Movement behavior is an essential element of fundamental ecological processes such as competition and predation. Although intraspecific trait variation (ITV) in movement behaviors is pervasive, its ...consequences for ecological community dynamics are still not fully understood. Using a newly developed individual‐based model, we analyzed how given and constant ITVs in foraging movement affect differences in foraging efficiencies between species competing for common resources under various resource distributions. Further, we analyzed how the effect of ITV on emerging differences in competitive abilities ultimately affects species coexistence. The model is generic but mimics observed patterns of among‐individual covariation between personality, movement and space use in ground‐dwelling rodents. Interacting species differed in their mean behavioral types along a slow–fast continuum, integrating consistent individual variation in average behavioral expression and responsiveness (i.e. behavioral reaction norms). We found that ITV reduced interspecific differences in competitive abilities by 5–35% and thereby promoted coexistence via an equalizing mechanism. The emergent relationships between behavioral types and foraging efficiency are characteristic for specific environmental contexts of resource distribution and population density. As these relationships are asymmetric, species that were either ‘too fast’ or ‘too slow’ benefited differently from ITV. Thus, ITV in movement behavior has consequences for species coexistence but to predict its effect in a given system requires intimate knowledge on how variation in movement traits relates to fitness components along an environmental gradient.
There are two major limitations to the potential of computational models in ecology for producing general insights: their design is path-dependent, reflecting different underlying questions, ...assumptions, and data, and there is too little robustness analysis exploring where the model mechanisms explaining certain observations break down. We here argue that both limitations could be overcome if modellers in ecology would more often replicate existing models, try to break the models, and explore modifications. Replication comprises the re-implementation of an existing model and the replication of its results. Breaking models means to identify under what conditions the mechanisms represented in a model can no longer explain observed phenomena. The benefits of replication include less effort being spent to enter the iterative stage of model development and having more time for systematic robustness analysis. A culture of replication would lead to increased credibility, coherence and efficiency of computational modelling and thereby facilitate theory development.
Ecosystem and community ecology have evolved along different pathways, with little overlap. However, to meet societal demands for predicting changes in ecosystem services, the functional and ...structural view dominating these two branches of ecology, respectively, must be integrated. Biodiversity –ecosystem function research has addressed this integration for two decades, but full integration that makes predictions relevant to practical problems is still lacking. We argue that full integration requires going, in both branches, deeper by taking into account individual organisms and the evolutionary and physico-chemical principles that drive their behavior. Individual-based models are a major tool for this integration. They have matured by using individual-level mechanism to replace the demographic thinking which dominates classical theoretical ecology. Existing individual-based ecosystem models already have proven useful both for theory and application. Still, next-generation individual-based models will increasingly use standardized and re-usable submodels to represent behaviors and mechanisms such as growth, uptake of nutrients, foraging, and home range behavior. The strategy of pattern-oriented modeling then helps make such ecosystem models structurally realistic by developing theory for individual behaviors just detailed enough to reproduce and explain patterns observed at the system level. Next-generation ecosystem scientists should include the individual-based approach in their toolkit and focus on addressing real systems because theory development and solving applied problems go hand-inhand in individual-based ecology.
The ‘ODD’ (Overview, Design concepts, and Details) protocol was published in 2006 to standardize the published descriptions of individual-based and agent-based models (ABMs). The primary objectives ...of ODD are to make model descriptions more understandable and complete, thereby making ABMs less subject to criticism for being irreproducible. We have systematically evaluated existing uses of the ODD protocol and identified, as expected, parts of ODD needing improvement and clarification. Accordingly, we revise the definition of ODD to clarify aspects of the original version and thereby facilitate future standardization of ABM descriptions. We discuss frequently raised critiques in ODD but also two emerging, and unanticipated, benefits: ODD improves the rigorous formulation of models and helps make the theoretical foundations of large models more visible. Although the protocol was designed for ABMs, it can help with documenting any large, complex model, alleviating some general objections against such models.
Decision makers must have sufficient confidence in models if they are to influence their decisions. We propose three screening questions to critically evaluate models with respect to their purpose, ...organization, and evidence. They enable a more transparent, robust, and secure use of model outputs.
•Uncertainty about validation is a challenge in using models for decision support.•Confusing terminology is a major cause of scepticism about model application.•Based on the modelling cycle, we ...devised a set of terms related to model evaluation.•We suggest “evaludation” to describe the entire process of model's quality.•Ecological modelling methods are too diverse to provide simple evaluation protocols.
