Erling Meisingset
Research Scientist
(+47) 918 08 860
erling.meisingset@nibio.no
Place
Tingvoll
Visiting address
Gunnars veg 6, 6630 Tingvoll
Authors
Atle Mysterud William Ryan Easterday Vetle Malmer Stigum Anders Aas Erling Meisingset Hildegunn ViljugreinAbstract
No abstract has been registered
Authors
Even Unsgård Erling Meisingset Inger Maren Rivrud Gunn Randi Fossland Pål Thorvaldsen Vebjørn Veiberg Atle MysterudAbstract
No abstract has been registered
Abstract
The timing of migration is fundamental for species exploiting seasonally variable environments. For ungulates, earlier spring migration is expected with earlier vegetation green-up. However, other drivers, such as access to agricultural farmland and variation in local conditions, are also known to affect migration. We investigated the timing of spring migration for 96 male and 201 female red deer (Cervus elaphus) using a long-term dataset (2005–2020). Overall, the timing of migration was mainly characterized by large individual variability between and within years (95% range 6 April to 18 June). The spring migration timing was, as expected, later with colder winter and spring conditions (North Atlantic Oscillation (NAO) winter and April indices) and later peak vegetation green-up (NDVI), with a five-day delay in green-up causing a migration delay of 1.2 days. Timing was also influenced by local conditions in summer and winter home ranges. Red deer with greater access to farmland and a more variable topography (hence variable plant phenology) in winter delayed migration. Similarly, individuals with higher-elevation summer ranges (with delayed onset of plant growth) also delayed migration. Our analyses highlight that the timing of red deer migration is determined by multiple drivers affecting foraging conditions in the landscape, indicative of considerable phenotypic plasticity.
Abstract
Reliable estimates of the size and composition of harvested populations over time are key to designing adequate population management plans, regardless of management objectives. In Norway, a national system for collecting and analysing hunter-reported data on red deer (Cervus elaphus) has been operational for about 20 years. The system was expected to provide population metrics that would substantially improve deer population management routines at the municipal level. This has proven to be challenging when using existing state-of-the-art estimation methodology. The main reasons are that the variation in the observation data is generally much larger than population abundance variability, and that one does not have a clear understanding of the stochastic process generating the observation data. Here, using hunter-reported observation data and harvest data from six Norwegian municipalities collected in the period 2007–2023, we show that a straightforward estimation methodology based on population modelling can produce robust abundance estimates despite frequent low quality of the observation data. Its major assets are that it does not involve strong assumptions about the stochastic processes underlying the observation process and that it does not involve assumptions about initial population size and structure in terms of prior statistical distributions. We anticipate that the method can be applied in several other population management contexts, and we think that the results offer fresh perspectives on to what extent noisy citizen-collected time series data can be used to inform management decisions.