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Tag: Ecology--Mathematical models
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  • Considerations for Integrating Ecological and Hydrogeomorphic Models: Developing a Comprehensive Marsh Vegetation Model

    PURPOSE: Predictive models for salt marsh management require a systems perspective that recognizes the dynamic interactions between physical and ecological processes. It is critical to link physical process and landscape evolution models to quantify hydro-eco-geomorphic feedbacks in marsh environments. A framework that explicitly defines how to integrate these disparate models is a necessary step towards developing a comprehensive marsh model. This technical note (TN) proposes an approach to integrate existing hydrodynamic and geomorphic models with a mechanistic vegetation model into a coupled framework to better simulate salt marsh evolution.
  • Review of Riparian Models for Assessing Ecological Impacts and Benefits

    BACKGROUND: Riparian zones are key transitional ecosystems between upland and aquatic zones, and these systems are often degraded due to both land use change and stream processes (e.g., deforestation and water impoundments and/or diversions). These important ecosystems require restoration because of the many benefits they provide ranging from providing habitat for diverse species to promoting water quality. Restoration practitioners, regulators, and researchers require riparian assessment methods and models to efficiently guide mitigation and restoration planning. This technical note (TN) compiles a subset of existing riparian tools and evaluates them relative to model objectives, modeling approach, and input variables. Findings are synthesized into a gap analysis of these models to inform future riparian model development and improve riparian assessment.
  • Defining Levels of Effort for Ecological Models

    BACKGROUND: While models are useful tools for decision-making in environmental management, the question arises about the level of effort required to develop an effective model for a given application. In some cases, it is unclear whether more analysis would lead to choosing a better course of action. This technical note (TN) examines the role of ecological model complexity in ecosystem management. First, model complexity is examined through the lens of risk informed planning. Second, a framework is presented for categorizing five different levels of effort that range from conceptual models to detailed predictive tools. This framework is proposed to enhance communication and provide consistency in ecological modeling applications. Third, the level of effort framework is applied to a set of models in the Middle Rio Grande River system to demonstrate the framework’s utility and application. Ultimately, this TN seeks to guide planners in determining an appropriate level of effort relative to risks associated with uncertainty and resource availability for a given application.
  • Swan Island Resilience Model Development; Phase I: Conceptual Model

    Abstract: This report documents the development of an integrated hydrodynamic and ecological model to test assumptions about island resilience. Swan Island, a 25-acre island in Chesapeake Bay, Maryland, was used as a case study. An interagency, interdisciplinary team of scientists and engineers came together in a series of workshops to develop a simplified resilience model to examine the ability of islands to reduce waves and erosion and the impacts to nearby habitats and shorelines. This report describes the model development process and the results from this first key step: model conceptualization. The final conceptual model identifies four main components: vegetative biomass, island elevation, waves/currents, and sediment supply. These components interact to form and support specific habitat types occurring on the island: coastal dunes, high marsh, low marsh, and submerged aquatic vegetation. The pre-and post-construction field data, coupled with hydrodynamic ecological models, will provide predictive capabilities of island resilience and evaluations of accrued benefits for future island creation and restoration projects. The process and methods described can be applied to island projects in a variety of regions and geographic scales.
  • Ecological Model Development: Evaluation of System Quality

    PURPOSE: Ecological models are used throughout the US Army Corps of Engineers (USACE) to inform decisions related to ecosystem restoration, water operations, environmental impact assessment, environmental mitigation, and other topics. Ecological models are typically developed in phases of conceptualization, quantification, evaluation, application, and communication. Evaluation is a process for assessing the technical quality, reliability, and ecological basis of a model and includes techniques such as calibration, verification, validation, and review. In this technical note (TN), we describe an approach for evaluating system quality, which generally includes the computational integrity, numerical accuracy, and programming of a model or modeling system. Methods are presented for avoiding computational errors during development, detecting errors through model testing, and updating models based on review and use. A formal structure is proposed for model test plans and subsequently demonstrated for a hypothetical habitat suitability model. Overall, this TN provides ecological modeling practitioners with a rapid guide for evaluating system quality.
  • Geospatial Suitability Indices (GSI) Toolbox: User’s Guide

