2 resultados para field methods


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Birds are vulnerable to collisions with human-made fixed structures. Despite ongoing development and increases in infrastructure, we have few estimates of the magnitude of collision mortality. We reviewed the existing literature on avian mortality associated with transmission lines and derived an initial estimate for Canada. Estimating mortality from collisions with power lines is challenging due to the lack of studies, especially from sites within Canada, and due to uncertainty about the magnitude of detection biases. Detection of bird collisions with transmission lines varies due to habitat type, species size, and scavenging rates. In addition, birds can be crippled by the impact and subsequently die, although crippling rates are poorly known and rarely incorporated into estimates. We used existing data to derive a range of estimates of avian mortality associated with collisions with transmission lines in Canada by incorporating detection, scavenging, and crippling biases. There are 231,966 km of transmission lines across Canada, mostly in the boreal forest. Mortality estimates ranged from 1 million to 229.5 million birds per year, depending on the bias corrections applied. We consider our most realistic estimate, taking into account variation in risk across Canada, to range from 2.5 million to 25.6 million birds killed per year. Data from multiple studies across Canada and the northern U.S. indicate that the most vulnerable bird groups are (1) waterfowl, (2) grebes, (3) shorebirds, and (4) cranes, which is consistent with other studies. Populations of several groups that are vulnerable to collisions are increasing across Canada (e.g., waterfowl, raptors), which suggests that collision mortality, at current levels, is not limiting population growth. However, there may be impacts on other declining species, such as shorebirds and some species at risk, including Alberta’s Trumpeter Swans (Cygnus buccinator) and western Canada’s endangered Whooping Cranes (Grus americana). Collisions may be more common during migration, which underscores the need to understand impacts across the annual cycle. We emphasize that these estimates are preliminary, especially considering the absence of Canadian studies.

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The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture–recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals) using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence), which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low) homogenous rates per interval with those singing at (high and low) heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant individuals and by individuals with low singing rates also having very low detection probabilities.