Geology topics

John T. Delaney

Publications and source records attributed to John T. Delaney.

10 recordsLinked to original sources

USGS2025

Evaluating hydrologic data products for scientific and management applications related to potential future streamflow conditions in the Upper Mississippi and Illinois Rivers

The hydrology of the Upper Mississippi and Illinois Rivers is a fundamental driver of ecosystem patterns and processes across a large portion of the United States. Quantitative hydrologic data for the main stems of these rivers underlie numerous scientific investigations, statistical models, and decision-making processes for local, State, and Federal agencies involved in the Upper Mississippi River Restoration program. Although historical hydrologic data exist, data representing potential future conditions of the Upper Mississippi and Illinois Rivers lack the resolution necessary to anticipate biotic and abiotic responses to altered hydrology and to determine resilient management actions. A source of future hydrologic scenarios is the readily available LOCA–VIC–mizuRoute hydrologic data products (named for the chain of models the data are produced from—localized constructed analogs, Variable Infiltration Capacity macroscale hydrological model, and the mizuRoute hydrologic routing model—that we shorten further to LVM in this report) that include simulated discharges for historic and future timeframes. The objective of this study is to assess the reliability of the hydrologic data products for their use in Upper Mississippi River Restoration program applications. Key study questions are (1) do the hydrologic data products reproduce characteristics of hydrology necessary to support ecological modeling and restoration decision-making applications within the Upper Mississippi River Restoration program? and (2) are there geographic differences in the reliability of the hydrologic data products? Seven characteristics of river hydrology were selected related to flow magnitude, seasonality, and regime for evaluation. The seven characteristics were calculated using observed and historical simulated hydrologic data at 19 U.S. Geological Survey streamgages throughout the basins of the Upper Mississippi and Illinois Rivers; two streamgages are located on the main stem of the Mississippi River and two streamgages are located on the main stem of the Illinois River. Statistical comparisons between observed and historical simulated characteristics indicated that the hydrologic data products did not reliably represent historical hydrologic conditions in the basin or main stem. The hydrologic data products we evaluated could not reliably capture the overall hydrologic regime or flow magnitudes; the latter is evidenced by substantial underestimates of discharge at most streamgages. Seasonal hydrologic characteristics were captured more reliably than flow magnitude, but overall correspondence was low for most streamgages. A weak latitudinal pattern in seasonal characteristics indicated the hydrologic data products poorly represent streamflow timing in snow-affected regions of the basin. Discrepancies in magnitude, seasonality, and regime indicate the potential for multiple sources of error. Because poor correspondence was present across all 19 streamgages, it was not possible to identify specific drivers of poor performance (that is, drainage area or geography). The modeling chain should be evaluated for biases associated with meteorologic forcing data, as well as hydrologic model formulation and calibration. We conclude that the hydrologic data products we evaluated appear unsuitable for applications tied to habitat and ecosystem restoration and management in the Upper Mississippi and Illinois Rivers. Plans to develop a future hydrology dataset for the Upper Mississippi River Restoration program would benefit from ongoing work to improve global climate model output downscaling methods, to improve hydrologic models, to make use of innovations in machine-learning approaches for projecting hydrology, and other efforts. The framework developed herein to evaluate hydrometeorological outputs generated using global climate models for a specific water resources application is a transferrable approach that could be applied to other data products and river systems.

Illinois, Indiana, Iowa, Minnesota, Missouri, Sout↗

USGS2025

Characterizing the niche of Phalaris arundinacea (reed canarygrass) in floodplain forests of the Upper Mississippi River

