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.

Short-Term Dispersal and Long-Term Spatial and Temporal Patterns of Carabidae (Coleoptera) in Lowbush Blueberry Fields.

Carabidae (Coleoptera) are important natural enemies of many insect pests in various cropping systems. Their population dynamics and how they disperse determine how effective they are at carrying out the natural enemy function. There are robust patterns of community dynamics in annual cropping systems, but it is unclear if these would carry over into a relatively underexplored North American perennial crop. In Nova Scotia lowbush blueberry fields, we found that Carabidae diversity did not change with distance from field edge nor with time. Their activity density also did not change with time, but it did change with distance from field edge. We also found that the most abundant carabid of lowbush blueberry, Harpalus rufipes (De Geer) (Coleoptera: Carabidae), can disperse approximately 14.5 m/d. Our results shed more light on the community dynamics of Carabidae in lowbush blueberry fields and can help growers make informed decisions when it comes to incorporating natural enemies into their pest management practices.

Poecilus lucublandus (Coleoptera: Carabidae) and Pterostichus mutus Do Not Feed on Hair Fescue, Red Sorrel, and Poverty Oatgrass Seeds.

Poecilus lucublandus (Say), Pterostichus mutus (Say), and Harpalus rufipes (De Geer) are abundant Carabidae in lowbush blueberry fields and may contribute to weed seed predation. We used laboratory no-choice test experiments to determine if these beetles feed on seeds of hair fescue (Festuca filiformis Pourr., Poales: Poaceae), poverty oatgrass (Danthonia spicata L.), and red sorrel (Rumex acetosella L., Caryophyllales: Polygonaceae), which are common weeds in lowbush blueberry (Vaccinium angustifolium Ait., Ericales: Ericaceae) fields. Poecilus lucublandus and P. mutus did not feed on seeds of the test weed species, but H. rufipes consumed on average over 30 seeds of each species. There are other weed seeds in blueberry fields that could be palatable to P. lucublandus and P. mutus, which warrants further research on the granivory potential of these important carabid species.

Movement Path Tortuosity in Free Ambulation: Relationships to Age and Brain Disease.

Ambulation is defined by duration, distance traversed, number and size of directional changes, and the interval separating successive movement episodes; more complex measures of ambulation can be created by aggregating these features. This review article of published findings defines random changes in direction during movement as "movement path tortuosity" and relates tortuosity to the understanding of cognitive impairments of persons of all ages. Path tortuosity is quantified by subjecting tracking data to fractal analysis, specifically Fractal Dimension (Fractal D), which ranges from a value of 1 when the movement path is perfectly straight to a value of 2 when the movement path is random, resembling the "drunkard's walk." The review elucidates the mathematical assumptions underlying Fractal D, its use in the analysis of movements of free ranging animals, and its application to the study of cognitive impairment and the prediction of falls in older adults. We conclude Fractal D offers a reliable, valid, sensitive, and easily interpreted real-time longitudinal measure of unrestricted movement path tortuosity unaffected by mobility aid use.

Combining animal movements and behavioural data to detect behavioural states.

Animal movement paths show variation in space caused by qualitative shifts in behaviours. I present a method that (1) uses both movement path data and ancillary sensor data to detect natural breakpoints in animal behaviour and (2) groups these segments into different behavioural states. The method can also combine analyses of different path segments or paths from different individuals. It does not assume any underlying movement mechanism. I give an example with simulated data. I also show the effects of random variation, # of states and # of segments on this method. I present a case study of a fisher movement path spanning 8 days, which shows four distinct behavioural states divided into 28 path segments when only turning angles and speed were considered. When accelerometer data were added, the analysis shows seven distinct behavioural states divided into 41 path segments.

Sampling animal movement paths causes turn autocorrelation.

Animal movement models allow ecologists to study processes that operate over a wide range of scales. In order to study them, continuous movements of animals are translated into discrete data points, and then modelled as discrete models. This discretization can bias the representation of the movement path. This paper shows that discretizing correlated random movement paths creates a biased path by creating correlations between successive turning angles. The discretization also biases statistical tests for correlated random walks (CRW) and causes an overestimate in distances travelled; a correction is given for these biases. This effect suggests that there is a natural scale to CRWs, but that distance-discretized CRWs are in a sense, scale invariant. Perhaps a new null model for continuous movement paths is needed. Authors need to be aware of the biases caused by discretizing correlated random walks, and deal with them appropriately.

Shape of patch edges affects edge permeability for meadow voles.

Human development typically fragments natural habitats into patches, affecting population and metapopulation dynamics via changes in animal behavior. Emigration from one habitat patch to another has a large effect on population and metapopulation dynamics. One factor that affects emigration is permeability of patch edges. This study looks at the effects of edge shape (convex, concave, and straight) on edge permeability for meadow voles (Microtus pennsylvanicus).. I tested five hypotheses for responses of animal movement to patch shape: (1) neutral edge response; (2) edge attraction; (3) edge avoidance; (4) time-minimizing, in which an animal attempts to minimize the time spent in inhospitable matrix, and thus travels as far as possible in the patch before crossing the edge; and (5) protection, in which an animal attempts to maximize protection while in the inhospitable matrix by keeping the patch close by. These hypotheses were tested by an experimental manipulation of meadow vole habitats. A strip was mowed with different edge shapes through an old field, and vole response was measured by tracking plates. Voles crossed edges at concave treatments twice as often compared to convex and straight shapes. Hypotheses (2) and (5) were supported. Although edge attraction causes a passive effect of a decrease in edge-crossing at concavities, this effect was eclipsed by the active effect of voles choosing to cross at concavities. The results can be generalized to edge tortuosity in general. Conservation biologists should consider edge shapes when exploring the effects of habitat fragmentation on animal populations.

