Quantifying reliability and data deficiency in global vertebrate population trends using the Living Planet Index

Global biodiversity is facing a crisis, which must be solved through effective policies and on‐the‐ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because...

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Veröffentlicht in:Global change biology Jg. 29; H. 17; S. 4966 - 4982
Hauptverfasser: Dove, Shawn, Böhm, Monika, Freeman, Robin, McRae, Louise, Murrell, David J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Blackwell Publishing Ltd 01.09.2023
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ISSN:1354-1013, 1365-2486, 1365-2486
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Abstract Global biodiversity is facing a crisis, which must be solved through effective policies and on‐the‐ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. However, without a basis for real‐world comparison, there is no way to directly assess an indicator's accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand‐ins for the “real world”, degraded samples as stand‐ins for indicator datasets (e.g., the Living Planet Database), and a distance measure to quantify reliability by comparing partially sampled to fully sampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, whereas revisiting previously studied populations is a quick and efficient way to improve trend reliability until new long‐term studies can be completed and made available. Global biodiversity indicators provide vital information about the changing state of global biodiversity to guide research, conservation actions, and policy decisions. However, little is known about how gaps and biases in the underlying data affect their accuracy or reliability. We developed a model of trend accuracy based on properties of biodiversity time series data and used it to quantitatively assess the reliability of trends in the Living Planet Index. Our results suggest that many trends need more data to be considered reliable, particularly reptile and amphibian trends, and trends across the global south.
AbstractList Global biodiversity is facing a crisis, which must be solved through effective policies and on‐the‐ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. However, without a basis for real‐world comparison, there is no way to directly assess an indicator's accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand‐ins for the “real world”, degraded samples as stand‐ins for indicator datasets (e.g., the Living Planet Database), and a distance measure to quantify reliability by comparing partially sampled to fully sampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, whereas revisiting previously studied populations is a quick and efficient way to improve trend reliability until new long‐term studies can be completed and made available.
Global biodiversity is facing a crisis, which must be solved through effective policies and on‐the‐ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. However, without a basis for real‐world comparison, there is no way to directly assess an indicator's accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand‐ins for the “real world”, degraded samples as stand‐ins for indicator datasets (e.g., the Living Planet Database), and a distance measure to quantify reliability by comparing partially sampled to fully sampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, whereas revisiting previously studied populations is a quick and efficient way to improve trend reliability until new long‐term studies can be completed and made available. Global biodiversity indicators provide vital information about the changing state of global biodiversity to guide research, conservation actions, and policy decisions. However, little is known about how gaps and biases in the underlying data affect their accuracy or reliability. We developed a model of trend accuracy based on properties of biodiversity time series data and used it to quantitatively assess the reliability of trends in the Living Planet Index. Our results suggest that many trends need more data to be considered reliable, particularly reptile and amphibian trends, and trends across the global south.
Global biodiversity is facing a crisis, which must be solved through effective policies and on-the-ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. However, without a basis for real-world comparison, there is no way to directly assess an indicator's accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand-ins for the "real world", degraded samples as stand-ins for indicator datasets (e.g., the Living Planet Database), and a distance measure to quantify reliability by comparing partially sampled to fully sampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, whereas revisiting previously studied populations is a quick and efficient way to improve trend reliability until new long-term studies can be completed and made available.Global biodiversity is facing a crisis, which must be solved through effective policies and on-the-ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. However, without a basis for real-world comparison, there is no way to directly assess an indicator's accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand-ins for the "real world", degraded samples as stand-ins for indicator datasets (e.g., the Living Planet Database), and a distance measure to quantify reliability by comparing partially sampled to fully sampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, whereas revisiting previously studied populations is a quick and efficient way to improve trend reliability until new long-term studies can be completed and made available.
Author Freeman, Robin
Böhm, Monika
McRae, Louise
Murrell, David J.
Dove, Shawn
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  surname: Murrell
  fullname: Murrell, David J.
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  organization: University College London
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Issue 17
Keywords biodiversity indicators
Living Planet Index
biodiversity trends
indicator accuracy
indicator reliability
global biodiversity monitoring
biodiversity data
data deficiency
indicator testing
Language English
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Snippet Global biodiversity is facing a crisis, which must be solved through effective policies and on‐the‐ground conservation. But governments, NGOs, and scientists...
Global biodiversity is facing a crisis, which must be solved through effective policies and on-the-ground conservation. But governments, NGOs, and scientists...
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StartPage 4966
SubjectTerms Amphibians
Aquatic reptiles
Biodiversity
biodiversity data
biodiversity indicators
biodiversity trends
birds
Collating
Conservation
data collection
data deficiency
Data reduction
Datasets
global biodiversity monitoring
global change
Growth rate
indicator accuracy
indicator reliability
indicator testing
Indicators
issues and policy
Living Planet Index
Planets
Population studies
Reliability
Reliability aspects
Reptiles
Reptiles & amphibians
Time series
time series analysis
Trends
variance
Vertebrates
Title Quantifying reliability and data deficiency in global vertebrate population trends using the Living Planet Index
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fgcb.16841
https://www.ncbi.nlm.nih.gov/pubmed/37376728
https://www.proquest.com/docview/2844053578
https://www.proquest.com/docview/2830672009
https://www.proquest.com/docview/2887634742
Volume 29
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