Efnisyfirlit

• Front Matter
  • Dedication
  • Preface to Fourth Edition
  • Acknowledgments
  • Authors
  • Introduction
    • Approach and Organization of This Book
      • FIGURE 0.1 Schematic relationship of linkages between responses at different organizational levels.
    • Applications and Conclusions
• Section I Pollutants and Their Fate in Ecosystems
  • 1 Major Classes of Pollutants
    • 1.1 Inorganic Ions
      • 1.1.1 Metals
        • TABLE 1.1 Anthropogenic Enrichment Factors (AEFs) for Total Global Annual Emissions of Cadmium, Lead, Zinc, Manganese, and Mercury in the 1980s
        • FIGURE 1.1 Periodic table of the elements. Those considered metals are surrounded by bold lines. Metalloids (with properties of metals and nonmetals) are shaded.
        • TABLE 1.2 Separation of Some Essential and Nonessential Metal Ions of Importance as Pollutants into Class A (Oxygen Seeking), Class B (Sulfur or Nitrogen Seeking), and Borderline Elements
        • FIGURE 1.2 Relationships between performance (growth, fecundity, survival; P) and concentrations of essential (Ce) or nonessential (Cne) elements in the diets of animals. Possible deficiency effects at ultratrace levels (d) of apparently nonessential elements may be discovered as the sensitivities of analytical techniques are improved.
      • 1.1.2 Anions
        • TABLE 1.3 Levels of Activities of Carbonic Anhydrase Expressed Relative to Levels of Zinc for Different Metals Substituted in Proteins
    • 1.2 Organic Pollutants
      • 1.2.1 Hydrocarbons
        • BOX 1.1 CHEMICAL WARFARE
        • FIGURE 1.3 Hydrocarbons consist only of hydrogen and carbon. They exhibit low polarity and thus low solubility in water and high solubility in oils and organic solvents. Propane and cyclohexane are examples of alkanes. Benzene, and benzo(a)pyrene are aromatic compounds that contain six-membered carbon (benzene) rings with delocalized electrons. The benzene ring is represented as a hexagon (six-membered carbon frame) surrounding a circle (cloud of delocalized electrons). Aromatic hydrocarbons undergo certain characteristic biotransformations influenced by the delocalized electrons (Section 5.1.5).
      • 1.2.2 Polychlorinated Biphenyls (PCBs)
        • FIGURE 1.4 Organohalogens are organic compounds containing halogen atoms (fluorine, chlorine, bromine, or iodine). The examples shown are organochlorine compounds, although organofluorine compounds (chlorfluorocarbons) and organobromine compounds (polybrominated biphenyls) are also environmental pollutants. The compounds shown here are stable solids of low polarity and water solubility. They are not found in nature; they are often only slowly metabolized and consequently are persistent in living organisms (Chapter 5).
      • 1.2.3 Polychlorinated Benzodioxins (PCDDs)
      • 1.2.4 Polychlorinated Dibenzofurans (PCDFs)
      • 1.2.5 Polybrominated Biphenyls (PBBs)
        • BOX 1.2 PCDDS
      • 1.2.6 Organochlorine Insecticides
      • 1.2.7 Organophosphorous Insecticides (OPs)
        • FIGURE 1.5 Organophosphorous and carbamate insecticides are toxic to insects because they inhibit the acetylcholinesterase enzyme (Chapter 7). They vary in their polarity and water solubility and are generally more reactive and less stable and persistent than the organochlorine insecticides. The leaving group of the organophosphorous compounds breaks away from the rest of the molecule when hydrolysis occurs (Chapter 5).
      • 1.2.8 Carbamate Insecticides
      • 1.2.9 Pyrethroid Insecticides
      • 1.2.10 Neonicotinoids
        • FIGURE 1.6 Pyrethroid insecticides have low polarity and limited water solubility. They are related in structure to the natural pyrethrins that are also toxic to insects.
        • FIGURE 1.7 Imidacloprid is an example of a neonicotinoid insecticide that structurally resembles nicotine.
      • 1.2.11 Phenoxy Herbicides (Plant Growth Regulators)
        • FIGURE 1.8 Phenoxyalkanoic acid herbicides. The example is a general formula for phenoxyacetic acids that include 2,4-D and MCPA. Others are phenoxypropionic acids such as CMPP and phenoxybutyric acids such as 2,4-DB). All of them regulate plant growth and resemble indoleacetic acid, a natural growth regulator.
        • FIGURE 1.9 Warfarin and related compounds such as diphenacoum and brodifacoum, are anticoagulant rodenticides. They are complex molecules bearing some structural resemblance to vitamin K. Their toxic actions arise from competition with vitamin K in the liver (vitamin K antagonism).
      • 1.2.12 Anticoagulant Rodenticides
      • 1.2.13 Detergents
      • 1.2.14 Chlorophenols
        • FIGURE 1.10 Detergent molecules contain both polar and nonpolar elements. They may have permanent negative charges (anionic detergents), permanent positive charges (cationic detergents), or a collection of small positive and negative charges over their structures (nonionic detergents).
        • FIGURE 1.11 Chlorinated phenols have acidic properties; they release H+ ions when they dissolve in water. They can interact to form dioxin (see Section 1.2.3).
        • FIGURE 1.12 17A-Ethinylestradiol (EE2) is a potent synthetic estrogen bearing a structural resemblance to estradiol.
      • 1.2.15 Ethinylestradiol (EE2)
      • 1.2.16 Pharmaceuticals
    • 1.3 Organometallic Compounds
    • 1.4 Radioactive Isotopes
      • 1.4.1 Introduction
      • 1.4.2 Natures and Intensities of Radioactive Decay Products
      • 1.4.3 Half-Lives
      • 1.4.4 Biochemistry
        • TABLE 1.4 Half-Lives of Some Radioactive Isotopes
    • 1.5 Gaseous Pollutants
    • 1.6 Nanoparticles
    • 1.7 Summary
    • Further Reading
  • 2 Routes by which Pollutants Enter Ecosystems
    • 2.1 Entry into Surface Waters
      • TABLE 2.1 Major Routes of Entry to Surface Waters
      • FIGURE 2.1 Conventional treatment of sewage by the activated sludge process. The top of diagram illustrates typical stages in sewage treatment. The lower figure indicates the quality of sewage at different stages of treatment.
    • 2.2 Contamination of Land
      • TABLE 2.2 Major Routes of Land Contamination
    • 2.3 Discharge into Atmosphere
      • TABLE 2.3 Major Points of Entry into Atmosphere
      • FIGURE 2.2 Inversion effects in air pollution.
      • TABLE 2.4 Gaseous Pollutants Released Globally (Tons per Year)
    • 2.4 Quantification of Release of Pollutants
    • 2.5 Summary
    • Further Reading
  • 3 Long-Range Movements and Global Transport of Pollutants
    • 3.1 Factors Determining Movements and Distributions of Pollutants
      • 3.1.1 Polarity and Water Solubility
        • FIGURE 3.1 Water molecule.
        • FIGURE 3.2 Effects of poisonous effluent on a river. Quantity (vertical axis) is the concentration of chemical or number of individuals per unit volume in water.
