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USGS2014

Users' guide to system dynamics model describing Coho salmon survival in Olema Creek, Point Reyes National Seashore, Marin County, California

The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a starting point, for other watersheds. This report describes each of the model elements with sufficient detail to guide the primary target audience, the NPS resource specialist, to run the model, interpret the results, change the input data to explore hypotheses, and ultimately modify and improve the model. Running the model and interpreting the results does not require modeling expertise on the part of the user. Additional companion publications will highlight other aspects of the model, such as its development, the rationale behind the methodological approach, scenario testing, and discussions of its use. System dynamics models consist of three basic elements: stocks , flows , and converters . Stocks are measurable quantities that can change over time, such as animal populations. Flows are any processes or conditions that change the quantity in a stock over time (Ford, 1999), are expressed in the model as a rate of change, and are diagrammed as arrows to or from stocks. Converters are processes or conditions that change the rate of flows. A converter is connected to a flow with an arrow indicating that it alters the rate of change. Anything that influences the rate of change (such as different environmental conditions, other external factors, or feedbacks from other stocks or flows) is modeled as a converter. For example, the number of fish in a population is appropriately modeled as a stock. Mortality is modeled as a flow because it is a rate of change over time used to determine the number of fish in the population. The density-dependent effect on mortality is modeled as a converter because it influences the rate of morality. Together, the flow and converter change the number, or stock, of juvenile coho. The instructions embedded in the stocks, flows, converters, and the sequence in which they are linked are processed by the simulation software with each completed sequence composing a model run. At each modeled time step within the model run, the stock counts will go up, down, or stay the same based on the modeled flows and the influence of converters on those flows. The model includes a user-friendly interface to change model parameters, which allows park staff and others to conduct sensitivity analyses, incorporate future knowledge, and implement scenarios for various future conditions. The model structure incorporates place holders for relationships that we hypothesize are significant but data are currently lacking. Future climate scenarios project stream temperatures higher than any that have ever been recorded at Olema Creek. Exploring climate change impacts on coho survival is a high priority for park staff, therefore the model provides the user with the option to experiment with hypothesized effects and to incorporate effects based on future observations.

California↗

USGS1990

Behavioral toxicology: Stimulating challenges for a growing discipline

Since the early 1970s, contaminants have been shown to affect virtually every aspect of behavior in terrestrial and aquatic organisms. Behavior inte- grates many cellular processes and is essential to the viability of the organism, the population and the community. Therefore, observations of behavior provide a unique toxicological perspective - one that links the biochemical and ecological conse- quences of environmental contamination.

Environmental Toxicology and Chemistry↗

USGS2021

The application of metacommunity theory to the management of riverine ecosystems

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

WIREs Water↗

USGS2014

Foraging and predation risk for larval cisco (Coregonus artedi) in Lake Superior: A modelling synthesis of empirical survey data

The relative importance of predation and food availability as contributors to larval cisco ( Coregonus artedi ) mortality in Lake Superior were investigated using a visual foraging model to evaluate potential predation pressure by rainbow smelt ( Osmerus mordax ) and a bioenergetic model to evaluate potential starvation risk. The models were informed by observations of rainbow smelt, larval cisco, and zooplankton abundance at three Lake Superior locations during the period of spring larval cisco emergence and surface-oriented foraging. Predation risk was highest at Black Bay, ON, where average rainbow smelt densities in the uppermost 10 m of the water column were >1000 ha −1 . Turbid conditions at the Twin Ports, WI-MN, affected larval cisco predation risk because rainbow smelt remained suspended in the upper water column during daylight, placing them alongside larval cisco during both day and night hours. Predation risk was low at Cornucopia, WI, owing to low smelt densities (<400 ha −1 ) and deep light penetration, which kept rainbow smelt near the lakebed and far from larvae during daylight. In situ zooplankton density estimates were low compared to the values used to develop the larval coregonid bioenergetics model, leading to predictions of negative growth rates for 10 mm larvae at all three locations. The model predicted that 15 mm larvae were capable of attaining positive growth at Cornucopia and the Twin Ports where low water temperatures (2–6 °C) decreased their metabolic costs. Larval prey resources were highest at Black Bay but warmer water temperatures there offset the benefit of increased prey availability. A sensitivity analysis performed on the rainbow smelt visual foraging model showed that it was relatively insensitive, while the coregonid bioenergetics model showed that the absolute growth rate predictions were highly sensitive to input parameters (i.e., 20% parameter perturbation led to order of magnitude differences in model estimates). Our modelling indicated that rainbow smelt predation may limit larval cisco survival at Black Bay and to a lesser extent at Twin Ports, and that starvation may be a major source of mortality at all three locations. The framework we describe has the potential to further our understanding of the relative importance of starvation and predation on larval fish survivorship, provided information on prey resources available to larvae are measured at sufficiently fine spatial scales and the models provide a realistic depiction of the dynamic processes that the larvae experience.

