Integrated distribution modelling to estimate the national population size of an alpine bird

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Diana Bowler, Erlend Birkeland Nilsen 


1) Estimates of species’ population abundances have important ramifications for conservation decision-making. Conservation practice, however, often has to rely on indices of relative abundance rather than absolute estimates. Attempts to estimate large-scale abundance estimates of species are limited by both the availability of data and statistical challenges. New opportunities are, however, emerging as a result of the development of an open data culture.
2) Here we integrate information from two distinct citizen science data sources, opportunistic occurrence data and targeted standardized distance-sampling survey data, to estimate the population size of an alpine bird - the willow ptarmigan, Lagopus lagopus - in Norway between 2008 and 2017. Our model combines the strengths of the occurrence data (widespread but coarse) and standardised survey data (spatially restricted but detailed) to estimate ptarmigan population size at both local and national-scales. Using simulations, we also examined the sensitivity of the population size estimates to each data type to guide future data collection.
3) An occupancy-detection model fit to the occurrence data predicted that willow ptarmigan were present in 29% of 5 x 5 grid cells across Norway. Occupancy probability was most strongly affected by habitat covariates. The distance-sampling model predicted that ptarmigan density in the area covered by the line-transect surveys was, on average, 13 individuals per km2, and most strongly affected by climatic variables. On integration, we predicted a mean annual population size of c. 1.2 million individuals.
4) Most of the uncertainty in the national population size estimate was driven by uncertainty in occupancy in western and central Norway. Hence, data collection activities might be encouraging in these regions to increase the precision of population size estimate.
5) Synthesis and applications: Our study shows the possibilities of new data sources and modelling approaches to provide absolute estimates of species’ population sizes, which are often more revealing than relative abundance indices for understanding species’ population dynamics and trends. Ecologists can take advantage of the open data revolution, and especially the relative strengths of different available data types, to estimate species’ abundance at large spatial scales.



Biodiversity, Life Sciences



Published: 2022-02-07 14:34


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