Improving assessments of data‐limited populations using life‐history theory
1. Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct popu...
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Online Access: | http://nora.nerc.ac.uk/id/eprint/529986/ https://nora.nerc.ac.uk/id/eprint/529986/1/N529986JA.pdf https://doi.org/10.1111/1365-2664.13863 |
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ftnerc:oai:nora.nerc.ac.uk:529986 2023-05-15T15:44:58+02:00 Improving assessments of data‐limited populations using life‐history theory Horswill, Cat Manica, Andrea Daunt, Francis Newell, Mark Wanless, Sarah Wood, Matthew Matthiopoulos, Jason 2021-06 text http://nora.nerc.ac.uk/id/eprint/529986/ https://nora.nerc.ac.uk/id/eprint/529986/1/N529986JA.pdf https://doi.org/10.1111/1365-2664.13863 en eng Wiley https://nora.nerc.ac.uk/id/eprint/529986/1/N529986JA.pdf Horswill, Cat; Manica, Andrea; Daunt, Francis orcid:0000-0003-4638-3388 Newell, Mark; Wanless, Sarah; Wood, Matthew; Matthiopoulos, Jason. 2021 Improving assessments of data‐limited populations using life‐history theory. Journal of Applied Ecology, 58 (6). 1225-1236. https://doi.org/10.1111/1365-2664.13863 <https://doi.org/10.1111/1365-2664.13863> cc_by_4 CC-BY Ecology and Environment Publication - Article PeerReviewed 2021 ftnerc https://doi.org/10.1111/1365-2664.13863 2023-02-04T19:51:57Z 1. Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct population assessments by filling in missing values from surrogate species or other populations of the same species. However, using these independent surrogate values concurrently with observed data neglects the life‐history trade‐offs that connect the different aspects of a population's demography, thus introducing biases that could ultimately lead to erroneous management decisions. 2. We use a Bayesian hierarchical approach to combine fragmented multi‐population data with established life‐history theory and reconstruct population‐specific demographic data across a substantial part of a species breeding range. We apply our analysis to a long‐lived colonial species, the black‐legged kittiwake Rissa tridactyla, that is classified as globally Vulnerable and is highly threatened by increasing anthropogenic pressures, such as offshore renewable energy development. We then use a projection analysis to examine how the reconstructed demographic parameters may improve population assessments, compared to models that combine observed data with independent surrogate values. 3. Reconstructed demographic parameters can be utilised in a range of population modelling approaches. They can also be used as reference estimates to assess whether independent surrogate values are likely to over or underestimate missing demographic parameters. We show that surrogate values from independent sources are often used to fill in missing parameters that have large potential demographic impact, and that resulting biases can be driven in unpredictable directions thus precluding assessments from being consistently precautionary. 4. Synthesis and applications: Our study dramatically increases the spatial coverage of population‐specific demographic data ... Article in Journal/Newspaper Black-legged Kittiwake rissa tridactyla Natural Environment Research Council: NERC Open Research Archive Journal of Applied Ecology 58 6 1225 1236 |
institution |
Open Polar |
collection |
Natural Environment Research Council: NERC Open Research Archive |
op_collection_id |
ftnerc |
language |
English |
topic |
Ecology and Environment |
spellingShingle |
Ecology and Environment Horswill, Cat Manica, Andrea Daunt, Francis Newell, Mark Wanless, Sarah Wood, Matthew Matthiopoulos, Jason Improving assessments of data‐limited populations using life‐history theory |
topic_facet |
Ecology and Environment |
description |
1. Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct population assessments by filling in missing values from surrogate species or other populations of the same species. However, using these independent surrogate values concurrently with observed data neglects the life‐history trade‐offs that connect the different aspects of a population's demography, thus introducing biases that could ultimately lead to erroneous management decisions. 2. We use a Bayesian hierarchical approach to combine fragmented multi‐population data with established life‐history theory and reconstruct population‐specific demographic data across a substantial part of a species breeding range. We apply our analysis to a long‐lived colonial species, the black‐legged kittiwake Rissa tridactyla, that is classified as globally Vulnerable and is highly threatened by increasing anthropogenic pressures, such as offshore renewable energy development. We then use a projection analysis to examine how the reconstructed demographic parameters may improve population assessments, compared to models that combine observed data with independent surrogate values. 3. Reconstructed demographic parameters can be utilised in a range of population modelling approaches. They can also be used as reference estimates to assess whether independent surrogate values are likely to over or underestimate missing demographic parameters. We show that surrogate values from independent sources are often used to fill in missing parameters that have large potential demographic impact, and that resulting biases can be driven in unpredictable directions thus precluding assessments from being consistently precautionary. 4. Synthesis and applications: Our study dramatically increases the spatial coverage of population‐specific demographic data ... |
format |
Article in Journal/Newspaper |
author |
Horswill, Cat Manica, Andrea Daunt, Francis Newell, Mark Wanless, Sarah Wood, Matthew Matthiopoulos, Jason |
author_facet |
Horswill, Cat Manica, Andrea Daunt, Francis Newell, Mark Wanless, Sarah Wood, Matthew Matthiopoulos, Jason |
author_sort |
Horswill, Cat |
title |
Improving assessments of data‐limited populations using life‐history theory |
title_short |
Improving assessments of data‐limited populations using life‐history theory |
title_full |
Improving assessments of data‐limited populations using life‐history theory |
title_fullStr |
Improving assessments of data‐limited populations using life‐history theory |
title_full_unstemmed |
Improving assessments of data‐limited populations using life‐history theory |
title_sort |
improving assessments of data‐limited populations using life‐history theory |
publisher |
Wiley |
publishDate |
2021 |
url |
http://nora.nerc.ac.uk/id/eprint/529986/ https://nora.nerc.ac.uk/id/eprint/529986/1/N529986JA.pdf https://doi.org/10.1111/1365-2664.13863 |
genre |
Black-legged Kittiwake rissa tridactyla |
genre_facet |
Black-legged Kittiwake rissa tridactyla |
op_relation |
https://nora.nerc.ac.uk/id/eprint/529986/1/N529986JA.pdf Horswill, Cat; Manica, Andrea; Daunt, Francis orcid:0000-0003-4638-3388 Newell, Mark; Wanless, Sarah; Wood, Matthew; Matthiopoulos, Jason. 2021 Improving assessments of data‐limited populations using life‐history theory. Journal of Applied Ecology, 58 (6). 1225-1236. https://doi.org/10.1111/1365-2664.13863 <https://doi.org/10.1111/1365-2664.13863> |
op_rights |
cc_by_4 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1111/1365-2664.13863 |
container_title |
Journal of Applied Ecology |
container_volume |
58 |
container_issue |
6 |
container_start_page |
1225 |
op_container_end_page |
1236 |
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1766379322956840960 |