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.
-Monitoring physical variables associated with honeybee colonies, including weight, temperature, humidity, respiratory gases, vibration, sound, and forager traffic, in a continuous manner is becoming feasible for most researchers as the cost and size of electronic sensors decrease while their precision and capacity increase. Researchers have taken different approaches to collecting and analyzing the resulting datasets, with a view toward extracting information on colony behavior and phenology. The objective of this review is to examine critically the different kinds of data and data analyses, providing researchers with better-informed options for obtaining information on colony phenology in the field without disturbing the hive, and for combining information from different kinds of sensors to obtain a more complete picture of colony status. Wireless sensor networks and powering sensors are briefly discussed.continuous hive weight / colony temperature / colony humidity / forager traffic / hive vibration
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.