2026-10-13T06:10:11Z https://aem.pensoft.net/oai.php

10.3897/fmj.1.46561 2019-09-17 fmj

Open Science meets Food Modelling: Introducing the Food Modelling Journal (FMJ) Filter,Matthias Candela,Leonardo Guillier,Laurent Nauta,Maarten Georgiev,Teodor Stoev,Pavel Penev,Lyubomir Open Science Agri-food Infrastructure Modelling Knowledge exchange Data analytics Data analysis workflows Information exchange formats Software tools Web services Databases Data collections Food and Ecological Systems Modelling Journal 1: e46561 This Editorial describes the rationale, focus, scope and technology behind the newly launched, open access, innovative Food Modelling Journal (FMJ). The Journal is designed to publish those outputs of the research cycle that usually precede the publication of the research article, but have their own value and re-usability potential. Such outputs are methods, models, software and data. The Food Modelling Journal is launched by the AGINFRA+ community and is integrated with the AGINFRA+ Virtual Research Environment (VRE) to facilitate and streamline the authoring, peer review and publication of the manuscripts via the ARPHA Publishing Platform. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2019 Editorial text/html info:doi:10.3897/fmj.1.46561 https://doi.org/10.3897/fmj.1.46561 https://aem.pensoft.net/article/46561/ https://aem.pensoft.net/article/46561/download/pdf/ en

10.3897/fmj.1.39643 2019-12-23 fmj

Quantitative microbial risk assessment for Salmonella in eggs Desvignes,Virginie Buschhardt,Tasja Guillier,Laurent Sanaa,Moez QMRA model eggs Salmonella Enteritidis R programming language Food and Ecological Systems Modelling Journal 1: e39643 The scope of this quantitative risk assessment model is to estimate the number of salmonellosis cases per million servings of table egg, as well as the probability of illness when ingesting a random serving of table egg. The model describes the potential egg contamination by Salmonella Enteritidis from farm to fork according to time/temperature storage conditions, as well as consumption practices. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2019 FSKX (Food Safety Knowledge) text/html info:doi:10.3897/fmj.1.39643 https://doi.org/10.3897/fmj.1.39643 https://aem.pensoft.net/article/39643/ https://aem.pensoft.net/article/39643/download/pdf/ en

10.3897/fmj.2.63309 2021-06-03 fmj

A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard Sundermann,Esther M. Nauta,Maarten Swart,Arno exchange format mathematical modelling infection probability illness probability campylobacteriosis food safety executable document Food and Ecological Systems Modelling Journal 2: e63309 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. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2021 FSKX (Food Safety Knowledge) text/html info:doi:10.3897/fmj.2.63309 https://doi.org/10.3897/fmj.2.63309 https://aem.pensoft.net/article/63309/ https://aem.pensoft.net/article/63309/download/pdf/ en

10.3897/fmj.2.70008 2021-11-03 fmj

An FSKX compliant source attribution model for salmonellosis and a look at its major hidden pitfalls Sundermann,Esther M. Correia Carreira,Guido Käsbohrer,Annemarie Salmonella R programming language mathematical modelling Bayesian model Markov chain Monte Carlo method Food Safety Knowledge Exchange (FSKX) format Food and Ecological Systems Modelling Journal 2: e70008 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. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2021 FSKX (Food Safety Knowledge) text/html info:doi:10.3897/fmj.2.70008 https://doi.org/10.3897/fmj.2.70008 https://aem.pensoft.net/article/70008/ https://aem.pensoft.net/article/70008/download/pdf/ en

10.3897/fmj.2.74171 2021-11-17 fmj

A network model of the egg supply chain in Germany implemented as a FSKX compliant object Ganas,Petra Fuhrmann,Marcel Filter,Matthias Food supply chain network Chicken eggs network model FSKX FSK-Lab Food and Ecological Systems Modelling Journal 2: e74171 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. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2021 FSKX (Food Safety Knowledge) text/html info:doi:10.3897/fmj.2.74171 https://doi.org/10.3897/fmj.2.74171 https://aem.pensoft.net/article/74171/ https://aem.pensoft.net/article/74171/download/pdf/ en

10.3897/fmj.3.91024 2022-10-04 fmj

The Formal Model article format: justifying modelling intent and a critical review of data foundations through publication Topping,Christopher John Kondrup Marcussen,Luna Thomsen,Peet Chetcuti,Jordan Food and Ecological Systems Modelling Journal 3: e91024 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. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2022 Formal Model Article Format text/html info:doi:10.3897/fmj.3.91024 https://doi.org/10.3897/fmj.3.91024 https://aem.pensoft.net/article/91024/ https://aem.pensoft.net/article/91024/download/pdf/ en

10.3897/fmj.3.91025 2022-10-05 fmj

Data from an online survey on lentil consumption practices in France in 2022 Yabré,Aïssétou Membré,Jeanne-Marie consumption survey consumer behaviour diet preference microbiological risk food safety lentils Food and Ecological Systems Modelling Journal 3: e91025 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. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2022 Data Paper (Biosciences) text/html info:doi:10.3897/fmj.3.91025 https://doi.org/10.3897/fmj.3.91025 https://aem.pensoft.net/article/91025/ https://aem.pensoft.net/article/91025/download/pdf/ en

