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Habitat selection has been a central focus of animal ecology, with research primarily concentrating on habitat choice, utilization, and evaluation. However, studies confined to a single scale often fail to reveal the habitat selection needs of animals fully and accurately. This paper investigates the wintering whooper swan (Cygnus cygnus) in Manas National Wetland Park, Xinjiang, using satellite tracking to determine their locations. The Maximum Entropy model (MaxEnt) was applied to explore the multi-scales habitat selection needs of Manas National Wetland Park's wintering whooper swans across nighttime, daytime, and landscape scales. This study showed that the habitat selection of the wintering whooper swans varied in different scales. At the landscape scale, wintering whooper swans prefer habitats with average winter precipitations of 6.9 mm and average temperatures of −6 °C, including water bodies and wetlands, indicating that climate (precipitation and temperature) and land type (wetlands and water bodies) influence their winter habitat selection. During daytime, whooper swans prefer areas close to wetlands, water bodies, and bare land, with a more dispersed distribution of water bodies. For nighttime, they tend to choose areas within the wetland park where human disturbance is minimal and safety is higher. This study can provide scientific basis and data support for habitat conservation and management of wintering waterbirds like whooper swans, recommending targeted conservation measures to effectively manage and protect the wintering grounds of whooper swans. [ABSTRACT FROM AUTHOR]

1. The biases and shortcomings of stepwise multiple regression are well established within the statistical literature. However, an examination of papers published in 2004 by three leading ecological and behavioural journals suggested that the use of this technique remains widespread: of 65 papers in which a multiple regression approach was used, 57% of studies used a stepwise procedure. 2. The principal drawbacks of stepwise multiple regression include bias in parameter estimation, inconsistencies among model selection algorithms, an inherent (but often overlooked) problem of multiple hypothesis testing, and an inappropriate focus or reliance on a single best model. We discuss each of these issues with examples. 3. We use a worked example of data on yellowhammer distribution collected over 4 years to highlight the pitfalls of stepwise regression. We show that stepwise regression allows models containing significant predictors to be obtained from each year's data. In spite of the significance of the selected models, they vary substantially between years and suggest patterns that are at odds with those determined by analysing the full, 4-year data set. 4. An information theoretic (IT) analysis of the yellowhammer data set illustrates why the varying outcomes of stepwise analyses arise. In particular, the IT approach identifies large numbers of competing models that could describe the data equally well, showing that no one model should be relied upon for inference. [ABSTRACT FROM AUTHOR]

This review clarifies important points on habitat selection by the Swamp Rat Rattus lutreolus (Rodentia: Muridae), a species that has been the subject of much research in Australia and has provided a useful model for understanding ecological and biological processes. It also provides an opportunity to cite important earlier research, not readily available through electronic search engines, thus bringing it into current literature to avoid its disappearance into Internet obscurity. We comment on some papers in the literature to correct errors detected and to emphasize the importance of due care in all aspects of a research project, including its reporting. We show that both floristic and structural components have been reported as important to an understanding of habitat and microhabitat selection by R. lutreolus and conclude that it is vegetation density that is of paramount importance. Female R. lutreolus are clearly dominant in driving microhabitat selection, occupying the ‘best’ or densest habitats with male R. lutreolus occupying the next best and Pseudomys or other species, where present occupying the remainder. This demonstrates the important role that intraspecific and interspecific competition play in determining habitat selection. Direct predation and the perception of predation risk may also play a role in habitat selection, again perceived to be pushing individuals towards denser vegetation, representing ‘better cover’. Whether these effects operate as bottom-up or top-down needs careful consideration. Climatic variables, such as ENSO-affecting productivity, and related variables such as temperature and humidity may also play important roles in habitat selection, as can disturbance effects such as wildfire. The relative importance of all of these potential determining factors may vary from place to place, particularly when climatic clines are involved. [ABSTRACT FROM AUTHOR]

The development of methods to analyze habitat selection when resources are defined by several categories (e.g., vegetation types) is a topical issue in radio-tracking studies. The White and Garrott statistic, an extension of the widely used test of Neu et al., can be used to determine whether habitat selection is significant. As well, Manly's selection ratio, a particularly useful measure of resource selectivity by resource users, allows detection of the most strongly selected habitat types. However, when both the number of animals and types of habitat are large, the biologist often has to deal with an excessively large number of measures. In this paper we present a new method, the eigenanalysis of selection ratios, that generalizes these two common methods within the framework of eigenanalyses. This method undertakes an additive linear partitioning of the White and Garrott statistic, so that the difference between habitat use and availability is maximized on the first factorial axes. The eigenanalysis of selection ratios is therefore optimal in habitat selection studies. Although we primarily consider the case where the habitat availability is the same for all animals (design II), we also extend this analysis to the case where the habitat availability varies from one animal to another (design III). An application of this method is provided using radio-tracking data collected on 17 squirrels in five habitat types. The results indicate variability in habitat selection, with two groups of animals displaying two patterns of preference. This difference between the two groups is explained by the patch structure of the study area. Because this method is mainly exploratory, and therefore does not rely on any distributional assumption, we recommend its use in studies of habitat selection. [ABSTRACT FROM AUTHOR]

