value, sustaining these and other long-term measurements remains problematic and undervalued.
Network and observational systems require different funding strategies than shorter-term research projects. For the network to serve its purpose, a long-term commitment to network components is needed. The U.S. Long Term Ecological Research (LTER) and the National Oceanic and Atmospheric Administration (NOAA) trace gas monitoring programs are examples of a longer-term commitment to addressing science questions that are not posed as hypotheses that can be resolved in a field season or two. There have been many examples of long-time-series datasets from the LTER program that have helped guide research questions and set hypotheses, as well as evaluate regulatory and policy effectiveness. For example, in research conducted as part of the Bonanza Creek LTER project in Alaska, Grünzweig et al. (2004) showed that as agriculture expands at high latitudes, soil carbon losses are likely to be greater than those in other biomes. In another review, LTER data collected in the mid-1980s from Bonanza Creek were used to generalize about the long-term impacts upon nitrogen cycling of severe forest fires (Smithwick et al., 2005).
To be important and worthy of long-term support, networks should not need to be driven by hypotheses that can be tested over two-to-five-year funding cycles. It is clear that longer-term observations can directly help experimental research by providing the tools needed to address specific hypotheses. However, incentives and rewards for building long-term datasets are not always apparent, given the prevalence of two-to-five-year funding cycles. Protection of intellectual property rights to use data collected by individual observers, while still making them accessible to a larger community of users, will also remain a complex challenge for networks. And one of the key challenges for sustaining the AON beyond an initial effort like the International Polar year (IPY) is how to make the transition from pilot-type efforts like Keeling’s in the late 1950s to an institutionalized observing system that fulfills broad societal and scientific needs.
In addition to being founded upon a philosophy that values systematic, long-term, extensive measurements, the AON will also benefit if participants adhere to several other philosophical approaches. These include recognizing the value of measuring variables that are not currently changing in addition to variables that are changing dramatically; valuing open source, nonproprietary software and tools that allow data sharing across platforms and disciplines; valuing the ability to evolve with and embrace new technologies, opportunities, and demands; valuing the human dimension of the arctic system (see Box 5.1) and participation of local observers who make the AON more cost-effective and help make year-round observations; and valuing data management because of the efficiencies and overall cost-effectiveness that it can bring to the AON.
The following text is adapted from a brochure produced by HARC (Human Dimensions of the Arctic System) called “Designing the Human Dimensions into an Arctic Observing Network” (HARC, 2005).
Arctic environmental change is the set of biophysical transformations of land, ice, oceans and atmosphere, driven by an interwoven system of human activities and natural processes. Research on the human dimensions of arctic change addresses the coupled human-natural system and investigates how individuals and societal groups contribute to, are influenced by, and mitigate and respond to the changes that take place on a local, regional, and global level. Human dimensions science therefore encompasses may topics, approaches, methods, and disciplines.
Understanding how social systems interact with natural systems (both physical and biological) involves qualitative analyses and quantitative studies that rely on forms of hypothesis testing and analysis familiar to fields such as atmospheric science, terrestrial ecology, glaciology, or ocean biogeochemistry. When biophysical scientists study human-influenced phenomena such as ice roads, river flows, or fish catches, understanding human influences becomes critical. These are nontrivial challenges for biophysical-human dimensions research.
The human dimensions component of the AON could consist of a network of social scientists, citizens, and other observers who help make available and accessible arctic human dimensions data that are being collected in a common data structure with circumpolar scope. This part of the AON could also identify data gaps and fill them. Data might include the size, well-being, and livelihoods of arctic communities; demographic vital statistics, health and economic statistics; qualitative data such as historical accounts or life histories; and global economic and institutional trends (see also Table 2.1).
A key role for the human dimensions component of the observing network beyond collecting and organizing data could be to perform analyses needed to disseminate useful, useable, relevant, and timely data to researchers, policy makers, and the public through a single Web portal with multiple links.