10.3897/fmj.4.102102 2023-06-06 fmj

The Formal Model for the solitary bee Osmia bicornis L. agent‑based model Ziółkowska,Elżbieta Bednarska,Agnieszka Laskowski,Ryszard Topping,Christopher John agroecosystem pollinators population dynamics spatially-explicit model wild bees Food and Ecological Systems Modelling Journal 4: e102102 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. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2023 Formal Model Article Format text/html info:doi:10.3897/fmj.4.102102 https://doi.org/10.3897/fmj.4.102102 https://aem.pensoft.net/article/102102/ https://aem.pensoft.net/article/102102/download/pdf/ en

10.3897/fmj.4.100714 2023-06-29 fmj

GeSoN: A Geo-Social Network model applying bounded rationality to farmers in socio-ecological simulations Paparella,Antonio Cembalo,Luigi Topping,Christopher John Food and Ecological Systems Modelling Journal 4: e100714 info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/grantAgreement/EC/H2020/773554 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2023 Formal Model Article Format text/html info:doi:10.3897/fmj.4.100714 https://doi.org/10.3897/fmj.4.100714 https://aem.pensoft.net/article/100714/ https://aem.pensoft.net/article/100714/download/pdf/ en

10.3897/fmj.4.107849 2023-12-13 fmj

Modelling dynamic pesticide amounts in multiple environmental compartments at landscape scales in ALMaSS Poulsen,Trine Duan,Xiaodong Topping,Christopher John Food and Ecological Systems Modelling Journal 4: e107849 A dynamic model of the pesticide amount at a landscape scale (10 km x 10 km with the finest spatial resolution of 1 m2) is implemented in the ALMaSS (Animal, Landscape and Man Simulation System) framework. The spatial resolution can be configured, allowing the user to control how detailed the simulation should be according to the specific needs. Three application types, spray, seed coating treatment and granular, can be applied through the pesticide engine according to the management plan of crops in ALMaSS. A drift model is implemented for the spray application to include the effect on adjacent unsprayed areas. After applying a pesticide, the pesticide module controls transfer amongst different environmental compartments and follows the fate of up to ten different pesticides simultaneously. It enables ALMaSS to be used for complex risk assessment through impact studies of pesticides on many species, including pollinators. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2023 Methods text/html info:doi:10.3897/fmj.4.107849 https://doi.org/10.3897/fmj.4.107849 https://aem.pensoft.net/article/107849/ https://aem.pensoft.net/article/107849/download/pdf/ en

10.3897/fmj.5.109502 2024-03-06 fmj

Quantitative risk assessment of Haemolytic and Uremic Syndrome (HUS) from consumption of raw milk soft cheese Basak,Subhasish Christy,Janushan Guillier,Laurent Audiat-Perrin,Frederique Sanaa,Moez Tenenhaus-Aziza,Fanny Bect,Julien Vazquez,Emmanuel QMRA model raw milk soft cheese E. coli R programming language Food and Ecological Systems Modelling Journal 5: e109502 The aim of this quantitative risk assessment model is to estimate the risk of Haemolytic Uremic Syndrome (HUS) caused by Shiga-toxin producing Escherichia coli (STEC) in raw milk soft cheese and explore intervention strategies to minimise this risk. Building upon previous work from literature, the model considers microbial contamination of raw milk at the farm level, as well as STEC growth and survival during cheese production, ripening and storage, along with intervention strategies in both pre- and post-harvest scenarios. It allows for the assessment of intervention steps at the farm level or during cheese production. Besides estimating the risk of HUS, it also assesses the production losses associated with interventions. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2024 FSKX (Food Safety Knowledge) text/html info:doi:10.3897/fmj.5.109502 https://doi.org/10.3897/fmj.5.109502 https://aem.pensoft.net/article/109502/ https://aem.pensoft.net/article/109502/download/pdf/ en

