Trond Simensen

• Horvath, Peter; Halvorsen, Rune; Simensen, Trond & Bryn, Anders (2021). A comparison of three ways to assemble wall-to-wall maps from distribution models of vegetation types. GIScience & Remote Sensing. ISSN 1548-1603. 58(8), s. 1458–1476. doi: 10.1080/15481603.2021.1996313. Fulltekst i vitenarkiv Vis sammendrag

  Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. While most often used for modeling species, distribution modeling methods can also be applied to vegetation types. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. The paper compares the performance of three methods for assembling predictions for multiple vegetation types, modeled individually, into a wall-to-wall map. The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. Thus the assembly methods worked in two principally different ways: the probability-based method assigned vegetation types to grid cells in a cell-by-cell manner, and both the performance-based method and prevalence-based method assigned them in a type-by-type manner. All methods were evaluated by use of reference data collected in the field, more or less independently of the data used to parameterize the vegetation-type models. Quantity, allocation, and total disagreement, as well as proportional dissimilarity metrics, were used for evaluation of assembly methods. Overlay analysis showed 38.1% agreement between all three assembly methods. The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics. The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved. area frame survey, assembly strategies, distribution modeling, spatial probabilities, vegetation mapping, vegetation types

• Simensen, Trond; Erikstad, Lars & Halvorsen, Rune (2021). Diversity and distribution of landscape types in Norway. Norsk Geografisk Tidsskrift. ISSN 0029-1951. s. 1–23. doi: 10.1080/00291951.2021.1892177. Fulltekst i vitenarkiv
• Halvorsen, Rune; Skarpaas, Olav; Bryn, Anders; Bratli, Harald; Erikstad, Lars & Simensen, Trond [Vis alle 7 forfattere av denne artikkelen] (2020). Towards a systematics of ecodiversity: the Ecosyst framework. Global Ecology and Biogeography. ISSN 1466-822X. 29(11), s. 1887–1906. doi: 10.1111/geb.13164. Fulltekst i vitenarkiv Vis sammendrag

  Background Although a standard taxonomy of organisms has existed for nearly 300 years, no consensus has yet been reached on principles for systematization of ecological diversity (i.e., the co‐ordinated variation of abiotic and biotic components of natural diversity). In a rapidly changing world, where nature is under constant pressure, standardized terms and methods for characterization of ecological diversity are urgently needed (e.g., to enhance precision and credibility of global change assessments). Aim The aim is to present the EcoSyst framework, a set of general principles and methods for systematization of natural diversity that simultaneously addresses biotic and abiotic variation, and to discuss perspectives opened by this framework. Innovation EcoSyst provides a framework for systematizing natural variation in a consistent manner across different levels of organization. At each ecodiversity level, EcoSyst principles can be used to establish: (a) an extensive attribute system with descriptive variables that cover all relevant sources of variation; (b) a hierarchical‐type system; and (c) a set of guidelines for land‐cover mapping that is consistent across spatial scales. EcoSyst type systems can be conceptualized as multidimensional models, by which a key characteristic (the response) is related to variation in one or more key sources of variation (predictors). EcoSyst type hierarchies are developed by a gradient‐based iterative procedure, by which the “ecodiversity distance” (i.e., the extent to which the key characteristic differs between adjacent candidate types) is standardized and the ecological processes behind observed patterns are explicitly taken into account. Application We present “Nature in Norway” (NiN), an implementation of the EcoSyst framework for Norway for the ecosystem and landscape levels of ecodiversity. Examples of applications to research and management are given. Conclusion The EcoSyst framework provides a theoretical platform, principles and methods that can complement and enhance initiatives towards a global‐scale systematics of ecodiversity. iodiversity complex gradient continuum theory ecodiversity ecosystem geodiversity gradient landscape mapping typology

• Simensen, Trond; Horvath, Peter; Vollering, Julien; Erikstad, Lars; Halvorsen, Rune & Bryn, Anders (2020). Composite landscape predictors improve distribution models of ecosystem types. Diversity and Distributions: A journal of biological invasions and biodiversity. ISSN 1366-9516. 26(8), s. 928–943. doi: 10.1111/ddi.13060. Fulltekst i vitenarkiv Vis sammendrag

  Aim: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red-list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner-outer coast” and “land use intensity.” Location: Norway. Methods: We used data from field-based ecosystem-type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data. Results: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models. Main conclusions: Our study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.conservation planning, distribution modelling, ecosystem classification, ecosystem types, IUCN Red List of Ecosystems, landscape gradients, spatial prediction, species response curves

• Simensen, Trond; Halvorsen, Rune & Erikstad, Lars (2018). Methods for landscape characterisation and mapping: A systematic review. Land Use Policy. ISSN 0264-8377. 75, s. 557–569. doi: 10.1016/j.landusepol.2018.04.022. Fulltekst i vitenarkiv

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• Simensen, Trond Aalvik (2021). History, state of art and future of landscape ecological research.
• Simensen, Trond (2019). Nordlige barskoger kan bli et usikkert karbonlager. Aftenposten Viten. ISSN 2464-3033. s. 18–19.
• Halleraker, Jo Halvard; Simensen, Trond; Løbersli, Else Marie; Nybø, Signe & Alfredsen, Knut (2019). Bridging ecology-science with decision making - despite different understanding of the science policy interface . Vis sammendrag

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• Simensen, Trond; Halvorsen, Rune; Erikstad, Lars & Bakkestuen, Vegar (2018). A gradient perspective on landscape classification.
• Asmervik, Sigmund & Simensen, Trond (2005). The roots of ecourbanism.
• Simensen, Trond & Hofstad, Christian (2003). TDR 03. Vis sammendrag

  Det utstilte kunstverket beskriver, forklarer og illustrerer et nytt planverktøy for bærekraftig byutvikling. Forslaget beskriver et planverktøy som griper inn i eiendomsforholdene gjennom en mekansime for overføring av utbyggingsrettigheter.

• Simensen, Trond (2021). Mapping and analysis of landscape diversity. Thesis for the degree for Philosophiae Doctor (PhD). University of Oslo, Faculty of Mathematics and Natural Sciences, Natural History Museum.

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