Abstract

Monitoring the ecological impacts of environmental pollution and the effectiveness of remediation efforts requires identifying relationships between contaminants and the disruption of biological processes in populations, communities, or ecosystems. Wildlife are useful bioindicators, but traditional comparative experimental approaches rely on a staunch and typically unverifiable assumption that, in the absence of contaminants, reference and contaminated sites would support the same densities of bioindicators, thereby inferring direct causation from indirect data. We demonstrate the utility of spatial capture-recapture (SCR) models for overcoming these issues, testing if community density of common small mammal bioindicators was directly influenced by soil chemical concentrations. By modeling density as an inhomogeneous Poisson point process, we found evidence for an inverse spatial relationship between Peromyscus density and soil mercury concentrations, but not other chemicals, such as polychlorinated biphenyls, at a site formerly occupied by a nuclear reactor. Although the coefficient point estimate supported Peromyscus density being lower where mercury concentrations were higher (β = –0.44), the 95% confidence interval overlapped zero, suggesting no effect was also compatible with our data. Estimated density from the most parsimonious model (2.88 mice/ha; 95% CI = 1.63–5.08), which did not support a density-chemical relationship, was within the range of reported densities for Peromyscus that did not inhabit contaminated sites elsewhere. Environmental pollution remains a global threat to biodiversity and ecosystem and human health, and our study provides an illustrative example of the utility of SCR models for investigating the effects that chemicals may have on wildlife bioindicator populations and communities.

Highlights

  • Wildlife populations and communities have played critical roles as bioindicators of environmental contamination for decades

  • The findings from that study were revealing, the authors used a traditional comparative experimental approach that was predicated on the untestable assumption that in the absence of polychlorinated biphenyls (PCBs) contamination, both study areas would support the same densities of American mink [15, 22]

  • Among the inhomogeneous Poisson point process models that we fit, the most support existed for an inverse relationship between mercury concentrations and density; mercury has been implicated in deleterious effects observed in populations of Peromyscus and other wildlife elsewhere [89, 90]

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Summary

Introduction

Wildlife populations and communities have played critical roles as bioindicators of environmental contamination for decades. Numerous species have been used to evaluate the presence of heavy metals and persistent organic pollutants in ecosystems, examine the associated physiological effects of bioaccumulation, and determine the effectiveness of environmental remediation efforts [1,2,3]. General consensus exists regarding the criteria that make a particular wildlife species useful as a bioindicator [2, 10, 11], and studies at the individual level of the molecular, cellular, and physiological effects of pollutants on wildlife are prevalent [12]. A major challenge to developing reliable predictions about the ecological ramifications of pollution and evaluating the effectiveness of remediation efforts is causally linking pollutants to disruption of natural biological processes in populations, communities, and ecosystems [12,13,14]

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