    Abstract: Habitat suitability models have been widely adopted in ecosystem management and restoration to assess environmental impacts and benefits according to the quantity and quality of a given habitat. Many spatially distributed ecological processes require application of suitability models within a geographic information system (GIS). This technical report presents a geospatial toolbox for assessing habitat suitability. The geospatial suitability indices (GSI) toolbox was developed in ArcGIS Pro 2.7 using the Python 3.7 programming language and is available for use on the local desktop in the Windows 10 environment. Two main tools comprise the GSI toolbox. First, the suitability index (SIC) calculator tool uses thematic or continuous geospatial raster layers to calculate parameter suitability indices using user-specified habitat relationships. Second, the overall suitability index calculator (OSIC) combines multiple parameter suitability indices into one overarching index using one or more options, including arithmetic mean, weighted arithmetic mean, geometric mean, and minimum limiting factor. The result is a raster layer representing habitat suitability values from 0.0–1.0, where zero (0) is unsuitable habitat and one (1) is ideal suitability. This report documents the model purpose and development and provides a user’s guide for the GSI toolbox.
  • Ecological Model Development: Toolkit for interActive Modeling (TAM)

    Overview: Ecological models provide crucial tools for informing many aspects of ecosystem restoration and management, ranging from increasing understanding of complex ecological functions to prioritizing restoration sites and quantifying benefits for project reporting. The diversity of ecosystem types and restoration objectives often precludes the use of existing models; as such, model development is commonly required to inform restoration decision-making. Index-based habitat models are a common approach for assessing ecosystem condition. These models relate habitat quality to species’ distributions. Habitat suitability (quality) typically ranges on a scale from 0 to 1. Habitat models have been developed to assess habitat suitability for specific taxa, communities, or ecosystem functions. Restoration-project timelines often require that these models be developed rapidly and in conjunction with many external stakeholders or partners. Here, the Toolkit for interActive Modeling (TAM) is proposed as a platform for rapidly developing index-based models, particularly for US Army Corps of Engineers’ (USACE) ecosystem-restoration or mitigation planning processes. The TAM is a consistent quantitative framework that allows for development of a generic platform for index-based model development
  • Scenario Analyses in Ecological Modeling and Ecosystem Management

    Purpose: Ecosystem management and restoration practitioners are challenged with complex problems, diverse project goals, multiple management alternatives, and potential future scenarios that change the systems of interest. Scenario analysis aids in forecasting, evaluating, and communicating outcomes of potential management actions under different plausible conditions, such as land-use change or sea level rise. However, little guidance exists for practitioners on the utility and execution of scenario analysis. Therefore, this technical note highlights the usefulness of scenario analysis as a tool for addressing uncertainty in potential project outcomes. The mechanics of the scenario-analysis process are explained, and examples of different types of scenario analyses are described for context on the breadth of its use. Lastly, two hypothetical case studies of scenario analysis in ecological modeling are presented showing a semiquantitative approach for assessing anadromous fish and a quantitative approach examining freshwater mussel habitat. Overall, this technical note provides a brief review of the utility and application of scenario analyses in the context of ecological modeling and ecosystem management decision-making.
  • PUBLICATION NOTICE: Proceedings from the US Army Corps of Engineers (USACE) and the National Oceanic and Atmospheric Administration (NOAA)–National Ocean Service (NOS): Ecological Habitat Modeling Workshop

    ABSRACT: This special report summarizes the activities of the Ecological Habitat Modeling Workshop held April 11–12, 2019, at the US Fish and Wildlife Service (USFWS) Blackwater National Wildlife Refuge Visitors Center in Cambridge, Maryland. The workshop guided 21 participants through the process of conceptualizing, quantifying, evaluating, and communicating ecological responses to inform guidance and management decisions for ecological restoration projects. Working in interactive groups, participants used the restoration work already in progress at nearby Swan Island as the basis for their model development. Over the course of the two-day workshop, participants learned the mechanics and challenges of applying modeling processes to shape the restoration of dynamic ecosystems. Through group work and brainstorming, they identified a number of benchmarks to assess restoration success and future resilience. To accommodate the changeable and often unpredictable natural events that can shape ecosystems, workshop facilitators emphasized building iterative, fluid ecological habitat models. Next steps include publishing this special report and scheduling a follow-up workshop that will include a site visit to Swan Island.