Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 351466
Title Field weed population dynamics : a review of model approaches and applications
Author(s) Holst, N.; Rasmussen, I.A.; Bastiaans, L.
Source Weed Research 47 (2007)1. - ISSN 0043-1737 - p. 1 - 14.
Department(s) Crop and Weed Ecology
Publication type Refereed Article in a scientific journal
Publication year 2007
Keyword(s) species hypericum-perforatum - tolerant rapeseed crops - ryegrass lolium-rigidum - long-term evolution - soybean glycine-max - seed bank dynamics - corn zea-mays - bioeconomic model - alopecurus-myosuroides - integrated management
Abstract Mathematical modelling is a commonly used tool for studying the long-term dynamics of weed populations in agriculture. This was reflected in our review by the large number of scientific papers (134 original publications) and the continuing need to gain an overview over this fast developing field (20 previous review papers were found). In this article, we provide a more comprehensive review than earlier seen, striving to include all relevant publications. Thus, we cover models of the population dynamics of 60 weed species in 40 crops. An online, accompanying database provides an indexed bibliography. Despite the large variation in crops, weeds and geography, the models were surprisingly similar in their approach: structured around the weed life cycle, excluding environmental factors and giving little attention to validation or even documentation of model construction. In addition, their application was similar, limited mostly to strategic decision making. We hope that the overview provided by this review will inspire weed modellers and that it will serve as a basis for discussion and as a frame of reference when we proceed to advance the modelling of weed populations to a new level, developing new approaches and tackling new application domains
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