Abstract: Food and Ecological Systems Modelling Journal 4: e100714 DOI : 10.3897/fmj.4.100714 Authors : Antonio Paparella, Luigi Cembalo, Christopher Topping : HTML XML PDF PubDate: Thu, 29 Jun 2023 11:46:18 +030
Abstract: Food and Ecological Systems Modelling Journal 4: e102102 DOI : 10.3897/fmj.4.102102 Authors : Elżbieta Ziółkowska, Agnieszka Bednarska, Ryszard Laskowski, Christopher Topping : Solitary bees provide an important ecological and agricultural service by pollinating both wild plants and crops, often more effectively than honey bees. In the context of worldwide pollinators' declines, it is important to better understand the functioning of populations under multiple stressors at larger spatial and temporal scales. Here we propose building a detailed, spatially-explicit agent-based model of one of the best-studied species of solitary bees, Osmia bicornis L. In this Formal Model, we review various aspects of O. bicornis biology and ecology in detail and provide descriptions of their planned implementations in the model. We also discuss the model gaps and limitations, as well as inclusions and exclusions, allowing a dialogue with the reviewers about the model's design.The ALMaSS model of O. bicornis aims to provide a realistic and detailed representation of O. bicornis populations in space and time in European agricultural landscapes. The model will be a part of the Animal, Landscape and Man Simulation System (ALMaSS); thus will be able to utilise a highly detailed, dynamic ALMaSS landscape model. It will consider the behaviour of all bee life stages daily and use state transitions to allow each individual to decide their behaviour. The development of egg-to-pupa stages in the nest will be temperature-driven. Adult bees, after they emerge from the nest in spring, will interact with the environment. They will be able to search for suitable nesting locations, provision their brood cells with pollen and reproduce. Modelled females will balance offspring size and number following the optimal allocation theory, but local environmental factors will modify their actual parental investment decisions. The model will include the daily mortality rate for the egg-to-pupa stages, overwintering mortality, and background mortality outside the nest. We will also consider the risk of open-cell parasitism as increasing with the time the brood cell is open.With the level of detail suggested, the model will be able to simulate population-level dynamics in response to multiple factors at the landscape scale over long periods. The European Food Safety Authority (EFSA) has suggested O. bicornis as a model organism for non-Apis solitary bees in the pesticide risk assessment scheme. Therefore, we hope our model will be a first step in building future landscape risk assessments for solitary bees. HTML XML PDF PubDate: Tue, 6 Jun 2023 09:16:43 +0300
Abstract: Food and Ecological Systems Modelling Journal 3: e91025 DOI : 10.3897/fmj.3.91025 Authors : Aïssétou Yabré, Jeanne-Marie Membré : In a context of transition towards plant-based protein diet, a survey aiming to collect the lentil consumer practices in France in 2022 was performed. There were 607 responses to the survey, of which a large majority (556) were lentil consumers. Amongst those, 283 people indicated that they currently eat more lentils than 5 years ago.The questions were related to type of lentil meals, frequency of consumption, type of preparation, storage duration once cooked etc. (Table 1). There were also general questions on age, gender and region. The survey may be used to obtain information on what type of lentils is consumed (and how often) in France, how it is cooked and stored. This information may be then plugged into a food safety risk assessment to refine, for instance, a microbial exposure model.In particular, of the 21 questions asked, four were about possible leftovers and their duration and two about cooling practices for hot meals. This information is crucial for lentils because consumer information about legumes, especially those prepared at home, is still scarce. HTML XML PDF PubDate: Wed, 5 Oct 2022 11:55:48 +0300
Abstract: Food and Ecological Systems Modelling Journal 3: e91024 DOI : 10.3897/fmj.3.91024 Authors : Christopher John Topping, Luna Kondrup Marcussen, Peet Thomsen, Jordan Chetcuti : Documenting complex models has long been a problem. Models are currently developed, implemented, and applied before review. Combined this leads to details hidden in the appendices or too little detail in the methods section to be reproducible. Modellers involve reviewers too late in the process. This does not allow them to flag issues, suggesting redesigns and reruns only after the analysis is complete. We propose splitting the model documentation, before analysis, into three steps: the Formal Model, Implementation Documentation, and Evaluation and Testing. Researchers can then use the well-built model for analysis. We introduce the first of these, the Formal Model as a peer-reviewed paper format that lays out the intentions for the model. The Formal Model includes reviewed literature that identifies the components