TY - JOUR A1 - Ayllon, Daniel A1 - Grimm, Volker A1 - Attinger, Sabine A1 - Hauhs, Michael A1 - Simmer, Clemens A1 - Vereecken, Harry A1 - Lischeid, Gunnar T1 - Cross-disciplinary links in environmental systems science BT - Current state and claimed needs identified in a meta-review of process models JF - The science of the total environment : an international journal for scientific research into the environment and its relationship with man N2 - Terrestrial environmental systems are characterised by numerous feedback links between their different compartments. However, scientific research is organized into disciplines that focus on processes within the respective compartments rather than on interdisciplinary links. Major feedback mechanisms between compartments might therefore have been systematically overlooked so far. Without identifying these gaps, initiatives on future comprehensive environmental monitoring schemes and experimental platforms might fail. We performed a comprehensive overview of feedbacks between compartments currently represented in environmental sciences and explores to what degree missing links have already been acknowledged in the literature. We focused on process models as they can be regarded as repositories of scientific knowledge that compile findings of numerous single studies. In total, 118 simulation models from 23 model types were analysed. Missing processes linking different environmental compartments were identified based on a meta-review of 346 published reviews, model inter-comparison studies, and model descriptions. Eight disciplines of environmental sciences were considered and 396 linking processes were identified and ascribed to the physical, chemical or biological domain. There were significant differences between model types and scientific disciplines regarding implemented interdisciplinary links. The most wide-spread interdisciplinary links were between physical processes in meteorology, hydrology and soil science that drive or set the boundary conditions for other processes (e.g., ecological processes). In contrast, most chemical and biological processes were restricted to links within the same compartment. Integration of multiple environmental compartments and interdisciplinary knowledge was scarce in most model types. There was a strong bias of suggested future research foci and model extensions towards reinforcing existing interdisciplinary knowledge rather than to open up new interdisciplinary pathways. No clear pattern across disciplines exists with respect to suggested future research efforts. There is no evidence that environmental research would clearly converge towards more integrated approaches or towards an overarching environmental systems theory. (c) 2017 Elsevier B.V. All rights reserved. KW - Review KW - Interdisciplinary links KW - Integrated environmental modelling KW - Research needs Y1 - 2018 U6 - https://doi.org/10.1016/j.scitotenv.2017.12.007 SN - 0048-9697 SN - 1879-1026 VL - 622 SP - 954 EP - 973 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Langhammer, Maria A1 - Thober, Jule A1 - Lange, Martin A1 - Frank, Karin A1 - Grimm, Volker T1 - Agricultural landscape generators for simulation models BT - a review of existing solutions and an outline of future directions JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - There is an increasing need for an assessment of the impacts of land use and land use change (LUCC). In this context, simulation models are valuable tools for investigating the impacts of stakeholder actions or policy decisions. Agricultural landscape generators (ALGs), which systematically and automatically generate realistic but simplified representations of land cover in agricultural landscapes, can provide the input for LUCC models. We reviewed existing ALGs in terms of their objectives, design and scope. We found eight ALGs that met our definition. They were based either on generic mathematical algorithms (pattern-based) or on representations of ecological or land use processes (process-based). Most ALGs integrate only a few landscape metrics, which limits the design of the landscape pattern and thus the range of applications. For example, only a few specific farming systems have been implemented. We conclude that existing ALGs contain useful approaches that can be used for specific purposes, but ideally generic modular ALGs are developed that can be used for a wide range of scenarios, regions and model types. We have compiled features of such generic ALGs and propose a possible software architecture. Considerable joint efforts are required to develop such generic ALGs, but the benefits in terms of a better understanding and development of more efficient agricultural policies would be high. KW - Agricultural landscape KW - Field pattern KW - Agricultural landscape generator KW - Landscape simulator KW - Neutral landscape model KW - Process-based model Y1 - 2019 U6 - https://doi.org/10.1016/j.ecolmodel.2018.12.010 SN - 0304-3800 SN - 1872-7026 VL - 393 SP - 135 EP - 151 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Augusiak, Jacqueline A1 - Van den Brink, Paul J. A1 - Grimm, Volker T1 - Merging validation and evaluation of ecological models to 'evaludation': A review of terminology and a practical approach JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - 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. (C) 2013 Elsevier B.V. All rights reserved. KW - Model validation KW - Terminology KW - Decision support KW - Documentation KW - Ecological models KW - Risk assessment Y1 - 2014 U6 - https://doi.org/10.1016/j.ecolmodel.2013.11.009 SN - 0304-3800 SN - 1872-7026 VL - 280 SP - 117 EP - 128 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Sibly, Richard M. A1 - Grimm, Volker A1 - Martin, Benjamin T. A1 - Johnston, Alice S. A. A1 - Kulakowska, Katarzyna A1 - Topping, Christopher J. A1 - Calow, Peter A1 - Nabe-Nielsen, Jacob A1 - Thorbek, Pernille A1 - DeAngelis, Donald L. T1 - Representing the acquisition and use of energy by individuals in agent-based models of animal populations JF - Methods in ecology and evolution : an official journal of the British Ecological Society N2 - Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests. KW - bioenergetics KW - energy budget KW - individual-based models KW - population dynamics Y1 - 2013 U6 - https://doi.org/10.1111/2041-210x.12002 SN - 2041-210X VL - 4 IS - 2 SP - 151 EP - 161 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Becher, Matthias A. A1 - Osborne, Juliet L. A1 - Thorbek, Pernille A1 - Kennedy, Peter J. A1 - Grimm, Volker T1 - Towards a systems approach for understanding honeybee decline - a stocktaking and synthesis of existing models JF - Journal of applied ecology : an official journal of the British Ecological Society N2 - 1. The health of managed and wild honeybee colonies appears to have declined substantially in Europe and the United States over the last decade. Sustainability of honeybee colonies is important not only for honey production, but also for pollination of crops and wild plants alongside other insect pollinators. A combination of causal factors, including parasites, pathogens, land use changes and pesticide usage, are cited as responsible for the increased colony mortality. 2. However, despite detailed knowledge of the behaviour of honeybees and their colonies, there are no suitable tools to explore the resilience mechanisms of this complex system under stress. Empirically testing all combinations of stressors in a systematic fashion is not feasible. We therefore suggest a cross-level systems approach, based on mechanistic modelling, to investigate the impacts of (and interactions between) colony and land management. 3. We review existing honeybee models that are relevant to examining the effects of different stressors on colony growth and survival. Most of these models describe honeybee colony dynamics, foraging behaviour or honeybee - varroa mite - virus interactions. 4. We found that many, but not all, processes within honeybee colonies, epidemiology and foraging are well understood and described in the models, but there is no model that couples in-hive dynamics and pathology with foraging dynamics in realistic landscapes. 5. Synthesis and applications. We describe how a new integrated model could be built to simulate multifactorial impacts on the honeybee colony system, using building blocks from the reviewed models. The development of such a tool would not only highlight empirical research priorities but also provide an important forecasting tool for policy makers and beekeepers, and we list examples of relevant applications to bee disease and landscape management decisions. KW - Apis mellifera KW - colony decline KW - feedbacks KW - integrated model KW - multiple stressors KW - predictive systems ecology KW - review Y1 - 2013 U6 - https://doi.org/10.1111/1365-2664.12112 SN - 0021-8901 VL - 50 IS - 4 SP - 868 EP - 880 PB - Wiley-Blackwell CY - Hoboken ER -