      • 3.1.2 Partition Coefficients
        • TABLE 3.1 Properties of Pollutants
      • 3.1.3 Vapor Pressure
      • 3.1.4 Partition between Environmental Compartments
      • 3.1.5 Molecular Stability and Recalcitrant Molecules
    • 3.2 Transport in Water
      • FIGURE 3.3 Deep water circulation in the oceans. Thick lines = major bottom currents; thin lines = return flows.
    • 3.3 Transport in Air
      • FIGURE 3.4 Idealized global circulation of air
    • 3.4 Models for Environmental Distribution of Chemicals
      • FIGURE 3.5 States of the compartments at two different times. In A, the two insecticides are present only in water. In B, they have moved from water into all the neighboring compartments to achieve equilibrium. The arrows indicate direction of movement in accordance with fugacity values. Thus A shows only movement away from the water compartment. B shows equal movements in all directions of all phase boundaries because the system is in equilibrium. The number of moles (gram molecular weights) is indicated for the two insecticides. The major difference between the two compounds in distribution is the greater tendency for sulfotep to escape from water to air. It has a higher vapor pressure (measure of fugacity). S = sulfotep. C = chlorfenvinphos. fs and fc= fugacities of sulfotep and chlorfenvinphos, respectively. Long arrows indicate fs; short ones indicate f.
    • 3.5 Summary
    • Further Reading
  • 4 The Fate of Metals and Radioactive Isotopes in Contaminated Ecosystems
    • 4.1 Introduction
      • 4.1.1 Localization
      • 4.1.2 Persistence
        • FIGURE 4.1 Comparison of distribution of metals in (A) disused mine site rehabilitated by application of uncontaminated topsoil and (B) site subject to aerial contamination.
      • 4.1.3 Bioconcentration and Bioaccumulation Factors
      • 4.1.4 Bioavailability
      • 4.1.5 Cocktails of Inorganic Pollutants
    • 4.2 Terrestrial Ecosystems
      • 4.2.1 Introduction
      • 4.2.2 Metals
        • FIGURE 4.2 (A) Parys Mountain, Anglesey, north Wales. During the early nineteenth century, this was the largest copper mine in the world. Mining ceased about 100 years ago, but recolonization by vegetation has been slow because of the very high concentrations of copper in surface soils. (B) Rehabilitation of mining waste at a disused copper mine in the Gusum area in Sweden. The spoil tip is being capped with an impermeable layer before landscaping with a 2-m layer of topsoil on which trees will be planted.
        • FIGURE 4.3 Concentrations of cadmium (mg/kg dry weight) in Hallen Wood soil profiles from 1975 through 1987. Hallen Wood is 3 km northeast of a primary cadmium, lead, and zinc smelting works at Avonmouth, southwest England. Each value for the mineral soil represents an analysis of a block of soil collected at depths of 0 to 1 cm and then at 2.5-cm intervals to the final depth. The profiles show two main features (i) a reduction over time in concentration in the litter (L), primary (F), and secondary (H) layers; (ii) a progressive wave of cadmium moving down the profile. The increased mobility of cadmium arose from increased acid deposition in the woodland following construction of a tall chimney at a sulfuric acid plant at the smelting works in the mid-1970s.
      • 4.2.3 Radioactivity
    • 4.3 Aquatic Systems
      • FIGURE 4.4 (A) Distribution of radioactive cesium in surface soils of Byelorussia after the Chernobyl accident. (B) Areas of Byelorussia where mushroom gathering is restricted.
      • FIGURE 4.5 Activity concentrations of 137Cs in reindeer from the Saami community, Vilhelmina Norra, Sweden, from 1986 to 1992. Mean ± standard deviation from separate slaughter occasions (n = 10 to 825 animals).
      • FIGURE 4.6 Mercury (Hg) distribution in sediments of the Paraiba do Sul river, estuary, and adjacent continental shelf, Rio de Janeiro State, southeast Brazil.
    • 4.4 Summary
      • FIGURE 4.7 Mercury concentrations in bed sediments of the Yatsushiro Sea (1975) and Minimata Bay (1973) in Japan.
      • FIGURE 4.8 Variations in outlet water pH and concentrations of zinc in Lake, Holmeshultasjön, Sweden over time. Note the close relationship between pulses of lower pH in the lake and increased levels of dissolved zinc.
      • FIGURE 4.9 (A) Variations in annual quantities of 137Cs discharged from the Sellafield nuclear fuel reprocessing plant over time. (B) 137Cs concentration profiles for Solway Firth salt marsh sediment sections S1 and S2, north of Sellafield.
    • Further Reading
  • 5 Fates of Organic Pollutants in Individuals and in Ecosystems
    • 5.1 Fate within Individual Organisms
      • 5.1.1 General Model
        • FIGURE 5.1 General model describing fates of lipophilic xenobiotics in living organisms.
        • TABLE 5.1 Major Routes of Uptake for Organic Pollutants
      • 5.1.2 Processes of Uptake
        • FIGURE 5.2 Passive diffusion of xenobiotics across a biological membrane. They move through the membrane into water on other side.
        • FIGURE 5.3 Equilibrium of weak acid.
      • 5.1.3 Processes of Distribution
      • 5.1.4 Storage
      • 5.1.5 Metabolism
        • TABLE 5.2 Enzymes that Metabolize Lipophilic Xenobiotics (Phase I)
        • FIGURE 5.4A Phase I biotransformations. MO = microsomal monooxygenase.
        • FIGURE 5.4B
        • BOX 5.1 ARYL HYDROCARBON (AH) RECEPTOR-MEDIATED TOXICITY
        • FIGURE 5.5 Relative monooxygenase activities of mammals, birds, and fish. (A) Mammals and birds.
        • FIGURE 5.6 Phase II biotransformations.
        • TABLE 5.3 Enzymes that Metabolize Xenobiotics (Phase II)
      • 5.1.6 Sites of Excretion
        • FIGURE 5.7 Excretion in bile. Transverse section of liver cell showing bile canaliculus.
        • FIGURE 5.8 Excretion routes of anionic conjugates.
      • 5.1.7 Toxicokinetic Models
        • FIGURE 5.9 Kinetics of uptake and loss. When an animal is continually dosed with a chemical, the log concentration increases until a steady state is reached. When dosing stops, the log concentration falls linearly over time if first-order kinetics apply (as in a one-compartment model).
        • FIGURE 5.10 Kinetics of loss. (A) Rate of loss of chemical is proportional to tissue concentration. (B) Tissue concentration of chemical falls exponentially over time. (C) Log of tissue concentration of pollutant falls linearly over time. C = tissue concentration. t = time (minutes or hours). t50 = half-life. x = initial tissue concentration.
      • 5.1.8 Toxicokinetic Models for Bioconcentration and Bioaccumulation
        • FIGURE 5.11 Bioconcentration factors and Kow values.
        • TABLE 5.4 Model System for Bioaccumulation of Lipophilic Pollutants
    • 5.2 Organic Pollutants in Terrestrial Ecosystems
      • 5.2.1 Fate in Soils
        • FIGURE 5.12 Fates of pollutants in soil.