10.3897/fmj.5.99103 2024-03-06 fmj

Modelling foraging strategies of honey bees as agents in a dynamic landscape representation Capela,Nuno Duan,Xiaodong Ziółkowska,Elżbieta Topping,Christopher John honey bee foraging model floral resource model ALMaSS agent-based model Food and Ecological Systems Modelling Journal 5: e99103 Introduction: Both intrinsic colony mechanisms and external environmental variables affect the honey bee colony development rates and response and a key aspect of this is the use of resources within the landscape by honey bees. Although several models have been developed to explore the foraging behaviour of bees, none fully considered the spatial and temporal dynamics of landscape resources and the role of the colony in the process.Methodology: Here, we introduce a new honey bee foraging model being developed as a part of the ApisRAM honey bee colony model. Based on agent-based modelling, we used a dynamic ALMaSS landscape model enhanced with floral resource modelling to assess the impacts of weather conditions and resource availability on the possible foraging behaviour of honey bees. Several possible mechanisms (defined, based on honey bee traits) for scouting and foraging were investigated, separately for nectar and pollen collection, including prioritising foraging polygons for nectar foraging according to their distance to the colony, the quality or the energetic efficiency and, for pollen foraging, according to their distance to the colony and pollen quantity.Results: If model foraging bees prioritised the polygons, based on their distance from the colony, the number of unsuccessful flights increased compared to other tested strategies and the total amount of sugar collected showed a high variability. Contrary to expectations, the energetic efficiency strategy did not provide the colony with the highest amount of sugar. Overall, the tested strategies provide different outcomes on the collection of resources, the number of performed flights and their success rate, evidencing that the model's outcome at the colony level arises from the individual types of behaviour.Conclusions and Relevance: Variability in the mass of collected nectar and pollen was found mostly when scout bees applied the distance strategy. This higher variability in sugar collection means that model bees were not able to find the most profitable foraging sites at the landscape level, but only at the local level. Other strategies showed less dependence on the surrounding landscape (i.e. quality or random), but it comes at a cost (i.e. lower production for both nectar and pollen collection). These outputs help us evaluate which strategies could be used for future model development and confirm the models' ability to create dynamic responses. These responses at the colony level were only possible thanks to the implementation of a dynamic landscape model and dynamic spatiotemporal resource model, as well as implementing a social communication mechanism for bees to share information about the resources. Plant nectar production and quality information is essential to predict honey bee foraging distribution. In future model development, the implementation of pollen quality should also be explored to evaluate if it influences the overall pollen collection. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/grantAgreement/EC/H2020/817622 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2024 Research Article text/html info:doi:10.3897/fmj.5.99103 https://doi.org/10.3897/fmj.5.99103 https://aem.pensoft.net/article/99103/ https://aem.pensoft.net/article/99103/download/pdf/ en

10.3897/fmj.5.117593 2024-03-06 fmj

Managing large and complex population operations with agent-based models: The ALMaSS Population_Manager Topping,Christopher John Duan,Xiaodong ALMaSS Agent-based model multi-threaded software scheduling simulation Food and Ecological Systems Modelling Journal 5: e117593 We describe the method used to manage large and complicated populations of autonomous agent-based animal models in the Animal Landscape and Man Simulation System, as implemented in the ALMaSS Population_Manager class. Using three examples, we show how this approach facilitates the representation of populations in a mixed serial and parallel computer model, contributes to the efficiency of code operation and allows detailed behavioural representations to be modelled. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2024 Methods text/html info:doi:10.3897/fmj.5.117593 https://doi.org/10.3897/fmj.5.117593 https://aem.pensoft.net/article/117593/ https://aem.pensoft.net/article/117593/download/pdf/ en

10.3897/fmj.5.121215 2024-06-27 fmj

ALMaSS Landscape and Farming Simulation: software classes and methods Topping,Christopher John Duan,Xiaodong ALMaSS OOP Vegetation Growth Modelling Food and Ecological Systems Modelling Journal 5: e121215 This article describes the landscape model for the Animal Landscape and Man Simulation System (ALMaSS). The article itself provides an overall description of the software classes and functions, with examples of use. In addition, there are links for code access, executable directory and code documentation for the model. These provide access to model details. The descriptions cover the landscape class, its internal data, and the class hierarchy primarily associated with the landscape simulation. They also cover the timing and scheduling of actions and provide an overview of the landscape class interface. The Farm and Farm Manager classes responsible for simulating farming activities are presented together with descriptions of crop classes for crop management and weather and calendar classes. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2024 Methods text/html info:doi:10.3897/fmj.5.121215 https://doi.org/10.3897/fmj.5.121215 https://aem.pensoft.net/article/121215/ https://aem.pensoft.net/article/121215/download/pdf/ en

10.3897/fmj.5.123747 2024-07-11 fmj

Formal model for Acyrthosiphon pisum, Aphis fabae, Myzus persicae and Sitobion avenae using the ALMaSS subpopulation approach Thomsen,Peet Duan,Xiaodong Topping,Christopher John Acyrthosiphon pisum ALMaSS Aphis fabae black bean aphid grain aphid Myzus persicae pea aphid peach aphid Sitobion avenae subpopulation Food and Ecological Systems Modelling Journal 5: e123747 Aphids are one of the most harmful insect species for crops and are thus an important group to model in ALMaSS because they drive both management and natural enemy dynamics. Due to the enormous number of aphids, using an agent-based method to model aphids is not feasible. To deal with this, we propose creating an Aphid model using a spatial subpopulation model approach. Built on the dynamic landscape model in ALMaSS, subpopulations are assumed to occupy the landscape in a set of regular grid cells of equal size. The aphid population will be tracked in each grid using a stage-structured population model; population size and behaviour will depend on the habitat structure under the grid. They will develop, reproduce, and die based on the aphids’ physiological processes, the effects of predators, and the grids’ weather and vegetation host conditions. Aphid dispersal by flying and local movement to adjacent grids will interconnect the populations in the grid cells. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2024 Formal Model Article Format text/html info:doi:10.3897/fmj.5.123747 https://doi.org/10.3897/fmj.5.123747 https://aem.pensoft.net/article/123747/ https://aem.pensoft.net/article/123747/download/pdf/ en

