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Martin T, Hodson ME, Thompson H, Hutter V, Ashauer R. Can TK-TD modelling bridge the gap between in vitro and in vivo mammalian toxicity data? Toxicol In Vitro 2024; 101:105937. [PMID: 39237057 DOI: 10.1016/j.tiv.2024.105937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 08/22/2024] [Accepted: 09/02/2024] [Indexed: 09/07/2024]
Abstract
Repeated dietary dose testing is used to assess longer term toxicity of chemicals, such as pesticides, to mammals. However, the internal pesticide concentration varies significantly as feeding rate relative to body size fluctuates over time. Toxicokinetic-toxicodynamic (TK-TD) models can estimate internal toxicant concentration over time and link this directly to observed effects on endpoints such as the growth rate of laboratory rats. Using TK-TD models it is therefore possible to predict the effects that would result from a constant internal concentration of a pesticide. This presents the possibility of comparison with data from in vitro experiments, potentially facilitating quantitative in vitro to in vivo extrapolation (QIVIVE). We used in vivo TK-TD models to identify relevant internal concentrations and then estimated the experimental conditions required to replicate these in cultured cells, using in vitro TK models. Cell population growth was measured, with a view to extrapolating through time and comparing effect sizes with in vivo predictions. However, observed cell proliferation was not significantly affected by the tested concentrations of any of the five pesticides in this study and so extrapolation was not possible. In light of this negative result, we highlight areas for future work towards QIVIVE of graded sublethal effects in mammals. The most pressing objective is improving the accuracy of in vivo TK predictions, which could be achieved with dietary dosing in TK studies.
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Affiliation(s)
- Thomas Martin
- Rifcon GmbH, Goldbeckstrasse 13, 69493 Hirschberg an der Bergstrasse, Germany; University of York, Dept. Environment & Geography, York, YO10 5NG, UK.
| | - Mark E Hodson
- University of York, Dept. Environment & Geography, York, YO10 5NG, UK
| | - Helen Thompson
- Syngenta, Jealotts Hill, Warfield, Bracknell RG42 6EY, UK
| | - Victoria Hutter
- University of Hertfordshire, School of Life and Medical Sciences, Hatfield, Hertfordshire AL10 9AB, UK
| | - Roman Ashauer
- University of York, Dept. Environment & Geography, York, YO10 5NG, UK; Syngenta Crop Protection AG, Rosentalstrasse 67, 4058 Basel, Switzerland
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2
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Rattner BA, Bean TG, Beasley VR, Berny P, Eisenreich KM, Elliott JE, Eng ML, Fuchsman PC, King MD, Mateo R, Meyer CB, O'Brien JM, Salice CJ. Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2024; 20:725-748. [PMID: 37417421 DOI: 10.1002/ieam.4806] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/24/2023] [Accepted: 06/27/2023] [Indexed: 07/08/2023]
Abstract
Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the "eco" component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to postregistration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory- and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole-animal data and simple hazard ratios. Integr Environ Assess Manag 2024;20:725-748. © 2023 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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Affiliation(s)
- Barnett A Rattner
- US Geological Survey, Eastern Ecological Science Center, Laurel, Maryland, USA
| | | | - Val R Beasley
- College of Veterinary Medicine, University of Illinois at Urbana, Champaign, Illinois, USA
| | | | - Karen M Eisenreich
- US Environmental Protection Agency, Washington, District of Columbia, USA
| | - John E Elliott
- Environment and Climate Change Canada, Delta, British Columbia, Canada
| | - Margaret L Eng
- Environment and Climate Change Canada, Dartmouth, Nova Scotia, Canada
| | | | - Mason D King
- Simon Fraser University, Burnaby, British Columbia, Canada
| | | | | | - Jason M O'Brien
- Environment and Climate Change Canada, Ottawa, Ontario, Canada
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3
