virginia, USA
| | - Douglas Sheil
- Forest Ecology and Forest Management Group, Wageningen University & Research, Wageningen, The Netherlands
- Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Akershus, Norway
- Center for International Forestry Research, Bogor, Indonesia
| | - Jayasilan Mohd-Azlan
- Institute of Biodiversity and Environmental Conservation, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia
| | | | | | - Robyn D Appleton
- Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
- Spectacled Bear Conservation Society Peru, Lambayeque, Peru
| | - Robert Bitariho
- Institute of Tropical Forest Conservation, Mbarara University of Science and Technology, Mbarara, Uganda
| | - Santiago Espinosa
- Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
- Escuela de Ciencias Biológicas, Pontificia Universidad Católica del Ecuador, Quito, Ecuador
| | | | - Kristofer M Helgen
- Australian Museum Research Institute, Australian Museum, Sydney, New South Wales, Australia
| | - Andy Hubbard
- National Park Service, Sonoran Desert Network, Tucson, Arizona, USA
| | - Cindy M Hurtado
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Patrick A Jansen
- Wildlife Ecology and Conservation Group, Wageningen University & Research, Wageningen, The Netherlands
- Smithsonian Tropical Research Institute, Panamá, República de Panamá
| | - Xuelong Jiang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Alex Jones
- Campus Natural Reserves, University of California, Santa Cruz, Santa Cruz, California, USA
| | | | | | - Xueyou Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | | | - Erik Meyer
- Sequoia & Kings Canyon National Parks, Three Rivers, California, USA
| | - Anna B Miller
- Department of Environment and Society, Institute of Outdoor Recreation and Tourism, Utah State University, Logan, Utah, USA
| | - Thomas Murphy
- Department of Anthropology, Edmonds College, Lynwood, Washington, USA
| | - Renzo Piana
- Spectacled Bear Conservation Society Peru, Lambayeque, Peru
| | - Rui-Chang Quan
- Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, China
| | - Christopher T Rota
- Division of Forestry and Natural Resources, West Virginia University, Morgantown, West Virginia, USA
| | - Francesco Rovero
- Department of Biology, University of Florence, Trento, Italy
- MUSE - Museo delle Scienze, Trento, Italy
| | | | | | - Aisha Uduman
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Joanna Klees van Bommel
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Hilary Young
- Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California, USA
| | - A Cole Burton
- Department of Forest Resources Management, University of British Columbia, Vancouver, British Columbia, Canada
- Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
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Callaghan CT, Santini L, Spake R, Bowler DE. Population abundance estimates in conservation and biodiversity research. Trends Ecol Evol 2024; 39:515-523. [PMID: 38508923 DOI: 10.1016/j.tree.2024.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/24/2024] [Accepted: 01/29/2024] [Indexed: 03/22/2024]
Abstract
Measuring and tracking biodiversity from local to global scales is challenging due to its multifaceted nature and the range of metrics used to describe spatial and temporal patterns. Abundance can be used to describe how a population changes across space and time, but it can be measured in different ways, with consequences for the interpretation and communication of spatiotemporal patterns. We differentiate between relative and absolute abundance, and discuss the advantages and disadvantages of each for biodiversity monitoring, conservation, and ecological research. We highlight when absolute abundance can be advantageous and should be prioritized in biodiversity monitoring and research, and conclude by providing avenues for future research directions to better assess the necessity of absolute abundance in biodiversity monitoring.
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Affiliation(s)
- Corey T Callaghan
- Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, University of Florida, Davie, FL 33314-7719, USA.
| | - Luca Santini
- Department of Biology and Biotechnologies 'Charles Darwin', Sapienza University of Rome, Rome, Italy
| | - Rebecca Spake
- School of Biological Sciences, University of Reading, Reading RG6 6AS, UK
| | - Diana E Bowler
- UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
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Malchow AK, Fandos G, Kormann UG, Grüebler MU, Kéry M, Hartig F, Zurell D. Fitting individual-based models of spatial population dynamics to long-term monitoring data. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2024; 34:e2966. [PMID: 38629509 DOI: 10.1002/eap.2966] [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: 10/04/2023] [Accepted: 12/20/2023] [Indexed: 06/04/2024]
Abstract
Generating spatial predictions of species distribution is a central task for research and policy. Currently, correlative species distribution models (cSDMs) are among the most widely used tools for this purpose. However, a fundamental assumption of cSDMs, that species distributions are in equilibrium with their environment, is rarely fulfilled in real data and limits the applicability of cSDMs for dynamic projections. Process-based, dynamic SDMs (dSDMs) promise to overcome these limitations as they explicitly represent transient dynamics and enhance spatiotemporal transferability. Software tools for implementing dSDMs are becoming increasingly available, but their parameter estimation can be complex. Here, we test the feasibility of calibrating and validating a dSDM using long-term monitoring data of Swiss red kites (Milvus milvus). This population has shown strong increases in abundance and a progressive range expansion over the last decades, indicating a nonequilibrium situation. We construct an individual-based model using the RangeShiftR modeling platform and use Bayesian inference for model calibration. This allows the integration of heterogeneous data sources, such as parameter estimates from published literature and observational data from monitoring schemes, with a coherent assessment of parameter uncertainty. Our monitoring data encompass counts of breeding pairs at 267 sites across Switzerland over 22 years. We validate our model using a spatial-block cross-validation scheme and assess predictive performance with a rank-correlation coefficient. Our model showed very good predictive accuracy of spatial projections and represented well the observed population dynamics over the last two decades. Results suggest that reproductive success was a key factor driving the observed range expansion. According to our model, the Swiss red kite population fills large parts of its current range but has potential for further increases in density. We demonstrate the practicality of data integration and validation for dSDMs using RangeShiftR. This approach can improve predictive performance compared to cSDMs. The workflow presented here can be adopted for any population for which some prior knowledge on demographic and dispersal parameters as well as spatiotemporal observations of abundance or presence/absence are available. The fitted model provides improved quantitative insights into the ecology of a species, which can greatly aid conservation and management efforts.
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Affiliation(s)
| | - Guillermo Fandos
- Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany
- Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, Madrid, Spain
| | - Urs G Kormann
- Swiss Ornithological Institute, Sempach, Switzerland
| | | | - Marc Kéry
- Swiss Ornithological Institute, Sempach, Switzerland
| | - Florian Hartig
- Theoretical Ecology, Faculty of Biology and Pre-Clinical Medicine, University of Regensburg, Regensburg, Germany
| | - Damaris Zurell
- Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany
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6
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Leoni C, Vinci L, Marzano M, D’Erchia AM, Dellino M, Cox SN, Vitagliano A, Visci G, Notario E, Filomena E, Cicinelli E, Pesole G, Ceci LR. Endometrial Cancer: A Pilot Study of the Tissue Microbiota. Microorganisms 2024; 12:1090. [PMID: 38930472 PMCID: PMC11205883 DOI: 10.3390/microorganisms12061090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 05/20/2024] [Accepted: 05/23/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND The endometrium remains a difficult tissue for the analysis of microbiota, mainly due to the low bacterial presence and the sampling procedures. Among its pathologies, endometrial cancer has not yet been completely investigated for its relationship with microbiota composition. In this work, we report on possible correlations between endometrial microbiota dysbiosis and endometrial cancer. METHODS Women with endometrial cancer at various stages of tumor progression were enrolled together with women with a benign polymyomatous uterus as the control. Analyses were performed using biopsies collected at two specific endometrial sites during the surgery. This study adopted two approaches: the absolute quantification of the bacterial load, using droplet digital PCR (ddPCR), and the analysis of the bacterial composition, using a deep metabarcoding NGS procedure. RESULTS ddPCR provided the first-ever assessment of the absolute quantification of bacterial DNA in the endometrium, confirming a generally low microbial abundance. Metabarcoding analysis revealed a different microbiota distribution in the two endometrial sites, regardless of pathology, accompanied by an overall higher prevalence of pathogenic bacterial genera in cancerous tissues. CONCLUSIONS These results pave the way for future studies aimed at identifying potential biomarkers and gaining a deeper understanding of the role of bacteria associated with tumors.
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Affiliation(s)
- Claudia Leoni
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Amendola n. 122/O, 70126 Bari, Italy; (M.M.); (E.N.)
| | - Lorenzo Vinci
- 2nd Unit of Obstetrics and Gynaecology, Department of Biomedical Science and Human Oncology, University of Bari “A. Moro”, Piazza G. Cesare, 70124 Bari, Italy; (L.V.); (M.D.); (A.V.); (E.C.)
| | - Marinella Marzano
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Amendola n. 122/O, 70126 Bari, Italy; (M.M.); (E.N.)
| | - Anna Maria D’Erchia
- Department of Biosciences, Biotechnologies and Environment, University of Bari A. Moro, Via Orabona n. 4, 70126 Bari, Italy; (A.M.D.); (S.N.C.); (G.V.); (E.F.); (G.P.)
| | - Miriam Dellino
- 2nd Unit of Obstetrics and Gynaecology, Department of Biomedical Science and Human Oncology, University of Bari “A. Moro”, Piazza G. Cesare, 70124 Bari, Italy; (L.V.); (M.D.); (A.V.); (E.C.)
| | - Sharon Natasha Cox
- Department of Biosciences, Biotechnologies and Environment, University of Bari A. Moro, Via Orabona n. 4, 70126 Bari, Italy; (A.M.D.); (S.N.C.); (G.V.); (E.F.); (G.P.)
| | - Amerigo Vitagliano
- 2nd Unit of Obstetrics and Gynaecology, Department of Biomedical Science and Human Oncology, University of Bari “A. Moro”, Piazza G. Cesare, 70124 Bari, Italy; (L.V.); (M.D.); (A.V.); (E.C.)
| | - Grazia Visci
- Department of Biosciences, Biotechnologies and Environment, University of Bari A. Moro, Via Orabona n. 4, 70126 Bari, Italy; (A.M.D.); (S.N.C.); (G.V.); (E.F.); (G.P.)
| | - Elisabetta Notario
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Amendola n. 122/O, 70126 Bari, Italy; (M.M.); (E.N.)
| | - Ermes Filomena
- Department of Biosciences, Biotechnologies and Environment, University of Bari A. Moro, Via Orabona n. 4, 70126 Bari, Italy; (A.M.D.); (S.N.C.); (G.V.); (E.F.); (G.P.)
| | - Ettore Cicinelli
- 2nd Unit of Obstetrics and Gynaecology, Department of Biomedical Science and Human Oncology, University of Bari “A. Moro”, Piazza G. Cesare, 70124 Bari, Italy; (L.V.); (M.D.); (A.V.); (E.C.)
| | - Graziano Pesole
- Department of Biosciences, Biotechnologies and Environment, University of Bari A. Moro, Via Orabona n. 4, 70126 Bari, Italy; (A.M.D.); (S.N.C.); (G.V.); (E.F.); (G.P.)
| | - Luigi Ruggiero Ceci
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Amendola n. 122/O, 70126 Bari, Italy; (M.M.); (E.N.)
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Waterhouse RM, Adam-Blondon AF, Balech B, Barta E, Ying Shi Chua P, Di Cola V, Heil KF, Hughes GM, Jermiin LS, Kalaš M, Lanfear J, Pafilis E, Palagi PM, Papageorgiou AC, Paupério J, Psomopoulos F, Raes N, Burgin J, Gabaldón T. The ELIXIR Biodiversity Community: Understanding short- and long-term changes in biodiversity. F1000Res 2024; 12:ELIXIR-499. [PMID: 38882711 PMCID: PMC11179050 DOI: 10.12688/f1000research.133724.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/09/2024] [Indexed: 06/18/2024] Open
Abstract
Biodiversity loss is now recognised as one of the major challenges for humankind to address over the next few decades. Unless major actions are taken, the sixth mass extinction will lead to catastrophic effects on the Earth's biosphere and human health and well-being. ELIXIR can help address the technical challenges of biodiversity science, through leveraging its suite of services and expertise to enable data management and analysis activities that enhance our understanding of life on Earth and facilitate biodiversity preservation and restoration. This white paper, prepared by the ELIXIR Biodiversity Community, summarises the current status and responses, and presents a set of plans, both technical and community-oriented, that should both enhance how ELIXIR Services are applied in the biodiversity field and how ELIXIR builds connections across the many other infrastructures active in this area. We discuss the areas of highest priority, how they can be implemented in cooperation with the ELIXIR Platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for a Biodiversity Community in ELIXIR and is an appeal to identify and involve new stakeholders.