      • 5.2.2 Transfer along Terrestrial Food Chains
        • FIGURE 5.13 Loss of pesticides from soil.
        • TABLE 5.5 Persistence of Organochlorine Insecticides in Soils
        • FIGURE 5.14 Organochlorine insecticides in British birds.
        • FIGURE 5.15 Organochlorine insecticides in the Farne Island ecosystem.
    • 5.3 Organic Pollutants in Aquatic Ecosystems
      • 5.3.1 Pollutants in Sediments
      • 5.3.2 Transfer along Aquatic Food Chains
    • 5.4 Summary
    • Further Reading
• Section II Effects of Pollutants on Individual Organisms
  • 6 Testing for Ecotoxicity
    • 6.1 General Principles
      • FIGURE 6.1 Toxicity after 96-hour exposure in an aquatic toxicity test. Note that NOEC can be determined only where LOEC is known; otherwise there would be no indications of toxic concentrations. NOEC = no-observed-effect concentration. LOEC = lowest-observed-effect concentration. LC50 = median lethal concentration at 96 hours.
      • TABLE 6.1 Selective Toxicities of Some Pesticides
      • FIGURE 6.2 Plot of standardized normal frequency distribution (P) with its integral, the cumulative normal frequency function (z).
    • 6.2 Determination of Toxicities of Mixtures
    • 6.3 Toxicity Testing with Terrestrial Organisms
      • 6.3.1 Introduction
      • 6.3.2 Invertebrate Testing
        • 6.3.2.1 Testing with Earthworms
          • BOX 6.1 OECD EARTHWORM TOXICITY TEST
          • FIGURE 6.3 (A) Group of earthworms (Eisenia fetida) in standard OECD soil. Adults are approximately 8 cm in length. (B) Juvenile Eisenia fetida emerging from a cocoon approximately 2 mm in diameter.
          • FIGURE 6.4 Rate of cocoon production by Eisenia fetida exposed to (A) cadmium, (B) lead, (C) copper, and (D) zinc (μg/g dry weight). Bars with the same number of asterisks (*) were not significantly different at P < 0.05.
        • 6.3.2.2 Tests with Springtails
        • 6.3.2.3 Tests with Beneficial Arthropods
          • FIGURE 6.5 Adult and juvenile Folsomia candida, a parthenogenetic springtail. The largest specimen is 2 mm in length.
          • FIGURE 6.6 Folsomia candida with a batch of eggs.
          • BOX 6.2 TEST ON SPRINGTAILS
          • FIGURE 6.7 Total numbers of Folsomia candida individuals at different levels of cadmium in artificial soil. Blank (N), 34.8 (c), 71.3 (▵), 148 (▪), 326 (○), 707 (▴), and 1491 ( , ) μg Cd/g dry weight.
        • 6.3.2.4 Automated Videotracking
          • BOX 6.3 TOXICITY TESTS WITH BEES
      • 6.3.3 Vertebrates
        • FIGURE 6.8 Determination of LD50. For details, see text.
      • 6.3.4 Plants
        • TABLE 6.2 Tolerance of Three Grass Species from Hallen Wood Contaminated by Aerial Deposition from Smelting and from Uncontaminated Midger Wood
    • 6.4 Toxicity Testing with Aquatic Organisms
      • 6.4.1 Tests for Direct Absorption from Water
        • FIGURE 6.9 Relationship of LC50 to exposure period.
        • FIGURE 6.10 Determination of LC50. For details, see text.
        • BOX 6.4 Daphnia Reproduction Test
        • BOX 6.5 ALGAL TOXICITY TEST
        • BOX 6.6 Sediment Toxicity Text Using Rhephoxynius abronius
      • 6.4.2 Sediment Toxicity Tests
    • 6.5 Risk Assessment
      • FIGURE 6.11 Organisms used in aquatic ecotoxicity testing. (A) Daphnia magna 2 mm in length. (B) Chironomid larvae 1 cm in length.
    • 6.6 Field Testing for Toxicity
      • BOX 6.7 FIELD STUDY TO ASSESS ENVIRONMENTAL EFFECTS OF 137CS ON BIRDS
    • 6.7 Alternative Methods in Ecotoxicity Testing
      • 6.7.1 Alternative Methods for Estimating Toxicity to Vertebrates
        • 6.7.1.1 Toxicity Testing on Live Vertebrates
        • 6.7.1.2 Toxicity Testing on Nonvertebrates
        • 6.7.1.3 Toxicity Testing on Cellular Systems
        • 6.7.1.4 Predictive Models
      • 6.7.2 Alternative Approaches toward More Ecological End Points
        • 6.7.2.1 Field Studies
          • BOX 6.8 QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSARS)
        • 6.7.2.2 Microcosms and Mesocosms
        • 6.7.2.3 Theoretical Models
    • 6.8 Summary
    • Further Reading
  • 7 Biochemical Effects of Pollutants
    • 7.1 Introduction
      • TABLE 7.1 Protective and Nonprotective Responses to Chemicals
      • FIGURE 7.1 Pathways of activation and detoxification of chemicals.
      • FIGURE 7.2 Mechanism of DNA repair after adduct formation to remove covalently bound adduct.
      • TABLE 7.2 Specificities of Responses
    • 7.2 Protective Biochemical Responses
    • 7.3 Molecular Mechanisms of Toxicity
      • FIGURE 7.3 Mechanism of action of AChE. Under normal conditions, acetylcholine binds to acetylcholinesterase and is broken down (hydrolyzed) to yield acetic acid and choline that break away from the enzyme. Organophosphates bind to hydroxyl groups belonging to the serine amino acid, which is part of the binding site shown on the right side of the enzyme surface. When this happens, the enzyme is inhibited and can no longer hydrolyze acetylcholine.
    • 7.4 Examples of Molecular Mechanisms of Toxicity
      • 7.4.1 Genotoxic Compounds
      • 7.4.2 Neurotoxic Compounds
        • FIGURE 7.4 Sodium channels and GABA receptors.
        • FIGURE 7.5 Cross section of a mitochondrion showing mitochondrial poison reaction. Protons (H+) are actively transported from the matrix across the inner membrane via electron flow along the electron transport chain. These protons can then flow back to the matrix via the ATP synthetase enzyme; the associated energy is used to synthesize ATP in the matrix. Uncouplers such as 2,4-dinitrophenol can carry these protons to the matrix before ATP synthesis occurs. Other poisons, for example, rotenone and CN–, can inhibit the flow of electrons along the transport chain.
      • 7.4.3 Mitochondrial Poisons
      • 7.4.4 Vitamin K Antagonists
      • 7.4.5 Thyroxine Antagonists
      • 7.4.6 Inhibition of ATPases
      • 7.4.7 Environmental Estrogens and Androgens
        • FIGURE 7.6 Mechanism of toxicity of a polychlorinated biphenyl. Retinol binds to retinol-binding protein (RBP) that is then attached to transthyretin (TTR). Thyroxine (T4) binds to TTR and is transported via the blood in this form. The coplanar PCB 3,3′,4,4′-tetrachlorobiphenyl (3,3′,4,4′-TCB) is converted into hydroxymetabolites by the inducible cytochrome P450 called P450 1A1. The metabolite 4′-OH-3,3′,4,5′-tetrachlorobiphenyl (TCBOH) is structurally similar to thyroxine and strongly competes for thyroxine binding sites. The consequences are the loss of thyroxine from TTR, the fragmentation of the TTR–RBPr complex, and the loss of both thyroxine and retinol from blood.