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Trijau M, Goussen B, Brain R, Maul J, Galic N. Development of a mechanistic model for analyzing avian reproduction data for pesticide risk assessment. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 327:121477. [PMID: 37011778 DOI: 10.1016/j.envpol.2023.121477] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/20/2023] [Accepted: 03/20/2023] [Indexed: 06/19/2023]
Abstract
Mechanistic effect models are increasingly recommended as tools for refining evaluations of risk from exposure to pesticides. In the context of bird and mammal risk assessments, DEB-TKTD models have been recommended for characterizing sublethal effects at lower tiers. However, there are currently no such models. Currently, chronic, multi-generational studies are performed to characterize potential effects of pesticides on avian reproduction, but it is has not been established to what extent results from these studies can inform effect models. Here, a standard Dynamic Energy Budget (DEB) model was extended to account for the avian toxicity endpoints observed in regulatory studies. We linked this new implementation to a toxicological module to capture observed pesticide effects on reproduction via a decreased efficiency of egg production. We analysed ten reproduction studies with five different pesticides conducted with the mallard (Anas platyrhynchos) and the northern bobwhite (Colinus virginianus). The new model implementation accurately distinguished between effects on egg production from direct mechanism of toxicity and from food avoidance. Due to the specific nature of regulatory studies, model applicability for risk refinement is currently limited. We provide suggestions for next steps in model development.
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Affiliation(s)
- Marie Trijau
- Ibacon GmbH, Arheilger Weg 17, D-64380, Roßdorf, Germany
| | - Benoit Goussen
- Ibacon GmbH, Arheilger Weg 17, D-64380, Roßdorf, Germany.
| | - Richard Brain
- Syngenta Crop Protection, LLC, Greensboro, NC, 27419, United States
| | - Jonathan Maul
- Syngenta Crop Protection, LLC, Greensboro, NC, 27419, United States
| | - Nika Galic
- Syngenta Crop Protection, LLC, Greensboro, NC, 27419, United States
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4
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Mauritsson K, Desforges JP, Harding KC. Maternal Transfer and Long-Term Population Effects of PCBs in Baltic Grey Seals Using a New Toxicokinetic-Toxicodynamic Population Model. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2022; 83:376-394. [PMID: 36242644 PMCID: PMC9637078 DOI: 10.1007/s00244-022-00962-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 10/03/2022] [Indexed: 05/04/2023]
Abstract
Empirical evidence has shown that historical exposure of polychlorinated biphenyls (PCBs) to Baltic grey seals not only severely affected individual fitness, but also population growth rates and most likely caused the retarded recovery rate of the depleted population for decades. We constructed a new model which we term a toxicokinetic-toxicodynamic (TKTD) population model to quantify these effects. The toxicokinetic sub-model describes in detail the bioaccumulation, elimination and vertical transfer from mother to offspring of PCBs and is linked to a toxicodynamic model for estimation of PCB-related damage, hazard and stress impacts on fertility and survival rates. Both sub-models were linked to a Leslie matrix population model to calculate changes in population growth rate and age structure, given different rates of PCB exposure. Toxicodynamic model parameters related to reproductive organ lesions were calibrated using published historical data on observed pregnancy rates in Baltic grey seal females. Compared to empirical data, the TKTD population model described well the age-specific bioaccumulation pattern of PCBs in Baltic grey seals, and thus, the toxicokinetic parameters, deduced from the literature, are believed to be reliable. The model also captured well the general effects of PCBs on historical population growth rates. The model showed that reduced fertility due to increased PCB exposure causes decreased vertical transfer from mother to offspring and in turn increased biomagnification in non-breeding females. The developed TKTD model can be used to perform population viability analyses of Baltic grey seals with multiple stressors, also including by-catches and different hunting regimes. The model can also be extended to other marine mammals and other contaminants by adjustments of model parameters and thus provides a test bed in silico for new substances.