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Affiliation(s)
- Robert M. Waterhouse
- Department of Ecology and Evolution, SIB Swiss Institute of Bioinformatics, Universite de Lausanne, Lausanne, Vaud, 1015, Switzerland
| | - Anne-Françoise Adam-Blondon
- INRAE, BioinfOmics, Plant Bioinformatics Facility, Universite Paris-Saclay, Gif-sur-Yvette, Île-de-France, 78026, France
| | - Bachir Balech
- Istituto di Biomembrane, Bioenergetica e Biotecnologie Molecolari, Bari, 70126, Italy
| | - Endre Barta
- Institute of Genetics and Biotechnology, Magyar Agrar- es Elettudomanyi Egyetem, Gödöllő, Pest County, Hungary
| | | | - Valeria Di Cola
- SIB Swiss Institute of Bioinformatics, Lausanne, Vaud, 1015, Switzerland
| | | | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Dublin, Leinster, Ireland
| | - Lars S. Jermiin
- Systems Biology Ireland, School of Medicine, University College Dublin, Dublin, Leinster, Ireland
- School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland
| | - Matúš Kalaš
- Department of Informatics, Universitetet i Bergen, Bergen, Hordaland, Norway
| | - Jerry Lanfear
- ELIXIR, Wellcome Genome Campus, Hinxton, England, CB10 1SD, UK
| | - Evangelos Pafilis
- Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, 71003, Greece
| | - Patricia M. Palagi
- SIB Swiss Institute of Bioinformatics, Lausanne, Vaud, 1015, Switzerland
| | | | - Joana Paupério
- EMBL-EBI, Wellcome Genome Campus, Hinxton, England, CB10 1SD, UK
| | - Fotis Psomopoulos
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Niels Raes
- Naturalis Biodiversity Center, Leiden, South Holland, The Netherlands
| | - Josephine Burgin
- EMBL-EBI, Wellcome Genome Campus, Hinxton, England, CB10 1SD, UK
| | - Toni Gabaldón
- Institut de Recerca Biomedica, Barcelona, Catalonia, Spain
- Centro Nacional de Supercomputacion, Barcelona, Catalonia, Spain
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8
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Chapman OS, McLean BS. Seasonal and sex-specific changes in the gastrointestinal tracts of Peromyscus maniculatus. J Mammal 2023; 104:1364-1376. [PMID: 38059007 PMCID: PMC10697414 DOI: 10.1093/jmammal/gyad086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/08/2023] [Indexed: 12/08/2023] Open
Abstract
Functional traits are phenotypic characteristics that contribute to fitness of individuals in dynamic and changing environments. In mammals, both categorical and continuous (e.g., quantitative) functional traits have been extensively utilized as proxies for diet, locomotion, and other aspects of species ecology, but there has been less focus on form and function of soft tissues. This is particularly true for the digestive system, which varies in size and complexity across Class Mammalia and plays a major role in the energetics of species. To guide more effective utilization of gastrointestinal (GI) morphology as a functional proxy in small mammal ecology, we examined how GI tracts (lengths and masses of four GI sections) varied within a population of deer mice (Peromyscus maniculatus) in the Southern Appalachian Mountains of North Carolina, United States. We collected samples of adult P. maniculatus monthly for 1 year and measured GI tracts to quantify variation with respect to seasonality and trophic level, providing insight into plasticity in this soft tissue trait over time. We found that season had a significant effect on the total length and wet mass of the GI tract, with January mice having the longest GI tracts and lengths being shortest in the summer. The relative shortening of the GI tract in summer corresponded with a partial trophic increase detected by stable isotope signatures. GI length and wet mass also were affected by reproduction, but males and females responded in sex-specific ways to demands of reproduction, with reproductively active males having shorter and lighter GI tracts than nonreproductively active males. Our study provides proof-of-concept for understanding population-level plasticity in a rarely collected soft tissue trait, which may also be complementary to standard craniodental measurements as a functional dietary proxy to understand mammalian ecology and community assembly.
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Affiliation(s)
- Olivia S Chapman
- Department of Biology, University of North Carolina at Greensboro, 325 McIver Street, Greensboro, North Carolina 27412, USA
| | - Bryan S McLean
- Department of Biology, University of North Carolina at Greensboro, 325 McIver Street, Greensboro, North Carolina 27412, USA
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9
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Abstract
Biodiversity is being lost at an unprecedented rate on Earth. As a first step to more effectively combat this process we need efficient methods to monitor biodiversity changes. Recent technological advance can provide powerful tools (e.g. camera traps, digital acoustic recorders, satellite imagery, social media records) that can speed up the collection of biological data. Nevertheless, the processing steps of the raw data served by these tools are still painstakingly slow. A new computer technology, deep learning based artificial intelligence, might, however, help. In this short and subjective review I oversee recent technological advances used in conservation biology, highlight problems of processing their data, shortly describe deep learning technology and show case studies of its use in conservation biology. Some of the limitations of the technology are also highlighted.
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Affiliation(s)
- Zoltán Barta
- HUN-REN-DE Behavioural Ecology Research Group, Department of Evolutionary Zoology and Humanbiology, University of Debrecen, Debrecen, Hungary.
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10
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Boyd RJ, August TA, Cooke R, Logie M, Mancini F, Powney GD, Roy DB, Turvey K, Isaac NJB. An operational workflow for producing periodic estimates of species occupancy at national scales. Biol Rev Camb Philos Soc 2023; 98:1492-1508. [PMID: 37062709 DOI: 10.1111/brv.12961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 03/31/2023] [Accepted: 04/03/2023] [Indexed: 04/18/2023]
Abstract
Policy makers require high-level summaries of biodiversity change. However, deriving such summaries from raw biodiversity data is a complex process involving several intermediary stages. In this paper, we describe an operational workflow for generating annual estimates of species occupancy at national scales from raw species occurrence data, which can be used to construct a range of policy-relevant biodiversity indicators. We describe the workflow in detail: from data acquisition, data assessment and data manipulation, through modelling, model evaluation, application and dissemination. At each stage, we draw on our experience developing and applying the workflow for almost a decade to outline the challenges that analysts might face. These challenges span many areas of ecology, taxonomy, data science, computing and statistics. In our case, the principal output of the workflow is annual estimates of occupancy, with measures of uncertainty, for over 5000 species in each of several defined 'regions' (e.g. countries, protected areas, etc.) of the UK from 1970 to 2019. This data product corresponds closely to the notion of a species distribution Essential Biodiversity Variable (EBV). Throughout the paper, we highlight methodologies that might not be applicable outside of the UK and suggest alternatives. We also highlight areas where the workflow can be improved; in particular, methods are needed to mitigate and communicate the risk of bias arising from the lack of representativeness that is typical of biodiversity data. Finally, we revisit the 'ideal' and 'minimal' criteria for species distribution EBVs laid out in previous contributions and pose some outstanding questions that should be addressed as a matter of priority. Going forward, we hope that this paper acts as a template for research groups around the world seeking to develop similar data products.
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Affiliation(s)
- Robin J Boyd
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Thomas A August
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Robert Cooke
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Mark Logie
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Francesca Mancini
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Gary D Powney
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - David B Roy
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Katharine Turvey
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Nick J B Isaac
- UK Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
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11
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Gregory RD, Eaton MA, Burfield IJ, Grice PV, Howard C, Klvaňová A, Noble D, Šilarová E, Staneva A, Stephens PA, Willis SG, Woodward ID, Burns F. Drivers of the changing abundance of European birds at two spatial scales. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220198. [PMID: 37246375 DOI: 10.1098/rstb.2022.0198] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 01/16/2023] [Indexed: 05/30/2023] Open
Abstract
Detecting biodiversity change and identifying its causes is challenging because biodiversity is multifaceted and temporal data often contain bias. Here, we model temporal change in species' abundance and biomass by using extensive data describing the population sizes and trends of native breeding birds in the United Kingdom (UK) and the European Union (EU). In addition, we explore how species' population trends vary with species' traits. We demonstrate significant change in the bird assemblages of the UK and EU, with substantial reductions in overall bird abundance and losses concentrated in a relatively small number of abundant and smaller sized species. By contrast, rarer and larger birds had generally fared better. Simultaneously, overall avian biomass had increased very slightly in the UK and was stable in the EU, indicating a change in community structure. Abundance trends across species were positively correlated with species' body mass and with trends in climate suitability, and varied with species' abundance, migration strategy and niche associations linked to diet. Our work highlights how changes in biodiversity cannot be captured easily by a single number; care is required when measuring and interpreting biodiversity change given that different metrics can provide very different insights. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.
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Affiliation(s)
- Richard D Gregory
- RSPB Centre for Conservation Science, Sandy, Befordshire SG19 2DL, UK
- Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK
| | | | - Ian J Burfield
- BirdLife International, Cambridge, Cambridgeshire CB2 3QZ, UK
| | - Philip V Grice
- Chief Scientist Directorate, Natural England, Peterborough PE2 8YY, UK
| | - Christine Howard
- Conservation Ecology Group, Department of Biosciences, Durham University, South Road, Durham, County Durham DH1 3LE, UK
| | - Alena Klvaňová
- Czech Society for Ornithology, 150 00 Prague 5, Czech Republic
| | - David Noble
- British Trust for Ornithology, The Nunnery, Thetford, Norfolk IP24 2PU, UK
| | - Eva Šilarová
- Czech Society for Ornithology, 150 00 Prague 5, Czech Republic
| | - Anna Staneva
- BirdLife International, Cambridge, Cambridgeshire CB2 3QZ, UK
| | - Philip A Stephens
- Conservation Ecology Group, Department of Biosciences, Durham University, South Road, Durham, County Durham DH1 3LE, UK
| | - Stephen G Willis
- Conservation Ecology Group, Department of Biosciences, Durham University, South Road, Durham, County Durham DH1 3LE, UK
| | - Ian D Woodward
- British Trust for Ornithology, The Nunnery, Thetford, Norfolk IP24 2PU, UK
| | - Fiona Burns
- RSPB Centre for Conservation Science, Cambridge CB2 3QZ, UK
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12
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Cheeseman T, Southerland K, Acebes JM, Audley K, Barlow J, Bejder L, Birdsall C, Bradford AL, Byington JK, Calambokidis J, Cartwright R, Cedarleaf J, Chavez AJG, Currie JJ, De Weerdt J, Doe N, Doniol-Valcroze T, Dracott K, Filatova O, Finn R, Flynn K, Ford JKB, Frisch-Jordán A, Gabriele CM, Goodwin B, Hayslip C, Hildering J, Hill MC, Jacobsen JK, Jiménez-López ME, Jones M, Kobayashi N, Lyman E, Malleson M, Mamaev E, Martínez Loustalot P, Masterman A, Matkin C, McMillan CJ, Moore JE, Moran JR, Neilson JL, Newell H, Okabe H, Olio M, Pack AA, Palacios DM, Pearson HC, Quintana-Rizzo E, Ramírez Barragán RF, Ransome N, Rosales-Nanduca H, Sharpe F, Shaw T, Stack SH, Staniland I, Straley J, Szabo A, Teerlink S, Titova O, Urban R J, van Aswegen M, de Morais MV, von Ziegesar O, Witteveen B, Wray J, Yano KM, Zwiefelhofer D, Clapham P. A collaborative and near-comprehensive North Pacific humpback whale photo-ID dataset. Sci Rep 2023; 13:10237. [PMID: 37353581 PMCID: PMC10290149 DOI: 10.1038/s41598-023-36928-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 06/12/2023] [Indexed: 06/25/2023] Open
Abstract
We present an ocean-basin-scale dataset that includes tail fluke photographic identification (photo-ID) and encounter data for most living individual humpback whales (Megaptera novaeangliae) in the North Pacific Ocean. The dataset was built through a broad collaboration combining 39 separate curated photo-ID catalogs, supplemented with community science data. Data from throughout the North Pacific were aggregated into 13 regions, including six breeding regions, six feeding regions, and one migratory corridor. All images were compared with minimal pre-processing using a recently developed image recognition algorithm based on machine learning through artificial intelligence; this system is capable of rapidly detecting matches between individuals with an estimated 97-99% accuracy. For the 2001-2021 study period, a total of 27,956 unique individuals were documented in 157,350 encounters. Each individual was encountered, on average, in 5.6 sampling periods (i.e., breeding and feeding seasons), with an annual average of 87% of whales encountered in more than one season. The combined dataset and image recognition tool represents a living and accessible resource for collaborative, basin-wide studies of a keystone marine mammal in a time of rapid ecological change.
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Affiliation(s)
- Ted Cheeseman
- Happywhale, Santa Cruz, California, USA.