Lake Superior↗

USGS2025

RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning

Climate change is transforming ecosystems globally. The Resist-Accept-Direct (RAD) framework has gained traction within many natural resource management institutions to help consider the decision space in response to this transformation. Because RAD helps manage for directional change, RAD choices entail considering which RAD pathway to implement and for how long. For example, one may accept a slowly changing ecosystem, but at a certain point, decide to begin resisting or directing the change an ecosystem is experiencing. Alternatively, one may begin resisting an ecosystem transformation, but ultimately realize resistance is no longer feasible based on cost or efficacy. These choices are challenging and encompass broad domains of cultural, ecological, financial, organizational, public, regulatory, and technological considerations to determine when to switch RAD pathways. We introduce the concepts of RAD switch points and triggers to help support these decision processes. We illustrate these concepts using case studies on walleye ( Sander vitreus ) stocking decisions in Wisconsin, wildfire response in the Greater Yellowstone Ecosystem, and bull trout ( Salvelinus confluentus ) management in Oregon, USA. Synthesizing across these examples, we delineate key points for decision makers as they (iteratively) reevaluate among the RAD pathways as conditions continue to change.

Journal of Environmental Management↗

USGS2019

Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas

Sustainability has been at the forefront of the environmental research agenda of the integrated anthroposphere, hydrosphere, and biosphere since the last century and will continue to be critically important for future environmental science. However, linking humans and the environment through effective policy remains a major challenge for sustainability research and practice. Here we address this gap using an agent-based model (ABM) for a coupled natural and human systems in the Smoky Hill River Watershed (SHRW), Kansas, USA. For this freshwater-dependent agricultural watershed with a highly variable flow regime influenced by human-induced land-use and climate change, we tested the support for an environmental policy designed to conserve and protect fish biodiversity in the SHRW. We develop a proof of concept interdisciplinary ABM that integrates field data on hydrology, ecology (fish richness), social-psychology (value-belief-norm) and economics, to simulate human agents' decisions to support environmental policy. The mechanism to link human behaviors to environmental changes is the social-psychological sequence identified by the value-belief-norm framework and is informed by hydrological and fish ecology models. Our results indicate that (1) cultural factors influence the decision to support the policy; (2) a mechanism modifying social-psychological factors can influence the decision-making process; (3) there is resistance to environmental policy in the SHRW, even under potentially extreme climate conditions; and (4) the best opportunities for policy acceptance were found immediately after extreme environmental events. The modeling approach presented herein explicitly links biophysical and social science has broad generality for sustainability problems.

Kansas↗

USGS2013

Assessment of macroinvertebrate communities in adjacent urban stream basins, Kansas City, Missouri, metropolitan area, 2007 through 2011