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Affiliation(s)
- Karl Mauritsson
- Division of Biology and Bioinformatics, University of Skövde, Skövde, Sweden.
| | - Jean-Pierre Desforges
- Department of Environmental Studies and Sciences, University of Winnipeg, Winnipeg, MB, Canada
| | - Karin C Harding
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
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5
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Martin T, Hodson ME, Ashauer R. Modelling the effects of variability in feeding rate on growth - a vital step for DEB-TKTD modelling. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 232:113231. [PMID: 35104776 PMCID: PMC8873987 DOI: 10.1016/j.ecoenv.2022.113231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 01/07/2022] [Accepted: 01/20/2022] [Indexed: 06/14/2023]
Abstract
A major limitation of dietary toxicity studies on rodents is that food consumption often differs between treatments. The control treatment serves as a reference of how animals would have grown if not for the toxicant in their diet, but this comparison unavoidably conflates the effects of toxicity and feeding rate on body weight over time. A key advantage of toxicity models based on dynamic energy budget theory (DEB) is that chemical stress and food consumption are separate model inputs, so their effects on growth rate can be separated. To reduce data requirements, DEB convention is to derive a simplified feeding input, f, from food availability; its value ranges from zero (starvation) to one (food available ad libitum). Observed food consumption in dietary toxicity studies shows that, even in the control treatment, rats limit their food consumption, contradicting DEB assumptions regarding feeding rate. Relatively little work has focused on addressing this mismatch, but accurately modelling the effects of food intake on growth rate is essential for the effects of toxicity to be isolated. This can provide greater insight into the results of chronic toxicity studies and allows accurate extrapolation of toxic effects from laboratory data. Here we trial a new method for calculating f, based on the observed relationships between food consumption and body size in laboratory rats. We compare model results with those of the conventional DEB method and a previous effort to calculate f using observed food consumption data. Our results showed that the new method improved model accuracy while modelled reserve dynamics closely followed observed body fat percentage over time. The new method assumes that digestive efficiency increases with body size. Verifying this relationship through data collection would strengthen the basis of DEB theory and support the case for its use in ecological risk assessment.
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Affiliation(s)
- Thomas Martin
- University of York, Environment Department, Heslington, York YO10 5NG, UK.
| | - Mark E Hodson
- University of York, Environment Department, Heslington, York YO10 5NG, UK
| | - Roman Ashauer
- University of York, Environment Department, Heslington, York YO10 5NG, UK; Syngenta Crop Protection AG, Basel 4002, Switzerland
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6
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Gallagher CA, Chudzinska M, Larsen-Gray A, Pollock CJ, Sells SN, White PJC, Berger U. From theory to practice in pattern-oriented modelling: identifying and using empirical patterns in predictive models. Biol Rev Camb Philos Soc 2021; 96:1868-1888. [PMID: 33978325 DOI: 10.1111/brv.12729] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 04/14/2021] [Accepted: 04/16/2021] [Indexed: 01/21/2023]
Abstract
To robustly predict the effects of disturbance and ecosystem changes on species, it is necessary to produce structurally realistic models with high predictive power and flexibility. To ensure that these models reflect the natural conditions necessary for reliable prediction, models must be informed and tested using relevant empirical observations. Pattern-oriented modelling (POM) offers a systematic framework for employing empirical patterns throughout the modelling process and has been coupled with complex systems modelling, such as in agent-based models (ABMs). However, while the production of ABMs has been rising rapidly, the explicit use of POM has not increased. Challenges with identifying patterns and an absence of specific guidelines on how to implement empirical observations may limit the accessibility of POM and lead to the production of models which lack a systematic consideration of reality. This review serves to provide guidance on how to identify and apply patterns following a POM approach in ABMs (POM-ABMs), specifically addressing: where in the ecological hierarchy can we find patterns; what kinds of patterns are useful; how should simulations and observations be compared; and when in the modelling cycle are patterns used? The guidance and examples provided herein are intended to encourage the application of POM and inspire efficient identification and implementation of patterns for both new and experienced modellers alike. Additionally, by generalising patterns found especially useful for POM-ABM development, these guidelines provide practical help for the identification of data gaps and guide the collection of observations useful for the development and verification of predictive models. Improving the accessibility and explicitness of POM could facilitate the production of robust and structurally realistic models in the ecological community, contributing to the advancement of predictive ecology at large.