of the model. Lays out the theoretical framework, modelling approaches and externalities. Plans to implement each process, with equations, descriptions, state variables and scales. Finally, the Formal Model gives the model’s strengths, weaknesses, exclusions, and place in the literature. We provide a flexible template for a Formal Model to aid in establishing a new common format.The Formal Model aims to improve transparency and provide a formal approach to documentation. Reviewers can help improve the model by identifying problems early. The Formal model contains the details needed to allow for reproducibility. It also encourages modellers to think about the consequences of what is and is not included within the model. And finally, it gives the credit that modellers deserve for the involved process of creating a model. HTML XML PDF PubDate: Tue, 4 Oct 2022 15:47:28 +0300
Abstract: Food and Ecological Systems Modelling Journal 2: e74171 DOI : 10.3897/fmj.2.74171 Authors : Petra Ganas, Marcel Fuhrmann, Matthias Filter : In our days, food supply chains are becoming more and more complex, generating global networks involving production, processing, distribution and sale of food products. To follow the "farm to fork" paradigm when assessing risks from various hazards linked to food products, supply chain network models are useful and versatile tools.The objective of the present "egg supply chain network model" is to allow users to predict and visualise the spatial commodity flow within the German egg supply chain. The network model provides for the user the option to select values for the input parameter "actor" in order to allow simulation of estimates for different supply chain scenarios. It generates a data frame as output regarding the estimates of food flows for the product "chicken eggs" in Germany on NUTS-3 level according to the selected parameter and a chloropleth map for illustrating the distribution of product quantities.The network model and all required resources are provided as a fully annotated file compliant to the community standard Food Safety Knowledge Exchange (FSKX) and can be executed online or with the desktop FSK-Lab software. HTML XML PDF PubDate: Wed, 17 Nov 2021 12:30:00 +020
Abstract: Food and Ecological Systems Modelling Journal 2: e70008 DOI : 10.3897/fmj.2.70008 Authors : Esther M. Sundermann, Guido Correia Carreira, Annemarie Käsbohrer : To reduce the burden of human society that is caused by zoonotic diseases, it is important to attribute sources to human illnesses. One powerful approach in supporting any intervention decision is mathematical modelling. This paper presents a source attribution model which considers five sources (broilers, laying hens, pigs, turkeys) for salmonellosis and uses two datasets from Germany collected over two time periods; one from 2004 to 2007 and one from 2010 to 2011. The model uses a Bayesian modelling approach derived from the so-called Hald model and is based on microbial subtyping. In this case, Salmonella isolates from humans and animals were subtyped with respect to serovar and phage type. Based on that typing, the model estimates how many human salmonellosis cases can be attributed to each of the considered sources. A reference description of the model is available under DOI : 10.1111/zph.12645. Here, we present this model as a ready-to-use resource in the Food Safety Knowledge Exchange (FSKX) format. This open information exchange format allows to re-use, modify, and further develop the model and uses model metadata and controlled vocabulary to harmonise the annotation. In addition to the model, we discuss some technical pitfalls that might occur when running this Bayesian model based on Markov chain Monte Carlo calculations. As source attribution of zoonotic disease is one useful tool for the One Health approach, our work facilitates the exchange, adjustment, and re-usage of this source attribution model by the international and multi-sectoral community. HTML XML PDF PubDate: Wed, 3 Nov 2021 09:15:00 +0200
Abstract: Food and Ecological Systems Modelling Journal 2: e63309 DOI : 10.3897/fmj.2.63309 Authors : Esther M. Sundermann, Maarten Nauta, Arno Swart : Dose-response models are an important part of quantitative microbiological risk assessments. In this paper, we present a transparent and ready-to-use version of a published dose-response model that estimates the probability of infection and illness after the consumption of a meal that is contaminated with the pathogen Campylobacter jejuni. To this end, model and metadata are implemented in the fskx-standard. The model parameter values are based on data from a set of different studies on the infectivity and pathogenicity of Campylobacter jejuni. Both, challenge studies and outbreaks are considered, users can decide which of these is most suitable for their purpose. We present examples of results for typical ingested doses and demonstrate the utility of our ready-to-use model re-implementation by supplying an executable model embedded in this manuscript. HTML XML PDF PubDate: Thu, 3 Jun 2021 11:00:00 +0300
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