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Assessment of Population Density and Structure of Primates in Pandam Wildlife Park, Plateau State, Nigeria
Sustainability, Agri, Food and Environmental Research, (ISSN: 0719-3726) , 6(2), 2018: 18-35 18 http://dx.doi.org/10.7770/safer-V6N2-art1503 ASSESSMENT OF POPULATION DENSITY AND STRUCTURE OF PRIMATES IN PANDAM WILDLIFE PARK, PLATEAU STATE, NIGERIA DENSIDAD POBLACIONAL Y ESTRUCTURA DE PRIMATES DIURNOS EN EL PARQUE DE VIDA SILVESTRE EN PANDAM, ESTADO DE PLATEAU, NIGERIA. Gabriel Ortyom Yager*, James Oshita Bukie and Avalumun Emmanuel Kaa, Department of Wildlife and Range Management, University of Agriculture, Makurdi, Benue State, Nigeria. *Correspondent author email & Phone: [email protected]; 08150609846 ABSTRACT A survey of diurnal primate species in Pandam Wildlife Park, Nigeria was conducted to determine its population density and structure. Eight transect lines (2.0km length, 0.02km width) at interval of 1.0km were located as representative samples in the Park within the Three-range stratum (riparian forest, savannah woodland and, swampy area) based on proportional to size of the strata in providing information on the primates’ species present in the Park which include Cercopithecus mona, Erythrocebus patas, Papio anubis and, Chlorocebus tantalus. Direct method of animal sighting was employed. Data was collected and analyzed using descriptive statistics, ANOVA and diversity indices. The results showed that savannah woodland strata had more number of individual species encountered (132) and the lowest was the swampy area. Also the savannah woodland had the highest species diversity and richness while the riparian forest strata had the highest number of species evenness. More so, Cercopithecus tantalus was widespread throughout the Park among other primates and Cercopithecus mona is most likely to decline even more rapidly than others since they inhabit the very tall trees. -
Swarm Intelligence
Swarm Intelligence Leen-Kiat Soh Computer Science & Engineering University of Nebraska Lincoln, NE 68588-0115 [email protected] http://www.cse.unl.edu/agents Introduction • Swarm intelligence was originally used in the context of cellular robotic systems to describe the self-organization of simple mechanical agents through nearest-neighbor interaction • It was later extended to include “any attempt to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies and other animal societies” • This includes the behaviors of certain ants, honeybees, wasps, cockroaches, beetles, caterpillars, and termites Introduction 2 • Many aspects of the collective activities of social insects, such as ants, are self-organizing • Complex group behavior emerges from the interactions of individuals who exhibit simple behaviors by themselves: finding food and building a nest • Self-organization come about from interactions based entirely on local information • Local decisions, global coherence • Emergent behaviors, self-organization Videos • https://www.youtube.com/watch?v=dDsmbwOrHJs • https://www.youtube.com/watch?v=QbUPfMXXQIY • https://www.youtube.com/watch?v=M028vafB0l8 Why Not Centralized Approach? • Requires that each agent interacts with every other agent • Do not possess (environmental) obstacle avoidance capabilities • Lead to irregular fragmentation and/or collapse • Unbounded (externally predetermined) forces are used for collision avoidance • Do not possess distributed tracking (or migration) -
The Behavioral Ecology of the Tibetan Macaque
Fascinating Life Sciences Jin-Hua Li · Lixing Sun Peter M. Kappeler Editors The Behavioral Ecology of the Tibetan Macaque Fascinating Life Sciences This interdisciplinary series brings together the most essential and captivating topics in the life sciences. They range from the plant sciences to zoology, from the microbiome to macrobiome, and from basic biology to biotechnology. The series not only highlights fascinating research; it also discusses major challenges associ- ated with the life sciences and related disciplines and outlines future research directions. Individual volumes provide in-depth information, are richly illustrated with photographs, illustrations, and maps, and feature suggestions for further reading or glossaries