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Affiliation(s)
- Cara A Gallagher
- Department of Plant Ecology and Conservation Biology, University of Potsdam, Am Mühlenberg 3, Potsdam, 14469, Germany.,Department of Bioscience, Aarhus University, Frederiksborgvej 399, Roskilde, 4000
| | - Magda Chudzinska
- Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, St Andrews, KY16 9ST, U.K
| | - Angela Larsen-Gray
- Department of Integrative Biology, University of Wisconsin-Madison, 250 N. Mills St., Madison, WI, 53706, U.S.A
| | | | - Sarah N Sells
- Montana Cooperative Wildlife Research Unit, The University of Montana, 205 Natural Sciences, Missoula, MT, 59812, U.S.A
| | - Patrick J C White
- School of Applied Sciences, Edinburgh Napier University, 9 Sighthill Ct., Edinburgh, EH11 4BN, U.K
| | - Uta Berger
- Institute of Forest Growth and Computer Science, Technische Universität Dresden, Dresden, 01062, Germany
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7
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Silva WTAF, Harding KC, Marques GM, Bäcklin BM, Sonne C, Dietz R, Kauhala K, Desforges JP. Life cycle bioenergetics of the gray seal (Halichoerus grypus) in the Baltic Sea: Population response to environmental stress. ENVIRONMENT INTERNATIONAL 2020; 145:106145. [PMID: 33038624 DOI: 10.1016/j.envint.2020.106145] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 09/14/2020] [Accepted: 09/15/2020] [Indexed: 05/21/2023]
Abstract
Wildlife population dynamics are shaped by multiple natural and anthropogenic factors, including predation, competition, stressful life history events, and external environmental stressors such as diseases and pollution. Marine mammals such as gray seals rely on extensive blubber layers for insulation and energy storage, making this tissue critical for survival and reproduction. This lipid rich blubber layer also accumulates hazardous fat soluble pollutants, such as polychlorinated biphenyls (PCBs), that can directly impact adipose function or be mobilized during periods of negative energy balance or transferred to offspring to exert further impacts on target tissues or vulnerable life stages. To predict how marine mammals will respond to ecological and anthropogenic stressors, it is necessary to use process-based modelling approaches that integrate environmental inputs, full species life history, and stressor impacts with individual dynamics of energy intake, storage, and utilization. The purpose of this study was to develop a full lifecycle dynamic energy budget and individual based model (DEB-IBM) that captured Baltic gray seal physiology and life history, and showcase potential applications of the model to predict population responses to select stressors known to threaten gray seals and other marine mammals around the world. We explore variations of three ecologically important stressors using phenomenological simulations: food limitation, endocrine disrupting chemicals that reduce fertility, and infectious disease. Using our calibrated DEB-IBM for Baltic gray seals, we found that continuous incremental food limitation can be more detrimental to population size than short random events of starvation, and further, that the effect of endocrine disruptors on population growth and structure is delayed due to bioaccumulation, and that communicable diseases significantly decrease population growth even when spillover events are relatively less frequent. One important finding is the delayed effect on population growth rate from some stressors, several years after the exposure period, resulting from a decline in somatic growth, increased age at maturation and decreased fecundity. Such delayed responses are ignored in current models of population viability and can be important in the correct assessment of population extinction risks. The model presented here provides a test bed on which effects of new hazardous substances and different scenarios of future environmental change affecting food availability and/or seal energetic demands can be investigated. Thus, the framework provides a tool for better understanding how diverse environmental stressors affect marine mammal populations and can be used to guide scientifically based management.