10.3897/fmj.5.122467 2024-11-12 fmj

A general subpopulation model for the Animal Landscape and Man Simulation System (ALMaSS) Duan,Xiaodong Topping,Christopher John ALMaSS dispersal landscape simulation mortality reproduction subpopulation modelling Food and Ecological Systems Modelling Journal 5: e122467 ALMaSS (the Animal Landscape and Man Simulation System) is a well-established modelling system known for its detailed agent-based animal models. However, for certain species, such as aphids, extremely high population sizes and limited detailed individual behaviour information make agent-based approaches either computationally expensive or unfeasible. Additionally, when these species are modelled as a prey base for other species, such as aphids for ladybirds, an efficient and accurate modelling approach is required. To address these challenges, we introduce a subpopulation-based model framework that effectively handles high population densities, while reducing computational complexity. This framework divides the landscape into a non-overlapping grid and population dynamics are managed within each grid using a flexible stage-structured population model. Grids are interconnected through short- and long-distance dispersal mechanisms, allowing for realistic movement and interactions. Parallel programming is employed to enhance performance, enabling faster simulation runs. We demonstrate the application of this model framework with a hypothetical species (not a species in the real world) and showcase its use in modelling aphid populations. This foundational subpopulation model could be used to model species with large population sizes within the ALMaSS framework and can be integrated into other simulation systems. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2024 Methods text/html info:doi:10.3897/fmj.5.122467 https://doi.org/10.3897/fmj.5.122467 https://aem.pensoft.net/article/122467/ https://aem.pensoft.net/article/122467/download/pdf/ en

10.3897/fmj.6.142802 2025-02-14 fmj

The Formal Model for the butterfly Pieris napi (Lepidoptera, Pieridae) agent-based model in the Animal Landscape and Man Simulation System (ALMaSS) Topping,Christopher John Duan,Xiaodong Agent-based model ALMaSS dispersal foraging parasitoids Pieris napi Food and Ecological Systems Modelling Journal 6: e142802 We present a formal model for Pieris napi, the green-veined white. This model is intended for inclusion in the Animal Landscape and Man Simulation System as the basis for regulatory assessment of the impacts of pesticides on butterfly pollinators. We propose implementing the model using an individual-based format, with the added complication of a dynamically coupled individual-based model for parasitoids and hyperparasitoids. The model’s main drivers are weather, temperature and the distribution of larval food plants and nectar forage resources in space and time. A prototype model description is presented, describing the full model ready for implementation. The model considers individuals at all life stages, from eggs to adults and utilises thermal performance models to represent development. Movement is modelled in detail, integrating dispersal, egg laying and foraging. Mortality sources include parasitoids, background mortality, slow development and pesticide and farm management mortality. A simple toxicological model is described as a basis for future expansion. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Formal Model Article Format text/html info:doi:10.3897/fmj.6.142802 https://doi.org/10.3897/fmj.6.142802 https://aem.pensoft.net/article/142802/ https://aem.pensoft.net/article/142802/download/pdf/ en

10.3897/fmj.6.149273 2025-06-17 fmj

Landscapes from the bee perspective: an application of SolBeePop to field study data Schmolke,Amelie Galic,Nika Hinarejos,Silvia floral resources landscape composition Osmia bicornis population model solitary bees Food and Ecological Systems Modelling Journal 6: e149273 Introduction: The temporal and spatial pattern of floral resources in a landscape is an important driver of dynamics of pollinator species, such as solitary bees. Thus, the representation of complex landscapes in models is of interest when assessing whether landscapes could provide sufficient resources to sustain populations of solitary bee species. The consideration of landscape compositions is also important when estimating exposures to pesticides and their potential effects on managed and natural populations. At the same time, information on the use of complex landscapes by solitary bees is lacking for most species. This challenges the inclusion of this important aspect into models representing bee species and model applications for risk assessment and management. Methods: In the current paper, we tested options to include different levels of information available to represent compositions of agricultural landscapes. We applied the population model for solitary bees, SolBeePop, to simulate untreated control trials from field studies conducted with Osmia bicornis, compared model outputs to study data and assessed model performance using different scenarios. First, we reviewed literature reporting pollen compositions of bee-collected brood provisions for O. bicornis. As studies were conducted in a range of different landscapes and geographical regions, generalised floral preferences of the species could be derived. Results: In aggregating land-cover information using increasingly detailed information, we showed that the consideration of multiple resources across the landscape and study period improved the model performance in representing the field study data. At the same time, we demonstrated that simplified, conservative scenarios can be generated and evaluated with the model if information is lacking on species’ preferences as well as resource distributions in time and space. Conclusions and relevance: The representation of complex landscapes using different levels of detail makes SolBeePop a flexible tool for simulating solitary bee populations in agricultural landscapes using often limited information, thereby supporting ecological risk assessment and management. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Research Article text/html info:doi:10.3897/fmj.6.149273 https://doi.org/10.3897/fmj.6.149273 https://aem.pensoft.net/article/149273/ https://aem.pensoft.net/article/149273/download/pdf/ en

