Modelling interactions of toxicants and density dependence in wildlife populations

Schipper, Aafke M.; Hendriks, Harrie; Kauffman, Matthew J.; Hendriks, A. Jan; Huijbregts, Mark A. J.

doi:10.1111/1365-2664.12142

Cited by 17 publications

(28 citation statements)

References 52 publications

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“…, Schipper et al. ); however, to our knowledge, this is the first demonstration of the role density dependence plays in magnifying population response to multiple stressors at different stages. Considering that many species experience different stressors throughout their life history (Kingsolver et al.…”

Section: Discussionmentioning

confidence: 65%

“…, Dobson and Randolph ) or models only include stressors acting on one demographic process (Schipper et al. ). One exception to these generalities is Power (), who explored the interactions between stressors acting on growth and mortality, finding magnified reductions in abundance of 0+ and 1+ individuals when both stressors occur.…”

Section: Discussionmentioning

confidence: 99%

“…Stress on early life stages, especially if the stressor acts prior to density dependence, often has less of a population impact than stress on later life stages (Shuter 1990, Punt et al 2014, 2016, Shelton et al 2014. Additionally, compensatory density dependence can mitigate the impacts of a single stressor (Moe et al 2002, Schipper et al 2013 or even multiple stressors (Power 1997). Certain forms of density dependence or model structure can lead to higher equilibrium population sizes when survival is lowered, the "hydra effect" (Abrams 2009, Liz andRuiz-Herrera 2016).…”

Section: Introductionmentioning

confidence: 99%

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Density dependence governs when population responses to multiple stressors are magnified or mitigated

Hodgson

Essington

Halpern

2017

Ecology

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Population endangerment typically arises from multiple, potentially interacting anthropogenic stressors. Extensive research has investigated the consequences of multiple stressors on organisms, frequently focusing on individual life stages. Less is known about population-level consequences of exposure to multiple stressors, especially when exposure varies through life. We provide the first theoretical basis for identifying species at risk of magnified effects from multiple stressors across life history. By applying a population modeling framework, we reveal conditions under which population responses from stressors applied to distinct life stages are either magnified (synergistic) or mitigated. We find that magnification or mitigation critically depends on the shape of density dependence, but not the life stage in which it occurs. Stressors are always magnified when density dependence is linear or concave, and magnified or mitigated when it is convex. Using Bayesian numerical methods, we estimated the shape of density dependence for eight species across diverse taxa, finding support for all three shapes.

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Section: Discussionmentioning

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Density dependence governs when population responses to multiple stressors are magnified or mitigated

Hodgson

Essington

Halpern

2017

Ecology

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“…Either way, decisions about how to include density dependence need thoughtful consideration, because density dependence can interact with chemicals in different ways, with contrasting consequences for population persistence. The present review suggests that, in some cases, density dependence is likely to reduce the impacts of low exposures to pesticides (and other stressors) at the population level . Removal of organisms releases the rest of the population from competition, and a subsequent increase in vital rates compensates for initial adverse effects of chemicals.…”

Section: Special Considerations For Listed Species Assessmentsmentioning

confidence: 88%

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work

Forbes

Galić

Schmolke

et al. 2016

Enviro Toxic and Chemistry

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United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:190435: -191335: . # 2016

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“…(), and Schipper et al. (), we assumed that exposure to past and current prevailing environmental concentrations of DDE affects the fertility of these species (via abnormal breeding and eggshell thinning) rather than their survivorship. To parameterize Eq.…”

Section: Methodsmentioning

confidence: 99%

Using field data to quantify chemical impacts on wildlife population viability

Hilbers

Hoondert

Schipper

et al. 2018

Ecological Applications

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Abstract. Environmental pollution is an important driver of biodiversity loss. Yet, to date, the effects of chemical exposure on wildlife populations have been quantified for only a few species, mainly due to a lack of appropriate laboratory data to quantify chemical impacts on vital rates. In this study, we developed a method to quantify the effects of toxicant exposure on wildlife population persistence based on field monitoring data. We established field-based vital-rate-response functions for toxicants, using quantile regression to correct for the influences of confounding factors on the vital rates observed, and combined the response curves with population viability modelling. We then applied the method to quantify the impact of DDE on three bird species: the White-tailed Eagle, Bald Eagle, and Osprey. Population viability was expressed via five population extinction vulnerability metrics: population growth rate (r 1 ), critical patch size (CPS), minimum viable population size (MVP), probability of population extirpation (PE), and median time to population extirpation (MTE). We found that past DDE exposure concentrations increased population extirpation vulnerabilities of all three bird species. For example, at DDE concentrations of 25 mg/kg wet mass of egg (the maximum historic exposure concentration reported in literature for the Osprey), r 1 became small (White-tailed Eagle and Osprey) or close to zero (Bald Eagle), the CPS increased up to almost the size of Connecticut (White-tailed Eagle and Osprey) or West Virginia (Bald Eagle), the MVP increased up to approximately 90 (White-tailed Eagle and Osprey) or 180 breeding pairs (Bald Eagle), the PE increased up to almost certain extirpation (Bald Eagle) or only slightly elevated levels (White-tailed Eagle and Osprey) and the MTE became within decades (Bald Eagle) or remained longer than a millennium (White-tailed Eagle and Osprey). Our study provides a method to derive species-specific field-based response curves of toxicant exposure, which can be used to assess population extinction vulnerabilities and obtain critical levels of toxicant exposure based on maximum permissible effect levels. This may help conservation managers to better design appropriate habitat restoration and population recovery measures, such as reducing toxicant levels, increasing the area of suitable habitat or reintroducing individuals.

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Modelling interactions of toxicants and density dependence in wildlife populations

Cited by 17 publications

References 52 publications

Density dependence governs when population responses to multiple stressors are magnified or mitigated

Density dependence governs when population responses to multiple stressors are magnified or mitigated

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work

Using field data to quantify chemical impacts on wildlife population viability

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