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Olesen RS, Reiner F, den Braber B, Hall C, Kilawe CJ, Kinabo J, Msuya J, Rasmussen LV. The importance of different forest management systems for people's dietary quality in Tanzania. LANDSCAPE ECOLOGY 2024; 39:176. [PMID: 39279919 PMCID: PMC11390844 DOI: 10.1007/s10980-024-01961-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 08/11/2024] [Indexed: 09/18/2024]
Abstract
Context A large body of literature has shown that forests provide nutritious foods in many low- and middle-income countries. Yet, there is limited evidence on the contributions from different types of forest and tree systems. Objectives Here, we focus on individual trees and smaller forest patches outside established forest reserves as well as different forest management systems. Methods We do so by combining novel high-resolution data on tree cover with 24-h dietary recall surveys from 465 women in Tanzania. Results We show that people with more unclassified tree cover (i.e., individual trees and small forest patches) in their nearby surroundings have more adequate protein, iron, zinc, and vitamin A intakes. We also find that having a nearby forest under Participatory Forest Management (PFM) system is associated with higher adequacy levels of energy, iron, zinc and vitamin A. By contrast, tree cover within other types of forest (e.g., Government Forest Reserves and Government Forest Plantations) is not positively associated with people's dietary quality. Conclusions Our key finding is that having individual trees, smaller forest patches and/or forest under PFM in close proximity is more beneficial for people's diets than other types of established forests. Our results highlight the nutritional importance of trees outside established forests and question the often-assumed benefits of forests if these are made inaccessible by social barriers (e.g., legislation). Finally, our results emphasize the need to distinguish between different forest management systems when studying forest-diet linkages. Supplementary Information The online version contains supplementary material available at 10.1007/s10980-024-01961-6.
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Affiliation(s)
- R S Olesen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
| | - F Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
| | - B den Braber
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
| | - C Hall
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
- Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA UK
| | - C J Kilawe
- Department of Ecosystems and Conservation, Sokoine University of Agriculture, Morogoro, Tanzania
| | - J Kinabo
- Department of Human Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania
| | - J Msuya
- Department of Human Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania
| | - L V Rasmussen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
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2
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Zhao T, Wang S, Ouyang C, Chen M, Liu C, Zhang J, Yu L, Wang F, Xie Y, Li J, Wang F, Grunwald S, Wong BM, Zhang F, Qian Z, Xu Y, Yu C, Han W, Sun T, Shao Z, Qian T, Chen Z, Zeng J, Zhang H, Letu H, Zhang B, Wang L, Luo L, Shi C, Su H, Zhang H, Yin S, Huang N, Zhao W, Li N, Zheng C, Zhou Y, Huang C, Feng D, Xu Q, Wu Y, Hong D, Wang Z, Lin Y, Zhang T, Kumar P, Plaza A, Chanussot J, Zhang J, Shi J, Wang L. Artificial intelligence for geoscience: Progress, challenges, and perspectives. Innovation (N Y) 2024; 5:100691. [PMID: 39285902 PMCID: PMC11404188 DOI: 10.1016/j.xinn.2024.100691] [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: 01/15/2024] [Accepted: 08/17/2024] [Indexed: 09/19/2024] Open
Abstract
This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.