      • 7.4.8 Reactions with Protein Sulfhydryl (SH) Groups
      • 7.4.9 Photosystems of Plants
      • 7.4.10 Plant Growth Regulator Herbicides
    • 7.5 Summary
    • Further Reading
  • 8 Physiological Effects of Pollutants
    • 8.1 Introduction
    • 8.2 Effects of Pollutants at Cellular Level
      • FIGURE 8.1 Relationship between complexities and sizes of natural systems and compartments (black circles) and typical response times to pollutant insults.
      • FIGURE 8.2 Three pathways of detoxification of metals from digestive fluids by the B and S cells of the hepatopancreas of the woodlouse Porcellio scaber. M = metallothionein. S3 = sulfydryl group.
      • FIGURE 8.3 Three pathways of detoxification of metals from digestive fluids by the digestive cells in the hepatopancreas of the woodlouse-eating spider Dysdera crocata. M = metallothionein.
      • FIGURE 8.4 (A) Dysdera crocata attacking a specimen of Porcellio scaber 1 cm in length. (B) Scanning transmission electron micrograph (bright-field image) of unstained resin-embedded section (0.5 µm thick) through two type A calcium phosphate granules in a digestive cell of the hepatopancreas of D. crocata. Diameter of each granule section = 1 µm. Electron-generated x-ray maps for phosphorus (C), calcium (D), zinc (E), and iron (F) of the type A granules shown in (B). Philips CM12 STEM, EDAX 9900 x-ray analyzer, screen resolution 256–200 pixels, dwell time on each pixel 50 ms, spot diameter 20 nm.
    • 8.3 Effects at Organ Level in Animals
      • BOX 8.1 DETOXIFICATION PATHWAYS OF METALS
      • FIGURE 8.5 Concentrically structured type A granule from the hepatopancreas of the woodlouse-eating spider Dysdera crocata (diameter 2 µm)
      • FIGURE 8.6 Salt and water transport in a saltwater fish.
      • FIGURE 8.7 Light micrographs of B cells (B) and S cells (S) within the hepatopancreas of two specimens of woodlouse Oniscus asellus 6 weeks after release from the same brood pouch of a female from an uncontaminated woodland. The S cells of the juvenile reared on leaf litter contaminated with metal pollutants from a woodland near to a smelting works (2) contain far more metal-containing granules (g) than the S cells of the juvenile reared on uncontaminated litter (1). h = haemocoel; lip = lipid; lum = lumen of hepatopancreas tubule. Scale bars: 20 µm.
    • 8.4 Effects at Whole Organism Level
      • 8.4.1 Neurophysiological Effects
        • FIGURE 8.8 Neurons and synapses.
      • 8.4.2 Effects on Behavior
        • FIGURE 8.9 Components of foraging behavior.
        • FIGURE 8.10 Differences in percentages of seeds dropped between dosing days and control days plotted against brain acetylcholinesterase activity in house sparrows. A through D show results in successive 1.5-hour time bins after dosing. Doses are shown in the key.
        • FIGURE 8.11 Body weight loss in relation to percentage food items dropped by birds in Figure 8.10.
        • BOX 8.2 FOREST SPRAYING IN NEW BRUNSWICK, CANADA
      • 8.4.3 Reproductive Effects
        • FIGURE 8.12 Mechanisms by which endocrine disruptors affect the reproduction and survival of wildlife.
        • FIGURE 8.13 Correlation between median molecular length (inversely proportional to strand breaks) and fecundity of mosquitofish collected from a radionuclide-contaminated pond. (A) Total strand breaks (liver). (B) Double-strand breaks (liver).
    • 8.5 Effects on Plants
    • 8.6 Energy Costs of Physiological Change
      • FIGURE 8.14 Energy–nutrient allocation diagram illustrating scope for growth.
      • FIGURE 8.15 Effects of TBT (tributyl tin) on scope for growth (SFG) in Mytilus edulis mussels.
      • FIGURE 8.16 (A) Concentration of detoxifying enzyme E4 in seven strains of the Myzus persicae aphid in relation to the number of copies of a structural gene hypothetically present in each strain. (B) Mortality rates of three strains in relation to E4 concentration. Aphids were placed on potato leaves dipped in an organophosphorous insecticide (Demeton-S-methyl).
      • FIGURE 8.17 (A) Initial peak levels and final steady-state levels of Cu and Pb in the bodies of springtails in relation to levels in nutrient broth. (B) Growth rate (reciprocal of time to first reproduction) and mortality rate (calculated from survivorship over first 10 weeks of life). (C) Mortality rate in relation to final steady-state levels of metals in the bodies. Mortality must increase at very low levels as the animals then suffer from copper deficiency.
    • 8.7 Summary
      • FIGURE 8.18 Likely form of trade-off between production rate and mortality rate that may constrain the operation of detoxification mechanisms. Allocation of resources to defense reduces mortality rate and simultaneously cuts growth rate.
    • Further Reading
  • 9 Interactive Effects of Pollutants
    • 9.1 Introduction
      • FIGURE 9.1 PCB congeners in tissues of marine organisms [mussels (Macoma baltica) and harbor seals (Phoca vitulina)] from the Dutch Wadden Sea. The compounds were separated, identified, and quantified by capillary gas chromatography. Each of the numbered peaks represents a PCB congener. HCB (hexachlorobenzene) served as an internal standard.
      • TABLE 9.1 Examples of Synergism
    • 9.2 Additive Effects
    • 9.3 Potentiation of Toxicity
      • FIGURE 9.2 Potentiation of toxicity. The vertical axis indicates the degree of toxic effect of the compound, and the horizontal axis represents the composition of the mixture. The maximum doses of compounds A and B both yielded the same degree of toxic response X. Potentiation occurs when the toxicity of a mixture of two compounds exceeds the total toxicities of the individual components.
      • FIGURE 9.3 Additive toxicity and potentiation. In (1), compounds A and B produce a linear response over the dose range 0 to 4. If toxicity is simply additive, the response to 1 mg/kg A + 1 mg/kg B is intermediate between the responses to 2 mg/kg A and 2 mg/kg B. If potentiation occurs, the response to the combination will be higher than is shown for the additive response. In (2), the response to A is linear and the response to B is nonlinear; the additive response to 2 mg/kg A + 2 mg/kg B is greater than in (1). This demonstrates that linearity cannot be assumed for individual response curves. If, in this case, dose–response curves were known only up to 2 mg/kg for A and for B and the response to 2 mg/kg A + 2 mg/kg B were as shown, it might be wrongly assumed that potentiation occurred. To establish that potentiation occurred, the dose–response curves for compounds A and B must be determined for doses above those used in combination.
