Habitat quality influences population distribution, individual space use and functional responses in habitat selection by a large herbivore

Identifying factors shaping variation in resource selection is central for our understanding of the behaviour and distribution of animals. We examined summer habitat selection and space use by 108 Global Positioning System (GPS)-collared moose in Norway in relation to sex, reproductive status, habitat quality, and availability. Moose selected habitat types based on a combination of forage quality and availability of suitable habitat types. Selection of protective cover was strongest for reproducing females, likely reflecting the need to protect young. Males showed strong selection for habitat types with high quality forage, possibly due to higher energy requirements. Selection for preferred habitat types providing food and cover was a positive function of their availability within home ranges (i.e. not proportional use) indicating functional response in habitat selection. This relationship was not found for unproductive habitat types. Moreover, home ranges with high cover of unproductive habitat types were larger, and smaller home ranges contained higher proportions of the most preferred habitat type. The distribution of moose within the study area was partly related to the distribution of different habitat types. Our study shows how distribution and availability of habitat types providing cover and high-quality food shape ungulate habitat selection and space use.     

Effects of spatial scale and sample size in GPS-based species distribution models: are the best models trivial for red deer management?

Species distribution models (SDMs) are popular in conservation and management of a wide array of taxa. Often parameterized with coarse GIS-based environmental maps, they perform well in macro-ecological settings but it is debated if the models can predict distribution within broadly suitable “known” habitats of interest to local managers. We parameterized SDMs with GIS-derived environmental variables and location data from 82 GPS-collared female red deer (Cervus elaphus) from two study areas in Norway. Candidate GLM models were fitted to address the effect of spatial scale (landscape vs. home range), sample size, and transferability between study areas, with respect to predictability (AUC) and explained variance (Generalized R ² and deviance). The landscape level SDM captured variation in deer distribution well and performed best on all diagnostic measures of model quality, caused mainly by a trivial effect of avoidance of non-habitat (barren mountains). The home range level SDMs were far less predictable and explained comparatively little variation in space use. Landscape scale models stabilized at the low sample size of 5–10 individuals and were highly transferrable between study areas implying a low degree of individual variation in habitat selection at this scale. It is important to have realistic expectations of SDMs derived from digital elevation models and coarse habitat maps. They do perform well in highlighting potential habitat on a landscape scale, but often miss nuances necessary to predict more fine-scaled distribution of wildlife populations. Currently, there seems to be a trade-off between model quality and usefulness in local management.     

Screening and identification of Shigella flexneri 2a virulence-related genes induced after invasion of epithelial cells

~~Screening and identification of Shigella flexneri 2a virulence-related genes induced after invasion of epithelial cells1. Jin, Q., Yuan, Z., Xu, J., Wang, Y., Shen, Y., Lu, W., Wang, J., Liu, H., Yang, J., Yang, P., Zhang, X., Zhang, J., Yang, G, Wu, H., Qu, D., Dong, J., Sun, L., Xue, Y, Zhao, A., Gao, Y., Zhu, J., Kan, B., Ding, K.. Chen, S., Cheng, H., Yao, Z., He, B., Chen, R., Ma, D., Qiang, B., Wen, Y, Hou, Y., Yu, J., Genome sequence of Shigella flexneri 2…     

Comparative Studies on the Soluble Components of Adenovirus Types 9 and 15 and the Intermediate Strain 9-15

