Cross‐scale Perspectives: Integrating Long‐term and High‐frequency Data into Our Understanding of Communities and Ecosystems

Abstract

Ecologists are amassing extensive data sets that include both long-term records documenting trends and variability in natural systems on inter-annual to decadal time scales and sensor-based measurements on minute to subhourly scales for extended periods (Hampton et al. 2013 ). Together, these long-term and high-frequency data are contributing to our ecological understanding. Although there have been several previous ESA sessions that have explored the insights provided by either long-term data or highfrequency data, to our knowledge this organized oral session provided one of the fi rst opportunities to synthesize the lessons learned from leveraging both long-term data and high-frequency approaches.The session included speakers at a variety of career stages and institutions chosen specifi cally for their unique and complementary perspectives on high-frequency and long-term data collection from desert ecosystems, grasslands, forests, streams, lakes, and coral reefs. While the focus of the session was on the ecological insights gained by using high-frequency and/or long-term data, the speakers also discussed the data approaches used to collect, manage, and analyze time series, as well as the inherent challenges in harnessing "big data" for ecology.Scott Collins (University of New Mexico) kicked off the session by describing the use of sensor arrays to study responses to precipitation experiments in the United States and China (EDGE, edge. biology.colostate.edu). Collins emphasized the fallibility of sensors during long-term deployments, and how this unreliability resulted in data gaps that necessitated aggregating data to coarser temporal intervals than planned. Collins advised ecologists collecting sensor data to develop plans for dealing with data gaps a priori and to think carefully about what these data are telling us: e.g., soil CO 2 sensors give measurements of CO 2 concentrations, which then need to be interpreted carefully to get to the variables that we are actually interested in, e.g., soil respiration.Kim La Pierre (University of California, Berkeley) presented fi ndings from a long-term ecological research (LTER) synthesis of plant community responses to factorial experiments manipulating multiple components of global change (e.g., nutrient concentrations, water availability; corredata.weebly.com). Unlike aggregate ecosystem parameters, whose responses were not affected by the duration or number of global change factors simultaneously manipulated (Leuzinger et al. 2011 ) , community properties were much more sensitive and effects strengthened with time and number of global change treatments. Thus, a key take-home message was that long-term experiments are important to understanding the magnitude and interactions of global change effects, especially of ongoing "press" perturbations. As such, La Pierre recommended that ecologists conduct studies that manipulate multiple drivers simultaneously over periods longer than 3 years.

The Broken Window: An algorithm for quantifying and characterizing misleading trajectories in ecological processes

“…Ecological systems are inherently dynamic, and variations in the metrics humans collect about these systems can be driven by a variety of stochastic and deterministic processes, as well as by sampling error or other research-induced effects (Suding & Gross, 2006). Short-term dynamics observed in an ecological system are not always indicative of the long-term trajectory of that system (Carey & Cottingham, 2016), and furthermore, shorter observation periods can lead to spurious observations because of sampling error variance (Daskalova et al, 2021). In population processes, for example, density-dependent deterministic mechanisms, combined with environmental perturbations, can produce highly variable population numbers over various time scales (Turchin, 2003).…”