    • 9.4 Potentiation Due to Inhibition of Detoxification (Box 9.1)
      • BOX 9.1 TWO EXAMPLES OF POTENTIATION FROM INHIBITION OF DETOXIFICATION
      • FIGURE 9.4 Metabolism of permethrin. Permethrin is detoxified by two systems. Monooxygenase attacks both acid and alcohol moieties. The B esterase system breaks the carboxyester bonds. Inhibitors of monooxygenase can increase the toxicities of permethrin and other pyrethroids.
      • FIGURE 9.5 Metabolism of malathion. Malathion is detoxified by the action of a carboxyesterase but activated by monooxygenase. Toxicity depends on the relative importance of these competing enzymes. Chemicals that induce the monooxygenase system can make malathion more toxic.
    • 9.5 Potentiation from Increased Activation
    • 9.6 Field Detection of Potentiation
      • BOX 9.2 TWO EXAMPLES OF POTENTIATION FROM INCREASED ACTIVATION
    • 9.7 Summary
    • Further Reading
  • 10 Biomarkers
    • 10.1 Classification of Biomarkers
      • TABLE 10.1 Biomarkers at Different Organizational Levels
      • FIGURE 10.1 Specificity and ecological relevance of biochemical effects measurements.
    • 10.2 Specificity of Biomarkers
      • FIGURE 10.2 Relationship of exposure to pollutants, health status, and biomarker responses. Upper curve shows the progression of the health status of an individual as exposure to pollutant increases. h = Point at which departure from normal homeostatic response range is initiated; c = limit at which compensatory responses can prevent development of overt disease; r = limit beyond which the pathological damage is irreversible by repair mechanisms. The lower graph shows responses of five hypothetical biomarkers used to assess the health of the individual.
      • TABLE 10.2 Biomarkers Listed by Decreasing Specificities to Pollutants
    • 10.3 Relationship of Biomarkers to Adverse Effects
      • TABLE 10.3 Biomarkers Listed by Decreasing Specificities of Adverse Effects
    • 10.4 Specific Biomarkers
      • 10.4.1 Inhibition of Esterases
      • 10.4.2 The Induction of Monooxygenases
      • 10.4.3 Studies of Genetic Materials
      • 10.4.4 Porphyrins and Heme Synthesis
      • 10.4.5 Induction of Vitellogenin
      • 10.4.6 Behavioral Biomarkers
        • BOX 10.1 INDUCTION OF VITELLOGENIN IN FISH
      • 10.4.7 Biomarkers in Plants
    • 10.5 Role of Biomarkers in Environmental Risk Assessment
    • 10.6 Summary
    • Further Reading
  • 11 In Situ Biological Monitoring
    • 11.1 Introduction
    • 11.2 Community Effects (Type 1 Biomonitoring)
      • FIGURE 11.1 Schematic graphs to illustrate a principle of in situ biological monitoring of pollution. In this hypothetical example, the re-sponses R (as measured by concentrations or effects of the pollutant on the y axis) of species “a” (A) and “b” (B) in sites with different levels of contamination are not closely related to concentrations of the pollutant (x axis) in abiotic samples (soil, air, water sediment) from the same sites. Because the relationship between species in the same sites is much closer (C), the responses of species “a” to the pollutant can be used to predict the responses of species “b” more accurately than similar predictions from abiotic samples (see Figures 11.5 and 11.6 for data that support this hypothesis).
      • 11.2.1 Terrestrial Ecosystems
      • 11.2.2 Freshwater Ecosystems
        • FIGURE 11.2 Cover (as percentage of type maximum) of foliose (—), fruticose (− − −), and crustose (–·–) corticolous lichens in eight permanent quadrates set up on broad-leaved trees within 1 km of the aluminum works in Anglesey, North Wales, from 1970 to 1985.
        • BOX 11.1 THE USE OF THE BMWP SCORE TO ASSESS THE HEALTH OF FRESH WATERS
        • FIGURE 11.3 Abundance of (A) total Collembola, (B) Onychiurus armatus (Collembola), and (C) Isotoma olivacea (Collembola) in the 0- to 3-cm layer in lead-contaminated soils in the vicinity of a natural metalliferous outcrop in a Norwegian spruce forest. The concentrations of lead represent metal extracted from soil over 18 h in 0.1 M buffered acetic acid. Note that O. armatus is sensitive to lead pollution, whereas I. olivacea reached higher population densities in contaminated soils.
        • TABLE 11.1 Biological Banding of Average Score per Taxon (ASPT), Number of Taxa, and Biological Monitoring Working Party Score (BMWP) Based on Sampling for Three Seasons
      • 11.2.3 Marine Ecosystems
    • 11.3 Bioconcentration of Pollutants (Type 2 Biomonitoring)
      • 11.3.1 Terrestrial Ecosystems
        • FIGURE 11.4 Radiocesium (134Cs and 137Cs) activity from 1987 to 1989 in goat milk during the grazing seasons from 15 June to 15 September in the Jotunheimen mountain range (mean ± SE, three to eight animals in 1987 and eight in 1988 and 1989).
      • 11.3.2 Freshwater Ecosystems
      • 11.3.3 Marine Ecosystems
        • FIGURE 11.5 Relationships between concentrations of cadmium (dry weight) in the terrestrial isopods (woodlice) Oniscus asellus (A) and Porcellio scaber (B) and soil, and between the two species (C) collected from sites in Avon and Somerset, southwest England in 1998 and 1989. The region includes a primary zinc, cadmium, and lead smelting works and disused zinc mining areas. Each point represents the mean of twelve isopods and six samples of soil from each site. Note that the concentrations of cadmium in P. scaber in this region can be predicted more accurately from the concentrations in O. asellus (C) than from levels in soil (B).
        • FIGURE 11.6 Relationships between concentrations of cadmium (dry weight) in the snail Helix aspersa and soil (A) and Oniscus asellus (B) collected from the same region as in Figure 11.5. Each point represents the mean of seven snails, twelve woodlice, or six samples of soil from each site. Note that the concentrations of cadmium in H. aspersa can be predicted more accurately from the concentrations in O. asellus (B) than from levels in soil (A).
        • FIGURE 11.7 Concentrations of PCB in eggs of herring gulls from Muggs Island/Leslie Spit colonies, Lake Ontario, 1974–1997.
    • 11.4 Effects of Pollutants (Type 3 Biomonitoring)
      • 11.4.1 Terrestrial Ecosystems
      • 11.4.2 Freshwater Ecosystems
      • 11.4.3 Marine Ecosystems
        • BOX 11.2 IMPOSEX IN DOG WHELK
        • FIGURE 11.8 Levels of relative penis size index (RPSI) (percentage size of female penis relative to males) in dog whelks (Nucella lapillus) collected from southwest England in 1984–1985. Imposex develops in females in response to TBT leached from antifouling paints and is most prevalent in areas of high boating activity (e.g., the Looe and Yealm estuaries).
