Geology topics

Kevin J. Suir

Publications and source records attributed to Kevin J. Suir.

9 recordsLinked to original sources

USGS2021

EverForecast—A near-term forecasting application for ecological decision support

The Everglades Forecasting application (EverForecast) provides decision makers with a support tool to examine optimal allocations of water across the managed landscape while explicitly quantifying the conflicting needs of multiple species. Covering the Greater Everglades (a vast, subtropical wetland ecosystem in South Florida), EverForecast provides 6-month forecasts of daily projected water stage across the region. It then runs these forecasts through a suite of species models and illustrates potential tradeoffs. All output is summarized by subregion and hydrologic category. Decision makers can use these near-term forecasts to manage the transition from current conditions to future alternatives according to their management priorities.

Florida↗

USGS2019

Council monitoring and assessment program (CMAP) compilation of existing habitat and water quality monitoring and mapping assessments for the Gulf of Mexico Region

This report is a deliverable to the RESTORE Council for Task 7: Document the existing baseline habitat and water quality conditions prior to implementation of the restoration projects; these baseline conditions will serve as a basis for measuring change/progress after restoration. It is the second in a series of CMAP reports. The first report describes the process and development of the CMAP monitoring program inventory, herein the Inventory (NOAA and USGS, 2019). The goals and objectives for the Inventory were to identify and document existing habitat and water quality monitoring, and mapping programs, data, and protocols in the GoM. The Inventory built upon existing databases, such as the Ocean Conservancy (Love, 2015), Global Change Monitoring Portal (GCMP; GCMP, 2017), and Gulf of Mexico Alliance (GOMA) databases (GOMA, 2013), including habitat and water quality monitoring programs at national, regional, State and local scales. This second report identifies and catalogs existing water quality, habitat and mapping assessments within the Gulf of Mexico. This assessment catalog, herein the Catalog, was intended to supplement the Inventory to identify the best available science necessary for restoration, conservation or management activities. Both the Inventory and the Catalog databases will be accessible to the Council and the greater GoM restoration, monitoring, management, and academic communities through a searchable web-based tool.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗

USGS2019

Council Monitoring and Assessment Program (CMAP): Inventory of existing water quality and habitat monitoring, and mapping metadata for Gulf of Mexico Programs

Under the Council-Selected Restoration Component of the RESTORE Act, the Council develops Funded Priority Lists (FPLs) that describe the projects and programs it will fund. Projects and programs funded through this component must be in furtherance of the goals and objectives of the Council’s Comprehensive Plan and address at least one of the restoration criteria identified in the RESTORE Act. The Initial FPL, finalized in December of 2015, had a strong focus on watershed and estuary restoration and foundational cross-Gulf projects. Approved as a Gulf-wide investment in the 2015 Initial FPL, The Council Monitoring and Assessment Program (CMAP) is administered jointly by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS). Funded activities include the development of basic, foundational components for Gulf-wide monitoring to measure beneficial impacts of investments in Gulf restoration by the Council. The program, in coordination with the Gulf of Mexico Alliance (GOMA) and through collaboration with the Gulf States, Federal and local partners, academia, non-governmental organizations, and business and industry, has leveraged existing resources, capacities, and expertise and build on existing monitoring data and programs.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗

USGS2019

Regional protocol framework for the inventory and monitoring of breeding Atlantic Coast Piping Plovers

This regional protocol provides a framework for quantifying the number of breeding pairs and productivity of Atlantic Coast piping plover (Charadrius melodus) populations during the breeding season. A primary purpose of this protocol is to standardize piping plover monitoring during the breeding season. The survey techniques described herein involve repeated visual counts of adults, nests, eggs, and chicks within a defined survey site (i.e., beach) as well as visual identification of potential threats to survival and productivity. Resulting data can be compiled and analyzed across multiple geographic units (i.e., sites, states, and recovery units) to assess progress toward recovery goals, inform local management decisions, assess management effectiveness, and improve monitoring efforts. This protocol framework was developed as part of the United States Fish and Wildlife Service (USFWS) National Wildlife Refuge System (NWRS) Inventory and Monitoring (I&M) Initiative in coordination with Ecological Services (ES) and state coordinators within the Southeast and Northeast Regions (4 and 5, respectively). Although this protocol framework is to be used primarily by NWRS to inform recovery goals, assist with local management decision-making, and meet State reporting requirements, the approach strives to assist monitoring efforts of nonNWRS partners, such as other federal agencies (e.g. National Park Service), State wildlife agencies, non-governmental organizations, and private landowners. This protocol framework and associated data management system (PIPLweb) aims to interface with existing data management and analysis tools (i.e., PIPLODES, NestStory, and PiperEx) to ensure that data collection is efficient and comparable across scales, and supports management decisions across partners. The content and structure of the protocol framework follows standards set forth in the USFWS’s How to Develop Survey Protocols: A Handbook (Version 1.0; 2013). The eight elements addressed include: introduction, sampling design, field methods, data management and analysis, reporting, personnel requirements and training, operational requirements, and references. A series of standard operating procedures (SOPs) provides greater detail on recommended methods and technical aspects of this protocol. Data entry, archival, and multi-scale analysis are handled through a secure web application (Plover Inventory and Productivity Library; PIPLweb) developed by the United States Geological Survey (USGS). When management activities and survey objectives are similar across management units, partners (Refuges, other federal agencies, State, NGOs, private) are encouraged to use this protocol framework to develop stepped-down site-specific survey protocols that include guidance for conducting on-the-ground monitoring and management plans.