- Southern Cross University, Lismore, NSW, Australia.
| | | | | | | | - Jay Barlow
- NOAA Southwest Fisheries Science Center, San Diego, California, USA
| | - Lars Bejder
- Hawai'i Institute of Marine Biology, University of Hawai'i at Manoa, Kaneohe, Hawai'i, USA
| | - Caitlin Birdsall
- Marine Education and Research Society, Port McNeill, British Columbia, Canada
- Ocean Wise, Vancouver, British Columbia, Canada
| | - Amanda L Bradford
- NOAA Fisheries Pacific Islands Fisheries Science Center, Honolulu, Hawai'i, USA
| | - Josie K Byington
- Pacific Wildlife Foundation, Port Moody, British Columbia, Canada
| | | | | | | | | | | | | | - Nicole Doe
- Marine Education and Research Society, Port McNeill, British Columbia, Canada
| | | | - Karina Dracott
- Ocean Wise, Vancouver, British Columbia, Canada
- North Coast Cetacean Society, Hartley Bay, British Columbia, Canada
| | | | - Rachel Finn
- NOAA Hawaiian Islands Humpback Whale National Marine Sanctuary, Kihei, Maui, Hawaii, USA
| | | | - John K B Ford
- Fisheries and Oceans Canada, Nanaimo, British Columbia, Canada
| | | | - Christine M Gabriele
- Glacier Bay National Park and Preserve, Gustavus, Alaska, USA
- Hawai'i Marine Mammal Consortium, Kamuela, Hawai'i, USA
| | - Beth Goodwin
- Eye of the Whale Marine Mammal Research, Kamuela, Hawai'i, USA
| | - Craig Hayslip
- Marine Mammal Institute, Oregon State University, Newport, Oregon, USA
| | - Jackie Hildering
- Marine Education and Research Society, Port McNeill, British Columbia, Canada
| | - Marie C Hill
- NOAA Fisheries Pacific Islands Fisheries Science Center, Honolulu, Hawai'i, USA
- Cooperative Institution of Marine and Atmospheric Research, Research Corporation of the University of Hawai'i, Honolulu, Hawai'i, USA
| | | | - M Esther Jiménez-López
- Departamento Académico de Ingeniería en Pesquerías, Universidad Autónoma de Baja California Sur, La Paz, Baja California Sur, México
| | | | | | - Edward Lyman
- NOAA Hawaiian Islands Humpback Whale National Marine Sanctuary, Kihei, Maui, Hawaii, USA
| | - Mark Malleson
- Humpback Whales of the Salish Sea, Duncan, British Columbia, Canada
| | - Evgeny Mamaev
- Commander Islands National Park, Kamchatka Krai, Russian Federation
| | | | | | | | - Christie J McMillan
- Marine Education and Research Society, Port McNeill, British Columbia, Canada
- Fisheries and Oceans Canada, Nanaimo, British Columbia, Canada
| | - Jeff E Moore
- NOAA Southwest Fisheries Science Center, San Diego, California, USA
| | - John R Moran
- NOAA Alaska Fisheries Science Center, Juneau, Alaska, USA
| | - Janet L Neilson
- Glacier Bay National Park and Preserve, Gustavus, Alaska, USA
| | | | - Haruna Okabe
- Okinawa Churashima Foundation, Kunigami-gun, Japan
| | | | - Adam A Pack
- University of Hawai'i at Hilo, Hilo, Hawai'i, USA
- The Dolphin Institute, Hilo, Hawai'i, USA
| | - Daniel M Palacios
- Marine Mammal Institute, Oregon State University, Newport, Oregon, USA
- Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Newport, Oregon, USA
| | | | | | | | | | - Hiram Rosales-Nanduca
- Departamento Académico de Ingeniería en Pesquerías, Universidad Autónoma de Baja California Sur, La Paz, Baja California Sur, México
| | - Fred Sharpe
- Alaska Whale Foundation, Petersburg, Alaska, USA
| | - Tasli Shaw
- Humpback Whales of the Salish Sea, Duncan, British Columbia, Canada
| | | | | | - Jan Straley
- University of Alaska Southeast, Juneau, Alaska, USA
| | - Andrew Szabo
- Alaska Whale Foundation, Petersburg, Alaska, USA
| | - Suzie Teerlink
- NOAA Fisheries Alaska Regional Office, Juneau, Alaska, USA
| | - Olga Titova
- Severtsov Institute of Ecology and Evolution, Moscow, Russian Federation
| | - Jorge Urban R
- Universidad Autónoma de Baja California Sur, La Paz, Mexico
| | | | | | | | | | - Janie Wray
- North Coast Cetacean Society, Hartley Bay, British Columbia, Canada
| | - Kymberly M Yano
- NOAA Fisheries Pacific Islands Fisheries Science Center, Honolulu, Hawai'i, USA
- Cooperative Institution of Marine and Atmospheric Research, Research Corporation of the University of Hawai'i, Honolulu, Hawai'i, USA
| | | | - Phil Clapham
- Seastar Scientific, Vashon Island, Washington, USA
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13
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Zhang H, Mächler E, Morsdorf F, Niklaus PA, Schaepman ME, Altermatt F. A spatial fingerprint of land-water linkage of biodiversity uncovered by remote sensing and environmental DNA. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 867:161365. [PMID: 36634788 DOI: 10.1016/j.scitotenv.2022.161365] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 12/06/2022] [Accepted: 12/30/2022] [Indexed: 06/17/2023]
Abstract
Aquatic and terrestrial ecosystems are tightly connected via spatial flows of organisms and resources. Such land-water linkages integrate biodiversity across ecosystems and suggest a spatial association of aquatic and terrestrial biodiversity. However, knowledge about the extent of this spatial association is limited. By combining satellite remote sensing (RS) and environmental DNA (eDNA) extraction from river water across a 740-km2 mountainous catchment, we identify a characteristic spatial land-water fingerprint. Specifically, we find a spatial association of riverine eDNA diversity with RS spectral diversity of terrestrial ecosystems upstream, peaking at a 400 m distance yet still detectable up to a 2.0 km radius. Our findings show that biodiversity patterns in rivers can be linked to the functional diversity of surrounding terrestrial ecosystems and provide a dominant scale at which these linkages are strongest. Such spatially explicit information is necessary for a functional understanding of land-water linkages.
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Affiliation(s)
- Heng Zhang
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland; Eawag, Swiss Federal Institute of Aquatic Science and Technology, Department of Aquatic Ecology, Überlandstrasse 133, CH-8600 Dübendorf, Switzerland.
| | - Elvira Mächler
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland; Eawag, Swiss Federal Institute of Aquatic Science and Technology, Department of Aquatic Ecology, Überlandstrasse 133, CH-8600 Dübendorf, Switzerland
| | - Felix Morsdorf
- Remote Sensing Laboratories, Department of Geography, University of Zurich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland
| | - Pascal A Niklaus
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland
| | - Michael E Schaepman
- Remote Sensing Laboratories, Department of Geography, University of Zurich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland
| | - Florian Altermatt
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland; Eawag, Swiss Federal Institute of Aquatic Science and Technology, Department of Aquatic Ecology, Überlandstrasse 133, CH-8600 Dübendorf, Switzerland.
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14
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Cervantes F, Altwegg R, Strobbe F, Skowno A, Visser V, Brooks M, Stojanov Y, Harebottle DM, Job N. BIRDIE: A data pipeline to inform wetland and waterbird conservation at multiple scales. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2023.1131120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023] Open
Abstract
IntroductionEfforts to collect ecological data have intensified over the last decade. This is especially true for freshwater habitats, which are among the most impacted by human activity and yet lagging behind in terms of data availability. Now, to support conservation programmes and management decisions, these data need to be analyzed and interpreted; a process that can be complex and time consuming. The South African Biodiversity Data Pipeline for Wetlands and Waterbirds (BIRDIE) aims to help fast and efficient information uptake, bridging the gap between raw ecological datasets and the information final users need.MethodsBIRDIE is a full data pipeline that takes up raw data, and estimates indicators related to waterbird populations, while keeping track of their associated uncertainty. At present, we focus on the assessment of species abundance and distribution in South Africa using two citizen-science bird monitoring datasets, namely: the African Bird Atlas Project and the Coordinated Waterbird Counts. These data are analyzed with occupancy and state-space models, respectively. In addition, a suite of environmental layers help contextualize waterbird population indicators, and link these to the ecological condition of the supporting wetlands. Both data and estimated indicators are accessible to end users through an online portal and web services.Results and discussionWe have designed a modular system that includes tasks, such as: data cleaning, statistical analysis, diagnostics, and computation of indicators. Envisioned users of BIRDIE include government officials, conservation managers, researchers and the general public, all of whom have been engaged throughout the project. Acknowledging that conservation programmes run at multiple spatial and temporal scales, we have developed a granular framework in which indicators are estimated at small scales, and then these are aggregated to compute similar indicators at broader scales. Thus, the online portal is designed to provide spatial and temporal visualization of the indicators using maps, time series and pre-compiled reports for species, sites and conservation programmes. In the future, we aim to expand the geographical coverage of the pipeline to other African countries, and develop more indicators specific to the ecological structure and function of wetlands.
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15
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Tsuji S, Inui R, Nakao R, Miyazono S, Saito M, Kono T, Akamatsu Y. Quantitative environmental DNA metabarcoding shows high potential as a novel approach to quantitatively assess fish community. Sci Rep 2022; 12:21524. [PMID: 36513686 PMCID: PMC9747787 DOI: 10.1038/s41598-022-25274-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
The simultaneous conservation of species richness and evenness is important to effectively reduce biodiversity loss and keep ecosystem health. Environmental DNA (eDNA) metabarcoding has been used as a powerful tool for identifying community composition, but it does not necessarily provide quantitative information due to several methodological limitations. Thus, the quantification of eDNA through metabarcoding is an important frontier of eDNA-based biomonitoring. Particularly, the qMiSeq approach has recently been developed as a quantitative metabarcoding method and has attracted much attention due to its usefulness. The aim here was to evaluate the performance of the qMiSeq approach as a quantitative monitoring tool for fish communities by comparing the quantified eDNA concentrations with the results of fish capture surveys. The eDNA water sampling and the capture surveys using the electrical shocker were conducted at a total of 21 sites in four rivers in Japan. As a result, we found significant positive relationships between the eDNA concentrations of each species quantified by qMiSeq and both the abundance and biomass of each captured taxon at each site. Furthermore, for seven out of eleven taxa, a significant positive relationship was observed between quantified DNA concentrations by sample and the abundance and/or biomass. In total, our results demonstrated that eDNA metabarcoding with the qMiSeq approach is a suitable and useful tool for quantitative monitoring of fish communities. Due to the simplicity of the eDNA analysis, the eDNA metabarcoding with qMiSeq approach would promote further growth of quantitative monitoring of biodiversity.
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Affiliation(s)
- Satsuki Tsuji
- grid.258799.80000 0004 0372 2033Graduate School of Science, Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-Ku, Kyoto, 606–8502 Japan ,grid.268397.10000 0001 0660 7960Graduate School of Science and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, 755–8611 Japan
| | - Ryutei Inui
- grid.418051.90000 0000 8774 3245Faculty of Socio-Environmental Studies, Fukuoka Institute of Technology, Wajiro-Higashi, Higashi-Ku, Fukuoka, 811–0295 Japan
| | - Ryohei Nakao
- grid.268397.10000 0001 0660 7960Graduate School of Science and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, 755–8611 Japan
| | - Seiji Miyazono
- grid.268397.10000 0001 0660 7960Graduate School of Science and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, 755–8611 Japan
| | - Minoru Saito
- grid.268397.10000 0001 0660 7960Graduate School of Science and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, 755–8611 Japan ,grid.452611.50000 0001 2107 8171Fisheries Division, Japan International Research Center for Agricultural Sciences, 1-1, Ohwashi, Tsukuba, Ibaraki 305–8686 Japan
| | - Takanori Kono
- grid.268397.10000 0001 0660 7960Graduate School of Science and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, 755–8611 Japan ,grid.472015.50000 0000 9513 8387Aqua Restoration Research Center, Public Works Research Institute, National Research and Development Agency, Kawashima, Kasada-Machi, Kakamigahara, Gifu, 501–6021 Japan
| | - Yoshihisa Akamatsu
- grid.268397.10000 0001 0660 7960Graduate School of Science and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, 755–8611 Japan
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Shin N, Saitoh TM, Takeuchi Y, Miura T, Aiba M, Kurokawa H, Onoda Y, Ichii K, Nasahara KN, Suzuki R, Nakashizuka T, Muraoka H. Review: Monitoring of land cover changes and plant phenology by remote‐sensing in East Asia. Ecol Res 2022. [DOI: 10.1111/1440-1703.12371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Nagai Shin
- Research Institute for Global Change Japan Agency for Marine‐Earth Science and Technology Yokohama Japan
- River Basin Research Centre Gifu University Gifu Japan
| | | | - Yayoi Takeuchi
- Biodiversity Division National Institute for Environmental Studies Tsukuba Japan
| | - Tomoaki Miura
- Research Institute for Global Change Japan Agency for Marine‐Earth Science and Technology Yokohama Japan
- Department of Natural Resources and Environmental Management University of Hawaii at Manoa Honolulu Hawaii USA
| | - Masahiro Aiba
- Research Institute for Humanity and Nature Kyoto Japan
| | - Hiroko Kurokawa
- Department of Forest Vegetation Forestry and Forest Products Research Institute Tsukuba Japan
| | - Yusuke Onoda
- Faculty of Graduate School of Agriculture Kyoto University Kyoto Japan
| | - Kazuhito Ichii
- Center for Environmental Remote Sensing Chiba University Chiba Japan
| | | | - Rikie Suzuki
- Research Institute for Global Change Japan Agency for Marine‐Earth Science and Technology Yokohama Japan
| | - Tohru Nakashizuka
- Department of Forest Vegetation Forestry and Forest Products Research Institute Tsukuba Japan
| | - Hiroyuki Muraoka
- River Basin Research Centre Gifu University Gifu Japan
- Biodiversity Division National Institute for Environmental Studies Tsukuba Japan
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17
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Huang S, Yoshitake K, Watabe S, Asakawa S. Environmental DNA study on aquatic ecosystem monitoring and management: Recent advances and prospects. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 323:116310. [PMID: 36261997 DOI: 10.1016/j.jenvman.2022.116310] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
Environmental DNA (eDNA) is organismal DNA that can be detected in the environment and is derived from cellular material of organisms shed into aquatic or terrestrial environments. It can be sampled and monitored using molecular methods, which is important for the early detection of invasive and native species as well as the discovery of rare and cryptic species. While few reviews have summarized the latest findings on eDNA for most aquatic animal categories in the aquatic ecosystem, especially for aquatic eDNA processing and application. In the present review, we first performed a bibliometric network analysis of eDNA studies on aquatic animals. Subsequently, we summarized the abiotic and biotic factors affecting aquatic eDNA occurrence. We also systematically discussed the relevant experiments and analyses of aquatic eDNA from various aquatic organisms, including fish, molluscans, crustaceans, amphibians, and reptiles. Subsequently, we discussed the major achievements of eDNA application in studies on the aquatic ecosystem and environment. The application of eDNA will provide an entirely new paradigm for biodiversity conservation, environment monitoring, and aquatic species management at a global scale.
