2015
DOI: 10.1371/journal.pone.0132255
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Combined Influences of Model Choice, Data Quality, and Data Quantity When Estimating Population Trends

Abstract: Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have known impacts in population risk assessments, but their combined impact has not been thoroughly investigated. We tested the ability of s… Show more

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Cited by 30 publications
(39 citation statements)
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“…If this population trend is maintained, the probability of extinction within 100 years was estimated at 37%. Lengthening a time series improves the precision of the results and reduces the bias of the predicted population trend [39]. Although our estimate was based on a PVA using 10 years of count data, which is the minimum number of years required to undertake the analysis, and should therefore be considered with caution, some information useful for management may be derived from these results.…”
Section: Discussionmentioning
confidence: 99%
“…If this population trend is maintained, the probability of extinction within 100 years was estimated at 37%. Lengthening a time series improves the precision of the results and reduces the bias of the predicted population trend [39]. Although our estimate was based on a PVA using 10 years of count data, which is the minimum number of years required to undertake the analysis, and should therefore be considered with caution, some information useful for management may be derived from these results.…”
Section: Discussionmentioning
confidence: 99%
“…The temporal extent of the data needs to be considered relative to the lifespan of the taxa of interest and the projection horizon (Zeigler et al 2013;Rueda-Cediel et al 2015), as well as the importance of infrequent catastrophes as determinants of population change (Ralls & Taylor 1997). The data period:projection horizon ratio was 0.01-0.23-1.2, meaning that in most cases the temporal extent of the data was much shorter than the period over which projections were being made.…”
Section: Parametrisation Datamentioning
confidence: 99%
“…GitHub) to help increase transparency and repeatability (see Wood et al 2017). (5) PVA should be based on as long and high-quality data as possible given the context the model is being developed and used in (Coulson et al 2001;Zeigler et al 2013;Rueda-Cediel et al 2015). We do not, however, advocate waiting indefinitely for the 'perfect' dataset, as not making any decision does carry a cost.…”
Section: Recommendationsmentioning
confidence: 99%
“…, Rueda‐Cediel et al. , Holmes ). Classification schemes such as the IUCN Red List must prescribe general rules for the categorisation of populations in order to achieve comparability and remain accessible, but in this generality they may miss population‐specific measures, leading to misrepresentative classification (Akçakaya et al.…”
Section: Introductionmentioning
confidence: 99%