| 1. |
- Lindström, Tom, et al.
(författare)
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A spectral and Bayesian approach for analysis of fluctuations and synchrony in ecological datasets
- 2012
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Ingår i: Methods in Ecology and Evolution. - : Wiley-Blackwell. - 2041-210X. ; 3:6, s. 1019-1027
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Tidskriftsartikel (refereegranskat)abstract
- Autocorrelation within ecological time series and synchrony between them may provide insight into the main drivers of observed dynamics. We here present methods that analyse autocorrelation and synchrony in ecological datasets using a spectral approach combined with Bayesian inference. To exemplify, we implement the method on dendrochronological data of the pedunculate oak (Quercus robur). The data consist of 110 years of growth of 10 live trees and seven trees that died during a synchronized oak death in Sweden in c. 2002-2007. We find that the highest posterior density is found for a noise colour of tree growth of gamma approximate to 0.95 (i.e. pink noise) with little difference between trees, suggesting climatic variation as a driving factor. This is further supported by the presence of synchrony, which we estimate based on phase-shift analysis. We conclude that the synchrony is time-scale dependent with higher synchrony at larger time-scales. We further show that there is no difference between the growth patterns of the alive and dead tree groups. This suggests that the trees were driven by the same factors prior to the synchronized death. We argue that this method is a promising approach for linking theoretical models with empirical data.
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| 2. |
- Lindström, Tom, et al.
(författare)
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Estimation of distance related probability of animal movements between holdings and implications for disease spread modeling
- 2009
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Ingår i: Preventive Veterinary Medicine. - : Elsevier. - 0167-5877 .- 1873-1716. ; 91:2-4, s. 85-94
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Tidskriftsartikel (refereegranskat)abstract
- Between holding contacts are more common over short distances and this may have implications for the dynamics of disease spread through these contacts. A reliable estimation of how contacts depend on distance is therefore important when modeling livestock diseases. In this study, we have developed a method for analyzing distant dependent contacts and applied it to animal movement data from Sweden. The data were analyzed with two competing models. The first model assumes that contacts arise from a purely distance dependent process. The second is a mixture model and assumes that, in addition, some contacts arise independent of distance. Parameters were estimated with a Bayesian Markov Chain Monte Carlo (MCMC) approach and the model probabilities were compared. We also investigated possible between model differences in predicted contact structures, using a collection of network measures. We found that the mixture model was a much better model for the data analyzed. Also, the network measures showed that the models differed considerably in predictions of contact structures, which is expected to be important for disease spread dynamics. We conclude that a model with contacts being both dependent on, and independent of, distance was preferred for modeling the example animal movement contact data.
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