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STAR Report D5.2 Population Models

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STAR Report D5.2 Population Models STAR (Contract Number: Fission-2010-3.5.1-269672 ) DELIVERABLE (D-N°5.2) Life history traits, radiosensitivity and population modeling: methods to extrapolate from individual endpoints to population dynamics Editor(s) : Frédéric Alonzo (IRSN), Jacqueline Garnier-Laplace (IRSN), Almudena Real (CIEMAT), Deborah Oughton (UMB) Author(s): Frédéric Alonzo (IRSN), Jordi Vives i Batlle (SCK•CEN), Turid Hertel-Aas (UMB), Clare Bradshaw (SU), Hildegarde Vandenhove (SCK•CEN), Jacqueline Garnier-Laplace (IRSN) Reporting period: 01/02/11 – 31/10/11 Date of issue of this report: 31/07/2012 Start date of project: 01/02/2011 Duration: 54 Months Project co-funded by the European Commission under the Seventh Euratom Framework Programme for Nuclear Research &Training Activities (2007-2011) Dissemination Level PU Public PU RE Restricted to a group specified by the partners of the [ STAR ] project CO Confidential, only for partners of the [ STAR ] project [[[STAR ]]] DISTRIBUTION LIST Name Number of copies Comments A. Jouve, STAR EC Project Officer 1 Electronically (through webportal) T. Hinton, STAR Co-ordinator Electronically (word, pdf file) 1 (WP-1), IRSN L. Février, IRSN 1 Electronically (word, pdf file) STAR Management Team members: 1 per member Electronically (pdf file) WP-2; T. Ikaheimonen, STUK WP-3; M. Dowdall, NRPA WP-4; H. Vandenhove, SCK-CEN WP-5; J. Garnier-Laplace, IRSN WP-6; D. Oughton, UMB WP-7; B. Howard, NERC STAR Steering Committee 1 per member Electronically (pdf file) G. Kirchner, BfS A. Real, CIEMAT J-C. Gariel, IRSN T. Ikaheimonen, STUK H. Vandenhove, SCK-CEN C. Bradshaw, SU A. Liland, NRPA B. Howard, NERC B. Salbu, UMB STAR Wiki site 1 Electronically (pdf file) STAR’s External Advisory Board 1 per member Electronically (pdf file) ALLIANCE members 1 per member Electronically (pdf file) [[[STAR ]]] (D-N°: 5.1 ) – Experimental plan 2 Dissemination level : PU Date of issue of this report : 31/10/2011 Executive Summary This report describes in details the basic concepts, needs and data treatment for the population modeling approaches that have been implemented under WP-5 dedicated to “ecologically- relevant low doses effects to non-human species” as part of Task 5.1 devoted to the derivation of population-level protection criteria. Two modeling approaches are presented for extrapolating radiation dose effects from individuals to populations of non-human biota. The first approach, developed as part of the STAR programme, is inspired from methods which are increasingly used in ecotoxicology to address population effects of chemical contaminants. The approach applies Leslie matrix techniques to the case of chronic external gamma irradiation on a range of wildlife species, based on effect data available in the FREDERICA database and interpreted as dose rate response curves. Considered species cover 14 species representing four taxonomic groups (aquatic and soil invertebrates, fish and terrestrial mammals). The strength of the method is its suitability to integrate outcomes of DEBTox applications that will be conducted under Task 5.3 as consequences for population dynamics (limited to the few experimentally tested species). The second approach evolves from a model specifically developed to address radiation effects at the population level in the European lobster and generalised to some mammalian species during the IAEA programme EMRAS II from 2009 to 2011. The model, based on a set of differential equations describing a simplified life history (with two life stages) with logistic functions for reproduction and mortality and a radiation repair mechanism, is reported in this deliverable with its application to fish and mouse. Results of simulations are compared and discussed underlying the following conclusions: (i) Population consequences vary depending on impaired individual endpoints and life history characteristics of exposed species; (ii) Populations can be more radiosensitive than the most sensitive individual endpoint, as a result of combined slight effects on several individual endpoints; (iii) The scarcity of data for acute and chronic exposure often makes it necessary to rely on highly speculative extrapolations (e.g. among species, acute to chronic exposures, among radiation types). This point underlines the need to improve our understanding of the mechanisms underlying radiation toxicity, in order to make better use and interpretation of all the available effect data. (iv) One major limit of the present approaches resides in their incapacity to integrate all the molecular, cellular or histological damages described in exposed organisms. This limit is the cause for one main discrepancy between population-level results and those based on the most sensitive individual endpoints taking account of all sub-individual levels of biological organisation. Future directions include analysing effects using mechanistic concepts in order to make the best possible use of all available data and defining adequate threshold levels assumed to protect species and/or taxonomic groups according to their life history characteristics. [[[STAR ]]] 3 (D-N°: 5.2) – Life history traits radiosensitivity and population modeling Dissemination level : PU Date of issue of this report : 31/07/2012 [[[STAR ]]] 4 (D-N°: 5.2) – Life history traits radiosensitivity and population modeling Dissemination level : PU Date of issue of this report : 31/07/2012 Table of contents Executive Summary .............................................................................................................................................. 3 1. Scope and background ................................................................................................................................ 7 2. Overview of the methods for estimating population effects for animals and plants.............................. 9 2.1. Background.......................................................................................................................................... 9 2.2. Combining individual dose-response curves using Leslie matrices................................................... 11 2.2.1. Why matrix population models? ................................................................................................... 12 2.2.2. Main demographic endpoints ........................................................................................................ 13 2.2.3. Sensitivity analyses ....................................................................................................................... 13 2.2.4. Population response to ionising radiation...................................................................................... 15 2.3. A dual age-class model associated with radiotoxic effects assumptions............................................ 15 2.4. Species selection ................................................................................................................................ 17 2.4.1. Species addressed with the Leslie matrices................................................................................... 17 2.4.2. Species addressed with the dual age class model.......................................................................... 18 2.4.3. ICRP “Reference Animals and Plants” ......................................................................................... 18 2.4.4. Vascular plants, phytoplankton, bivalves...................................................................................... 19 2.5. Collecting information on species life history parameters ................................................................ 20 2.5.1. Life history parameters for the Leslie matrices............................................................................. 20 2.5.2. Inferring life history parameters for the dual age class model ...................................................... 21 2.5.3. Dealing with gaps of knowledge................................................................................................... 21 2.6. Collecting information on species radiosensitivity ............................................................................ 22 2.6.1. Chronic dose rate response curves for Leslie matrices.................................................................. 22 2.6.2. Extrapolation rules ........................................................................................................................ 22 2.6.3. Inferring 30-day lethal dose for the dual age class model............................................................. 25 2.6.4. Validation of the model with fish effect data from the EPIC study .............................................. 26 3. Combining dose rate-response curves using Leslie matrices................................................................. 27 3.1. Mathematical formulation.................................................................................................................. 27 3.1.1. Modeling life history..................................................................................................................... 27 3.1.2. Modeling individual R0 and population λ...................................................................................... 28 3.1.3. Sensitivity of individual R 0 and population λ to changes in individual endpoints ........................ 29 3.1.4. Effects of external gamma radiations............................................................................................ 30 3.1.5. Building and propagating uncertainty
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