State-space model for Svalbard ptarmigan ...

• Main Authors: Marolla, Filippo, Henden, John-Andre, Fuglei, Eva, Pedersen, Ashild Ønvik, Itkin, Mikhail, Ims, Rolf Anker
• Format: Dataset
• Language: English
• Published: Dryad 2021
• Subjects: FOS Earth and related environmental sciences; Bayesian state-space modelling; Svalbard; rock ptarmigan; Arctic; Climate change; Norwegian Polar Institute; Svalbard Rock Ptarmigan
• Online Access: https://dx.doi.org/10.5061/dryad.ngf1vhht0; https://datadryad.org/stash/dataset/doi:10.5061/dryad.ngf1vhht0

To improve understanding and management of the consequences of current rapid environmental change, ecologists advocate using long-term monitoring data series to generate iterative near-term predictions of ecosystem responses. This approach allows scientific evidence to increase rapidly and management strategies to be tailored simultaneously. Iterative near-term forecasting may therefore be particularly useful for adaptive monitoring of ecosystems subjected to rapid climate change. Here, we show how to implement near-term forecasting in the case of a harvested population of rock ptarmigan in high-arctic Svalbard, a region subjected to the largest and most rapid climate change on Earth. We fitted state-space models to ptarmigan counts from point-transect distance-sampling during 2005-2019 and developed two types of predictions: 1) explanatory predictions to quantify the effect of potential drivers of ptarmigan population dynamics, and 2) anticipatory predictions to assess the ability of candidate models of ... : The time series of the Svalbard rock ptarmigan population is part of an ecosystem-wide monitoring system that encompasses the period of the most rapid recent climate warming with associated changes in the abiotic and biotic domains of the Svalbard terrestrial ecosystem. Ptarmigan data come from point-transect distance sampling conducted by the Norwegian Polar Institute on calling territorial males during four weeks in April. ...