Winter Flocking Behaviour of Speckled Warblers and the Allee Effect
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Disaggregation of Bird Families Listed on Cms Appendix Ii
Convention on the Conservation of Migratory Species of Wild Animals 2nd Meeting of the Sessional Committee of the CMS Scientific Council (ScC-SC2) Bonn, Germany, 10 – 14 July 2017 UNEP/CMS/ScC-SC2/Inf.3 DISAGGREGATION OF BIRD FAMILIES LISTED ON CMS APPENDIX II (Prepared by the Appointed Councillors for Birds) Summary: The first meeting of the Sessional Committee of the Scientific Council identified the adoption of a new standard reference for avian taxonomy as an opportunity to disaggregate the higher-level taxa listed on Appendix II and to identify those that are considered to be migratory species and that have an unfavourable conservation status. The current paper presents an initial analysis of the higher-level disaggregation using the Handbook of the Birds of the World/BirdLife International Illustrated Checklist of the Birds of the World Volumes 1 and 2 taxonomy, and identifies the challenges in completing the analysis to identify all of the migratory species and the corresponding Range States. The document has been prepared by the COP Appointed Scientific Councilors for Birds. This is a supplementary paper to COP document UNEP/CMS/COP12/Doc.25.3 on Taxonomy and Nomenclature UNEP/CMS/ScC-Sc2/Inf.3 DISAGGREGATION OF BIRD FAMILIES LISTED ON CMS APPENDIX II 1. Through Resolution 11.19, the Conference of Parties adopted as the standard reference for bird taxonomy and nomenclature for Non-Passerine species the Handbook of the Birds of the World/BirdLife International Illustrated Checklist of the Birds of the World, Volume 1: Non-Passerines, by Josep del Hoyo and Nigel J. Collar (2014); 2. -
DRAFT Biodiversity Action Plan 2021 - 2026
DRAFT Biodiversity Action Plan 2021 - 2026 Prepared by: Infrastructure Services & Planning and Ecology Australia Contents Acknowledgments 4 A Vision for the Future 5 Introduction 6 Summary of state and extent of biodiversity in Greater Dandenong 7 Study area 7 Flora and fauna 9 Existing landscape habitat types 10 Key threats to local biodiversity values 12 Habitat assessments 15 Habitat connectivity for icon species 16 Community consultation and engagement 18 Biodiversity legislation considerations 20 Council strategies 22 Actions 23 Protection and enhancement of existing biodiversity values 24 Improving knowledge of biodiversity values 26 Facilitating and encouraging biodiversity conservation and enhancement on private land 27 Managing threatening processes 28 Community engagement and education 30 References 32 Tables Table 1 Summary of most common reasons why biodiversity is considered important from online survey and examples of comments provided 19 Table 2 Commonwealth and Victorian biodiversity legislation 20 Plates Plate 1 City of Greater Dandenong LGA and municipality study area, including surrounding areas of biodiversity significance. 8 Plate 2 Potential connectivity sites within Greater Dandenong for all five icon species 17 DRAFT City of Greater Dandenong Biodiversity Action Plan 2021 – 2026 ii Appendices Appendix 1 Vegetation coverage across the City of Greater Dandenong pre 1750 (left) and today (right). 34 Appendix 2 Fauna species listed as threatened under the EPBC Act 1999 (DAWE 2020), FFG Act 1988 (DELWP 2019b) or the Victorian Threatened Species Advisory List recorded within the City of Greater Dandenong municipality ....................................................................................................... 35 Appendix 3 Flora species listed as threatened under the EPBC Act 1999 (DAWE 2020), FFG Act 1988 (DELWP 2019b) or the Victorian Threatened Species Advisory List recorded within the City of Greater Dandenong municipality ...................................................................................................... -
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. -
Malte Andersson 30.10.2019