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Affiliation(s)
- Songqian Huang
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, College of Fisheries and Life Sciences, Shanghai Ocean University, Shanghai, 201306, China; Key Laboratory of Freshwater Aquatic Genetic Resources, Ministry of Agriculture, College of Fisheries and Life Sciences, Shanghai Ocean University, Shanghai, 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai, 200120, China; Department of Aquatic Bioscience, Graduate School of Agricultural and Life Science, The University of Tokyo, Tokyo, 113-8657, Japan.
| | - Kazutoshi Yoshitake
- Department of Aquatic Bioscience, Graduate School of Agricultural and Life Science, The University of Tokyo, Tokyo, 113-8657, Japan
| | - Shugo Watabe
- School of Marine Biosciences, Kitasato University, Minami-ku, Sagamihara, Kanagawa, 252-0313, Japan
| | - Shuichi Asakawa
- Department of Aquatic Bioscience, Graduate School of Agricultural and Life Science, The University of Tokyo, Tokyo, 113-8657, Japan.
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Cordeiro CA, Aued AW, Barros F, Bastos AC, Bender M, Mendes TC, Creed JC, Cruz IC, Dias MS, Fernandes LD, Coutinho R, Gonçalves JE, Floeter SR, Mello-Fonseca J, Freire AS, Gherardi DF, Gomes LE, Lacerda F, Martins RL, Longo GO, Mazzuco AC, Menezes R, Muelbert JH, Paranhos R, Quimbayo JP, Valentin JL, Ferreira CE. Long-term monitoring projects of Brazilian marine and coastal ecosystems. PeerJ 2022; 10:e14313. [PMID: 36389402 PMCID: PMC9653053 DOI: 10.7717/peerj.14313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/06/2022] [Indexed: 11/11/2022] Open
Abstract
Biodiversity assessment is a mandatory task for sustainable and adaptive management for the next decade, and long-term ecological monitoring programs are a cornerstone for understanding changes in ecosystems. The Brazilian Long-Term Ecological Research Program (PELD) is an integrated effort model supported by public funds that finance ecological studies at 34 locations. By interviewing and compiling data from project coordinators, we assessed monitoring efforts, targeting biological groups and scientific production from nine PELD projects encompassing coastal lagoons to mesophotic reefs and oceanic islands. Reef environments and fish groups were the most often studied within the long-term projects. PELD projects covered priority areas for conservation but missed sensitive areas close to large cities, as well as underrepresenting ecosystems on the North and Northeast Brazilian coast. Long-term monitoring projects in marine and coastal environments in Brazil are recent (<5 years), not yet integrated as a network, but scientifically productive with considerable relevance for academic and human resources training. Scientific production increased exponentially with project age, despite interruption and shortage of funding during their history. From our diagnosis, we recommend some actions to fill in observed gaps, such as: enhancing projects' collaboration and integration; focusing on priority regions for new projects; broadening the scope of monitored variables; and, maintenance of funding for existing projects.
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Affiliation(s)
- Cesar A.M.M. Cordeiro
- PELD Ilhas Oceânicas Brasileiras, Laboratório de Ciências Ambientais, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Rio de Janeiro, Brazil
| | - Anaide W. Aued
- PELD Ilhas Oceânicas Brasileiras, Memorial University of Newfoundland, St John’s, Newfoundland, Canada
| | - Francisco Barros
- Laboratório de Ecologia Bentônica, IBIO & CIEnAM & INCT IN-TREE, Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Alex C. Bastos
- PELD Abrolhos, Departamento de Oceanografia, Universidade Federal do Espírito Santo, Vitória, Espírito Santo, Brazil
| | - Mariana Bender
- PELD Ilhas Oceânicas Brasileiras, Marine Macroecology and Conservation Lab, Universidade Federal de Santa Maria, Santa Maria, Rio Grande do Sul, Brazil
| | - Thiago C. Mendes
- PELD Ilhas Oceânicas Brasileiras, Laboratório de Ecologia e Conservação de Ambientes Recitais, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil,PELD Ilhas Oceânicas Brasileiras, Instituto do Mar, Universidade Federal de São Paulo, Santos, São Paulo, Brazil
| | - Joel C. Creed
- Departamento de Ecologia, Instituto de Biologia Roberto Alcântara Gomes, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Igor C.S. Cruz
- Laboratório de Oceanografia Biológica, Departamento de Oceanografia, Instituto de Geociências da Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Murilo S. Dias
- PELD Ilhas Oceânicas Brasileiras, Departamento de Ecologia, Universidade de Brasília, Brasília, Distrito Federal, Brazil
| | - Lohengrin D.A. Fernandes
- PELD Ressurgência de Cabo Frio, Instituto de Estudos do Mar Almirante Paulo Moreira (IEAPM), Arraial do Cabo, Rio de Janeiro, Brazil
| | - Ricardo Coutinho
- PELD Ressurgência de Cabo Frio, Instituto de Estudos do Mar Almirante Paulo Moreira (IEAPM), Arraial do Cabo, Rio de Janeiro, Brazil
| | - José E.A. Gonçalves
- PELD Ressurgência de Cabo Frio, Instituto de Estudos do Mar Almirante Paulo Moreira (IEAPM), Arraial do Cabo, Rio de Janeiro, Brazil
| | - Sergio R. Floeter
- PELD Ilhas Oceânicas Brasileiras, Marine Macroecology and Biogeography Lab, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Juliana Mello-Fonseca
- PELD Ilhas Oceânicas Brasileiras, Laboratório de Ecologia e Conservação de Ambientes Recitais, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil
| | - Andrea S. Freire
- PELD Ilhas Oceânicas Brasileiras, Laboratório de Crustáceos e Plâncton, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Douglas F.M. Gherardi
- PELD Ilhas Oceânicas Brasileiras, Laboratory of Ocean and Atmosphere Studies (LOA), Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São José dos Campos, São Paulo, Brazil
| | - Luiz E.O. Gomes
- PELD Habitats Costeiros do Espírito Santo, Grupo de Ecologia Bêntica, Departamento de Oceanografia e Ecologia, Universidade Federal do Espírito Santo, Vitória, Espírito Santo, Brazil
| | - Fabíola Lacerda
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brasília, Distrito Federal, Brazil
| | - Rodrigo L. Martins
- PELD Restingas e Lagoas Costeiras do norte do Estado do Rio de Janeiro, Instituto de Biodiversidade e Sustentabilidade (NUPEM), Universidade Federal do Rio de Janeiro, Macaé, Rio de Janeiro, Brazil
| | - Guilherme O. Longo
- PELD Ilhas Oceânicas Brasileiras, Laboratório de Ecologia Marinha, Departamento de Oceanografia e Limnologia, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Ana Carolina Mazzuco
- PELD Habitats Costeiros do Espírito Santo, Grupo de Ecologia Bêntica, Departamento de Oceanografia e Ecologia, Universidade Federal do Espírito Santo, Vitória, Espírito Santo, Brazil
| | - Rafael Menezes
- PELD Ressurgência de Cabo Frio, Instituto de Estudos do Mar Almirante Paulo Moreira (IEAPM), Arraial do Cabo, Rio de Janeiro, Brazil
| | - José H. Muelbert
- PELD Estuário da Lagoa dos Patos e Costa Marinha Adjacente, Instituto de Oceanografia, Universidade Federal do Rio Grande, Rio Grande, Rio Grande do Sul, Brazil
| | - Rodolfo Paranhos
- PELD Baía de Guanabara, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Juan P. Quimbayo
- PELD Ilhas Oceânicas Brasileiras, Centro de Biologia Marinha, Universidade de São Paulo, São Sebastião, São Paulo, Brazil
| | - Jean L. Valentin
- PELD Baía de Guanabara, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Carlos E.L. Ferreira
- PELD Ilhas Oceânicas Brasileiras, Laboratório de Ecologia e Conservação de Ambientes Recitais, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil
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Lara W, Londoño MC, Gonzalez I, Gutierrez‐Velez VH. ecochange: An R‐package to derive ecosystem change indicators from freely available earth observation products. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Wilson Lara
- Department of Geography and Urban Studies Temple University Philadelphia Pennsylvania USA
- Forest Management and Technology, Division of Forest and Forest Resources Norwegian Institute of Bioeconomy Research Steinkjer Norway
| | - Maria C. Londoño
- The Alexander von Humboldt Institute for Research on Biological Resources Bogotá Colombia
| | - Ivan Gonzalez
- School of Informatics, Computing, and Cyber Systems (SICCS) Northern Arizona University Flagstaff Arizona USA
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20
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Measuring the Impact of Conservation: The Growing Importance of Monitoring Fauna, Flora and Funga. DIVERSITY 2022. [DOI: 10.3390/d14100824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Many stakeholders, from governments to civil society to businesses, lack the data they need to make informed decisions on biodiversity, jeopardising efforts to conserve, restore and sustainably manage nature. Here we review the importance of enhancing biodiversity monitoring, assess the challenges involved and identify potential solutions. Capacity for biodiversity monitoring needs to be enhanced urgently, especially in poorer, high-biodiversity countries where data gaps are disproportionately high. Modern tools and technologies, including remote sensing, bioacoustics and environmental DNA, should be used at larger scales to fill taxonomic and geographic data gaps, especially in the tropics, in marine and freshwater biomes, and for plants, fungi and invertebrates. Stakeholders need to follow best monitoring practices, adopting appropriate indicators and using counterfactual approaches to measure and attribute outcomes and impacts. Data should be made openly and freely available. Companies need to invest in collecting the data required to enhance sustainability in their operations and supply chains. With governments soon to commit to the post-2020 global biodiversity framework, the time is right to make a concerted push on monitoring. However, action at scale is needed now if we are to enhance results-based management adequately to conserve the biodiversity and ecosystem services we all depend on.
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21
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Alagador D, Cerdeira JO. Operations research applicability in spatial conservation planning. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 315:115172. [PMID: 35525048 DOI: 10.1016/j.jenvman.2022.115172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/12/2022] [Accepted: 04/23/2022] [Indexed: 06/14/2023]
Abstract
A large fraction of the current environmental crisis derives from the large rates of human-driven biodiversity loss. Biodiversity conservation questions human practices towards biodiversity and, therefore, largely conflicts with ordinary societal aspirations. Decisions on the location of protected areas, one of the most convincing conservation tools, reflect such a competitive endeavor. Operations Research (OR) brings a set of analytical models and tools capable of resolving the conflicting interests between ecology and economy. Recent technological advances have boosted the size and variety of data available to planners, thus challenging conventional approaches bounded on optimized solutions. New models and methods are needed to use such a massive amount of data in integrative schemes addressing a large variety of concerns. This study provides an overview on the past, present and future challenges that characterize spatial conservation models supported by OR. We discuss the progress of OR models and methods in spatial conservation planning and how those models may be optimized through sophisticated algorithms and computational tools. Moreover, we anticipate possible panoramas of modern spatial conservation studies supported by OR and we explore possible avenues for the design of optimized interdisciplinary collaborative platforms in the era of Big Data, through consortia where distinct players with different motivations and services meet. By enlarging the spatial, temporal, taxonomic and societal horizons of biodiversity conservation, planners navigate around multiple socioecological/environmental equilibria and are able to decide on cost-effective strategies to improve biodiversity persistence under complex environments.
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Affiliation(s)
- Diogo Alagador
- Biodiversity Chair, Institute for Advanced Studies and Research, Universidade de Évora, Rua Joaquim Henrique da Fonseca, Casa Cordovil, 2°, 7000-890, Évora, Portugal; MED - Mediterranean Institute for Agriculture, Environment and Development, CHANGE - Global Change and Sustainability Institute, Universidade de Évora, Évora, Portugal.
| | - Jorge Orestes Cerdeira
- Department of Mathematics, Faculdade de Ciências e Tecnologia da Universidade NOVA de Lisboa, Quinta da Torre, 282 -516, Costa da Caparica, Portugal; Centre for Mathematics and Applications, Faculdade de Ciências e Tecnologia da Universidade NOVA de Lisboa, Quinta da Torre, 282 -516, Costa da Caparica, Portugal.
