Dispersal, Philopatry, and the Role of Fissionfusion Dynamics In
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The Influence of Density in Population Dynamics with Strong and Weak Allee Effect
Keya et al. J Egypt Math Soc (2021) 29:4 https://doi.org/10.1186/s42787-021-00114-x Journal of the Egyptian Mathematical Society ORIGINAL RESEARCH Open Access The infuence of density in population dynamics with strong and weak Allee efect Kamrun Nahar Keya1, Md. Kamrujjaman2* and Md. Shafqul Islam3 *Correspondence: [email protected] Abstract 2 Department In this paper, we consider a reaction–difusion model in population dynamics and of Mathematics, University of Dhaka, Dhaka 1000, study the impact of diferent types of Allee efects with logistic growth in the hetero- Bangladesh geneous closed region. For strong Allee efects, usually, species unconditionally die out Full list of author information and an extinction-survival situation occurs when the efect is weak according to the is available at the end of the article resource and sparse functions. In particular, we study the impact of the multiplicative Allee efect in classical difusion when the sparsity is either positive or negative. Nega- tive sparsity implies a weak Allee efect, and the population survives in some domain and diverges otherwise. Positive sparsity gives a strong Allee efect, and the popula- tion extinct without any condition. The infuence of Allee efects on the existence and persistence of positive steady states as well as global bifurcation diagrams is presented. The method of sub-super solutions is used for analyzing equations. The stability condi- tions and the region of positive solutions (multiple solutions may exist) are presented. When the difusion is absent, we consider the model with and without harvesting, which are initial value problems (IVPs) and study the local stability analysis and present bifurcation analysis. -
Comparative Methods Offer Powerful Insights Into Social Evolution in Bees Sarah Kocher, Robert Paxton
Comparative methods offer powerful insights into social evolution in bees Sarah Kocher, Robert Paxton To cite this version: Sarah Kocher, Robert Paxton. Comparative methods offer powerful insights into social evolution in bees. Apidologie, Springer Verlag, 2014, 45 (3), pp.289-305. 10.1007/s13592-014-0268-3. hal- 01234748 HAL Id: hal-01234748 https://hal.archives-ouvertes.fr/hal-01234748 Submitted on 27 Nov 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Apidologie (2014) 45:289–305 Review article * INRA, DIB and Springer-Verlag France, 2014 DOI: 10.1007/s13592-014-0268-3 Comparative methods offer powerful insights into social evolution in bees 1 2 Sarah D. KOCHER , Robert J. PAXTON 1Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA 2Institute for Biology, Martin-Luther-University Halle-Wittenberg, Halle, Germany Received 9 September 2013 – Revised 8 December 2013 – Accepted 2 January 2014 Abstract – Bees are excellent models for studying the evolution of sociality. While most species are solitary, many form social groups. The most complex form of social behavior, eusociality, has arisen independently four times within the bees. -
Interactive Robots in Experimental Biology 3 4 5 6 Jens Krause1,2, Alan F.T
1 2 Interactive Robots in Experimental Biology 3 4 5 6 Jens Krause1,2, Alan F.T. Winfield3 & Jean-Louis Deneubourg4 7 8 9 10 11 12 1Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Department of Biology and 13 Ecology of Fishes, 12587 Berlin, Germany; 14 2Humboldt-University of Berlin, Department for Crop and Animal Sciences, Philippstrasse 15 13, 10115 Berlin, Germany; 16 3Bristol Robotics Laboratory, University of the West of England, Coldharbour Lane, Bristol 17 BS16 1QY, UK; 18 4Unit of Social Ecology, Campus Plaine - CP 231, Université libre de Bruxelles, Bd du 19 Triomphe, B-1050 Brussels - Belgium 20 21 22 23 24 25 26 27 28 Corresponding author: Krause, J. ([email protected]), Leibniz Institute of Freshwater 29 Ecology and Inland Fisheries, Department of the Biology and Ecology of Fishes, 30 Müggelseedamm 310, 12587 Berlin, Germany. 31 32 33 1 33 Interactive robots have the potential to revolutionise the study of social behaviour because 34 they provide a number of methodological advances. In interactions with live animals the 35 behaviour of robots can be standardised, morphology and behaviour can be decoupled (so that 36 different morphologies and behavioural strategies can be combined), behaviour can be 37 manipulated in complex interaction sequences and models of behaviour can be embodied by 38 the robot and thereby be tested. Furthermore, robots can be used as demonstrators in 39 experiments on social learning. The opportunities that robots create for new experimental 40 approaches have far-reaching consequences for research in fields such as mate choice, 41 cooperation, social learning, personality studies and collective behaviour. -
University of Groningen Sociable Schedules Helm, Barbara
