4 resultados para Seclusion and restraint predictor

em Avian Conservation and Ecology - Eletronic Cientific Hournal - Écologie et conservation des oiseaux:


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There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species–area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species–area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km × 10 km) and regional (290 km × 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.

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Declining grassland breeding bird populations have led to increased efforts to assess habitat quality, typically by estimating density or relative abundance. Because some grassland habitats may function as ecological traps, a more appropriate metric for determining quality may be breeding success. Between 1994 and 2003 we gathered data on the nest fates of Eastern Meadowlarks (Sturnella magna), Bobolinks (Dolichonyx oryzivorous), and Savannah Sparrows (Passerculus sandwichensis) in a series of fallow fields and pastures/hayfields in western New York State. We calculated daily survival probabilities using the Mayfield method, and used the logistic-exposure method to model effects of predictor variables on nest success. Nest survival probabilities were 0.464 for Eastern Meadowlarks (n = 26), 0.483 for Bobolinks (n = 91), and 0.585 for Savannah Sparrows (n = 152). Fledge dates for first clutches ranged between 14 June and 23 July. Only one obligate grassland bird nest was parasitized by Brown-headed Cowbirds (Molothrus ater), for an overall brood parasitism rate of 0.004. Logistic-exposure models indicated that daily nest survival probabilities were higher in pastures/hayfields than in fallow fields. Our results, and those from other studies in the Northeast, suggest that properly managed cool season grassland habitats in the region may not act as ecological traps, and that obligate grassland birds in the region may have greater nest survival probabilities, and lower rates of Brown-headed Cowbird parasitism, than in many parts of the Midwest.

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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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Feeding wild birds creates an important link between homeowners and conservation. The effects of bird feeders and year-round feeding on birds have not been well studied, however, particularly in relationship to bird-window collisions. We determined effects of bird feeder presence and placement on bird-window collisions at residential homes. Paired month-long trials in which a feeder was either present or absent for one month and then removed or added for the second month were completed at 55 windows at 43 houses. In each trial, homeowners were asked to search their study window daily for evidence of a bird-window collision. During the study there were 51 collisions when there was no bird feeder and 94 when the feeder was present. The season when each trial was set up was the best individual predictor of bird-window collisions. The largest number of collisions was observed during fall migration and the lowest during the winter months. There were no collisions at 26 of the study windows. High variance was observed in the number of collisions at different houses, indicating that effects of bird feeders are context dependent. Changing the occurrence, timing, and placement of feeders can alter collision rates but is only one of many factors that influence whether a residential house is likely to have a bird window-collision or not.