共查询到10条相似文献，搜索用时 234 毫秒
1.
2.
3.
- 1 Dogs Canis familiaris are the world's most common carnivore and are known to interact with wildlife as predators, prey, competitors, and disease reservoirs or vectors.
- 2 Despite these varied roles in the community, the interaction of dogs with sympatric wild carnivore species is poorly understood. We review how dogs have been classified in the literature, and illustrate how the location and ranging behaviour of dogs are important factors in predicting their interactions with wild prey and carnivores.
- 3 We detail evidence of dogs as intraguild competitors with sympatric carnivores in the context of exploitative, interference and apparent competition.
- 4 Dogs can have localized impacts on prey populations, but in general they are not exploitative competitors with carnivores. Rather, most dog populations are highly dependent on human‐derived food and gain a relatively small proportion of their diet from wild prey. However, because of human‐derived food subsidies, dogs can occur at high population densities and thus could potentially outcompete native carnivores, especially when prey is limited.
- 5 Dogs can be effective interference competitors, especially with medium‐sized and small carnivores. Dogs may fill the role of an interactive medium‐sized canid within the carnivore community, especially in areas where the native large carnivore community is depauperate.
- 6 Dogs can also be reservoirs of pathogens, because most populations around the world are free‐ranging and unvaccinated. Diseases such as rabies and canine distemper have resulted in severe population declines in several endangered carnivores coexisting with high‐density dog populations. Dogs can therefore be viewed as pathogen‐mediated apparent competitors, capable of facilitating large‐scale population declines in carnivores.
- 7 Based on this information, we propose conceptual models that use dog population size and ranging patterns to predict the potential for dogs to be intraguild competitors. We discuss how interactions between dogs and carnivores might influence native carnivore communities.
4.
5.
6.
7.
8.
9.
- 1 Environmental heterogeneity is important in determining the distribution and abundance of organisms at various spatial scales. The ability to understand and predict distribution patterns is important for solving many management problems in conservation biology and wildlife epidemiology.
- 2 The badger Meles meles is a highly adaptable, medium‐sized carnivore, distributed throughout temperate Eurasia, which shows a wide diversity of social and spatial organization. Within Britain, badgers are not only legally protected, but they also serve as a wildlife host for bovine tuberculosis Mycobacterium bovis. An evaluation of the role of badgers in the dynamics of this infection depends on understanding the responses of badgers to the environment at different spatial scales.
- 3 The use of digital data to provide information on habitats for distribution models is becoming common. Digital data are increasingly accessible and are generally cheaper than field surveys. There has been little research, however, to compare the accuracy of models based on field‐derived and remotely derived data.
- 4 In this paper, we make quantified comparisons between large‐scale presence/absence models for badgers in Britain, based on field‐surveyed habitat data and remotely derived digital data, comprising elevation, geology and soil.
- 5 We developed four models: 1980s badger survey data using field‐based and digital data, and 1990s badger survey data using field‐based and digital data. We divided each of the four datasets into two subsets and used one subset for training (developing) the model and the other for testing it.
- 6 All four training models had classification accuracies in excess of 69%. The models generated from digital data were slightly more accurate than those generated from field‐derived habitat data.
- 7 The high classificatory ability of the digital‐based models suggests that the use of digital data may overcome many of the problems associated with field data in wildlife‐habitat modelling, such as cost and restricted geographical coverage, without any significant impact on model performance for some species. The more widespread use of digital data in wildlife‐habitat models should enhance their accuracy, repeatability and applicability and make them better‐suited as tools to aid policy‐ and decision‐making processes.