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USGS2012

Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

Alabama;Florida;Georgia;Mississippi;South Carolina↗

USGS2015

Development of conceptual ecological models linking management of the Missouri River to pallid sturgeon population dynamics

This report documents the process of developing and refining conceptual ecological models (CEMs) for linking river management to pallid sturgeon ( Scaphirhynchus albus ) population dynamics in the Missouri River. The refined CEMs are being used in the Missouri River Pallid Sturgeon Effects Analysis to organize, document, and formalize an understanding of pallid sturgeon population responses to past and future management alternatives. The general form of the CEMs, represented by a population-level model and component life-stage models, was determined in workshops held in the summer of 2013. Subsequently, the Missouri River Pallid Sturgeon Effects Analysis team designed a general hierarchical structure for the component models, refined the graphical structure, and reconciled variation among the components and between models developed for the upper river (Upper Missouri & Yellowstone Rivers) and the lower river (Missouri River downstream from Gavins Point Dam). Importance scores attributed to the relations between primary biotic characteristics and survival were used to define a candidate set of working dominant hypotheses about pallid sturgeon population dynamics. These CEMs are intended to guide research and adaptive-management actions to benefit pallid sturgeon populations in the Missouri River.

Missouri River, Yellowstone River↗

USGS2006

Conceptual ecological model for management of breeding grassland birds in the Mid-Atlantic Region

The status of grassland birds has become an increasingly important conservation issue. These species exhibit the most consistent population declines of any group of North American birds during the past 40 years. Anecdotal evidence suggests these declines have been occurring for nearly a century (Peterjohn and Sauer 1999). While the widespread conversion of grasslands into other habitats contributed to these declining populations, other factors such as habitat fragmentation and mowing regimes are also implicated (Vickery et al. 1999a). This plight of grassland birds has heightened awareness of the need for concerted conservation actions to reverse these seriously declining population trends. The National Park Service (NPS) is positioned to potentially contribute to grassland bird conservation in the Mid-Atlantic Region. The NPS maintains a number of historic sites and former battlefields that are managed for their cultural significance but also support wildlife populations. Many of these “cultural parks” maintain open landscapes to recreate land use patterns that existed at the times of the historical events. These open landscapes are primarily managed grasslands which could be maintained to benefit grassland birds. In 2005, the NPS initiated a project exploring the potential of “cultural parks” to support significant breeding grassland bird communities. This project involved parks within three NPS Inventory and Monitoring Program (I&M) networks, Mid-Atlantic, National Capital, and Eastern Rivers and Mountains. Five parks were selected for the initial focus of this study, all of which maintain open landscapes for interpretation of historic events. Most parks were selected because they represent the most extensive grassland habitats within their networks, with the rationale that if these parks cannot support significant breeding grassland bird communities, then parks with smaller acreages cannot support these communities either. The five parks included in this study are: Antietam National Battlefield, Fort Necessity National Battlefield, Gettysburg National Battlefield, Manassas National Battlefield, and Monocacy National Battlefield. This conceptual ecological model is one product of this project. The information presented below allows NPS Network Coordinators to understand the factors to consider when making decisions concerning grassland management within their networks. This model provides park Resource Managers with information on grassland ecology in the Mid-Atlantic Region, the ecological requirements of grassland birds likely to occur in their parks, and management issues that influence whether significant breeding populations can be expected to occupy grasslands created and maintained in the parks. The Resource Managers can then make informed decisions concerning their ability to create and maintain grassland habitats. The emphasis of this conceptual model is restricted to management of breeding grassland birds. Additional species may occur in this region during migration and winter, while habitat requirements of all grassland birds during nonbreeding seasons will differ from those described for the breeding season.

Natural Resource Report↗

USGS2006

Conceptual ecological model for management of breeding shrubland birds in the Mid-Atlantic Region