Macroinvertebrates were collected as part of two separate urban water-quality studies from adjacent basins, the Blue River Basin (Kansas City, Missouri), the Little Blue River and Rock Creek Basins (Independence, Missouri), and their tributaries. Consistent collection and processing procedures between the studies allowed for statistical comparisons. Seven Blue River Basin sites, nine Little Blue River Basin sites, including Rock Creek, and two rural sites representative of Missouri ecological drainage units and the area’s ecoregions were used in the analysis. Different factors or levels of urban intensity may affect the basins and macroinvertebrate community metrics differently, even though both basins are substantially developed above their downstream streamgages (Blue River, 65 percent; Little Blue River, 52 percent). The Blue River has no flood control reservoirs and receives wastewater effluent and stormflow from a combined sewer system. The Little Blue River has flood control reservoirs, receives no wastewater effluent, and has a separate stormwater sewer system. Analysis of macroinvertebrate community structure with pollution-tolerance metrics and water-quality parameters indicated differences between the Blue River Basin and the Little Blue River Basin. A four-metric score (total taxa richness, Ephemeroptera plus Plecoptera plus Trichoptera taxa richness, Macroinvertebrate Biotic Index, and Shannon Diversity Index) for richest-targeted habitat was used to calculate a Stream Condition Index (SCI) in order to evaluate the aquatic-life status of the streams. About 80 percent of all samples combined were determined to be less than fully biologically supporting, and about 11 percent of spring samples were fully biologically supporting. No sites within the Blue River Basin had a fully supporting score. The aquatic-life status scores for the Little Blue River and its tributaries were higher (indicating more optimal conditions) than for the Blue River and its tributaries. Fall samples scored higher than spring samples. However, fall samples were collected at the Little Blue River Basin and rural sites only. The Little Blue River sites scored higher for fall samples than spring samples; about 39 percent fully biologically supporting and 61 percent partially biologically supporting; more similar to the rural comparison sites, 40 percent fully biologically supporting and 60 percent partially biologically supporting. The SCI was compared to other multimetric indices with more or other component metrics to determine if the SCI effectively described differences among sites. Environmental variables (streamflow, water quality, land use, impervious cover, and population density) were used in statistical analyses to evaluate relations to macroinvertebrate metrics. Multimetric indices (MMIs) were modeled using step regression with a simple urban intensity index (SUII) based on percentage of impervious cover, population density, and forest cover in a 30-meter stream-buffer zone, and two were selected for further analysis. Three other multimetric indices composed of metrics common to local and national studies show results similar to the two modeled MMIs. A common Benthic Index of Biotic Integrity (R 2 equals 0.71) developed for a national study had the highest correlation with urban intensity as measured with the SUII, followed by a modeled 6-metric index (R 2 equals 0.61). The other MMIs and the SCI explained less than a half of the variability in macroinvertebrate communities in relation to the SUII. Wastewater-treatment plant discharges during base flow, which elevated specific conductance and nutrient concentrations, combined sewer overflows, and nonpoint sources likely contributed to water-quality impairment and lower aquatic-life status at the Blue River Basin sites. Releases from upstream reservoirs to the Little Blue River likely decreased specific conductance, suspended-sediment, and dissolved constituent concentrations and may have benefitted water quality and aquatic life of main-stem sites. Chloride concentrations in base-flow samples, attributable to winter road salt application, had the highest correlation with the SUII (Spearman’s ρ equals 0.87), were negatively correlated with the SCI (Spearman’s ρ equals -0.53) and several pollution sensitive Ephemeroptera plus Plecoptera plus Trichoptera abundance and percent richness metrics, and were positively correlated with pollution tolerant Oligochaeta abundance and percent richness metrics. Study results show that the easily calculated SUII and the selected modeled multimetric indices are effective for comparing urban basins and for evaluation of water quality in the Kansas City metropolitan area.

Missouri↗

USGS2021

Extreme events trigger terrestrial and marine ecosystem collapses: A tale of two regions

