Suchergebnisse

1: Introduction -- 1.1 Inverse problems in population ecology -- 1.2 Copepod mortality rate estimation -- 1.3 The theoretical problems of mortality estimation -- 1.4 Existing methods for mortality estimation -- 1.5 This monograph -- 2: Mortality Estimation Schemes Related to Stage Structured Population Models -- 2.1 Introduction -- 2.2 Preliminaries: mortality estimation for an unstructured population with known birth rate -- 2.3 Mortality estimation for a single stage of known duration -- 2.4 Instabilities associated with mortality estimators -- 2.5 Discussion -- 3: Cubic Splines and Histosplines -- 3.1 Introduction -- 3.2 A brief guide to splines -- 3.3 Cubic splines for exact or noisy histogram data -- 3.4 Choosing the smoothing parameter with covariant error terms -- 3.5 Two examples of the application of cubic area splines to age-structured population data -- 4: Population Surfaces: A New Method of Mortality Estimation -- 4.1 The structured population model -- 4.2 Preliminary estimation of population surface f(?,t) -- 4.3 Characteristics of f(?,t) -- 4.4 Error estimates -- 4.5 What to do about adults -- 4.6 A simpler method -- 4.7 Messy practicalities -- 4.8 Summary -- 5: Tests of the New Method -- 5.1 Parslow and Sonntag's Lag-Manly model method -- 5.2 The method of Hay, Evans and Gamble -- 5.3 Manly's (1987) method -- 5.4 Comparison and testing of the sophisticated and simplified versions of the new method -- 5.5 Discussion -- 6: Loch Ewe Copepods: Some Speculation (Written with S.J. Hay) -- 6.1 The Loch Ewe mesocosm experiments -- 6.2 Stage durations -- 6.3 Modelling sampling error -- 6.4 Death rate patterns for the different copepod species in bag C2: comparison and speculation -- 7: Discussion -- 7.1 What we've done -- 7.2 Experimental suggestions -- 7.3 Production estimation -- 7.4 Methodological improvements -- 7.5 The take home message -- References.

Despite often violent fluctuations in nature, species extinction is rare. California red scale, a potentially devastating pest of citrus, has been suppressed for fifty years in California to extremely low yet stable densities by its controlling parasitoid. Some larch budmoth populations undergo extreme cycles; others never cycle. In Consumer-Resource Dynamics, William Murdoch, Cherie Briggs, and Roger Nisbet use these and numerous other biological examples to lay the groundwork for a unifying theory applicable to predator-prey, parasitoid-host, and other consumer-resource interactions. Thro

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations—where observing outcomes is difficult—versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test endpoints, duration, and study conditions—including ENM test concentrations—that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

This major reference is an overview of the current state of theoretical ecology through a series of topical entries centered on both ecological and statistical themes. Coverage ranges across scales—from the physiological, to populations, landscapes, and ecosystems. Entries provide an introduction to broad fields such as Applied Ecology, Behavioral Ecology, Computational Ecology, Ecosystem Ecology, Epidemiology and Epidemic Modeling, Population Ecology, Spatial Ecology and Statistics in Ecology. Others provide greater specificity and depth, including discussions on the Allee effect, ordinary differential equations, and ecosystem services. Descriptions of modern statistical and modeling approaches and how they contributed to advances in theoretical ecology are also included. Succinct, uncompromising, and authoritative—a "must have" for those interested in the use of theory in the ecological sciences