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Affiliation(s)
- Tianjie Zhao
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Sheng Wang
- School of Computer Science, China University of Geosciences, Wuhan 430078, China
| | - Chaojun Ouyang
- State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Chen
- Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
| | - Chenying Liu
- Data Science in Earth Observation, Technical University of Munich, 80333 Munich, Germany
| | - Jin Zhang
- The National Key Laboratory of Water Disaster Prevention, Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China
| | - Long Yu
- School of Computer Science, China University of Geosciences, Wuhan 430078, China
| | - Fei Wang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yong Xie
- School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jun Li
- School of Computer Science, China University of Geosciences, Wuhan 430078, China
| | - Fang Wang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Department of Chemistry, Technical University of Munich, 85748 Munich, Germany
| | - Sabine Grunwald
- Soil, Water and Ecosystem Sciences Department, University of Florida, PO Box 110290, Gainesville, FL, USA
| | - Bryan M Wong
- Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy, University of California, California, Riverside, CA 92521, USA
| | - Fan Zhang
- Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
| | - Zhen Qian
- Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
| | - Yongjun Xu
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chengqing Yu
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Han
- School of Computer Science, China University of Geosciences, Wuhan 430078, China
| | - Tao Sun
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
| | - Zezhi Shao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tangwen Qian
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhao Chen
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
| | - Jiangyuan Zeng
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Huai Zhang
- Key Laboratory of Computational Geodynamics, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Husi Letu
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Bing Zhang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Li Wang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Lei Luo
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
| | - Chong Shi
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Hongjun Su
- College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
| | - Hongsheng Zhang
- Department of Geography, The University of Hong Kong, Hong Kong 999077, SAR, China
| | - Shuai Yin
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Ni Huang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Wei Zhao
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Nan Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing 210044, China
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Chaolei Zheng
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Yang Zhou
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Changping Huang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Defeng Feng
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qingsong Xu
- Data Science in Earth Observation, Technical University of Munich, 80333 Munich, Germany
| | - Yan Wu
- Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing 100044, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Danfeng Hong
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhenyu Wang
- Department of Catchment Hydrology, Helmholtz Centre for Environmental Research - UFZ, Halle (Saale) 06108, Germany
| | - Yinyi Lin
- Department of Geography, The University of Hong Kong, Hong Kong 999077, SAR, China
| | - Tangtang Zhang
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Prashant Kumar
- Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK
- Institute for Sustainability, University of Surrey, Guildford GU2 7XH, Surrey, UK
| | - Antonio Plaza
- Hyperspectral Computing Laboratory, University of Extremadura, 10003 Caceres, Spain
| | - Jocelyn Chanussot
- University Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
| | - Jiabao Zhang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiancheng Shi
- National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
| | - Lizhe Wang
- School of Computer Science, China University of Geosciences, Wuhan 430078, China
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3
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Huang K, Brandt M, Hiernaux P, Tucker CJ, Rasmussen LV, Reiner F, Li S, Kariryaa A, Mugabowindekwe M, den Braber B, Small J, Sino S, Fensholt R. Mapping every adult baobab (Adansonia digitata L.) across the Sahel and relationships to rural livelihoods. Nat Ecol Evol 2024; 8:1632-1640. [PMID: 39054350 DOI: 10.1038/s41559-024-02483-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 05/24/2024] [Indexed: 07/27/2024]
Abstract
The baobab tree (Adansonia digitata L.) is an integral part of rural livelihoods throughout the African continent. However, the combined effects of climate change and increasing global demand for baobab products are currently exerting pressure on the sustainable utilization of these resources. Here we use sub-metre-resolution satellite imagery to identify the presence of nearly 2.8 million (underestimation bias 27.1%) baobab trees in the Sahel, a dryland region of 2.4 million km2. This achievement is considered an essential step towards an improved management and monitoring system of valuable woody species. Using Senegal as a case country, we find that 94% of rural buildings have at least one baobab tree in their immediate surroundings and that the abundance of baobabs is associated with a higher likelihood of people consuming a highly nutritious food group: dark green leafy vegetables. The generated database showcases the feasibility of mapping the location of single tree species at a sub-continental scale, providing vital information in times when deforestation and climate change cause the extinction of numerous tree species.
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Affiliation(s)
- Ke Huang
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
- Department of Food and Resource Economics, University of Copenhagen, Copenhagen, Denmark.
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA.
| | - Pierre Hiernaux
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Pastoralisme Conseil, Caylus, France
| | - Compton J Tucker
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Laura Vang Rasmussen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Sizhuo Li
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Département Sciences de la terre et de l'univers, espace, Université Paris-Saclay, Paris, France
| | - Ankit Kariryaa
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Maurice Mugabowindekwe
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Bowy den Braber
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer Small
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Scott Sino
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
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4
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Vansant E, den Braber B, Hall C, Kamoto J, Reiner F, Oldekop J, Rasmussen LV. Food-sourcing from on-farm trees mediates positive relationships between tree cover and dietary quality in Malawi. NATURE FOOD 2024; 5:661-666. [PMID: 39138379 PMCID: PMC11343702 DOI: 10.1038/s43016-024-01028-4] [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: 05/01/2023] [Accepted: 07/11/2024] [Indexed: 08/15/2024]
Abstract
Food security policies often overlook the potential of trees to provide micronutrient-rich foods. Here, through causal mediation analysis, we show the positive effect of tree cover on micronutrient adequacy, explained by people sourcing food from on-farm trees. Detailed survey data (n = 460 households with repeated surveys) from Malawi were linked to high-resolution (3 m) tree-cover data to capture forest and non-forest trees. Our findings support integrating nutrition and landscape restoration policies.