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22
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Boyd RJ, Powney GD, Burns F, Danet A, Duchenne F, Grainger MJ, Jarvis SG, Martin G, Nilsen EB, Porcher E, Stewart GB, Wilson OJ, Pescott OL. ROBITT: A tool for assessing the risk-of-bias in studies of temporal trends in ecology. Methods Ecol Evol 2022; 13:1497-1507. [PMID: 36250156 PMCID: PMC9541136 DOI: 10.1111/2041-210x.13857] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/21/2022] [Indexed: 02/05/2023]
Abstract
Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete 'risk-of-bias' assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology.We introduce ROBITT, a structured tool for assessing the 'Risk-Of-Bias In studies of Temporal Trends in ecology'. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken.Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis.We propose that researchers should be strongly encouraged to include a ROBITT assessment when publishing studies of biodiversity trends, especially when using aggregated data. This will help researchers to structure their thinking, clearly acknowledge potential sampling issues, highlight where expert consultation is required and provide an opportunity to describe data checks that might go unreported. ROBITT will also enable reviewers, editors and readers to establish how well research conclusions are supported given a dataset combined with some analytical approach. In turn, it should strengthen evidence-based policy and practice, reduce differing interpretations of data and provide a clearer picture of the uncertainties associated with our understanding of reality.
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Affiliation(s)
| | | | - Fiona Burns
- RSPB Centre for Conservation ScienceCambridgeUK
| | - Alain Danet
- Centre d'Ecologie et des Sciences de la Conservation (CESCO), Muséum national d'Histoire naturelle, CNRSSorbonne UniversitéParisFrance
| | - François Duchenne
- Swiss Federal Institute for ForestSnow and Landscape Research (WSL)BirmensdorfSwitzerland
| | | | - Susan G. Jarvis
- UK Centre for Ecology & HydrologyLancaster Environment CentreLancasterUK
| | - Gabrielle Martin
- Laboratoire EDB Évolution & Diversité Biologique UMR 5174Université de Toulouse, Université Toulouse 3 Paul Sabatier, UPS, CNRS, IRDToulouseFrance
| | - Erlend B. Nilsen
- Norwegian Institute for Nature Research (NINA)TrondheimNorway
- Faculty of Biosciences and AquacultureNord UniversitySteinkjerNorway
| | - Emmanuelle Porcher
- Centre d'Ecologie et des Sciences de la Conservation (CESCO), Muséum national d'Histoire naturelle, CNRSSorbonne UniversitéParisFrance
| | - Gavin B. Stewart
- Evidence Synthesis Lab, School of Natural and Environmental ScienceUniversity of NewcastleNewcastle‐upon‐TyneUK
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23
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Cavender-Bares J, Schneider FD, Santos MJ, Armstrong A, Carnaval A, Dahlin KM, Fatoyinbo L, Hurtt GC, Schimel D, Townsend PA, Ustin SL, Wang Z, Wilson AM. Integrating remote sensing with ecology and evolution to advance biodiversity conservation. Nat Ecol Evol 2022; 6:506-519. [PMID: 35332280 DOI: 10.1038/s41559-022-01702-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 02/10/2022] [Indexed: 12/31/2022]
Abstract
Remote sensing has transformed the monitoring of life on Earth by revealing spatial and temporal dimensions of biological diversity through structural, compositional and functional measurements of ecosystems. Yet, many aspects of Earth's biodiversity are not directly quantified by reflected or emitted photons. Inclusive integration of remote sensing with field-based ecology and evolution is needed to fully understand and preserve Earth's biodiversity. In this Perspective, we argue that multiple data types are necessary for almost all draft targets set by the Convention on Biological Diversity. We examine five key topics in biodiversity science that can be advanced by integrating remote sensing with in situ data collection from field sampling, experiments and laboratory studies to benefit conservation. Lowering the barriers for bringing these approaches together will require global-scale collaboration.
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Affiliation(s)
| | - Fabian D Schneider
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | - Amanda Armstrong
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Ana Carnaval
- Department of Biology, Ph.D. Program in Biology, City University of New York and The Graduate Center of CUNY, New York City, NY, USA
| | - Kyla M Dahlin
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA
| | - Lola Fatoyinbo
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - George C Hurtt
- Department of Geographical Sciences, University of Maryland, College Park, MD, USA
| | - David Schimel
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Philip A Townsend
- Department of Forest and Wildlife Ecology, Univ. of Wisconsin-Madison, Madison, WI, USA
| | - Susan L Ustin
- Department of Land, Air and Water Resources and the John Muir Institute of the Environment, University of California, Davis, CA, USA
| | - Zhihui Wang
- Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China
| | - Adam M Wilson
- Department of Geography, University at Buffalo, Buffalo, NY, USA
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24
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Ribeiro BR, Velazco SJE, Guidoni‐Martins K, Tessarolo G, Jardim L, Bachman SP, Loyola R. bdc
: A toolkit for standardizing, integrating, and cleaning biodiversity data. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13868] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Bruno R. Ribeiro
- Programa de Pós‐graduação em Ecologia e Evolução, Universidade Federal de Goiás, Goiânia Goiás Brazil
| | - Santigo José Elías Velazco
- Department of Botany and Plant Sciences University of California ‐ Riverside California USA
- Instituto de Biología Subtropical, Universidad Nacional de Misiones ‐ CONICET Puerto Iguazú Misiones Argentina
- Programa de Pós‐Graduação em Biodiversidade Neotropical, Universidade Federal da Integração Latino‐Americana (UNILA), Foz do Iguaçu Paraná Brazil
| | - Karlo Guidoni‐Martins
- Programa de Pós‐graduação em Ecologia e Evolução, Universidade Federal de Goiás, Goiânia Goiás Brazil
| | - Geiziane Tessarolo
- Universidade Estadual de Goiás, UEG, Campus de Ciências Exatas e Tecnológicas ‐ CCET, Anápolis Goiás Brazil
| | - Lucas Jardim
- Instituto Nacional de Ciência e Tecnologia em Ecologia, Evolução e Conservação da Biodiversidade, Universidade Federal de Goiás, Goiânia Goiás Brazil
| | | | - Rafael Loyola
- Departamento de Ecologia, Universidade Federal de Goiás, Goiânia Goiás Brazil
- Fundação Brasileira para o Desenvolvimento Sustentável Rio de Janeiro Brazil
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25
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A comprehensive but practical methodology for selecting biological indicators for long-term monitoring. PLoS One 2022; 17:e0265246. [PMID: 35290396 PMCID: PMC8923439 DOI: 10.1371/journal.pone.0265246] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/27/2022] [Indexed: 11/30/2022] Open
Abstract
The selection of the many biological indicators described in scientific literature is rarely based on systematic or clear-cut processes, and often takes into account only a single or very few taxa, or even disregards the complex interactions that exist between the components of biodiversity. In certain cases, the particular context of a site–for example in the Mediterranean Basin–makes it difficult to apply the choice of indicators to other regions proposed in the literature. Therefore, the selection of appropriate methodologies for generating relevant indicators for a particular site is of crucial importance. Here, we present a simple quantitative methodology capable of incorporating multidisciplinary information for assessing and selecting appropriate methods and indicators for monitoring local biodiversity. The methodology combines several ecological levels (species, habitats, processes, and ecosystem disturbances), and embraces biological interactions and common functional guilds (detritivores, producers, herbivores, and carnivores). We followed an iterative selection procedure consisting of five phases: 1) collection focal area useful information; 2) classification of this information into interrelated datasets; 3) assessment and selection of the relevant components using a quantitative relevance index; 4) the adding of taxonomic, physiognomic and functional similarities to the relevant components; and 5) the quantitative selection of the priority indicators in the study area. To demonstrate the potential of this methodology, we took as a case study the biodiversity components and their ecological interactions present in a protected area. We show that our methodology can help select appropriate local and long-term indicators, reduce the number of components required for thorough biodiversity monitoring, and underline the importance of ecological processes.
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26
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Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro. REMOTE SENSING 2022. [DOI: 10.3390/rs14030786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.
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27
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Escamilla Molgora JM, Sedda L, Diggle PJ, Atkinson PM. A taxonomic-based joint species distribution model for presence-only data. J R Soc Interface 2022; 19:20210681. [PMID: 35193392 PMCID: PMC8864348 DOI: 10.1098/rsif.2021.0681] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/20/2022] [Indexed: 11/17/2022] Open
Abstract
Species distribution models (SDMs) are an important class of model for mapping taxa spatially and are a key tool for tackling biodiversity loss. However, most common SDMs depend on presence-absence data and, despite the accumulation and exponential growth of biological occurrence data across the globe, the available data are predominantly presence-only (i.e. they lack real absences). Although presence-only SDMs do exist, they inevitably require assumptions about absences of the considered taxa and they are specified mostly for single species and, thus, do not exploit fully the information in related taxa. This greatly limits the utility of global biodiversity databases such as GBIF. Here, we present a Bayesian-based SDM for multiple species that operates directly on presence-only data by exploiting the joint distribution between the multiple ecological processes and, crucially, identifies the sampling effort per taxa which allows inference on absences. The model was applied to two case studies. One, focusing on taxonomically diverse taxa over central Mexico and another focusing on the monophyletic family Cactacea over continental Mexico. In both cases, the model was able to identify the ecological and sampling effort processes for each taxon using only the presence observations, environmental and anthropological data.
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Affiliation(s)
- Juan M. Escamilla Molgora
- Lancaster Environment Centre
- Centre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School, Faculty of Health and Medicine, and
| | - Luigi Sedda
- Lancaster Medical School, Faculty of Health and Medicine
| | - Peter J. Diggle
- Centre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School, Faculty of Health and Medicine, and
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28
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Chen C, Brodie JF, Kays R, Davies TJ, Liu R, Fisher JT, Ahumada J, McShea W, Sheil D, Agwanda B, Andrianarisoa MH, Appleton RD, Bitariho R, Espinosa S, Grigione MM, Helgen KM, Hubbard A, Hurtado CM, Jansen PA, Jiang X, Jones A, Kalies EL, Kiebou‐Opepa C, Li X, Lima MGM, Meyer E, Miller AB, Murphy T, Piana R, Quan R, Rota CT, Rovero F, Santos F, Schuttler S, Uduman A, Bommel JK, Young H, Burton AC. Global camera trap synthesis highlights the importance of protected areas in maintaining mammal diversity. Conserv Lett 2022. [DOI: 10.1111/conl.12865] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
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Combining Citizen Science Data and Satellite Descriptors of Ecosystem Functioning to Monitor the Abundance of a Migratory Bird during the Non-Breeding Season. REMOTE SENSING 2022. [DOI: 10.3390/rs14030463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Migratory birds are particularly exposed to habitat changes in their breeding and non-breeding grounds. Remote sensing technologies offer an excellent opportunity to monitor species’ habitats from space at unprecedented spatiotemporal scales. We analyzed if remotely sensed ecosystem functioning attributes (EFAs) adequately predict the spatiotemporal variation of the Woodcock’s (Scolopax rusticola) relative abundance in southwest Europe, during autumn migration and wintering periods. We used data gathered from Woodcock monitoring through citizen science (N = 355,654 hunting trips) between 2009 and 2018. We computed a comprehensive set of EFAs on a weekly basis from three MODIS satellite products: enhanced vegetation index (EVI), tasseled cap transformation (TCT), and land surface temperature (LST). We developed generalized linear mixed models to explore the predictive power of EFAs on Woodcock’s abundance during the non-breeding season. Results showed that Woodcock abundance is correlated with spatiotemporal dynamics in primary productivity (measured through the EVI), water cycle dynamics (wetness component of TCT), and surface energy balance (LST) in both periods. Our findings underline the potential of combining citizen science and remote sensing data to monitor migratory birds throughout their life cycles—an issue of critical importance to ensure adequate habitat management in the non-breeding areas.
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30
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Cardoso D, Moonlight PW, Ramos G, Oatley G, Dudley C, Gagnon E, Queiroz LPD, Pennington RT, Särkinen TE. Defining Biologically Meaningful Biomes Through Floristic, Functional, and Phylogenetic Data. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.723558] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
While we have largely improved our understanding on what biomes are and their utility in global change ecology, conservation planning, and evolutionary biology is clear, there is no consensus on how biomes should be delimited or mapped. Existing methods emphasize different aspects of biomes, with different strengths and limitations. We introduce a novel approach to biome delimitation and mapping, based upon combining individual regionalizations derived from floristic, functional, and phylogenetic data linked to environmentally trained species distribution models. We define “core Biomes” as areas where independent regionalizations agree and “transition zones” as those whose biome identity is not corroborated by all analyses. We apply this approach to delimiting the neglected Caatinga seasonally dry tropical forest biome in northeast Brazil. We delimit the “core Caatinga” as a smaller and more climatically limited area than previous definitions, and argue it represents a floristically, functionally, and phylogenetically coherent unit within the driest parts of northeast Brazil. “Caatinga transition zones” represent a large and biologically important area, highlighting that ecological and evolutionary processes work across environmental gradients and that biomes are not categorical variables. We discuss the differences among individual regionalizations in an ecological and evolutionary context and the potential limitations and utility of individual and combined biome delimitations. Our integrated ecological and evolutionary definition of the Caatinga and associated transition zones are argued to best describe and map biologically meaningful biomes.
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31
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Townsend PA, Clare JDJ, Liu N, Stenglein JL, Anhalt‐Depies C, Van Deelen TR, Gilbert NA, Singh A, Martin KJ, Zuckerberg B. Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2021; 31:e02436. [PMID: 34374154 PMCID: PMC9286556 DOI: 10.1002/eap.2436] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 03/25/2021] [Accepted: 04/21/2021] [Indexed: 06/13/2023]
Abstract
Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.
