Identifying Best Agricultural Management Practices for Maintaining Soil Health and Sustainability Under Changing Climate Conditions

Funding Amount and Duration:

$12,000 from September 15, 2016 - September 14, 2017

Funding Source:

US Geological Survey

Principal Investigators:

John Zak, Texas Tech University (TTU)

Cooperators & Partners:

Veronica Acosta Martinez (USGS, USDA)

Bobbie McMichael (TTU)

About:

The role of soil temperature in agricultural health is largely understudied, but recent research suggests that it can affect soil health in important ways. Researchers at Texas Tech University found that lower daily temperature ranges of soil in the Southern High Plains were associated with higher levels of soil microbes (which help make critical nutrients available for plants) and decreased nitrogen availability. These results suggest that climate variability may have implications for soil health and microbial content. In the South Central U.S., a more developed understanding of how management practices, climate variability, and soil health interact is essential for sound agricultural decision-making.

This project will implement demonstration fields in which various sustainable management practices can be tested and their impacts on soil temperature and health can be monitored. The demonstration fields will focus on cotton production and will test management practices related to water use efficiency, carbon storage, and soil health. In addition to demonstrating the effects of various management practices, these plots will help to determine how much variability cotton production systems can tolerate before ecosystems and the services they provide are negatively affected.

This demonstration system is in high demand amongst regional stakeholders and will be implemented with the support of the South‐Central USDA Climate Hub, NRCS scientists, and Cotton Inc. It will contribute substantially to our collective understanding of the interactions between climate variability, soil health, and agricultural productivity in the Southern High Plains while equipping stakeholders with the knowledge they need to make appropriate management decisions for optimal agroecosystem health.

Characterizing Uncertainties in Climate Projections to Support Regional Decision-Making

Funding Amount and Duration:

$94,379 from April 1, 2016 - March 31, 2017

Funding Source:

US Geological Survey

Principal Investigators:

Adrienne Wootten, University of Oklahoma

About:

Global Climate Models (GCMs) use our understanding of atmospheric physics and other earth processes to simulate potential future changes in climate on a global scale. However, these large scale models are not fit for predicting smaller scale, local changes. Downscaling methods can be applied to the outputs of GCMs to give guidance appropriate for a more regional level. No standard approach to downscaling currently exists, however, and the process often results in climate projections that suggest a wide array of possible futures. It is critical that decision-makers looking to incorporate climate information understand the uncertainties associated with different downscaling approaches and can evaluate downscaled data to determine which datasets are appropriate for addressing their questions.

The goal of this project is to provide decision-makers with this information by evaluating the uncertainties associated with different downscaled datasets. Materials will then be developed to communicate these uncertainties to managers and explore how they can be incorporated into risk decision-making. The results will enable managers across the country to better understand possible climate futures in their jurisdictions, allowing them to make more informed planning decisions in the face of uncertainty.

Developing Tools for Improved Water Supply Forecasting in the Rio Grande Headwaters

Funding Amount and Duration:

$50,000 from April 1, 2016 - March 31, 2017

Funding Source:

US Geological Survey

Principal Investigators:

David Clow, USGS Colorado Water Science Center

Cooperators & Partners:

Colin Penn & Graham Sexston, USGS Colorado Water Science Center

About:

The Rio Grande River is a critical source of freshwater for 13 million people in Colorado, Texas, New Mexico, and Mexico. More than half of the Rio Grande’s streamflow originates as snowmelt in Colorado’s mountains, meaning that changes in the amount of snowmelt can impact the water supply for communities along the entire river. Snowmelt runoff is therefore an important component of water supply outlooks for the region, which are used by a variety of stakeholders to anticipate water availability in the springtime.

It is critical that these water supply outlooks be as accurate as possible. Errors can cost states millions of dollars due to mis-allocation of water and lost agricultural productivity. There is a perception that runoff forecast accuracy has declined over the last several decades in Colorado and New Mexico, making water supply outlooks less reliable. Declines in accuracy could be related to changes in climate and land cover; however, potential sources of error have not yet been examined in the upper Rio Grande basin.
This study aims to improve runoff forecast models for the upper Rio Grande. Researchers will identify potential sources of error in existing models, improve the representation of snowpack in models of the watershed, develop a new hydrologic model for the basin, and test this model’s ability to forecast runoff. The end product of this study will be a tool for making improved runoff forecasts for the upper Rio Grande basin. The tool will be transferable to other snowmelt-dominated basins in the region that have similar characteristics. These improved runoff forecasts, in turn, can be used to develop more accurate water supply outlooks in the region, empowering stakeholders in the basin to plan their water use more effectively.

