Using Egocentric Networks to Illustrate Information Seeking and Sharing by Alfalfa Farmers in Wyoming

We explored using farmers\u27 egocentric (personal) networks to understand how they seek farming advice and how their advice networks map onto their friendship networks. We examined results from a survey of alfalfa farmers (n = 634) in Wyoming. Farmers reported seeking advice from neighbors and fellow farmers, and most indicated that these people are also their friends. In this article, we outline the procedure for collecting egocentric network data and report some of our results from using this tool. We conclude by illustrating the utility of acquiring egocentric network information for Extension professionals across domains, contending that such information can facilitate Extension program and technology implementation and information sharing with the public

Organic Agriculture Teaching and Learning in 2025: Transforming the Future Learning Landscape

University instructors are compelled to anticipate future changes in farming and food systems that will impact their students. Sixteen educators met in 2018 to envision the future of organic agriculture courses needed by 2025. Likely future global issues include food access, especially for people of limited economic means; climate change; and fossil fuel costs. Changes that will impact education are increasing demand for quality food, more organic production, and globalization of food systems due to consolidation. Probable course content changes are increasing focus on whole farm systems; designing for resilience in changing physical, economic, environmental, and political climates; and increasing diversity of systems and emergence of the urban and peri-urban food sector. Expected changes in teaching methods include more practical, hands-on learning; face-to-face interactions with farmers; guided practical apprenticeships; and student-driven learning activities. We were surprised by the difficulty that workshop participants confronted in discussing transformational change, often opting for fine-tuning the current system. We identified a need for developing and practicing skills for future visioning, currently a challenge for instructors and for many students

A Unifying Gravity Framework for Dispersal

Most organisms disperse at some life-history stage, but different research traditions to study dispersal have evolved in botany, zoology, and epidemiology. In this paper, we synthesize concepts, principles, patterns, and processes in dispersal across organisms. We suggest a consistent conceptual framework for dispersal, which utilizes generalized gravity models. This framework will facilitate communication among research traditions, guide the development of dispersal models for theoretical and applied ecology, and enable common representation across taxonomic groups, encapsulating processes at the source and destination of movement, as well as during the intervening relocation process, while allowing each of these stages in the dispersal process to be addressed separately and in relevant detail. For different research traditions, certain parts of the dispersal process are less studied than others (e.g., seed release processes in plants and termination of dispersal in terrestrial and aquatic animals). The generalized gravity model can serve as a unifying framework for such processes, because it captures the general conceptual and formal components of any dispersal process, no matter what the relevant biological timescale involved. We illustrate the use of the framework with examples of passive (a plant), active (an animal), and vectored (a fungus) dispersal, and point out promising applications, including studies of dispersal mechanisms, total dispersal kernels, and spatial population dynamics

A Unifying Gravity Framework for Dispersal

Most organisms disperse at some life-history stage, but different research traditions to study dispersal have evolved in botany, zoology, and epidemiology. In this paper, we synthesize concepts, principles, patterns, and processes in dispersal across organisms. We suggest a consistent conceptual framework for dispersal, which utilizes generalized gravity models. This framework will facilitate communication among research traditions, guide the development of dispersal models for theoretical and applied ecology, and enable common representation across taxonomic groups, encapsulating processes at the source and destination of movement, as well as during the intervening relocation process, while allowing each of these stages in the dispersal process to be addressed separately and in relevant detail. For different research traditions, certain parts of the dispersal process are less studied than others (e.g., seed release processes in plants and termination of dispersal in terrestrial and aquatic animals). The generalized gravity model can serve as a unifying framework for such processes, because it captures the general conceptual and formal components of any dispersal process, no matter what the relevant biological timescale involved. We illustrate the use of the framework with examples of passive (a plant), active (an animal), and vectored (a fungus) dispersal, and point out promising applications, including studies of dispersal mechanisms, total dispersal kernels, and spatial population dynamics

Correction: Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States

<p>Correction: Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States</p

Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States

<div><p>Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 80% of conventional yield. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (<i>Glycine max</i>) and potato (<i>Solanum tuberosum</i>), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (<i>Hordeum vulgare</i>), wheat (<i>Triticum aestevum</i>), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap.</p></div