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Affiliation(s)
- Philip A. Townsend
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - John D. J. Clare
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Nanfeng Liu
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | | | - Christine Anhalt‐Depies
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
- Wisconsin Department of Natural ResourcesMadisonWisconsin53707USA
| | - Timothy R. Van Deelen
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Neil A. Gilbert
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Aditya Singh
- Department of Agricultural and Biological EngineeringUniversity of FloridaGainesvilleFlorida32603USA
| | - Karl J. Martin
- Division of ExtensionUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Benjamin Zuckerberg
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
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32
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Brito JC, Del Barrio G, Stellmes M, Pleguezuelos JM, Saarinen J. Drivers of change and conservation needs for vertebrates in drylands: an assessment from global scale to Sahara-Sahel wetlands. THE EUROPEAN ZOOLOGICAL JOURNAL 2021. [DOI: 10.1080/24750263.2021.1991496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Affiliation(s)
- J. C. Brito
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos da, Universidade do Porto, Portugal
- Departamento de Biologia da Faculdade de Ciências da, Universidade do Porto, Portugal
| | - G. Del Barrio
- Estación Experimental de Zonas Áridas (CSIC), Ctra. Sacramento sn, La Cañada, Spain
| | - M. Stellmes
- Institute of Geographical Sciences, Remote Sensing and Geoinformatics, Freie Universität Berlin, Germany
| | - J. M. Pleguezuelos
- Departamento de Zoología, Facultad de Ciencias, Universidad de Granada, Spain
| | - J. Saarinen
- Geography Research Unit, University of Oulu, Finland
- School of Tourism and Hospitality, University of Johannesburg, South Africa
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33
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Perino A, Pereira HM, Felipe‐Lucia M, Kim H, Kühl HS, Marselle MR, Meya JN, Meyer C, Navarro LM, van Klink R, Albert G, Barratt CD, Bruelheide H, Cao Y, Chamoin A, Darbi M, Dornelas M, Eisenhauer N, Essl F, Farwig N, Förster J, Freyhof J, Geschke J, Gottschall F, Guerra C, Haase P, Hickler T, Jacob U, Kastner T, Korell L, Kühn I, Lehmann GUC, Lenzner B, Marques A, Motivans Švara E, Quintero LC, Pacheco A, Popp A, Rouet‐Leduc J, Schnabel F, Siebert J, Staude IR, Trogisch S, Švara V, Svenning J, Pe'er G, Raab K, Rakosy D, Vandewalle M, Werner AS, Wirth C, Xu H, Yu D, Zinngrebe Y, Bonn A. Biodiversity post‐2020: Closing the gap between global targets and national‐level implementation. Conserv Lett 2021. [DOI: 10.1111/conl.12848] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Affiliation(s)
- Andrea Perino
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
| | - Henrique M. Pereira
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos Universidade do Porto, Campus Agrário de Vairão, R. Padre Armando Quintas Vairão Portugal
| | - Maria Felipe‐Lucia
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Ecosystem Services, Helmholtz Center for Environmental Research ‐ UFZ Leipzig Germany
| | - HyeJin Kim
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Hjalmar S. Kühl
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Max Planck Institute for Evolutionary Anthropology Leipzig Germany
| | - Melissa R. Marselle
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Ecosystem Services, Helmholtz Center for Environmental Research ‐ UFZ Leipzig Germany
- School of Psychology University of Surrey Guildford Surrey UK
| | - Jasper N. Meya
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Economics University of Leipzig Leipzig Germany
| | - Carsten Meyer
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Geosciences and Geography Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
- Institute of Biology Leipzig University Leipzig Germany
| | - Laetitia M. Navarro
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Roel van Klink
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
| | - Georg Albert
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biodiversity Friedrich Schiller University Jena Jena Germany
| | - Christopher D. Barratt
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
| | - Helge Bruelheide
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Yun Cao
- Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment of China Nanjing China
| | - Ariane Chamoin
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Ecosystem Services, Helmholtz Center for Environmental Research ‐ UFZ Leipzig Germany
| | - Marianne Darbi
- Institut für Landschaftsplanung und Naturschutz Geisenheim Germany
- Helmholtz Centre for Environmental Research ‐ UFZ
| | - Maria Dornelas
- Centre for Biological Diversity University of St Andrews St Andrews Scotland
| | - Nico Eisenhauer
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Leipzig University Leipzig Germany
| | - Franz Essl
- BioInvasions, Global Change, Macroecology‐Group, Department of Botany and Biodiversity Research University of Vienna Rennweg 14 Vienna 1030 Austria
| | - Nina Farwig
- Conservation Ecology, Department of Biology University of Marburg Marburg Germany
| | - Johannes Förster
- Helmholtz Centre for Environmental Research ‐ UFZ Department of Environmental Politics Leipzig Germany
| | - Jörg Freyhof
- Museum für Naturkunde Leibniz Institute for Evolution and Biodiversity Science Berlin Germany
| | - Jonas Geschke
- Institute of Plant Sciences University of Bern Bern Switzerland
| | - Felix Gottschall
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Leipzig University Leipzig Germany
| | - Carlos Guerra
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Peter Haase
- Senckenberg Research Institute and Natural History Museum Frankfurt Gelnhausen Germany
- Faculty of Biology University of Duisburg‐Essen Essen Germany
| | - Thomas Hickler
- Senckenberg Biodiversity and Climate Research Centre Frankfurt am Main Germany
- Department of Physical Geography at Goethe University Frankfurt Germany
| | - Ute Jacob
- Helmholtz Institute for Marine Functional Biodiversity at the University of Oldenburg Oldenburg Germany
- Alfred Wegener Institute Bremerhaven Germany
| | - Thomas Kastner
- Senckenberg Biodiversity and Climate Research Centre Frankfurt am Main Germany
| | - Lotte Korell
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
- Helmholtz Centre for Environmental Research ‐ UFZ Department of Community Ecology Halle (Saale) Germany
| | - Ingolf Kühn
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
- Helmholtz Centre for Environmental Research ‐ UFZ Department of Community Ecology Halle (Saale) Germany
| | - Gerlind U. C. Lehmann
- Evolutionary Ecology, Department of Biology Humboldt University Berlin Berlin Germany
- DINA (Diversity of Insects in Nature protected Areas), National Headquarter Nature and Biodiversity Conservation Union (NABU) Berlin Germany
| | - Bernd Lenzner
- BioInvasions, Global Change, Macroecology‐Group, Department of Botany and Biodiversity Research University of Vienna Rennweg 14 Vienna 1030 Austria
| | - Alexandra Marques
- PBL Netherlands Environmental Assessment Agency The Hague The Netherlands
| | - Elena Motivans Švara
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
- Helmholtz Centre for Environmental Research ‐ UFZ Department of Community Ecology Halle (Saale) Germany
| | - Laura C. Quintero
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Andrea Pacheco
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
| | - Alexander Popp
- Potsdam Institute for Climate Impact Research Member of the Leibniz Association Potsdam Germany
| | - Julia Rouet‐Leduc
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Ecosystem Services, Helmholtz Center for Environmental Research ‐ UFZ Leipzig Germany
- Institute of Biology Leipzig University Leipzig Germany
| | - Florian Schnabel
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Systematic Botany and Functional Biodiversity University of Leipzig Leipzig Germany
| | - Julia Siebert
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Leipzig University Leipzig Germany
| | - Ingmar R. Staude
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Stefan Trogisch
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biology Martin Luther University Halle‐Wittenberg Halle (Saale) Germany
| | - Vid Švara
- Department of Evolutionary Ecology and Environmental Toxicology Goethe University Frankfurt Frankfurt am Main Germany
- Helmholtz Centre for Environmental Research ‐ UFZ Department of Effect‑Directed Analysis Leipzig Germany
| | - Jens‐Christian Svenning
- Department of Biology Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Aarhus University Aarhus C Denmark
- Department of Biology Section for Ecoinformatics and Biodiversity, Aarhus University Aarhus C Denmark
| | - Guy Pe'er
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Ecosystem Services, Helmholtz Center for Environmental Research ‐ UFZ Leipzig Germany
| | | | - Demetra Rakosy
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Helmholtz Centre for Environmental Research ‐ UFZ Department of Community Ecology Halle (Saale) Germany
| | | | - Alexandra S. Werner
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Institute of Biodiversity Friedrich Schiller University Jena Jena Germany
| | - Christian Wirth
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Systematic Botany and Functional Biodiversity University of Leipzig Leipzig Germany
- Max‐Planck‐Institute for Biogeochemistry Jena Germany
| | - Haigen Xu
- Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment of China Nanjing China
| | - Dandan Yu
- Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment of China Nanjing China
| | - Yves Zinngrebe
- Helmholtz Centre for Environmental Research ‐ UFZ
- Department for Agricultural Economics and Rural Development Georg‐August‐Universität Göttingen Göttingen Germany
| | - Aletta Bonn
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany
- Department of Ecosystem Services, Helmholtz Center for Environmental Research ‐ UFZ Leipzig Germany
- Institute of Biodiversity Friedrich Schiller University Jena Jena Germany
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34
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Strydom T, Catchen MD, Banville F, Caron D, Dansereau G, Desjardins-Proulx P, Forero-Muñoz NR, Higino G, Mercier B, Gonzalez A, Gravel D, Pollock L, Poisot T. A roadmap towards predicting species interaction networks (across space and time). Philos Trans R Soc Lond B Biol Sci 2021; 376:20210063. [PMID: 34538135 PMCID: PMC8450634 DOI: 10.1098/rstb.2021.0063] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/29/2021] [Indexed: 11/12/2022] Open
Abstract
Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.
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Affiliation(s)
- Tanya Strydom
- Sciences Biologiques, Université de Montréal, Montréal, Canada H2V 0B3
- Québec Centre for Biodiversity Sciences, Montréal, Canada
| | - Michael D. Catchen
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- McGill University, Montréal, Canada
| | - Francis Banville
- Sciences Biologiques, Université de Montréal, Montréal, Canada H2V 0B3
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- Université de Sherbrooke, Sherbrooke, Canada
| | - Dominique Caron
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- McGill University, Montréal, Canada
| | - Gabriel Dansereau
- Sciences Biologiques, Université de Montréal, Montréal, Canada H2V 0B3
- Québec Centre for Biodiversity Sciences, Montréal, Canada
| | - Philippe Desjardins-Proulx
- Sciences Biologiques, Université de Montréal, Montréal, Canada H2V 0B3
- Québec Centre for Biodiversity Sciences, Montréal, Canada
| | - Norma R. Forero-Muñoz
- Sciences Biologiques, Université de Montréal, Montréal, Canada H2V 0B3
- Québec Centre for Biodiversity Sciences, Montréal, Canada
| | | | - Benjamin Mercier
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- Université de Sherbrooke, Sherbrooke, Canada
| | - Andrew Gonzalez
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- McGill University, Montréal, Canada
| | - Dominique Gravel
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- Université de Sherbrooke, Sherbrooke, Canada
| | - Laura Pollock
- Québec Centre for Biodiversity Sciences, Montréal, Canada
- McGill University, Montréal, Canada
| | - Timothée Poisot
- Sciences Biologiques, Université de Montréal, Montréal, Canada H2V 0B3
- Québec Centre for Biodiversity Sciences, Montréal, Canada
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35
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Pekár S, Wolff JO, Černecká Ľ, Birkhofer K, Mammola S, Lowe EC, Fukushima CS, Herberstein ME, Kučera A, Buzatto BA, Djoudi EA, Domenech M, Enciso AV, Piñanez Espejo YMG, Febles S, García LF, Gonçalves-Souza T, Isaia M, Lafage D, Líznarová E, Macías-Hernández N, Magalhães I, Malumbres-Olarte J, Michálek O, Michalik P, Michalko R, Milano F, Munévar A, Nentwig W, Nicolosi G, Painting CJ, Pétillon J, Piano E, Privet K, Ramírez MJ, Ramos C, Řezáč M, Ridel A, Růžička V, Santos I, Sentenská L, Walker L, Wierucka K, Zurita GA, Cardoso P. The World Spider Trait database: a centralized global open repository for curated data on spider traits. Database (Oxford) 2021; 2021:baab064. [PMID: 34651181 PMCID: PMC8517500 DOI: 10.1093/database/baab064] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 08/13/2021] [Accepted: 09/23/2021] [Indexed: 11/12/2022]
Abstract
Spiders are a highly diversified group of arthropods and play an important role in terrestrial ecosystems as ubiquitous predators, which makes them a suitable group to test a variety of eco-evolutionary hypotheses. For this purpose, knowledge of a diverse range of species traits is required. Until now, data on spider traits have been scattered across thousands of publications produced for over two centuries and written in diverse languages. To facilitate access to such data, we developed an online database for archiving and accessing spider traits at a global scale. The database has been designed to accommodate a great variety of traits (e.g. ecological, behavioural and morphological) measured at individual, species or higher taxonomic levels. Records are accompanied by extensive metadata (e.g. location and method). The database is curated by an expert team, regularly updated and open to any user. A future goal of the growing database is to include all published and unpublished data on spider traits provided by experts worldwide and to facilitate broad cross-taxon assays in functional ecology and comparative biology. Database URL:https://spidertraits.sci.muni.cz/.