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by University of Groningen University of Groningen Sociable schedules Helm, Barbara; Piersma, Theunis; Van der Jeugd, Henk Published in: Animal Behavior DOI: 10.1016/j.anbehav.2005.12.007 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2006 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Helm, B., Piersma, T., & Van der Jeugd, H. (2006). Sociable schedules: interplay between avian seasonal and social behaviour. Animal Behavior, 72(2), 245-262. https://doi.org/10.1016/j.anbehav.2005.12.007 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 12-11-2019 ANIMAL BEHAVIOUR, 2006, 72, 245e262 doi:10.1016/j.anbehav.2005.12.007 REVIEWS Sociable schedules: interplay between avian seasonal and social behaviour BARBARA HELM*,THEUNISPIERSMA†‡ & HENK VAN DER JEUGD†§ *Max Planck Institute for Ornithology yAnimal Ecology Group, Centre for Ecological and Evolutionary Studies zDepartment of Ecology and Evolution, Royal Netherlands Institute for Sea Research (NIOZ) xSOVON Dutch Centre for Field Ornithology (Received 26 June 2004; initial acceptance 15 September 2004; final acceptance 6 December 2005; published online 21 June 2006; MS. -
Breeding Site Fidelity in Southern Elephant Seals of the Falkland Islands
Filippo Galimberti 1 and Simona Sanvito 1,2 1 Elephant Seal Research Group, Sea Lion Island, Falkland Islands 2 Dept. of Biology, Memorial University of Newfoundland, St. John’s NF A1B 3X9, Canada ESRG technical report no. 3 Breeding site fidelity in southern elephant seals of the Falkland Islands Milano, 25th April 2000 © Elephant Seal Research Group – 2000 No part of this report can be cited without written permission from the authors. Address for correspondence: Dr. Filippo Galimberti – Via Buonarroti 35 – 20145 Milano – Italy Phone +39 02 4980504 – Fax +39 02 48008145 – Email [email protected] ABSTRACT Breeding site fidelity, i.e., the tendency to return to the same breeding site for consecutive breeding attempts, is an important component of mammal life history strategies, and seems almost ubiquitous in Pinnipedia species, at least for land breeding ones. Site fidelity may entail significant somatic benefits and costs, and, if coupled with return for first breeding attempt to birth site, may produce a genetic sub-structuring of populations. We present data on female and male site fidelity, together with preliminary information on female phylopatry, of southern elephant seals (Mirounga leonina) of Sea Lion Island, the main breeding site of the species in the Falkland Islands. We found a high level of site fidelity at small scale (hundred of metres) in both sexes, although higher in females, even when considering up to five consecutive breeding seasons of the same individual. We discuss the behavioural and genetic implications of site fidelity, emphasizing that it may affect mating tactics, breeding success, and genetic sub-structuring of local populations. -
Author's Personal Copy
Author's personal copy Provided for non-commercial research and educational use. Not for reproduction, distribution or commercial use. This article was originally published in Encyclopedia of Animal Behavior, published by Elsevier, and the attached copy is provided by Elsevier for the author's benefit and for the benefit of the author's institution, for non-commercial research and educational use including without limitation use in instruction at your institution, sending it to specific colleagues who you know, and providing a copy to your institution's administrator. All other uses, reproduction and distribution, including without limitation commercial reprints, selling or licensing copies or access, or posting on open internet sites, your personal or institution’s website or repository, are prohibited. For exceptions, permission may be sought for such use through Elsevier’s permissions site at: https://www.elsevier.com/about/our-business/policies/copyright/permissions From Shen, S-F., Rubenstein, D.R. (2019). Environmental Uncertainty and Social Behavior. In: Choe, J.C. (Ed.), Encyclopedia of Animal Behavior, (2nd ed.). vol. 4, pp. 807–815. Elsevier, Academic Press. ISBN: 9780128132517 Copyright © 2019 Elsevier Ltd. All rights reserved. Academic Press Author's personal copy Environmental Uncertainty and Social Behavior Sheng-Feng Shen, Biodiversity Research Center, Academia Sinica, Taipei, Taiwan Dustin R Rubenstein, Columbia University, New York, NY, United States © 2019 Elsevier Ltd. All rights reserved. Glossary Cooperative breeding A form of social system in which more than two individuals care for your young. In most cooperatively breeding systems, some mature offspring delay dispersal, remain in their natal social groups, and often “help” raise the their parents’ offspring (their siblings) from subsequent breeding attempts. -
Philopatry and Migration of Pacific White Sharks
