3 resultados para LOGISTIC REGRESSION WITH STATE-DEPENDENT SAMPLE SELECTION


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To migrate successfully, birds need to store adequate fat reserves to fuel each leg of the journey. Migrants acquire their fuel reserves at stopover sites; this often entails exposure to predators. Therefore, the safety attributes of sites may be as important as the feeding opportunities. Furthermore, site choice might depend on fuel load, with lean birds more willing to accept danger to obtain good feeding. Here, we evaluate the factors underlying stopover-site usage by migrant Western Sandpipers (Calidris mauri) on a landscape scale. We measured the food and danger attributes of 17 potential stopover sites in the Strait of Georgia and Puget Sound region. We used logistic regression models to test whether food, safety, or both were best able to predict usage of these sites by Western Sandpipers. Eight of the 17 sites were used by sandpipers on migration. Generally, sites that were high in food and safety were used, whereas sites that were low in food and safety were not. However, dangerous sites were used if there was ample food abundance, and sites with low food abundance were used if they were safe. The model including both food and safety best-predicted site usage by sandpipers. Furthermore, lean sandpipers used the most dangerous sites, whereas heavier birds (which do not need to risk feeding in dangerous locations) used safer sites. This study demonstrates that both food and danger attributes are considered by migrant birds when selecting stopover sites, thus both these attributes should be considered to prioritize and manage stopover sites for conservation.

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The Marbled Murrelet (Brachyramphus marmoratus) is a threatened alcid that nests almost exclusively in old-growth forests along the Pacific coast of North America. Nesting habitat has significant economic importance. Murrelet nests are extremely difficult and costly to find, which adds uncertainty to management and conservation planning. Models based on air photo interpretation of forest cover maps or assessments by low-level helicopter flights are currently used to rank presumed Marbled Murrelet nesting habitat quality in British Columbia. These rankings are assumed to correlate with nest usage and murrelet breeding productivity. Our goal was to find the models that best predict Marbled Murrelet nesting habitat in the ground-accessible portion of the two regions studied. We generated Resource Selection Functions (RSF) using logistic regression models of ground-based forest stand variables gathered at plots around 64 nests, located using radio-telemetry, versus 82 random habitat plots. The RSF scores are proportional to the probability of nests occurring in a forest patch. The best models differed somewhat between the two regions, but include both ground variables at the patch scale (0.2-2.0 ha), such as platform tree density, height and trunk diameter of canopy trees and canopy complexity, and landscape scale variables such as elevation, aspect, and slope. Collecting ground-based habitat selection data would not be cost-effective for widespread use in forestry management; air photo interpretation and low-level aerial surveys are much more efficient methods for ranking habitat suitability on a landscape scale. This study provides one method for ground-truthing the remote methods, an essential step made possible using the numerical RSF scores generated herein.

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There is persistent interest in understanding responses of passerine birds to habitat fragmentation, but research findings have been inconsistent and sometimes contradictory in conclusions about how birds respond to characteristics of sites they occupy, such as habitat patch size or edge density. We examined whether these inconsistencies could result from differences in the amount of habitat in the surrounding landscape, e.g., for woodland birds, the amount of tree cover in the surrounding landscape. We compared responses of 22 woodland bird species to proximate-scale tree cover in open landscapes versus wooded landscapes. Our main expectation was that woodland birds would tolerate less suitable sites (less tree cover at the site scale) in open environments where they had little choice–where little tree cover was available in the surrounding area. We compared responses using logistic regression coefficients and loess plots in open and wooded landscapes in eastern North Dakota, USA. Responses to proximate-scale tree cover were stronger, not weaker, as expected, in open landscapes. In some cases the sign of the response changed from positive to negative in contrasting landscapes. We draw two conclusions: First, observed responses to proximate habitat measures such as habitat extent or edge density cannot be interpreted reliably unless landscape context is specified. Second, birds appear more selective, not less so, where habitat is sparse. Habitat loss and fragmentation at the landscape scale are likely to reduce the usefulness of local habitat conservation, and regional drivers in land-use change can have important effects for site-scale habitat use.