Daniel Ian Rubenstein, Ph.D. - US grants

9520626 Flying insects vary in the metabolic fuels they use to support energetically costly flight. Flies and bees usually use sugars to fuel flight, while moths and butterflies usually use fat stores. This research will examine metabolic physiology at several levels in a hawkmoth whose heavy body, narrow wings and rapid flight impose high flight costs. Measurement of rates of oxygen consumption and carbon dioxide production during flight will indicate whether sugars or fats are being oxidized. Moths that have fed on sugar-rich nectar will be compared with unfed moths to determine whether fuel use varies with nutritional status. Maximum reaction rates of catabolic enzymes in the carbohydrate and lipid burning pathways of flight muscle will be assayed to determine how feeding and flight performance relate to the moth's underlying metabolic biochemistry. Stable isotope analysis will be used to characterize the contribution of larvally-obtained and adult- obtained resources to egg provisioning. The research will improve understanding of the constraints on activity metabolism and the relative importance of metabolic capacity and fuel availability in limiting performance. Improved understanding of the way energy is allocated between flight and reproduction may increase our understanding of the population dynamics of flying insects.

Animal Behavior Program

Non-technical Abstract



Title: Multilevel social organization in plains zebra: from mating systems to social systems

PI: Daniel I. Rubenstein

Proposal #: 9874523

The core of many animal societies is the mating system, which is built upon the amicable and aggressive relationships that develop between reproductive males and females. But reproductive units are themselves often organized into larger social groups thus creating layers in animal societies. Dr. Rubenstein will examine these issues in the multilevel society of plains zebras (Equus burchelli), a grazing mammal of the East African savanna ecosystem. The mating system of plains zebras consists of year-round harems in which females and their young offspring live with one dominant male. These reproductive groups often associate with other similar groups or with subadult males. Therefore, the plains zebra is an ideal species to examine the structure and function of societies with multiple levels of organization. Dr. Rubenstein will determine why higher level associations form and persist; and he will determine how they act as coordinated units. Long-term movements and associations of individually recognizable zebras will be monitored in relation to underlying variation in environmental factors such as vegetation quality and predator risk. Leadership and following decisions of individuals within core groups, and resolution of conflicts among individuals with differing interests will elucidate the trade-offs involved in this social system.

The overall result of the study will be a better understanding of the dynamics of complex societies that are often hierarchically structured--but much less visibly than those of zebras where membership in a core group restricts total freedom of movement within a society at large. In addition to elucidating these general 'rules' of social organization data on zebra abundances, distributions and patterns of recruitment in relation to ecology and social organization will have important applications for managing wildlife in sustainable ways.

Differences in population density are often reflected in social behavior yet the pathways and mechanisms remain to be elucidated, particularly in natural populations. This research on a wild population of the prosimian, Lemur catta, uses endocrine responses to identify the relative contributions of several ecological and social stressors to density-dependent changes in behavior, physiology, and reproductive success. The study benefits from unique field conditions in which six habituated primate groups are studied across a well-documented population-density gradient, and research methods have been established for obtaining individual-level data on survival, reproduction, foraging efficiency, aggressive behavior, and levels of stress response as measured by excreted steroids sampled without intervention. The data for approximately 80 animals over a two-year period permit testing the hypotheses that food scarcity, conflicts within groups, and conflicts between groups are reflected to varying degrees in cortisol levels and that the magnitude of this stress response predicts individual health and short-term reproductive success.

Improvements in Facilities and Equipment at Mpala Research Centre, Kenya
Daniel I.Rubenstein, P.I.

The goal of the project is to enhance the quality of ecological research in the arid lands of East Africa by improving the physical infrastructure and the research capabilities of the Mpala Research Centre. The Centre, whose purpose is to advance research in the environmental, biological, and conservation sciences, lies at the heart of the Laikipia ecosystem, a diverse savanna maintaining prodigious wildlife populations, much of it not formally protected in National Parks or Reserves. This landscape is prone to severe environmental fluctuations that produce periodic droughts and floods which challenges the ability of indigenous peoples, commercial ranchers and the wildlife itself to survive. It is part of the Centre's mission to shape research programs that will provide scientific insights that help maintain the ecosystem while enhancing the quality of life of the people utilizing the ecosystem's resources. Fulfilling this mission requires melding institutionally driven mission-motivated research with applications emerging from fundamental research projects initiated by individual investigators. Improving the ability of scientists from all over the world, but mostly those from the US whose research is already supported by the National Science Foundation, to carry out these different types of research requires that the Centre enhance and enlarge its physical plant and provide additional common research support facilities.