    • 11.5 Genetically Based Resistance to Pollution (Type 4 Biomonitoring)
    • 11.6 Conclusions
    • 11.7 Summary
    • Further Reading
• Section III Effects of Pollutants on Populations and Communities
  • 12 Changes in Numbers: Population Dynamics
    • FIGURE 12.1 Possible responses of population size to pollution.
    • 12.1 Population Abundance
    • 12.2 Population Growth Rate
    • 12.3 Population Growth Rate Depends on the Properties of Individual Organisms
      • BOX 12.1 DIFFERENT WAYS OF ASSESSING POPULATION GROWTH
      • FIGURE 12.2 General life history. t1, t2, t3, ... represent the ages at which the organism breeds; n1, n2, n3, ... are the number of offspring then produced by each breeding female.
      • 12.3.1 The Life History and Population Growth Rate of the Coastal Copepod Eurytemora affinis
        • FIGURE 12.3 Effect of dieldrin on the life history of Eurytemora affinis. (A) Survivorship curves. These show for each treatment the proportion of animals that survive from birth to each age. Numbers indicate treatments, i.e., concentrations of dieldrin, in μg l−1. C is the acetone control. (B) Birth rate in relation to age. Birth rate was measured at all concentrations, but only two representative concentrations, 2 and 4 μg l−1, are shown here (upper and lower graphs, respectively).
        • FIGURE 12.4 Effects of dieldrin concentration in E. affinis. (A) Effects on mortality rate, birth rate, and development period (age at first reproduction) estimated as described in the text. (B) Reductions in population growth rate, r, caused by the effects shown in (A).
        • FIGURE 12.5 Contour plots of population growth rate for two species of grain beetle, Sitophilus oryzae (− − −) and Rhizopertha dominica (——). Contours are here labeled in terms of population growth rate; net reproductive rate was used in the original.
    • 12.4 Density Dependence
      • FIGURE 12.6 Density dependence in Daphnia pulex.
      • FIGURE 12.7 The sigmoidal growth curve that results from the logistic Equation 12.7. K is the carrying capacity of the environment.
    • 12.5 Identifying Which Factors Are Density Dependent: K-Value Analysis
      • FIGURE 12.8 Sea trout mortalities K1–K5, in relation to population density in each of the five periods depicted in Figure 12.9. Thus (A) refers to alevin, (B) to young parr, and so on. Population densities S, R1, ..., R4 are defined in Figure 12.9; K1–K5 were calculated for the periods shown in Figure 12.9 using Equation 12.8. Each datum point refers to a single year.
      • FIGURE 12.9 The life history of the sea trout at a stream in northwest England. The eggs hatch after about 5 months. The young trout are known as alevin from hatching until they resorb their yolk sacs; after this they are known as parr. Population density at each age was measured by electric fishing and designated S, R1, R2, ... as shown.
    • 12.6 Interactions between Species
    • 12.7 Field Studies: Three Case Studies
      • 12.7.1 The Decline of the Partridges
        • FIGURE 12.10 (A) The UK Game Conservancy's National Game Census March pair counts for the partridge from 1933 to 1985, with estimated minimum densities for the early 1930s ± 2 standard errors. (B) The trend in density of breeding pairs km−2 over the period 1952–1985 in various regions of the world range.
        • TABLE 12.1 Comparison of Mortality Rates (K-Values) in Stable and Declining Populations ± Standard Errorsa
        • FIGURE 12.11 Annual chick mortality in relation to the density of preferred insects in the third week of June.
        • FIGURE 12.12 Trend in herbicide use on cereals.
        • TABLE 12.2 Summary of Estimates of Partridge Chick Mortality Rates Grouped According to Herbicide and Insecticide Use
        • FIGURE 12.13 Dependence of nest losses on nesting density with and without gamekeepers.
        • FIGURE 12.14 Simulations of the Sussex partridge population showing the actual decline, the less severe decline that would have occurred if gamekeepers had been employed at 1968 levels, and how no decline would have occurred if gamekeepers had been employed and pesticides had not been used.
        • TABLE 12.3 Population Trends of Selected Species of Birds in the UK
        • TABLE 12.4 Some of the Surveys Undertaken by the British Trust for Ornithology (BTO)
      • 12.7.2 Population Studies of Pesticides and Birds of Prey in the UK
        • FIGURE 12.15 The decline in peregrine eggshell thickness that commenced in the UK in 1947. Shaded areas represent 90% confidence limits. The eggshell thickness index is defined as index = weight of eggshell (mg)/length × breadth (mm).
        • FIGURE 12.16 In sparrowhawks, (A) DDE is negatively correlated with shell thickness, and (B) eggshell thickness is positively correlated with the percentage of young raised per brood (fledgling success).
        • FIGURE 12.17 Peregrine population size in Britain (1930–1939 = 100) showing the 1961 population decline and subsequent recovery, together with an outline of pesticide usage.
        • FIGURE 12.18 Changes in the status of sparrowhawks in relation to agricultural land use and organochlorine use. The agricultural map (left) indicates the proportion of tilled land, where almost all pesticide is used. The sparrowhawk map (right) shows the status of the species in different regions and time periods. Zone 1, sparrowhawks survived in greatest numbers through the height of the organochlorine era around 1960; population decline judged at less than 50% and recovery effectively complete before 1970. Zone 2, population decline more marked than in zone 1, but recovered to more than 50% by 1970. Zone 3, population decline more marked than in zone 2, but recovered to more than 50% by 1980. Zone 4, population almost extinct around 1960, and little or no recovery evident by 1980. In general, population decline was most marked, and recovery latest, in areas with the greatest proportion of tilled land (based on agricultural statistics for 1966).
      • 12.7.3 The Boxworth Project (Experimental Analysis of the Effects of Pesticides on Farmland)
        • FIGURE 12.19 Dieldrin (HEOD) levels in the livers of sparrowhawks found dead in the four zones shown in Figure 12.18. HEOD is the active principle of the commercial insecticide dieldrin and accounts for some 80% of the technical product. Broken lines show periods when populations were depleted or decreasing; solid lines show periods when populations were normal or increasing. Population increase occurred when liver levels were less than about 1.0 ppm wet weight.
        • FIGURE 12.20 Number of sparrow hawk carcasses (—–—–) received in a region of eastern Britain, together with concentrations of DDE (− − − − −) and dieldrin (·–·–·–·–·) found in their livers.
        • FIGURE 12.21 Map of the farm at which the Boxworth project was conducted, showing the locations of the fields treated with each pesticide regime.
        • FIGURE 12.22 Efficacy of the Boxworth pesticide regimes on the densities per m2 of (A) the weed grass couch (Elymus repens) in July and (B) the broad-leaved weeds in spring; 1982 and 1983 were baseline years before the pesticide regimes were applied. The dotted lines show spray decision thresholds used in deciding whether to apply pesticides.
    • 12.8 Modeling the Effects of Insecticides on Skylarks for Risk Assessment Purposes
      • FIGURE 12.23 A 2.5 km section of the map used in simulations of the effects of insecticides on skylarks, showing the level of mapping detail. This section shows agricultural land containing individual farm buildings and fields, bordered by a small town (NE) and some wooded areas (SW).