Confusion about model validation is one of the main challenges in using ecological models for decision support, such as the regulation of pesticides. Decision makers need to know whether a model is a sufficiently good representation of its real counterpart and what criteria can be used to answer this question. Unclear terminology is one of the main obstacles to a good understanding of what model validation is, how it works, and what it can deliver. Therefore, we performed a literature review and derived a standard set of terms. ‘Validation’ was identified as a catch-all term, which is thus useless for any practical purpose. We introduce the term ‘evaludation’, a fusion of ‘evaluation’ and ‘validation’, to describe the entire process of assessing a model's quality and reliability. Considering the iterative nature of model development, the modelling cycle, we identified six essential elements of evaludation: (i) ‘data evaluation’ for scrutinising the quality of numerical and qualitative data used for model development and testing; (ii) ‘conceptual model evaluation’ for examining the simplifying assumptions underlying a model's design; (iii) ‘implementation verification’ for testing the model's implementation in equations and as a computer programme; (iv) ‘model output verification’ for comparing model output to data and patterns that guided model design and were possibly used for calibration; (v) ‘model analysis’ for exploring the model's sensitivity to changes in parameters and process formulations to make sure that the mechanistic basis of main behaviours of the model has been well understood; and (vi) ‘model output corroboration’ for comparing model output to new data and patterns that were not used for model development and parameterisation. Currently, most decision makers require ‘validating’ a model by testing its predictions with new experiments or data. Despite being desirable, this is neither sufficient nor necessary for a model to be useful for decision support. We believe that the proposed set of terms and its relation to the modelling cycle can help to make quality assessments and reality checks of ecological models more comprehensive and transparent.
The Overview, Design concepts and Details (ODD) protocol for describing Individual- and Agent-Based Models (ABMs) is now widely accepted and used to document such models in journal articles. As a ...standardized document for providing a consistent, logical and readable account of the structure and dynamics of ABMs, some research groups also find it useful as a workflow for model design. Even so, there are still limitations to ODD that obstruct its more widespread adoption. Such limitations are discussed and addressed in this paper: the limited availability of guidance on how to use ODD; the length of ODD documents; limitations of ODD for highly complex models; lack of sufficient details of many ODDs to enable reimplementation without access to the model code; and the lack of provision for sections in the document structure covering model design rationale, the model's underlying narrative, and the means by which the model's fitness for purpose is evaluated. We document the steps we have taken to provide better guidance on: structuring complex ODDs and an ODD summary for inclusion in a journal article (with full details in supplementary material; Table 1); using ODD to point readers to relevant sections of the model code; update the document structure to include sections on model rationale and evaluation. We also further advocate the need for standard descriptions of simulation experiments and argue that ODD can in principle be used for any type of simulation model. Thereby ODD would provide a lingua franca for simulation modelling.
Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical ...to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait‐ and individual‐based model of grassland community assembly by adding variation to the plants’ functional traits, which then drive life‐history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise‐coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively‐average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low‐diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity.
Bahlburg et al. re-implemented eight growth models of Antarctic krill and showed that their predictions are all over the place. The authors discuss the reasons for this and how more coherence in ...modelling could be achieved through systematic model comparison and integration. For this, we need a common language.
This open access book is about causal thinking and the use of causal language, with a focus on introducing philosophical ideas about causation to students and researchers of Social-Ecological Systems ...(SES). It takes a systematic approach to three central topics: the meanings of different causal expressions, sufficiency of evidence for inferences from observations to causal relations, and how to handle the complexity of causal relations in social-ecological systems. Consequently, the book is divided into three parts. In the first part the authors analyse and discuss the use of causal idiom in ordinary language, and in the second part they scrutinise the use of causal concepts and causal inference in science. Finally, the authors discuss causal reasoning about social-ecological systems in multi- and interdisciplinary contexts. This book provides an analysis of the concept of causation useful in the empirical sciences, where causal notions and idioms often are used without sufficient reflection. Empirical sciences often use causal idiom drawn from ordinary language, and similarly there is little formalisation of causal language and technical concepts in the humanities and social sciences. This book is a valuable resource for the application of current philosophical discussions about the concept of causation, in particular when applied to the analysis of social-ecological systems, but also when applied to research in the sciences and humanities.
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