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Affiliation(s)
- Willian T A F Silva
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden.
| | - Karin C Harding
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Gonçalo M Marques
- Marine, Environment & Technology Center (MARETEC), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Christian Sonne
- Department of Bioscience, Arctic Research Centre, Aarhus University, Roskilde, Denmark
| | - Rune Dietz
- Department of Bioscience, Arctic Research Centre, Aarhus University, Roskilde, Denmark
| | - Kaarina Kauhala
- Natural Resources Institute Finland, Itäinen Pitkäkatu, Turku, Finland
| | - Jean-Pierre Desforges
- Department of Bioscience, Arctic Research Centre, Aarhus University, Roskilde, Denmark; Department of Natural Resource Sciences, McGill University, Ste Anne de Bellevue, Canada.
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8
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Sonne C, Siebert U, Gonnsen K, Desforges JP, Eulaers I, Persson S, Roos A, Bäcklin BM, Kauhala K, Tange Olsen M, Harding KC, Treu G, Galatius A, Andersen-Ranberg E, Gross S, Lakemeyer J, Lehnert K, Lam SS, Peng W, Dietz R. Health effects from contaminant exposure in Baltic Sea birds and marine mammals: A review. ENVIRONMENT INTERNATIONAL 2020; 139:105725. [PMID: 32311628 DOI: 10.1016/j.envint.2020.105725] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 03/29/2020] [Accepted: 04/04/2020] [Indexed: 05/21/2023]
Abstract
Here we review contaminant exposure and related health effects in six selected Baltic key species. Sentinel species included are common eider, white-tailed eagle, harbour porpoise, harbour seal, ringed seal and grey seal. The review represents the first attempt of summarizing available information and baseline data for these biomonitoring key species exposed to industrial hazardous substances focusing on anthropogenic persistent organic pollutants (POPs). There was only limited information available for white-tailed eagles and common eider while extensive information exist on POP exposure and health effects in the four marine mammal species. Here we report organ-tissue endpoints (pathologies) and multiple biomarkers used to evaluate health and exposure of key species to POPs, respectively, over the past several decades during which episodes of significant population declines have been reported. Our review shows that POP exposure affects the reproductive system and survival through immune suppression and endocrine disruption, which have led to population-level effects on seals and white-tailed eagles in the Baltic. It is notable that many legacy contaminants, which have been banned for decades, still appear to affect Baltic wildlife. With respect to common eiders, changes in food composition, quality and contaminant exposure seem to have population effects which need to be investigated further, especially during the incubation period where the birds fast. Since new industrial contaminants continuously leak into the environment, we recommend continued monitoring of them in sentinel species in the Baltic, identifying possible effects linked to climate change, and modelling of population level effects of contaminants and climate change.
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Affiliation(s)
- Christian Sonne
- Department of Bioscience, Arctic Research Centre (ARC), Aarhus University, Faculty of Science and Technology, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark; Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou CN-450002, China.
| | - Ursula Siebert
- Institute for Terrestrial and Aquatic Wildlife Research, University of Veterinary Medicine Hannover, Werftstr. 6, 25761 Büsum, Germany.
| | - Katharina Gonnsen
- Institute for Terrestrial and Aquatic Wildlife Research, University of Veterinary Medicine Hannover, Werftstr. 6, 25761 Büsum, Germany.
| | - Jean-Pierre Desforges
- Department of Bioscience, Arctic Research Centre (ARC), Aarhus University, Faculty of Science and Technology, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark.
| | - Igor Eulaers
- Department of Bioscience, Arctic Research Centre (ARC), Aarhus University, Faculty of Science and Technology, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark.
| | - Sara Persson
- Swedish Museum of Natural History, Department of Environmental Research and Monitoring, Frescativägen 40, SE-104 05 Stockholm, Sweden.
| | - Anna Roos
- Swedish Museum of Natural History, Department of Environmental Research and Monitoring, Frescativägen 40, SE-104 05 Stockholm, Sweden.
| | - Britt-Marie Bäcklin
- Swedish Museum of Natural History, Department of Environmental Research and Monitoring, Frescativägen 40, SE-104 05 Stockholm, Sweden.
| | - Kaarina Kauhala
- Natural Resources Institute Finland, Luke. Itäinen Pitkäkatu 4 A, FI-20520 Turku, Finland.