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Affiliation(s)
- Stano Pekár
- Department of Botany and Zoology, Faculty of Science, Masaryk University, Kotlářská 2, Brno 611 37, Czechia
| | - Jonas O Wolff
- Zoological Institute and Museum, University of Greifswald, Loitzer Str. 26, Greifswald 17489, Germany
- Department of Biological Sciences, Macquarie University, 6 Wally’s Walk, Sydney, NSW 2109, Australia
| | - Ľudmila Černecká
- Slovak Academy of Sciences, Institute of Forest Ecology, Ľ. Štúra 2, Zvolen 960 01, Slovak Republic
| | - Klaus Birkhofer
- Department of Ecology, Brandenburg University of Technology Cottbus-Senftenberg, Konrad-Wachsmann-Allee 6, Cottbus 03046, Germany
| | - Stefano Mammola
- Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History LUOMUS, University of Helsinki, Pohjoinen Rautatiekatu 13, Helsinki 00014, Finland
- Molecular Ecology Group (MEG), Water Research Institute (IRSA), National Research Council (CNR), Corso Tonolli, 50, Pallanza 28922, Italy
| | - Elizabeth C Lowe
- Department of Biological Sciences, Macquarie University, 6 Wally’s Walk, Sydney, NSW 2109, Australia
| | - Caroline S Fukushima
- Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History LUOMUS, University of Helsinki, Pohjoinen Rautatiekatu 13, Helsinki 00014, Finland
| | - Marie E Herberstein
- Department of Biological Sciences, Macquarie University, 6 Wally’s Walk, Sydney, NSW 2109, Australia
| | - Adam Kučera
- Department of Botany and Zoology, Faculty of Science, Masaryk University, Kotlářská 2, Brno 611 37, Czechia
| | - Bruno A Buzatto
- Department of Biological Sciences, Macquarie University, 6 Wally’s Walk, Sydney, NSW 2109, Australia
- School of Biological Sciences, University of Western Australia, 35 Stirling highway, Crawley, WA 6009, Australia
| | - El Aziz Djoudi
- Department of Ecology, Brandenburg University of Technology Cottbus-Senftenberg, Konrad-Wachsmann-Allee 6, Cottbus 03046, Germany
| | - Marc Domenech
- Department of Evolutionary Biology, Ecology and Environmental Sciences & Biodiversity Research Institute (IRBio), Universitat de Barcelona, Av. Diagonal 643, Barcelona 08028, Spain
| | | | | | - Sara Febles
- Grupo de Investigaciones Entomológicas de Tenerife (GIET), C/ San Eulogio 15, 1º, La Laguna, Canary Islands 38108, Spain
| | - Luis F García
- Centro Universitario Regional del Este, Universidad de la República, Ruta 8 Km 282, Treinta y Tres, Uruguay
| | - Thiago Gonçalves-Souza
- Department of Biology, Ecological Synthesis and Biodiversity Conservation Lab, Federal Rural University of Pernambuco, Dom Manuel de Medeiros, s/n, Dois Irmãos—CEP, Recife, PE 50710-270, Brazil
| | - Marco Isaia
- Department of Life Sciences and Systems Biology, University of Turin, Via Accademia Albertina, 13, Turin 10123, Italy
| | - Denis Lafage
- UMR CNRS 6553 ECOBIO, Université de Rennes 1, 263 Avenue du General Leclerc, Rennes 35042, France
| | - Eva Líznarová
- Department of Botany and Zoology, Faculty of Science, Masaryk University, Kotlářská 2, Brno 611 37, Czechia
| | - Nuria Macías-Hernández
- Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History LUOMUS, University of Helsinki, Pohjoinen Rautatiekatu 13, Helsinki 00014, Finland
- Departamento de Biología Animal, Edafología y Geología, Universidad de La Laguna, La Laguna, Tenerife 38206, Spain
| | - Ivan Magalhães
- Division of Arachnology, Museo Argentino de Ciencias Naturales ‘Bernardino Rivadavia’—CONICET, Av. Ángel Gallardo 470, Buenos Aires C1405DJR, Argentina
| | - Jagoba Malumbres-Olarte
- Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History LUOMUS, University of Helsinki, Pohjoinen Rautatiekatu 13, Helsinki 00014, Finland
- CE3C—Centre for Ecology, Evolution and Environmental Changes, Azorean Biodiversity Group and Universidade dos Açores, Angra do Heroísmo, Azores, Portugal
| | - Ondřej Michálek
- Department of Botany and Zoology, Faculty of Science, Masaryk University, Kotlářská 2, Brno 611 37, Czechia
| | - Peter Michalik
- Zoological Institute and Museum, University of Greifswald, Loitzer Str. 26, Greifswald 17489, Germany
| | - Radek Michalko
- Department of Forest Ecology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, Brno 613 00, Czech Republic
| | - Filippo Milano
- Department of Life Sciences and Systems Biology, University of Turin, Via Accademia Albertina, 13, Turin 10123, Italy
| | - Ana Munévar
- Instituto de Biología Subtropical (UNAM-CONICET), Puerto Iguazú, Argentina
| | - Wolfgang Nentwig
- Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, Bern 3012, Switzerland
| | - Giuseppe Nicolosi
- Department of Life Sciences and Systems Biology, University of Turin, Via Accademia Albertina, 13, Turin 10123, Italy
| | - Christina J Painting
- Te Aka Mātuatua School of Science, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand
| | - Julien Pétillon
- UMR CNRS 6553 ECOBIO, Université de Rennes 1, 263 Avenue du General Leclerc, Rennes 35042, France
| | - Elena Piano
- Department of Life Sciences and Systems Biology, University of Turin, Via Accademia Albertina, 13, Turin 10123, Italy
| | - Kaïna Privet
- UMR CNRS 6553 ECOBIO, Université de Rennes 1, 263 Avenue du General Leclerc, Rennes 35042, France
| | - Martín J Ramírez
- Division of Arachnology, Museo Argentino de Ciencias Naturales ‘Bernardino Rivadavia’—CONICET, Av. Ángel Gallardo 470, Buenos Aires C1405DJR, Argentina
| | - Cândida Ramos
- Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History LUOMUS, University of Helsinki, Pohjoinen Rautatiekatu 13, Helsinki 00014, Finland
| | - Milan Řezáč
- Crop Research Institute, Drnovská 507, Prague 6 CZ-16106, Czechia
| | - Aurélien Ridel
- UMR CNRS 6553 ECOBIO, Université de Rennes 1, 263 Avenue du General Leclerc, Rennes 35042, France
| | - Vlastimil Růžička
- Biology Centre, Czech Academy of Sciences, Institute of Entomology, Branišovská 31, České Budějovice 370 05, Czechia
| | - Irene Santos
- Grupo de Investigaciones Entomológicas de Tenerife (GIET), C/ San Eulogio 15, 1º, La Laguna, Canary Islands 38108, Spain
- Island Ecology and Evolution Research Group, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), La Laguna, Tenerife, Canary Islands 38206, Spain
| | - Lenka Sentenská
- Department of Botany and Zoology, Faculty of Science, Masaryk University, Kotlářská 2, Brno 611 37, Czechia
| | - Leilani Walker
- Natural Sciences, Auckland War Memorial Museum, Parnell, Auckland 1010, New Zealand
| | - Kaja Wierucka
- Department of Biological Sciences, Macquarie University, 6 Wally’s Walk, Sydney, NSW 2109, Australia
- Department of Anthropology, University of Zürich, Winterthurerstrasse 190, Zürich 8057, Switzerland
| | | | - Pedro Cardoso
- Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History LUOMUS, University of Helsinki, Pohjoinen Rautatiekatu 13, Helsinki 00014, Finland
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Sustainability, Big Data and Mathematical Techniques: A Bibliometric Review. MATHEMATICS 2021. [DOI: 10.3390/math9202557] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
This article has reviewed international research, up to the first half of 2021, focused on sustainability, big data and the mathematical techniques used for its analysis. In addition, a study of the spatial component (city, region, nation and beyond) of the works has been carried out and an analysis has been made of which Sustainable Development Goals (SDGs) have received the most attention. A bibliometric analysis and a fractal cluster analysis were performed on the papers published in the Web of Science. The results show a continuous increase in the number of published articles and citations over the whole period, demonstrating a growing interest in this topic. China, the United States and India are the most productive countries and there are more papers at the regional level. It has been found that the environmental dimension is the most studied and the least studied is the social dimension. The mathematical techniques used in the empirical work are mainly regression analysis, neural networks and multi-criteria decision methods. SDG9 and SDG11 are the most worked on. The trend shows a convergence in recent years towards big data applied to supply chains, Industry 4.0 and the achievement of sustainable cities.
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Giannini TC, Acosta AL, Costa WF, Miranda L, Pinto CE, Watanabe MTC, Zappi DC, Giulietti AM, Imperatriz-Fonseca VL. Flora of Ferruginous Outcrops Under Climate Change: A Study in the Cangas of Carajás (Eastern Amazon). FRONTIERS IN PLANT SCIENCE 2021; 12:699034. [PMID: 34557210 PMCID: PMC8454948 DOI: 10.3389/fpls.2021.699034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/18/2021] [Indexed: 06/13/2023]
Abstract
Climate change has impacted biodiversity, affecting species and altering their geographical distribution. Besides understanding the impact in the species, it has been advocated that answering if different traits will be differently impacted could allow refined predictions of how climate change will jeopardize biodiversity. Our aim was to evaluate if climate change will potentially impact plant species differently, considering their traits. We evaluated 608 plant species that occur in the naturally open areas of ferruginous outcrops (namely, cangas) in the National Forest of Carajás (Eastern Amazon). Firstly, we estimated the effects of climate change on each species using species distribution modeling, and analyzed this impact in the set containing all species. Secondly, we classified plant species considering the following traits: (i) pollination syndromes (melittophily, phalaenophily, psychophily, cantharophily, entomophily, ornithophily, chiropterophily, anemophily); (ii) habit (tree, shrub, herb, liana, parasite); and (iii) the main habitat of occurrence (open areas and forests). Thirdly, we investigated if the effects of climate change could be significantly more intense considering all the different traits quoted. Our results showed that most plant species will potentially face reduction of suitable habitats under future climate and the scenarios showed that 42% of them may not find suitable areas in the cangas of Carajás. We found no significant difference within each analyzed trait, considering the potential impact of climate change. The most climatically suitable areas (i.e., areas with high probability of species occurrence in the future) are those in the southwest of the study area. These areas can be considered as priority areas for species protection against climate change.
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Affiliation(s)
- Tereza Cristina Giannini
- Instituto Tecnológico Vale, Belém, Brazil
- Programa de Pós Graduação em Zoologia, Universidade Federal do Pará, Belém, Brazil
| | | | - Wilian França Costa
- Instituto Tecnológico Vale, Belém, Brazil
- Faculdade de Computação e Informática, Universidade Presbiteriana Mackenzie, São Paulo, Brazil
| | - Leonardo Miranda
- Instituto Tecnológico Vale, Belém, Brazil
- Museu Paraense Emílio Goeldi, Belém, Brazil
| | - Carlos Eduardo Pinto
- Instituto Tecnológico Vale, Belém, Brazil
- Departamento de Química Fundamental, Centro de Ciências Exatas e da Natureza, Universidade Federal de Pernambuco, Recife, Brazil
| | | | - Daniela Cristina Zappi
- Instituto Tecnológico Vale, Belém, Brazil
- Programa de Pós-Graduação em Botânica, Instituto de Ciências Biológicas, Universidade de Brasília, Brasília, Brazil
| | - Ana Maria Giulietti
- Instituto Tecnológico Vale, Belém, Brazil
- Programa de Pós-Graduação em Botânica, Universidade Estadual de Feira de Santana, Feira de Santana, Brazil
| | - Vera Lucia Imperatriz-Fonseca
- Instituto Tecnológico Vale, Belém, Brazil
- Departamento de Ecologia, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
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Vanderbilt K, Gries C. Integrating long-tail data: How far are we? ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2021.101372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Arenas-Castro S, Sillero N. Cross-scale monitoring of habitat suitability changes using satellite time series and ecological niche models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 784:147172. [PMID: 34088022 DOI: 10.1016/j.scitotenv.2021.147172] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 04/06/2021] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
One of the biggest challenges to deal with the global crisis of biodiversity loss is the lack of efficient and viable monitoring systems across scales. Unlike traditional in situ biodiversity monitoring, a usually costly and time-consuming enterprise, satellite remote sensing (SRS) data offer a technically feasible and sustainable in time solution. Here, we devise a cost-effective and upgradeable spatiotemporal framework for monitoring the species-specific habitat availability changes across scales by trend analysis of habitat suitability index (HSI) derived from ecological niche models (ENMs; Maxent) and using time series of SRS data (MODIS). The SRS-ENM framework was applied for a large suite of native species (911), from major taxonomic groups (flora (vascular plants), amphibians, reptiles, birds and mammals), and listed in the IUCN Red List at regional (Iberian Peninsula) and continental (Europe) scales. The HSI-trend analyses predict cumulative reductions in habitat suitability for Threatened and Non-Threatened species across scales for the period 2002-2016. Specifically, 19% and 66% of the total grid cells for both species' groups showed negative trends at both regional and continental scales, respectively. Results were similar when considering all IUCN threat categories. All taxa groups showed a decrease in habitat suitability, but amphibians and reptiles groups hosted the largest number of negative HSI-trends grid cells. Considering all groups together, 12% and 34% of both study areas have strong reductions in habitat quality. We conclude that our framework detects increases and decreases in species' habitat suitability regardless of the spatial scale, extent, and pixel size. Species' range predictions across space and time based on SRS time series represent a promising Earth observation tool to support traditional risk assessment protocols and anticipate the decision-making process, while serving as a cross-scale biodiversity monitoring system.