Information on the favorable conditions for invasive species as well as potential constraints to their distribution can be valuable for management efforts. We used a niche modeling approach to analyze the patterns of species distributions along gradients of hypothesized influential environmental variables. Many ecological datasets may have incomplete coverage across the environmental gradients, infrequent sampling under some conditions, insufficient time for an invasive species to occupy all sites, and complex interactions among environmental variables (measured or unmeasured) that may result in species response curves that are difficult to interpret and may be ecologically misleading. To ensure the model and species response curves aligned with ecological niche theory, shape constraints were imposed to guarantee relationships follow a unimodal distribution to reflect the fundamental niche (where a species could occur). We compared a shape-constrained model to an unconstrained model and interpreted the species response curves from the constrained model to better characterize the ecological niche of reed canarygrass in floodplain forests of the Upper Mississippi River, USA. We found the probability of reed canarygrass occurrence decreases with increasing tree canopy cover, tree species richness, distance from forest edge, distance from invaded wet meadows, and island isolation. Probability of reed canarygrass presence exhibited bell-shaped curves in response to hydrology (inundation depth, frequency, and duration) and forest stress metrics indicating an optimum with less favorable conditions on either end of the ecological gradients. This information could be used to prioritize restoration efforts and enhance landcover change research in forested floodplains.

upper Mississippi River↗

USGS2025

Managing for tomorrow—A climate adaptation decision framework

Climate change presents new and compounding challenges to natural resource management. With changing climate patterns, managers are confronted with difficult decisions on how to minimize climate effects on habitats, infrastructure, and wildlife populations. To support climate adaptation decision making, we first conceptualized an approach that integrates the principles of the resist–accept–direct framework, climate scenario planning, and decision analysis into a general framework to support adaptation planning. This framework was implemented and refined by working with three National Wildlife Refuge System refuges within the Midwest Region. The objectives of this report are to describe the climate adaptation decision framework and provide guidance for how to apply the framework to support transparent, consistent, and decision-focused adaptation planning. We include a workbook to support the application of each step of the framework as well as lessons learned from our experiences developing the framework. The climate adaptation decision framework has wide applicability to aid adaptation planning within natural resource management and underscores the important role of engaging interest groups in climate adaptation decisions.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗

USGS2025

Workshop: Nature-based solutions to ecological and economic problems caused by extreme precipitation events in the Upper Mississippi River Basin

Future climate conditions in the Upper Mississippi River Basin are projected to include many more extreme precipitation events. These intense periods of rain can lead to flooding of the Mississippi River itself, as well the small streams and rivers that feed it. This flooding presents a challenge for local communities, farmers, small businesses, river users, and the ecosystems and wildlife in the area. To reduce the damage done by these extreme rainfall events, ‘natural solutions’ are often helpful. This might include preserving forests and grasslands to absorb rainwater before it arrives at streams or restoring wetlands to slow and clean runoff water. For river and natural resource managers to adapt to future climate by using these natural solutions, however, they require accurate information about the projected increase in extreme rainfall events and the effectiveness and costs of a variety of solutions. To provide this information, researchers must understand the decisions that managers are making and the challenges they face. In this project, researchers will host a workshop to facilitate knowledge sharing between natural resource managers, climate modelers, and scientists studying natural solutions. Participants will discuss climate projections related to extreme precipitation events in the region, as well as the management implications and decision-making challenges associated with these events. These conversations will cultivate collaborative relationships between managers and researchers to address critical knowledge gaps and improve future management efforts in the Upper Mississippi River Basin.

Upper Mississippi River basin↗

USGS2024

Spatial differences in predicted Phalaris arundinacea (reed canarygrass) occurrence in floodplain forest understories

