The Concentration-Discharge Research Network
The shape of the relationship between solute concentration (C) and flow (Q) in streams and rivers (C-Q relationships) can reveal important characteristics about a watershed and how it responds to disturbance and long-term change. C-Q science is advancing rapidly thanks to increasing use of high-frequency sensors and new quantitative tools. The C-Q Network is a group of early career catchment scientists working to synthesize the current state of C-Q science and provide new quantitative tools to push this science forward. This effort is a collaboration between the Webster Lab, the ECOSHEDS lab, the Shogren Lab, the Blaszczak Lab, the Speir Lab, the Rose Lab, Dustin Kincaid, Hannah Fazekas, and others.
Sustainable Water Resources Grand Challenge
Website | Media Coverage
Planning a sustainable water future is as much about ensuring that our water resource systems are resilient as it is about balancing supply and demand. The Webster Lab is integrating resilience theory, system science, and the analysis of big datasets to conduct a resilience assessment of New Mexico's water resources and provide a template for continued leadership in interdisciplinary research on water resources at the University of New Mexico. This work is supported by UNM's Sustainable Water Resources Grand Challenge Initiative in collaboration with the Sustainable Water Resources Grand Challenge leadership team.
Innovative Approaches for
Managing Water Scarcity in Agriculture
District- and community-scale agricultural water management often differs from what is described in regional management plans and legal doctrines. Water management at these finer scales often involves creative solutions, including collective regulation and reasonable sharing of water, and diverse motivations, including promoting community cohesion and ecosystem services. This research aims to document innovative but poorly documented collaborative strategies for managing water scarcity through interviews with New Mexican farmers, water managers, and community-scale experts, and to better understand the motivations and practical application of such strategies. This work is supported by an NSF-ADVANCE award and UNM's Center for Water and the Environment CREST center. Learn more and the project and team here and here.
Monitoring Ecosystem Resilience in Stream Chemistry
Stream chemistry data is rich with information about connected upstream terrestrial and aquatic ecosystems. We are exploring long-term stream chemistry datasets for signals of changing ecosystem resilience using tools from catchment biogeochemistry, aquatic ecosystem ecology, and quantitative resilience theory. The resulting generalized approach aims to allow monitoring of ecosystem resilience on whole-catchment scales. This work is in collaboration with the Harms Lab.
Stream Chemistry Indicators of Changing Permafrost and Ecological Dynamics in Subarctic Catchments
Perennially frozen ground (permafrost) covers much of the land surface in arctic and subarctic regions and stores twice as much carbon as is currently in the atmosphere. Permafrost is unstable and is projected to thaw under rising air temperatures in many regions, and as it thaws, the release of carbon may accelerate global climate change. Permafrost thaw also damages buildings and roads and is expected to fundamentally reorganize arctic and subarctic ecosystems with consequences for wildlife and subsistence resources. These impacts make predicting the changing distribution of permafrost a critical research priority, but this remains challenging. We are using stream chemistry to understand and better predict permafrost thaw by tracking permafrost-influenced ecosystem dynamics in watersheds' biogeochemical signals. This work involves deconvoluting complex high-frequency and spatially-extensive stream chemistry data to distill signals of permafrost thaw from other processes. This work was part of my postdoctoral research in the Harms Lab.
1. Webster AJ, Douglas TA, Regier P, Scheuerell MD, Harms TK. 2021. Multi-Scale Temporal Patterns in Stream Biogeochemistry Indicate Linked Permafrost and Ecological Dynamics of Boreal Catchments. Ecosystems. https://doi.org/10.1007/s10021-021-00709-6 (PDF)
The Transformation Network was formed in 2021 with an award from the NSF Sustainable Regional Systems Program. We aim to build resilient communities and ecosystems throughout the Intermountain Western United States through research and collaboration among eight universities and over 50 partner organizations representing Tribal partners, governmental and non-governmental organizations, public utilities, conservation districts, irrigation districts, and municipalities. The Webster Lab is directing our research program in the Upper Rio Grande Watershed, which is providing a case study for understanding resilience and transformative capacity of headwater-depended social-ecological systems.
Collaborative for Research in Aridland Stream Systems
The Collaborative for Research in Aridland Stream Systems (CRASS) is a working group of aridland stream ecologists, hydrologists, climate scientists, and statisticians using long-term and broad-scale aridland stream data to evaluate stream ecosystem models with an emphasis on aridland stream responses to climate change. The Webster Lab is co-leading a data synthesis designed to understand the impact of wildfires on aridland water quality across hydroclimate gradients. This initiative is in collaboration with the Grimm Lab, the Harms Lab, and others.
Water Availability-Driven Tipping Points
in Aridland Ecosystem Transitions
Aridland ecosystems, covering 40% of terrestrial surface of the Earth, are particularly sensitive to changes in water availability. As climate change shifts aridity gradients across the US and increases the frequency and severity of drought, some aridland ecosystems may approach tipping points and transition to other types, while others may be resilient. We are applying quantitative resilience analyses to a) a 15 year record of continuously measured carbon, water and energy exchange across nine aridland ecosystem types and b) full state coverage of remotely sensed vegetation structure to pinpoint the most vulnerable aridland ecosystems in New Mexico to changes in climate and interacting disturbances. This research is in collaboration with the Litvak Lab.
Nitrate and Suspended Sediment Capture
in Agricultural Ditch Networks
As human populations grow and demand for food and water continue to rise, we are challenged with finding new ways to balance food production with maintaining water quality. One strategy to meet this challenge is to promote the ecological function of riparian and stream networks embedded in agricultural landscapes. This work characterized the ability of interconnected networks of remnant streams and artificial ditches to capture nitrate and suspended sediments in agricultural runoff across spatial scales of land and water management. I identified characteristics of management regimes at the scale of farm field edges to whole irrigation districts that promote water quality improvement and can thus be leveraged to improve water quality conditions in this region. This work was part of my dissertation research in the CLUE lab.
Impacts on Riparian Metacommunity Dynamics in
Urban and Agricultural Landscapes
Riparian zones are rich in resources and biodiversity relative to adjacent uplands, particularly in arid and semi-arid settings where water availability limits plant growth. The riparian vegetation communities of these unique ecosystems influence watershed-scale nutrient and sediment dynamics, habitat for fish and other wildlife, food web energetics, and downstream water quality. However, riparian vegetation has dramatically decreased in many contemporary landscapes and what remains may be impacted by intensive land uses such as industrial agriculture and urban development. These impacts occur and interact on local, stream network-wide, and regional scales, making them difficult to parse and manage. This work is identifying the multi-scale mechanisms that drive the cover and composition of riparian vegetation across an intensive agricultural and urban landscape using metacommunity theory and analysis. This work is in collaboration with the CLUE lab.
Cover photo: The Rio Grande in Albuquerque; Photo credit: Zuruda