We outline the multiple, cross-scale, and complex consequences of terrestrial and marine ecosystem heatwaves in two regions on opposite sides of the planet: the southwestern USA and southwestern Australia, both encompassing Global Biodiversity Hotspots, and where ecosystem collapses or features of it have occurred in the past two decades. We highlight ecosystem shifts that have clearly demonstrated a substantial change from a baseline state over time, although not necessarily across their entire distribution, with evidence of collapse at local scales. Responses to temperature extremes, such as heatwaves, encompass processes at all scales, including population level (e.g. altered demography such as survival, recruitment, and fecundity, together resulting in structural changes), community level (e.g. species compositional shifts), and ecosystem level (e.g. carbon loss), as well as physical properties altered by vegetation loss (e.g. microclimate, fire behaviour on land). These changes impact all trophic levels with foundational species losses (such as seagrasses, kelp, and trees), flowing through to vertebrates (such as sea turtles, penguins, and cockatoos). Where extensive collapse has occurred, shifts in microclimate could affect important biosphere-to-atmosphere feedbacks including fluxes of energy, carbon, and water. Such extensive changes usually do not occur in isolation and frequently interact with other disturbance processes such as fire, storms, pathogen and pest outbreaks, and anthropogenic stressors. Interactions may alter the likelihood, extent, or severity of subsequent disturbances (linked disturbances) as well as condition the ecological response and recovery (compound disturbances). In addition, if ecosystem collapse is extensive enough (e.g. tree die-off), those changes also can impact climate and ecosystems elsewhere via ecoclimate teleconnections. Increasing rates of climatic extremes will drive a host of direct and indirect feedbacks certain to produce large-scale shifts in ecological functioning at unprecedented rates. Understanding how, why, and where these shifts will occur will be critical for effective ecosystem management and climate change mitigation.

Book chapter↗

USGS2008

Delayed genetic effects of habitat fragmentation on the ecologically specialized Florida sand skink ( Plestiodon reynoldsi )

Populations rarely show immediate genetic responses to habitat fragmentation, even in taxa that possess suites of traits known to increase their vulnerability to extinction. Thus conservation geneticists must consider the time scale over which contemporary evolutionary processes operate to accurately portray the effects of habitat isolation. Here, we examine the genetic impacts of fragmentation on the Florida sand skink Plestiodon reynoldsi , a sand swimming lizard that is highly adapted to the upland scrub habitat of central Florida. We studied fragments located on the southern Lake Wales Ridge, where human activity in the latter half of the 20th century has modified the natural patchiness of the landscape. Based on a relaxed molecular clock method, we estimate that sand skinks have persisted in this region for approximately 1.5 million years and that the time frame of human disturbance is equivalent to fewer than 30 skink generations. Using genotypes from eight microsatellite loci, we screened for molecular signatures of this disturbance by assessing congruence between population structure, as inferred from spatially-informed Bayesian assignment tests, and the current geography of scrub fragments. We also tested for potential intrapopulation genetic effects of inbreeding in isolated populations by comparing the average pairwise relatedness of individuals within fragments of different areas and isolation. Our results indicate that although some patches show a higher degree of relatedness than expected under random mating, the genetic effects of recent isolation are not evident in this part of the species’ range. We argue that this result is an artefact of a time-lag in the response to disturbance, and that species-typical demographic features may explain the genetic inertia observed in these populations.

Conservation Genetics↗

USGS2022

Floodplain ecology: A novel wetland community of the Amazon

An expedition to the upper estuarine reaches of the Amazon River reveals intriguing overlap of tropical mangrove wetlands with riverine floodplain forests. This newly discovered type of forested wetland assemblage may provide a uniquely process-rich carbon hotspot.

Amazon River↗

USGS2015

Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders

Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29) . Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions and objectives prior to sampling data and fitting models.

PLoS ONE↗

USGS2020

A latent process model approach to improve the utility of indicator species

The state of an ecosystem is governed by dynamic biotic and abiotic processes, which can only be partially observed. Costs associated with measuring each component limit the feasibility of comprehensive assessments of target ecosystems. Instead, indicator species are recommended as a surrogate index. While this is an attractive concept, indicator species have rarely proven to be an effective tool for monitoring ecosystems and informing management decisions. One deficiency in the existing theoretical development of indicator species may be overcome with the incorporation of latent (i.e. unobservable) states. Advancements in quantitative ecological models allow for latent‐state models to be tested empirically, facilitating the robust evaluation and practical use of indicator species for ecosystem science and management. Here, we extend the existing conceptual models of indicator species to include a direct relationship between an indicator species, ecosystem change drivers and latent processes and variables. Our approach includes explicit consideration of important estimation uncertainty and narrows the range of values a latent variable may take by relating it to measurable attribute(s) of an indicator species. We demonstrate the utility of this approach by relating a commonly cited indicator species, the red‐backed salamander Plethodon cinereus , to a typical latent process of interest – ecosystem health.

