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2014

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Sammendrag

Background: Climate change can affect the activity and distribution of species, including pathogens and parasites. The densities and distribution range of the sheep tick (Ixodes ricinus) and it’s transmitted pathogens appears to be increasing. Thus, a better understanding of questing tick densities in relation to climate and weather conditions is urgently needed. The aim of this study was to test predictions regarding the temporal pattern of questing tick densities at two different elevations in Norway. We predict that questing tick densities will decrease with increasing elevations and increase with increasing temperatures, but predict that humidity levels will rarely affect ticks in this northern, coastal climate with high humidity. Methods: We described the temporal pattern of questing tick densities at ~100 and ~400 m a.s.l. along twelve transects in the coastal region of Norway. We used the cloth lure method at 14-day intervals during the snow-free season to count ticks in two consecutive years in 20 m2 plots. We linked the temporal pattern of questing tick densities to local measurements of the prevailing weather. Results: The questing tick densities were much higher and the season was longer at ~100 compared to at ~400 m a.s.l. There was a prominent spring peak in both years and a smaller autumn peak in one year at ~100 m a.s.l.; but no marked peak at ~400 m a.s.l. Tick densities correlated positively with temperature, from low densities <5°C, then increasing and levelling off >15-17°C. We found no evidence for reduced questing densities during the driest conditions measured. Conclusions: Tick questing densities differed even locally linked to elevation (on the same hillside, a few kilometers apart). The tick densities were strongly hampered by low temperatures that limited the duration of the questing seasons, whereas the humidity appeared not to be a limiting factor under the humid conditions at our study site. We expect rising global temperatures to increase tick densities and lead to a transition from a short questing season with low densities in the current cold and sub-optimal tick habitats, to longer questing seasons with overall higher densities and a marked spring peak.

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Understanding the responses of ecological communities to perturbation is a key challenge within contemporary ecology research. In this study we seek to separate specifi c community responses from general community responses of plant communities to exclusion of large cervid herbivores. Cervid herbivory and forestry are the main drivers of vegetation structure and diversity in boreal forests. While many studies focus on the impact of cervids on trees, a high proportion of the biodiversity and ecosystem services in boreal forests is found in the fi eld layer. However, experimental approaches investigating the infl uence of herbivory on understory vegetation are highly localised. In this study we use a regionalscale design with 51 sites in four boreal forest regions of Norway, to investigate the infl uence of cervid herbivory on the physical and ecological structure of fi eld layer vegetation. Our study sites cover a range of forest types diff ering in productivity, management and dominant cervid species, allowing us to identify generic responses and those that are specifi c to particular conditions. We found that the height of the fi eld layer and the abundances of individual species were most susceptible to change following short-term cervid exclusion across diff erent forest types and cervid species. Total vegetation density and vascular plant diversity did not respond to cervid exclusion on the same time scale. We also found that the fi eld-layer vegetation in clear-cut forests used by moose was more susceptible to change following cervid exclusion than mature forests used by red deer, but no strong evidence that the response of vegetation to herbivore exclusion varied with productivity. Our study suggests that the parameters that respond to cervid exclusion are consistent across forest types, but that the responsiveness of diff erent forest types is idiosyncratic and hard to predict.

Sammendrag

Usnea longissima Ach. is a circumboreal epiphytic lichen draping tree canopies in moist coastal and mountainous forests. It is extinct from many European and North-American localities, presumably due to industrial forestry and air pollution, but still has a stronghold in parts of Scandinavia and U.S. and Canadian Pacific Northwest. In 2005/06 we used a comparative and retrospective approach to evaluate how present and historic tree and stand characteristics influenced the occurrence and abundance of the lichen (Storaunet et al. 2008). In 2012, we re-inventoried ten Norway spruce forest stands with 401 U. longissima-bearing trees and recorded changes in the number of U. longissima thalli. Seven of the stands had been experimentally, selectively logged 5–8 years before, where the lichen-bearing trees had been marked in the field and were avoided during the logging operation. Total number of lichen-bearing trees decreased slightly (2.9%), whereas the number of thalli had increased with 34%. Number of thalli increased more where the forest was open (low basal area, m2ha-1) whether or not the low tree density was caused by the logging events. At high tree densities the change in number of thalli was negligible. We suggest that selective logging, securing lichen-bearing trees, may be a viable management option to keep tree density from becoming too dense, thereby enhancing growth and establishment of U. longissima.

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National Forest Inventories (NFIs) provide estimates of forest parameters for national and regional scales. Many key variables of interest, such as biomass and timber volume, cannot be measured directly in the field. Instead, models are used to predict those variables from measurements of other field variables. Therefore, the uncertainty or variability of NFI estimates results not only from selecting a sample of the population but also from uncertainties in the models used to predict the variables of interest. The aim of this study was to quantify the model-related variability of Norway spruce (Picea abies [L.] Karst) biomass stock and change estimates for the Norwegian NFI. The model-related variability of the estimates stems from uncertainty in parameter estimates of biomass models as well as residual variability and was quantified using a Monte Carlo simulation technique. Uncertainties in model parameter estimates, which are often not available for published biomass models, had considerable influence on the model-related variability of biomass stock and change estimates. The assumption that the residual variability is larger than documented for the models and the correlation of within-plot model residuals influenced the model-related variability of biomass stock change estimates much more than estimates of the biomass stock. The larger influence on the stock change resulted from the large influence of harvests on the stock change, although harvests were observed rarely on the NFI sample plots in the 5-year period that was considered. In addition, the temporal correlation between model residuals due to changes in the allometry had considerable influence on the model-related variability of the biomass stock change estimate. The allometry may, however, be assumed to be rather stable over a 5-year period. Because the effects of model-related variability of the biomass stock and change estimates were much smaller than those of the sampling-related variability, efforts to increase the precision of estimates should focus on reducing the sampling variability. If the model-related variability is to be decreased, the focus should be on the tree fractions of living branches as well as stump and roots.