where appropriate. Interested researchers in all areas of the life sciences, as well as biology enthu- siasts, will find the series’ interdisciplinary focus and highly readable volumes especially appealing. More information about this series at http://www.springer.com/series/15408 Jin-Hua Li • Lixing Sun • Peter M. Kappeler Editors The Behavioral Ecology of the Tibetan Macaque Editors Jin-Hua Li Lixing Sun School of Resources Department of Biological Sciences, Primate and Environmental Engineering Behavior and Ecology Program Anhui University Central Washington University Hefei, Anhui, China Ellensburg, WA, USA International Collaborative Research Center for Huangshan Biodiversity and Tibetan Macaque Behavioral Ecology Anhui, China School of Life Sciences Hefei Normal University Hefei, Anhui, China Peter M. Kappeler Behavioral Ecology and Sociobiology Unit, German Primate Center Leibniz Institute for Primate Research Göttingen, Germany Department of Anthropology/Sociobiology University of Göttingen Göttingen, Germany ISSN 2509-6745 ISSN 2509-6753 (electronic) Fascinating Life Sciences ISBN 978-3-030-27919-6 ISBN 978-3-030-27920-2 (eBook) https://doi.org/10.1007/978-3-030-27920-2 This book is an open access publication. -
Dietary Adaptations of Assamese Macaques (Macaca Assamensis) in Limestone Forests in Southwest China
American Journal of Primatology 77:171–185 (2015) RESEARCH ARTICLE Dietary Adaptations of Assamese Macaques (Macaca assamensis)in Limestone Forests in Southwest China ZHONGHAO HUANG1,2, CHENGMING HUANG3, CHUANGBIN TANG4, LIBIN HUANG2, 5 1,6 2 HUAXING TANG , GUANGZHI MA *, AND QIHAI ZHOU ** 1School of Life Sciences, South China Normal University, Guangzhou, China 2Guangxi Key Laboratory of Rare and Endangered Animal Ecology, Guangxi Normal University, Guilin, China 3National Zoological Museum, Institute of Zoology, Chinese Academy of Sciences, Beijing, China 4College of Forest Resources and Environment, Nanjing Forestry University, Nanjing, China 5The Administration of Nonggang Nature Reserve, Chongzuo, China 6Guangdong Institute of Science and Technology, Zhuhai, China Limestone hills are an unusual habitat for primates, prompting them to evolve specific behavioral adaptations to the component karst habitat. From September 2012 to August 2013, we collected data on the diet of one group of Assamese macaques living in limestone forests at Nonggang National Nature Reserve, Guangxi Province, China, using instantaneous scan sampling. Assamese macaques were primarily folivorous, young leaves accounting for 75.5% and mature leaves an additional 1.8% of their diet. In contrast, fruit accounted for only 20.1%. The young leaves of Bonia saxatilis, a shrubby, karst‐ endemic bamboo that is superabundant in limestone hills, comprised the bulk of the average monthly diet. Moreover, macaques consumed significantly more bamboo leaves during the season when the availability of fruit declined, suggesting that bamboo leaves are an important fallback food for Assamese macaques in limestone forests. In addition, diet composition varied seasonally. The monkeys consumed significantly more fruit and fewer young leaves in the fruit‐rich season than in the fruit‐lean season. -
The Copulatory Behaviour of Adult Male Patas Monkeys
THE COPULATORY BEHAVIOUR OF ADULT MALE PATAS MONKEYS, ERYTHROCEBUS PATAS JAMES LOY Department of Sociology and Anthropology, University of Rhode Island, Kingston, Rhode Island 02881, U.S.A. (Received 22nd February 1975) The present observations of the reproductive behaviour of adult male patas monkeys (Erythrocebus patas) suggest that these primates typically copulate during a single mount unless they experience difficulty achieving intromission and/or they are harassed by conspecifics. These observations are in contrast to the report by Hall et al. (1965), who described a patas male who copulated in a series of mounts, i.e. behaviour similar to that of males of several macaque species (Bielert & Goy, 1973; Nadler & Rosenblum, 1973). The patas monkey group observed during the present study was maintained in a \m=1/2\acre outdoor corral at the primate colony at La Parguera, Puerto Rico, a facility of the Caribbean Primate Research Center. The monkeys were pro- vided with an unlimited supply of Wayne Monkey Diet and water. Behavioural observations were made from November 1971 until June 1974 for a total of 781 hr. The original social group consisted of a single adult male (A), eight adult females, two immature males and two immature females. All of the monkeys were thought to be of East African origin. During the spring of 1972, Male A was replaced by adult Male LI73; this switch was necessitated because of repeated attacks on the colony staff by Male A. The birthplace of Male LI 73 was not known. In addition to the copulatory behaviour of Males LI73 and A, some data from adult Male I are included. -