Resource-selection probability functions and occupancy models are powerful methods of identifying areas within a landscape that are highly used by a species. One common design/analysis method for estimation of a resource-selection probability function is to classify a sample of units as used or unused and estimate the probability of use as a function of independent variables using, for example, logistic regression. This method requires that resource units are correctly classified as unused (i.e., the species is never undetected in a used unit), or that the probability of misclassification is the same for all units. In this paper, I explore these issues, illustrating how misclassifying units as unused may lead to incorrect conclusions about resource use. I also show how recently developed occupancy models can be utilized within the resource-selection context to improve conclusions by explicitly accounting for detection probability. These models require that multiple surveys be conducted at each of a sample of resource units within a relatively short timeframe, but given the growing evidence from simulation studies and field data, I recommend that such procedures should be incorporated into studies of resource use. [ABSTRACT FROM AUTHOR]

Despite many decades of study, scientists cannot answer why colonial breeding has evolved. This paper shows that the evolution of colonial breeding cannot be sufficiently explained by the evolutionary conditions proposed in previous studies. Until now, studies have compared colonial breeding with only solitary non-territorial breeding (two-state comparison) and have discussed factors that facilitate evolution of the former. Here, I propose a new approach, a three-state comparison, which compares colonial breeding with not only solitary non-territorial breeding but also solitary territorial breeding. This three-state comparison indicates that (i) merely determining the factors that make colonial breeding advantageous over non-territorial solitary breeding is not sufficient to explain the evolution of colonial breeding, (ii) the disadvantages of solitary territorial breeding can promote the evolution of colonial breeding, and (iii) the evolution of colonial breeding is far more influenced by different selection pressures than has been predicted by previous studies. Thus, the three-state comparison provides a more precise description of the conditions that lead to the evolution of colonial breeding. [ABSTRACT FROM AUTHOR]

Understanding habitat selection is of primary interest in theoretical and applied ecology. One approach is to infer habitat selection processes from differences in population densities between habitats using methods such as isodar and isoleg analysis. Another approach is to directly observe the movements of individuals. However, habitat selection models based on movement data often fail to adequately incorporate spatial processes. This is problematic if the probability of selecting a particular habitat is dependent upon its spatial context. This would occur, for example, where organisms exhibit home range behavior and the choice of habitat is dependent on its location relative to the home range. In this paper we present a spatially explicit habitat selection model for movement data that incorporates home range behavior as a spatial process. Our approach extends a previous model by formulating the probability of selecting a habitat as a function of its distance from the animal's current location and home range center. We demonstrate that these enhancements lead to more parsimonious models when applied to a koala radio- tracking data set from eastern Australia. This approach could also be applied to modeling other spatial habitat selection processes, leading to more biologically meaningful models for a range of species and applications. [ABSTRACT FROM AUTHOR]

Interspecific competition is one of several constraints that might prevent an individual from maximising its energy intake. When an interspecific competitor is introduced, an individual is often forced to shift its diet according to the intensity of the competitive pressure. In this paper, we explore whether the introduced American mink ( Mustela vison Schreber) shifts its diet when the density of its potential competitor, the Eurasian otter ( Lutra lutra L.), is increased. We compared the diets of otter and mink at the same location but at two moments in time when the relative densities of these two species were different while controlling for the abundance of aquatic prey. Mink and otters are semi-aquatic mammals belonging to the same guild of mustelids and otters are expected to be the dominant competitor because they are larger and better at hunting underwater. The diets of otters and mink overlap to a great extent but while otters specialise mainly on aquatic prey, mink are able to exploit both aquatic and terrestrial prey. These observations prompted the hypothesis investigated in this work that at higher otter densities the diet of mink should change to include a higher proportion of terrestrial items. This hypothesis was supported by the data and at higher otter densities mink diet was observed to consist of a higher proportion of mammals and birds while fewer fish were present, although this pattern was present only in winter while no changes were observed in spring. Meanwhile the diet of otters remained basically unchanged. In the second part of the study, we investigated whether niche breadth and niche overlap between otter and mink changed at different otter densities. We found that niche overlap declined as the density of otters increased, in agreement with the prediction of habitat selection theory. [ABSTRACT FROM AUTHOR]

Forest bats of eastern North America select habitats for roosting, foraging, and winter hibernation/migration over a myriad of scales. An understanding of forest-bat habitat use over scales of time and space is important for their conservation and management. The papers in this Special Section report studies of bat habitat use across multiple scales from locations across the eastern forests of North America. The consensus of the studies in the Special Section is that the larger portion of the variability in bat habitat use occurs at the smaller scales of sites (roost trees) and stands (foraging areas). Nevertheless, it was also recognized that these features occur discontinuously across larger-scale watersheds and landscapes. [ABSTRACT FROM AUTHOR]