TY - JOUR A1 - Weise, Hanna A1 - Auge, Harald A1 - Baessler, Cornelia A1 - Bärlund, Ilona A1 - Bennett, Elena M. A1 - Berger, Uta A1 - Bohn, Friedrich A1 - Bonn, Aletta A1 - Borchardt, Dietrich A1 - Brand, Fridolin A1 - Jeltsch, Florian A1 - Joshi, Jasmin Radha A1 - Grimm, Volker T1 - Resilience trinity BT - safeguarding ecosystem functioning and services across three different time horizons and decision contexts JF - Oikos N2 - Ensuring ecosystem resilience is an intuitive approach to safeguard the functioning of ecosystems and hence the future provisioning of ecosystem services (ES). However, resilience is a multi-faceted concept that is difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough. We suggest a conceptual framework, resilience trinity, to facilitate management based on resilience mechanisms in three distinctive decision contexts and time-horizons: 1) reactive, when there is an imminent threat to ES resilience and a high pressure to act, 2) adjustive, when the threat is known in general but there is still time to adapt management and 3) provident, when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. Resilience has different interpretations and implications at these different time horizons, which also prevail in different disciplines. Social ecology, ecology and engineering are often implicitly focussing on provident, adjustive or reactive resilience, respectively, but these different notions of resilience and their corresponding social, ecological and economic tradeoffs need to be reconciled. Otherwise, we keep risking unintended consequences of reactive actions, or shying away from provident action because of uncertainties that cannot be reduced. The suggested trinity of time horizons and their decision contexts could help ensuring that longer-term management actions are not missed while urgent threats to ES are given priority. KW - concepts KW - ecosystems KW - ecosystem services provisioning KW - management KW - resilience Y1 - 2020 U6 - https://doi.org/10.1111/oik.07213 SN - 0030-1299 SN - 1600-0706 VL - 129 IS - 4 SP - 445 EP - 456 PB - Wiley-Blackwell CY - Oxford ER - TY - JOUR A1 - Grimm, Volker A1 - Berger, Uta T1 - Robustness analysis: Deconstructing computational models for ecological theory and applications JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - The design of computational models is path-dependent: the choices made in each step during model development constrain the choices that are available in the subsequent steps. The actual path of model development can be extremely different, even for the same system, because the path depends on the question addressed, the availability of data, and the consideration of specific expert knowledge, in addition to the experience, background, and modelling preferences of the modellers. Thus, insights from different models are practically impossible to integrate, which hinders the development of general theory. We therefore suggest augmenting the current culture of communicating models as working just fine with a culture of presenting analyses in which we try to break models, i.e., model mechanisms explaining certain observations break down. We refer to the systematic attempts to break a model as “robustness analysis” (RA). RA is the systematic deconstruction of a model by forcefully changing the model's parameters, structure, and representation of processes. We discuss the nature and elements of RA and provide brief examples. RA cannot be completely formalized into specific techniques and instead corresponds to detective work that is driven by general questions and specific hypotheses, with strong attention focused on unusual behaviours. Both individual modellers and ecological modelling in general will benefit from RA because RA helps with understanding models and identifying “robust theories”, which are general principles that are independent of the idiosyncrasies of specific models. Integrating the results of RAs from different models to address certain systems or questions will then provide a comprehensive overview of when certain mechanisms control system behaviour and when and why this control ceases. This approach can provide insights into the mechanisms that lead to regime shifts in actual ecological systems. KW - Sensitivity analysis KW - Ecological theory KW - Computational modelling KW - Robustness KW - Model analysis KW - Understanding Y1 - 2016 U6 - https://doi.org/10.1016/j.ecolmodel.2015.07.018 SN - 0304-3800 SN - 1872-7026 VL - 326 SP - 162 EP - 167 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Stillman, Richard A. A1 - Railsback, Steven Floyd A1 - Giske, Jarl A1 - Berger, Uta A1 - Grimm, Volker T1 - Making Predictions in a Changing World: The Benefits of Individual-Based Ecology JF - Bioscience N2 - Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions-fitness maximization by individual organisms-is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research. KW - ecology KW - fitness-maximization KW - individual-based KW - modeling KW - prediction Y1 - 2015 U6 - https://doi.org/10.1093/biosci/biu192 SN - 0006-3568 SN - 1525-3244 VL - 65 IS - 2 SP - 140 EP - 150 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Lin, Yue A1 - Huth, Franka A1 - Berger, Uta A1 - Grimm, Volker T1 - The role of belowground competition and plastic biomass allocation in altering plant mass-density relationships JF - Oikos Y1 - 2014 U6 - https://doi.org/10.1111/j.1600-0706.2013.00921.x SN - 0030-1299 SN - 1600-0706 VL - 123 IS - 2 SP - 248 EP - 256 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Lin, Yue A1 - Berger, Uta A1 - Grimm, Volker A1 - Huth, Franka A1 - Weiner, Jacob T1 - Plant interactions alter the predictions of metabolic scaling theory JF - PLoS one N2 - Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive. Y1 - 2013 U6 - https://doi.org/10.1371/journal.pone.0057612 SN - 1932-6203 VL - 8 IS - 2 PB - PLoS CY - San Fransisco ER - TY - JOUR A1 - Lin, Yue A1 - Berger, Uta A1 - Grimm, Volker A1 - Ji, Qian-Ru T1 - Differences between symmetric and asymmetric facilitation matter - exploring the interplay between modes of positive and negative plant interactions JF - The journal of