Distinguishing local and global correlates of population change in migratory species
Aim Understanding the processes driving population declines in migratory species can be challenging. Not only are monitoring data spatially and temporally sparse, but conditions in one location can carry over to indirectly (and disproportionately) affect the population in another location. Here, we...
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ftdatacite:10.13016/m2zt8t-w6wg 2023-05-15T15:12:26+02:00 Distinguishing local and global correlates of population change in migratory species Dhanjal‐Adams, Kiran L. Fuller, Richard A. Murray, Nicholas J. Studds, Colin E. Wilson, Howard B. Milton, David A. Kendall, Bruce E. 2019 https://dx.doi.org/10.13016/m2zt8t-w6wg http://mdsoar.org/handle/11603/13341 unknown John Wiley & Sons Ltd Attribution 4.0 International (CC BY 4.0) This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. https://creativecommons.org/licenses/by/4.0 CC-BY migratory species shorebirds Moreton Bay Australia and the East Asian–Australasian Flyway CreativeWork article 2019 ftdatacite https://doi.org/10.13016/m2zt8t-w6wg 2021-11-05T12:55:41Z Aim Understanding the processes driving population declines in migratory species can be challenging. Not only are monitoring data spatially and temporally sparse, but conditions in one location can carry over to indirectly (and disproportionately) affect the population in another location. Here, we explore whether remote factors can sequentially, and potentially cumulatively, influence local population fluctuations in declining populations of shorebirds. Location Moreton Bay (Australia) and the East Asian–Australasian Flyway. Methods We use N‐mixture models to account for variable observer effort and estimate yearly population growth rate. We then use least squares regressions to correlate population growth rates with remotely sensed climate anomalies at different migratory stages. From this, we estimate species‐specific climate sensitivity indices and explore whether species which are declining more rapidly, or which rely more heavily on areas undergoing rapid habitat loss, have higher climate sensitivity indices. Results We find that species which rely more on the Yellow Sea during migratory stopover (a region which has undergone severe habitat loss) are more sensitive to rainfall anomalies in their Arctic breeding grounds, suggesting that habitat loss reduces the resilience of shorebirds to climate extremes. Furthermore, species with higher sensitivities to climatic conditions during stopover are also those which are declining quickest, suggesting that declining populations may also be less resilient to climate fluctuations at bottleneck sites. We also observed species‐specific correlations between climate anomalies at all migratory stages and population growth rates, primarily for eastern curlew and lesser sand plover. Main conclusion By applying methods in combination, it is possible to use citizen science data from a single location in a flyway of over 160 sites up to 11,680 km apart, to investigate how different stressors correlate with local population dynamics. Article in Journal/Newspaper Arctic DataCite Metadata Store (German National Library of Science and Technology) Arctic Moreton ENVELOPE(-46.033,-46.033,-60.616,-60.616) Moreton Bay ENVELOPE(-117.952,-117.952,75.734,75.734) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
migratory species shorebirds Moreton Bay Australia and the East Asian–Australasian Flyway |
spellingShingle |
migratory species shorebirds Moreton Bay Australia and the East Asian–Australasian Flyway Dhanjal‐Adams, Kiran L. Fuller, Richard A. Murray, Nicholas J. Studds, Colin E. Wilson, Howard B. Milton, David A. Kendall, Bruce E. Distinguishing local and global correlates of population change in migratory species |
topic_facet |
migratory species shorebirds Moreton Bay Australia and the East Asian–Australasian Flyway |
description |
Aim Understanding the processes driving population declines in migratory species can be challenging. Not only are monitoring data spatially and temporally sparse, but conditions in one location can carry over to indirectly (and disproportionately) affect the population in another location. Here, we explore whether remote factors can sequentially, and potentially cumulatively, influence local population fluctuations in declining populations of shorebirds. Location Moreton Bay (Australia) and the East Asian–Australasian Flyway. Methods We use N‐mixture models to account for variable observer effort and estimate yearly population growth rate. We then use least squares regressions to correlate population growth rates with remotely sensed climate anomalies at different migratory stages. From this, we estimate species‐specific climate sensitivity indices and explore whether species which are declining more rapidly, or which rely more heavily on areas undergoing rapid habitat loss, have higher climate sensitivity indices. Results We find that species which rely more on the Yellow Sea during migratory stopover (a region which has undergone severe habitat loss) are more sensitive to rainfall anomalies in their Arctic breeding grounds, suggesting that habitat loss reduces the resilience of shorebirds to climate extremes. Furthermore, species with higher sensitivities to climatic conditions during stopover are also those which are declining quickest, suggesting that declining populations may also be less resilient to climate fluctuations at bottleneck sites. We also observed species‐specific correlations between climate anomalies at all migratory stages and population growth rates, primarily for eastern curlew and lesser sand plover. Main conclusion By applying methods in combination, it is possible to use citizen science data from a single location in a flyway of over 160 sites up to 11,680 km apart, to investigate how different stressors correlate with local population dynamics. |
format |
Article in Journal/Newspaper |
author |
Dhanjal‐Adams, Kiran L. Fuller, Richard A. Murray, Nicholas J. Studds, Colin E. Wilson, Howard B. Milton, David A. Kendall, Bruce E. |
author_facet |
Dhanjal‐Adams, Kiran L. Fuller, Richard A. Murray, Nicholas J. Studds, Colin E. Wilson, Howard B. Milton, David A. Kendall, Bruce E. |
author_sort |
Dhanjal‐Adams, Kiran L. |
title |
Distinguishing local and global correlates of population change in migratory species |
title_short |
Distinguishing local and global correlates of population change in migratory species |
title_full |
Distinguishing local and global correlates of population change in migratory species |
title_fullStr |
Distinguishing local and global correlates of population change in migratory species |
title_full_unstemmed |
Distinguishing local and global correlates of population change in migratory species |
title_sort |
distinguishing local and global correlates of population change in migratory species |
publisher |
John Wiley & Sons Ltd |
publishDate |
2019 |
url |
https://dx.doi.org/10.13016/m2zt8t-w6wg http://mdsoar.org/handle/11603/13341 |
long_lat |
ENVELOPE(-46.033,-46.033,-60.616,-60.616) ENVELOPE(-117.952,-117.952,75.734,75.734) |
geographic |
Arctic Moreton Moreton Bay |
geographic_facet |
Arctic Moreton Moreton Bay |
genre |
Arctic |
genre_facet |
Arctic |
op_rights |
Attribution 4.0 International (CC BY 4.0) This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. https://creativecommons.org/licenses/by/4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.13016/m2zt8t-w6wg |
_version_ |
1766343116303892480 |