Flagged observation analyses as a tool for scoping and communication in Integrated Ecosystem Assessments
Hiroko Kato Solvang, Per Arneberg

TL;DR
This paper introduces Flagged observation analyses, a statistical method using structural time series models and Kalman filtering to identify recent data points that deviate from predicted trends, aiding ecosystem assessment and communication.
Contribution
The paper presents a novel statistical procedure for identifying and communicating recent ecosystem changes through flagged observations in time series data.
Findings
Effective identification of flagged observations outside forecast bands.
Ability to detect unexpected trends in recent data.
Practical applications demonstrated with two case studies.
Abstract
We provide a procedure termed Flagged observation analyses that can be applied to all the available time series to help identifying time series that should be prioritized.The statistical procedure first applies a structural time series model including a stochastic trend model to the data to estimate the long-term trend. The model adopts a state space representation, and the trend component is estimated by a Kalman filter algorithm.The algorithm obtains one- or more-years-ahead prediction values using all past information from the data. Thus, depending on the number of years the investigator wants to consider as "the most recent", the expected trend for these years is estimated through the statistical procedure by using only information from the years prior to them.Forecast bands are estimated around the predicted trends for the recent years, and in the final step, an assessment is made…
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Taxonomy
TopicsEcosystem dynamics and resilience · Sustainability and Ecological Systems Analysis
