Improving assessments of data-limited populations using life-history theory
Funder: Research England Funder: UK Joint Nature Conservation Committee (DEFRA) 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 gr...
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ftunivcam:oai:www.repository.cam.ac.uk:1810/321996 2024-02-04T09:59:20+01:00 Improving assessments of data-limited populations using life-history theory Horswill, C Manica, A Daunt, F Newell, M Wanless, S Wood, M Matthiopoulos, J 2021-05-05T20:30:34Z application/pdf text/xml https://www.repository.cam.ac.uk/handle/1810/321996 https://doi.org/10.17863/CAM.69454 en eng eng Wiley http://dx.doi.org/10.1111/1365-2664.13863 Journal of Applied Ecology https://www.repository.cam.ac.uk/handle/1810/321996 doi:10.17863/CAM.69454 black‐ legged kittiwake data‐ limited environmental impact assessment fecundity marine renewables population assessment seabird survival Article 2021 ftunivcam https://doi.org/10.17863/CAM.69454 2024-01-11T23:32:37Z Funder: Research England Funder: UK Joint Nature Conservation Committee (DEFRA) 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. 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. Consequently, this approach introduces biases that could ultimately lead to erroneous management decisions. We use a Bayesian hierarchical framework 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, including 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. Demographic parameters reconstructed using a hierarchical framework 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 are driven in unpredictable directions thus precluding assessments from being consistently precautionary. ... Article in Journal/Newspaper Black-legged Kittiwake rissa tridactyla Apollo - University of Cambridge Repository |
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Apollo - University of Cambridge Repository |
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ftunivcam |
language |
English |
topic |
black‐ legged kittiwake data‐ limited environmental impact assessment fecundity marine renewables population assessment seabird survival |
spellingShingle |
black‐ legged kittiwake data‐ limited environmental impact assessment fecundity marine renewables population assessment seabird survival Horswill, C Manica, A Daunt, F Newell, M Wanless, S Wood, M Matthiopoulos, J Improving assessments of data-limited populations using life-history theory |
topic_facet |
black‐ legged kittiwake data‐ limited environmental impact assessment fecundity marine renewables population assessment seabird survival |
description |
Funder: Research England Funder: UK Joint Nature Conservation Committee (DEFRA) 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. 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. Consequently, this approach introduces biases that could ultimately lead to erroneous management decisions. We use a Bayesian hierarchical framework 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, including 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. Demographic parameters reconstructed using a hierarchical framework 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 are driven in unpredictable directions thus precluding assessments from being consistently precautionary. ... |
format |
Article in Journal/Newspaper |
author |
Horswill, C Manica, A Daunt, F Newell, M Wanless, S Wood, M Matthiopoulos, J |
author_facet |
Horswill, C Manica, A Daunt, F Newell, M Wanless, S Wood, M Matthiopoulos, J |
author_sort |
Horswill, C |
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 |
https://www.repository.cam.ac.uk/handle/1810/321996 https://doi.org/10.17863/CAM.69454 |
genre |
Black-legged Kittiwake rissa tridactyla |
genre_facet |
Black-legged Kittiwake rissa tridactyla |
op_relation |
https://www.repository.cam.ac.uk/handle/1810/321996 doi:10.17863/CAM.69454 |
op_doi |
https://doi.org/10.17863/CAM.69454 |
_version_ |
1789964090764951552 |