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Do Spatially Explicit Wildlife Exposure Models Improve the Estimation of Risk for Small Mammals? Case Study: Application of Spatially Explicit Exposure Model to Small Mammal Exposures to Lead in Heterogeneous Landscapes.
Integrated Environmental Assessment and Management ( IF 3.0 ) Pub Date : 2020-08-14 , DOI: 10.1002/ieam.4326
Mark S Johnson 1 , Michael J Quinn 1 , Theodore Wickwire 2, 3 , John Buonagurio 4 , Marc A Williams 1
Affiliation  

Understanding risks to terrestrial wildlife species from exposure to chemicals in the environment requires knowledge of how species make habitat decisions and how subsequent exposure events occur. Heterogeneity of chemical distribution and of habitat quality can influence exposure. Previous studies in birds have shown that individually based, spatially explicit models can be useful in predicting exposure and risk; however, studies investigating these influences in small mammals with limited ranges have been lacking. Here we test a spatially explicit, individually based exposure model (Spatially Explicit Exposure Model [SEEM]) in which model predictions based on life history traits, habitat preferences, and varying soil Pb concentrations are used and compared to those with field‐collected blood or tissue Pb concentrations in small (e.g., Peromyscus, Blarina spp.) and medium‐sized mammalian species (e.g., Lepus spp.) at 3 Pb‐contaminated sites. These species were chosen because they were expected to be present in suitable habitat, and Pb was modeled when adequate tissue‐based toxicity thresholds were available. Oral exposure estimates from SEEM were compared with a traditional deterministic model and with field‐collected tissue Pb concentrations using ecological hazard quotients (EHQs) to normalize between oral and real‐time tissue Pb concentrations. Ecological hazard quotients at the 90% population effect level (for SEEM) and at the 95% upper confidence level (assuming a single Pb concentration with no consideration of habitat quality in the deterministic model) were compared with maximum EHQs developed from blood or tissue Pb concentrations. Deterministic estimates and SEEM were similar for small mammal species, yet slightly overpredicted risk compared to field tissue or blood Pb data. Estimates for hares (medium‐sized mammals) using SEEM provided more accurate predictions compared with field tissue data. These data suggest that spatially explicit models may be sensitive to grain size, given that small mammals experience the environment in limited spatial contexts, a scale at which habitat may not change significantly. Integr Environ Assess Manag 2021;17:259–272. Published 2020. This article is a US Government work and is in the public domain in the USA.

中文翻译:

空间上明确的野生动物暴露模型是否可以提高对小型哺乳动物风险的估计?案例研究:空间显式暴露模型在异质景观中铅的小哺乳动物暴露中的应用。

了解环境中暴露于化学物质对陆生野生生物物种的风险,需要了解物种如何做出栖息地决策以及随后的暴露事件如何发生的知识。化学分布和生境质量的异质性会影响暴露。先前对鸟类的研究表明,基于个体的空间明确模型可用于预测暴露和风险。然而,缺乏对范围有限的小型哺乳动物中这些影响的研究。在这里,我们测试了一个空间明确的,基于个体的暴露模型(空间显式暴露模型[SEEM]),其中使用了基于生活史特征,生境偏好和变化的土壤Pb浓度的模型预测,并将其与现场采集的血液或组织中的Pb浓度较小(例如,Peromyscus,Blarina spp。)和中等大小的哺乳动物(如天牛)spp。)在3个受Pb污染的地点。选择这些物种是因为它们预期会存在于合适的栖息地中,并且当有足够的基于组织的毒性阈值时,才对Pb进行建模。将SEEM的口腔暴露估计值与传统的确定性模型以及使用生态危害商(EHQ)现场采集的组织中Pb的浓度进行比较,以标准化口腔和实时组织Pb的浓度。将在90%人口影响水平(对于SEEM)和95%高置信水平(假设确定性模型中不考虑生境质量的单个Pb浓度)下的生态危害商与从血液或组织Pb中得出的最大EHQ进行比较浓度。小哺乳动物物种的确定性估算值和SEEM相似,与野外组织或血铅数据相比,风险略有高估。与野外组织数据相比,使用SEEM进行的野兔(中型哺乳动物)估计提供了更准确的预测。这些数据表明,鉴于小型哺乳动物在有限的空间环境中体验环境,在此范围内生境可能不会发生显着变化,因此空间上明确的模型可能对晶粒尺寸敏感。Integr环境评估管理2021; 17:259–272。出版于2020年。本文是美国政府的工作,在美国属于公共领域。
更新日期:2020-08-14
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