Evidence map›Paper›PMID 41787574›Full record

ArticleMovement ecology2026

When experience breeds variability: age-dependent movement diversity in a successful shorebird.

Yang Wu, Weipan Lei, Jing Zhang, Chun Zhao, Jili He, Ziqiang Zhu, Yu Liu, Jin Liu, De Chen, Zhijun Ma and 4 more

Abstract read
In one paragraph

Article in Movement ecology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Yang WuGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510260, China.
Weipan LeiKey Laboratory for Biodiversity Sciences and Ecological Engineering, Ministry of Education, College of Life Sciences, Beijing Normal University, Beijing, 100875, China. leiweipan@bnu.edu.cn.
Jing ZhangState Key Laboratory of Wetland Conservation and Restoration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing, 100091, China.
Chun ZhaoSchool of the Environment, The University of Queensland, Brisbane, Qld, 4072, Australia.
Jili HeKey Laboratory for Biodiversity Sciences and Ecological Engineering, Ministry of Education, College of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Ziqiang ZhuSchool of Ecological and Nature Conservation, Beijing Forestry University, Beijing, 100083, China.
Yu LiuState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100107, China.
Jin LiuInstitute of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China.
De ChenKey Laboratory for Biodiversity Sciences and Ecological Engineering, Ministry of Education, College of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Zhijun MaShanghai Institute of Infectious Disease and Biosecurity, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of the Yangtze River Estuary, Institute of Biodiversity Science, School of Life Sciences, Fudan University, Shanghai, 200433, China.
Tatsuya AmanoSchool of the Environment, The University of Queensland, Brisbane, Qld, 4072, Australia.
Min ZhangGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510260, China.
Zhengwang ZhangKey Laboratory for Biodiversity Sciences and Ecological Engineering, Ministry of Education, College of Life Sciences, Beijing Normal University, Beijing, 100875, China. zzw@bnu.edu.cn.
Richard A FullerSchool of the Environment, The University of Queensland, Brisbane, Qld, 4072, Australia.

Funding

China Scholarship Council Grant 202106040115GDAS' Project of Science and Technology 2022GDASZH-2022010106National Key Research and Development Program of China 2022YFF0802400National Natural Science Foundation of China 31830089National Natural Science Foundation of China 32001098National Natural Science Foundation of China 32270518National Natural Science Foundation of China 32470491
6 · The paper itself

Abstract

Migratory species are vulnerable to habitat loss, especially migratory birds that rely on multiple stopover sites during migration. According to conventional understanding, migratory birds typically show reduced behavioral variability as they age, with their migration routes becoming increasingly fixed through experience, which may make them even more vulnerable to habitat loss along their flyway. Indeed, in the East Asian-Australasian Flyway (EAAF), most waterbird populations have rapidly declined due to habitat loss and land use changes. However, some migratory species like the Pied Avocet Recurvirostra avosetta have maintained or even increased their populations. We investigated whether this success might be linked to age-related patterns in migration behavior. Using satellite tracking technology, we monitored the movement behaviors of 48 adult and 20 juvenile Pied Avocets in eastern China from 2021 to 2024. Contrary to expectations, adults exhibited greater movement variability than juveniles. In the first two years of life, Pied Avocets performed relatively limited movements, adopting conservative migration strategies, which may reduce mortality risks. In contrast, experienced adults showed greater variability in their movement patterns. Some migrated to more southerly wintering grounds or more northerly breeding sites, and occasionally pioneered entirely new flight paths. Compared to juveniles, adult birds also showed larger home ranges during the pre-migration period and greater within-season movements during the non-migration period. This age-related increase in ranging behavior and movement variability may contribute to their population resilience in rapidly changing environments. Our findings suggest that the combination of risk-averse strategies in young birds and diverse movement strategies within adult populations, ranging from conservative to exploratory individuals, might represent an important adaptation mechanism for long-lived species facing environmental change.

Indexed as

Behavioral variabilityHome rangeJuvenileMigrationSatellite tracking

Identifiers

PMID41787574
PMCPMC13072586

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.