| | - Morten Tange Olsen
- Evolutionary Genomics, Natural History Museum of Denmark, Department of Biology, University of Copenhagen, Øster Voldgade 5-7, DK-1350 Copenhagen K, Denmark.
| | - Karin C Harding
- Department of Biological and Environmental Sciences, University of Gothenburg, Box 463, 25 SE-405 30 Gothenburg, Sweden.
| | - Gabriele Treu
- German Environment Agency, Section Chemicals, Wörlitzer Platz 1, 06844 Dessau-Roßlau, Germany.
| | - Anders Galatius
- Department of Bioscience, Arctic Research Centre (ARC), Aarhus University, Faculty of Science and Technology, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark.
| | - Emilie Andersen-Ranberg
- Department of Veterinary Clinical Sciences, University of Copenhagen, Faculty of Health, Dyrlægevej 16, 1870 Frederiksberg C, Denmark.
| | - Stephanie Gross
- Institute for Terrestrial and Aquatic Wildlife Research, University of Veterinary Medicine Hannover, Werftstr. 6, 25761 Büsum, Germany.
| | - Jan Lakemeyer
- Institute for Terrestrial and Aquatic Wildlife Research, University of Veterinary Medicine Hannover, Werftstr. 6, 25761 Büsum, Germany.
| | - Kristina Lehnert
- Institute for Terrestrial and Aquatic Wildlife Research, University of Veterinary Medicine Hannover, Werftstr. 6, 25761 Büsum, Germany.
| | - Su Shiung Lam
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou CN-450002, China; Pyrolysis Technology Research Group, Institute of Tropical Aquaculture and Fisheries (Akuatrop) & Institute of Tropical Biodiversity and Sustainable Development (Bio-D Tropika), Universiti Malaysia Terengganu, MY-21030 Kuala Terengganu, Terengganu, Malaysia.
| | - Wanxi Peng
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou CN-450002, China
| | - Rune Dietz
- Department of Bioscience, Arctic Research Centre (ARC), Aarhus University, Faculty of Science and Technology, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark.
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9
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Impact of environmental variability on Pinctada margaritifera life-history traits: A full life cycle deb modeling approach. Ecol Modell 2020. [DOI: 10.1016/j.ecolmodel.2020.109006] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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10
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Martin T, Thompson H, Thorbek P, Ashauer R. Toxicokinetic-Toxicodynamic Modeling of the Effects of Pesticides on Growth of Rattus norvegicus. Chem Res Toxicol 2019; 32:2281-2294. [PMID: 31674768 PMCID: PMC7007285 DOI: 10.1021/acs.chemrestox.9b00294] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Indexed: 12/25/2022]
Abstract
Ecological risk assessment is carried out for chemicals such as pesticides before they are released into the environment. Such risk assessment currently relies on summary statistics gathered in standardized laboratory studies. However, these statistics extract only limited information and depend on duration of exposure. Their extrapolation to realistic ecological scenarios is inherently limited. Mechanistic effect models simulate the processes underlying toxicity and so have the potential to overcome these issues. Toxicokinetic-toxicodynamic (TK-TD) models operate at the individual level, predicting the internal concentration of a chemical over time and the stress it places on an organism. TK-TD models are particularly suited to addressing the difference in exposure patterns between laboratory (constant) and field (variable) scenarios. So far, few studies have sought to predict sublethal effects of pesticide exposure to wild mammals in the field, even though such effects are of particular interest with respect to longer term exposure. We developed a TK-TD model based on the dynamic energy budget (DEB) theory, which can be parametrized and tested solely using standard regulatory studies. We demonstrate that this approach can be used effectively to predict toxic effects on the body weight of rats over time. Model predictions separate the impacts of feeding avoidance and toxic action, highlighting which was the primary driver of effects on growth. Such information is relevant to the ecological risk posed by a compound because in the environment alternative food sources may or may not be available to focal species. While this study focused on a single end point, growth, this approach could be expanded to include reproductive output. The framework developed is simple to use and could be of great utility for ecological and toxicological research as well as to risk assessors in industry and regulatory agencies.
