tailieunhanh - Ecological Modeling in Risk Assessment - Chapter 15

Dân số, hệ sinh thái và cảnh quan các mô hình nói chung là mô hình cơ học dự đoán các biến trạng thái sinh thái bằng cách sử dụng các mối quan hệ toán học để đại diện cho các thành phần và các quá trình trong các hệ thống môi trường. Trong nhiều trường hợp, các biến nhà nước ước tính của các mô hình này là thiết bị đầu cuối có liên quan đánh giá rủi ro sinh thái (ví dụ như, sự phong phú sinh vật sinh khối, tuyển dụng, hoặc tỷ lệ tăng dân số) | CHAPTER 15 Conclusions and Recommendations Robert A. Pastorok and Lev. R. Ginzburg Population ecosystem and landscape models are generally mechanistic models that predict ecological state variables by using mathematical relationships to represent components and processes in environmental systems. In many cases the state variables estimated by these models are relevant endpoints for ecological risk assessment . organism abundance or biomass recruitment or population growth rate . Thus these models are directly applicable in a risk characterization for assessing the significance of estimated risks initially expressed in terms of individual-level endpoints. In this mode ecological models aid in translating risks for individual-level endpoints to more relevant endpoints at higher levels of biological organization. In contrast with population and higher-level models toxicity-extrapolation models are generally nonmechanistic statistical models that attempt to extrapolate as precisely as possible the toxicity of a chemical from one endpoint to another from one species to another or across a whole community of species . by formulating species-sensitivity distributions . Toxicity-extrapolation models may be applied in an effects assessment to support the use of a population ecosystem or landscape model. Currently many ecological risk assessments are limited by a failure to consider population- ecosystem- or landscape-level endpoints. The typical hazard quotient approach compares an exposure estimate to a toxicity threshold for some individual-level endpoints such as organism survival growth or reproduction. Some authors interpret the hazard quotient for individual-level endpoints to infer population-level risks. This approach often leads to an overestimation of risk at the population level but in some cases may lead to an underestimation of population risk. For example in their summary of toxicity test data with both individual-level endpoints and population .