While grassland birds have become the focus of increased conservation activities, the status of birds occupying shrubland habitats has received relatively little attention (Hunter et al. 2001). Yet, in eastern North America, shrubland birds exhibited consistent population declines during the past 40 years, based on data from the North American Breeding Bird Survey (Pardieck and Sauer 2001). These population declines primarily reflect large-scale changes in land use patterns during the previous century (Lorimer 2001). Large areas of marginal farmland were abandoned and underwent secondary succession during the first half of the twentieth century, producing abundant successional habitats favored by shrubland birds. As these habitats matured, combined with strict fire-suppression policies (Hunter et al. 2001), shrublands succeeded into mature forests, and shrubland bird communities were replaced by woodland birds (Irland 1982; Askins 1993). For example, while nearly 29% of New England forests were classified as sapling stage in 1950, only 8% remained at that stage in the 1980s (Askins 1993). The trend towards forest maturation and loss of shrubland habitats continues, yet concerted conservation activities have not been directed to benefit declining shrubland bird populations. The National Park Service (NPS) could contribute to shrubland bird conservation in the Mid- Atlantic Region. The NPS maintains a number of historic sites and former battlefields managed for their cultural significance but also support wildlife populations. Many of these “cultural parks” maintain open landscapes, recreating land use patterns existing at the times of the historical events. While these open landscapes are frequently managed grasslands, some parks also support successional habitats that could be managed to benefit shrubland birds. In 2005, the NPS initiated a project exploring the potential of “cultural parks” to support significant breeding grassland and shrubland bird communities. This project involved parks within three NPS Inventory and Monitoring Program (I&M) networks, Mid-Atlantic, National Capital, and Eastern Rivers and Mountains. Five parks were selected for the initial focus of this study, all of which maintain open landscapes for interpreting historic events. Most parks were selected because they contain the most extensive grassland habitats within their networks, although some also support shrubby successional habitats. The five parks included in this study are Antietam National Battlefield, Fort Necessity National Battlefield, Gettysburg National Battlefield, Manassas National Battlefield, and Monocacy National Battlefield. This conceptual ecological model is one product of this project. The information presented below allows NPS network coordinators to understand which factors should be considered when making decisions concerning shrubland management within their networks. This model provides park resource managers with information on shrubland ecology in the Mid-Atlantic Region, the ecological requirements of shrubland birds likely to occur in their parks, and management issues influencing whether significant breeding populations can occupy shrublands created and maintained in the parks. Resource managers can then make informed decisions concerning their ability to create and maintain shrubland habitats. The emphasis of this conceptual model is restricted to management of breeding shrubland birds. Additional species occur during migration and winter, and habitat requirements of shrubland birds during nonbreeding seasons may differ from those described for the breeding season.

Technical Report↗

USGS2019

Selecting ecological models using multi-objective optimization

Choices in ecological research and natural resource management require balancing multiple, often competing objectives. Examples include maximizing species persistence in a wildlife conservation context, while minimizing cost, or balancing opposing stakeholder objectives when managing wildlife populations. Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical component of ecological inference and prediction and requires balancing the competing objectives of model fit and model complexity. The tradeoff between model fit and model complexity provides a basis for describing the model-selection problem within the MOO framework. We discuss MOO and two strategies for solving the MOO problem; modeling preferences pre-optimization and post-optimization. Most conventional model selection methods can be formulated as solutions of MOO problems via specification of pre-optimization preferences. We reconcile model selection within the MOO framework. We also consider model selection using post-optimization specification of preferences. That is, by first identifying Pareto optimal solutions, and then selecting among them. We demonstrate concepts with an ecological application of model selection using avian species richness data in the continental United States.

Ecological Modelling↗

USGS2017

Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability

Streamflow is essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Changes in climate, land use and water use practices may alter water availability. Understanding the potential effect of these changes on aquatic ecosystems is critical for long-term water management to maintain a balance between water for human consumption and ecosystem needs. Fish species data and streamflow estimates from a rainfall-runoff and flow routing model were used to develop boosted regression tree models to predict the relationship between streamflow and fish species richness (FSR) under plausible scenarios of (1) water withdrawal, (2) climate change and (3) increases in impervious surfaces in the Piedmont ecoregion of North Carolina, U.S.A. Maximum monthly flow, the fraction of total flow originating from impervious surface runoff, coefficient of monthly streamflow variability, and the specific river basin accounted for 50% of the variability in FSR. This model was used to predict FSR values for all twelve-digit Hydrological Unit Code catchments (HUC-12s) in the North Carolina Piedmont under current flow conditions and under water withdrawal, climate change and impervious surface scenarios. Flow–ecology modeling results indicate that predicted FSR declined significantly with increased water withdrawals. However, the magnitude of decline varied geographically. A “hot-spot” analysis was conducted based on predicted changes in FSR under each scenario to understand which HUC-12s were most likely to be affected by changes in water withdrawals, climate and impervious surfaces. Under the 20% withdrawal increase scenario, 413 of 886 (47%) HUC-12s in the study area were predicted to lose one or more species. HUC-12s in the Broad, Catawba, Yadkin and Cape Fear river basins were most susceptible to species loss. These findings may help decision making efforts by identifying catchments most vulnerable to changing water availability. Additionally, FSR-discharge modeling results can assist resource agencies, water managers and stakeholders in assessing the effect of water withdrawals in catchments to better support the protection and long-term conservation of species.