      • FIGURE 12.24 The results of two models of the effects of an insecticide on skylarks. Population abundance is plotted against time for four scenarios (columns), modeled by an agent-based landscape model (ABM, A–D, top row) and modeled by a life history model (E–H, bottom row). In A–D the individual runs are shown, and the thick line represents their mean. In E–H bars indicate standard deviations, and the range over 1,000 simulations is also indicated.
    • 12.9 Summary
    • Further Reading
  • 13 Evolution of Resistance to Pollution
    • 13.1 Chronic Pollution Is Environmental Change
    • 13.2 Evolutionary Processes in Constant Environments
      • FIGURE 13.1 Simple example of an evolutionary process. Axes represent two life history traits. Note that the alleles far from the origin (C–E) have increased in numbers between graph A and graph B, whereas those near the origin (A) have decreased. Graph C shows the per copy rates of increase, i.e., fitnesses, here labeled r. Graph D shows the genetic options set with genotypes obtainable by recombination represented as dots. The boundary of the options set is the trade-off curve (thick line). Graph E shows the optimal strategy (evolutionary outcome), starred. Graph F shows the genetic options that may persist in the population at the end of the evolutionary process. See text for further details.
    • 13.3 The Evolution of Resistance When There Is a Mortality–Production Trade-Off
      • FIGURE 13.2 (A) Genetic options set (shaded) and trade-off curve. (B) Fitness contours. Note that the zero fitness contour goes through the origin. (C) Superimposing (A) and (B) allows identification of the evolutionary outcome as the allele achieving highest fitness.
    • 13.4 Evolutionary Responses to Environmental Changes
      • FIGURE 13.3 The evolutionary outcomes of long-term mortality and production stresses. The straight lines are zero fitness contours.
      • FIGURE 13.4 If the trade-off curves in (A) polluted and (B) unpolluted environments have different shapes, then the evolutionary outcomes (starred) may involve more defense in polluted environments, as shown.
      • TABLE 13.1 Fitness Advantages of Resistant Strains in Environments with or without Pesticidesa
      • FIGURE 13.5 Additive genetic variance in development period and mortality rate increased as predicted after introduction of rice weevils Sitophilus oryzae to a new toxin-rich environment, although the changes were not significant. Units are eggs day–1 female–1 (oviposition rate), 4 days (development period) or 4 × 10–5 (mortality rate). (B) Changes in genetic correlations. Vertical bars represent 95% confidence intervals.
    • 13.5 Monogenic Resistance
      • FIGURE 13.6 Dose–response curves for the mosquito Culex quinquifasciatus tested with permethrin (NRDC 167). Percentage mortality is plotted on a probit scale. SS shows the response of homozygous susceptible individuals, RS of heterozygotes, and RR of homozygous resistant individuals.
    • 13.6 Case Studies
      • 13.6.1 Evolution of Pesticide Resistance
        • TABLE 13.2 Primary Mechanisms of Resistance
        • FIGURE 13.7 The evolution of pyrethroid resistance in cotton budworm, Helicoverpa armigera, in the Namoi–Gwydir cotton-growing region of New South Wales, Australia. The stages of the resistance management program are indicated by roman numerals at the top of the graph. The period of pyrethroid use each year (stage II) is shaded. Percentage resistant refers to the percentage surviving a dose of pyrethroid fenvalerate that killed 99% of susceptibles. Vertical bars are standard errors.
      • 13.6.2 Evolution of Metal Tolerance in Plants
        • FIGURE 13.8 Copper tolerance in the grass Agrostis tenuis along a transect on the surface of a copper mine. The copper-impregnated part of the mine is shaded.
        • TABLE 13.3 Percentage of Copper-Tolerant Individuals in Normal Populations of Grass Species That Are Commonly Found near Mines in Britain in Relation to Whether Copper-Tolerant Populations of These Species Have Been Found on Copper Mines
      • 13.6.3 Evolution of Industrial Melanism
        • FIGURE 13.9 The relative frequencies of the normal and two melanic forms of the peppered moth Biston betularia in Britain. The results are based on more than 30,000 records collected from 1952 to 1970 at 83 sites.
        • FIGURE 13.10 The decline in the frequency of the melanic form of the peppered moth near Manchester after clean-air legislation reduced emissions of smoke and sulfur dioxide.
        • TABLE 13.4 Relative Recoveries of Marked Individuals of Two Forms of the Peppered Moth, Biston betularia (typica and carbonaria) from Two Sites, One Rural and One Industrial
      • 13.6.4 Evolutionary Response of Dog Whelks, Nucella lapillus, to TBT Contamination
      • 13.6.5 Evolution of Resistance to Pollution in Estuaries
        • FIGURE 13.11 The survival of progeny of the mummichog Fundulus heteroclitus in aquaria containing water con-taminated with various concentrations of PCB 126. The fish in the upper graph came from a PCB-contaminated site, New Bedford Harbor; those in the lower graph came from a nearby unpolluted site. Unfilled symbols and light lines represent data from first-generation progeny; second-generation progeny are represented by filled symbols and heavy lines. Bars represent standard errors; each treatment was replicated either two or three times.
    • 13.7 Summary
    • Further Reading
  • 14 Changes in Communities and Ecosystems
    • 14.1 Introduction
    • 14.2 Changes in Soil Processes: The Functional Approach
      • FIGURE 14.1 Carbon cycle.
      • FIGURE 14.2 Nitrogen cycle.
      • FIGURE 14.3 Effect of an herbicide (dichlobenil) on the rate of CO2 production in soil. {14C}-Glucose was added to soil as a carbon source for microorganisms. The addition of the herbicide dichlobenil caused an increase in the rate of release of 14CO2 (derived from {14C}-glucose) over a 22-day period. The rate of 14CO2 release from soil is expressed as the percentage added 14C, which appears in this form.
      • TABLE 14.1 Effects of Pollutants on Nitrification in Soila
    • 14.3 Changes in Compositions of Communities: The Structural Approach
      • 14.3.1 Changes in Soil Ecosystems
        • FIGURE 14.4 Mean abundance of earthworms collected from six 25 × 25 cm quadrants taken at 13 sites along a gradient of contamination in the Avonmouth area and a control (site 14) 100 km from the smelting works (error bars indicate SE values) in April 1996. Worms are absent from the most heavily contaminated sites (1 and 2) and are present in reduced numbers at sites with a medium level of contamination (sites 3–7) in comparison with relatively uncontaminated localities (sites 8–14). Sites sharing the same letter indicate no significant differences at P > 0.05 as given by Tukey's test for the multiple comparison of means.
        • FIGURE 14.5 Dendrograms of earthworm communities at Avonmouth sampled in April 1996 from the sites described in Figure 14.4 ordered by cluster analysis using Euclidean distance and Ward's minimum variance method.
