3 resultados para model selection in binary regression


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Detailed knowledge of waterfowl abundance and distribution across Canada is lacking, which limits our ability to effectively conserve and manage their populations. We used 15 years of data from an aerial transect survey to model the abundance of 17 species or species groups of ducks within southern and boreal Canada. We included 78 climatic, hydrological, and landscape variables in Boosted Regression Tree models, allowing flexible response curves and multiway interactions among variables. We assessed predictive performance of the models using four metrics and calculated uncertainty as the coefficient of variation of predictions across 20 replicate models. Maps of predicted relative abundance were generated from resulting models, and they largely match spatial patterns evident in the transect data. We observed two main distribution patterns: a concentrated prairie-parkland distribution and a more dispersed pan-Canadian distribution. These patterns were congruent with the relative importance of predictor variables and model evaluation statistics among the two groups of distributions. Most species had a hydrological variable as the most important predictor, although the specific hydrological variable differed somewhat among species. In some cases, important variables had clear ecological interpretations, but in some instances, e.g., topographic roughness, they may simply reflect chance correlations between species distributions and environmental variables identified by the model-building process. Given the performance of our models, we suggest that the resulting prediction maps can be used in future research and to guide conservation activities, particularly within the bounds of the survey area.

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Understanding the effect of habitat fragmentation is a fundamental yet complicated aim of many ecological studies. Beni savanna is a naturally fragmented forest habitat, where forest islands exhibit variation in resources and threats. To understand how the availability of resources and threats affect the use of forest islands by parrots, we applied occupancy modeling to quantify use and detection probabilities for 12 parrot species on 60 forest islands. The presence of urucuri (Attalea phalerata) and macaw (Acrocomia aculeata) palms, the number of tree cavities on the islands, and the presence of selective logging,and fire were included as covariates associated with availability of resources and threats. The model-selection analysis indicated that both resources and threats variables explained the use of forest islands by parrots. For most species, the best models confirmed predictions. The number of cavities was positively associated with use of forest islands by 11 species. The area of the island and the presence of macaw palm showed a positive association with the probability of use by seven and five species, respectively, while selective logging and fire showed a negative association with five and six species, respectively. The Blue-throated Macaw (Ara glaucogularis), the critically endangered parrot species endemic to our study area, was the only species that showed a negative association with both threats. Monitoring continues to be essential to evaluate conservation and management actions of parrot populations. Understanding of how species are using this natural fragmented habitat will help determine which fragments should be preserved and which conservation actions are needed.

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Successful conservation of migratory birds demands we understand how habitat factors on the breeding grounds influences breeding success. Multiple factors are known to directly influence breeding success in territorial songbirds. For example, greater food availability and fewer predators can have direct effects on breeding success. However, many of these same habitat factors can also result in higher conspecific density that may ultimately reduce breeding success through density dependence. In this case, there is a negative indirect effect of habitat on breeding success through its effects on conspecific density and territory size. Therefore, a key uncertainty facing land managers is whether important habitat attributes directly influence breeding success or indirectly influence breeding success through territory size. We used radio-telemetry, point-counts, vegetation sampling, predator observations, and insect sampling over two years to provide data on habitat selection of a steeply declining songbird species, the Canada Warbler (Cardellina canadensis). These data were then applied in a hierarchical path modeling framework and an AIC model selection approach to determine the habitat attributes that best predict breeding success. Canada Warblers had smaller territories in areas with high shrub cover, in the presence of red squirrels (Tamiasciurus hudsonicus), at shoreline sites relative to forest-interior sites and as conspecific density increased. Breeding success was lower for birds with smaller territories, which suggests competition for limited food resources, but there was no direct evidence that food availability influenced territory size or breeding success. The negative relationship between shrub cover and territory size in our study may arise because these specific habitat conditions are spatially heterogeneous, whereby individuals pack into patches of preferred breeding habitat scattered throughout the landscape, resulting in reduced territory size and an associated reduction in resource availability per territory. Our results therefore highlight the importance of considering direct and indirect effects for Canada warblers; efforts to increase the amount of breeding habitat may ultimately result in lower breeding success if habitat availability is limited and negative density dependent effects occur.