Social evolution, and levels of selection Malte Andersson 30.10.2019 1 Social evolution, Malte Andersson, 30.10. 2019 Fitness: an individual’s expected genetic contribution to the next generation Direct fitness: numbers of surviving own offspring A behaviour leading to higher fitness is favored by selection and will spread over the generations 2 1 Mobbing a raptor is risky for a crow 3 A honey bee dies after stinging an enemy 4 2 Costly helping: how can it evolve and persist? Does it benefit the donor of help via: 1) direct fitness (individual selection) ? 2) delayed direct fitness, by reciprocity ? 3) donor’s relatives: kin selection ? 4) a larger community: group selection ? These questions are debated. They were first asked by Darwin (1859), about sterile workers in eusocial insects. Some individuals can not reproduce, but offer their lives for the colony (for instance honey bee workers). Can natural selection lead to such behaviour? 5 Altruism (meaning in ecology): Helpful behavior that raises the recipient’s but lowers the donor’s direct fitness 6 3 Alarm signals - selfish or altruistic? Black-throated Shrike-Tanager, Springbok stotting, Kalahari Belize Stotting tells a predator it is detected Warning flock members, also using by a gazelle in good condition. Better the signal for own feeding advantage to hunt another prey (Caro 1986) 7 Is sentinel behavior in meerkats altruistic? Probably not. Sentinels are safer and have a direct benefit from their behavior. (Clutton-Brock et al. 1999) 8 4 0.5 0.4 0.3 Females 0.2 Males 0.1 0 Without close With With offspring genetic relatives nondescendant relatives Black-tailed prairie dogs Individuals give alarm calls mainly with relatives (offspring and others). -
Animating Predator and Prey Fish Interactions
Georgia State University ScholarWorks @ Georgia State University Computer Science Dissertations Department of Computer Science 5-6-2019 Animating Predator and Prey Fish Interactions Sahithi Podila Follow this and additional works at: https://scholarworks.gsu.edu/cs_diss Recommended Citation Podila, Sahithi, "Animating Predator and Prey Fish Interactions." Dissertation, Georgia State University, 2019. https://scholarworks.gsu.edu/cs_diss/149 This Dissertation is brought to you for free and open access by the Department of Computer Science at ScholarWorks @ Georgia State University. It has been accepted for inclusion in Computer Science Dissertations by an authorized administrator of ScholarWorks @ Georgia State University. For more information, please contact [email protected]. ANIMATING PREDATOR AND PREY FISH INTERACTIONS by SAHITHI PODILA Under the Direction of Ying Zhu, PhD ABSTRACT Schooling behavior is one of the most salient social and group activities among fish. They form schools for social reasons like foraging, mating and escaping from predators. Animating a school of fish is difficult because they are large in number, often swim in distinctive patterns that is they take the shape of long thin lines, squares, ovals or amoeboid and exhibit complex coordinated patterns especially when they are attacked by a predator. Previous work in computer graphics has not provided satisfactory models to simulate the many distinctive interactions between a school of prey fish and their predator, how does a predator pick its target? and how does a school of fish react to such attacks? This dissertation presents a method to simulate interactions between prey fish and predator fish in the 3D world based on the biological research findings. -
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. -
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. -
Basic Hunting Booklet
Basic Hunting Passing on a time-honored tradition Kentucky Department of Fish and Wildlife Resources From the Commissioner. The North American Model of Wildlife Management depends on hunters. This model incorporates principles of conservation from the past 100 years and was formally adopted in 2002. Over the years the number of hunters has decreased. Fish and Wildlife agencies from across the nation view this as a major problem. Many factors contrib- ute to this decline, including habitat loss, a growing urban population, and increased competition for leisure time. We do have one key ele- ment upon which we can rely: the people who enjoy the opportunity to step outside and enjoy shooting and hunting. Kentucky’s Department of Fish and Wildlife Resources has worked for several decades to give the shooter and hunter every pos- sible opportunity. We have developed shooting ranges, assisted land- owners in improving habitat, and enhanced the quality of the hunt for numerous species. In addition, we strive to provide Wildlife Manage- ment Areas for public use. In fact, the amount of land the department manages has more than doubled in the last 10 years. You and your family and friends are essential to the future of hunting. Each new hunter must have consistent support to continue to grow and expand his or her interest. I think you will find this expe- rience extremely rewarding for everyone involved. In a tribute to his father, Alan Jackson stated in a song about boating that it was “…a piece of my childhood that will never be forgotten.” I feel your involve- ment in hunting with your friends and family will fall in that “special memory” category. -
Interaction Ruling Animal Collective Behavior Depends on Topological Rather Than Metric Distance: Evidence from a Field Study
Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study M. Ballerini*†, N. Cabibbo‡§, R. Candelier‡¶, A. Cavagna*ʈ**, E. Cisbani†, I. Giardina*ʈ, V. Lecomte††‡‡, A. Orlandi*, G. Parisi*‡§**, A. Procaccini*‡, and M. Viale‡§§, and V. Zdravkovic* *Centre for Statistical Mechanics and Complexity (SMC), Consiglio Nazionale delle Ricerche-Istituto Nazionale per la Fisica della Materia, ‡Dipartimento di Fisica, and §Sezione Instituto Nazionale di Fisica Nucleare, Universita’ di Roma ‘‘La Sapienza,’’ Piazzale Aldo Moro 2, 00185 Roma, Italy; †Istituto Superiore di Sanita’, viale Regina Elena 299, 00161 Roma, Italy; ʈIstituto dei Sistemi Complessi (ISC), Consiglio Nazionale delle Ricerche, via dei Taurini 19, 00185 Roma, Italy; and ††Laboratoire Matie`re et Syste`mes Complexes, (Centre National de la Recherche Scientifique Unite Mixte de Recherche 7057), Universite´Paris VII, 10 rue Alice Domon et Le´onie Duquet, 75205 Paris Cedex 13, France Contributed by G. Parisi, December 4, 2007 (sent for review September 25, 2007) Numerical models indicate that collective animal behavior may no bird remains isolated, and soon the flock reforms as whole. emerge from simple local rules of interaction among the individ- The question we want to answer is ‘‘what kind of interaction uals. However, very little is known about the nature of such maintains cohesion in such a robust way?’’ interaction, so that models and theories mostly rely on aprioristic To grant cohesion, models make the sound assumption that assumptions. By reconstructing the three-dimensional positions of individuals align and attract each other, and that such interaction individual birds in airborne flocks of a few thousand members, we decays with increasing distance between individuals. -
Predictors of Nomadism in Birds of an Australian Mediterraneanclimate Ecosystem
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Nebraska Cooperative Fish & Wildlife Research Nebraska Cooperative Fish & Wildlife Research Unit -- Staff Publications Unit 2002 Variability between Scales: Predictors of Nomadism in Birds of an Australian Mediterraneanclimate Ecosystem Craig R. Allen U.S. Geological Survey, [email protected] Denis A. Saunders Clemson University Follow this and additional works at: https://digitalcommons.unl.edu/ncfwrustaff Part of the Other Environmental Sciences Commons Allen, Craig R. and Saunders, Denis A., "Variability between Scales: Predictors of Nomadism in Birds of an Australian Mediterraneanclimate Ecosystem" (2002). Nebraska Cooperative Fish & Wildlife Research Unit -- Staff Publications. 23. https://digitalcommons.unl.edu/ncfwrustaff/23 This Article is brought to you for free and open access by the Nebraska Cooperative Fish & Wildlife Research Unit at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Nebraska Cooperative Fish & Wildlife Research Unit -- Staff Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Ecosystems (2002) 5: 348–359 DOI: 10.1007/s10021-001-0079-2 ECOSYSTEMS © 2002 Springer-Verlag Variability between Scales: Predictors of Nomadism in Birds of an Australian Mediterranean- climate Ecosystem Craig R. Allen1* and Denis A. Saunders2 1US Geological Survey, Biological Resources Division, South Carolina Cooperative Fish and Wildlife Research Unit, G27 Lehotsky, Clemson University, Clemson, South Carolina 29634, USA; and 2CSIRO Sustainable Ecosystems, GPO Box 284, Canberra ACT 2601, Australia ABSTRACT Nomadism in animals is a response to resource dis- cance of the variables body mass and diet (nectar) tributions that are highly variable in time and space. may reflect the greater energy requirements of Using the avian fauna of the Mediterranean-climate large birds and the inherent variability of nectar as region of southcentral Australia, we tested a num- a food source. -
Stigmergy As a Universal Coordination Mechanism: Components, Varieties and Applications
to appear in T. Lewis & L. Marsh (Eds.), Human Stigmergy: Theoretical Developments and New Applications. Springer. Stigmergy as a Universal Coordination Mechanism: components, varieties and applications Francis Heylighen Evolution, Complexity and Cognition group Vrije Universiteit Brussel Abstract: The concept of stigmergy has been used to analyze self-organizing activities in an ever-widening range of domains, including social insects, robotics, web communities, and human society. Yet, it is still poorly understood, and as such its full power remains underappreciated. The present paper clarifies the issue by defining stigmergy as a mechanism of indirect coordination in which the trace left by an action in a medium stimulates a subsequent action. It then analyses the fundamental concepts used in the definition: action, agent, medium, trace and coordination. Stigmergy enables complex, coordinated activity without any need for planning, control, communication, simultaneous presence, or even mutual awareness. This makes the concept applicable to a very broad variety of cases, from chemical reactions to individual cognition and Internet-supported collaboration in Wikipedia. The paper classifies different varieties of stigmergy according to general aspects (number of agents, scope, persistence, sematectonic vs. marker-based, and quantitative vs. qualitative), while emphasizing the fundamental continuity between these cases. This continuity can be understood from a non-linear dynamics that lets more complex forms of coordination evolve out of simpler ones. The paper concludes with two specifically human applications, cognition and cooperation, suggesting that without stigmergy these phenomena may never have evolved in the first place. Past, present and future of the “stigmergy” concept The concept of stigmergy was introduced by the French entomologist Pierre-Paul Grassé (Grassé, 1959) to describe a mechanism of coordination used by insects. -
Diffusion of Individual Birds in Starling Flocks
Diffusion of individual birds in starling flocks A. Cavagna♯,♭, S. M. Duarte Queir´os♯, I. Giardina♯,♭, F. Stefanini† and M. Viale♯,♭ ♯ Istituto dei Sistemi Complessi, UOS Sapienza, CNR, via dei Taurini 19, 00185 Roma, Italy ♭ Dipartimento di Fisica, Universit`aSapienza, P.le Aldo Moro 2, 00185 Roma, Italy † Institute of Neuroinformatics, University of Zurich and ETH Zurich, Winterthurerstrasse, 190 CH-8057, Zurich, Switzerland Abstract Flocking is a paradigmatic example of collective animal behaviour, where global order emerges out of self-organization. Each individual has a tendency to align its flight direction with those of neighbours, and such a simple form of interaction produces a state of collective motion of the group. As compared to other cases of collective ordering, a crucial feature of animal groups is that the interaction network is not fixed in time, as each individual moves and continuously changes its neighbours. The possibility to exchange neighbours strongly enhances the stability of global ordering and the way information is propagated through the group. Here, we assess the relevance of this mechanism in large flocks of starlings (Sturnus vulgaris). We find that birds move faster than Brownian walkers both with respect to the centre of mass of the flock, and with respect to each other. Moreover, this behaviour is strongly anisotropic with respect to the direction of motion of the flock. We also measure the amount of neighbours reshuffling and find that neighbours change in time exclusively as a consequence of the random fluctuations in the individual motion, so that no specific mechanism to keep one’s neighbours seems to be enforced.