Regional Protocol Framework↗

USGS2018

Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings

On an annual basis, federal and state agencies are responsible for mapping and removing large expanses of aquatic nuisance vegetation from navigable waterways. This study set out to achieve four primary objectives: (1) utilize recent advancements in remote sensing techniques to classify the extent and distribution of aquatic vegetation in coastal ecosystems using satellite imagery, (2) assess primary aquatic vegetation growth and management efforts in coastal Louisiana, (3) statistically identify the ecological drivers that promote growth and infestation of aquatic nuisance vegetation, and (4) develop numerical models and a spatial tool to predict the probability of occurrence and growth of aquatic vegetation given ecological drivers. Moderate spatial resolution multispectral satellite imagery were used in conjunction with environmental variables from available data streams to generate regression models that predict aquatic vegetation occurrence in the eastern coastal region of south Louisiana. Geospatial tools were developed to execute the model logic using recent environmental conditions, thereby predicting aquatic vegetation occurrence and producing classified maps for end users. These products provide more efficient and enhanced capabilities for management of aquatic nuisance vegetation.

Louisiana↗

USGS2015

Modeling apple snail population dynamics on the Everglades landscape

Context The Florida Everglades has diminished in size and its existing wetland hydrology has been altered. The endangered snail kite ( Rostrhamus sociabilis ) has nearly abandoned the Everglades, and its prey, the apple snail ( Pomacea paludosa ), has declined. Objective We developed a population model (EverSnail) to understand apple snail response to inter- and intra-annual fluctuations in water depths over the Everglades landscape. EverSnail was developed as a tool to understand how apple snails respond to different hydrologic scenarios. Methods EverSnail is an age- and size-structured, spatially-explicit landscape model of P. paludosa in the Everglades. Landscape-level inputs are water depth and air temperature. We conducted sensitivity analyses by running EverSnail with ± 20 % the baseline value of eight parameters. Results EverSnail was sensitive to changes in survival and water depth associated with reproduction. The EverSnail population varied with changes and/or differences in depth generally consistent with empirical data; site-specific comparisons to field data proved less reliable. A simulated 3-year wet period resulted in a shift in apple snail distribution, but little change in total abundance over the landscape. In contrast, a simulated 3-year succession of relatively dry years resulted in overall lower snail abundances. Conclusions Comparisons of model output to empirical data indicate the need for more data to better understand, and eventually parameterize, several aspects of snail ecology in support of EverSnail. A primary value of EverSnail is its capacity to describe the relative response of snail abundance to alternative hydrologic scenarios considered for Everglades water management and restoration.

Florida↗

USGS2015

EverVIEW: a visualization platform for hydrologic and Earth science gridded data

The EverVIEW Data Viewer is a cross-platform desktop application that combines and builds upon multiple open source libraries to help users to explore spatially-explicit gridded data stored in Network Common Data Form (NetCDF). Datasets are displayed across multiple side-by-side geographic or tabular displays, showing colorized overlays on an Earth globe or grid cell values, respectively. Time-series datasets can be animated to see how water surface elevation changes through time or how habitat suitability for a particular species might change over time under a given scenario. Initially targeted toward Florida's Everglades restoration planning, EverVIEW has been flexible enough to address the varied needs of large-scale planning beyond Florida, and is currently being used in biological planning efforts nationally and internationally.

Computers & Geosciences↗

USGS2014

A visualization tool to support decision making in environmental and biological planning

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

Environmental Modelling and Software↗

USGS2013

Predicting the effects of proposed Mississippi River diversions on oyster habitat quality; application of an oyster habitat suitability index model

In an attempt to decelerate the rate of coastal erosion and wetland loss, and protect human communities, the state of Louisiana developed its Comprehensive Master Plan for a Sustainable Coast. The master plan proposes a combination of restoration efforts including shoreline protection, marsh creation, sediment diversions, and ridge, barrier island, and hydrological restoration. Coastal restoration projects, particularly the large-scale diversions of fresh water from the Mississippi River, needed to supply sediment to an eroding coast potentially impact oyster populations and oyster habitat. An oyster habitat suitability index model is presented that evaluates the effects of a proposed sediment and freshwater diversion into Lower Breton Sound. Voluminous freshwater, needed to suspend and broadly distribute river sediment, will push optimal salinities for oysters seaward and beyond many of the existing reefs. Implementation and operation of the Lower Breton Sound diversion structure as proposed would render about 6,173 ha of hard bottom immediately east of the Mississippi River unsuitable for the sustained cultivation of oysters. If historical harvests are to be maintained in this region, a massive and unprecedented effort to relocate private leases and restore oyster bottoms would be required. Habitat suitability index model results indicate that the appropriate location for such efforts are to the east and north of the Mississippi River Gulf Outlet.

Louisiana↗