Bee alert: Scientists warn of declines in Asia’s important pollinators
IMAGE: ASIAN BEE MONTAGE FROM THE NEW ARTICLE view more
CREDIT: PHOTOS COURTESY: MICHAEL ORR, VASUKI BELAVADI, HAUKE KOCH, QINGSONG ZOU AND XIN ZHOU
Bee pollinators are a crucial link to food production and food security for more than half the world’s population living in Asia – but few species have been closely studied or assessed for their range, numbers and conservation status.
The warning comes as 74 scientists working in 13 Asian and other countries warn that the region’s bees – which comprise 15% of the world’s known bee species but only 1% of records – could be under threat due to major habitat loss to urbanisation, pollutants, alien species, climate change and other human forces.
“While most studies of bees take place in high-income countries, they have all raised concerns and calls for more conservation or management solutions to curb or stop declines of bees and other pollinators,” says entomologist Dr Michael Orr, from Germany’s Staatliches Museum für Naturkunde Stuttgart, a lead author in a new article in Biological Conservation.
“Given the key roles native bees play, both ecologically and economically in a region like Asia, understanding how to manage and maintain bee diversity is crucial to sustainable development in the region,” says Dr Orr, who also is a member of the International Union for Conserving Nature (IUCN) Wild Bee Specialist Group (Asia) as well as Beijing and America ecological societies.
“The biggest impediment is a lack of knowledge about where and how species live, and foundationally an inability to even identify different species.”
In the meantime, the authors call for attention flagship social species such as native honey bees, stingless bees and bumble bees to start the important conservation work. Flagship species can be essential for conservation messaging and to support broader conservation of the other 85-90% of non-social bees, the experts say.
Solitary flagship bees are also important, including the world’s largest bee, the Indonesian Megachile pluto, which is frequently sold online to western buyers for exorbitant sums despite being listed as Vulnerable by the IUCN.
The authors call for trans-border partnerships to work on bee and other pollinator management, given the complex political dynamics of the region. As well, active restoration of more intact or threatened habitat should be prioritised, given “dire threats” such as land conservation to palm oil and widescale agricultural expansion.
“Science and research collaborations can help mend some of these divisions, but more open sharing of specimens and data will be key,” adds Flinders University co-author, Dr James Dorey.
“Ecological studies at the national and regional level must be conducted to better understand how best we can maintain pollinator communities and the ecosystem services they provide.”
To reach their maximum potential, the scientists say conservation efforts must also be multi-disciplinary and cross-sectoral, bridging fields and methods as well as governmental, NGO and research personnel to better translate research into practical applications and effective conservation management for bees across Asia.
The article, Opportunities and challenges in Asian bee research and conservation (2023) by Natapot Warrit, John Ascher … Michael C Orr … has been published in Biological Conservation DOI: 10.1016/j.biocon.2023.110173
Please credit photos courtesy: Michael Orr, Vasuki Belavadi, Hauke Koch, Qingsong Zou and Xin Zhou
https://drive.google.com/drive/folders/1DH41W4RaVKX5N76UNp2PJ0w-YRQ5nmli
JOURNAL
Biological Conservation
METHOD OF RESEARCH
Observational study
SUBJECT OF RESEARCH
Animals
ARTICLE TITLE
Opportunities and challenges in Asian bee research and conservation
ARTICLE PUBLICATION DATE
7-Aug-2023
Asia bee
Ceratina sp Photo Qingsong Zhou
Apis dorsata
CREDIT
Photo Michael Orr
Bees and ETRVs: an unlikely match-up of the natural world and electric trackless rubber-tyred vehicles
IMAGE: LOW-CARBON ROUTING ISSUES CAN BE SOLVED BY USING IMPROVED ARTIFICIAL BEE COLONIES (IABC) TO PROVIDE OPTIMAL ROUTES TO MINIMIZE ENERGY CONSUMPTION AND OTHER LIMITATIONS THAT COME WITH ELECTRIC TRACKLESS RUBBER-TYRED VEHICLES (ETRVS). view more
CREDIT: YINAN GUO, CHINA UNIVERSITY OF MINING AND TECHNOLOGY (BEIJING)
The natural world works off algorithms, so researchers thought to use one of the world’s most industrious animals, the honeybee, as a basis for determining energy-efficient routes in electric trackless rubber-tyred vehicles (ETRVs).
Bees are an effective, integral and orderly part of the animal kingdom, though learning to stop and smell the roses isn’t the only thing we can borrow from the bees. The foraging behavior of honeybees might be a useful tool in figuring out the best, most energy-efficient routes for electric trackless rubber-tyred vehicles (ETRVs) which are a crucial piece of equipment for mining operations and transportation. Limitations of ETRVs include excessive energy consumption, potential operational safety issues and a lack of control when considering load size, slope, and vehicle avoidance. Finding out the routes these vehicles can take by using an improved artificial bee colony (IABC) algorithm can minimize potential issues all while reducing the energy consumption of the vehicle. This has positive implications not only economically and environmentally, but can also improve the overall safety and function of the vehicles for a smarter future of ETRVs.
