Coproduction of knowledge is believed to be an effective way to produce usable climate science knowledge through a process of collaboration between scientists and decision makers. While the general principles of coproduction—establishing long-term relationships between scientists and stakeholders, ensuring two-way communication between both groups, and keeping the focus on the production of usable science—are well understood, the mechanisms for achieving those goals have been discussed less. It is proposed here that a more deliberate approach to building the relationships and communication channels between scientists and stakeholders will yield better outcomes. The authors present five approaches to collaborative research that can be used to structure a coproduction process that each suit different types of research or management questions, decision-making contexts, and resources and skills available to contribute to the process of engagement. By using established collaborative research approaches scientists can be more effective in learning from stakeholders, can be more confident when engaging with stakeholders because there are guideposts to follow, and can assess both the process and outcomes of collaborative projects, which will help the whole community of stakeholder-engaged climate-scientists learn about coproduction of knowledge.

Information and services delivered through mobile phones, ‘m-services', have transformative potential to provide rural African farmers with important agro-meteorological information. However, a greater understanding is needed regarding the types of m-services available to farmers, how farmers access that information, and possible factors affecting m-service use. With a study of smallholder farming communities in central Kenya, we examine factors affecting the likelihood of Kenyan farmers’ adoption of m-services specifically related to agriculture and livestock information, buying and selling products, and alerts about agricultural or livestock activities. According to a survey of 577 farming households, 98% of respondents own a mobile phone. Approximately 25% use it to access information about agriculture and livestock, 23% access information about buying and selling products, and 18% receive alerts. Personal smartphone ownership increases the likelihood of m-services use (p < .001), as does membership in farmer organizations (p < .001). We find that age and income are not significantly related to m-service use, and we discuss this result in terms of intersections between smartphone ownership, gender, and education. Consistent with prior qualitative research, our quantitative results further support the need for m-services providers to design for basic or feature phone users for improved dissemination of agro-meteorological information.

In this perspective, we draw on recent scientific research on the coffee leaf rust (CLR) epidemic that severely impacted several countries across Latin America and the Caribbean over the last decade, to explore how the socioeconomic impacts from COVID-19 could lead to the reemergence of another rust epidemic. We describe how past CLR outbreaks have been linked to reduced crop care and investment in coffee farms, as evidenced in the years following the 2008 global financial crisis. We discuss relationships between CLR incidence, farmer-scale agricultural practices, and economic signals transferred through global and local effects. We contextualize how current COVID-19 impacts on labor, unemployment, stay-at-home orders, and international border policies could affect farmer investments in coffee plants and in turn create conditions favorable for future shocks. We conclude by arguing that COVID-19’s socioeconomic disruptions are likely to drive the coffee industry into another severe production crisis. While this argument illustrates the vulnerabilities that come from a globalized coffee system, it also highlights the necessity of ensuring the well-being of all. By increasing investments in coffee institutions and paying smallholders more, we can create a fairer and healthier system that is more resilient to future social-ecological shocks.

During the Last Glacial Maximum (LGM), a 5000 km² ice cap covered the San Juan Mountains of southwest Colorado. The largest valley glacier draining this ice cap occupied the Animas Valley and flowed 91 km to the south. To characterize the post-LGM demise of the Animas Valley glacier, we employ cosmogenic ¹⁰Be to date the LGM terrace outside the terminal moraines and a suite of seven glacially polished bedrock samples. The ¹⁰Be depth profile within the terrace sediments suggests abandonment at 19.4 ± 1.5 ka. As deglaciation began, the ponding of Glacial Lake Durango behind the terminal moraines shut off fluvial sediment supply and caused terrace abandonment. The age of the terrace therefore records the initiation of LGM retreat. Negligible ¹⁰Be inheritance in the terrace profile suggests that glacial erosion of the bedrock valley floor from which sediments were derived erased all cosmogenic inventory. Glacial polish exposure ages monotonically decrease up-valley from 17.1 to 12.3 ka, with the single exception of a sample collected from a quartzite rib, yielding an average retreat rate of 15.4 m/yr. This trend and the lack of inherited cosmogenic nuclides in the terrace sediments imply that polish ages accurately record the glacial retreat history. Retreat of the Animas lobe began at a time of regional drying recorded in sediments and shoreline elevations of large lakes. Deglaciation lasted for ∼7.2 k.y., and was complete by 12.3 ± 1.0 ka. The retreat history followed the pattern of increasing insolation and was perhaps fastest during a time of regional drying.