Five different soluble components of adenovirus types 9, 9-15, and 15 have been identified. These are: (i) a slowly sedimenting, trypsin-resistant, incomplete hemagglutinin (HA). (This component was demonstrable by hemagglutination-enhancement (HE) tests in the presence of heterotypic antisera against members of Rosen's subgroups II and III, but not of subgroup I); (ii) a slowly sedimenting, trypsin-resistant, complete HA, causing only a partial agglutination of cells; (iii) a rapidly sedimenting, incomplete HA, demonstrable by HE tests in the presence of heterotypic antisera against members of all Rosen's subgroups. (Trypsin treatment of this component caused a conversion into slowly sedimenting incomplete HA); (iv) a group-specific complement-fixing (CF) antigen devoid of HA activity; and (v) a rapidly sedimenting, trypsin-sensitive, complete HA, which in the electron microscope was found to represent a dodecahedral aggregate of 12 pentons (a dodecon). On the basis of their biological and physicochemical characteristics, the first four components were interpreted to represent (i) fibers, (ii) a polymer of a few, probably two, fibers, (iii) pentons, and (iv) hexons, respectively. The length of fibers extending from dodecons and virions was estimated to be 11 to 14 nm. A similar value was suggested from exclusion chromatography experiments. Adenovirus types 9 and 15 fibers were recovered in a position intermediate to that of fibers of types 3 and 4, the lengths of which are 10 and 17 nm, respectively. The sequence of elution of different components of types 9 and 9-15 from an anion exchanger was fibers, fiber-aggregate, pentons, hexons, and dodecons. Type 15 components appeared in the same order except for the fact that dodecons eluted before hexons. The molarities of NaCl required to elute the different types 9 and 9-15 components, excluding hexons, were identical. They were distinctly different from those of the corresponding type 15 components. However, hexons of all three serotypes eluted in proximity to each other and there was a slight tendency for type 9-15 hexons to take a position intermediate to those of types 9 and 15.     

Block-Surface Staining

A method is described by which the tissue exposed on sectioning a specimen embedded in paraffin can be visualized in situ. The fixed specimen is impregnated with lead acetate, dehydrated in dioxane, infiltrated with paraffin and embedded. Tissues exposed on sectioning are developed by applying to the cut surface of the block a solution of potassium sulphide in water. Concentrations of the reagents used and the time intervals for the procedure are dependent upon the size of the specimen and upon the degree of contrast required. The method is described as it was applied to the study of a small human fetus in cross section. Representative photographs are included to show the results obtained.     

Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway

Many publications make use of opportunistic data, such as citizen science observation data, to infer large‐scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS‐telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat‐use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat‐use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat‐use studies.     

Seasonal distribution and dive behaviour of harp seals (<Emphasis Type="Italic">Pagophilus groenlandicus</Emphasis>) of the White Sea–Barents Sea stock

Eight adult female harp seals (Pagophilus groenlandicus) of the White Sea–Barents Sea stock were tagged with satellite-linked dive recorders during the nursing period and followed from breeding in late February 1995 until moulting in late April 1995. Another ten adult harp seals of both sexes were tagged and followed from moult in early May 1996 until breeding in late February the following year. Between breeding and moult the seals were distributed along the coasts of Kola of Russia and eastern Finnmark of Norway, coinciding in time and space with the spawning capelin (Mallotus villosus). Between moulting and breeding they encircled the entire Barents Sea, mostly in open water, using the water column from 20 to 300 m, and in so doing by and large reflecting the annual migrations of the capelin. Capelin is therefore assumed to be the main source of prey for the White Sea–Barents Sea stock of harp seals, to be substituted, in part, by amphipods (e.g. Themisto libellula) in mid-summer and polar cod (Boreogadus saida) and herring (Clupea pallasii) in late autumn and winter. These data provide a baseline for the evaluation of the effects of future climatic change in the rich Barents Sea ecosystem.     

Scale dependency and functional response in moose habitat selection

Habitat selection can be influenced by the distribution of the habitat types in the landscape as well as net gain in visiting patches of resources, causing individual variation in habitat selection. Moreover, the hypothesis of functional response in habitat selection predicts that the degree of selection of a resource depends on its relative availability. We used radio-telemetry data from individual moose on an island off the coast of northern Norway to evaluate whether the selection of habitat types at the landscape scale differed from the choice of habitat types within the home range, and investigated the functional response in habitat selection by relating individual habitat selection to home range characteristics. At the landscape scale, moose selected for habitat types that provided both good forage and cover, with small differences between sex and age groups. At the home range scale, all individuals selected habitat types that were associated with cover and low human impact. Habitat selection was not modified by local moose density, but was related to home range size at both spatial scales. Larger home ranges contained larger proportions of non-preferred habitat types compared to smaller home ranges. At the home range scale, the selection for a habitat type decreased with its relative availability, indicating a functional response in habitat selection. This suggests that habitat selection is modified by home range size, which influences the availability of habitat types and shapes individual habitat selection patterns. Our results support previous suggestions that analyses of habitat or resource selection should follow a multi-scale approach. Both the relative availability of habitat types as well as individual variation in home range size should be accounted for in order to disentangle the complex mechanisms that contribute to shape patterns of resource selection in animals.