Migration and Conservation: Frameworks, Gaps, and Synergies in Science, Law, and Management
GAL.MERETSKY.DOC 5/31/2011 6:00 PM MIGRATION AND CONSERVATION: FRAMEWORKS, GAPS, AND SYNERGIES IN SCIENCE, LAW, AND MANAGEMENT BY VICKY J. MERETSKY,* JONATHAN W. ATWELL** & JEFFREY B. HYMAN*** Migratory animals provide unique spectacles of cultural, ecological, and economic importance. However, the process of migration is a source of risk for migratory species as human actions increasingly destroy and fragment habitat, create obstacles to migration, and increase mortality along the migration corridor. As a result, many migratory species are declining in numbers. In the United States, the Endangered Species Act provides some protection against extinction for such species, but no protection until numbers are severely reduced, and no guarantee of recovery to population levels associated with cultural, ecological, or economic significance. Although groups of species receive some protection from statutes such as the Migratory Bird Treaty Act and Marine Mammal Protection Act, there is no coordinated system for conservation of migratory species. In addition, information needed to protect migratory species is often lacking, limiting options for land and wildlife managers who seek to support these species. In this Article, we outline the existing scientific, legal, and management information and approaches to migratory species. Our objective is to assess present capacity to protect the species and the phenomenon of migration, and we argue that all three disciplines are necessary for effective conservation. We find significant capacity to support conservation in all three disciplines, but no organization around conservation of migration within any discipline or among the three disciplines. Areas of synergy exist among the disciplines but not as a result of any attempt for coordination. -
Swarm Intelligence for Multiobjective Optimization of Extraction Process
Swarm Intelligence for Multiobjective Optimization of Extraction Process T. Ganesan* Department of Chemical Engineering, Universiti Technologi Petronas, 31750 Tronoh, Perak, Malaysia *email: [email protected] I. Elamvazuthi Department of Electrical & Electronics Engineering, Universiti Technologi Petronas, 31750 Tronoh, Perak, Malaysia P. Vasant Department of Fundamental & Applied Sciences, Universiti Technologi Petronas, 31750 Tronoh, Perak, Malaysia ABSTRACT Multi objective (MO) optimization is an emerging field which is increasingly being implemented in many industries globally. In this work, the MO optimization of the extraction process of bioactive compounds from the Gardenia Jasminoides Ellis fruit was solved. Three swarm-based algorithms have been applied in conjunction with normal-boundary intersection (NBI) method to solve this MO problem. The gravitational search algorithm (GSA) and the particle swarm optimization (PSO) technique were implemented in this work. In addition, a novel Hopfield-enhanced particle swarm optimization was developed and applied to the extraction problem. By measuring the levels of dominance, the optimality of the approximate Pareto frontiers produced by all the algorithms were gauged and compared. Besides, by measuring the levels of convergence of the frontier, some understanding regarding the structure of the objective space in terms of its relation to the level of frontier dominance is uncovered. Detail comparative studies were conducted on all the algorithms employed and developed in this work. -
The Consequences of Habitat Loss and Fragmentation on the Distribution, Population Size, Habitat Preferences, Feeding and Rangin