In particular the Centre will improve its: 1) electrical system to provide uninterrupted electricity to run laboratory equipment and computers essential for data recording and analysis; 2) research space so that the large and integrated projects have adequate space for the teams to function coherently; 3) housing stock to accommodate the Resident Scientist who serves as the local research coordinator and the newly hired Geographical Information System specialist who will provide support for the analysis of spatial problems so important for the understanding of climate patterns and wildlife as well as livestock movements and population dynamics; 4) monitoring equipment both on the ground and in the air to provide the long-term data bases so essential for forecasting changes in environmental conditions, wildlife numbers and livestock levels so that rational and sustainable programs of management and conservation can be formulated; and 5) stock of shared and communal research, communication and computer equipment along with 4 x 4 vehicles for traveling over the rugged terrain.

Research at Mpala Research Centre is intended to advance an informed and integrated approach to natural resource management and conservation within the Laikipia savanna ecosystem. In doing so the research provides the scientific background that is used by commercial ranches and the group ranches composed of indigenous peoples to better manage their lands, stock and wildlife in economically and ecologically sensible ways. Policies based on research are helping ensure that wildlife helps 'pay' for its protection by means of sustainable regimes of culling and consumption on some lands and ecotourism enterprises on others. In addition, outreach to these various communities on how to live with predators and wildlife competitors is helping maintain the dynamics of this harsh ecosystem. Courses taught with 'hands on' projects to wildlife professionals from governmental and non-governmental organization as well as student groups from Kenyan and international Universities are common and are helping transform the minds of the next generation of environmental leaders along with those who are making critical decisions today.

As computer systems become increasingly ubiquitous, computer systems research and design has moved
from being a highly performance-centric process to being one that juggles many design goals and metrics.
Mobile and embedded computing systems must, in addition to providing sufficient performance, be rugged,
reliable, power-efficient, and lightweight. Because of the extreme and multidimensional design constraints they face, they must also be attentive to the specific needs of application domains, so they can be designed to satisfy these needs while still meeting power budgets and weight limits.

The Princeton ZebraNet Project is an inter-disciplinary effort with thrusts in both Biology and Computer
Systems. On the computer systems side, ZebraNet is studying power-aware, position-aware
computing/communication systems. Namely, the ZebraNet project works to develop, evaluate, implement,
and test systems that integrate computing, wireless communication, and non-volatile storage along with
global positioning systems (GPS) and other sensors. On the biology side, the technology enables novel
studies of animal migrations and inter-species interactions. From a computing standpoint, key research
breakthroughs are required in protocol and system design in order to make the system power-efficient and
reliable. From a biology standpoint, the system enables fundamentally new types of biological
observations that allow us to: (i) understand long-range migrations in large mammals, (ii) observe inter-species interactions between carnivores (predators) and ungulates (prey), and (iii) track the behavior of extremely endangered species.

As a computer systems research problem, ZebraNet is compelling because the needs of the biological
researchers are stringent enough to require real breakthroughs in wireless protocols and in low-power
computer systems design and computer systems power management. These breakthroughs can be
leveraged into other (non-wildlife-oriented) fields of research; essentially ZebraNet is a power-aware
wireless ad hoc sensor network, but with more serious bandwidth and computational needs than most prior
sensor networks research problems. As a biology research problem, ZebraNet allows researchers to pose
and to answer important long-standing questions about long-range migration, inter-species interactions, and nocturnal behavior.

