Chloé R. Nater, Francesco Frassinelli, James A. Martin, Erlend B. NilsenPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
<p>Quantifying temporal and spatial variation in animal population size and demography is a central theme in ecological research and important for directing management and policy. However, this requires field sampling at large spatial extents and over long periods of time, which is not only prohibitively costly but often politically untenable. Participatory monitoring programs (also called citizen science programmes) can alleviate these constraints by recruiting stakeholders and the public to increase the spatial and temporal resolution of sampling effort and hence resulting data. While the majority of participatory monitoring programs are limited by opportunistic sampling designs, we are starting to see the emergence of structured citizen science programs that employ trained volunteers to collect data according to standardized protocols. Simultaneously, there is much ongoing development of statistical models that are increasingly more powerful and able to make more efficient use of field data. Integrated population models (IPMs), for example, are able to use multiple streams of data from different field monitoring programmes and/or multiple aspects of single datasets to estimate population sizes and key vital rates. Here, we developed a multi-area version of a recently developed integrated distance sampling model (IDSM) and applied it to data from a large-scale participatory monitoring program – the “Hønsefuglportalen” – to study spatio-temporal variation in population dynamics of willow ptarmigan (Lagopus lagopus) in Norway. We constructed an open and reproducible workflow for exploring temporal, spatial (latitudinal, longitudinal, altitudinal), and residual variation in recruitment, survival, and population density, as well as relationships between vital rates and relevant covariates and signals of density dependence. Recruitment rates varied more across space than over time, while the opposite was the case for survival. Slower life history patterns (higher survival, lower recruitment) appeared to be more common at higher latitudes and altitudes, portending differential effects of climate change on ptarmigan across their range. While there was variation in the magnitude of the effect small rodent occupancy had on recruitment, the relationships were predominantly positive and thus consistent with the alternative prey hypothesis. Notably, the accurate estimation of covariate effect was only made possible by integrating data from several monitoring areas for analysis. Our study highlights the potential of participatory monitoring and integrated modelling approaches for estimating and understanding spatio-temporal patterns in species abundance and demographic rates, and showcases how corresponding workflows can be set up in reproducible and semi-automated ways that increase their usefulness for informing management and regular reporting towards national and international biodiversity frameworks.</p>
https://osf.io/7326r/, https://data.livingnorway.no/dataset?key=b49a2978-0e30-4748-a99f-9301d17ae119, https://data.livingnorway.no/dataset?key=6a948a1c-7e23-4d99-b1c1-ec578d0d3159, https://data.livingnorway.no/dataset?key=c47f13c1-7427-45a0-9f12-237aad351040You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://
https://www.r-project.org/, https://r-nimble.org/, https://nixos.org/manual/nix/stable, https://www.gnu.org/software/parallel/You should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://
population dynamics, workflow, Vital rates, Temporal variation, survival, spatiotemporal variation, spatial variation, recruitment, ptarmigan, Alpine, Pipeline, modelling, large-scale, Lagopus lagopus, integrated distance sampling model, IDSM, distance sampling, detection
Biodiversity, Biogeography, Conservation biology, Demography, Euring Conference, Landscape ecology, Life history, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Statistical ecology, Terrestrial ecology
Ben Augustine; ba378@cornell.edu, Heather Gaya; heather.e.gaya@gmail.com, Rob Robinson; rob.robinson@bto.org, Marc Kéry; marc.kery@vogelwarte.ch, James Saracco; jsaracco@birdpop.org, Todd Arnold; arnol065@umn.edu, Stefan Vriend; S.Vriend@nioo.knaw.nl, Emily Simmonds; emily.g.simmonds@ntnu.no, Alison Johnston; alison.johnston@st-andrews.ac.uk, Cat Morrison; C.Morrison@uea.ac.uk, Michael Schaub suggested: Thomas Riecke, Thomas Riecke <thomasvanceriecke@gmail.com>, Brett K. Sandercock [brett.sandercock@nina.no] suggested: Apologies but I have a conflict of interest on the manuscript. I am a colleague and collaborator with the authors and know the study. Suggest Todd Arnold at Univ. Minnesota, Dave Koons at Colorado State University or Larkin Powell at Univ. Nebraska.
e.g. John Doe john@doe.com
No need for them to be recommenders of PCIEcology. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct
