Encyclopedia of ecology s jørgensen, b fath (elsevier, 2008) 5 volumes 1

CONTENTS BY SUBJECT AREAOptimal Foraging Theory Orientation, Navigation, and Searching Evolution of Defense Strategies Fungal Defense Strategies Defense Strategies of Marine and Aquatic

E NCYCLOPEDIA OF ECOLOGY

Volume 1 A–C Volume 2 D–F Volume 3 G–O Volume 4 P–S Volume 5 T–X

EDITORIAL BOARD

EDITOR-IN-CHIEFSven Erik Jørgensen

ASSOCIATE EDITOR-IN CHIEF

Brian D Fath

EDITORSSteve Bartell

Principal Scientist and Manager of Maryville Operations,

E2 Consulting Engineers, Inc., 339 Whitecrest Drive,

Maryville, TN 37801, USA

Tae-Soo Chon

Division of Biological Sciences, Pusan National

University, 30 Jangjeon-Dong, Geumjeong-Gu, Busan

(Pusan) 609-735, Republic of Korea (South Korea)

James Elser

Ecology, Evolution, and Environmental Science, School of

Life Sciences, Arizona State University, Tempe, AZ

Department of Chemical & Biosystems Sciences,University of Siena, Via A Moro, 2, 53100 Siena, ItalyDonald de Angelis

Department of Biology, University of Miami, P O Box

249118, Coral Gables, FL 33124, USAMichael Graham

Moss Landing Marine Laboratories, 8272 Moss LandingRoad, Moss Landing, CA 95039, USA

Rudolph HarmsenDepartment of Biology, Queen’s University, Kingston,Ontario, K7L 3N6, Canada

Yuri SvirezhevyPotsdam Institute for Climate Impact Research, Postfach

60 12 03, D-14412 Potsdam, GermanyAlexey Voinov

University of Vermont, Burlington, VT 05405, USA

E NCYCLOPEDIA OF ECOLOGY

Editor-in-Chief SVEN ERIK JØRGENSEN

Copenhagen University,Faculty of Pharmaceutical Sciences,

Institute A,Section of Environmental Chemistry, Toxicology and Ecotoxicology,

University Park 2,Copenhagen Ø, 2100,Denmark

Associate Editor-in-Chief BRIAN D FATH

Department of Biological Sciences,Towson University,

Towson, Maryland 21252,

USA

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08 09 10 11 12 10 9 8 7 6 5 4 3 2 1

In Memoriam Yuri Svirezhev†

22 September 1938 – 22 February 2007

AGRICULTURE MODELS J C Ascough II, L R Ahuja, G S McMaster, L Ma and A A Andales 85

AIR QUALITY MODELING R San Jose´, A Baklanov, R S Sokhi, K Karatzas and J L Pe´rez 111

vii

ALTRUISM K R Foster 154

ANTAGONISTIC AND SYNERGISTIC EFFECTS OF ANTIFOULING CHEMICALS IN MIXTURE S Nagata, X Zhou and

ANTIBIOTICS IN AQUATIC AND TERRESTRIAL ECOSYSTEMS B W Brooks, J D Maul and J B Belden 210

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Pollution Indices

BIOGEOCHEMICAL APPROACHES TO ENVIRONMENTAL RISK ASSESSMENT V N Bashkin and O A Demidova 378

viii Contents

BIOGEOCHEMICAL MODELS F L Hellweger 386 BIOGEOCOENOSIS AS AN ELEMENTARY UNIT OF BIOGEOCHEMICAL WORK IN THE BIOSPHERE J Puzachenko 396 EVOLUTIONARY ECOLOGY see GENERAL ECOLOGY: Island Biogeography

C

GENERAL ECOLOGY see GENERAL ECOLOGY: Autotrophs

Contents ix

COASTAL AND ESTUARINE ENVIRONMENTS J C Marques 619

CONSERVATION BIOLOGICAL CONTROL AND BIOPESTICIDES IN AGRICULTURAL S D Wratten 744 ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Coastal and Estuarine Environments

x Contents

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Coastal and Estuarine Environments

E

Contents xi

ECOSYSTEM HEALTH INDICATORS B Burkhard, F Mu¨ller and A Lill 1132

ECOTOXICOLOGICAL MODEL OF POPULATIONS, ECOSYSTEMS, AND LANDSCAPES R A Pastorok,

ENDOCRINE DISRUPTORS: EFFECT IN WILDLIFE AND LABORATORY ANIMALS F S vom Saal, L J Guillette Jr.,

ENDOCRINE DISRUPTOR CHEMICALS: OVERVIEW J P Myers, L J Guillette Jr., S H Swan and F S vom Saal 1265

ENVIRONMENTAL AND BIOSPHERIC IMPACTS OF NUCLEAR WAR P Carl, Y Svirezhev†and G Stenchikov 1314

ENVIRONMENTAL IMPACT OF SLUDGE TREATMENT AND RECYCLING IN REED BED SYSTEMS S Nielsen 1339

ENVIRONMENTAL STRESS AND EVOLUTIONARY CHANGE B van Heerwaarden, V M Kellermann and A A Hoffmann 1363

EPIDEMIOLOGICAL STUDIES OF REPRODUCTIVE EFFECTS IN HUMANS S H Swan, L J Guillette Jr.,

EQUILIBRIUM CONCEPT IN PHYTOPLANKTON COMMUNITIES A Basset, G C Carrada, M Fedele and L Sabetta 1394

xii Contents

ESTUARINE ECOHYDROLOGY E Wolanski, L Chicharo and M A Chicharo 1413

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Coastal and Estuarine Environments

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Coastal and Estuarine Environments

FISHES AS INDICATORS OF ESTUARINE HEALTH AND ESTUARINE IMPORTANCE A K Whitfield and T D Harrison 1593

Contents xiii

FUNGAL DEFENSE STRATEGIES D Spiteller and P Spiteller 1702

VOLUME 3

G

ECOSYSTEMS see ECOSYSTEMS: Steppes and Prairies

GROWTH CONSTRAINTS: MICHAELIS–MENTEN EQUATION AND LIEBIG’S LAW S E Jørgensen 1797

H

HABITAT SELECTION AND HABITAT SUITABILITY PREFERENCES B Doligez and T Boulinier 1810

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Coastal and Estuarine Environments

INSECT PEST MODELS AND INSECTICIDE APPLICATION J C Ascough II, E M Fathelrahman and G S McMaster 1978

K

L

LANDSCAPE MODELING T R Lookingbill, R H Gardner, L A Wainger and C L Tague 2108

Contents xv

LIGHT EXTINCTION A Barausse 2180

GENERAL ECOLOGY see GENERAL ECOLOGY: Detritus

M

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Coastal and Estuarine Environments

MARICULTURE WASTE MANAGEMENT A H Buschmann, M C Herna´ndez-Gonza´lez, C Aranda, T Chopin, A Neori,

MICROBIAL ECOLOGICAL PROCESSES: AEROBIC/ANAEROBIC J S-C Liou and E L Madsen 2348

MONITORING, OBSERVATIONS, AND REMOTE SENSING – GLOBAL DIMENSIONS S Unninayar and L Olsen 2425

xvi Contents

MULTILAYER PERCEPTRON S Lek and Y S Park 2455 MULTITROPHIC INTEGRATION FOR SUSTAINABLE MARINE AQUACULTURE T Chopin, S M C Robinson,

N

O

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Development Capacity

Contents xvii

PEATLANDS D H Vitt 2656

PHYSICAL TRANSPORT PROCESSES IN ECOLOGY: ADVECTION, DIFFUSION, AND DISPERSION A Marion 2739

PLANT GROWTH MODELS P de Reffye, E Heuvelink, D Barthe´le´my and P H Courne`de 2824

xviii Contents

RADIONUCLIDES: THEIR BIOGEOCHEMICAL CYCLES AND THE IMPACTS ON THE BIOSPHERE H N Lee 2966

GENERAL ECOLOGY see BEHAVIORAL ECOLOGY: Mating Systems

RHIZOSPHERE ECOLOGY C D Broeckling, D K Manter, M W Paschke and J M Vivanco 3030

RIVERS AND STREAMS: ECOSYSTEM DYNAMICS AND INTEGRATING PARADIGMS K W Cummins and M A Wilzbach 3084 RIVERS AND STREAMS: PHYSICAL SETTING AND ADAPTED BIOTA M A Wilzbach and K W Cummins 3095

S

SEDIMENTS: SETTING, TRANSPORT, MINERALIZATION, AND MODELING L Kamp-Nielsen 3181

Contents xix

SENSITIVITY, CALIBRATION, VALIDATION, VERIFICATION A A Voinov 3221

GLOBAL ECOLOGY see GLOBAL ECOLOGY: Pedosphere

SPATIAL MODELS AND GEOGRAPHIC INFORMATION SYSTEMS T-X Yue, Z-P Du and Y-J Song 3315

ECOLOGICAL MODELS see ECOLOGICAL MODELS: Empirical Models

xx Contents

VOLUME 5

T

ECOLOGICAL INDICATORS see ECOLOGICAL INDICATORS: Ascendency

U

V

VISUALIZATION AND INTERACTION DESIGN FOR ECOSYSTEM MODELING H Shim and P A Fishwick 3685

Contents xxi

VITALISM VERSUS PHYSICAL–CHEMICAL EXPLANATIONS S N Salthe 3694

ECOTOXICOLOGY see ECOLOGICAL PROCESSES: Volatalization

W

WAVES AS AN ECOLOGICAL PROCESS C A Blanchette, M J O’Donnell and H L Stewart 3764

WIRELESS SENSOR NETWORKS ENABLING ECOINFORMATICS S S Iyengar, S Sastry and N Balakrishnan 3812

CONTENTS BY SUBJECT AREA

Optimal Foraging Theory

Orientation, Navigation, and Searching

Evolution of Defense Strategies

Fungal Defense Strategies

Defense Strategies of Marine and Aquatic

Organisms

Marine and Aquatic Defense Strategies

Plant Defense Strategies

Ecological Engineering: OverviewEnvironmental Impact Assessment andApplication – Part 1

Environmental Impact Assessment andApplication – Part 2

Environmental Impact of Sludge Treatmentand Recycling in Reed Bed SystemsErosion

Estuarine EcohydrologyEstuary RestorationForest ManagementHuman Population GrowthImpoundments

Invasive PlantsInvasive SpeciesLake RestorationLake Restoration MethodsLandscape PlanningMariculture Waste ManagementMass Cultivation of Freshwater MicroalgaeMass Production of Marine MacroalgaeMesocosm Management

MicrocosmsMine Area RemediationMultitrophic Integration for Sustainable MarineAquaculture

Natural WetlandsOrganic FarmingPhytoremediationRiparian Zone Management and RestorationSewage Sludge Technologies

Soil Movement by Tillage and OtherAgricultural Activities

Stream ManagementStream RestorationWater Cycle ManagementWatershed Management

xxiii

ECOLOGICAL INDICATORS

Abundance Biomass Comparison Method

Ascendency

Average Taxonomic Diversity and Distinctness

Benthic Response Index

Berger–Parker Index

Biological Integrity

Biomass, Gross Production, and Net

Production

Coastal and Estuarine Environments

Connectance and Connectivity

Development Capacity

Driver–Pressure–State–Impact–Response

Eco-Exergy as an Ecosystem Health

Indicator

Eco-Exergy to Emergy Flow Ratio

Ecological Health Indicators

Ecosystem Health Indicators

System Omnivory Index

Technology for Sustainability

Trophic Classification for Lakes

Trophic Index and Efficiency

Turnover Time

ECOLOGICAL INFORMATICS

Adaptive Agents

Application of Ecological Informatics

Artificial Neural Networks: Temporal

Classification and Regression TreesComputer Languages

Data MiningEcological Informatics: OverviewEvolutionary Algorithms

Hopfield NetworkInternet

Multilayer PerceptronSelf-Organizing MapSimulated AnnealingSupport Vector MachinesWavelet NetworkWireless Sensor Networks EnablingEcoinformatics

ECOLOGICAL MODELS

Agriculture ModelsAir Quality ModelingArtificial Neural NetworksBifurcation

Biogeochemical ModelsClimate Change ModelsConceptual Diagrams and Flow DiagramsEcological Models, Optimization

Empirical ModelsFish GrowthFisheries ManagementForest ModelsFuzzy ModelsGrassland ModelsGrazing ModelsHydrodynamic ModelsHysteresis

Individual-Based ModelsInsect Pest Models and Insecticide ApplicationLake Models

Landscape ModelingLand-Use ModelingLeaf Area IndexMarine ModelsMatrix ModelsMicrobial ModelsModel Development and AnalysisModel Types: Overview

Modules in ModelingNumerical Methods for Distributed ModelsNumerical Methods for Local ModelsParameters

Participatory ModelingPlant Competition

xxiv Contents by Subject Area

Plant Growth Models

Remote Sensing

River Models

Sensitivity and Uncertainty

Sensitivity, Calibration, Validation,

Biological Nitrogen Fixation

Composting and Formation of Humic

Physical Transport Processes in Ecology:

Advection, Diffusion, and Dispersion

Predation

Reaeration

Respiration

Scale

Sediment Retention and Release

Soil Erosion by Water

Soil Formation

The Significance of O2 for Biology

Transport in Porous Media

Transport over MembranesVolatalization

Waves as an Ecological ProcessWind Effects

ECOLOGICAL STOICHIOMETRY

Ecological Stoichiomety: OverviewEcosystem Patterns and ProcessesEvolutionary and Biochemical AspectsOrganismal Ecophysiology

Population and Community InteractionsTrace Elements

ECOSYSTEMS

Agriculture SystemsAlpine Ecosystems and the High-ElevationTreeline

Alpine ForestBiological Wastewater Treatment SystemsBoreal Forest

Botanical GardensCaves

ChaparralCoral ReefsDesert StreamsDesertsDunesEstuariesFloodplainsForest PlantationsFreshwater LakesFreshwater MarshesGreenhouses, Microcosms, and MesocosmsLagoons

LandfillsMangrove WetlandsMediterraneanPeatlandsPolar Terrestrial EcologyRiparian WetlandsRivers and Streams: Ecosystem Dynamics andIntegrating Paradigms

Rivers and Streams: Physical Setting andAdapted Biota

Rocky Intertidal ZoneSaline and Soda LakesSalt Marshes

SavannaSteppes and PrairiesSwamps

Temperate Forest

Contents by Subject Area xxv

Acute and Chronic Toxicity

Antagonistic and Synergistic Effects of

Antifouling Chemicals in Mixture

Antibiotics in Aquatic and Terrestrial

Ecological Risk Assessment

Ecotoxicological Model of Populations,

Ecosystems, and Landscapes

Ecotoxicology Nomenclature: LC, LD,

LOC, LOEC, MAC

Ecotoxicology: The Focal Topics

Ecotoxicology: The History and Present

Directions

Effects of Endocrine Disruptors in Wildlife

and Laboratory Animals

Endocrine Disruptors

Endocrine Disruptor Chemicals: Overview

Epidemiological Studies of Reproductive

Effects in Humans

Exposure and Exposure Assessment

Food-Web Bioaccumulation Models

TeratogenesisUraniumVeterinary Medicines

Fitness LandscapesGause’s Competitive Exclusion PrincipleLimiting Factors and Liebig’s PrincipleMacroevolution

Optimal ForagingOptimal Reproductive TacticsParasitism

Physiological EcologyPopulations: r- and K-SelectionStability versus ComplexityUnits of Selection

GENERAL ECOLOGY

AbundanceAdaptive CycleAllopatryAnimal Home RangesAnimal PhysiologyAnimal Prey DefensesApplied EcologyAssociationAutecologyAutotrophsBiodiversityBiomassBiotopesCarrying CapacityClines

CoevolutionColonizationCommunity

xxvi Contents by Subject Area

Growth Constraints: Michaelis–Menten

Equation and Liebig’s Law

Leaf Area Index

Life Forms, Plants

SynecologyTaxisTemperature RegulationTolerance RangeTrophic StructureTropical EcologyWater AvailabilityWildlife Ecology

GLOBAL ECOLOGY

Abiotic and Biotic Diversity in theBiosphere

AgricultureAnthropospheric and AnthropogenicImpact on the Biosphere

AstrobiologyBiogeochemical Approaches to EnvironmentalRisk Assessment

Biogeocoenosis as an Elementary Unit ofBiogeochemical Work in the BiosphereBiosphere: Vernadsky’s ConceptCalcium Cycle

Carbon CycleClimate Change 1: Short-Term DynamicsClimate Change 2: Long-Term DynamicsClimate Change 3: History and Current StateCoevolution of the Biosphere and ClimateDeforestation

Energy BalanceEnergy Flows in the BiosphereEntropy and Entropy Flows in the BiosphereEnvironmental and Biospheric Impacts ofNuclear War

Evolution of OceansEvolution of ‘Prey–Predator’ SystemsFungi and Their Role in the BiosphereGaia Hypothesis

Global Change Impacts on the BiosphereHydrosphere

Information and Information Flows in theBiosphere

Iron CycleMaterial and Metal EcologyMatter and Matter Flows in the Biosphere

Contents by Subject Area xxvii

Methane in the Atmosphere

Radionuclides: Their Biogeochemical Cycles

and the Impacts on the Biosphere

Structure and History of Life

Philosophy of Ecology: Overview

Vitalism versus Physical–Chemical

Explanations

POPULATION DYNAMICS

AdaptationAge Structure and Population DynamicsAge-Class Models

Allee EffectsAmensalismAquatic OrganismsBiological Control ModelsCannibalism

CoexistenceCommensalismsCompetition and Coexistence in ModelPopulations

Competition and Competition ModelsDemography

Dispersal–MigrationFecundity

Fishery ModelsForestry ManagementGrowth ModelsHerbivore-Predator CyclesMetapopulation ModelsMicrobial CommunitiesMortality

MutualismPlant DemographyPopulation Viability AnalysisPrey–Predator ModelsRecruitment

ResilienceResistance and Buffer Capacityr-Strategist/K-StrategistsSex Ratio

Spatial DistributionSpatial Distribution ModelsStability

Statistical MethodsTerrestrial ArthropodsWeed Control Models

SYSTEMS ECOLOGY

AutocatalysisBody-Size PatternsCyberneticsCycling and Cycling IndicesEcological ComplexityEcological Network Analysis, AscendencyEcological Network Analysis, Energy AnalysisEcological Network Analysis, EnvironAnalysis

Emergent PropertiesEmergy and Network Analysis

xxviii Contents by Subject Area

Environmental Security

Equilibrium Concept in Phytoplankton

Communities

Exergy

Fundamental Laws in Ecology

Goal Functions and Orientors

Hierarchy Theory in Ecology

Indirect Effects in Ecology

Mathematical EcologyPanarchy

Retrospective AnalysisSelf-OrganizationSemiotic EcologySocioecological SystemsSystems Ecology

Contents by Subject Area xxix

E cology is the science of the interrelations between living organisms and their environments These interrelationsare complex, varied, and hierarchical As such, it is a broad and diverse discipline that covers topics from naturalselection to population dynamics to biogeochemistry to ecosystem health and sustainability Our aim in this compen-dium is to aggregate, in one major reference work, a thorough overview that does justice to this diversity and, at the sametime, makes connections between the topics The result is the five-volume work before you, containing over 530 expertlyauthored entries The entries together form a comprehensive picture of the science of ecology and its major sub-disciplines Individually, the entries are succinct, informative, state-of-the-art reviews for use as research

references or teaching aids The Encyclopedia of Ecology covers many facets of this wide-ranging and far-reaching field

The section on general ecology is the largest in the encyclopedia since it forms the bedrock of knowledge developedover a century of ecological research These characteristics of fundamental ecology are what one would expect to find inany textbook Additional entries cover the major ecosystem types, including their distribution and unique features Keybasic ecological processes are given a wide coverage in the encyclopedia, as are aspects of global ecology Both naturaland abiotic components are considered The central question in this context deals with ‘How are natural ecologicaldynamics influenced by the introduction of new components?’ This question draws from the well-represented field ofecotoxicology As we move away from primary questions dealing with pristine natural environments, the interplay oforganisms and their environment extends to include human action

Ecology also plays an important role in the management and stewardship of environmental resources In the

mid-1960s, we experienced a renewed awareness and concern for the environment, sparked in part by Rachel Carson’s Silent

Spring, growing human population, and conspicuous air and water pollution Environmental problems are rooted in how

humans influence nature and to understand these interactions between man and nature fully, we need ecology, becauseecology focuses on the organization, processes, and changes in nature There is no doubt that the environmental

xxxi

problems have accelerated the development of ecology while at the same time our increased knowledge about thefunctioning of ecosystems has been implemented in ecologically friendly design Each successive environmental alarm,from ozone depletion to biodiversity loss to eutrophication to climate change, has pushed the envelope of ecologicalknowledge More and more resources are directed towards research to help us understand the natural world and our role

as a dominant species in it Our policies towards environmental management require us to be able to ask and answerecological questions such as: What will be the impact of a particular chemical released into nature? What is nature’sbuffer capacity to accept the release? How can we better manage and design systems to prevent such releases? Theanswers to these questions require a profound knowledge of nature as a whole, the core questions of ecology

Out of the need for a better ecological understanding have grown several new subdisciplines in ecology Manyexamples are covered in the encyclopedia, but let us mention here three: ecological modeling, ecological engineering,and ecological indicators First, ecological modeling provides a formal, structured approach to quantify ecologicalprocesses in order to understand the methods by which they function Second, ecological engineering brings designprinciples from nature into application for basic human needs such as wastewater treatment, sustainable agroecosystems,and lake restoration The objective is to develop systems that work within the natural order rather than at odds with it.Ecological engineering is based on a close cooperation between humans and nature for the benefit of both Third,ecological indicators are easy-to-understand metrics to ‘measure the pulse of the ecosystem’ The selection of theappropriate indicators requires accurate knowledge of the ecosystems and their functioning, exactly as indicators forhuman diseases require knowledge of the medical sciences The application of ecological indicators to assess ecosystemhealth is drawing heavily on the entire spectrum of ecological knowledge Key ideas, methods, and examples ofecological modeling, engineering, and indicators are described in detail in the encyclopedia

The encyclopedia and entry layout are designed to maximize usability and usefulness of the material for the reader.The entries are alphabetically arranged within ecological subcategories, with running titles Each entry has a concisesynopsis followed by the body of the work, and ending with suggested further readings of the key references related tothe subject As ecology is a holistic science, it is not possible to completely separate one topic from the others Therefore,cross-references to other entries within the encyclopedia are also given The appendix contains several informativetables more appropriate to the whole body of work than to any one specific entry topic The encyclopedia has acomprehensive index allowing the reader to quickly search the wide range of topics Together, the many entries, likeknots in an ecological network, weave together to make a rich tapestry of the science of ecology

Sven Erik JørgensenCopenhagen, 29 February 2008

Brian D FathVienna, 10 March 2008

xxxii Preface

GUIDE TO THE ENCYCLOPEDIA

T he Encyclopedia of Ecology is a complete source of information on ecology, contained within the covers of a single

unified work Within the five volumes are over 530 separate articles from international experts on a diverse array

of topics including Behavioral Ecology, Ecological Processes, Ecological Modeling, Ecological Engineering, EcologicalIndicators, Ecological Informatics, Ecosystems, Ecotoxicology, Evolutionary Ecology, General Ecology, GlobalEcology, Human Ecology, and Systems Ecology This encyclopedia provides a comprehensive review of the state ofthe art in ecology and will be a valuable resource to researchers, teachers, students, environmental managers andplanners, and the general public In order that you, the reader, will derive the greatest possible benefit from your use of

the Encyclopedia of Ecology, we have provided this Guide.

ORGANIZATION

The Encyclopedia of Ecology is organized to provide maximum ease of use for its readers All of the articles are arranged

in a single alphabetical sequence by title Articles whose titles begin with the letters A to C are in Volume 1, articleswith titles from D to F are in Volume 2, articles with titles from G to O are in Volume 3, articles from P to S are inVolume 4, and Volume 5 comprises articles from T to Z, a complete subject index for the entire work, and analphabetical list of the contributors to the Encyclopedia

TABLE OF CONTENTS

A complete table of contents for the Encyclopedia of Ecology appears at the front of each volume This list of article titles

represents topics that have been carefully selected by the Editors-in-Chief, Sven Erik Jørgensen and Brian D Fath, andthe Section Editors The Encyclopedia provides coverage of 13 specific subject areas within the overall field of ecology.For example, the Encyclopedia includes 34 different articles dealing with Population Dynamics (See p [xxiii] for atable of contents by subject area.) The list of subject areas covered is as follows:

cross-‘‘Cellular Automata’’, ‘‘Ecological Complexity’’, ‘‘Ecological Informatics: Overview’’, ‘‘Evolutionary Algorithms’’ and

‘‘Individual-Based Models’’

FURTHER READING

The Further Reading section appears as the last element in an article The reference sources listed there are the author’srecommendations of the most appropriate materials for further reading on the given topic The Further Reading entriesare for the benefit of the reader and thus they do not represent a complete listing of all the materials consulted by theauthor in preparing the article

xxxiv Guide to the Encyclopedia

PERMISSION ACKNOWLEDGMENTS

The following material is reproduced with kind permission of Nature Publishing Group

Figures 4a and 4b from Altruism

Figures 4b and 5 from Orientation, Navigation, and Searching

Figures 7 and 9 from Coral Reefs

Figure 5 from Savanna

Figures 3a and 3b from Allopatry

Figure 6 from Ecosystems

Table 1 from Astrobiology

Figures 3b and 3d from Fecundity

Figures 4, 5a, 5b, 5c, 5d, 5e, 5f, 6a and 6b from Demography

Figure 5 from Microbial Communities

Figure 3 from Metapopulation Models

Figures 1 and 2 from Parasitism

Figures 2a, 2b and 2c from Life-History Patterns

http:/ /www.nat ure.com/natu re

The following material is reproduced with kind permission of Taylor & Francis Group

Figure 10e from Habitat Selection and Habitat Suitability Preferences

Table 1 from Statistical Prediction

Figures 1 and 3 from Transport over Membranes

Figures 2, 3, 4 and 13 from Ecotoxicological Model of Populations, Ecosystems, and Landscapes

http:/ /www.t andf.no/ boreas

The following material is reproduced with kind permission of Oxford University Press

Figure 3 from Plant Growth Models

Figure 3 from Statistical Methods

Figures 1a and 1b from Metapopulation Models

Tables 1 and 3 from Optimal Reproductive Tactics

Figure 4 from Soil Ecology

www.o up.com

The following material is reproduced with kind permission of Science

Figures 2c, 2d and 4c from Orientation, Navigation, and Searching

Figure 2 from Environmental Stress and Evolutionary Change

Figures 5 and 10 from Coral Reefs

Figure 6 from Steppes and Prairies

Table 4 from Biomass

Table 1 from Succession

Figures 5a, 5b and 5c from Body Size, Energetics, and Evolution

Figure 2 from Animal Home Ranges

The following material is reproduced with kind permission of American Association for the Advancement of Science

Figure 10d from Habitat Selection and Habitat Suitability Preferences

http:// www.scien cemarg org

xxxv

Abiotic and Biotic Diversity in the Biosphere

P J Geogievich, AN Severtsov Institute of Ecology and Evolution, Moscow, Russia

ª 2008 Elsevier B.V All rights reserved.

Introduction

Model

Living Matter

Landscape DiversityConclusion

Further Reading

Introduction

The phenomenon ‘diversity’ is related to the reflection

of any natural phenomena through a set of elements

(particles, material points) with different classes of

prop-erty states observed in space The elements are

confirmed to interact potentially with each other This

is a thermostatistical model of the world acceptable for a

wide set of phenomena, from the atomic level to the

social–economic one As in physics, within the

frame-work of a model of a particular phenomenon, an element

is considered, as that is invariable in the process of all the

imaginable transformations The invariability is nothing

more than an assumption simplifying the model In

general, if physical essence is given to an element, the

very element is implied as an integral system supported

by internal negative and positive relations between the

parts forming it The proven universality of fractality of

nature, that is, its correspondence to the model of

continuous–discontinuous set enables to determine an

element as a cell of certain size in the accepted scale of

space–time

Model

Gene, allele, chromosome, cell, individual, chemical

ele-ment, compound of elements, mineral, rock, community

of organisms described on a sample plot selected, pixel of

a cosmic image, car, plant, settlement, town, country, and

so on may be elements of models In all the cases, we have

n elements, and each of them may be referred to one of

the k classes according to its properties In the process of

interactions, the elements belonging to different classes

may be assumed to form structures locally stable in time

It is unknown a priori what structures are stable or

unstable, but their whole diversity is described by the

formula I ¼ n1!n2!n3! n m !, where n iis the number of

i¼1 pi is the Gibbs–Shannon’s entropy (see

Shannon–Wiener Index) (p i ¼ n i =N is the probability of elements of class i in sample N, K is the analog of Planck’s

constant)

Under equilibrium (derivatives are close to zero), in alinear case, the Gibbs’s distribution has resulted A.Levich in 1980 supposed the nonlinearity of relations tothe property space and obtained the rank distributions:

•p i¼  exp(i) – the Gibbs’ rank distribution, that is,condition of linear dependence of a system on aresource;

•p i ¼  exp( log(i)) ¼ i– the Zipf ’s rank tion, that is, logarithmic dependence on a resource;

distribu-•p i ¼  exp( log(a þ i)) ¼ (a þ i) – the Zipf–Mandelbrot’s rank distribution, that is, logarithmic

dependence on an resource, where a is the number of

unoccupied (vacant) state with an unused resource;

•p i ¼  exp( log(log i)) ¼  log i– the MacArthur’srank distribution (the broken stick), at twice logarith-mic dependence on a resource

1

Simple transformations on making the assumption that

there is some class with only one element allow finding

widespread relationships of the number of species with

the volume of sampling N or with the area, where the

sampling was made Such relations obtained in island

biogeography are true for any phenomenon

If these relations are nonequilibrium, members with

order >1 are included into rank distributions These

forms of distributions are typical in nature If a system is

nonstationary, Kulback’s entropy is a measure of

nonsta-tionarity Under the same conditions, entropy of the

nonstationary system is less than entropy nonequilibrium

one, and the entropy of the nonequilibrium system is less

than that of equilibrium one

According to the model, diversity (entropy) of a

sys-tem is the function of power or diversity of the

environment and evolutionary parameters The first

para-meter is identical to free energy of Gibbs (exergy in a

nonstationary case), the second one to temperature Thus,

in the closed space, evolution of diversity corresponds to

the thermodynamic model, and entropy increases in time

Living Matter

If a system is open and dissipative, its diversity and

non-stationarity is supported by the flow of information and

energy from the environment The system selects an

order from the environment and increases its entropy

(disturbs its own environment)

Living matter differs from abiotic one As V I Vernadsky

in 1926 wrote, ‘‘living organisms change the course of

the biosphere equilibrium (unlike abiotic substance) and

represent specific autonomic formations, as if special ondary systems of dynamic equilibria in the primarythermodynamic field of the biosphere.’’ According toJorgensen’s ideas, they also increase their own exergy (usefulwork) supporting their local stability in aggressive medium.Probably, the maximization of stability via increasing exergy

sec-is not the single way of survival Many organsec-isms make thestability maximum at very low energy expenditures via thecomplexity of their own structure that decrease the destruc-tive action of the environment

Evolution of living systems appears to be founded onmechanisms that do not fit the framework of three prin-ciples of thermodynamics Nowadays, a satisfactoryphysical model of this evolution is absent An empiricalfact is the growth of biological diversity (see AverageTaxonomic Diversity and Distinctness and Biodiversity)

in time according to hypergeometric progression Themode of the statistical model shows that in the course ofevolution, the dimension of the space as well as thevolume of resources increase (Figure 1)

•Model 1. log(number of families)¼ (0.078 61 þ

0.031 733 log T )T log T, where T is the time (unit of

measurement is 1 million years)

•Model 2. Number of families¼ exp(0.030 053(1.038 47T )T ).

The younger the taxon, the faster the growth of its

diver-sity The rate (T ) of evolution increases in time

(Figure 2) as T ¼ constant  T3.7(R2¼ 0.53) In order

to explain this phenomenon, the memory about the pastsuccesses and failures in the synthesis of new structures andvariability that allow opening new possibilities of the envir-onment should be added The thermodynamic law of

–2750 –3000

–2250 –2500 –2000

–1250 –1500

–750 –1000

Time (1 million years)

–1750

Figure 1 Changes of a global biodiversity biological variety at a level of families on a database (Fossil Record 2) Based on Puzachenko Yu G (2006) A global biological variety and his (its) spatially times changes In: Kasimov NS (ed.) Recent Global Changes of the Natural Environment, vol 1, pp 306–737 Moscow: Scientific World (in Russian).

2 Global Ecology|Abiotic and Biotic Diversity in the Biosphere

evolution for living matter appears to reduce to a decrease

of expenditures per unit of complexity (1 bit) Such

struc-tures extracting energy and substance from the

environment can keep the area far from equilibrium for a

long time

Phenomenology of changes in the number of species as

a function of environmental quality with regard to the

time of continuous development is within the framework

of this model

Landscape Diversity

Unlike biological diversity, landscape diversity combines

biotic and abiotic constituents As the landscape diversity is

assessed using cosmic images, it is maximum for territories

without vegetation and minimum for rainy tropical forests

of Amazonia This effect is determined by a more complete

absorption of solar radiation by plants that transform it into

energy spent for evaporation, production, internal energy,

and heat flow Upon the transformation of solar radiation,

vegetation (due to the species diversity) lowers the

diver-sity of reflection (in each particular variant of the

environment, there is found a plant species with the most

efficient absorption) In this case, Ashby’s ‘law of the

neces-sary diversity’ manifests itself The same effect is also true

for the diversity of the soil cover and other abiotic factors

Autofluctuations described by the Holling’s model of

panarchy are imposed upon the general trend of evolution

of living matter and socium.

Conclusion

The phenomenon of diversity is a basic property ofany forms of matter, being observable via the locallystable state of particles (elements) The behavior of a set

of particles in space of their material properties followsthe principles of nonequilibrium dynamics Living matter,unlike abiotic substance, expands its thermodynamic pos-sibilities via a search for structures that use spaces withincreasing volume and dimension and, accordingly, with ahigh flow of energy Evolution of abiotic substance obeysthe second principle of thermodynamics – the growth ofentropy as a measure of disorder Evolution of livingmatter obeys the opposite growth of order, also uponincrease in the total entropy, that is, upon self-organiza-tion in Foerster’s opinion

See also: Average Taxonomic Diversity and Distinctness;Biodiversity; Shannon–Wiener Index

Further Reading

Benton MJ (ed.) (1993) The Fossil Record 2, 845pp London: Chapman

& Hall http://www.fossilrecord.net/fossilrecord/

index.html (accessed December 2007).

Holling CS and Gunderson LH (2002) Resilience and adaptive cycles In: Gunderson LH and Holling CS (eds.) Panarchy: Understanding Transformations in Human and Ecological Systems, pp 25–62 Washington, DC: Island Press.

Jorgensen SE (2000) 25 years of ecological modelling by ecological modelling Ecological Modelling 126(2–3): 95–99.

Time from the beginning of evolution (million years)

Figure 2 The proper time (T) change.

Global Ecology|Abiotic and Biotic Diversity in the Biosphere 3

Jorgensen SE and Svirezhev Iu M (2004) Towards a Thermodynamic

Theory for Ecological Systems, 366pp Amsterdam: Elsevier

Science.

Levich AP and Solov’yov AV (1999) Category-function modeling of

natural systems Cybernetics and Systems 30(6): 571–585.

Puzachenko Yu G (2006) A global biological variety and his (its) spatially

times changes In: Kasimov NS (ed.) Recent Global Changes of the

Natural Environment, vol 1, pp 306–737 Moscow: Scientific World

Abundance

J T Harvey, Moss Landing Marine Laboratories, Moss Landing, CA, USA

ª 2008 Elsevier B.V All rights reserved.

Introduction

Population Dynamics and Growth Models

r-Selected versus K-Selected Organisms

Factors Affecting AbundanceFurther Reading

Introduction

The abundance of an organism, often considered as total

population size or the number of organisms in a particular

area (density), is one of the basic measures in ecology

Ecologists often are interested in the abundance and

dis-tribution of organisms because the number and spatial

extent of an organism reflects the influences of many

factors such as patterns in nutrients (fuel), predators or

herbivores, competitors, dispersal, and physical

condi-tions Organisms generally are more abundant where

conditions are favorable, such as locations with sufficient

quantity and quality of food or nutrients, fewer herbivores

or predators, fewer competitors, and optimal physical

features The physical features that affect abundance

could be substrate type, moisture, light, temperature,

pH, salinity, oxygen or CO2, wind, or currents

Ultimately, the abundance of an organism is dependent

on the number of individuals that survive and reproduce

Therefore, any factors that affect survival or reproduction

will affect abundance

Abundance can be measured at many levels, such as

the number of individuals of a certain sex or age within a

population, the number in a certain geographical region,

the number in a certain population (possibly defined as

the interbreeding individuals of the same species in a

certain geographical area), or the number of individuals

of a certain species Species or populations have different

levels of abundance and different population dynamics

because of inherent biological characteristics (vital rates),

such as the number of young produced per individual,

longevity, and survival, and because the species may beadapted and exposed to various environmental condi-tions Estimating abundance, however, can be difficultdepending on the distribution, visibility, density, andbehaviors of the organism

Estimates of abundance can be obtained by countingall individuals in the population or sampling some portion

of the population A census or total count of all duals is a common technique used to assess abundance oforganisms that are relatively rare and easily observed Ifthe organism is too numerous or not easily counted then arepresentative portion of the population is sampled usingvarious techniques such as (1) counts within randomlyselected sampling units (e.g., quadrats, cores, nets, ortraps); (2) mark-recapture; (3) strip or line transects,which is essentially sampling a long thin quadrat; and(4) distance methods (e.g., nearest neighbor) Most ofthese methods have a well-developed theoretical andanalytical basis Based on whether the organism is numer-ous and relatively stationary (e.g., plants), or rare andmobile (e.g., many vertebrates) certain techniques areappropriate Numbers of individuals within a sample can

indivi-be determined directly by visually counting individuals

or indirectly using acoustics, such as hydroacoustics forassessing fishes or counting calls of bird or whales Otherindirect methods include counting the number of eggs orjuveniles, which is an indication of the number of adults(sometimes used to assess fish abundance) or countingnests (such as used for birds) Recently the amount ofgenetic variation in a population has been used to esti-mate abundance

4 General Ecology|Abundance

If an actual number of individuals cannot be determined,

scientists have used indices of abundance, such as changes

through time, percentage cover or harvested biomass (e.g.,

for plants), and catch per unit effort (e.g., for fishes)

Ecologists are always striving for an accurate and precise

estimate of abundance; therefore, a thorough knowledge of

the organism and its environment is necessary to design the

proper sample unit and best allocation of that sample unit in

space and time Estimates of abundance can be made more

accurate or at least accuracy assessed by eliminating or

decreasing biases and by using various methods to

deter-mine abundance Determining whether there is an accurate

estimate of abundance is difficult because usually the true

abundance is unknown and the estimate may contain

unknown biases Being aware of the potential biases and

striving to minimize and investigate biases will increase the

chances of an accurate abundance estimate Different

sam-pling designs will help ensure a representative sample is

obtained that also will increase accuracy Variability in the

estimate of abundance, or precision, is affected by the

natural variability in abundance among the samples and

by the number of samples Because natural variability

can-not be controlled, the single best means of increasing the

precision of the abundance estimate is to increase sample

size (e.g., number of transects, cores, marked individuals)