Researchers published their results in Complex System Modeling and Simulation on August 02.
“The experimental results on four real-world instances indicate that improved artificial bee colony algorithm (IABC) outperforms other comparative algorithms and the special designs in its three phases effectively avoid premature convergence and speed up convergence,” said Yinan Guo, researcher and author of the study.
IABC isn’t the only algorithm tested in this study, though it did seem to be the most effective in setting up routes that are energy efficient. Other colony models researchers used to determine what route may be the most effective include particle swarm optimization, which utilizes the randomly selected (stochastic) social interactions of swarming agents to look for the best solution in a given space. The other algorithms used are genetic algorithms, which employ the theory of “natural evolution” for problem-solving, and ant colony optimization which ideally will find the shortest path to a solution.
Parameters were set amongst all four algorithms used to ensure a fair comparison, including population size, the maximum number participating in a neighborhood search and weight. The artificial bee colony (and the other colony models) is tasked with searching for a food source. The best, least energetically costly route the artificial bees take is likely the best, least energetically costly option for the ETRVs, too.
Within the IABC there are three strategies: adaptive neighborhood search for employed bees (those who go to the food source and return to the hive and dance), adaptive selection probability for onlookers (those who evaluate nectar information via the dance of employed bees) and knowledge-driven initialization for scout bees (employed bees whose food source has been abandoned and searches for a new food source).
“IABC achieves the most competitive solution on all instances and is significantly better than its variants. This proves that three newly designed strategies are helpful to effectively enhance the algorithm performance,” said Guo.
To solve the problem of electric vehicle routing, load size, slope, energy consumption, vehicle avoidance and driving state all need to be considered, and the adaptive neighborhood search strategy helps guide the bees to the more appropriate area. The onlookers adjust their selection of food sources based on quality and evolution efficiency, and the scouts help to improve convergence efficiency and the population diversity, producing better solutions for the population.
The implicit parallels among bees searching for the best route to reach their food and an ETRV taking the most energy-efficient route can be seen plainly when given the comparison. With the increasing number of service nodes, the search space is expanded dramatically, and the algorithms performance becomes worse. The most effective solution tops out at 15 service node stops, with a particular pattern between the nodes that should minimize carbon emissions and energy consumption.
Even though researchers have found promise in utilizing IABC to solve some of the issues with routing the ETRVs, future work involves scheduling heterogeneous TRVs with variable powers built-in to the vehicle. This will help to eliminate some of the problems related to energy consumption the IABC doesn’t quite account for, such as the limited ability for cruising, speed adjustment and road conditions. These are complex issues to address with any algorithm, but the groundwork done using IABC might be enough for studies in the coming years.
Yinan Guo, Shirong Ge, Yao Huang, Yizhe Zhang, Ersong Jiang, and Bin Cheng of the School of Mechanical and Electronic Engineering at China University of Mining and Technology (Beijing), with Yinan Guo and Shirong Ge also of the Inner Mongolia Research Institute at China University of Mining and Technology (Beijing), and Shengxiang Yang of the Institute of Artificial Intelligence, School of Computer Science and Informatics at De Montfort University contributed to this research.
This work was supported by the National Key R&D Program of China, the Natural National Science Foundation of China, the Royal Society International Exchanges 2020 cost Share, and the 111 Project.
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About Complex System Modeling and Simulation
Complex System Modeling and Simulation is a peer-reviewed international academic journal. Aiming to provide an academic exchange platform, it publishes high-level original research papers and review papers in the fields of complex system modeling, simulation, optimization and control after strict peer review. The scope includes but is not limited to the following topics in terms of theories, methods, technologies as well as applications in manufacturing systems, social systems, service systems, military systems, medical systems, energy systems, and unmanned systems, etc.
About Tsinghua University Press
Established in 1980, belonging to Tsinghua University, Tsinghua University Press (TUP) is a leading comprehensive higher education and professional publisher in China. Committed to building a top-level global cultural brand, after 42 years of development, TUP has established an outstanding managerial system and enterprise structure, and delivered multimedia and multi-dimensional publications covering books, audio, video, electronic products, journals and digital publications. In addition, TUP actively carries out its strategic transformation from educational publishing to content development and service for teaching & learning and was named First-class National Publisher for achieving remarkable results.
JOURNAL
Complex System Modeling and Simulation
ARTICLE TITLE
Low-Carbon Routing Based on Improved Artificial Bee Colony Algorithm for Electric Trackless Rubber-Tyred Vehicles
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