Evidence map›Paper›PMID 38155557›Full record

ArticleIntegrated environmental assessment and management2024

Mechanistic population models for ecological risk assessment and decision support: The importance of good conceptual model diagrams.

Valery E Forbes, Chiara Accolla, Thomas Banitz, Kristin Crouse, Nika Galic, Volker Grimm, Sandy Raimondo, Amelie Schmolke, Maxime Vaugeois

Abstract read
In one paragraph

Article in Integrated environmental assessment and management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Valery E ForbesDepartment of Biological Sciences, Florida Atlantic University, Boca Raton, Florida, USA.
Chiara AccollaWaterborne Environmental Inc, Leesburg, Virginia, USA.
Thomas BanitzDepartment of Ecological Modelling, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.
Kristin CrouseDepartment of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, USA.
Nika GalicSyngenta Crop Protection AG, Basel, Switzerland.
Volker GrimmDepartment of Ecological Modelling, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.
Sandy RaimondoUnited States Environmental Protection Agency, Office of Research and Development, Gulf Breeze, Florida, USA.
Amelie SchmolkeWaterborne Environmental Inc, Leesburg, Virginia, USA.
Maxime VaugeoisSyngenta Crop Protection LLC, Greensboro, North Carolina, USA.

Funding

HelmholtzIntramural EPA EPA999999Svenska Forskningsrådet Formas 2018-06139
6 · The paper itself

Abstract

The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;20:1566-1574. © 2023 SETAC.

Indexed as

Decision Support TechniquesEcologyEnvironmental MonitoringModels, TheoreticalRisk AssessmentGood modeling practiceMechanistic effect modelsModel visualizationpop‐cmd.comPop‐GUIDE

Identifiers

PMID38155557
PMCPMC12203779

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.