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Affiliation(s)
- Emilie Vansant
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
| | - Bowy den Braber
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Charlotte Hall
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Biological and Environmental Sciences, University of Stirling, Stirling, UK
| | - Judith Kamoto
- Forestry Department, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Johan Oldekop
- Global Development Institute, University of Manchester, Manchester, UK.
| | - Laura Vang Rasmussen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
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5
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Fraval S, Mutua JY, Amole T, Tolera A, Feyisa T, Thornton PK, Notenbaert AMO, Adesogan A, Balehegn M, Ayantunde AA, Zampaligre N, Duncan AJ. Feed balances for ruminant livestock: gridded estimates for data-constrained regions. Animal 2024; 18:101199. [PMID: 38897107 DOI: 10.1016/j.animal.2024.101199] [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: 12/19/2023] [Revised: 05/11/2024] [Accepted: 05/14/2024] [Indexed: 06/21/2024] Open
Abstract
Demand for animal-source foods and livestock feed are forecast to increase across sub-Saharan Africa. In this context, there is a need to estimate the availability of livestock feed to support decision-making at local, sub-national and national levels. In this study, we assess feed balances for ruminant livestock in Ethiopia and Burkina Faso. Feed availability was estimated using remotely sensed products and detailed feed composition data. Feed requirements were estimated for maintenance, growth, lactation, gestation and locomotion using a data-intensive model. Biomass available as animal feed was estimated to be 8.6 tonnes of DM per hectare in the Ethiopian highlands and midlands, 3.2 tonnes DM per hectare in the Ethiopian lowlands, 2.9 tonnes DM per hectare in Burkina Faso's Sudanian agro-ecological zone and 1.0 tonne DM per hectare in the Sahel. The energy requirements of lactating cows were estimated to be 62.1 Megajoules (MJs) per animal per day in the Ethiopian highlands and midlands, 62.7 MJ in the Ethiopian lowlands, 88.5 MJ in Burkina Faso's Sudanian agro-ecological zone and 53.1 MJ per animal per day in the Sahel. Feed scarcity hotspots are most prominently located in the Ethiopian highlands and the Sahelian agro-ecological zone of Burkina Faso. Demand-side policy and investment initiatives can address hotspots by influencing herd sizes, nutritional requirements and herd mobility. Supply-side policy and investment initiatives can secure existing feed resources, develop new sources of feed and incentivise trade in feed resources. Improving feed balances will be of value to decision-makers with the aims of optimising livestock productivity, minimising exposure to climatic shocks and minimising greenhouse gas emission intensity.
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Affiliation(s)
- S Fraval
- Global Academy of Agriculture and Food Systems, The Royal (Dick) School of Veterinary Studies and The Roslin Institute, University of Edinburgh, Easter Bush Campus, EH25 9RG, United Kingdom.
