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Record W4384406778 · doi:10.1111/ibi.13255

British Ornithologists' Union <scp>Godman‐Salvin</scp> Prize

2023· article· en· W4384406778 on OpenAlexaboutno aff
Anthony David Fox

Bibliographic record

VenueIbis · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicInsects and Parasite Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsZoologyBiologyGeographyFishery

Abstract

fetched live from OpenAlex

Cao Lei Cao Lei has been passionate about birds since she grew up among pigeons and domestic geese as a small child. This passion was kindled by her careful observation and understanding of urban birds as a child and student, but remains pre-eminent in all she does, perhaps the secret behind her success as a communicator of science and mentor to her numerous students. It also explains her quite extraordinary ability to coordinate waterbird researchers not just within China, but also in Russia, Mongolia, Japan and Korea, throughout Far East Asia and much of the world, in pioneering research and monitoring programmes that have not just established new knowledge in Asia, but broken new ground in ornithology and movement ecology. Her contribution in creating functional research and conservation networks across cultural divides in regions formerly lacking scientific collaboration has been truly impressive. After graduating with a Biology degree from Hunan Normal University in her home town of Changsha in 1991 and a PhD from Lanzhou University, Gansu Province in 2005, Cao Lei was appointed Associate Professor at the School of Life Sciences, University of Science and Technology of China (USTC), Hefei, Anhui Province in December 2005. Due to her prodigious output, Lei was promoted to Full Professor at USTC in December 2010 and in 2013, she moved to take up her present position as Professor at the State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences in Beijing. Lei studied the breeding biology and behaviour of Red-footed Boobies (Sula sula) on Dong Island, in the Xisha Archipelago of the northern South China Sea, during the 2003 and 2004 breeding seasons, but by then her attention was already turning to waterbirds of freshwater habitats. Lei had met Mark Barter, adviser for the first ever WWF waterbird surveys of the Middle and Lower Yangtze River Floodplain in 2004 and 2005, and had become fascinated by the systematic approach of counting waterbirds at wetlands, especially by applying shorebird survey techniques to the massive inland freshwater wetlands of the Yangtze River Floodplain. Mark and Lei were instrumental in developing pioneer census methods, training survey teams and compiling survey reports accessible to all, leading to the generation of the first rigorous flyway population estimates for many of the large bodied waterbirds of the region published in two ground-breaking publications in Biological Conservation in 2008 (141: 2301–2309) and 2010 (143: 650–659). As her studies showed declines among many waterbirds of the Yangtze since the 1990s, so her research expanded to attempt to understand better the ecology of these species, their habitat requirements and their conservation needs (for example Aquatic Conservation 21: 82–91). Much of Professor Cao Lei's research work since her PhD has therefore centred on wetland and biodiversity ecology and conservation, and movement ecology. All of her research has been conservation orientated, focussing on relationships between wetland quality and waterbird diversity and abundance in an attempt to understand the causes behind local population declines in wintering waterbirds. An early triumph was the initiation of autecological studies of the wintering Lesser White-fronted Goose Anser erythropus at East Dongting Lake by PhD student Wang Xin, which highlighted some of the nutritional and energetic challenges of being a small specialist feeding herbivore that helps explain its global rarity (Ibis 155: 576–592). She also threw her energies into looking at the effects of hydrological change on the productivity and growth of submerged macrophytes that (in the form of overwintering subterranean rhizomes) are such important sources of food for critical but often declining species such as wintering Swan Geese Anser cygnoides, swans and cranes. However, it quickly became apparent that not all the pressures on Chinese wintering waterbird populations were the result of factors operating within China, necessitating a more flyway-based approach and broader international collaboration. In the almost complete absence of avian ringing-recovery data in Far East Asia, Lei immediately embraced the use of the latest cutting-edge technological innovations in IT and microelectronics that have recently provided GPS tracking devices deployable on waterbirds. Working closely with a hard-won network of collaborating researchers and institutes across the Russian Arctic and taiga biomes, as well as in the Mongolian, Chinese and Russian steppe regions, Lei and the team marked many thousands of waterbirds of many different species with tracking devices, and followed them back to their Chinese wintering quarters. Using these techniques, combined with genetic studies, she and her team have established, in just a very few years, previously unknown flyway relationships and biogeographical subpopulations of long-distance migratory East Asian waterbirds, patterns for which it had taken decades to establish in Europe and North America using conventional metal ringing-recovery programmes. In this way, Lei and her group have been able to plot the migration pathways, including critical spring and autumn staging sites along their length, between summer breeding areas and wintering sites for more than 20 species (summarized in many articles, including special issues of Wildfowl in 2020 and Avian Research in 2022). In particular, Lei and her group, with Mongolian support and collaboration, were able to reveal some of the secrets of the annual cycle of two endemic species to the region, the Bar-headed Goose Anser indicus and the Swan Goose, as well as the many conservation challenges that face these species. Closely cooperating in cross border research with Russian partners, her team's tracking data has also been instrumental in understanding the threats to the IUCN Endangered Oriental Stork Ciconia boyciana during its annual cycle and help guide its effective conservation management and early population recovery. She has also been bold and innovative in introducing her team to the application of other “big datasets” to aid their interpretation of emerging patterns. In particular, using large-scale land-use cover imagery, snow cover, precipitation, wind and other remote sensing macro-environmental datasets to understand the effects of land-use, weather and climate change on individual migration patterns of waterbirds from a host of species, including testing the “green wave” hypothesis explaining the migration progress of Arctic nesting herbivores (Nature Communications 10: 2187). Until recently, much of Lei's work has centred on her beloved Yangtze River Floodplain wetlands, her core interest and expertise. Indeed, as I write this, Lei and her dedicated team are busy completing and reporting the incredibly complex logistics of yet another full coordinated survey of all the numerous Yangtze wetlands in early 2023. However, never someone to stay still, Lei's energies are increasingly looking to other problems around the globe, collaborating with scientists in North America, Europe, Mongolia and India (among many others) to provide the scientific basis for effective nature conservation interventions for a range of different taxa throughout the northern hemisphere. Cao Lei has developed an impressive research group, including a vibrant collection of young enthusiastic students. Her enthusiasm and joy in the field, especially under a dense flock of overflying geese in the company of undergraduate students, most of whom have never witnessed such Chinese wildlife spectaculars, is not to be forgotten. Her passion for wetland conservation thus lives on in generations of students, who take such experiences forward in their hearts to contribute to China's dream of a more “ecological” society, more in harmony with its environment. She has published over 100 internationally refereed articles, including contributions to Nature, Current Biology and Diversity and Distributions. It is cheering to see her work gaining increasing international respect, reflected in invitations to give plenaries/keynote speeches at the 26th and 27th International Ornithological Congresses (Tokyo, 2014 and Vancouver 2018), 20th National Congress of Ecology of China (Shanghai, 2021) and the Alfred Newton Lecture to the British Ornithologists' Union (Warwick 2019). Such international recognition, including the well-deserved Godman-Salvin Prize, help strengthen her reputation within China, where her contributions are already acknowledged in the form of other research awards and academic prizes, including the Cheng Tso-Hsin Young Ornithologist Prize of the China Ornithological Society (2006) and Young Science and Technology Award of the China Zoological Society (2013). More important, such recognition levers continued support for Professor Cao Lei to persist with her quest to gain global recognition for the massive importance of the ephemeral wetlands of the Yangtze River Floodplain. These rank among the world's most outstanding inundation wetlands and their ecosystems urgently need her expertise to protect them more effectively for the enormous ecosystem services they provide and for the enjoyment of generations to come.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.012

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.256
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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