Ecosystems life histories

Davidson AT, Marchant HJ (1992) The biology and ecology of Phaeocystis (Prymnesiophyceae). In Round FE, Chapman DJ (eds) Progress in Phycological Research. Biopress Ltd, Bristol, UK pp 1-45 Eilertsen HC (1989) Phaeocystis pouchetii (Hariot) Lager-heim, a key species in Arctic marine ecosystems Life history and physiology. Rapp P-v Reun Cons int Ex-plor Mer 188 131... 

The proper choice and appHcation of an insecticide for pest control are predicated upon factors, eg, the life history and ecology of the pest, the relation of pest population to economic damage, the effect of the insecticide on the pest or its plant or animal host, related organisms in the ecosystem, and proper timing of the appHcation to prevent illegal residues at harvest and to avoid damaging of bees and other pollinating insects. 

Criteria 1) Relevance to human health endpoints. 2) Sensitivity to change in loadings. 3) Overall historical data quality. 4) Data collection infrastructure. 5) Feasibility of data collection and analysis. 6) Ability to adjust for confounding factors. 7) Understanding of linkages with rest of ecosystem. 8) Broad geographic distribution. 9) Well-known life history (for fauna). 10) Nonintrusive sampling. 

Morphological, behavioural and life-history responses to the chemical presence of kairomones from potential predators are comprehensively surveyed by Lass and Spaak (2003). Phenotypic plasticity that has been intensely studied in freshwater ecosystems is reviewed by Miner et al. (2005) and van Holthoon et al. (2003). Behavioural responses to kairomones are treated by von Elert and Pohnert (2000). 

The last step in the problem formulation phase is the development of an analysis plan or proposal that identifies measures to evaluate each risk hypothesis and that describes the assessment design, data needs, assumptions, extrapolations, and specific methods for conducting the analysis. There are three categories of measures that can be selected. Measures of effect (also called measurement end points) are measures used to evaluate the response of the assessment end point when exposed to a stressor. Measures of exposure are measures of how exposure may be occurring, including how a stressor moves through the environment and how it may co-occur with the assessment end point. Measures of ecosystem and receptor characteristics include ecosystem characteristics that influence the behavior and location of assessment end points, the distribution of a stressor, and life history characteristics of the assessment end point that may affect exposure or response to the stressor. These diverse measures increase in importance as the complexity of the assessment increases. 

Carroll S. 2002a. Population models life history. In Pastorok RA, Bartell SM, Ferson S, Ginzburg LR, editors. Ecological modeling in risk assessment chemical effects on populations, ecosystems, and landscapes. Boca Raton (FL) Lewis Publishers, p 55-64. 

This section describes only the most general attributes of aquatic ecosystems. All ecosystems can be functionally characterized in terms of their processing of energy and their cycling of mass (e.g., carbon and nutrients). These functions, as well as the life history aspects of ecosystems, are discussed in the following subsections. [For a more complete discussion of ecosystems, the reader is referred to several texts, such as Odum (1971), Ricklefs (1990), or Curtis (1983)]. 

The spatial and temporal distributions of ecological components also are considered in ecosystem characterization. Characteristics of ecological components that influence their exposure to the stressor are evaluated, including habitat needs, food preferences, reproductive cycles, and seasonal activities such as migration and selective use of resources. Spatial and temporal variations in the distribution of the ecological component (e.g., sediment invertebrate distribution) may complicate evaluations of exposure. When available, species-specific information about activity patterns, abundance, and life histories can be very useful in evaluating spatial and temporal distributions. 

Even though the Baltic is a young ecosystem, species-poor and vulnerable to the threat of invasive marine and exotic species, both the strong gradient and the rapid change in salinity conditions especially in the southern Baltic inhibit an unhindered colonization. As a result, the Baltic benthic fauna is still largely characterized by species with obvious opportunistic life history traits (Rumohr et al., 1996). 

Another important advantage of employing ecological models in risk assessment is that they provide outputs that are closer to the protection goals of the assessment (i.e., populations, communities, and ecosystems) than other approaches. Application of even very simple population models provides a better measure of response to chemicals than the individual-level endpoints (survival, reproduction, development) most widely in use for risk assessments today, not the least because such models integrate effects on all of the key life-history traits that determine population-level attributes (Forbes and Calow 1999). 

Many of the models simulate the population dynamics of the species often used in ecotoxicological laboratory studies. Often these species are highly relevant for risk assessments, but they are also characterized by life cycles that make them suitable for laboratory culture. Therefore, regulators are sometimes more concerned about other species that are perceived to have life histories that make them more vulnerable or which are thought to be more important for ecosystem functioning. 

Stetter KO (1996) Hyperthermophiles in the history of life. In Bock GR, Goode JA (eds) Ciba Foundation Symposium 202 Evolution of Hydrothermal Ecosystems on Earth (and Mars ). Wiley, Chichester, UK,... 

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