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  • 1. Meissner, Kristian
    et al.
    Juntunen, Antti
    Malmqvist, Björn
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Muotka, Timo
    Predator-prey interactions in a variable environment: responses of a caddis larva and its blackfly prey to variations in stream flow2009In: Annales Zoologici Fennici, ISSN 0003-455X, E-ISSN 1797-2450, Vol. 46, no 3, p. 193-204Article in journal (Other academic)
    Abstract [en]

    Predator-prey studies in streams have traditionally focused on mayfly-stonefly interactions in relatively constant flow conditions. In reality, however, lotic prey encounter multiple types of predators, most of which are restricted to low-velocity microhabitats. By contrast, some invertebrate prey may occur in very high current velocities. For example, many blackfly species are able to feed at velocities of 100 cm s(-1), whereas even moderate currents reduce the hunting efficiency of their invertebrate predators. The caddisfly larvae of the genus Rhyacophila, however, may be an exception to the pattern of reducing predator efficiency with increasing velocity. Using a combination of laboratory and field experiments and behavioral field observations, we examined the interaction between predatory Rhyacophila caddis larvae and larval blackflies along a velocity gradient of 20-120 cm s(-1). In laboratory experiments, Rhyacophila preferred currents slower than 50 cm s(-1) while blackflies exhibited a wide tolerance of currents and frequently occurred in currents exceeding 100 cm s(-1). In direct field observations, total activity and distance moved by Rhyacophila were similar at all current velocity regimes tested, but frequency of predation attempts on blackflies was lowest at the highest velocities (> 100 cm s(-1)). In a field colonization study, blackflies avoided substrates with the slowest velocities (< 40 cm s(-1)), as also did the caddis larvae. Only velocities approaching 100 cm s(-1) provide blackflies with refuge from predation by Rhyacophila. Being able to maneuver across a wide range of velocities, Rhyacophila may have more pervasive effects on their prey than other lotic invertebrate predators.

  • 2. Suominen, O
    et al.
    Olofsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Impacts of semi-domesticated reindeer on structure of tundra and forest communities in Fennoscandia: a review2000In: Annales Zoologici Fennici, ISSN 0003-455X, E-ISSN 1797-2450, Vol. 37, no 4, p. 233-249Article in journal (Refereed)
    Abstract [en]

    Grazing and trampling by semi-domesticated reindeer are important factors controlling vegetation in northern Fennoscandia. In this article we review Nordic studies on the effects of reindeer on vegetation and animal communities. The studies have shown clear effects on vegetation, especially on Cladina lichen dominated sites. Cladina is the main forage of reindeer during winter and dominates climax vegetation in dry site types in the absence of reindeer. Reindeer can even affect galling and ground-dwelling invertebrates. Due to the special relationship between reindeer and Cladina majority of the research has concentrated on winter grazing on Cladina, but there are some studies of summer grazing which have also shown substantial changes in vegetation. Reindeer grazing increases richness and diversity of vegetation and invertebrate assemblages in most cases, but this influence depends on site type and grazing intensity. The enriching effect seems to be strongest at moderate grazing intensity.

  • 3. van den Brink, Valentijn
    et al.
    Bokma, Folmer
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Morphometric shape analysis using learning vector quantization neural networks: an example distinguishing two microtine vole species2011In: Annales Zoologici Fennici, ISSN 0003-455X, E-ISSN 1797-2450, Vol. 48, no 6, p. 359-364Article in journal (Refereed)
    Abstract [en]

    Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

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