ecology N2 - Facilitation (positive interaction) has received increasing attention in plant ecology over the last decade. Just as for competition, distinguishing different modes of facilitation (mutualistic, commensal or even antagonistic) may be crucial. We therefore introduce the new concept of symmetric versus asymmetric facilitation and present a generic individual-based zone-of-influence model. The model simultaneously implements different modes of both facilitation and competition among individual plants via their overlapping zone of influence. Because we consider facilitation modes as a continuum related to environmental context, we integrated this concept with the stress-gradient hypothesis (SGH) by exploring differences in spatial pattern formation in self-thinning plants along a stress gradient in our model. The interplay among modes of interaction creates distinctly varied spatial patterns along stress gradients. When competition was symmetric, symmetric facilitation (mutualism) consistently led to plant aggregation along stress gradients. However, asymmetric facilitation (commensalism) produces plant aggregation only under more benign conditions but tends to intensify local competition and spatial segregation when conditions are harsh. When competition was completely asymmetric, different modes of facilitation contributed little to spatial aggregation. Symmetric facilitation significantly increased survival at the severe end of the stress gradient, which supports the claim of the SGH that facilitation should have generally positive net effects on plants under high stress levels. Asymmetric facilitation, however, was found to increase survival only under intermediate stress conditions, which contradicts the current predictions of the SGH. Synthesis. Our modelling study demonstrates that the interplay between modes of facilitation and competition affects different aspects of plant populations and communities, implying context-dependent outcomes and consequences. The explicit consideration of the modes and mechanisms of interactions (both facilitation and competition) and the nature of stress factors will help to extend the framework of the SGH and foster research on facilitation in plant ecology. KW - asymmetry KW - competition KW - metabolic scaling theory KW - plant population and community dynamics KW - plant-plant interaction KW - self-thinning KW - spatial pattern KW - stress-gradient hypothesis KW - symmetry Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2745.2012.02019.x SN - 0022-0477 VL - 100 IS - 6 SP - 1482 EP - 1491 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Berger, Uta A1 - Piou, Cyril A1 - Schiffers, Katja A1 - Grimm, Volker T1 - Competition among plants : concepts, individual-based modelling approaches, and a proposal for a future research strategy N2 - Competition is a key process in plant populations and communities. We thus need, if we are to predict the responses of ecological systems to environmental change, a comprehensive and mechanistic understanding of plant competition. Considering competition, however, only at the population level is not sufficient because plant individuals usually are different, interact locally, and can adapt their behaviour to the current state of themselves and of their biotic and abiotic environment. Therefore, simulation models that are individual-based and spatially explicit are increasingly used for studying competition in plant systems. Many different individual-based modelling approaches exist to represent competition, but it is not clear how good they are in reflecting essential aspects of plant competition. We therefore first summarize current concepts and theories addressing plant competition. Then, we review individual-based approaches for modelling competition among plants. We distinguish between approaches that are used for more than 10 years and more recent ones. We identify three major gaps that need to be addressed more in the future: the effects of plants on their local environment, adaptive behaviour, and below-ground competition. To fill these gaps, the representation of plants and their interactions have to be more mechanistic than most existing approaches. Developing such new approaches is a challenge because they are likely to be more complex and to require more detailed knowledge and data on individual-level processes underlying competition. We thus need a more integrated research strategy for the future, where empirical and theoretical ecologists as well as computer scientists work together on formulating, implementing, parameterization, testing, comparing, and selecting the new approaches. (c) 2008 Rubel Foundation, ETH Zurich. Published by Elsevier GmbH. All rights reserved. Y1 - 2008 SN - 1433-8319 ER - TY - JOUR A1 - Grimm, Volker A1 - Berger, Uta A1 - Bastiansen, Finn A1 - Eliassen, Sigrunn A1 - Ginot, Vincent A1 - Giske, Jarl A1 - Goss-Custard, John A1 - Grand, Tamara A1 - Heinz, Simone K. A1 - Huse, Geir A1 - Huth, Andreas A1 - Jepsen, Jane U. A1 - Jorgensen, Christian A1 - Mooij, Wolf M. A1 - Mueller, Birgit A1 - Piou, Cyril A1 - Railsback, Steven Floyd A1 - Robbins, Andrew M. A1 - Robbins, Martha M. A1 - Rossmanith, Eva A1 - Rueger, Nadja A1 - Strand, Espen A1 - Souissi, Sami A1 - Stillman, Richard A. A1 - Vabo, Rune A1 - Visser, Ute A1 - DeAngelis, Donald L. T1 - A standard protocol for describing individual-based and agent-based models JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers. (c) 2006 Elsevier B.V. All rights reserved. KW - individual-based model KW - agent-based model KW - model description KW - scientific communication KW - standardization Y1 - 2006 U6 - https://doi.org/10.1016/j.ecolmodel.2006.04.023 SN - 0304-3800 VL - 198 SP - 115 EP - 126 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Grimm, Volker A1 - Revilla, Eloy A1 - Berger, Uta A1 - Jeltsch, Florian A1 - Mooij, Wolf M. A1 - Railsback, Steven Floyd A1 - Thulke, Hans-Hermann A1 - Weiner, Jacob A1 - Wiegand, Thorsten A1 - DeAngelis, Donald L. T1 - Pattern-oriented modeling of agend-based complex systems : lessons from ecology N2 - Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity Y1 - 2005 ER -