Hose J E, Guillette L J
Department of Biology, Occidental College, Los Angeles, California, USA.
Environ Health Perspect. 1995 May;103 Suppl 4(Suppl 4):87-91. doi: 10.1289/ehp.95103s487.
Although chemical exposure has been associated with reduced reproduction in certain North American fish, reptiles, and mammals, definitive cause-and-effect data are lacking in many instances. Because the increasing use and global transport of industrial chemicals pose significant risk to successful reproduction, methods should be developed that can define the geographic extent and magnitude of injury and risk to wildlife. Because industrial chemicals are articles of commerce, information about injury to wildlife has been contentious and too often ineffective in changing societal behavior. The following strategies are advocated for inferring causal relationships. First, a balanced and comprehensive assessment of the data is necessary to determine the geographic extent of exposure and reproductive effects associated with environmental pollution. Initial efforts to document reproductive injury should focus on specific ecosystems in which detrimental effects have been observed, but lack sufficient causal data. Model systems (including experimental mesocosms or field ecosystems) should be identified or designed that can adequately test multigenerational reproductive effects. Mechanistic data from supportive laboratory studies on reproductive toxicity, quantitative structure-activity relationships, and bioaccumulation can be used to predict effects of related pollutants and to determine risk. Such information is essential to prevent future injury to wildlife and to prioritize the numerous remediation decisions facing our society.
尽管在某些北美鱼类、爬行动物和哺乳动物中,化学物质暴露与繁殖能力下降有关,但在许多情况下,确凿的因果关系数据仍然缺乏。由于工业化学品的使用增加及其全球运输对成功繁殖构成了重大风险,因此应开发出能够确定对野生动物造成伤害和风险的地理范围及程度的方法。由于工业化学品是商业物品,有关野生动物受到伤害的信息一直存在争议,而且在改变社会行为方面往往效果不佳。以下是一些用于推断因果关系的策略。首先,有必要对数据进行全面、平衡的评估,以确定与环境污染相关的暴露地理范围和生殖影响。记录生殖损伤的初步工作应集中在已观察到有害影响但缺乏足够因果关系数据的特定生态系统上。应确定或设计能够充分测试多代生殖影响的模型系统(包括实验性中宇宙或野外生态系统)。来自生殖毒性、定量构效关系和生物累积性的支持性实验室研究的机制数据可用于预测相关污染物的影响并确定风险。此类信息对于防止未来对野生动物的伤害以及确定我们社会面临的众多补救决策的优先级至关重要。