Enhancing the Capacity of Coastal Wetlands to Adapt to Sea-Level Rise and Coastal Development

Funding Amount and Duration:

$35,000 from April 1, 2016 - March 31, 2017

Funding Source:

US Geological Survey

Principal Investigators:

Michael Osland, USGS Wetland and Aquatic Research Center

Cooperators & Partners:

Nicholas Enwright & Sinead Borchert, USGS Wetland and Aquatic Research Center

About:

Coastal wetlands provide a suite of valuable benefits to people and wildlife, including important habitat, improved water quality, reduced flooding impacts, and protected coastlines. However, in the 21st century accelerated sea-level rise and coastal development are expected to greatly alter coastal landscapes across the globe. The future of coastal wetlands is uncertain, challenging coastal environmental managers to develop conservation strategies that will increase the resilience of these valuable ecosystems to change and preserve the benefits they provide.

One strategy for preparing for the effects of sea-level rise is to ensure that there is space available for coastal wetlands to adapt by migration. In a recent study, researchers identified areas where coastal wetlands may move inland along the northern Gulf of Mexico coast, one of the most wetland-rich and sea-level rise sensitive regions of the world. Building on these findings, this project will produce customized landscape conservation-design products focused on identifying landward migration routes for coastal wetlands. The resulting products will provide environmental managers with information to make decisions to enhance the capacity of coastal wetlands to adapt to sea-level rise and coastal development, protecting these ecosystems and the critical economic and ecological benefits that they provide.

Identifying Conservation Objectives for the Gulf Coast Habitats of the Black Skimmer and Gull-billed Tern

Funding Amount and Duration:

$ from April 1, 2016 - March 31, 2017

Funding Source:

US Geological Survey

Jointly funded by the South Central Climate Science Center and the Southeast Climate Science Center

Principal Investigators:

James Cronin, USGS Wetland and Aquatic Research Center

About:

Many shorebirds and nearshore waterbirds are of conservation concern across the Gulf of Mexico due to stressors such as human disturbance, predation, and habitat loss and degradation. Conservation and protection of these birds is important for the functioning of healthy ecosystems and for maintaining biodiversity in North America. Consequently, resource managers along the gulf need decision-aiding tools that can efficiently help to answer important conservation questions for different species (e.g. which areas and how much area should be targeted by management actions to meet a particular species’ needs).

To address this need, project researchers are developing statistical models that will help identify habitat conservation objectives and actions for bird species taking into account different gulf coast conservation scenarios that might occur in response to sea-level rise. The project will focus specifically on the Black Skimmer (Rynchops niger) and Gull-billed Tern (Gelochelidon nilotica), two species identified as representative of sustainable gulf habitats and designated as U.S. Fish and Wildlife Service Species of Conservation Concern and Gulf Coast Joint Venture Priority Species. These two birds are also representative of a variety of other beach and barrier-island nesting birds whose nesting habitats are threatened by sea-level rise (e.g., Least Tern, Snowy and Wilson’s Plover). The statistical models will link each bird’s population abundance to habitat characteristics that could be influenced by different management actions and will use this information to identify conservation objectives under different conservation scenarios.

Improving Predictions of Water Supply in the Rio Grande under Changing Climate Conditions

Funding Amount and Duration:

$92,915 from April 1, 2016 - March 31, 2017

Funding Source:

US Geological Survey

Principal Investigators:

David Gutzler, University of New Mexico

About:

On its southbound course from Colorado to the Gulf of Mexico, the Rio Grande provides water resources for more than 13 million people. The quantity of water flowing into the northern section of the river depends on how much snowpack from the Rocky Mountains melts into runoff and on seasonal precipitation rates. Models describing the relationship between winter snowpack quantity and springtime snowmelt runoff quantities for the basin are combined with models describing long-term natural variation in precipitation to create water supply outlooks. The outlooks developed by the U.S. Natural Resources Conservation Service are currently used by stakeholders to make critical water allocation decisions in the basin. Improvements to water supply outlooks could be worth millions of dollars associated with better water allocation strategies.

In order to ensure that these outlooks are as accurate as possible for water management planning, there is a need to better understand how snowpack and snowmelt runoff are related to each other and how both may be influenced by large climatic variation such as El Niño and global climate change. To address this need, this project will combine historical data and climate model projections to develop enhanced prediction models relating winter snowpack to subsequent snowmelt runoff in the upper Rio Grande.
The results of this research will identify changes to streamflow predictability over the past several decades (a period of rapid observed warming), and assess future predictability. This work will also help to inform the development of more reliable water supply outlooks essential for planning purposes in the Rio Grande Basin, such as reservoir management and irrigated agriculture.