10.3897/fmj.6.152847 2025-07-18 fmj

The Formal Model for the hoverfly Eristalis tenax (Diptera, Syrphidae) agent-based model in the Animal Landscape and Man Simulation System (ALMaSS) Ziółkowska,Elżbieta Walczyńska,Aleksandra Topping,Christopher John Agroecosystem common drone fly pollinators population dynamics spatially explicit model syrphids Food and Ecological Systems Modelling Journal 6: e152847 We present a formal model for Eristalis tenax, the common drone fly, one of the most widespread syrphid species globally. This model is intended for inclusion in the Animal Landscape and Man Simulation System as a basis for regulatory assessment of the effects of pesticides on hoverfly pollinators. We propose to implement the model using an individual-based approach. The main drivers of the model are temperature, larval habitat distribution and quality, and nectar and pollen food resources in space and time. A prototype model description is presented that describes the full model, ready for implementation. The model considers individuals at all life stages, from egg to adult, with development from egg to pupa driven by temperature and larval development also influenced by larval density linked with the larval habitat quality. The model uses thermal performance curve models to represent the development and survival of the pupal stage, which is the most critical moment in the life cycle. Movement is modelled in detail, integrating dispersal, oviposition and foraging. Sources of mortality include overwintering mortality, slow development, density-dependent mortality at the larval stage, background mortality and pesticide and farm management mortality. A simple toxicological model is described as a basis for future expansion. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Formal Model Article Format text/html info:doi:10.3897/fmj.6.152847 https://doi.org/10.3897/fmj.6.152847 https://aem.pensoft.net/article/152847/ https://aem.pensoft.net/article/152847/download/pdf/ en

10.3897/fmj.6.152914 2025-08-07 fmj

The Formal Model for Coccinella septempunctata for implementation in Animal Landscape and Man Simulation System Topping,Christopher John Ziółkowska,Elżbieta Chuhutin,Andrey Duan,Xiaodong Agent-based model ALMaSS ecology and behaviour landscape model seven-spotted ladybird Food and Ecological Systems Modelling Journal 6: e152914 We present the Formal Model for the seven-spotted ladybird Coccinella septempunctata L., to be implemented in the Animal Landscape and Man Simulation System. This agent-based model is designed to dynamically interact with pre-existing aphid species models, providing a foundation for studying the effects of landscape-scale management on these species. It also serves as a crucial component in developing a model system to support the analysis of Integrated Pest Management strategies. We present an extensive literature survey of C. septempunctata ecology and behaviour. The model primarily considers temperature and aphid prey availability as the major driving factors, given the species’ reliance on aphids during its juvenile stage. Mechanisms and parameters are, as far as possible, derived from previous models and literature studies. Each major section of behaviour is described first in terms of what is known ecologically and secondly in terms of planned implementation. We present a description of the factors included in the model and those consciously excluded, providing justifications for these decisions. Additionally, we discuss aspects of the model’s implementation and identify data gaps, highlighting specific areas for future improvement. The next phase involves the implementation and calibration of the model. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Formal Model Article Format text/html info:doi:10.3897/fmj.6.152914 https://doi.org/10.3897/fmj.6.152914 https://aem.pensoft.net/article/152914/ https://aem.pensoft.net/article/152914/download/pdf/ en

10.3897/fmj.6.155397 2025-09-03 fmj

UrbanAnts: An R Shiny app for exploring ant diversity data in urban environments Gonçalves,Débora Silva,Nathalia Sampaio da Pires do Prado,Livia Morini,Maria Anthropogenic habitat ecology biodiversity biological data repository data-driven conservation Formicidae fauna monitoring species occurrence records Food and Ecological Systems Modelling Journal 6: e155397 With the advance of urbanisation and the challenges associated with the process of documenting new species, biodiversity is increasingly threatened, especially in urban areas, where species are more exposed to the negative effects of landscape transformation. In this context, databases are fundamental tools for documenting, monitoring and conserving biological diversity. Within this scope, UrbanAnts was developed as a web application designed to centralise information on ant diversity and occurrences in urban environments. The platform was created using the Shiny framework, built on the R programming language and integrated with a relational SQLite database. UrbanAnts improves accessibility and streamlines data exploration, enabling users to efficiently retrieve and analyse information. In addition, it serves as a tool that highlights the importance of conserving the diversity of ant fauna in urban environments. This database is accessible to the public through the dissemination of knowledge and the encouragement of participation, allowing contributions from both professionals who study ants and members of the general public interested in collaborating through citizen science. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Software Description text/html info:doi:10.3897/fmj.6.155397 https://doi.org/10.3897/fmj.6.155397 https://aem.pensoft.net/article/155397/ https://aem.pensoft.net/article/155397/download/pdf/ en

