Abstract-The term "location fingerprinting" covers a wide variety of methods for determining receiver position using databases of radio signal strength measurements from different sources. In this work we present a survey of location fingerprinting methods, including deterministic and probabilistic methods for static estimation, as well as filtering methods based on Bayesian filter and Kalman filter. We present a unified mathematical formulation of radio map database and location estimation, point out the equivalence of some methods from the literature, and present some new variants. A set of tests in an indoor positioning scenario using WLAN signal strengths is performed to determine the influence of different calibration and location method parameters. In the tests, the probabilistic method with the kernel function approximation of signal strength histograms was the best static positioning method. Moreover, all filters improved the results significantly over the static methods.

The demographic Allee effect, or depensation, implies positive association between per capita population growth rate and population size at low abundances, thereby lowering growth ability of sparse populations. This can have far-reaching consequences on population recovery ability and colonization success. In the context of marine fishes, there is a widespread perception that Allee effects are rare or non-existent. However, studies that have failed to detect Allee effects in marine fishes have suffered from several fundamental methodological and data limitations. In the present study, we challenge the prevailing perception about the rarity of Allee effects by analysing nine populations of Atlantic herring (Clupea harengus), using Bayesian statistical methods. We find that populations of the same species can show either strong evidence for Allee effects or compensation. We explicitly demonstrate how the evidence for Allee effects is strongly provisional on observations made at low population abundances. We contrast our statistical approach with previous attempts to detect Allee effects and illustrate methodological issues that can lead to erroneous conclusions about the nature of population dynamics at low abundance. The present study demonstrates that there is no substantive scientific basis to support the perception that Allee effects are rare or non-existent in marine fishes.

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Marine ecosystems can undergo regime shifts, which result in nonstationarity in the dynamics of the fish populations inhabiting them. The assumption of time-invariant parameters in stock–recruitment models can lead to severe errors when forecasting renewal ability of stocks that experience shifts in their recruitment dynamics. We present a novel method for fitting stock–recruitment models using the Bayesian online change point detection algorithm, which is able to cope with sudden changes in the model parameters. We validate our method using simulations and apply it to empirical data of four demersal fishes in the southern Gulf of St. Lawrence. We show that all of the stocks have experienced shifts in their recruitment dynamics that cannot be captured by a model that assumes time-invariant parameters. The detected shifts in the recruitment dynamics result in clearly different parameter distributions and recruitment predictions between the regimes. This study illustrates how stock–recruitment relationships can experience shifts, which, if not accounted for, can lead to false predictions about a stock’s recovery ability and resilience to fishing.

The study of eco-evolutionary dynamics has become a prominent field in the contemporary biology research (Hendry, 2017). The field and its current terminology was largely catalysed by the realization that evolution occurs more rapidly when viewed across contemporary time scales (Hendry & Kinnison, 1999), yet its roots stem from the earlier studies looking into the role of trait evolution on species interactions such as consumer-resource and host