A method to predict overall food preferences

Most natural ecosystems contain animals feeding on many different types of food, but it is difficult to predict what will be eaten when food availabilities change. We present a method that estimates food preference over many study sites, even when number of food types vary widely from site to site. Sampling variation is estimated using bootstrapping. We test the precision and accuracy of this method using computer simulations that show the effects of overall number of food types, number of sites, and proportion of missing prey items per site. Accuracy is greater with fewer missing prey types, more prey types and more sites, and is affected by the number of sites more than the number of prey types. We present a case study using lion (Panthera leo) feeding data and show that preference vs prey size follows a bell-curve. Using just two estimated parameters, this curve can be used as a general way to describe predator feeding patterns. Our method can be used to: test hypotheses about what factors affect prey selection, predict preferences in new sites, and estimate overall prey consumed in new sites.The Natural Sciences and Engineering Research Council of Canada and a Hugh Kelly Fellowship from Rhodes University, Grahamstown, SA.http://www.plosone.orgdm2022Mammal Research Institut

Changes of movement patterns from early dispersal to settlement

Moving and spatial learning are two intertwined processes: (a) changes in movement behavior determine the learning of the spatial environment, and (b) information plays a crucial role in several animal decision-making processes like movement decisions. A useful way to explore the interactions between movement decisions and learning of the spatial environment is by comparing individual behaviors during the different phases of natal dispersal (when individuals move across more or less unknown habitats) with movements and choices of breeders (who repeatedly move within fixed home ranges), that is, by comparing behaviors between individuals who are still acquiring information vs. individuals with a more complete knowledge of their surroundings. When analyzing movement patterns of eagle owls, Bubo bubo, belonging to three status classes (floaters wandering across unknown environments, floaters already settled in temporary settlement areas, and territory owners with a well-established home range), we found that: (1) wandering individuals move faster than when established in a more stable or fixed settlement area, traveling larger and straighter paths with longer move steps; and (2) when floaters settle in a permanent area, then they show movement behavior similar to territory owners. Thus, movement patterns show a transition from exploratory strategies, when animals have incomplete environmental information, to a more familiar way to exploit their activity areas as they get to know the environment better. © Springer-Verlag 2009.Peer Reviewe

Diet selection in the Coyote Canis latrans

The Coyote (Canis latrans) is one of the most studied species in North America with at least 445 papers on its diet alone. While this research has yielded excellent reviews of what coyotes eat, it has been inadequate to draw deeper conclusions because no synthesis to date has considered prey availability. We accounted for prey availability by investigating the prey selection of coyotes across its distribution using the traditional Jacobs’ index method, as well as the new iterative preference averaging (IPA) method on scats and biomass. We found that coyotes selected for Dall’s Sheep (Ovis dalli), White-tailed Deer (Odocoileus virginianus), Eastern Cottontail Rabbit (Sylvilagus floridanus), and California Vole (Microtus californicus), which yielded a predator-to-preferred prey mass ratio of 1:2. We also found that coyotes avoided preying on other small mammals, including carnivorans and arboreal species. There was strong concordance between the traditional and IPA method on scats, but this pattern was weakened when biomass was considered. General linear models revealed that coyotes preferred to prey upon larger species that were riskier to hunt, reflecting their ability to hunt in groups, and were least likely to hunt solitary species. Coyotes increasingly selected Mule Deer (O. hemionus) and Snowshoe Hare (Lepus americanus) at higher latitudes, whereas Black-tailed Jackrabbit (L. californicus) were increasingly selected toward the tropics. Mule Deer were increasingly selected at higher coyote densities, while Black-tailed Jackrabbit were increasingly avoided at higher coyote densities. Coyote predation could constrain the realized niche of prey species at the distributional limits of the predator through their increased efficiency of predation reflected in increased prey selection values. These results are integral to improved understandings of Coyote ecology and can inform predictive analyses allowing for spatial variation, which ultimately will lead to better understandings about the ecological role of the coyote across different ecosystems

Density of animal locations vs. distance from edge of patch, for three different types of behaviors to the edge, for straight edges.

<p>Note the log scale for density. Densities are in proportion to the mean density in the whole patch - thus, 1 means no effect of the edge. Attraction and avoidance give proportionally similar effects, with most effects within 1 unit from the edge.</p

Example of densities of animals at different types of edge shapes, for width of shapes = 10.

<p>Example of densities of animals at different types of edge shapes, for width of shapes = 10.</p

Directionality towards the inside, where 1 means pointed towards the inside of the patch, and -1 means pointed towards the outside.

<p><b>A</b>: Overall effects for different edge behaviors and edge shapes. Bars are grouped by behavior to edge, and within each group, bars show animals' behaviors to the edge: straight, in and out. The main differences are in the type of avoidance behavior, not in edge shapes. <b>B</b>: For the Out shape only, To-inside vs. width of edge shape. Each color represents different edge behaviors. With all behaviors, directionality changes very close to the tips of the edge shapes.</p

The simulated habitat patch that modeled animals traveled in.

<p>The grey areas show the sampling sites for the three different kinds of treatment edges. Size and shape of the edge types was varied.</p

Density of animal locations vs. widths of edge shapes. Densities are in proportion to the mean density in the whole patch - thus, 1 means no effect of the edge.

<p>The three plots show different types of behaviors to the edge: <b>A</b> - attraction, <b>B</b> - neutral, <b>C</b> - avoidance. Within each graph, the different colors lines represent the different types of edge shapes. The different lines of each color represent different narrownesses. The tight clustering of the colored lines as compared to the change along the x-axis shows that most of the effects on density are due to point width, not point narrowness.</p

Three types of modeled behaviors to edges.

<p>The top row of figures represents how animals reflected from the edge and the bottom row represents how animals turned while within detecting distance of the edge.</p

Landscape Ecology vol. 11 no. 5 pp 289-297 (1996)

Fractal measurements of animal movement paths have been used to analyze how animals view habitats at different spatial scales. One problem has been the absence of error estimates for fractal d estimators. To address this weakness, I present and test 4 new estimators for measuring fractal dimension at different spatial scales, along with estimates of their variation. The estimators are based on dividing the movement path into pairs of steps, forming V&apos;s, and then estimating various statistics from each V