The consequences of habitat loss and fragmentation on the distribution, population size, habitat preferences, feeding and ranging Ecology of grivet monkey (Cercopithecus aethiopes aethiops) on the human dominated habitats of north Shoa, Amhara, Ethiopia: A Study of human-grivet monkey conflict 1 Table of contents Page 1. Introduction 1 1.1. Background And Justifications 3 1.2. Statement Of The Problem 6 1.3. Objectives 7 1.3.1. General Objective 7 1.3.2. Specific Objectives 8 1.4. Research Hypotheses Under Investigation 8 2. Description Of The Study Area 8 3. Methodology 11 3.1. Habitat Stratification, Vegetation Mapping And Land Use Cover 11 Change 3.2. Distribution Pattern And Population Estimate Of Grivet Monkey 11 3.3. Behavioral Data 12 3.4. Human Grivet Monkey Conflict 15 3.5. Habitat Loss And Fragmentation 15 4. Expected Output 16 5. Challenges Of The Project 16 6. References 17 i 1. Introduction World mammals status analysis on global scale shows that primates are the most threatened mammals (Schipper et al., 2008) making them indicators for investigating vulnerability to threats. Habitat loss and destruction are often considered to be the most serious threat to many tropical primate populations because of agricultural expansion, livestock grazing, logging, and human settlement (Cowlishaw and Dunbar, 2000). Deforestation and forest fragmentation have marched together with the expansion of agricultural frontiers, resulting in both habitat loss and subdivision of the remaining habitat (Michalski and Peres, 2005). This forest degradation results in reduction in size or fragmentation of the original forest habitat (Fahrig, 2003). Habitat fragmentation is often defined as a process during which “a large expanse of habitat is transformed into a number of smaller patches of smaller total area, isolated from each other by a matrix of habitats unlike the original”. -
Swarm Intelligence
Swarm Intelligence CompSci 760 Patricia J Riddle 8/20/12 760 swarm 1 Swarm Intelligence Swarm intelligence (SI) is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. ! 8/20/12 760 swarm 2 Main Focus collective behaviors that result from the ! ! local interactions of the individuals with ! ! each other and/or with ! ! their environment.! 8/20/12 760 swarm 3 Examples colonies of ants and termites, ! schools of fish, ! flocks of birds, ! bacterial growth,! herds of land animals. ! ! Artificial Systems:! some multi-robot systems! ! certain computer programs that are written to tackle optimization and data analysis problems! 8/20/12 760 swarm 4 Simple Local Rules agents follow very simple local rules! ! no centralized control structure dictating how individual agents should behave! ! local interactions between agents lead to the emergence of complex global behavior.! 8/20/12 760 swarm 5 Emergence emergence - the way complex systems and patterns arise out of a many simple interactions ! ! A complex system is composed of interconnected parts that as a whole exhibit one or more properties (behavior among the possible properties) not obvious from the properties of the individual parts! ! Classic Example: Life! ! 8/20/12 760 swarm 6 Taxonomy of Emergence Emergence may be generally divided into two perspectives, ! "weak emergence" and ! "strong emergence". ! 8/20/12 760 swarm 7 Weak Emergence new properties arising in systems as a result of the -
Journal of Threatened Taxa
The Journal of Threatened Taxa (JoTT) is dedicated to building evidence for conservaton globally by publishing peer-reviewed artcles OPEN ACCESS online every month at a reasonably rapid rate at www.threatenedtaxa.org. All artcles published in JoTT are registered under Creatve Commons Atributon 4.0 Internatonal License unless otherwise mentoned. JoTT allows unrestricted use, reproducton, and distributon of artcles in any medium by providing adequate credit to the author(s) and the source of publicaton. Journal of Threatened Taxa Building evidence for conservaton globally www.threatenedtaxa.org ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print) Communication First record of interspecies grooming between Raffles’ Banded Langur and Long-tailed Macaque Zan Hui Lee, Andie Ang & Nadine Ruppert 26 August 2021 | Vol. 13 | No. 9 | Pages: 19246–19253 DOI: 