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    Transnational field QA assessment: a tool to interpret spatial and temporal trends in plant diversity. Abstracts of the ICP Forests Conference 2012 "Monitoring european forests: detecting and understanding changes”

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    Maintenance of comparability and variability ranges in long-term studies is a major target. Monitoring forest ground vegetation has problematic facets which may lead to misinterpretation of plant diversity trends. When covering European scale programmes, methodological differences by Countries can introduce large bias, leading to consider this factor as a covariate. In the frame of the Life+ project FutMon, a first transnational inter-comparison course on plant diversity assessments was held, to test the differences between countries/surveyors. Objectives. Assess the accuracy and precision rates of vascular species density; inspect the sources of variation due to both different design\methods and observers; define Data Quality Indicators. Methods. Experimental field design in a Beech stand on Cansiglio plateau (Italy), was based on a common sampled area of 200 m2. (A) Three 50*50m plots devoted to surveys applying Country’s own sampling and assessment methods (including observer’s and methodological effects). (B) One 50*50m plot used for surveys applying a common sampling design and method (highlighting observer’s effects). (A)-(B) estimated the effect due to different methods. A “consensus species list” was used as standard reference. Accuracy was considered as the expression of the overall error, composed by precision (variance of species density) and bias (respect to the reference). Main results. Both precision and accuracy for the species density estimates were much lower on (B). Sources of variation were depicted as the mean performance of an ICP-Forests GV observer: the expected error, in terms of CV%, had a 49%magnitude, 2⁄3 due to the observer’s errors, and 1⁄3 due to methodological aspects. Tentative definition of Data Quality Indicators was discussed, although the indications from a unique international exercise are still unstable. The foreseen objective of 90% of observers achieving a MQO threshold of 30% respect to the reference, seems reasonable when a standardized sampling area is adopted

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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