North Carolina↗

USGS2014

Integrated conceptual ecological model and habitat indices for the southwest Florida coastal wetlands

The coastal wetlands of southwest Florida that extend from Charlotte Harbor south to Cape Sable, contain more than 60,000 ha of mangroves and 22,177 ha of salt marsh. These coastal wetlands form a transition zone between the freshwater and marine environments of the South Florida Coastal Marine Ecosystem (SFCME). The coastal wetlands provide diverse ecosystem services that are valued by society and thus are important to the economy of the state. Species from throughout the region spend part of their life cycle in the coastal wetlands, including many marine and coastal-dependent species, making this zone critical to the ecosystem health of the Everglades and the SFCME. However, the coastal wetlands are increasingly vulnerable due to rising sea level, changes in storm intensity and frequency, land use, and water management practices. They are at the boundary of the region covered by the Comprehensive Everglades Restoration Plan (CERP), and thus are impacted by both CERP and marine resource management decisions. An integrated conceptual ecological model (ICEM) for the southwest coastal wetlands of Florida was developed that illustrates the linkages between drivers, pressures, ecological process, and ecosystem services. Five ecological indicators are presented: (1) mangrove community structure and spatial extent; (2) waterbirds; (3) prey-base fish and macroinvertebrates; (4) crocodilians; and (5) periphyton. Most of these indicators are already used in other areas of south Florida and the SFCME, and therefore will allow metrics from the coastal wetlands to be used in system-wide assessments that incorporate the entire Greater Everglades Ecosystem.

Ecological Indicators↗

USGS2005

Southern marl prairies conceptual ecological model

About 190,000 ha of higher-elevation marl prairies flank either side of Shark River Slough in the southern Everglades. Water levels typically drop below the ground surface each year in this landscape. Consequently, peat soil accretion is inhibited, and substrates consist either of calcitic marl produced by algal periphyton mats or exposed limestone bedrock. The southern marl prairies support complex mosaics of wet prairie, sawgrass sawgrass ( Cladium jamaicense ), tree islands, and tropical hammock communities and a high diversity of plant species. However, relatively short hydroperiods and annual dry downs provide stressful conditions for aquatic fauna, affecting survival in the dry season when surface water is absent. Here, we present a conceptual ecological model developed for this landscape through scientific consensus, use of empirical data, and modeling. The two major societal drivers affecting the southern marl prairies are water management practices and agricultural and urban development. These drivers lead to five groups of ecosystem stressors: loss of spatial extent and connectivity, shortened hydroperiod and increased drought severity, extended hydroperiod and drying pattern reversals, introduction and spread of non-native trees, and introduction and spread of non-native fishes. Major ecological attributes include periphyton mats, plant species diversity and community mosaic, Cape Sable seaside sparrow ( Ammodramus maritimus mirabilis ), marsh fishes and associated aquatic fauna prey base, American alligator ( Alligator mississippiensis ), and wading bird early dry season foraging. Water management and development are hypothesized to have a negative effect on the ecological attributes of the southern marl prairies in the following ways. Periphyton mats have decreased in cover in areas where hydroperiod has been significantly reduced and changed in community composition due to inverse responses to increased nutrient availability. Plant species diversity and community mosaics have changed due to shifting gradients to more terrestrial or more aquatic communities, displacement of native communities by non-natives, expansion of woody plants, high-intensity dry season fires, tree-island burnout, and reduced microtopography resulting from alligator population decline. Cape Sable seaside sparrow populations are threatened by nest destruction resulting from extended hydroperiods, drying pattern reversals, and high intensity dry season fires, as well as by the expansion of woody plants into graminoid wetland habitats. Populations of marsh fishes and associated aquatic fauna that constitute the aquatic prey base for higher vertebrates have decreased in density and changed in species composition and size structure due to loss of wetland spatial extent, shortened hydroperiod, increased drought severity, loss of aquatic drought refugia in solution holes and alligator holes, and spread of exotic fishes. American alligator populations have declined in the Rocky Glades, and alligator holes have filled with sediment, as a result of shortened hydroperiod and increased drought severity. Habitat options for wading birds to forage during the early dry season and during unusually wet years have been reduced due to loss of spatial extent and shortened hydroperiod.