10.11609/jot.7510.13.9.19246-19253 For Focus, Scope, Aims, and Policies, visit htps://threatenedtaxa.org/index.php/JoTT/aims_scope For Artcle Submission Guidelines, visit htps://threatenedtaxa.org/index.php/JoTT/about/submissions For Policies against Scientfc Misconduct, visit htps://threatenedtaxa.org/index.php/JoTT/policies_various For reprints, contact <[email protected]> The opinions expressed by the authors do not refect the views of the Journal of Threatened Taxa, Wildlife Informaton Liaison Development Society, Zoo Outreach Organizaton, or any of the partners. The journal, the publisher, the host, and the part- Publisher & Host ners are not responsible for the accuracy of the politcal -
An Introduction to Swarm Intelligence Issues
An Introduction to Swarm Intelligence Issues Gianni Di Caro [email protected] IDSIA, USI/SUPSI, Lugano (CH) 1 Topics that will be discussed Basic ideas behind the notion of Swarm Intelligence The role of Nature as source of examples and ideas to design new algorithms and multi-agent systems From observations to models and to algorithms Self-organized collective behaviors The role of space and communication to obtain self-organization Social communication and stigmergic communication Main algorithmic frameworks based on the notion of Swarm Intelligence: Collective Intelligence, Particle Swarm Optimization, Ant Colony Optimization Computational complexity, NP-hardness and the need of (meta)heuristics Some popular metaheuristics for combinatorial optimization tasks 2 Swarm Intelligence: what’s this? Swarm Intelligence indicates a recent computational and behavioral metaphor for solving distributed problems that originally took its inspiration from the biological examples provided by social insects (ants, termites, bees, wasps) and by swarming, flocking, herding behaviors in vertebrates. Any attempt to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insects and other animal societies. [Bonabeau, Dorigo and Theraulaz, 1999] . however, we don’t really need to “stick” on examples from Nature, whose constraints and targets might differ profoundly from those of our environments of interest . 3 Where does it come from? Nest building in termite or honeybee societies Foraging in ant colonies Fish schooling Bird flocking . 4 Nature’s examples of SI Fish schooling ( c CORO, CalTech) 5 Nature’s examples of SI (2) Birds flocking in V-formation ( c CORO, Caltech) 6 Nature’s examples of SI (3) Termites’ nest ( c Masson) 7 Nature’s examples of SI (4) Bees’ comb ( c S. -
Expert Assessment of Stigmergy: a Report for the Department of National Defence
Expert Assessment of Stigmergy: A Report for the Department of National Defence Contract No. W7714-040899/003/SV File No. 011 sv.W7714-040899 Client Reference No.: W7714-4-0899 Requisition No. W7714-040899 Contact Info. Tony White Associate Professor School of Computer Science Room 5302 Herzberg Building Carleton University 1125 Colonel By Drive Ottawa, Ontario K1S 5B6 (Office) 613-520-2600 x2208 (Cell) 613-612-2708 [email protected] http://www.scs.carleton.ca/~arpwhite Expert Assessment of Stigmergy Abstract This report describes the current state of research in the area known as Swarm Intelligence. Swarm Intelligence relies upon stigmergic principles in order to solve complex problems using only simple agents. Swarm Intelligence has been receiving increasing attention over the last 10 years as a result of the acknowledgement of the success of social insect systems in solving complex problems without the need for central control or global information. In swarm- based problem solving, a solution emerges as a result of the collective action of the members of the swarm, often using principles of communication known as stigmergy. The individual behaviours of swarm members do not indicate the nature of the emergent collective behaviour and the solution process is generally very robust to the loss of individual swarm members. This report describes the general principles for swarm-based problem solving, the way in which stigmergy is employed, and presents a number of high level algorithms that have proven utility in solving hard optimization and control problems. Useful tools for the modelling and investigation of swarm-based systems are then briefly described.