Proc. R. Soc. B doi:10.1098/rspb.2009.1155 Published online Philopatry and migration of Pacific white sharks Salvador J. Jorgensen1,*, Carol A. Reeb1, Taylor K. Chapple2, Scot Anderson3, Christopher Perle1, Sean R. Van Sommeran4, Callaghan Fritz-Cope4, Adam C. Brown5, A. Peter Klimley2 and Barbara A. Block1 1Department of Biology, Stanford University, Pacific Grove, CA 93950, USA 2Department of Wildlife, Fish and Conservation Biology, University of California, Davis, CA 95616, USA 3Point Reyes National Seashore, P. O. Box 390, Inverness, California 94937, USA 4Pelagic Shark Research Foundation, Santa Cruz Yacht Harbor, Santa Cruz, CA 95062, USA 5PRBO Conservation Science, 3820 Cypress Drive #11, Petaluma, CA 94954, USA Advances in electronic tagging and genetic research are making it possible to discern population structure for pelagic marine predators once thought to be panmictic. However, reconciling migration patterns and gene flow to define the resolution of discrete population management units remains a major challenge, and a vital conservation priority for threatened species such as oceanic sharks. Many such species have been flagged for international protection, yet effective population assessments and management actions are hindered by lack of knowledge about the geographical extent and size of distinct populations. Combin- ing satellite tagging, passive acoustic monitoring and genetics, we reveal how eastern Pacific white sharks (Carcharodon carcharias) adhere to a highly predictable migratory cycle. Individuals persistently return to the same network of coastal hotspots following distant oceanic migrations and comprise a population genetically distinct from previously identified phylogenetic clades. We hypothesize that this strong homing behaviour has maintained the separation of a northeastern Pacific population following a historical introduction from Australia/New Zealand migrants during the Late Pleistocene. -
Flocks, Herds, and Schools: a Distributed Behavioral Model 1
Published in Computer Graphics, 21(4), July 1987, pp. 25-34. (ACM SIGGRAPH '87 Conference Proceedings, Anaheim, California, July 1987.) Flocks, Herds, and Schools: A Distributed Behavioral Model 1 Craig W. Reynolds Symbolics Graphics Division [obsolete addresses removed 2] Abstract The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle system, with the simulated birds being the particles. The aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course. Each simulated bird is implemented as an independent actor that navigates according to its local perception of the dynamic environment, the laws of simulated physics that rule its motion, and a set of behaviors programmed into it by the "animator." The aggregate motion of the simulated flock is the result of the dense interaction of the relatively simple behaviors of the individual simulated birds. Categories and Subject Descriptors: 1.2.10 [Artificial Intelligence]: Vision and Scene Understanding; 1.3.5 [Computer Graphics]: Computational Geometry and Object Modeling; 1.3.7 [Computer Graphics]: Three Dimensional Graphics and Realism-Animation: 1.6.3 [Simulation and Modeling]: Applications. General Terms: Algorithms, design.b Additional Key Words, and Phrases: flock, herd, school, bird, fish, aggregate motion, particle system, actor, flight, behavioral animation, constraints, path planning. -
The Ecology of Mutualism
Annual Reviews www.annualreviews.org/aronline AngRev. Ecol. Syst. 1982.13:315--47 Copyright©1982 by Annual Reviews lnc. All rightsreserved THE ECOLOGY OF MUTUALISM Douglas 1t. Boucher Departementdes sciences biologiques, Universit~ du Quebec~ Montreal, C. P. 8888, Suet. A, Montreal, Quebec, CanadaH3C 3P8 Sam James Departmentof Ecologyand Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, USA48109 Kathleen H. Keeler School of Life Sciences, University of Nebraska,Lincoln, Nebraska,USA 68588 INTRODUCTION Elementaryecology texts tell us that organismsinteract in three fundamen- tal ways, generally given the namescompetition, predation, and mutualism. The third memberhas gotten short shrift (264), and even its nameis not generally agreed on. Terms that may be considered synonyms,in whole or part, are symbiosis, commensalism,cooperation, protocooperation, mutual aid, facilitation, reciprocal altruism, and entraide. Weuse the term mutual- by University of Kanas-Lawrence & Edwards on 09/26/05. For personal use only. ism, defined as "an interaction betweenspecies that is beneficial to both," Annu. Rev. Ecol. Syst. 1982.13:315-347. Downloaded from arjournals.annualreviews.org since it has both historical priority (311) and general currency. Symbiosis is "the living together of two organismsin close association," and modifiers are used to specify dependenceon the interaction (facultative or obligate) and the range of species that can take part (oligophilic or polyphilic). We make the normal apologies concerning forcing continuous variation and diverse interactions into simple dichotomousclassifications, for these and all subsequentdefinitions. Thus mutualism can be defined, in brief, as a -b/q- interaction, while competition, predation, and eommensalismare respectively -/-, -/q-, and -t-/0. There remains, however,the question of howto define "benefit to the 315 0066-4162/82/1120-0315 $02.00 Annual Reviews www.annualreviews.org/aronline 316 BOUCHER, JAMES & KEELER species" without evoking group selection. -
Dispersal and Gene Flow in a Butterfly with Home Range Behavior: Heliconius Erato (Lepidoptera: Nymphalidae)