Wetlands↗

USGS2024

The use of conceptual ecological models to identify critical data and uncertainties to support numerical modeling: The northern Gulf of Mexico eastern oyster Crassostrea virginica example

Objective Increasing reliance on numerical simulation models to help inform management and restoration choices benefits from careful consideration of critical early steps in model development. Along the northern coast of the Gulf of Mexico, the eastern oyster Crassostrea virginica fulfills important ecological and economic roles. Using the eastern oyster as an example, we draw on several recent frameworks outlining best practices for model development and application for restoration, conservation, and management. Methods We identify priority model questions, outline a conceptual ecological model (CEM) to guide numerical model development, and use this framework to identify uncertainties and research needs. Result The CEM uses a nested design, identifying explicit vital rates, processes, attributes, and outcomes for the species (oysters), population, and metapopulation (i.e., network of populations) levels in response to drivers of species, population, and metapopulation changes and changing environmental factors. Most management actions related to oyster restoration and harvest affect population attributes directly, but many coastal management actions and changes (i.e., climate change and coastal and water resource engineering) impact environmental factors that alter vital rates and attributes of oysters, populations, and metapopulations. Conclusion Investment in studies targeting individual oyster‐ and population‐level multi‐stressor responses (filtration, respiration, growth, and reproduction) and improving hydrodynamic and environmental models targeting drivers that influence metapopulation vital rates and attributes (i.e., connectivity and substrate persistence) would contribute to reducing uncertainties. Development of numerical models covering the entire oyster life cycle and connectivity of populations using hydrodynamic models of current and predicted conditions to provide key abiotic and biotic factors influencing larval movement, recruitment, and on‐reef oyster vital rates would assist in balancing the goals of conservation, restoration, and fisheries management of this foundational estuarine species.

Marine and Coastal Fisheries: Dynamics, Management↗

USGS2008

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models ( Smith and Heath, 2001 and Allen et al., 2004 ). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

Ecological Modelling↗

USGS2023

The Everglades vulnerability analysis: Linking ecological models to support ecosystem restoration

Understanding of the Everglades’ ecological vulnerabilities and restoration needs has advanced over the past decade but has not been applied in an integrated manner. To address this need, we developed the Everglades Vulnerability Analysis (EVA), a decision support tool that uses modular Bayesian networks to predict the ecological outcomes of a subset of the ecosystem’s health indicators. This tool takes advantage of the extensive modeling work already done in the Everglades and synthesizes information across indicators of ecosystem health to forecast long-term, landscape-scale changes. In addition, the tool can predict indicator vulnerability through comparison to user-defined ideal system states that can vary in the level of certainty of outcomes. An integrated understanding of the Everglades system is essential for evaluation of trade-offs at local, regional, and system-wide scales. Through EVA, Everglades restoration decision makers can provide effective guidance during restoration planning and implementation processes to mitigate unintended consequences that could result in further damage to the Everglades system.

Florida↗

USGS2012

Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis

Introduction Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations, and the resultant land and resource management in the twenty-first century. Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes. At present, simulations of climate change available from global climate models [GCMs] require downscaling for hydrologic or ecological applications. Methods Using statistically downscaled future climate projections developed using constructed analogues, a methodology was developed to further downscale the projections spatially using a gradient-inverse-distance-squared approach for application to hydrologic modeling at 270-m spatial resolution. Results This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes. Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change. Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated. Conclusions The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.

Ecological Processes↗

USGS2014

Considerations in representing human individuals in social ecological models

In this chapter we focus on how to integrate the human individual into social-ecological systems analysis, and how to improve research on individual thought and action regarding the environment by locating it within the broader social-ecological context. We discuss three key questions as considerations for future research: (1) is human thought conceptualized as a dynamic and adaptive process, (2) is the individual placed in a multi-level context (including within-person levels, person-group interactions, and institutional and structural factors), and (3) is human thought seen as mutually constructed with the social and natural environment. Increased emphasis on the individual will be essential if we are to understand agency, innovation, and adaptation in social-ecological systems.

