Fieldwork Ready. Sara E. Vero

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are a number of groups and consortiums comprising discrete monitoring projects who collaborate across sites or adhere to agreed standards, measurements, and protocols. These programs might focus on one particular field of research or may take an integrative approach incorporating many distinct fields. As an example, the Long‐Term Ecological Research (LTER) Network includes 26 independent research sites funded by the U.S. National Science Foundation (NSF) since 1980. These sites represent a breadth of ecosystems including tallgrass prairie (Konza, Kansas), the Antarctic (Palmer Station, Anvers Island), and marine (California Current). The Long‐Term Agroecosystem Research (LTAR) network created by the USDA Agricultural Research Service (USDA‐ARS) similarly co‐ordinates 18 independent sites across the contiguous United States. The goal of LTAR is to investigate and develop strategies for the sustainability of agricultural production under the three pillars of productivity, environment, and rural prosperity.

      These distinct sites follow a consistent approach to data collection across the entire network, although specific measured variables are selected as appropriate to each site (for example, depth of permafrost is measured at the Artic site but would be irrelevant for the urban biome in Arizona). These measurements allow conceptual understanding of these ecosystems, development of ecological, hydrologic, and biogeochemical models, and collaborative investigations across contrasting environments. Ambitious research programs such as these support long‐term monitoring over multiple decades from which projections into the future can be modeled and act as a benchmark against which comparable sites can be evaluated. Furthermore, they provide well‐characterized, representative, and secure facilities in which controlled and replicated experiments can be executed. An example of this is the watershed‐scale tallgrass prairie experiment that has been conducted at the Konza Prairie LTER site in Kansas. In that experiment, 60 hydrologic watersheds have been subject to treatments including bison and cattle grazing, and five burn frequencies (annual, 2‐yr, 4‐yr, 20‐yr, and >20‐yr intervals, in addition to no‐burning) since the establishment of the facility in 1972 (it later became one of the six founding LTER sites in 1980). These treatments have provided insights into the implications of management for the remaining US prairie grasslands and species.

      Sampling Patterns

Photo depicts a few researchers are soil sampling in Alaska. There are a variety of sampling patterns which may be used and you should consider which approach is most appropriate before embarking on a sampling campaign.

      Source: Jaclyn Fiola.

Photo depicts coloured flags that are used here to mark where the researcher is identifying plant species composition using the Daubenmire method.

      Source: Jesse Nippert.

Photo depicts a GPS device that can be used to accurately identify sampling locations.

      Source: Sara Vero.

      Transect sampling is often used in ecological studies, in which measurements are made at regular intervals along a line through the sampling area (Fig. 2.15b). However, applications do exist in other disciplines such as boring of groundwater wells along hillslopes, or excavation of soil pits along a “catena” (a sequence of related but distinct soil profiles along a slope).

      Grid patterns (Fig. 2.15c) allow an even distribution of samples across an area and are often used in precision agriculture to identify variations in soil moisture, nutrients, crop yield, etc. at subfield scale. Detailed discussion of the methods and applications of precision agriculture approaches are available in Shannon et al. (2018).

      A completely randomized approach may be employed (Fig. 2.15d) as in the case in some ecological sampling regimes. This involves measurements or samples being obtained at randomized locations within the study area. Achieving true random selection can be difficult due to unintentional human influence. Dividing your study area into a grid and using a random generator to select squares in which to sample is one simple approach.

Schematic illustrations of field sampling patterns. (a) W-pattern, typical for soil survey, (b) transect, typical for herbage composition, (c) grid, common for high resolution mapping (e.g., to support precision agriculture, and (d) completely randomized.

      Source: Sara Vero.

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