Major research activities span a broad range, including:
Modeling long-range animal migrations
Observing inter-species predator-prey interactions
Analyzing the impact of human development on animal behavior
Developing power-aware systems for position-aware computing
Incorporating error resilience and domain-specific performance optimizations into lightweight
wireless protocols
Managing logged sensor data to minimize the number of required uploads from tracking nodes

ZebraNet is engaging in a mix of theoretical research, prototyping, and field experimentation. The project
is not solely about systems-building, but rather mixes theory with practical hands-on evaluations of the
ZebraNet designs. Research is conducted both at Princeton University and at the Mpala Research Centre.
Mpala is a biology field station in central Kenya that Princeton University administers along with the
Kenya Wildlife Service, the National Museums of Kenya, the Mpala Wildlife Foundation, and the
Smithsonian Institution.

Overall, ZebraNet represents a truly interdisciplinary effort bringing together research strengths from
disparate fields over a challenging problem. The potential contribution of the project includes significant
advances in computing technology as well as in our understanding of wildlife migrations. The three main
researchers bring strengths in wildlife biology, power-aware computer systems, and wireless technology.
The interplay between these disciplines fosters creative to the research problems in both arenas.

Project Summary
This project studies the role of ecological and social factors in shaping social
organizing relationships in fission-fusion ungulate societies. Current models of fission-
fusion societies focus either on examining preferential associations between individuals
or on examining factors that determine group size and its correlation with group size
variations. Individual relationships are still not completely understood. A novel model for
analyzing individual relationships incorporating key ecological and social drivers (i.e.
forage, water, predators and bachelor males) together with female internal state is used to
predict rules for associations between individuals. The consequences of these individual
decisions for population level association and dispersion patterns are also explored. The
predictions derived from this framework will be tested using ecological and behavioral
data from two endangered Equids: Grevys zebra (Equus grevyi) and Asiatic Wild Asses
(Equus hemionus) at four sites. Both species have similar morphology, physiology and
social systems. The four sites provide natural variation in ecological and social factors
and serve as an ideal system for exploring the predictions of our model. The broader
impacts of the study include educational activities about the value of ecological and
behavioral data for lay public, students and forest managers, and improvement of
conservation strategies for endangered Equids.

Rubenstein-Sundaresan Doctoral Dissertation Improvement Grant

Individual Behavior and Female Associations in Fission-Fusion Equid
Societies

Animal societies result from the sum of all relationships that develop among
individuals within populations. Many studies have demonstrated how
environmental circumstances, both ecological and social, influence the benefits
and costs associated with the various behavioral options available to
individuals and thus how they these factors structure animal societies. Yet in
species where potential relationships are many and those that form are fluid,
the link between environmental features and the relationships that develop are
poorly understood. This project explores how ecological features, such as the
distribution of food, water and predator-free sites, together with the
demographic and social features, such as population density and sex ratio,
shape individual relationships in the Grevy's zebra and wild ass, two
evolutionarily closely related species exhibiting 'fissioning' and 'fusing'
social systems. We have developed a novel model that predicts rules for the
formation and breakdown of relationships in such 'open-membership' societies
and forecasts the impact these rules will have on population-wide social
patterns and processes. Data will be gathered on two endangered equid species,
Grevy's zebra and Onagers, from four sites. The four sites provide natural
variation in the key environmental and social forces and will serve as an ideal
system for testing the predictions of our model. The study will also provide
useful information needed to improve conservation strategies for these species
by educating students and the local populace and by demonstrating to natural
resource managers how fundamental behavioral research can assist in designing
effective management plans.

This award provides partial support for improvements to the Mpala Research Centre (MRC) that will improve site access and safety. The enhancements include improved access to and safety within the most frequented parts of the landscape, namely, the large-scale exclosure experiments funded by NSF, and the campsite, which provides accommodation for large groups of students on courses, and increasingly, for delegates to workshops with research and conservation themes. It will also provide for sheltered parking for station research vehicles and enhanced rain water collection. Equipment to be purchased will provide enhanced archiving and retrieval of environmental monitoring data, and an updated inventory of satellite imagery of the 22,000 hectare MRC property and of neighboring habitats. The MRC lies at the core of the Ewaso ecosystem, a vast and diverse savanna maintaining prodigious wildlife populations, much of it not formally protected. The Centre is administered as a Trust, in partnership with Trustees that include Princeton University, the Smithsonian Institution, the National Museums of Kenya and the Kenya Wildlife service. Work at the MRC advances research in the environmental, biological, and conservation sciences, and also educates the next generation of environmental scientists by melding classroom learning with practical field experiences. Residential and scientific facilities are available for up to thirty-six scientists and students, including labs equipped for basic DNA analysis. In the last 12 years, more than fifty projects have been conducted at the MRC, including seven NSF funded projects currently underway, and another eight NSF supported projects that have been completed during the last five years. Because MRC has become central to the research and education of Kenyan scientists, including students of all grades and university levels and, as well, non-traditional students who work for governmental agencies, the improvements will continue the efforts of the four trustee organizations that manage the Center to enhance the capabilities of the next generation of scientific leaders world wide.

