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Abstract. Effective disaster management is a core feature for the protection of communities against natural disasters such as floods. Disaster management organizations (DMOs) are expected to contribute to ensuring this protection. However, what happens when their resources to cope with a flood are at stake or the intensity and frequency of the event exceeds their capacities? Many cities in the Free State of Saxony, Germany, were strongly hit by several floods in the last years and are additionally challenged by demographic change, with an ageing society and out-migration leading to population shrinkage in many parts of Saxony. Disaster management, which is mostly volunteer-based in Germany, is particularly affected by this change, leading to a loss of members. We propose an agent-based simulation model that acts as a "virtual lab" to explore the impact of various changes on disaster management performance. Using different scenarios we examine the impact of changes in personal resources of DMOs, their access to operation relevant information, flood characteristics as well as differences between geographic regions. A loss of DMOs and associated manpower caused by demographic change has the most profound impact on the performance. Especially in rural, upstream regions population decline in combination with very short lead times can put disaster management performance at risk.

Wood is a limited resource which is exposed to a continuously growing global demand not least because of a politically fostered bioenergy use. One approach to master the challenge to sustainably meet this increasing wood demand is short rotation forestry (SRF). However, SRF is only gradually evolving and it is not fully understood which determinants hamper its expansion. This study provides theoretical insights into economic and environmental determinants of an SRF expansion and their interplay. This assessment requires the incorporation of farmers' decision-making based on an explicit investment appraisal. Therefore, we use an agent-based model to depict the decision- making of profit-maximizing farmers facing the choice between SRF, the cultivation of conventional annual agricultural crops and abstaining from cultivation (fallow land). The land use decisions are influenced by general economic determinants, such as market prices for wood and annual crops, and by site-dependent determinants, such as the environmental site quality. We found that the willingness to pay for SRF-based products and for annual crops most strongly influences the coverage of SRF in the landscape. SRF will in most cases be established on sites with low productivity. However, a decrease in the willingness to pay for annual crops will lead to a reallocation of SRF plantations to sites with higher productivity. Furthermore, our model results indicate that the impact of the distance to processing plants on farmers' decisions strongly depends on general economic determinants and the given spatial structure of the underlying natural landscape. Analysing the relative importance of different determinants of an SRF expansion, this study gives insights into the approach of using SRF to sustainably meet the growing wood demand. Moreover, these insights are taken as a starting point for the design of effective government interventions to promote SRF.

We develop a comprehensive multi-level approach to ecological economics (CML-approach) which integrates philosophical considerations on the foundations of ecological economics with an adequate operationalization. We argue that the subject matter and aims of ecological economics require a specific combination of inter- and transdisciplinary research, and discuss the epistemological position on which this approach is based. In accordance with this understanding of inter- and transdisciplinarity and the underlying epistemological position, we develop an operationalization which comprises simultaneous analysis on three levels of abstraction: concepts, models and case studies. We explain these levels in detail, and, in particular, deduce our way of generic modeling in this context. Finally, we illustrate the CML-approach and demonstrate its fruitfulness by the example of the sustainable management of semi-arid rangelands.

We analyze a dynamic and stochastic ecological-economic model of grazing management in semi-arid rangelands. The non-equilibrium ecosystem is driven by stochastic precipitation. A risk averse farmer chooses a grazing management strategy under uncertainty such as to maximize expected utility from farming income. Grazing management strategies are rules about which share of the rangeland is given rest depending on the actual rainfall in that year. In a first step we determine the farmer's short-term optimal grazing management strategy. We show that a risk averse farmer chooses a strategy such as to obtain insurance from the ecosystem: the optimal strategy reduces income variability, but yields less mean income than possible. In a second step we analyze the long-run ecological and economic impact of different strategies. We conclude that the more risk averse a farmer is, the more conservative and sustainable is his short-term optimal grazing management strategy, even if he has no specific preference for the distant future.

Im vorliegenden Aufsatz wird ein Begriffskonzept entwickelt, das zum besseren Verständnis des Zusammenspiels der Dynamiken von Ökosystemen und Wirtschaft dient: das Konzept des Bestandes. Der Bestandsbegriff wird allgemein mengentheoretisch formuliert. Die zentrale Eigenschaft eines Bestandes liegt in seiner zeitlichen Dauerhaftigkeit. Damit eignen sich Bestände zur Abbildung von Einflüssen, die die Vergangenheit von Systemen auf deren Gegenwart ausübt, und damit zur Analyse von zeitlichen Entwicklungen. Da Beständigkeit eine Eigenschaft in der Zeit darstellt, ist das Konzept des Bestandes nicht spezifisch auf den Gegenstandsbereich einzelner wissenschaftlicher Disziplinen beschränkt und so für die interdisziplinäre Analyse geeignet. Der Begriff wird auf ökonomische und ökologische Beispiele angewandt und dabei auf stochastische Mengen verallgemeinert. Durch die Abgrenzung der Bestandsperspektive von einer Systemsicht kann die hierarchische Struktur realer ökologisch-ökonomischer Systeme analysiert werden. Die Theorie der Bestände stellt einen Baustein für die konzeptionellen Grundlagen der Ökologischen Ökonomie dar.

Meta-X is a user-friendly computer program that allows students, teachers, and researchers to perform a metapopulation viability analysis i.e. to assess the extinction risk of (meta)populations on discrete, partially isolated patches of habitat, in a comfortable way. The CD comes with an extensive handbook which explains the basic concept of the program and takes you on a guided tour through a model experiment. It further provides the necessary scientific background on both metapopulation dynamics and population viability analysis. A special feature of Meta-X is that it supports comparative analyses of alternative scenarios. This predestines Meta-X to serve as an aid for decision making in conservation management and landscape planning. Furthermore, handbook and software together provide an invaluable help in research and teaching. System Requirements:Windows 95/98, Windows 2000, Windows NT 4.0, or Windows XP, Pentium Processor with a least 133 MHz, 64 MB RAM, 15 MB of free space on hard disk, CD-ROM drive with at least 4x speed, Microsoft Internet Explorer 4.0 or higher

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socioenvironmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socioenvironmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems. ; National Socio-Environmental Synthesis Center (SESYNC) under the National Science Foundation [DBI-1639145]; Australian Government Research Training Program (AGRTP) ScholarshipAustralian Government; ANU Hilda-John Endowment Fund; USDAUnited States Department of Agriculture (USDA); ARSUnited States Department of Agriculture (USDA)USDA Agricultural Research Service [58-3091-6-035]; Texas A&M AgriLife Research; Key Program of NSF of China [41930648]; NSFNational Science Foundation (NSF) [EEC 1937012] ; Published version ; This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1639145. The primary author (Takuya Iwanaga) is supported through an Australian Government Research Training Program (AGRTP) Scholarship and a top-up scholarship from the ANU Hilda-John Endowment Fund. Hsiao-Hsuan Wang and Tomasz E. Koralewski acknowledge partial support from USDA, ARS Agreement No. 58-3091-6-035 with Texas A&M AgriLife Research, titled `Areawide pest management of the invasive sugarcane aphid in grain sorghum, regional population monitoring and forecasting.' Min Chen is supported by the Key Program of NSF of China (No. 41930648). John Little acknowledges partial support from NSF Award EEC 1937012. The authors would like to thank the three anonymous reviewers and Prof. Randall Hunt (USGS) for their constructive feedback and comments. The authors additionally thank Faye Duchin and Adrian Hindes for comments provided on an earlier draft. ; Public domain authored by a U.S. government employee