Emergent properties of patch shapes affect edge permeability to animals.

Animal travel between habitat patches affects populations, communities and ecosystems. There are three levels of organization of edge properties, and each of these can affect animals. At the lowest level are the different habitats on each side of an edge, then there is the edge itself, and finally, at the highest level of organization, is the geometry or structure of the edge. This study used computer simulations to (1) find out whether effects of edge shapes on animal behavior can arise as emergent properties solely due to reactions to edges in general, without the animals reacting to the shapes of the edges, and to (2) generate predictions to allow field and experimental studies to test mechanisms of edge shape response. Individual animals were modeled traveling inside a habitat patch that had different kinds of edge shapes (convex, concave and straight). When animals responded edges of patches, this created an emergent property of responding to the shape of the edge. The response was mostly to absolute width of the shapes, and not the narrowness of them. When animals were attracted to edges, then they tended to collect in convexities and disperse from concavities, and the opposite happened when animals avoided edges. Most of the responses occurred within a distance of 40% of the perceptual range from the tip of the shapes. Predictions were produced for directionality at various locations and combinations of treatments, to be used for testing edge behavior mechanisms. These results suggest that edge shapes tend to either concentrate or disperse animals, simply because the animals are either attracted to or avoid edges, with an effect as great as 3 times the normal density. Thus edge shape could affect processes like pollination, seed predation and dispersal and predator abundance.

The effect of phenotypic traits and external cues on natal dispersal movements.

1. Natal dispersal has the potential to affect most ecological and evolutionary processes. However, despite its importance, this complex ecological process still represents a significant gap in our understanding of animal ecology due to both the lack of empirical data and the intrinsic complexity of dispersal dynamics. 2. By studying natal dispersal of 74 radiotagged juvenile eagle owls Bubo bubo (Linnaeus), in both the wandering and the settlement phases, we empirically addressed the complex interactions by which individual phenotypic traits and external cues jointly shape individual heterogeneity through the different phases of dispersal, both at nightly and weekly temporal scales. 3. Owls in poorer physical conditions travelled shorter total distances during the wandering phase, describing straighter paths and moving slower, especially when crossing heterogeneous habitats. In general, the owls in worse condition started dispersal later and took longer times to find further settlement areas. Net distances were also sex biased, with females settling at further distances. Dispersing individuals did not seem to explore wandering and settlement areas by using a search image of their natal surroundings. Eagle owls showed a heterogeneous pattern of patch occupancy, where few patches were highly visited by different owls whereas the majority were visited by just one individual. During dispersal, the routes followed by owls were an intermediate solution between optimized and randomized ones. Finally, dispersal direction had a marked directionality, largely influenced by dominant winds. These results suggest an asymmetric and anisotropic dispersal pattern, where not only the number of patches but also their functions can affect population viability. 4. The combination of the information coming from the relationships among a large set of factors acting and integrating at different spatial and temporal scales, under the perspective of heterogeneous life histories, are a fruitful ground for future understanding of natal dispersal.

Animal movement rates as behavioural bouts.

Johnson et al. (Journal of Animal Ecology, 2002, 71, 225-235) have proposed a new technique for identifying scales of movement in animals. Animals are located at certain time intervals, and movement rates between successive animal relocations are calculated. The null model of a nonscalar response predicts a decreasing linear relationship between log (frequency) vs. movement rate, while a scalar response predicts a monotonically decreasing curve with an inflection point at the separation between the processes. I tested this technique using three types of simulated movement paths: correlated random walks, directed walks, and movements in patchy habitat. None of the simulations showed the results expected by the technique. This occurs because the technique assumes that movement rates are exponentially distributed, which is highly unlikely. Thus before this technique can be applied to animal movement data we need to understand how spatial and temporal scale, as well as sampling interval, affect the frequency histogram of animal movement rates.

Improving accuracy and precision in estimating fractal dimension of animal movement paths.

It is difficult to watch wild animals while they move, so often biologists analyse characteristics of animal movement paths. One common path characteristic used is tortuousity, measured using the fractal dimension (D). The typical method for estimating fractal D, the divider method, is biased and imprecise. The bias occurs because the path length is truncated. I present a method for minimising the truncation error. The imprecision occurs because sometimes the divider steps land inside the bends of curves, and sometimes they miss the curves. I present three methods for minimising this variation and test the methods with simulated correlated random walks. The traditional divider method significantly overestimates fractal D when paths are short and the range of spatial scales is narrow. The best method to overcome these problems consists of walking the dividers forwards and backwards along the path, and then estimating the path length remaining at the end of the last divider step.

Using animal movement paths to measure response to spatial scale.

Animals live in an environment that is patchy and hierarchical. I present a method of detecting the scales at which animals perceive their world. The hierarchical nature of habitat causes movement path structure to vary with spatial scale, and the patchy nature of habitat causes movement path structure to vary throughout space. These responses can be measured by a combination of path tortuousity (measured with fractal dimension) versus spatial scale, the variation in tortuousity of small path segments along the movement path, and the correlation between tortuousities of adjacent path segments. These statistics were tested using simulated animal movements. When movement paths contained no spatial heterogeneity, then fractal D and variance continuously increased with scale, and correlation was zero at all scales. When movement paths contained spatial heterogeneity, then fractal D sometimes showed a discontinuity at transitions between domains of scale, variation showed peaks at transitions, and correlations showed a statistically significant positive value at scales smaller than patch size, decreasing to below zero at scales greater than patch size. I illustrated these techniques with movement paths from deer mice and red-backed voles. These new analyses should help understand how animals perceive and react to their landscape structure at various spatial scales, and to answer questions about how habitat structure affects animal movement patterns.