Siva R. Sundaresan

Social relationships and reproductive state influence leadership roles in movements of plains zebra, Equus burchellii

In animal groups, collective movements emerge from individual interactions. Biologists seek to identify how characteristics of actors in these groups, and their relationships, influence the decision-making process. We distinguished two basic factors determining leadership in group choices: identity and state. We hypothesized that identity is more important to leadership in groups with stable relationships, which permit the development of habitual roles. In groups with fluid membership, particular individuals or subgroups are less likely to emerge as consistent leaders. Instead, we predicted that movement initiation in unstable groups depends on individual state at the time of the decision. We characterized how identity and reproductive state influenced leadership patterns in the movements of plains zebra. As in many other mammals, lactation in this species significantly alters water and energy needs. We investigated leadership in tightly knit harems and loosely bonded herds of multiple harems. Harem females tended to have habitual roles in the initiation of harem movement. In herds, however, we found no consistent leaders among harems. At both levels of social organization, lactation was a key determinant of leadership. In harems, lactating females were more likely to initiate movement than nonlactating females. In turn, harems containing lactating females were more likely to lead herd movements. Thus, we conclude that social relationships and reproductive state together shape the interactions that produce group behaviours. One benefit to lactating females of leading herd movements is preferential access to scarce water. Thus, leadership roles in group decisions may have fitness consequences.

Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager

For species in which group membership frequently changes, it has been a challenge to characterize variation in individual interactions and social structure. Quantifying this variation is necessary to test hypotheses about ecological determinants of social patterns and to make predictions about how group dynamics affect the development of cooperative relationships and transmission processes. Network models have recently become popular for analyzing individual contacts within a population context. We use network metrics to compare populations of Grevy’s zebra (Equus grevyi) and onagers (Equus hemionus khur). These closely related equids, previously described as having the same social system, inhabit environments differing in the distribution of food, water, and predators. Grevy’s zebra and onagers are one example of many sets of coarsely similar fission–fusion species and populations, observed elsewhere in other ungulates, primates, and cetaceans. Our analysis of the population association networks reveals contrasts consistent with their distinctive environments. Grevy’s zebra individuals are more selective in their association choices. Grevy’s zebra form stable cliques, while onager associations are more fluid. We find evidence that females associate assortatively by reproductive state in Grevy’s zebra but not in onagers. The current approach demonstrates the utility of network metrics for identifying fine-grained variation among individuals and populations in association patterns. From our analysis, we can make testable predictions about behavioral mechanisms underlying social structure and its effects on transmission processes.

Avoiding spurious findings of nonrandom social structure in association data

Researchers studying animal societies often begin by testing whether a population shows nonrandom social structure, by comparing observed social associations with the predictions of a null model. Association data comprises observations of individuals in groups, which are observed through repeated surveys. Each survey is conducted on a discrete occasion, for example, within 1 day or 1 week. Current null models randomize the interactions among individuals, while preserving two key elements of the data: the number of times that each individual has been seen, and the sizes of observed groups. A critical assumption of existing permutation methods is that each observed group is independent. However, this assumption is often violated. Typically, researchers search a large study area, relative to the distances moved by animals within the sampling occasion. Thus, most individuals will not have had opportunity to change their group associations during a sampling occasion. We show how randomization tests should be modified to account for this nonindependence of group membership. We generated association data sets in which we randomly assigned individuals to groups. We tested these data sets for nonrandom structure using the generally accepted ‘trial swap’ algorithm. We found that spurious conclusions of nonrandom structure occur when we allowed permutation of individuals across sampling occasions, but not when we ‘blocked’ the data by sampling occasion, and constrained our randomizations to permute individuals only among groups within each block.

Reproductive status influences group size and persistence of bonds in male plains zebra (Equus burchelli)

Animal groups arise from individuals’ choices about the number, characteristics, and identity of associates. Individuals make these choices to gain benefits from their associations. As the needs of an individual change with its phenotype, so too we expect the nature of its associations to vary. In this paper, we investigate how the social priorities of male plains zebra (Equus burchelli) depend on reproductive state. An adult male is either a bachelor, and lacking mating access, or a stallion defending a harem. Multiple harems and bachelor males aggregate in larger herds. Herds frequently split and merge, affording males opportunities to change associates. Over a 4-year period, we sampled the herd associations in a population of 500–700 zebras. To isolate the effects of reproductive state on male social behavior, we account for potential confounding factors: changes in population size, grouping tendencies, and sampling intensity. We develop a generally applicable permutation procedure, which allows us to test the null hypothesis that social behavior is independent of male status. Averaging over all individuals in the population, we find that a typical bachelor is found in herds containing significantly more adults, bachelors, and stallions than the herds of a typical stallion. Further, bachelors’ bonds with each other are more persistent over time than those among stallions. These results suggest that bachelors form cohesive cliques, in which we may expect cooperative behaviors to develop. Stallion–stallion associations are more diffuse, and less conducive to long-term cooperation.