Book chapter↗

USGS2017

Virginia flow-ecology modeling results—An initial assessment of flow reduction effects on aquatic biota

Background The U.S. Geological Survey (USGS), in cooperation with the Virginia Department of Environmental Quality (DEQ), reviewed a previously compiled set of linear regression models to assess their utility in defining the response of the aquatic biological community to streamflow depletion. As part of the 2012 Virginia Healthy Watersheds Initiative (HWI) study conducted by Tetra Tech, Inc., for the U.S. Environmental Protection Agency (EPA) and Virginia DEQ, a database with computed values of 72 hydrologic metrics, or indicators of hydrologic alteration (IHA), 37 fish metrics, and 64 benthic invertebrate metrics was compiled and quality assured. Hydrologic alteration was represented by simulation of streamflow record for a pre-water-withdrawal condition (baseline) without dams or developed land, compared to the simulated recent-flow condition (2008 withdrawal simulation) including dams and altered landscape to calculate a percent alteration of flow. Biological samples representing the existing populations represent a range of alteration in the biological community today. For this study, all 72 IHA metrics, which included more than 7,272 linear regression models, were considered. This extensive dataset provided the opportunity for hypothesis testing and prioritization of flow-ecology relations that have the potential to explain the effect(s) of hydrologic alteration on biological metrics in Virginia streams.

Virginia↗

USGS2013

Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.

Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km 2 region. We partitioned a Mahalanobis D 2 model of habitat use into k separate additive components each representing independent combinations of species–habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D 2 (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.

Ecology and Evolution↗

USGS2022

Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes

Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes), and institutional level (e.g., through science-policy interfaces across scales), represent promising approaches. To this end, we offer a generalized approach for linking modeling and decision-making.

Environmental Modelling & Software↗

USGS2006

Multimodeling: new approaches for linking ecological models

The Everglades region of South Florida presents one of the major natural system management challenges facing the United States. With its assortment of alligators, crocodiles, manatees, panthers, large mixed flocks of wading birds, highly diverse subtropical flora, and sea of sawgrass, the ecosystem is unique in this country (Davis and Ogden 1994). The region is also perhaps the largest human-controlled system on the planet in that the major environmental factor influencing the region is water, and water flows are managed on a daily basis--subject to the vagaries of rainfall--by a massive system of locks, pumps, canals, and levees constructed over the past century. The changes brought about by such control have led to extensive modifications of historical patterns and magnitudes of flow, causing large declines in many native species, extensive changes in nutrient cycling and vegetation across south Florida, and great increases in pollutants such as mercury. Constrained by the conflicting demands of agriculture, urban human populations, and wildlife for control of water resources, and the varying agendas of hosts of government agencies and nongovernmental organizations, there is now an ongoing effort to plan for major changes to the system with expenditure estimates of eight billion dollars or more over the next several decades (USACOE 1999). Carrying out such planning, particularly as it impacts the natural systems of the region, provides one of the major challenges to the new field of computational ecology.

Florida↗

USGS2011

Modelling ecological flow regime: an example from the Tennessee and Cumberland River basins

Predictive equations were developed for 19 ecologically relevant streamflow characteristics within five major groups of flow variables (magnitude, ratio, frequency, variability, and date) for use in the Tennessee and Cumberland River basins using stepbackward regression. Basin characteristics explain 50% or more of the variation for 12 of the 19 equations. Independent variables identified through stepbackward regression were statistically significant in 78 of 304 cases (α > 0.0001) and represent four major groups: climate, physical landscape features, regional indicators, and land use. Of these groups, the regional and climate variables were the most influential for determining hydrologic response. Daily temperature range, geologic factor, and rock depth were major factors explaining the variability in 17, 15, and 13 equations, respectively. The equations and independent datasets were used to explore the broad relation between basin properties and streamflow and the implication of streamflow to the study of ecological flow requirements. Key results include a high degree of hydrologic variability among least disturbed Blue Ridge streams, similar hydrologic behaviour for watersheds with widely varying degrees of forest cover, and distinct hydrologic profiles for streams in different geographic regions. Published in 2011. This article is a US Government work and is in the public domain in the USA.

Alabama;Georgia;Kentucky;Mississippi;North Carolin↗