| | - J Y Mutua
- Global Academy of Agriculture and Food Systems, The Royal (Dick) School of Veterinary Studies and The Roslin Institute, University of Edinburgh, Easter Bush Campus, EH25 9RG, United Kingdom; School of Geosciences, University of Edinburgh, Edinburgh EH9 3JN, United Kingdom
| | - T Amole
- International Livestock Research Institute (ILRI), PO Box 5689, Addis Ababa, Ethiopia
| | - A Tolera
- School of Animal and Range Sciences, Hawassa University, P.O. Box 05, Hawassa, Ethiopia
| | - T Feyisa
- School of Animal and Range Sciences, Hawassa University, P.O. Box 05, Hawassa, Ethiopia
| | - P K Thornton
- Clim-Eat, Agro Business Park, 10, Wageningen 6708 PW, the Netherlands
| | - A M O Notenbaert
- Alliance of Bioversity International and CIAT, Africa Hub, PO Box 823-00621, Nairobi, Kenya
| | - A Adesogan
- Feed the Future Innovation Lab for Livestock Systems, University of Florida, Gainesville, FL 32611, USA
| | - M Balehegn
- Feed the Future Innovation Lab for Livestock Systems, University of Florida, Gainesville, FL 32611, USA
| | - A A Ayantunde
- Wageningen Livestock Research, Wageningen University & Research, Wageningen 6708 WC, the Netherlands
| | - N Zampaligre
- International Livestock Research Institute (ILRI), PO Box 5689, Addis Ababa, Ethiopia
| | - A J Duncan
- Global Academy of Agriculture and Food Systems, The Royal (Dick) School of Veterinary Studies and The Roslin Institute, University of Edinburgh, Easter Bush Campus, EH25 9RG, United Kingdom; International Livestock Research Institute (ILRI), PO Box 5689, Addis Ababa, Ethiopia
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6
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Tong X, Zhang X, Fensholt R, Jensen PRD, Li S, Larsen MN, Reiner F, Tian F, Brandt M. Global area boom for greenhouse cultivation revealed by satellite mapping. NATURE FOOD 2024; 5:513-523. [PMID: 38741004 DOI: 10.1038/s43016-024-00985-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 04/16/2024] [Indexed: 05/16/2024]
Abstract
Greenhouse cultivation has been expanding rapidly in recent years, yet little knowledge exists on its global extent and expansion. Using commercial and freely available satellite data combined with artificial intelligence techniques, we present a global assessment of greenhouse cultivation coverage and map 1.3 million hectares of greenhouse infrastructures in 2019, a much larger extent than previously estimated. Our analysis includes both large (61%) and small-scale (39%) greenhouse infrastructures. Examining the temporal development of the 65 largest clusters (>1,500 ha), we show a recent upsurge in greenhouse cultivation in the Global South since the 2000s, including a dramatic increase in China, accounting for 60% of the global coverage. We emphasize the potential of greenhouse infrastructures to enhance food security but raise awareness of the uncertain environmental and social implications that may arise from this expansion. We further highlight the gap in spatio-temporal datasets for supporting future research agendas on this critical topic.
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Affiliation(s)
- Xiaoye Tong
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
| | - Xiaoxin Zhang
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
| | | | - Sizhuo Li
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Université Paris-Saclay, Gif-sur-Yvette, France
| | - Marianne Nylandsted Larsen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Feng Tian
- Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
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7
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van Tiel N, Fopp F, Brun P, van den Hoogen J, Karger DN, Casadei CM, Lyu L, Tuia D, Zimmermann NE, Crowther TW, Pellissier L. Regional uniqueness of tree species composition and response to forest loss and climate change. Nat Commun 2024; 15:4375. [PMID: 38821947 PMCID: PMC11143270 DOI: 10.1038/s41467-024-48276-3] [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: 06/16/2023] [Accepted: 04/26/2024] [Indexed: 06/02/2024] Open
Abstract
The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global occupancy of 10,590 tree species reveals complex taxonomic and phylogenetic gradients determining a local signature of tree lineage assembly. Species occupancy analyses indicate that historical forest loss has significantly restricted the potential suitable range of tree species in all forest biomes. Nevertheless, tropical moist and boreal forest biomes display the lowest level of range restriction and harbor extremely large ranged tree species, albeit with a stark contrast in richness and composition. Climate change simulations indicate that forest biomes are projected to differ in their response to climate change, with the highest predicted species loss in tropical dry and Mediterranean ecoregions. Our findings highlight the need for preserving the remaining large forest biomes while regenerating degraded forests in a way that provides resilience against climate change.
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Affiliation(s)
- Nina van Tiel
- Global Ecosystem Ecology, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland.
