The ecological futures of drylands pivot on two key axes of ongoing change: a drier mean environment and greater interannual variability. Past ecological work has largely emphasized mean trends or singular extreme events, yet theory predicts that temporal environmental variability can have large impacts at multiple levels of biological organization. If organisms are commonly sensitive to the combined effects of a changing mean and increasing variability, then current approaches will fail to predict the future. Long-term support is critical to scientific progress at this frontier because for interannual variance, one year is only one sample. SEV LTER research advanced the frontiers of ecology by developing and testing theory on the ecological consequences of shifting environmental mean and variance. A mechanistic, process-based approach used data-model integration to improve the accuracy of ecological forecasts, especially for future no-analog environmental conditions. SEV products inform ecology at multiple levels of biological organization from the physiology of individuals, evolution and demographics of populations, dynamic processes of ecosystems, and spatial patterns of landscapes.

Intellectual Merit

Conceptual significance and novelty. Theory predicts that temporal variance in the environment can have powerful ecological and evolutionary consequences. These effects arise from nonlinearities in biological responses to the environment and from the stochastic nature of environmental conditions. Empirical understanding of the ecology of interannual environmental variability has lagged behind theory because this variability occurs over timescales that greatly exceed most studies. Confronting variance has transformed some disciplines; however, advances in ecological theory on the impacts of temporal environmental variability have developed largely independently across subfields. SEV research has integrated concepts across subdisciplines and levels of biological organization to build a cohesive program to study temporal environmental variability. SEV research discovered that effective forecasts require attention to two components of non-stationary environments: the mean and the variance. Concurrent changes in environmental mean and variance interactively alter biological responses in ways that could not previously be predicted. During this funding cycle, SEV produced 291 peer-reviewed articles, book chapters, and theses cited >6,000 times and published or updated >100 public data packages that adhere to FAIR principles for information management.

Broader Impacts

SEV recruited and trained a diverse STEM workforce with activities at all levels of learning. Activities included interdisciplinary graduate & professional training with competitive summer research fellowships, undergraduate research in partnership with the REU Site program, collaborative teaching & mentoring with Southwestern Indian Polytechnic Institute, Course-based Undergraduate Research Experiences (CURE), a flagship Schoolyard LTER program -- the Bosque Ecosystem Monitoring Program, and interactions with land managers at local, state, and national levels. During 2018-24, SEV collectively mentored >70 undergraduates and 90 graduate students across 20 institutions, and supported 9 staff per year. Partnership with the Bosque Ecosystem Monitoring Program expanded support to 10 additional staff. The SEV worked closely with the University of New Mexico Museum of Southwestern Biology staff to archive specimens and samples. Additional collaborators included 106 research scientists at 50 academic, research, NGO, and government institutions

National and global importance. Dryland ecosystems rank among the most variable places on Earth. They cover >40% of land surface with increasing rates of expansion, support ~35% of the global human population, and store 33-59% of global soil carbon. The diversity of dryland ecosystems and ecotones represented among SEV sites advanced comparative study of the importance of temporal environmental variability at dryland ecotones and supported cross-site collaboration and synthesis.

Last Modified: 07/24/2025
Modified by: Jennifer A Rudgers