Oikos↗

USGS2012

Building the United States National Vegetation Classification

The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.

Annali di Botanica - Coenology and Plant Ecology↗

USGS2015

Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

Decision analytic approaches have been widely recommended as well suited to solving disputed and ecologically complex natural resource management problems with multiple objectives and high uncertainty. However, the difference between theory and practice is substantial, as there are very few actual resource management programs that represent formal applications of decision analysis. We applied the process of structured decision making to Atlantic horseshoe crab harvest decisions in the Delaware Bay region to develop a multispecies adaptive management (AM) plan, which is currently being implemented. Horseshoe crab harvest has been a controversial management issue since the late 1990s. A largely unregulated horseshoe crab harvest caused a decline in crab spawning abundance. That decline coincided with a major decline in migratory shorebird populations that consume horseshoe crab eggs on the sandy beaches of Delaware Bay during spring migration. Our approach incorporated multiple stakeholders, including fishery and shorebird conservation advocates, to account for diverse management objectives and varied opinions on ecosystem function. Through consensus building, we devised an objective statement and quantitative objective function to evaluate alternative crab harvest policies. We developed a set of competing ecological models accounting for the leading hypotheses on the interaction between shorebirds and horseshoe crabs. The models were initially weighted based on stakeholder confidence in these hypotheses, but weights will be adjusted based on monitoring and Bayesian model weight updating. These models were used together to predict the effects of management actions on the crab and shorebird populations. Finally, we used a dynamic optimization routine to identify the state dependent optimal harvest policy for horseshoe crabs, given the possible actions, the stated objectives and our competing hypotheses about system function. The AM plan was reviewed, accepted and implemented by the Atlantic States Marine Fisheries Commission in 2012 and 2013. While disagreements among stakeholders persist, structured decision making enabled unprecedented progress towards a transparent and consensus driven management plan for crabs and shorebirds in Delaware Bay.

Biological Conservation↗

USGS2015

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

Conservation Biology↗

USGS2007

Toward a transport-based analysis of nutrient spiraling and uptake in streams

Nutrient addition experiments are designed to study the cycling of nutrients in stream ecosystems where hydrologic and nonhydrologic processes determine nutrient fate. Because of the importance of hydrologic processes in stream ecosystems, a conceptual model known as nutrient spiraling is frequently employed. A central part of the nutrient spiraling approach is the determination of uptake length ( S w ), the average distance traveled by dissolved nutrients in the water column before uptake. Although the nutrient spiraling concept has been an invaluable tool in stream ecology, the current practice of estimating uptake length from steady‐state nutrient data using linear regression (called here the “ S w approach”) presents a number of limitations. These limitations are identified by comparing the exponential S w equation with analytical solutions of a stream solute transport model. This comparison indicates that (1) S w is an aggregate measure of uptake that does not distinguish between main channel and storage zone processes, (2) S w is an integrated measure of numerous hydrologic and nonhydrologic processes—this process integration may lead to difficulties in interpretation when comparing estimates of S w , and (3) estimates of uptake velocity and areal uptake rate ( v f and U ) based on S w are not independent of system hydrology. Given these findings, a transport‐based approach to nutrient spiraling is presented for steady‐state and time‐series data sets. The transport‐based approach for time‐series data sets is suggested for future research on nutrient uptake as it provides a number of benefits, including the ability to (1) separately quantify main channel and storage zone uptake, (2) quantify specific hydrologic and nonhydrologic processes using various model parameters (process separation), (3) estimate uptake velocities and areal uptake rates that are independent of hydrologic effects, and (4) use shortterm, non‐plateau nutrient additions such that the effects of regeneration and mineralization are minimized. In summary, the transport‐based, time‐series approach provides a means of estimating traditional measures of nutrient uptake ( S w , v f , U ) while providing additional information on the location and magnitude of uptake (main channel versus storage zone). Application of the transport‐based approach to time‐series data from Green Creek, Antarctica, indicates that the bulk of nitrate uptake (~74% to 100%) occurred within the main channel where benthic uptake by algal mats is a likely process. Substantial uptake (~26%) also occurred in the storage zone of one reach, where uptake is attributed to the microbial community.