10.3897/fmj.6.167755 2025-10-27 fmj

MAASSD: Methodology for Agent-based modelling for Agricultural System Simulation in Developing Countries BELEM,Mahamadou Agent-based model agricultural system meta-model modelling framework simulation Food and Ecological Systems Modelling Journal 6: e167755 Modelling agricultural systems in developing countries is attracting particular attention, as the models provide policy-makers with a relevant framework for ex ante analysis of their decision-making processes, enabling them to develop policies to address future challenges such as climate change and population growth. Agent-based modelling (ABM) is increasingly being used for this purpose. ABM enables the simulation of the heterogeneity of farmers’ decision-making processes and the interactions between human decision-making processes and the environment. However, despite the wide use of ABM in simulating agricultural systems in developing countries, a clear methodology is still lacking. Current applications of ABM in agricultural system simulations are disparate and cannot be replicated in other contexts. This study aims to propose a unique methodology for agent-based modelling of agricultural systems in developing countries. The resulting methodology, ‘MAASSD’ (Methodology for Agent-based Modelling for Agricultural System Simulation in Developing Countries), is generic and multi-scale, taking into account multi-stakeholder engagement for knowledge integration and sharing. Our methodology is based on existing methodologies and provides a unique approach to agricultural system modelling using ABM. However, MAASSD methodology differs from these existing methodologies with regard to agricultural systems. The methodology has been tested in the simulation of the feedback loop between agricultural dynamics and migration in Burkina Faso, demonstrating its robustness. In future, the MAASSD methodology will be tested in a large number of contexts to demonstrate its effectiveness in representing agricultural systems in developing countries. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Methods text/html info:doi:10.3897/fmj.6.167755 https://doi.org/10.3897/fmj.6.167755 https://aem.pensoft.net/article/167755/ https://aem.pensoft.net/article/167755/download/pdf/ en

10.3897/fmj.6.166845 2025-11-12 fmj

Energy modelling of the economic and environmental sustainability of rice farming in southern Brazil Carvalho Junior,Oldemar D'Aquino,Carla de Abreu Agroecology emergy ecosystem services green urban infrastructure nature-based solutions Food and Ecological Systems Modelling Journal 6: e166845 This study presents an emergy-based systems model to analyze the economic and environmental sustainability of rice farming in southern Brazil, with a focus on the states of Santa Catarina and Rio Grande do Sul. Odum’s ecological systems theory is at the heart of the model. It measures all flows of energy, matter, and services, whether they are renewable or not, using a single unit called solar emergy joules (seJ). This lets us look at the whole picture. By constructing an energy diagram and calculating critical energy-based sustainability indicators (%R, EYR, EIR, ELR, ESI, EFR), the model quantifies the system’s significant dependence on external inputs and underutilization of local ecosystem services. Although the current production model is important for the economy, the results show that it is not very sustainable. It has a very low emergy sustainability index (ESI = 0.26), a very low proportion of renewable sources (%R = 0.15), and a high environmental loading (ELR = 5.73). However, the rice-field landscape has a lot of potential to be used as a Nature-Based Solution if it is managed in more than one way. The results of the modeling efforts offer a solid quantitative foundation for the development of transformative policies, including the recognition of rice fields as multifunctional Green Urban Infrastructure and the implementation of payments for environmental services, in order to promote a more climate-adaptive and resilient agricultural system. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Research Article text/html info:doi:10.3897/fmj.6.166845 https://doi.org/10.3897/fmj.6.166845 https://aem.pensoft.net/article/166845/ https://aem.pensoft.net/article/166845/download/pdf/ en

10.3897/fmj.6.165232 2025-12-10 fmj

The Formal Model for Noctua pronuba (Lepidoptera, Noctuidae) representing a typical agricultural-landscape night-flying moth species for pesticide risk assessment Topping,Christopher John Pettersson,Lars B. Agent-based model ALMaSS noctuid moth risk assessment model Food and Ecological Systems Modelling Journal 6: e165232 Nocturnal lepidopteran pollinators face pesticide exposure risks in agricultural landscapes, yet lack adequate risk assessment frameworks compared to diurnal species. We present a formal model description for Noctua pronuba within the Animal Landscape and Man Simulation System (ALMaSS), providing the first comprehensive agent-based framework for assessing the impacts of pesticides on nocturnal moth pollinators. The model integrates temperature-dependent development using Lobry–Rosso–Flandrois thermal performance curves, stage-specific behaviours including photoperiod-triggered reproductive diapause and nocturnal foraging, and realistic dispersal capabilities up to 11 km. Three pesticide exposure pathways (dietary intake, contact, and overspray) enable risk assessment across all life stages, while multiple mortality sources capture natural population regulation through parasitism, disease, and density-dependent processes. Model parameterisation primarily draws on comprehensive historical studies of N. pronuba, supplemented by data from related noctuid species where gaps exist. The framework’s modular design enables adaptation to other nocturnal lepidopteran species by adjusting parameters. We explicitly define the model’s applicability domain as temperate European agricultural systems and acknowledge key limitations, including the exclusion of evolutionary responses and sublethal pesticide effects. This spatially explicit, behaviorally realistic framework provides regulators with a practical tool for comparing relative pesticide risks across landscape scenarios while recognising inherent uncertainties in predicting absolute population outcomes. The model addresses a critical gap in pollinator risk assessment by representing an ecologically important but understudied guild of nocturnal pollinators. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2025 Formal Model Article Format text/html info:doi:10.3897/fmj.6.165232 https://doi.org/10.3897/fmj.6.165232 https://aem.pensoft.net/article/165232/ https://aem.pensoft.net/article/165232/download/pdf/ en