Oecologia (Berlin) (1986) 68:210-217 Oecologia Springer-Verlag1986 Dispersal and gene flow in a butterfly with home range behavior: Heliconius erato (Lepidoptera: Nymphalidae) James Mallet Department of Zoology, University of Texas, Austin, TX 78712, USA Summary. Heliconius butterflies have been found to have Endler (1977) and Barton and Hewitt (1981) used measures low rates of dispersal in previous mark-recapture studies, of dispersal to analyse processes in clines and hybrid zones and this lack of movement is due home-range behavior. but came to differing conclusions as to whether divergence An experiment on Heliconius erato was designed to investi- of the hybridizing taxa occurred during a past period of gate movement from the site of pupal eclosion. It was found isolation. Many of these controversies can be traced to inad- that most of the movement occurs before the first capture equate knowledge of natural gene flow. of an individual in a mark-recapture study. After incorpor- Although dispersal and gene flow have never previously ating this early movement, the dispersal parameter, a, is been measured in Heliconius, mark-recapture studies have estimated to be at least 296 m (+_ 30 m jackknifed standard shown low rates of movement. Individuals return daily to error), and the "neighborhood population size", N, is sites for adult and larval hostplants (Turner 1971 a; Ehrlich about 50-150 individuals. These estimates of a and N are and Gilbert 1973; Cook et al. 1976; Mallet and Jackson more than 2 and 5 times larger, respectively, than estimates 1980), and nightly to sites of gregarious roosting (Turner based on standard mark-recapture data, though they are 1971 a; Brown 1981 ; Waller and Gilbert 1982). -
Finding a Mate with Eusocial Skills
Finding a Mate With Eusocial Skills Chris Marriott1 and Jobran Chebib2 1University of Washington, Tacoma, WA, USA 98402 2University of Zurich,¨ Zurich,¨ Switzerland 8057 [email protected] Downloaded from http://direct.mit.edu/isal/proceedings-pdf/alif2016/28/298/1904330/978-0-262-33936-0-ch052.pdf by guest on 30 September 2021 Abstract mutual response of the individuals in the herd with no need for social awareness or exchange of information. Sexual reproductive behavior has a necessary social coordina- Prior work (from now on when we reference the prior tion component as willing and capable partners must both be work we mean the work in Marriott and Chebib (2015a,b)) in the right place at the right time. It has recently been demon- strated that many social organizations that support sexual re- showed that herding, philopatry, and assortative mating production can evolve in the absence of social coordination arose through non-social mechanisms of convergence and between agents (e.g. herding, assortative mating, and natal common descent. This work raised a few questions regard- philopatry). In this paper we explore these results by includ- ing the role that social interaction plays in many of these ob- ing social transfer mechanisms to our agents and contrasting served behaviors. These mating behaviors can be explained their reproductive behavior with a control group without so- cial transfer mechanisms. We conclude that similar behaviors by both non-social and social mechanisms. In many cases emerge in our social learning agents as those that emerged in the non-social solution is the simpler one, though it is likely the non-social learning agents. -
Neural, Parallel, and Scientific Computations 25 (2017) 149-164 DYNAMICS of a SYMBIOTIC MODEL with HERD BEHAVIOUR and STRONG
Neural, Parallel, and Scientific Computations 25 (2017) 149-164 DYNAMICS OF A SYMBIOTIC MODEL WITH HERD BEHAVIOUR AND STRONG ALLEE EFFECT PROSENJIT SEN, ALAKES MAITI, AND G. P. SAMANTA Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah - 711 103, India, E-mail: [email protected] Department of Mathematics, Vidyasagar Evening College, Kolkata – 700006, India, E-mail: alakesh [email protected] Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah - 711 103, India, E-mail: g p [email protected], [email protected] ABSTRACT. In this paper we will consider the Allee effect on a symbiotic population system with herd behaviour. Criteria for stability of equilibrium points are derived. The effect of discrete time-delay on the model is investigated. Computer simulation of various solutions is presented to illustrate our mathematical findings. The biological implications of our analytical and numerical findings are discussed critically. Key Words Symbiotic model, Herd, Allee effect, Stability, Time-delay. 1. INTRODUCTION Symbiotic relationship is a most widespread phenomenon that is very common in nature. In this relationship, the organisms live together and influence their mutual livelihoods. Symbiotic relationship may be obligate or facultative. In obligate sym- biosis, two organisms cannot survive without each other. In facultative symbiosis, the species live together by choice. So far as the growth of a single-species population is concerned, it has long been recognised that the famous logistic growth function is a logical choice. The function is introduced in 1838 by the Belgian mathematician Pierre Francois Verhulst [42] and later it is rediscovered in 1920 by American biologists Reymon Pearl and Lowell Reed [36].