The goal of the proposed research is to create analytical and computational tools that explicitly address the time and order of social interactions between individuals. The proposed approach combines ideas from social network analysis, Internet computing, distributed computing, and machine learning to solve problems in population biology. The diverse computational tasks of this project include design of algorithmic techniques to identify social entities such as a communities, leaders, and followers, and to use these structures to predict social response patterns to danger or disturbances. Nowhere is the impact of social structure likely to be greater than when species come in
contact with predators. Thus, the accuracy and predictive power of the proposed computational tools will be tested by characterizing the social structure of horses and zebras (equids) both before and after human- or predator-induced perturbations to the social network. The proposed interdisciplinary research will have broader impacts on a wide range of research communities. New methods for analysis of social interactions in animal populations will be useful for behavioral biologists in such diverse fields as behavioral ecology, animal husbandry, conservation biology, and disease ecology. The machine learning algorithms that will be develop are relevant to many studies in which researchers need to classify temporal interaction data. The proposed network methods have broader relevance to human societies: disease transmission, dissemination
of ideas, and social response to crises are all dynamic processes occurring via social networks. Further, through teaching and participation in outreach, students and school teachers will gain access to opportunities for hands-on, interdisciplinary experiences in a new area of computational biology. The research and software resulting from the proposed project will be disseminated both in computational and biological communities and enhanced by cross-disciplinary training activities and will serve to train a new generation of interdisciplinary scientists.

Although male-male bonds are relatively common in male-philopatric primates, evidence for these bonds in species with male dispersal is rare. Despite documentation that male-male bonds have reproductive consequences in this context, little is known about how these bonds develop. Doctoral student Caitlin Barale (Princeton University), under the supervision of Dr. Daniel Rubenstein, investigates the ontogeny of male-male relationships in the gelada (Theropithecus gelada), a species characterized by both male dispersal and male-male bonds. The primary objective of this research is to examine the nature of male-male bonds, and identify the behavioral and hormonal factors that set juvenile gelada males on individual reproductive trajectories as they transition from their natal one-male unit, to a temporary peer group, and onwards into an all-male bachelor group. The project has four specific goals: (1) to describe juvenile peer groups, (2) to characterize male-male bonds in the juvenile period, (3) to evaluate a short-term benefit of these bonds, and (4) to investigate how male relationships change at adrenarche. The investigators employ a combination of cross-sectional and longitudinal behavioral analyses, social network analysis and non-invasive fecal hormone sampling on all juvenile males (N=51) in a band of geladas in the Simien Mountains National Park, Ethiopia.

This research represents the first long-term study focused exclusively on juvenile geladas. It provides a valuable new perspective on gelada social development through the collection of behavioral, physiological and network-based data, and initiates the first longitudinal dataset on known gelada males. Having detailed data on known individuals from juvenility to adulthood allows researchers to connect the effects of early life to lifetime reproductive success. The results of this research will contribute novel data on the development of male-male bonds in primates, advance the application of social network theory to animal systems, and help build a model for social development in early hominins, modern-day humans, and other non-human primates.