- Environmental Computational Science and Earth Observation Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - Fabian Fopp
- Ecosystems and Landscape Evolution, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
- Land Change Science Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
| | - Philipp Brun
- Land Change Science Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
| | - Johan van den Hoogen
- Global Ecosystem Ecology, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
| | - Dirk Nikolaus Karger
- Biodiversity and Conservation Biology, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
| | - Cecilia M Casadei
- Laboratory of Biomolecular Research, Biology and Chemistry Division, Paul Scherrer Institute, PSI, Villigen, Switzerland
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zürich, Zürich, Switzerland
| | - Lisha Lyu
- Ecosystems and Landscape Evolution, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
- Land Change Science Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
| | - Devis Tuia
- Environmental Computational Science and Earth Observation Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Niklaus E Zimmermann
- Land Change Science Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
| | - Thomas W Crowther
- Global Ecosystem Ecology, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
| | - Loïc Pellissier
- Ecosystems and Landscape Evolution, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
- Land Change Science Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
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8
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Scaini A, Mulligan J, Berg H, Brangarí A, Bukachi V, Carenzo S, Chau Thi D, Courtney-Mustaphi C, Ekblom A, Fjelde H, Fridahl M, Hansson A, Hicks L, Höjer M, Juma B, Kain JH, Kariuki RW, Kim S, Lane P, Leizeaga A, Lindborg R, Livsey J, Lyon SW, Marchant R, McConville JR, Munishi L, Nilsson D, Olang L, Olin S, Olsson L, Rogers PM, Rousk J, Sandén H, Sasaki N, Shoemaker A, Smith B, Thai Huynh Phuong L, Varela Varela A, Venkatappa M, Vico G, Von Uexkull N, Wamsler C, Wondie M, Zapata P, Zapata Campos MJ, Manzoni S, Tompsett A. Pathways from research to sustainable development: Insights from ten research projects in sustainability and resilience. AMBIO 2024; 53:517-533. [PMID: 38324120 PMCID: PMC10920586 DOI: 10.1007/s13280-023-01968-4] [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: 08/21/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 02/08/2024]
Abstract
Drawing on collective experience from ten collaborative research projects focused on the Global South, we identify three major challenges that impede the translation of research on sustainability and resilience into better-informed choices by individuals and policy-makers that in turn can support transformation to a sustainable future. The three challenges comprise: (i) converting knowledge produced during research projects into successful knowledge application; (ii) scaling up knowledge in time when research projects are short-term and potential impacts are long-term; and (iii) scaling up knowledge across space, from local research sites to larger-scale or even global impact. Some potential pathways for funding agencies to overcome these challenges include providing targeted prolonged funding for dissemination and outreach, and facilitating collaboration and coordination across different sites, research teams, and partner organizations. By systematically documenting these challenges, we hope to pave the way for further innovations in the research cycle.
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Affiliation(s)
- Anna Scaini
- Department of Physical Geography, Stockholm University, 10691, Stockholm, Sweden.
- Bolin Centre for Climate Research, Stockholm University, 10691, Stockholm, Sweden.
