After acquiring 91 km2 of lidar data from the Zacapu region, West Mexico, we confronted a series of issues that most archaeologists using this technology face. These include the large volume of data available, the limited training of potential “analysts,” the difficult development of a collective mapping tool and protocol, and the reliability of desk-based interpretation of archaeological features. In this article, we present an initiative conducted in 2015 and 2017 as an attempt to answer these methodological and pedagogical issues. We developed a web mapping platform to collectively interpret archaeological features using lidar-derived imagery and to train volunteer students to participate in this desk-based web mapping within a crowdsourcing framework. After evaluating the results of this initiative, we discuss the potential and limitations of this method for both lidar-based research and future training.

The discipline of weed science is at a critical juncture. Decades of efficient chemical weed control have led to a rise in the number of herbicide-resistant weed populations, with few new herbicides with unique modes of action to counter this trend and often no economical alternatives to herbicides in large-acreage crops. At the same time, the world population is swelling, necessitating increased food production to feed an anticipated 9 billion people by the year 2050. Here, we consider these challenges along with emerging trends in technology and innovation that offer hope of providing sustainable weed management into the future. The emergence of natural product leads in discovery of new herbicides and biopesticides suggests that new modes of action can be discovered, while genetic engineering provides additional options for manipulating herbicide selectivity and creating entirely novel approaches to weed management. Advances in understanding plant pathogen interactions will contribute to developing new biological control agents, and insights into plant–plant interactions suggest that crops can be improved by manipulating their response to competition. Revolutions in computing power and automation have led to a nascent industry built on using machine vision and global positioning system information to distinguish weeds from crops and deliver precision weed control. These technologies open multiple possibilities for efficient weed management, whether through chemical or mechanical mechanisms. Information is also needed by growers to make good decisions, and will be delivered with unprecedented efficiency and specificity, potentially revolutionizing aspects of extension work. We consider that meeting the weed management needs of agriculture by 2050 and beyond is a challenge that requires commitment by funding agencies, researchers, and students to translate new technologies into durable weed management solutions. Integrating old and new weed management technologies into more diverse weed management systems based on a better understanding of weed biology and ecology can provide integrated weed management and resistance management strategies that will be more sustainable than the technologies that are now failing.

Qualitative methods are gaining prominence in psychology, as well as related fields such as organizational behavior. Yet, we can find little evidence of qualitative research in our top industrial–organizational (I-O) psychology journals. We argue that the lack of research employing qualitative methods is a loss for the field, and we explore the reasons why few scholars adopt this approach. We then explore where this type of research is published and where it is not. Finally, we discuss and debunk several myths that continue to characterize qualitative methods with an eye toward encouraging a greater appreciation and acceptance of this research tradition.