Long-term Monitoring Data: Finding Some Light at the End of the Tunnel

Kristin E. Haskins and Sheila Murray (The Arboretum at Flagstaff), and Andrea Hazelton (Desert Butte Botany)

Acquisition of a long-term dataset is truly rare and can represent decades of hard work and thousands of dollars or more in exhausted resources. The standard model of monitoring year after year is unsustainable for most organizations and begs the question, when should it stop? The Arboretum at Flagstaff has a demography data set for Arizona cliffrose (Purshia subintegra) that has been on-going since 1996. Different ‘levels’ of monitoring have occurred over the years depending on available resources. With some recent funds, we set out to address the following questions with long-term data: 1) What is the long-term viability of the population? 2) Which life stages are most important to capture in the monitoring? And 3) can we monitor less often and still capture important life history events? Challenges included determining starting population sizes for population matrix models and gaps in data. Using the 22 years of monitoring data combined with data from published papers, anecdotes, and historic weather data, we produced population growth rates for P. subintegra and identified key life stages correlated with precipitation events, thus enabling implementation of a modified monitoring protocol, which will conserve valuable resources.