| | - Joseph Mulligan
- Kounkuey Design Initiative (KDI), Los Angeles, CA, USA
- Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Stockholm, Sweden
| | - Håkan Berg
- Department of Physical Geography, Stockholm University, 10691, Stockholm, Sweden
- Bolin Centre for Climate Research, Stockholm University, 10691, Stockholm, Sweden
| | - Albert Brangarí
- Microbial Ecology, Department of Biology, Lund University, Lund, Sweden
| | - Vera Bukachi
- Kounkuey Design Initiative (KDI), Los Angeles, CA, USA
- University College London, London, UK
| | - Sebastian Carenzo
- Instituto de Estudios sobre la Ciencia y la Tecnología, Universidad Nacional de Quilmes/CONICET, Buenos Aires, Argentina
| | - Da Chau Thi
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Colin Courtney-Mustaphi
- Geoecology, Department of Environmental Sciences, University of Basel, Klingelbergstrasse 27, 4056, Basel, Switzerland
- Center for Water Infrastructure and Sustainable Energy (WISE) Futures, Nelson Mandela African Institution of Science and Technology, P.O. Box 9124, Nelson Mandela, Tengeru, Tanzania
| | - Anneli Ekblom
- Department of Archaeology and Ancient History, Uppsala University, 752 38, Uppsala, Sweden
| | - Hanne Fjelde
- Department of Peace and Conflict Research, Uppsala University, Uppsala, Sweden
| | - Mathias Fridahl
- Unit of Environmental Change, Department of Thematic Studies, Institution of Arts and Sciences, Linköping University, 581 83, Linköping, Sweden
| | - Anders Hansson
- Unit of Environmental Change, Department of Thematic Studies, Institution of Arts and Sciences, Linköping University, 581 83, Linköping, Sweden
| | - Lettice Hicks
- Microbial Ecology, Department of Biology, Lund University, Lund, Sweden
| | - Mattias Höjer
- Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Stockholm, Sweden
- Division of Strategic Sustainability Studies, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Stockholm, Sweden
| | - Benard Juma
- Department of Civil and Construction Engineering, Technical University of Kenya, P.O Box 52428-00200, Nairobi, Kenya
| | - Jaan-Henrik Kain
- Gothenburg Research Institute, University of Gothenburg, 405 30, Göteborg, Sweden
| | - Rebecca W Kariuki
- School of School of Sustainability, Arizona State University, Arizona, USA
- School of Life Sciences and Bio-Engineering, Nelson Mandela African Institution of Science and Technology, P.O Box 447, Arusha, Tanzania
| | - Soben Kim
- Faculty of Forestry Science) Dangkor, Royal University of Agriculture, P.O. Box 2696, Phnom Phnom, Cambodia
| | - Paul Lane
- Department of Archaeology and Ancient History, Uppsala University, 752 38, Uppsala, Sweden
- Department of Archaeology, University of Cambridge, Cambridge, UK
| | - Ainara Leizeaga
- Microbial Ecology, Department of Biology, Lund University, Lund, Sweden
- Department of Earth and Environmental Sciences, The University of Manchester, Michael Smith Building, Manchester, UK
| | - Regina Lindborg
- Department of Physical Geography, Stockholm University, 10691, Stockholm, Sweden
- Bolin Centre for Climate Research, Stockholm University, 10691, Stockholm, Sweden
| | - John Livsey
- Department of Physical Geography, Stockholm University, 10691, Stockholm, Sweden
- Bolin Centre for Climate Research, Stockholm University, 10691, Stockholm, Sweden
| | - Steve W Lyon
- Department of Physical Geography, Stockholm University, 10691, Stockholm, Sweden
- School of Environment and Natural Resources, Ohio State University, Columbus, OH, 43210, USA
| | - Rob Marchant
- School of Life Sciences and Bio-Engineering, Nelson Mandela African Institution of Science and Technology, P.O Box 447, Arusha, Tanzania
| | - Jennifer R McConville
- Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU), 75007, Uppsala, Sweden
| | - Linus Munishi
- School of School of Sustainability, Arizona State University, Arizona, USA
| | - David Nilsson
- Division of History of Science, Technology and Environment, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Luke Olang
- Department of Biosystems and Environmental Engineering, Technical University of Kenya, P.O. Box 52428-00200, Nairobi, Kenya
| | - Stefan Olin
- Department of Physical Geography and Ecosystem Science, Lund University, 22362, Lund, Sweden
| | - Lennart Olsson
- Lund University Centre for Sustainability Studies (LUCSUS), Lund University, Box 170, 22100, Lund, Sweden
| | - Peter Msumali Rogers
- Institute of Resource Assessment, University of Dar es Salaam, Dar es Salaam, Tanzania
| | - Johannes Rousk
- Microbial Ecology, Department of Biology, Lund University, Lund, Sweden
| | - Hans Sandén
