Zakharova, Liubov

[["dc.bibliographiccitation.artnumber","109260"],["dc.bibliographiccitation.journal","Ecological Modelling"],["dc.bibliographiccitation.volume","434"],["dc.contributor.author","Zakharova, L."],["dc.contributor.author","Meyer, K. M."],["dc.contributor.author","Seifan, M."],["dc.date.accessioned","2020-12-08T08:09:33Z"],["dc.date.available","2020-12-08T08:09:33Z"],["dc.date.issued","2020"],["dc.description.abstract","Understanding the mechanisms driving community dynamics helps us to make reliable predictions about communities’ response to environmental change. Studying desert plant communities is particularly challenging because of strong intra- and interannual fluctuations in precipitation. Models rise to this challenge by providing an arena for systematic evaluation of the parameter space in virtual experiments. We applied a trait- and individual-based model to explore how community dynamics arise from the plant traits and interactions of plants with other plants and with their environment. The model is based on data from annual plant communities in the Negev Desert dominated by the True Rose of Jericho (Anastatica hierochuntica). We showed that functional traits that are involved in plant-plant interactions are equally important for community dynamics as traits promoting tolerance to abiotic stress. The sensitivity analysis of the model highlights relative growth rate, maximum biomass, the amount of time in dormancy and germination probability as the most important traits for community dynamics. The model reflects the particular importance of environmental factors such as precipitation and soil water availability based on topography for community dynamics. Our model benefits from the ability of individual-based models to capture plant-plant interactions and derive community properties from individual characteristics and from the feature of trait-based approaches to link traits to organismal functions. Our study demonstrates the advantages of the combined use of trait- and individual-based models for investigating community drivers in changing extreme environments."],["dc.identifier.doi","10.1016/j.ecolmodel.2020.109260"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/69459"],["dc.language.iso","en"],["dc.relation.issn","0304-3800"],["dc.relation.orgunit","Abteilung Ökosystemmodellierung"],["dc.subject.gro","Annual plants"],["dc.subject.gro","Community dynamics"],["dc.subject.gro","Functional trait"],["dc.subject.gro","Individual-based model"],["dc.subject.gro","Negev Desert"],["dc.title","Combining trait- and individual-based modelling to understand desert plant community dynamics"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","108703"],["dc.bibliographiccitation.journal","Ecological Modelling"],["dc.bibliographiccitation.volume","407"],["dc.contributor.author","Zakharova, L."],["dc.contributor.author","Meyer, K. M."],["dc.contributor.author","Seifan, M."],["dc.date.accessioned","2020-12-08T07:28:14Z"],["dc.date.available","2020-12-08T07:28:14Z"],["dc.date.issued","2019"],["dc.description.abstract","Trait-based approaches are an alternative to species-based approaches for functionally linking individual organisms with community structure and dynamics. In the trait-based approach, rather than focusing on the species identity of the organism, the focus is on the organism traits, which represent their physiological, morphological, or life-history characteristics. Although used in ecological research for several decades, this approach only emerged in ecological modelling about twenty years ago. We review this rise of trait-based models and trace the occasional transfer of trait-based modelling concepts between terrestrial plant ecology, animal and microbial ecology, and aquatic ecology, discuss terminology of trait-based approaches and evaluate future implementation of trait-based models, including cross-discipline exchange. Trait-based models have a variety of purposes, such as predicting changes in community patterns under climate and land-use change, understand underlying mechanisms for community assemblies, planning and assessing conservation management, or studying invasion processes. In modelling, trait-based approaches can reduce technical challenges such as computational limitations, scaling problems, and data scarcity. However, we note inconsistencies in the current usage of terms in trait-based approaches and these inconsistencies must be resolved if trait-based concepts are to be easily exchanged between disciplines. Specifically, future trait-based models may further benefit from incorporating intraspecific trait variability and addressing more complex species interactions. We also recommend expanding the combination of trait-based approaches with individual-based modelling to simplify the parameterization of models, to capture plant-plant interactions at the individual level, and to explain community dynamics under global change."],["dc.identifier.doi","10.1016/j.ecolmodel.2019.05.008"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/69445"],["dc.language.iso","en"],["dc.relation.issn","0304-3800"],["dc.relation.orgunit","Abteilung Ökosystemmodellierung"],["dc.subject.gro","Functional traits"],["dc.subject.gro","Functional types"],["dc.subject.gro","Model types"],["dc.subject.gro","Trait-based approach"],["dc.subject.gro","Trait-based model"],["dc.subject.gro","Individual-based modelling"],["dc.title","Trait-based modelling in ecology: A review of two decades of research"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","9"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Journal of Artificial Societies and Social Simulation"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Pietzsch, Bruno"],["dc.contributor.author","Fiedler, Sebastian"],["dc.contributor.author","Mertens, Kai G."],["dc.contributor.author","Richter, Markus"],["dc.contributor.author","Scherer, Cédric"],["dc.contributor.author","Widyastuti, Kirana"],["dc.contributor.author","Wimmler, Marie-Christin"],["dc.contributor.author","Zakharova, Liubov"],["dc.contributor.author","Berger, Uta"],["dc.date.accessioned","2020-12-08T08:09:17Z"],["dc.date.available","2020-12-08T08:09:17Z"],["dc.date.issued","2020"],["dc.description.abstract","The recent advancement of agent-based modeling is characterized by higher demands on the parameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for \"easy to go\" applications just mimicking the input-output behavior of such models. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consideration of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models."],["dc.identifier.doi","10.18564/jasss.4274"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/69456"],["dc.language.iso","en"],["dc.relation.issn","1460-7425"],["dc.relation.orgunit","Abteilung Ökosystemmodellierung"],["dc.rights","CC BY 4.0"],["dc.subject.gro","Individual-Based Model"],["dc.subject.gro","Surrogate Model"],["dc.subject.gro","Emulator"],["dc.subject.gro","Calibration"],["dc.subject.gro","Sensitivity Analysis"],["dc.subject.gro","Review"],["dc.title","Metamodels for Evaluating, Calibrating and Applying Agent-Based Models: A Review"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]