Similar but Different: Dynamic Social Network Analysis Highlights Fundamental Differences between the Fission-Fusion Societies of Two Equid Species, the Onager and Grevy’s Zebra

Understanding why animal societies take on the form that they do has benefited from insights gained by applying social network analysis to patterns of individual associations. Such analyses typically aggregate data over long time periods even though most selective forces that shape sociality have strong temporal elements. By explicitly incorporating the temporal signal in social interaction data we re-examine the network dynamics of the social systems of the evolutionarily closely-related Grevy’s zebras and wild asses that show broadly similar social organizations. By identifying dynamic communities, previously hidden differences emerge: Grevy’s zebras show more modularity than wild asses and in wild asses most communities consist of solitary individuals; and in Grevy’s zebras, lactating females show a greater propensity to switch communities than non-lactating females and males. Both patterns were missed by static network analyses and in general, adding a temporal dimension provides insights into differences associated with the size and persistence of communities as well as the frequency and synchrony of their formation. Dynamic network analysis provides insights into the functional significance of these social differences and highlights the way dynamic community analysis can be applied to other species.

HotSpotter — Patterned species instance recognition

We present HotSpotter, a fast, accurate algorithm for identifying individual animals against a labeled database. It is not species specific and has been applied to Grevys and plains zebras, giraffes, leopards, and lionfish. We describe two approaches, both based on extracting and matching keypoints or “hotspots”. The first tests each new query image sequentially against each database image, generating a score for each database image in isolation, and ranking the results. The second, building on recent techniques for instance recognition, matches the query image against the database using a fast nearest neighbor search. It uses a competitive scoring mechanism derived from the Local Naive Bayes Nearest Neighbor algorithm recently proposed for category recognition. We demonstrate results on databases of more than 1000 images, producing more accurate matches than published methods and matching each query image in just a few seconds.

Monitoring an Endangered savannah ungulate, Grevy's zebra Equus grevyi : choosing a method for estimating population densities

Methods that accurately estimate animal abundance or density are crucial for wildlife management. Although numerous techniques are available, there have been few comparisons of the precision and cost-effectiveness of different approaches. We assess the precision and cost of three methods for estimating densities of the Endangered Grevys zebra Equus grevyi . We compare distance sampling and photographic capture–recapture, and a new technique, the random encounter model (REM) that uses camera-trap encounter rates to estimate density. All three methods provide comparable density estimates for Grevys zebra and are preferable to the common practice of raw counts. Photographic capture–recapture is the most precise and line-transect distance sampling the least precise. Line transects and photographic capture–recapture surveys are cost-effective in the first year and REM is most cost-effective in the long-term. The methods used here for Grevys zebra may be applied to other rangeland ungulates. We suggest that for single species monitoring programmes in which individuals can be identified, photographic capture–recapture surveys may be the preferred method for estimating wildlife abundances. When encounter rates are low, distance sampling lacks the precision of the other methods but its cost advantage may make it appropriate for long-term or multi-species monitoring programmes. The REM is an efficient and precise method of estimating densities but has high initial equipment costs. We believe REM has the potential to work well for many species but it requires independent estimates of animal movements and group size.

Management and Analysis of Camera Trap Data: Alternative Approaches (Response to Harris et al. 2010)

A recent article in the ESA Bulletin introduces an approach to cataloging and analyzing the large numbers of photos typically generated by camera traps (Harris et al. 2010). The authors highlight the need for a simple, systematic way to archive and extract data from camera trap photos. The authors then present a system they have developed in an effort to meet this need. Here, we introduce two alternative approaches that each have distinct advantages over the approach outlined by Harris et al.

A rare fight in female plains zebra

We describe a fight between two female plains zebra (Equus burchelli). Plains zebra are ungulates with stable social groups known as harems. Female aggression rarely escalates to the level we observed. The fight immediately followed the birth of a foal to one of the females. The initiating female repeatedly kicked and bit the mother, who reacted aggressively and by guarding her foal. We present hypotheses on the causes underlying this rare event.

A Simple Graphical Approach to Quantitative Monitoring of Rangelands

A Simple Graphical Approach to Quantitative Monitoring of Rangelands DOI:10.2458/azu_rangelands_v33i4_riginos