10.3897/fmj.7.169793 2026-02-27 fmj

The Formal Model for the hoverfly Sphaerophoria scripta (Diptera, Syrphidae) agent-based model in the Animal Landscape and Man Simulation System (ALMaSS) Ziółkowska,Elżbieta Sowa,Grzegorz Duan,Xiaodong Topping,Christopher John Agroecosystem aphidophagous hoverfly biological control Long Hoverfly pollinator population dynamics spatially-explicit model Food and Ecological Systems Modelling Journal 7: e169793 We present a formal model for the aphidophagous hoverfly Sphaerophoria scripta, a species widely used for biological control of Myzus persicae and other aphids, as well as for pollination services. The model is structured for integration within the Animal Landscape and Man Simulation System (ALMaSS) to investigate population dynamics under variable field conditions, with the overarching aim of improving regulatory risk assessments of pesticide impacts on hoverflies. Our approach is individual-based, spatially explicit, and operates on a daily time step. The principal model drivers include temperature, the spatial and temporal distribution of aphid prey for larvae, and the availability of nectar and pollen resources for adult females. Dispersal functions are designed to interact dynamically with foraging and oviposition behaviours, with daily activity patterns governed by the interplay between reproductive objectives and foraging requirements. Key life-history parameters, including egg incubation duration, larval instar development, pupariation, adult longevity, and fecundity, were derived from available laboratory and field studies. The prototype model defines state transitions, developmental thresholds, mortality functions, and foraging-oviposition behaviours, and is prepared for calibration and scenario-based application. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2026 Formal Model Article Format text/html info:doi:10.3897/fmj.7.169793 https://doi.org/10.3897/fmj.7.169793 https://aem.pensoft.net/article/169793/ https://aem.pensoft.net/article/169793/download/pdf/ en

10.3897/fmj.7.175714 2026-03-16 fmj

Concept for APODEMUS – a wood mouse population model for pesticide risk assessment Singer,Alexander Schmolke,Amelie Becher,Matthias von Blanckenhagen,Felix van den Brink,Nico Grimm,Tina Ibrahim,Lara Imholt,Christian Jacob,Jens Jakoby,Oliver Laucht,Silke Løvik,Amund N. Martin,Thomas C. Muñoz,Cynthia Preuss,Thomas G. Galic,Nika Apodemus sylvaticus conceptual model pesticide risk assessment Pop-GUIDE small mammal spatially-explicit stakeholder involvement transparent modelling decisions Food and Ecological Systems Modelling Journal 7: e175714 The wood mouse, Apodemus sylvaticus, is a small mammal species that occurs across large parts of Europe. The species uses various habitats, has an omnivorous diet and can use pesticide-treated agricultural fields for foraging. Thus, it is one of the focal species in risk assessments of plant protection products (PPPs) in the European Union. However, exposures and effects of PPPs on populations in the field are challenging to assess across different regions and landscapes. Population modelling is suggested as a tool in higher-tier risk assessments, complementing and extending data from field studies. Population models can predict population-level effects from modelled life-cycle processes and individual-level exposure and effects. We present the development of a conceptual model for APODEMUS, a POpulation Dynamical spatially Explicit Model of the wood mOUSe. We used best practices for model development recommended in recent guidance documents by the European Food Safety Authority (EFSA). Thereby, we focus on the ecological model without the explicit representation of exposures and effects of PPPs as the first part of the model development. We conducted a comprehensive literature search and review on wood mouse ecology. The resulting data compilation was used as the basis for the development of the conceptual model. Decisions about processes included in or excluded from the model were taken in collaboration with stakeholders including small mammal experts, risk assessors and regulators, as well as ecological modellers. Beyond the presentation of the conceptual model for APODEMUS, we discuss the importance of stakeholder involvement in the model development process. In addition, we suggest additions to the comprehensive approach to model development for ecological risk assessment (Pop-GUIDE), particularly with respect to risk assessments of small mammals in the European Union. Our study shows how the systematic development of a population model with continued stakeholder support can lead to a transparent tool for higher-tier risk assessments. info:eu-repo/semantics/altIdentifier/eissn/2815-3197 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2026 Formal Model Article Format text/html info:doi:10.3897/fmj.7.175714 https://doi.org/10.3897/fmj.7.175714 https://aem.pensoft.net/article/175714/ https://aem.pensoft.net/article/175714/download/pdf/ en