        • TABLE 14.2 Shannon-Weiner Diversity Indices of Earthworm Communities at Avonmouth Sampled during the Period from Spring 1996 to Winter 1997 from the Sites Described in Figure 14.4
      • 14.3.2 Acidification of Lakes and Rivers
        • FIGURE 14.6 The declining catch of Atlantic salmon in acidified rivers (− − −) compared with less polluted rivers (—–). (A) In southernmost Norway: seven acidified rivers compared with the rest of the country. Modified from Leivestad, H., Hendry, G., Muniz, I.P., and Snekvik, E. (1976). Effects of acid precipitation on freshwater organisms. In Brakke, F.H., Ed., Impact of Acid Precipitation on Forest and Freshwater Ecosystems in Norway, pp. 87–111. Research Report FR 6/76. Oslo, SNSF Project. (B) In Nova Scotia: 12 rivers with pH > 5.0 compared with 10 with pH ≤ 5.0 in 1980.
      • 14.3.3 Mesocosms
        • BOX 14.1 STATISTICAL METHODS IN ECOTOXICOLOGY
        • FIGURE 14.7 Change in the community structure of an aquatic mesocosm following application of cypermethrin at a rate of 0.7 g a.i./ha.
    • 14.4 Global Processes
    • 14.5 Summary
    • Further Reading
  • 15 Extrapolating from Molecular Interactions to Consequent Effects at Population Level
    • 15.1 Introduction
    • 15.2 Translation of Toxic Effects across Organizational Boundaries
      • 15.2.1 From Effects at Site of Action to Localized Cellular Disturbances
        • FIGURE 15.1 Responses to pollutants at different levels of biological organization. The threshold tissue concentrations of biological responses for which no response is measurable are indicated by arrows. These thresholds tend to increase with movement toward higher levels of biological organization.
        • 15.2.1.1 Example A: Action of Organophosphates on Acetylcholinesterase of Nervous System
        • 15.2.1.2 Example B: Action of p,p′-DDT on Voltage-Dependent Sodium Channels of Axonal Membranes
          • FIGURE 15.2 The translation of toxic effects across organizational boundaries after exposure to pollutants. Examples A through D are described in Section 15.2 of the text. The use of biomarker assays to monitor the operation of these pathways is discussed in Section 15.2.1. Examples A and C are discussed further in Chapter 16, where they are used to illustrate the use of biomarker strategies in field studies.
        • 15.2.1.3 Example C: Action of p,p′-DDE on Transport of Calcium into Eggshell Glands of Birds
        • 15.2.1.4 Example D: Action of 17A-Ethinylestradiol (EE2) on Estrogenic Receptors of Fish
      • 15.2.2 From Cellular Disturbances to Effects at Whole Organism Level
        • 15.2.2.1 Example A: Actions of Organophosphates on Acetylcholinesterase of Nervous System
        • 15.2.2.2 Example B: Action of p,p′-DDT on Voltage-Dependent Sodium Channels of Axonal Membranes
        • 15.2.2.3 Example C: Action of p,p′-DDE on Transport of Calcium into Eggshell Glands of Birds
        • 15.2.2.4 Example D: Action of 17A-Ethinylestradiol on Estrogenic Receptors of Fish
      • 15.2.3 From Effects on Whole Organism to Population Effects
        • 15.2.3.1 Example A: Actions of Organophosphates on Acetylcholinesterase of Nervous System
        • 15.2.3.2 Example B: Action of p,p′-DDT on Voltage-Dependent Sodium Channels of Axonal Membranes
        • 15.2.3.3 Example C: Action of p,p′-DDE on Transport of Calcium into Eggshell Glands
        • 15.2.3.4 Example D: Action of 17A-Ethinylestradiol on Estrogenic Receptors in Fish
      • 15.2.4 Complete Causal Chain
    • 15.3 Biomarker Strategies
      • 15.3.1 Establishing Causality Where Pollution Already Exists
        • BOX 15.1 USE OF MICROARRAYS TO MEASURE EXPRESSION LEVELS OF GENES INVOLVED IN STRESS RESPONSES
      • 15.3.2 Biomarker Strategies in the Field
      • 15.3.3 Control Problems
      • 15.3.4 Selection of Biomarkers for Field Studies
    • 15.4 Biomarkers and Environmental Risk Assessment
    • 15.5 Summary
    • Further Reading
  • 16 Biomarkers in Population Studies
    • 16.1 DDE-Induced Eggshell Thinning in Raptorial and Fish-Eating Birds
      • FIGURE 16.1 (A) Crushed eggs in the nest of a brown pelican, Anacapa Island, California, 1970. (B) Double-crested cormorant with deformed bill from a colony on Lake Michigan, U.S.
      • FIGURE 16.2 Relationship of eggshell thickness index to DDE residue levels in peregrine eggs collected from Alaska and northern Canada.
      • FIGURE 16.3 Relationship between degree of eggshell thinning and status of populations of peregrines.
    • 16.2 Reproductive Failure of Fish-Eating Birds on Great Lakes of North America
      • FIGURE 16.4 Accumulation of DDT up the Lake Michigan food chain. Values represent total DDT on wet weight basis.
      • FIGURE 16.5 Residue levels of PCBs and DDE (ppm, wet weight) in herring gull eggs from six Great Lake colonies, 1974–1997. Left-hand axis (•) = PCBs. Right-hand axis (×) = DDE.
      • BOX 16.1 HERRING GULL: KEY INDICATOR SPECIES ON GREAT LAKES
      • TABLE 16.1 Egg Exchange Experiments
      • TABLE 16.2 Toxic Equivalency Factors and Dioxin Equivalents of Three Compounds
      • FIGURE 16.6 Relationship between dioxin equivalents and reproductive success in Caspian terns on the North American Great Lakes.
    • 16.3 Reproductive Failures of Mollusks Caused by Tributyl Tin
      • FIGURE 16.7 TBT concentration factors in sediment and organisms from the Itchen Estuary, Southampton (water concentration 67 ng TBT/liter). Figures above bars indicate percent organotin as TBT and half-life following 1987 legislation. Concentration factor = TBT concentration in tissue or sediment (dry weight) divided by TBT in water.
    • 16.4 Forest Spraying in Eastern Canada to Control Spruce Budworm
      • FIGURE 16.8 Map of New Brunswick, Canada, showing the extent of forest spraying (shaded) in 1976.
      • TABLE 16.3 Total Pesticides Used in New Brunswick in Forest Spray Operations, 1952–1996
      • BOX 16.2 LINE TRANSECT FOR MEASURING IMPACTS OF PESTICIDES
      • FIGURE 16.9 Relationship between inhibition of cholinesterase in songbirds and the doses of fenitrothion applied to the forest. The arrow marks the dosage above which effects are seen on songbirds as judged by transect analysis; g.a.i./ha = grams active ingredient per hectare.
    • 16.5 Summary
    • Further Reading
  • 17 Ecotoxicology: Looking to the Future
    • 17.1 Changing Patterns of Chemical Pollution
    • 17.2 Environmental Risk Assessment
    • 17.3 The Use of Models in Population Risk Assessment
    • 17.4 Technological Advances and New Biomarker Assays
    • 17.5 A Better Integrated Approach to Environmental Risk Assessment?
    • 17.6 Ethical Issues
    • 17.7 Summary
    • Further Reading
• Back Matter
  • Glossary
  • Bibliography
  • Index

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