An understanding of sampling design (or the observation

of sample units in space and time) can help determine

whether there are enough independent and representative

sample units to provide an accurate and precise estimate of

abundance

The spatial and temporal patterns of abundance

(i.e., dispersion) often indicate fluctuations in physical or

biological factors Abundance is a measure of how many

organisms are within an area whereas dispersion is how

those organisms are arranged within the area We usually

recognize three basic patterns of abundance in space or

time: uniform, random, or aggregated (Figure 1) A

uni-form abundance in space or time is one where the organism

is spaced evenly Rarely is this the case for organisms

because biological factors (e.g., attraction, aggression,

com-petition) will cause nonuniformity and most environmental

features that affect organisms are not uniformly distributed.With a random distribution we assume that the probabilitythat an organism can inhabit any location or time is equal.This also is rare for the same reasons that organisms are notuniformly distributed Finally, organisms can be aggre-gated if they occupy very specific locations, such that insome locations or times the probability of encounteringthat organism is nearly one and in other locations ortimes it is zero At some spatial scale all organisms aregrouped or aggregated Sea bird nests may be uniformlydistributed within a colony because the birds place theirnests just far enough apart to not be pecked by theirneighbor, but the nests are very much aggregated becausesome sea birds only nest on isolated islands If you focusedyour attention at the scale of the colony, the bird’s nestswould be distributed uniformly, but at the scale of theworld, the nests are aggregated Aggregations typicallyoccur where local conditions are optimum for survivaland reproduction For instance, certain plants require spe-cific soil types, light exposure, moisture, and nutrients.Through adaptive radiation, species have evolved specificrequirements; hence, they cannot live just anywhere.The aggregated distribution of organisms implies thatindividuals of a population will be abundant in some loca-tions and rare or absent from other locations The samepatterns and rationale can be used to assess abundancepatterns in time Certain periods of time are more condu-cive to some species; hence they are more abundant, thanother times The timescales that affect abundance can bedays for short-lived organisms like insects, or thousands ofyears like large trees Natural and anthropogenic changes

in environmental conditions will cause changes in dance for all organisms, and these changes can be predictedusing mathematical models of population dynamics Theactual patterns of dispersion in space and time form acontinuum, where populations can have varying levels ofuniform, random, or aggregated patterns Because organ-isms in space and time have an infinite array of patterns itmakes it difficult to accurately model and test patterns ofdispersion

abun-Population Dynamics and Growth Models

Population growth rate is defined as the change in ber of individuals in the population through a certainamount of time Changes in abundance often are assessed

num-at the populnum-ation level, because thnum-at is where the effects ofbiological and environmental conditions are most evident.Later the modeling of metapopulations (groups of popu-lations that share individuals) will be discussed Oftenecologists measure population changes using density(the number of individuals per area) because interactionsamong individuals and between an individual and itsenvironment are more affected by density than actual

Figure 1 Various forms of dispersion in space (uniform,

random, and aggregated) are depicted using red stars as

individual organisms In reality, there is a continuum of dispersion

from the extremely uniform to greatly aggregated, with random in

between these two forms.

General Ecology|Abundance 5

population abundance Changes in abundance of a

popu-lation, called population dynamics, are caused by many

factors, but at the most fundamental level the number of

individuals in the population at some later time period

begin-ning of the time period (N t ) plus the number of births (B)

and immigrants (I) minus the number of deaths (D) and

emigrants (E) that occur during the time period:

N t þ1 ¼ N t þ B – D þ I – E ½1

We can rearrange the terms to determine the change in

population abundance
N:

ðN t þ1 – N t Þ ¼
N ¼ B – D þ I – E ½2

If we assume the population is closed, that is, there is

no movement of individuals into the population

(immi-gration) or movement out of the population (emi(immi-gration),

then the equation becomes simplified In this case, we are

modeling only the changes that occur within a population

Although most populations are not closed (i.e., there is

immigration and emigration), it allows for some easier

calculations and allows us to provide details on a specific

population For a closed population, with I ¼ 0 and E ¼ 0,

the equation simplifies to

If we also assume that the period of time between

estimates of population abundance is extremely small

(i.e., t is nearly 0), then we can treat population growth

as continuous If we estimated population abundance only

after a large period of time then population growth would

not be modeled as continuous but would be a discrete

function Modeled as a discrete function the estimate of

the population abundance would be the same or changing

during the time period, then at the end of the period it

would change to a new level, stepping from one

abun-dance level to another after each time period (Figure 2)

By assuming population growth is continuous we can use

a differential equation to describe the change in

popula-tion size (dN) that occurs during an extremely small

period of time (dt):

dN

B and D now represent rates, or the number of births or

deaths in this population during these short periods of

time The birth rate (B) can be thought of as the number of

births per individual per time period (b), called the

instan-taneous birth rate, times the number of individuals in the

population (N) at that time The death rate (D) also can be

calculated using the instantaneous death rate (d) times the

population abundance (N) The continuous differential

The instantaneous rate of increase of the population

(r), often called the intrinsic rate of increase, is b  d, so substituting r for (b  d) produces a new model for popu-

lation growth that is

rate and mortality rate are equal (b  d ¼ 0) If r is positive

or greater than 1 (per capita birth rate exceeds per capitadeath rate) then the population would increase propor-

tional to the population abundance (N) in an exponential fashion If r is negative or less than 1 (death rate exceeds

the birth rate), then the population would decrease nentially (Figure 2) The greater the value of r the more

expo-rapidly the population will change The intrinsic rate ofincrease can be used to model or predict future population

abundance (N t þ 1) by integrating the population growth

model and knowing the time interval (t) over which you

6 General Ecology|Abundance