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Bark beetles and their symbiotic bluestain fungi kill more trees than all other natural factors and cause great economic losses in Norway spruce and other conifers. The tree's natural defenses are the most important factor maintaining bark beetle-fungus complexes at low, endemic levels. Spraying Norway spruce trees with the plant hormone methyl jasmonate (MeJA) primes tree defenses without eliciting notable induced defenses, but enables the trees to respond much more quickly and strongly when challenged by bark beetles or fungi several weeks after treatment. This phenomenon, known as defense priming, is a form of acquired resistance that enables cost-effective and vigorous defense responses. In field experiments with 50-year-old clonal spruce trees terpene concentrations in the bark increased 60-fold within 24 h after mechanical wounding of MeJA primed trees, compared with a 13-fold increase in unprimed control trees. We also observed altered transcriptional patterns in primed trees using Illumina deep transcriptome sequencing. When wounded, primed trees launched vigorous induced defenses with significant differential regulation of gene transcripts, such as those involved in phenylpropanoid synthesis leading to lignification. Resistance-like genes, such as the NB-LRR coding genes, are also more rapidly induced in primed than in unprimed trees. Transcriptome results from primed but unwounded trees indicate an alteration in the state of the chromatin, resembling changes associated with the activity of the epigenetic machinery creating long-lasting epigenetic marks. We do not know yet how long the primed state is activated in Norway spruce, but our data so far indicate that it may last for at least 3 years.

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We present a methodology for distinguishing between three types of animal movement behavior (foraging, resting, and walking) based on high-frequency tracking data. For each animal we quantify an individual movement path. A movement path is a temporal sequence consisting of the steps through space taken by an animal. By selecting a set of appropriate movement parameters, we develop a method to assess movement behavioral states, reflected by changes in the movement parameters. The two fundamental tasks of our study are segmentation and clustering. By segmentation, we mean the partitioning of the trajectory into segments, which are homogeneous in terms of their movement parameters. By clustering, we mean grouping similar segments together according to their estimated movement parameters. The proposed method is evaluated using field observations (done by humans) of movement behavior. We found that on average, our method agreed with the observational data (ground truth) at a level of 80.75% ± 5.9% (SE).