Wolf habitat selection at the territory level : seasonal and interannual variation and influence on reproductive success

Habitat selection has been one of the main research topics in ecology for decades. Nevertheless, many aspects of habitat selection still need to be explored. In particular, previous studies have overlooked the importance of temporal variation in habitat selection and the value of including data on reproductive success in order to describe the best quality habitat for a species. We used data collected from radiocollared wolves in Yellowstone National Park (USA), between 1996 and 2008, to describe wolf habitat selection. In particular, we aimed to identify i) seasonal differences in wolf habitat selection, ii) factors influencing interannual variation in habitat selection, and iii) the effect of habitat selection on wolf reproductive success. We used probability density functions to describe wolf habitat use and habitat coverages to represent the habitat available to wolves. We used regression analysis to connect habitat use with habitat characteristics and habitat selection with reproductive success. Our most relevant result was discovering strong interannual variability in wolf habitat selection. This variability was in part explained by pack identity and differences in litter size and leadership of a pack between two years (summer) and in pack size and precipitation (winter). We also detected some seasonal differences. Wolves selected open habitats, intermediate elevations, intermediate distances from roads, and avoided steep slopes in late winter. They selected areas close to roads and avoided steep slopes in summer. In early winter, wolves selected wetlands, herbaceous and shrub vegetation types, and areas at intermediate elevation and distance from roads. Surprisingly, the habitat characteristics selected by wolves were not useful in predicting reproductive success. We hypothesize that interannual variability in wolf habitat selection may be too strong to detect effects on reproductive success. Moreover, prey availability and competitor pressure may also have an influence on wolf reproductive success, which we did not assess. This project demonstrated how important temporal variation is in shaping patterns of habitat selection. We still believe in the value of running long-term studies, but the effect of temporal variation should always be taken into account.

Golden-winged Warbler habitat model validation for northern Wisconsin and central Minnesota

Between 1966 and 2003, the Golden-winged Warbler (Vermivora chrysoptera) experienced declines of 3.4% per year in large parts of the breeding range and has been identified by Partners in Flight as one of 28 land birds requiring expedient action to prevent its continued decline. It is currently being considered for listing under the Endangered Species Act. A major step in advancing our understanding of the status and habitat preferences of Golden-winged Warbler populations in the Upper Midwest was initiated by the publication of new predictive spatially explicit Golden-winged Warbler habitat models for the northern Midwest. Here, I use original data on observed Golden-winged Warbler abundances in Wisconsin and Minnesota to compare two population models: the hierarchical spatial count (HSC) model with the Habitat Suitability Index (HSI) model. I assessed how well the field data compared to the model predictions and found that within Wisconsin, the HSC model performed slightly better than the HSI model whereas both models performed relatively equally in Minnesota. For the HSC model, I found a 10% error of commission in Wisconsin and a 24.2% error of commission for Minnesota. Similarly, the HSI model has a 23% error of commission in Minnesota; in Wisconsin due to limited areas where the HSI model predicted absences, there was incomplete data and I was unable to determine the error of commission for the HSI model. These are sites where the model predicted presences and the Golden-winged Warbler did not occur. To compare predicted abundance from the two models, a 3x3 contingency table was used. I found that when overlapped, the models do not complement one another in identifying Golden-winged Warbler presences. To calculate discrepancy between the models, the error of commission shows that the HSI model has only a 6.8% chance of correctly classifying absences in the HSC model. The HSC model has only 3.3% chance of correctly classifying absences in the HSI model. These findings highlight the importance of grasses for nesting, shrubs used for cover and foraging, and trees for song perches and foraging as key habitat characteristics for breeding territory occupancy by singing males.

Mainari, Farmari, Lumperjäkki, Piika : “Ethnic Identity” and Earning a Living in the Keweenaw and Nickel Belts to 1930

Job seekers in resource-based economic settings like the Keweenaw Peninsula in Upper Michigan and the Nickel Basin surrounding Sudbury, Ontario faced many challenges, from the dangers of the job to corporate domination to the “boom and bust” nature of inevitably limited supplies of even “endless” natural riches. Adding to these many challenges in both settings was the employer view that you were best suited to certain tasks. This paper examines these expectations from “both” ends – how and why did employers see matters this way, and what did the “recipients” make of being cast in certain roles ? Did the newcomers also expect to earn their keep from a limited range of options ? While the last word on this issue awaits a much larger study, even a glance can inform both the scholar of resource settings and the ethnic historian about an important element of resource-based economies. This paper, then, examines the links between stereotype, preference, and necessity – to what extent did local populations fight, appreciate or succumb to expectation when “making a living.” As the title suggests, Finns get significant attention, as befits both settings under study. However, the paper looks to similar trends amongst a broad demographic swathe in each setting. Was “who” you were the crucial element in finding sustenance ? “Ethnic”, Aboriginal, or “established settler society” – what factors shaped economic expectations, choices and roles?