Reed canarygrass ( Phalaris arundinacea L.) is one of the most common invaders of floodplains and wetlands in North America. In the Upper Mississippi River floodplain, invasion by reed canarygrass in forest understories can inhibit forest regeneration when gaps form in the overstory. Understanding the distribution of reed canarygrass in forest understories is essential for effective management and control. We used an ensemble of species distribution models including Bayesian additive regression trees, boosted trees, and random forest algorithms to predict habitat suitability for reed canarygrass in forest understories across the Upper Mississippi River floodplain (~41,000 ha). Data from forest inventory study plots with reed canarygrass presence and absence were combined with 10 hypothesized environmental predictors of reed canarygrass invasion. We applied three approaches to better understand and incorporate the influence of spatial autocorrelation among our predictor variables, including random cross-validation, spatial cross-validation, and spatial cross-validation with Euclidean distance fields. Flood frequency, distance to contiguous floodplain, distance to forest edge, and distance to invaded wet meadow were among the most important environmental predictors across the three algorithms. Generally, the mean probability of reed canarygrass presence decreased with increasing flood depth, distance to contiguous floodplain, distance to invaded wet meadow, forest cover, and forest height, while relationships with other predictors were more variable. The ensemble of the three models (i.e., the average prediction) was used to map and summarize potential reed canary grass habitat suitability across the landscape. The maps generated quantified the habitat suitability for reed canarygrass and areas of agreement among the models in forest understories across the floodplain. This information can be used to better understand the extent of invasion, prioritize restoration efforts, and develop further research.

Illinois, Indiana, Iowa, Minnesota, Missouri, Wisc↗

USGS2024

Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold-type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning.

Conservation Biology↗

USGS2023

Improving the Midwest Climate Change Vulnerability Assessment Tool to support regional climate adaptation

An online climate vulnerability assessment dashboard was developed in 2021 through collaboration between U.S. Geological Survey (USGS) and U.S. Fish and Wildlife Service (FWS) to support regional climate adaptation efforts. The dashboard included 15 climate change impact metrics (five each from three categories: hydrology, precipitation, and temperature) and five metrics representing each watershed's capacity to adapt to changing conditions. Users could then adjust relative weights of each metric to generate vulnerability scores. The metrics included in the dashboard were identified by FWS for their programs but have broad relevance, making the dashboard useful to a wide range of stakeholders. For this project we had two primary goals: (1) update the online dashboard to better communicate the variability that is inherent in climate change projections, and (2) develop a use case example using the dashboard to collaboratively assess vulnerability of a resource of concern at a workshop with resource managers. For objective 2, we selected prairie-obligate butterflies (POBs), which are dependent on, and often restricted to, native prairie habitat. The extent of native prairie has been greatly reduced over the last two centuries resulting in a patchwork of isolated and often small tracts of land. For many POBs, declines and extirpations have been observed in recent decades. Although the causes are not always known, hypotheses include overuse of management tools (e.g., too frequent burning or overgrazing), lack of dispersal opportunities, or extreme weather events. With more extreme weather events anticipated in the future along with other changes in climate, it is important to better understand the vulnerability of POBs to design effective adaptation strategies. While research on extreme weather, climate change, and adaptation is ongoing for some prairie-obligate species, this workshop sought to take a broad perspective using POBs as the focal taxonomic group across eight U.S. States in the Midwest During the workshop we discussed weather and climate-related influences on butterfly communities and assessed climate change vulnerability using the Watershed-based Midwest Climate Change Vulnerability Assessment Tool (https://www.usgs.gov/apps/CC_Vulnerability/). We produced maps that quantify the regional vulnerability of POBs across 360 watersheds for two future emissions scenarios. The information developed during the workshop could help in regional planning for climate change adaptation and to identify avenues for research and collaboration for POBs in the Midwest.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗

USGS2022

Climate change adaptation thinking for managed wetlands

Climate change presents new and ongoing challenges to natural resource management. To confront these challenges effectively, managers need to develop proactive adaptation strategies to prepare for and deal with the effects of climate change. We engaged managers and biologists from several midwestern U.S. Fish and Wildlife Service field stations to understand recent and future climate change effects, identify adaptation barriers and opportunities, and pilot an approach for integrating adaptation thinking into management planning. To start, three structured discussions informed our understanding of how managers currently deal with climate change effects, the strategies being implemented to cope, and the barriers that limit climate change adaptation efforts. We used these insights to develop a multiday virtual workshop geared toward identifying potential adaptation strategies for managed wetlands. First, we developed a conceptual model to visualize how management actions are used to meet habitat objectives within wetland management systems. Next, we discussed how climate change may affect management actions and objectives; we used this understanding of potential effects to spatially assess vulnerability of managed wetlands to climate change. Using a scenario planning approach, we incorporated multiple potential future conditions and identified effects and adaptation strategies that could be considered for each scenario. As a result, several adaptation strategies for managed wetlands under dry and wet future scenarios were identified that can be applied when developing site-specific adaptation plans. Based on our piloted approach, we determined it would be important to have an adaptation team composed of scientists and managers to facilitate discussions, develop appropriate scenarios, and identify realistic adaptation options. We document the tools, findings, and adaptation thinking process taken to enhance adaptation efforts of managed wetlands. The adaptation thinking process can be applied to advance adaptation efforts in other habitats, ecosystems, and site-specific land management.

Open-File Report↗

USGS2021

Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators

Climate change has and is projected to continue to alter historical regimes of temperature, precipitation, and hydrology. To assess the vulnerability of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with land managers to develop a climate change vulnerability map for the midwestern United States with a focus on riparian systems. The map is intended for use by regional administrators to help them work across various program areas (e.g. fisheries, endangered species) to prioritize locations needing support for adaptation planning. The tool can also be utilized locally by managers to better understand the effects that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (360 watershed units within the region) and combines 15 climate change indicators that were selected by U.S. Fish and Wildlife Service natural resource managers based upon known and anticipated effects to species and habitats. The projected change in each of these indicators from the historical period (1986–2005) to the future period (2040–2059) was aggregated into a composite score for each watershed. Landscape-scale metrics reflective of a watershed’s adaptive capacity were combined with the climate change indicators to produce a vulnerability score. We found sub-regional variation in vulnerability to climate change with the greatest vulnerability in Iowa, central Illinois, and northwest Ohio. Greater vulnerability was seen in the higher greenhouse gas concentration scenario, Representative Concentration Pathway (RCP) 8.5 compared to the lower greenhouse gas concentration scenario RCP 4.5, when looking at the mean of the five downscaled climate models used in this study. By quantifying and mapping climate change vulnerability, natural resource managers can better understand the degree of vulnerability for individual watersheds and identify areas of prioritization in regional and local planning efforts.

Iowa, Illinois, Indiana, Michigan, Minnesota, Miss↗

USGS2021

Vulnerability assessment and adaptation planning for projected changes in water quality and quantity for protected areas in the upper Midwest

Climate change and the extreme weather associated with it can be a major challenge to natural resource managers charged with the protection, restoration, recovery, and management of wetlands and wildlife habitats. Forecasting the potential impacts of climate changes will be important for decision-makers and land managers seeking to minimize impacts to habitats, infrastructure, and wildlife populations and prepare for the future. In collaboration with U.S. Fish and Wildlife Service (FWS) managers, we developed a climate change vulnerability assessment to spatially evaluate climate vulnerabilities across the Midwest region. To create the vulnerability assessment, we convened resource managers and scientists working across the region to determine the components and scope of the vulnerability assessment. The vulnerability assessment was watershed-based and composed of 15 indicators of climate change and five indicators that reflect the capacity of a watershed to buffer against the effects of climate change. The indicators were selected by FWS managers to have broad applicability across systems and programs in the FWS. To facilitate usability, we created an online application that allows users to generate customizable vulnerability assessments. We then integrated the assessment into a process for engaging in climate change adaptation thinking as a precursor to formal planning, implementation, and monitoring of adaptation actions. The process we designed focused on understanding the components of the system, assessing climate change vulnerabilities, creating and describing possible climate change scenarios, and identifying impacts and adaptation options for each scenario. We piloted this process in a virtual workshop setting with FWS managers and biologists on the topic of managed wetland systems. This work is currently being used by the FWS to better understand regional vulnerabilities and adaptation strategies and to advance integration of climate science into formal planning processes.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