- University of Natural Resources and Life Sciences (BOKU), Vienna, Austria
| | - Nophea Sasaki
- Natural Resources Management, Asian Institute of Technology, P.O. Box 4, Klong Luang, 12120, Pathum Thani, Thailand
| | - Anna Shoemaker
- Department of Archaeology and Ancient History, Uppsala University, 752 38, Uppsala, Sweden
| | - Benjamin Smith
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, Australia
| | - Lan Thai Huynh Phuong
- Department of Rural Development and Natural Resources Management, An Giang University, Long Xuyên, 90000, An Giang Province, Vietnam
- Vietnam National University, Ho Chi Minh City, 70000, Vietnam
| | - Ana Varela Varela
- London School of Economics, Department of Geography and Environment, London, UK
| | - Manjunatha Venkatappa
- LEET Intelligence Co., Ltd., Suan Prikthai, Muang Pathum Thani, 12000, Pathum Thani, Thailand
| | - Giulia Vico
- Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), 750 07, Uppsala, Sweden
| | - Nina Von Uexkull
- Department of Peace and Conflict Research, Uppsala University, Uppsala, Sweden
| | - Christine Wamsler
- Lund University Centre for Sustainability Studies (LUCSUS), Lund University, Box 170, 22100, Lund, Sweden
- Centre of Natural Hazards and Disaster Science (CNDS), Uppsala, Sweden
| | - Menale Wondie
- Amhara Regional Agricultural Research Institute (ARARI), Bahir Dar, Ethiopia
| | - Patrick Zapata
- School of Public Administration, University of Gothenburg, Gothenburg, Sweden
| | - María José Zapata Campos
- Gothenburg Research Institute, University of Gothenburg, 405 30, Göteborg, Sweden
- Department of Business Administration, School of Business, Economics and Law, University of Gothenburg, 40530, Gothenburg, Sweden
| | - Stefano Manzoni
- Department of Physical Geography, Stockholm University, 10691, Stockholm, Sweden
- Bolin Centre for Climate Research, Stockholm University, 10691, Stockholm, Sweden
| | - Anna Tompsett
- Institute for International Economic Studies, Stockholm University, 10691, Stockholm, Sweden
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9
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Morrow N, Mock NB, Gatto A, Colantoni A, Salvati L. Farm forests, seasonal hunger, and biomass poverty: Evidence of induced intensification from panel data in the Ethiopian Highlands. AMBIO 2024; 53:435-451. [PMID: 38100004 PMCID: PMC10837407 DOI: 10.1007/s13280-023-01954-w] [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: 10/03/2022] [Revised: 07/31/2023] [Accepted: 10/09/2023] [Indexed: 02/03/2024]
Abstract
Seasonal hunger is the most common food insecurity experience for millions of small dryland farmers. This study tests the relationships between food insecurity, farm forests, and biomass poverty using a longitudinal dataset from the Amhara region of Ethiopia. These data form part of the Ethiopia Socioeconomic Survey, which collected panel data over three survey rounds from 530 households between 2011 and 2016. This dataset represents a collection of unique socioeconomic, wellbeing, and micro-land use measures, including farm forests. Hierarchical mixed effect regression models assessed the relationship between food insecurity and farm forests as well as the conditional effects of biomass poverty among the poorest farmers and women-headed households. Over a six-year study period, farmers reported increased stress from smaller land holdings, higher prices, and climate-related shocks. A clear trend towards spontaneous dispersed afforestation is observed by both researchers and satellite remote sensing. Model results indicate, dedicating approximately 10% of farm area to forest reduces months of food insecurity by half. The greatest reductions in food insecurity from farm forests are reported by ultra-poor and crop residue-burning households, suggesting that biomass poverty may be a major constraint to resilient food security on these farms. This research provides novel quantitative evidence of induced intensification and food security impacts of farm management preserving and building stores of biomass value as green assets. The results reported here have important implications for nature-based solutions as a major strategy to achieve sustainable development in some contexts.
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Affiliation(s)
- Nathan Morrow
- Tulane University School of Public Health & Tropical Medicine, 1440 Canal Street, New Orleans, LA, 70112, USA.
| | - Nancy B Mock
- Tulane University School of Public Health & Tropical Medicine, 1440 Canal Street, New Orleans, LA, 70112, USA
| | - Andrea Gatto
- Wenzhou-Kean University, Zhejiang Province, Wenzhou, 325060, China.
