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  • 1.
    Angelstam, Per
    et al.
    SLU.
    Mikusinski, Grzegorz
    Örebro.
    Rönnbäck, Britt-Inger
    Östman, Anders
    Lazdinis, Marius
    SLU.
    Roberge, Jean-Michel
    SLU.
    Arnberg, W.
    Stockholms Universitet.
    Olsson, Jan
    Örebro.
    Two-dimensional gap analysis: a tool for efficient conservation planning and biodiversity policy implementation2003Ingår i: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 32, nr 8, s. 527-534Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The maintenance of biodiversity by securing representative and well-connected habitat networks in managed landscapes requires a wise combination of protection, management, and restoration of habitats at several scales. We suggest that the integration of natural and social sciences in the form of "Two-dimensional gap analysis" is an efficient tool for the implementation of biodiversity policies. The tool links biologically relevant "horizontal" ecological issues with "vertical" issues related to institutions and other societal issues. Using forest biodiversity as an example, we illustrate how one can combine ecological and institutional aspects of biodiversity conservation, thus facilitating environmentally sustainable regional development. In particular, we use regional gap analysis for identification of focal forest types, habitat modelling for ascertaining the functional connectivity of "green infrastructures", as tools for the horizontal gap analysis. For the vertical dimension we suggest how the social sciences can be used for assessing the success in the implementation of biodiversity policies in real landscapes by identifying institutional obstacles while implementing policies. We argue that this interdisciplinary approach could be applied in a whole range of other environments including other terrestrial biota and aquatic ecosystems where functional habitat connectivity, nonlinear response to habitat loss and a multitude of economic and social interests co-occur in the same landscape.

  • 2. Rönnbäck, Britt-Inger
    Are uncertain uncertainties useful?: towards improved quality assessment of spatial data2004Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    A decision is usually based on some kind of information. In the decision- taking phase it is important to know the extent to which the information about the different alternatives that are to be decided on is reliable. This doctoral thesis focuses on data quality assessment in spatial analysis, and especially on evaluating data usability in the decision- taking phase. The first focus concerns the situation when information about the accuracy of source data is missing or insufficient. Questionnaires and interviews are used to obtain such information. In an effort to make the survey- situation user-friendlier and to obtain answers that are as complete as possible, a questionnaire template allowing vague responses and imprecise information is developed. The advantage and perhaps also the disadvantage of that concept are the independence of standardised data quality elements, as well as of available metadata. It is shown that a procedure for quality assessment by using a questionnaire allowing vague responses indeed increases the response rate. However, a recommended improvement is to include methods that assure that reliable answers are obtained. Then the second focus is on the decision-taking phase, where uncertainties in source datasets and their influences on the fitness for use for a specific decision are studied. The goal is to develop a procedure for decision analysis where expected utility measures are used to quantify the effects that uncertainties and errors in source data have on rational decisions. The purpose of this is to endeavour to make the decision-takers more aware of the impact that the uncertainties in the datasets used may have on their decisions. It is shown that standardised data quality elements are extremely useful for evaluating usability, but they have to be transformed into a domain understood by the user. Furthermore, it is shown that the expected utility of each dataset can be a measure of fitness for use in decision analysis. One advantage of such an approach is that it clearly demonstrates the connection between data quality, decisions and environmental and financial costs and benefits. When estimating the probabilities of different events, spatial micro-simulation techniques have proven to be useful. To improve the procedure, however, macro-constraints should also be used for aligning the simulation model. Three different case studies have been performed. As a result of these studies some basic procedures that are needed for data quality evaluation have been identified, viz. “Data quality assessment by using a questionnaire”, “Construction of artificial perfect datasets”, “Micro- simulation”, “Monte Carlo simulation”, “Artificial decision- maker”, “Decision evaluator”, and “Data variability reporter”. The studies also verify that these procedures can connect to each other. The idea is that they can be arranged in different ways, and hence be used in different contexts.

  • 3.
    Rönnbäck, Britt-Inger
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Arkitektur och vatten.
    Cellular automata as a tool for three-dimensional quality assessment1998Licentiatavhandling, monografi (Övrigt vetenskapligt)
  • 4. Rönnbäck, Britt-Inger
    et al.
    Nordberg, Maj-Liz
    Department of Physical Geography, Quaternary Geology, Stockholm University.
    Olsson, Anders
    Luleå tekniska universitet.
    Östman, Anders
    Evaluation of environmental monitoring strategies2003Ingår i: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 32, nr 8, s. 495-501Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In environmental monitoring, it is important that the monitoring system should emit early warnings when undesired events occur. These events may be sudden or of a more subtle nature. In the design of such monitoring systems, a proper balance between cost and risk must be achieved. There are 2 classic types of risk connected with early warning systems, namely the risk of not detecting significant changes and the risk of false alarms. The purpose of this paper is to describe a method for comparing the performance of different monitoring systems, considering the classic types of risk and cost. The method is applied to the monitoring of the lichen cover as a test case. The expected utility has been used as a measure of performance. When estimating the probabilities of the events, spatial microsimulation and Monte-Carlo simulation techniques have been used. The monitoring programs studied are based on satellite images, aerial photos, field samples, and land-cover maps. The major conclusions of this study are that standardized quality measures are extremely useful for evaluating the usability of environmental monitoring methods. In addition, when estimating gains and costs, spatial microsimulation techniques are useful. To improve the method, however, macroconstraints should also be used for aligning the simulation model.

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