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Measuring agricultural productivity is a multiscale spatiotemporal problem that requires multiscale solutions. In Vietnam, rice comprises a substantial portion of the cultivated area and is a major export crop that supplies much of the global food system. Understanding the when and where of rice productivity is vital to addressing changes to yields and food security, yet descriptive summarizations will vary depending on the spatial or temporal scale of analysis. This paper explores rice trends across Vietnam over a 19-year period, giving specific attention to modifiable spatiotemporal unit problems by evaluating productivity across multiple time periods and administrative levels. A generalizable procedure and tools are offered for visualizing multiscale time-series remote sensing data in matrix and map form, not only to elucidate the effects of modifiable spatiotemporal unit problems, but also to demonstrate how these problems serve as a useful research framework. Remote sensing indices (e.g., LAI and EVI) were evaluated against national and provincial estimates across Vietnam during multiple crop production periods using the Pearson Correlation Coefficient (PCC) to establish a relationship. To overcome challenges posed by long-term observations masking emerging phenomena, time-series matrices and multi-spatial and multi-temporal maps were produced to show when, where, and how rice productivity across Vietnam is changing. Results showed that LAI and EVI are favorable indices for measuring rice agriculture in Vietnam. At the province scale, LAI compared to nationally reported production estimates reached a Pearson's r of 0.960; 0.974 for EVI during the spring crop production period. For questions such as, "What portion of Vietnam exhibits a negative linear trend in rice production?", the answer depends on how space and time are organized. At the province scale, 25.4% of Vietnam can be observed as exhibiting a negative linear trend; however, when viewed at the district scale, this metric rises to 45.7%. This research contributes to the discussion surrounding ontological problems of how agricultural productivity is measured and conveyed. To better confront how agriculture is assessed, adopting a multiscale framework can provide a more holistic view than the conventional single spatial or temporal selection. [ABSTRACT FROM AUTHOR]

In recent decades, changes in precipitation, temperature, and air circulation patterns have led to increases in the occurrences of extreme weather events. These events can have devastating effects on communities causing destruction to property and croplands, as well as negative impacts on public health. As changes in the climate are projected to continue throughout the remainder of the twenty-first century, the ability for a community to plan for extreme weather events is essential to its survival. In this paper, we introduce a new index for examining the potential impacts of climate extremes on community resilience throughout the conterminous United States at the county level. We use an established disaster resilience index (baseline resilience indicators for communities) together with a revised version of the U.S. climate extremes index to create a combined measure of climate resilience-the climate extremes resilience index (CERI). To demonstrate the index, we test it on the 2021 Pacific Northwest heat wave, a 1000-yr weather event made 150 times as likely by climate change. To promote the use of the index, we also introduce a Google Earth Engine web app to calculate and map the CERI for the CONUS. By developing a web application for calculating the CERI, we expand the use of climate-resilience indices beyond theoretical applications. We anticipate that this tool and the CERI could be useful for policy makers to plan for climate-related disasters, as well as help the public with understanding and visualizing the impacts of extreme climatic events. [ABSTRACT FROM AUTHOR]

Heavy investments in hydroelectric development are occurring throughout the Amazon Basin, which holds 42.2 percent of Brazil's hydroelectric potential. The Belo Monte dam is the most recent and largest project in this region. The prevalence of septic systems in the Amazon, coupled with the widespread use of water wells and rising water table from filling the reservoir, create sanitation and health concerns for upstream communities. Using spatial analytical data and terrain analyses, we identify high-risk locations within the most densely populated neighborhoods in Altamira, Belo Monte's host city. The purpose of this research is to develop a heuristic for identifying areas susceptible to groundwater and well contamination in relation to existing and proposed hydroelectric projects. Altamira's city center persists as a high-risk location for contamination of wells because of its population density and relatively low elevation compared to other parts of the city. The methods, tools, and analyses presented in this article provide a framework that can be used to identify vulnerability to groundwater and drinking well contamination. The results presented here can guide implementation of public health and sanitation efforts in areas affected by large hydroelectric projects to avoid future water quality crises. Key Words: Belo Monte, groundwater contamination, hydroelectric infrastructure, risk assessment, spatial and terrain analyses. [ABSTRACT FROM AUTHOR]

SUMMARY: Perennial grain crops have been proposed as a transformative approach to agriculture. Replacing annual staple crops with perennialized growth types of the same crops could provide environmental services, improve labour efficiency and weather resilience, reduce seed costs and produce livestock fodder or fuelwood production. Yet, the technologies and science for agricultural development in Africa have focused almost exclusively on annuals. In this paper, we review the literature to explore what has been potentially overlooked, including missed opportunities as well as the disadvantages associated with perennial grains. The case studies of pigeon pea and sorghum are considered, as an analogue for perennial grain crops in Africa. We find that a substantial number of farmers persist in 'perennializing' pigeon pea systems through ratoon management, and that sorghum ratoons are widely practiced in some regions. In contrast, many crop scientists are not interested in perennial traits or ratoon management, citing the potential of perennials to harbour disease, and modest yield potential. Indeed, an overriding prioritization of high grain yield response to fertilizer, and not including accessory products such as fodder or soil fertility, has led to multipurpose, perennial life forms being overlooked. Agronomists are encouraged to consider a wide range of indicators of performance for a sustainable approach to agriculture, one that includes management for diversity in crop growth habits. [ABSTRACT FROM AUTHOR]

Successful scaling of agricultural development strategies is fundamental to increased production and yields, yet targeting efforts frequently fail to fully consider the underlying biophysical drivers of agricultural marginality, particularly at fine spatial resolutions. We present a heuristic for intelligent targeting, utilizing remotely sensed information to identify the intersection between marginal conditions for performance of a staple crop and the optimal niche for technologies that improve crop performance. Here, we explore the geographic potential of maize diversification with pigeonpea, a crop with soil productivity enhancing properties. Overall, 79 percent of agricultural land in Malawi exhibits climate conditions optimal for pigeonpea cultivation and, in total, approximately 51 percent of Malawian maize-based farming is expected to receive some benefit from pigeonpea integration, with 9 percent receiving predictable and substantial benefits. These findings illustrate the geographic scaling potential of pigeonpea in Malawi and provide direction for informed pigeonpea deployment and market development across the country. [ABSTRACT FROM AUTHOR]