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Affiliation(s)
- Thomas Martin
- University
of York, Environment Department, Heslington, York YO10
5NG, United Kingdom
| | - Helen Thompson
- Syngenta,
Jealott’s Hill International Research Centre Bracknell, Berkshire RG42 6EY, United Kingdom
| | - Pernille Thorbek
- Syngenta,
Jealott’s Hill International Research Centre Bracknell, Berkshire RG42 6EY, United Kingdom
| | - Roman Ashauer
- University
of York, Environment Department, Heslington, York YO10
5NG, United Kingdom
- Syngenta
Crop Protection AG, Basel 4002, Switzerland
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11
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Martin T, Thorbek P, Ashauer R. Common ground between growth models of rival theories: A useful illustration for beginners. Ecol Modell 2019. [DOI: 10.1016/j.ecolmodel.2019.05.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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12
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Maloney EM. How do we take the pulse of an aquatic ecosystem? Current and historical approaches to measuring ecosystem integrity. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2019; 38:289-301. [PMID: 30387526 DOI: 10.1002/etc.4308] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 05/23/2018] [Accepted: 10/31/2018] [Indexed: 06/08/2023]
Abstract
Global environmental monitoring has indicated that the structure and function of some aquatic ecosystems has been significantly altered by human activities. There are many potential causes for these changes; however, one major concern is the increasing release of anthropogenic contaminants into aquatic environments. Although toxicological responses of individual organisms are typically well characterized, few studies have focused on characterizing toxicity at the ecosystem level. In fact, because of their scale and complexity, changes in ecosystem integrity are rarely considered in assessments of risks to ecosystems. This work attempts to move the conversation forward by defining integrity of ecosystems, reviewing current and historical approaches to measuring ecosystem integrity status (e.g., structural and functional measurements), and highlighting methods that could significantly contribute to the field of ecosystem toxicology (e.g., keystone species, environmental energetics, ecotoxicological modeling, and adverse outcome pathways [AOPs]). Through a critical analysis of current and historical methodologies, the present study offers a comprehensive, conceptual framework for the assessment of risks of contaminant exposure for whole ecosystems and proposes steps to facilitate better diagnoses of the integrity of aquatic systems. Environ Toxicol Chem 2019;38:289-301. © 2018 SETAC.
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Affiliation(s)
- Erin M Maloney
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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Review: Using physiologically based models to predict population responses to phytochemicals by wild vertebrate herbivores. Animal 2018; 12:s383-s398. [PMID: 30251623 DOI: 10.1017/s1751731118002264] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
To understand how foraging decisions impact individual fitness of herbivores, nutritional ecologists must consider the complex in vivo dynamics of nutrient-nutrient interactions and nutrient-toxin interactions associated with foraging. Mathematical modeling has long been used to make foraging predictions (e.g. optimal foraging theory) but has largely been restricted to a single currency (e.g. energy) or using simple indices of nutrition (e.g. fecal nitrogen) without full consideration of physiologically based interactions among numerous co-ingested phytochemicals. Here, we describe a physiologically based model (PBM) that provides a mechanistic link between foraging decisions and demographic consequences. Including physiological mechanisms of absorption, digestion and metabolism of phytochemicals in PBMs allows us to estimate concentrations of ingested and interacting phytochemicals in the body. Estimated phytochemical concentrations more accurately link intake of phytochemicals to changes in individual fitness than measures of intake alone. Further, we illustrate how estimated physiological parameters can be integrated with the geometric framework of nutrition and into integral projection models and agent-based models to predict fitness and population responses of vertebrate herbivores to ingested phytochemicals. The PBMs will improve our ability to understand the foraging decisions of vertebrate herbivores and consequences of those decisions and may help identify key physiological mechanisms that underlie diet-based ecological adaptations.
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