Evolution of theoretical ecology in last decades: why did individual-based modelling emerge

Uchmański, Janusz; Kowalczyk, Kamila; Ogrodowczyk, Piotr

doi:10.12775/v10090-009-0002-3

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…For an example in which individual foraging decisions (behavioural ecology) were successfully used to predict food web complexity (community ecology), see [40]. Moreover, the development of individual-based and spatially explicit modelling provides tools to model ecological systems that integrate the behaviour of individuals [41] to their life histories and allow phenomena at higher levels of organization (populations, communities and ecosystems) to emerge from the interaction of processes at lower levels of organization [7,10] and spatial extent [42]. …”

Section: Previous Systems Approaches In Ecology Were Unsuccessfulmentioning

confidence: 99%

Predictive systems ecology

et al. 2013

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Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

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Section: Previous Systems Approaches In Ecology Were Unsuccessfulmentioning

confidence: 99%

Predictive systems ecology

et al. 2013

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“…An agent can be adaptive to its surrounding environment, and it can react to the environmental conditions . Recently, agent‐based modelling has been used in diverse fields such as economics, medicine, ecology, finance, and biology; however, an agent‐based model has not been used as a release phenomena simulator (especially flavour release).…”

Section: Introductionmentioning

confidence: 99%

An agent‐based simulation of a release process for encapsulated flavour using the NetLogo platform

Zandi

Mohebbi

2015

Flavour & Fragrance J

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In this study we developed an agent‐based model that simulates the release process of encapsulated flavour in different situations. Our model was built in the NetLogo platform, which is a multi‐agent programming language and modelling environment with a good documentation, user‐friendly environment and visualization abilities. The main aim of the work presented is to provide a model that will easily predict the release of encapsulated flavour. In this work we use the model developed to evaluate the flavour‐release properties (such as release time and rate) dependent upon input parameters. Release data of the encapsulated diacetyl (2,3‐butanedione) from alginate–whey‐protein concentrate microcapsules were then used for model validation. Results show that this model can simulate the release‐flavour process well, and there is a good correlation between experimental and model release data. Results also suggested that the flavour‐release process can easily be predicted using this agent‐based model. Copyright © 2015 John Wiley & Sons, Ltd.

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“…The development of ABMs that are based on general theories and first principles-so that they can be applied for different kind of OEUs, under different sets of biotic and abiotic circumstances, and at different spatiotemporal scales-has been a real challenge. For that, protocols, such as Pattern Oriented Modeling [88], Overview, Design concepts, and Details [89], and Approximate Bayesian Computation [90], have been proposed, evaluated [34,41,89,[91][92][93], and at least for one population successfully tested [94]. All this, as well as recent developments in trait-based approaches, molecular technologies, and big data approaches in general (Appendix 1), will help to further minimize the uncertainty and increase the general applicability of ABMs.…”

Section: Exploring Mechanismsmentioning

confidence: 99%

Enhancing the predictability of ecology in a changing world: A call for an organism-based approach

Musters

DeAngelis

Harvey

et al. 2023

Front. Appl. Math. Stat.

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Ecology is usually very good in making descriptive explanations of what is observed, but is often unable to make predictions of the response of ecosystems to change. This has implications in a human-dominated world where a suite of anthropogenic stresses are threatening the resilience and functioning of ecosystems that sustain mankind through a range of critical regulating and supporting services. In ecosystems, cause-and-effect relationships are difficult to elucidate because of complex networks of negative and positive feedbacks. Therefore, being able to effectively predict when and where ecosystems could pass into different (and potentially unstable) new states is vitally important under rapid global change. Here, we argue that such better predictions may be reached if we focus on organisms instead of species, because organisms are the principal biotic agents in ecosystems that react directly on changes in their environment. Several studies show that changes in ecosystems may be accurately described as the result of changes in organisms and their interactions. Organism-based theories are available that are simple and derived from first principles, but allow many predictions. Of these we discuss Trait-based Ecology, Agent Based Models, and Maximum Entropy Theory of Ecology and show that together they form a logical sequence of approaches that allow organism-based studies of ecological communities. Combining and extending them makes it possible to predict the spatiotemporal distribution of groups of organisms in terms of how metabolic energy is distributed over areas, time, and resources. We expect that this “Organism-based Ecology” (OE) ultimately will improve our ability to predict ecosystem dynamics.

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Evolution of theoretical ecology in last decades: why did individual-based modelling emerge

Cited by 3 publications

References 23 publications

Predictive systems ecology

Predictive systems ecology

An agent‐based simulation of a release process for encapsulated flavour using the NetLogo platform

Enhancing the predictability of ecology in a changing world: A call for an organism-based approach

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