Images are rapidly becoming the most abundant, widely available, and cheapest source of information about the natural world. Images taken by field scientists, tourists, and incidental photographers, and gathered from camera traps and autonomous vehicles provide rich data with the promise of addressing big ecological questions at high resolution and at fine-grained scale. Realizing this potential requires building a large autonomous computational system that starts from image collections and progresses all the way to answering ecological queries, such as population sizes, species distributions and interactions, and movement patterns. The system must have methods of extracting the relevant ecological information from the images and of integrating with other ecological data sources, with minimal human interaction, using state-of-the art information management, computer vision, and data analytics technologies. Such a system will advance computer systems and simultaneously enable ecology to develop as a science of connections across spatial, temporal, and biological scales, as well as provide data- and scientifically-grounded support for ecological decisions.

This work aims to build a prototype of an Image-Based Ecological Information Software System (IBEIS) that relies on a proliferation of images collected daily on a single facility from many different sources, both human and automatic, to determine both the species as well as recognition of distinct individuals. The system will allow for tracking location and movement while providing a data management system that will allow scientists to better understand, and at finer granularity, behaviors and motivations. The system will include: (1) an infrastructure and a mechanism for collecting images from tourists and other sources; (2) a (cloud) infrastructure and a data management system for storing, accessing, and manipulating the images and the derived data; (3) computer vision techniques for extracting information from the images about the identity of individual units, as well as techniques for combining that information with other relevant data to derive information about meaningful ecological units; and (4) statistical techniques and query structures to support ecological queries of the data, such as population sizes and dynamics, movement history and home ranges, and species interactions.

This work will advance computer systems including information management, computer vision, and data analytics technologies, all the while increasing public engagement in science and ecology.

The National Ecological Observatory Network (NEON) is coming online and will provide atmospheric and ecological data locally, regionally and continent wide. At the same time, images are rapidly becoming the most abundant, widely available, and cheapest source of information about the natural world, especially about animals. This project will extend NEON's data, scientific, and citizen science capacity with image-based animal sighting data to scalably collect, manage, and analyze data for individually identifiable wildlife using the Image-Based Ecological Information System (IBEIS) prototype recently developed under another NSF award. Combined with other ecological data, the image data offer the promise of addressing big questions about animal ecology, behavior, and conservation - who? where? when? what? and why? - at high resolution and at fine-grained scale, across landscapes and ecosystems, from an individual animal to regional and global systems. As part of this project, undergraduate and graduate students from ecology and computer science at four institutions will produce and test the application interface, and will develop a suite of companion applications and training tools to allow greater involvement of citizen scientists.

These tools will allow NEON to connect its database to data derived from large volumes of animal photographic images. Although this is primarily a proof of concept proposal focused on connecting whale shark images to NEONs atmospheric data, it will provide the means to be able to apply IBEIS algorithms and databases on images of distinctly marked North American species such as tortoises, monarch butterflies, salamanders, spotted skunk, bobcat, lynx, and humpback whales, thereby connecting these to NEON?s other data streams related to organisms, land use, hydrology and biogeochemistry. The proposed suite of tools includes: 1. an infrastructure and a mechanism for collecting images from scientists, automated remote cameras, citizen scientists and other sources; 2. a data management system for storing, accessing and manipulating images and derived data; 3. computer vision techniques for extracting information from the images about the identity of species and individual animals, as well as techniques for combining that information with other relevant data to derive information about ecological units such as animals, populations, species, and habitats; 4. a software application-program interface integrating the image and derived data with and within NEON; 5. a framework for engaging citizen scientists in data collection, derived science, and interaction with nature. Previous funding from NSF allowed building and testing of an IBEIS prototype. This project will focus on the detection and identification methods for the identifiable US species, on integrating the system with NEON, and on scaling the system to many thousands of daily images from a variety of sources.

Non-technical Abstract
Animal groups are remarkable for their ability to interact with the environment in a way that individuals are unable to, such as through migration, collective intelligence, or predator avoidance. For example, predators attacking highly coordinated fish schools have little success due to how efficient information transmission is in the group. The technological challenges of filming and tracking large groups of animals have limited our understanding of how they are so effective at predator avoidance, but recent advances in computer vision and high-speed filming now allow us to accurately recreate these information transmission networks and show how information moves through animal groups. Insights into these networks have put forth predictions that are at odds with long-established hypotheses on where in the group animals are safest: classic behavioral ecology theory suggests the center, while new network data suggests the edge of the group. The research carried out here will for the first time test these competing hypotheses. Live interactions between a northern pike predator and schools of golden shiners will be filmed in the laboratory and then recreated from a sensory network perspective using sophisticated computer vision software to better understand how information is transferred and the ramifications of individual location in the group. The experiment will provide insights into the fields of behavioral ecology, sensory ecology, game theory, and network science. It will provide scientific and statistical training to graduate and undergraduate students, and findings will be disseminated at scientific conferences, through blogging, and through science outreach to local high schools.