Limnology and Oceanography: Methods↗

USGS2009

Ecosystem effects of environmental flows: Modelling and experimental floods in a dryland river

Successful environmental flow prescriptions require an accurate understanding of the linkages among flow events, geomorphic processes and biotic responses. We describe models and results from experimental flow releases associated with an environmental flow program on the Bill Williams River (BWR), Arizona, in arid to semiarid western U.S.A. Two general approaches for improving knowledge and predictions of ecological responses to environmental flows are: (1) coupling physical system models to ecological responses and (2) clarifying empirical relationships between flow and ecological responses through implementation and monitoring of experimental flow releases. We modelled the BWR physical system using: (1) a reservoir operations model to simulate reservoir releases and reservoir water levels and estimate flow through the river system under a range of scenarios, (2) one- and two-dimensional river hydraulics models to estimate stage-discharge relationships at the whole-river and local scales, respectively, and (3) a groundwater model to estimate surface- and groundwater interactions in a large, alluvial valley on the BWR where surface flow is frequently absent. An example of a coupled, hydrology-ecology model is the Ecosystems Function Model, which we used to link a one-dimensional hydraulic model with riparian tree seedling establishment requirements to produce spatially explicit predictions of seedling recruitment locations in a Geographic Information System. We also quantified the effects of small experimental floods on the differential mortality of native and exotic riparian trees, on beaver dam integrity and distribution, and on the dynamics of differentially flow-adapted benthic macroinvertebrate groups. Results of model applications and experimental flow releases are contributing to adaptive flow management on the BWR and to the development of regional environmental flow standards. General themes that emerged from our work include the importance of response thresholds, which are commonly driven by geomorphic thresholds or mediated by geomorphic processes, and the importance of spatial and temporal variation in the effects of flows on ecosystems, which can result from factors such as longitudinal complexity and ecohydrological feedbacks. ?? Published 2009.

Freshwater Biology↗

USGS2015

Role of ground ice dynamics and ecological feedbacks in recent ice wedge degradation and stabilization

Ground ice is abundant in the upper permafrost throughout the Arctic and fundamentally affects terrain responses to climate warming. Ice wedges, which form near the surface and are the dominant type of massive ice in the Arctic, are particularly vulnerable to warming. Yet processes controlling ice wedge degradation and stabilization are poorly understood. Here we quantified ice wedge volume and degradation rates, compared ground ice characteristics and thermal regimes across a sequence of five degradation and stabilization stages and evaluated biophysical feedbacks controlling permafrost stability near Prudhoe Bay, Alaska. Mean ice wedge volume in the top 3 m of permafrost was 21%. Imagery from 1949 to 2012 showed thermokarst extent (area of water-filled troughs) was relatively small from 1949 (0.9%) to 1988 (1.5%), abruptly increased by 2004 (6.3%) and increased slightly by 2012 (7.5%). Mean annual surface temperatures varied by 4.9°C among degradation and stabilization stages and by 9.9°C from polygon center to deep lake bottom. Mean thicknesses of the active layer, ice-poor transient layer, ice-rich intermediate layer, thermokarst cave ice, and wedge ice varied substantially among stages. In early stages, thaw settlement caused water to impound in thermokarst troughs, creating positive feedbacks that increased net radiation, soil heat flux, and soil temperatures. Plant growth and organic matter accumulation in the degraded troughs provided negative feedbacks that allowed ground ice to aggrade and heave the surface, thus reducing surface water depth and soil temperatures in later stages. The ground ice dynamics and ecological feedbacks greatly complicate efforts to assess permafrost responses to climate change.

Journal of Geophysical Research F: Earth Surface↗