How, what, and where you perform inventories, monitoring, and assessments has a tremendous impact on how well the data you collect can support the kinds of decisions you need to make. Needless to say it’s very much worth the time and effort to plan and design a good monitoring program. There are no “one-size-fits-all” approaches to this and very few silver bullets. There are, however, some generally applicable, well-developed steps and useful tools that you can use to design a robust monitoring program.
Much of the information here is covered in more depth in volume II of the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems.
Monitoring Process Model
The process of designing and implementing a monitoring program can be broken down into a series of steps. These steps are intentionally quite broad, and while they are listed in the order they are normally completed, there is no “single” way to design a monitoring program.
Because rangelands are among the most diverse ecosystems in the world, it is impossible to design a monitoring system that perfectly reflects changes in all landscape units. However, the accuracy and precision of any monitoring system can be improved by carefully dividing the area into relatively uniform units for monitoring. These monitoring units are called strata.
Successful monitoring programs are focused on measuring indicators that are sensitive to changes in key ecosystem attributes. To effectively identify and interpret changes in indicator over time we need to understand how management and other disturbances, such as drought, affect the land. Conceptual ecosystem models are helpful for organizing this knowledge of ecosystems so that it can be applied to selecting and interpreting indicators. While not statistical or predictive, conceptual models contain enough detail to document the known (or hypothesized) impacts of management and other disturbances on plant communities and soils. Conceptual models can also highlight knowledge gaps in ecosystem structure or function.
Where you choose to collect inventory, monitoring, or assessment data is just as important as how you collect your data. Statistically-based approaches to selecting locations for monitoring protect against bias and ensure that you can draw conclusions about your entire monitoring area from the sample data you collect. Statistically-valid sample designs are also necessary if you want to combine data from different monitoring efforts.