Technical Abstract
For decades, Hamilton's Selfish Herd theory has served as the expectation for the spatial distribution of predation risk in animal groups. In this model, cohesive grouping emerges as animals move to position other individuals between themselves and a potential hidden predator, hence minimizing their "domain of danger". Support for this theory has been mixed for mobile animal groups such as fish schools, however, because the Selfish Herd theory does not allow for prey to respond to the predator. Real predator-prey interactions, on the other hand, are dynamic. Until very recently, directly testing Hamilton's Selfish Herd theory in fish schools has been impossible due to technological limitations on the quality and quantity of behavior data. Recent advances in computer vision and high-speed cameras, however, now allow for accurate measures of the fine-scale movements of all members of fish schools, as well as estimations of the visual information available to them. Networks constructed from this visual information are an accurate predictor of how movement decisions transfer through schools of fish. Here research will directly test the non-exclusive hypotheses of whether spatial positioning or network structure is a more accurate predictor of mortality risk by filming predator-prey interactions between golden shiners and a northern pike predator in the laboratory.

Technology is transforming the scale and scope of environmental research. Just as smartphones and social media have transformed the way people interact and acquire their news, breakthroughs in image processing, GPS satellite and wireless animal trackers as well as DNA and stable isotope analytical tools are emboldening scientist to solve old ecological and environmental problems in new ways and to design new studies that ask and answer questions that were inconceivable only a few years ago. At the 22,000 ha Mpala Research Center in central Kenya, US scientists from over a dozen US universities and Institutes supported by 14 NSF and NIH grants, resulting in 197 publications in the last 5 years, study the ecology of a 20,000 Km2 semi-arid ecosystem that sustains the second most diverse array of wildlife in Kenya as well as supporting livelihoods of commercial ranchers, pastoral herders and farmers who share the landscape with this wildlife. It is a model system that supports large scale experiments that are difficult to do within the continental US. Moreover, the Mpala, Research Center, especially with the new modern lab envisioned, continues to serve as an educational laboratory that teaches US undergraduate and graduate students of all ethnicities and walks of life how do real, important, relevant and transformative science. In addition, their interactions with students, faculty and PIs from Kenya and around the world provide a diversity of perspectives that will make them broader scientists able to work within different cultures. In this way, Mpala is training the next generation of environmental leaders, some of whom will practice science, but others of whom will shape science policy.

At Mpala, research generally focuses on the biogeochemistry as well as the population, community and behavioral dynamics of the animals and plants inhabiting the ecosystem. But as strong as the research has been to date, advances in DNA and genetical analytical techniques will transform science, allowing more in depth looks at the diets, the competitive and mutualistic relationships of animal species comprising food webs as well as the population genetics of species spread across expansive spatial and temporal scales. Similar advances in stable isotope analytical tools will enable novel and more detailed investigations into the functioning of the ecosystem, closer examination of water use by plants that drive and limit photosynthesis as well as those of animals that shape their movements, habitat uses and overall decision-making, and the paleoecology of many extinct species, including our human ancestors. These new tools will also provide important insights underlying interactions among wildlife and people, thus helping reduce conflict that accompanies human population growth and expansion. In order to carry out this research, the new analytical tools must be purchased and a new 'clean' building that isolates the equipment form the harsh, dusty and hot tropical climatic elements of central Kenya must be constructed. This new facility will propel the NSF and NIH supported scientists and their students to uncover new rules shaping environmental patterns and processes that were impossible to study before the emergence of these new technological advances. What is learned in Kenya where biodiversity is high and the land is shared between people and wildlife easily applies to similar ecosystems, species and problems found in the western and southwestern states in the US.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.