10.3897/aem.8.194160 2026-04-14 fmj

A journal by modellers, for modellers: Introducing Agricultural and Environmental Modelling Topping,Christopher John Nogoy,Nicole Boyadzhieva,Iva Stoev,Pavel Penev,Lyubomir Agricultural modelling ARPHA ecological modelling environmental modelling modelling lifecycle open science scholarly publishing Agricultural and Environmental Modelling 8: e194160 Modelling is central to modern agricultural, ecological and environmental science. From agent-based simulations of pollinator populations to coupled food-system models informing policy, the computational and mathematical work of modellers underpins some of the most consequential scientific outputs of our time. Yet the publishing landscape has consistently struggled to give that work its due. Formal model descriptions, calibration studies, implementation documentation and software workflows have rarely found a natural home in traditional journals. Too often, the foundational work that makes applied modelling possible goes uncited, unreviewed and unrewarded. Agricultural and Environmental Modelling (AEM) exists to change that. Through several iterations, this journal is the evolution of the Food and Ecological Systems Modelling Journal (FESMJ) and its earliest predecessor: the Food Modelling Journal (FMJ). AEM has now broadened in scope, deepened in Open Science ambition and redesigned around the full lifecycle of modelling research. info:eu-repo/semantics/altIdentifier/eissn/3134-1810 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2026 Editorial text/html info:doi:10.3897/aem.8.194160 https://doi.org/10.3897/aem.8.194160 https://aem.pensoft.net/article/194160/ https://aem.pensoft.net/article/194160/download/pdf/ en

10.3897/aem.8.184962 2026-04-27 fmj

Integrating spatial and environmental stressors in a population model of Folsomia candida (Collembola, Isotomidae): a Formal Model within ALMaSS framework Xie,Liyan Duan,Xiaodong Norouzi,Sarem de Jonge,Lis Wollesen Topping,Christopher John Environmental risk assessment multiple stressors population dynamics population matrix model spatially explicit model springtails Agricultural and Environmental Modelling 8: e184962 Collembola are key soil invertebrates that contribute to decomposition processes and nutrient cycling in agricultural ecosystems. Folsomia candida, a parthenogenetic euedaphic species, is widely used as a model organism in ecotoxicological testing, yet population-level responses to environmental stressors in spatially structured landscapes remain poorly understood. We present a formal model of F. candida developed using a subpopulation approach within the Animal, Landscape and Man Simulation System (ALMaSS). The model integrates stage-structured population dynamics with spatially explicit landscape processes, incorporating hourly weather data and daily soil moisture dynamics at 10 by 10 m resolution. Growth, development, reproduction, and mortality are driven by temperature, soil moisture, and food quality through empirically parameterised thermal performance curves and dose–response functions fitted to published experimental data. The model explicitly represents egg, juvenile, and adult life stages, with stage transitions and vital rates responding non-linearly to environmental conditions. Soil moisture effects are modelled using a novel integration of ERA5 reanalysis data, soil physical properties, and evapotranspiration to estimate surface soil water potential. Temperature and moisture effects are combined using a limiting-factor approach, reflecting current understanding of physiological constraints. The model is designed for simulations at subpopulation spatial scales of 100 m2, within landscapes typically 10 km × 10 km, providing a mechanistic framework for exploring F. candida population dynamics under realistic environmental heterogeneity in agricultural landscapes. This formal model documentation establishes the theoretical foundation and empirical basis for subsequent model implementation, evaluation, and application to questions in landscape ecology and environmental risk assessment. info:eu-repo/semantics/altIdentifier/eissn/3134-1810 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2026 Formal Model Article Format text/html info:doi:10.3897/aem.8.184962 https://doi.org/10.3897/aem.8.184962 https://aem.pensoft.net/article/184962/ https://aem.pensoft.net/article/184962/download/pdf/ en

10.3897/aem.8.167439 2026-04-29 fmj

Development of a spatio-temporal representation of agricultural landscapes as the modelling environment for spatially explicit agent-based models in the Animal Landscape and Man Simulation System (ALMaSS) Ziółkowska,Elżbieta Jaśkowiec,Barbara Groom,Geoffrey Brian Topping,Christopher John Agricultural data farming structure Integrated Administration and Control System (IACS) land-use/land-cover data Land Parcel Identification System (LPIS) landscape heterogeneity landscape simulation Agricultural and Environmental Modelling 8: e167439 The model environment constitutes the core component of the Animal, Landscape, and Man Simulation System (ALMaSS). ALMaSS was developed to evaluate the effects of changes in landscape structure and management on key animal species within agroecosystems. Consequently, it is designed to work with representations of actual agricultural landscape areas, capturing both spatial and temporal landscape heterogeneity to fulfil the specific requirements of the ALMaSS species models. This article presents the methodology for describing the land-use/land-cover of agricultural landscapes and generating detailed landscape representations for use in ALMaSS landscape simulations. We outline the external data requirements and data handling procedures necessary to prepare the final set of input files for an ALMaSS run. We provide a mapping algorithm to generate a landscape (land-use/land-cover) raster map and describe the methods for classifying and defining ALMaSS farm types and crop rotations. We present exemplary results and discuss potential applications beyond the ALMaSS modelling framework. Finally, we examine the ALMaSS landscape model generation process in the context of input data quality, accessibility, and data processing challenges and offer a perspective on future developments. info:eu-repo/semantics/altIdentifier/eissn/3134-1810 info:eu-repo/semantics/openAccess CC BY 4.0 Pensoft Publishers 2026 Methods text/html info:doi:10.3897/aem.8.167439 https://doi.org/10.3897/aem.8.167439 https://aem.pensoft.net/article/167439/ https://aem.pensoft.net/article/167439/download/pdf/ en