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Affiliation(s)
- Salvador Arenas-Castro
- CICGE - Centro de Investigação em Ciências Geo-Espaciais, Faculdade de Ciências, Universidade do Porto, Observatório Astronómico "Prof. Manuel de Barros", Alameda do Monte da Virgem, 4430-146 Vila Nova de Gaia, Portugal.
| | - Neftalí Sillero
- CICGE - Centro de Investigação em Ciências Geo-Espaciais, Faculdade de Ciências, Universidade do Porto, Observatório Astronómico "Prof. Manuel de Barros", Alameda do Monte da Virgem, 4430-146 Vila Nova de Gaia, Portugal.
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Research Data Management Challenges in Citizen Science Projects and Recommendations for Library Support Services. A Scoping Review and Case Study. DATA SCIENCE JOURNAL 2021. [DOI: 10.5334/dsj-2021-025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Regos A, Tapia L, Gil-Carrera A, Domínguez J. Caution Is Needed When Using Niche Models to Infer Changes in Species Abundance: The Case of Two Sympatric Raptor Populations. Animals (Basel) 2021; 11:2020. [PMID: 34359148 PMCID: PMC8300138 DOI: 10.3390/ani11072020] [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: 06/02/2021] [Revised: 06/23/2021] [Accepted: 07/01/2021] [Indexed: 11/16/2022] Open
Abstract
Despite the mounting evidence supporting positive relationships between species abundance and habitat suitability, the capacity of ecological niche models (ENMs) to capture variations in population abundance remains largely unexplored. This study focuses on sympatric populations of hen harrier (Circus cyaneus) and Montagu's harrier (Circus pygargus), surveyed in 1997 and 2017 in an upland moor area in northwestern Spain. The ENMs performed very well for both species (with area under the ROC curve and true skill statistic values of up to 0.9 and 0.75). The presence of both species was mainly correlated with heathlands, although the normalized difference water index derived from Landsat images was the most important for hen harrier, indicating a greater preference of this species for wet heaths and peat bogs. The findings showed that ENM-derived habitat suitability was significantly correlated with the species abundance, thus reinforcing the use of ENMs as a proxy for species abundance. However, the temporal variation in species abundance was not significantly explained by changes in habitat suitability predicted by the ENMs, indicating the need for caution when using these types of models to infer changes in population abundance.
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Affiliation(s)
- Adrián Regos
- Departamento de Zooloxía, Xenética e Antropoloxía Física, Universidade de Santiago de Compostela, Campus Sur, 15782 Santiago de Compostela, Spain; (L.T.); (J.D.)
- CIBIO/InBIO, Research Center in Biodiversity and Genetic Resources, Predictive Ecology Group, Campus Agrario de Vairão, R. Padre Armando Quintas, N° 7, 4485-661 Vairão, Portugal
| | - Luis Tapia
- Departamento de Zooloxía, Xenética e Antropoloxía Física, Universidade de Santiago de Compostela, Campus Sur, 15782 Santiago de Compostela, Spain; (L.T.); (J.D.)
- EBX, Estación Biolóxica do Xurés, Vilameá 121, 32870 Lobios, Spain;
| | - Alberto Gil-Carrera
- EBX, Estación Biolóxica do Xurés, Vilameá 121, 32870 Lobios, Spain;
- GREFA, Monte del Pilar S/N, 28220 Majadahonda, Spain
| | - Jesús Domínguez
- Departamento de Zooloxía, Xenética e Antropoloxía Física, Universidade de Santiago de Compostela, Campus Sur, 15782 Santiago de Compostela, Spain; (L.T.); (J.D.)
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Priority list of biodiversity metrics to observe from space. Nat Ecol Evol 2021; 5:896-906. [PMID: 33986541 DOI: 10.1038/s41559-021-01451-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 03/22/2021] [Indexed: 02/03/2023]
Abstract
Monitoring global biodiversity from space through remotely sensing geospatial patterns has high potential to add to our knowledge acquired by field observation. Although a framework of essential biodiversity variables (EBVs) is emerging for monitoring biodiversity, its poor alignment with remote sensing products hinders interpolation between field observations. This study compiles a comprehensive, prioritized list of remote sensing biodiversity products that can further improve the monitoring of geospatial biodiversity patterns, enhancing the EBV framework and its applicability. The ecosystem structure and ecosystem function EBV classes, which capture the biological effects of disturbance as well as habitat structure, are shown by an expert review process to be the most relevant, feasible, accurate and mature for direct monitoring of biodiversity from satellites. Biodiversity products that require satellite remote sensing of a finer resolution that is still under development are given lower priority (for example, for the EBV class species traits). Some EBVs are not directly measurable by remote sensing from space, specifically the EBV class genetic composition. Linking remote sensing products to EBVs will accelerate product generation, improving reporting on the state of biodiversity from local to global scales.
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eDNA sampled from stream networks correlates with camera trap detection rates of terrestrial mammals. Sci Rep 2021; 11:11362. [PMID: 34131168 PMCID: PMC8206079 DOI: 10.1038/s41598-021-90598-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 05/13/2021] [Indexed: 11/14/2022] Open
Abstract
Biodiversity monitoring delivers vital information to those making conservation decisions. Comprehensively measuring terrestrial biodiversity usually requires costly methods that can rarely be deployed at large spatial scales over multiple time periods, limiting conservation efficiency. Here we investigated the capacity of environmental DNA (eDNA) from stream water samples to survey terrestrial mammal diversity at multiple spatial scales within a large catchment. We compared biodiversity information recovered using an eDNA metabarcoding approach with data from a dense camera trap survey, as well as the sampling costs of both methods. Via the sampling of large volumes of water from the two largest streams that drained the study area, eDNA metabarcoding provided information on the presence and detection probabilities of 35 mammal taxa, 25% more than camera traps and for half the cost. While eDNA metabarcoding had limited capacity to detect felid species and provide individual-level demographic information, it is a cost-efficient method for large-scale monitoring of terrestrial mammals that can offer sufficient information to solve many conservation problems.
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45
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Rapacciuolo G, Young A, Johnson R. Deriving indicators of biodiversity change from unstructured community‐contributed data. OIKOS 2021. [DOI: 10.1111/oik.08215] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Giovanni Rapacciuolo
- Inst. for Biodiversity Science and Sustainability, California Academy of Sciences San Francisco CA USA
- NatureServe Arlington VA USA
| | - Alison Young
- Inst. for Biodiversity Science and Sustainability, California Academy of Sciences San Francisco CA USA
| | - Rebecca Johnson
- Inst. for Biodiversity Science and Sustainability, California Academy of Sciences San Francisco CA USA
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46
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Amini Tehrani N, Naimi B, Jaboyedoff M. Modeling current and future species distribution of breeding birds as regional essential biodiversity variables (SD EBVs): A bird perspective in Swiss Alps. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01596] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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47
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Rodríguez-Ezpeleta N, Zinger L, Kinziger A, Bik HM, Bonin A, Coissac E, Emerson BC, Lopes CM, Pelletier TA, Taberlet P, Narum S. Biodiversity monitoring using environmental DNA. Mol Ecol Resour 2021; 21:1405-1409. [PMID: 34032015 DOI: 10.1111/1755-0998.13399] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/12/2021] [Accepted: 04/15/2021] [Indexed: 11/29/2022]
Affiliation(s)
| | - Lucie Zinger
- Département de biologie, Institut de Biologie de l'ENS (IBENS, École normale supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Andrew Kinziger
- Department of Fisheries Biology, Humboldt State University, Arcata, CA, USA
| | - Holly M Bik
- Department of Marine Sciences and Institute of Bioinformatics, University of Georgia, Athens, Georgia, USA
| | - Aurélie Bonin
- Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy
| | - Eric Coissac
- Univ. Grenoble-Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Brent C Emerson
- Island Ecology and Evolution Research Group, Institute of Natural Products and Agrobiology (IPNA-CSIC, La Laguna, Spain
| | - Carla Martins Lopes
- Departamento de Biodiversidade, Universidade Estadual Paulista (UNESP, Rio Claro, SP, Brazil
| | | | - Pierre Taberlet
- Univ. Grenoble-Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France.,The Arctic University Museum of Norway, UiT the Arctic University of Norway, Tromsø, Norway
| | - Shawn Narum
- Hagerman Genetics Laboratory, Columbia River Inter-Tribal Fish Commission, University of Idaho, Hagerman, ID, USA
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48
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Belbin L, Wallis E, Hobern D, Zerger A. The Atlas of Living Australia: History, current state and future directions. Biodivers Data J 2021; 9:e65023. [PMID: 33935559 PMCID: PMC8081701 DOI: 10.3897/bdj.9.e65023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 03/29/2021] [Indexed: 12/03/2022] Open
Abstract
The Atlas of Living Australia (ALA) is Australia’s national biodiversity database, delivering data and related services to more than 80,000 Australian and international users annually. Established under the Australian Government’s National Collaborative Research Infrastructure Strategy to provide trusted biodiversity data to support the research sector, its utility now extends to government, higher education, non-government organisations and community groups. These partners provide data to the ALA and leverage its data and related services. The ALA has also played an important leadership role internationally in the biodiversity informatics and infrastructure space, both through its partnership with the Global Biodiversity Information Facility and through support for the international Living Atlases programmes which has now delivered 24 instances of ALA software to deliver sovereign biodiversity data capability around the world. This paper begins with a historical overview of the genesis of the ALA from the collections, museums and herbaria community in Australia. It details the biodiversity and related data and services delivered to users with a primary focus on species occurrence records which represent the ALA's primary data type. Finally, the paper explores the ALA's future directions by referencing results from a recently completed national consultation process.
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Affiliation(s)
- Lee Belbin
- Atlas of Living Australia, CSIRO, Canberra, Australia Atlas of Living Australia, CSIRO Canberra Australia
| | - Elycia Wallis
- Atlas of Living Australia, CSIRO, Melbourne, Australia Atlas of Living Australia, CSIRO Melbourne Australia
| | - Donald Hobern
- Atlas of Living Australia, CSIRO, Canberra, Australia Atlas of Living Australia, CSIRO Canberra Australia
| | - Andre Zerger
- Atlas of Living Australia, CSIRO, Canberra, Australia Atlas of Living Australia, CSIRO Canberra Australia
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49
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Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth. Proc Natl Acad Sci U S A 2021; 118:1921854118. [PMID: 33876741 PMCID: PMC8053992 DOI: 10.1073/pnas.1921854118] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth’s surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth’s albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth’s climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth’s surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.
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50
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Anton V, Germishuys J, Bergström P, Lindegarth M, Obst M. An open-source, citizen science and machine learning approach to analyse subsea movies. Biodivers Data J 2021; 9:e60548. [PMID: 33679174 PMCID: PMC7930014 DOI: 10.3897/bdj.9.e60548] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 02/11/2021] [Indexed: 11/29/2022] Open
Abstract
Background The increasing access to autonomously-operated technologies offer vast opportunities to sample large volumes of biological data. However, these technologies also impose novel demands on ecologists who need to apply tools for data management and processing that are efficient, publicly available and easy to use. Such tools are starting to be developed for a wider community and here we present an approach to combine essential analytical functions for analysing large volumes of image data in marine ecological research. New information This paper describes the Koster Seafloor Observatory, an open-source approach to analysing large amounts of subsea movie data for marine ecological research. The approach incorporates three distinct modules to: manage and archive the subsea movies, involve citizen scientists to accurately classify the footage and, finally, train and test machine learning algorithms for detection of biological objects. This modular approach is based on open-source code and allows researchers to customise and further develop the presented functionalities to various types of data and questions related to analysis of marine imagery. We tested our approach for monitoring cold water corals in a Marine Protected Area in Sweden using videos from remotely-operated vehicles (ROVs). Our study resulted in a machine learning model with an adequate performance, which was entirely trained with classifications provided by citizen scientists. We illustrate the application of machine learning models for automated inventories and monitoring of cold water corals. Our approach shows how citizen science can be used to effectively extract occurrence and abundance data for key ecological species and habitats from underwater footage. We conclude that the combination of open-source tools, citizen science systems, machine learning and high performance computational resources are key to successfully analyse large amounts of underwater imagery in the future.
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Affiliation(s)
- Victor Anton
- Wildlife.ai, New Plymouth, New Zealand Wildlife.ai New Plymouth New Zealand
| | | | - Per Bergström
- Department of Marine Sciences, Göteborg University, Gothenburg, Sweden Department of Marine Sciences, Göteborg University Gothenburg Sweden
| | - Mats Lindegarth
- Department of Marine Sciences, Göteborg University, Gothenburg, Sweden Department of Marine Sciences, Göteborg University Gothenburg Sweden
| | - Matthias Obst
- Department of Marine Sciences, Göteborg University, Gothenburg, Sweden Department of Marine Sciences, Göteborg University Gothenburg Sweden.,SeAnalytics AB, Gothenburg, Sweden SeAnalytics AB Gothenburg Sweden
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