- Centre for Studies on Europe, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan.
| | - Andrea Colantoni
- Department of Agriculture and Forest Science, Università Della Tuscia, 01100, Viterbo, Italy
| | - Luca Salvati
- Department of Methods and Models for Economics, Territory and Finance (MEMOTEF), Faculty of Economics, Sapienza University of Rome, Via del Castro Laurenziano 9, I-0061, Rome, Italy
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10
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den Braber B, Hall C, Brandt M, Reiner F, Mugabowindekwe M, Rasmussen LV. Even low levels of tree cover improve dietary quality in West Africa. PNAS NEXUS 2024; 3:pgae067. [PMID: 38404357 PMCID: PMC10890828 DOI: 10.1093/pnasnexus/pgae067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 01/29/2024] [Indexed: 02/27/2024]
Abstract
Forests are attracting attention as a promising avenue to provide nutritious and "free" food without damaging the environment. Yet, we lack knowledge on the extent to which this holds in areas with sparse tree cover, such as in West Africa. This is largely due to the fact that existing methods are poorly designed to quantify tree cover in drylands. In this study, we estimate how various levels of tree cover across West Africa affect children's (aged 12-59 months) consumption of vitamin A-rich foods. We do so by combining detailed tree cover estimates based on PlanetScope imagery (3 m resolution) with Demographic Health Survey data from >15,000 households. We find that the probability of consuming vitamin A-rich foods increases from 0.45 to 0.53 with an increase in tree cover from the median value of 8.8 to 16.8% (which is the tree cover level at which the predicted probability of consuming vitamin A-rich foods is the highest). Moreover, we observe that the effects of tree cover vary across poverty levels and ecoregions. The poor are more likely than the non-poor to consume vitamin A-rich foods at low levels of tree cover in the lowland forest-savanna ecoregions, whereas the difference between poor and non-poor is less pronounced in the Sahel-Sudan. These results highlight the importance of trees and forests in sustainable food system transformation, even in areas with sparse tree cover.
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Affiliation(s)
- Bowy den Braber
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark
| | - Charlotte Hall
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark
- Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, UK
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark
| | - Maurice Mugabowindekwe
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark
| | - Laura Vang Rasmussen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark
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11
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Liu S, Brandt M, Nord-Larsen T, Chave J, Reiner F, Lang N, Tong X, Ciais P, Igel C, Pascual A, Guerra-Hernandez J, Li S, Mugabowindekwe M, Saatchi S, Yue Y, Chen Z, Fensholt R. The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe. SCIENCE ADVANCES 2023; 9:eadh4097. [PMID: 37713489 PMCID: PMC10881069 DOI: 10.1126/sciadv.adh4097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/15/2023] [Indexed: 09/17/2023]
Abstract
Trees are an integral part in European landscapes, but only forest resources are systematically assessed by national inventories. The contribution of urban and agricultural trees to national-level carbon stocks remains largely unknown. Here we produced canopy cover, height and above-ground biomass maps from 3-meter resolution nanosatellite imagery across Europe. Our biomass estimates have a systematic bias of 7.6% (overestimation; R = 0.98) compared to national inventories of 30 countries, and our dataset is sufficiently highly resolved spatially to support the inclusion of tree biomass outside forests, which we quantify to 0.8 petagrams. Although this represents only 2% of the total tree biomass, large variations between countries are found (10% for UK) and trees in urban areas contribute substantially to national carbon stocks (8% for the Netherlands). The agreement with national inventory data, the scalability, and spatial details across landscapes, including trees outside forests, make our approach attractive for operational implementation to support national carbon stock inventory schemes.
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Affiliation(s)
- Siyu Liu
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Nord-Larsen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Jerome Chave
- Laboratoire Evolution et Diversité Biologique, CNRS, UPS, IRD, Université Paul Sabatier, Toulouse, France
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Nico Lang
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Xiaoye Tong
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France
| | - Christian Igel
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Adrian Pascual
- Department of Geographical Sciences, University of Maryland, College Park, MD, USA
| | - Juan Guerra-Hernandez
- Forest Research Center, School of Agriculture, University of Lisbon, Lisbon, Portugal
| | - Sizhuo Li
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Maurice Mugabowindekwe
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Sassan Saatchi
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Yuemin Yue
- Key Laboratory for Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
| | - Zhengchao Chen
- Airborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
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