When researchers study an ecosystem, the concept of resource allocation is often a major theme. The term frequently refers to how organisms, or even whole colonies, use their finite sources of energy in the most beneficial way to enhance survival. But when researchers begin to examine how human beings can conserve or restore ecosystems, the resources that come into play take on new levels of meaning.
In “Renewed Hope for Coastal Marshes in Louisiana,” Paige Byerly and her colleagues report about the many saltmarsh conservation and restoration efforts along the coast of this state, in areas that have endured not only numerous massive storms, but also the record-setting Deepwater Horizon oil spill in 2010. Here, the meaning of resources invested expands to include such factors as money, equipment, and time, as some of the reparation funds from the spill are being used to rebuild rapidly eroding areas in the region. However, many of the species that inhabit these areas received little monitoring before the oil spill, a fact that has complicated efforts to manage and conserve flora and fauna with these environmental changes.
This issue’s Ethics column, from Kaitlin Stack Whitney and her colleagues, shows how human factors further influence what the word resources can mean. In “Open Science Isn’t Always Open to All Scientists,” these authors point out that the movement toward “open science” involves convoluted and ambiguous definitions of what it means to conduct and publish science openly. They also illuminate certain barriers that may not be visible to scientists at all levels of academia. Although more conventional resources, such as funding, can help remove some of these barriers, intangible forms of human capital, such as prestige and career prospects, must also be considered.
Data is a resource that is fundamental to the sciences. Without accurate, representative data, conclusions drawn from scientific research can be incomplete or possibly erroneous. In this issue’s Technologue column, Ayanna Howard and Jeremy Borenstein examine how a lack of robust data can affect the role of robotics in human interactions. In “Trust and Bias in Robotics,” they show that humans tend to trust robots to make accurate decisions—faith that may be unwarranted, particularly when many of the underlying artificial- intelligence systems that robots rely on (such as computer vision) may be trained on data sets that aren’t representative of the population. Similarly, in this issue’s First Person, Latifa Jackson, an assistant professor of pediatrics at Howard University, points out how a historic lack of genomic information about non-European populations could affect health outcomes for everyone.
A recent series of colloquiums from the National Academies of Sciences, Engineering, and Medicine, reported about in this issue’s Spotlight column, takes up the need for data about research communication itself, to ensure that individuals aren’t left on their own to determine the veracity of media claims. The ensuing report from these colloquiums advocates for resources to be allocated to developing a “systems approach” to science communication, so that scientific evidence reaches discussions of policy and may be incorporated into larger solutions.
At all levels of our ecosystem, how we allocate our varied resources determines how we fare as a planet, not just as a species. Here’s hoping that the invaluable resource of information is used widely to improve our vital choices.—Fenella Saunders (@FenellaSaunders)