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USGS2000

Characteristic length scale of input data in distributed models: implications for modeling grain size

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m 2 modeling grid size. A modeling grid size of about 10×10 m 2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.

Idaho↗

USGS2001

Aeolian dust in Colorado Plateau soils: Nutrient inputs and recent change in source

Aeolian dust (windblown silt and clay) is an important component in arid-land ecosystems because it may contribute to soil formation and furnish essential nutrients. Few geologic surfaces, however, have been characterized with respect to dust-accumulation history and resultant nutrient enrichment. We have developed a combination of methods to identify the presence of aeolian dust in arid regions and to evaluate the roles of this dust in ecosystem processes. Unconsolidated sandy sediment on isolated surfaces in the Canyonlands region of the Colorado Plateau differs greatly in mineralogical and chemical composition from associated bedrock, mainly aeolian sandstone. Detrital magnetite in the surficial deposits produces moderately high values of magnetic susceptibility, but magnetite is absent in nearby bedrock. A component of the surficial deposits must be aeolian to account for the abundance of magnetite, which formed originally in far-distant igneous rocks. Particle-size analysis suggests that the aeolian dust component is typically as much as 20–30%. Dust inputs have enriched the sediments in many elements, including P, Mg, Na, K, and Mo, as well as Ca, at sites where bedrock lacks calcite cement. Soil-surface biologic crusts are effective dust traps that apparently record a change in dust sources over the past several decades. Some of the recently fallen dust may result from human disturbance of land surfaces that are far from the Canyonlands, such as the Mojave Desert. Some land-use practices in the study area have the potential to deplete soil fertility by means of wind-erosion removal of aeolian silt. Many studies have addressed the presence of aeolian dust in soils and surficial deposits in deserts to provide important geologic and ecologic information bearing on landscape dynamics (1–16). From this body of work, we have improved understanding about: ( i ) current and past sources and flux of dust, hence changing conditions of dust emission; ( ii ) the genesis of desert soils; ( iii ) the influences of aeolian silt and clay on water-infiltration rates in soil; ( iv ) the evolution of desert surfaces (such as desert pavement) relevant to surface stability, as well as the distribution of surface and subsurface water; and ( v ) interrelations among aeolian dust, distribution of plants and soil crust, rain-water runoff, and productivity. Nevertheless, we lack fundamental knowledge about the accumulation history of aeolian dust on most landscapes and about how to discriminate between contributions from parent material and aeolian dust to the biotic system. Although many different methods provide clear evidence for aeolian input into soils (4, 6, 8, 9, 11, 13, 17, 18), ecosystem studies would benefit from rapid assessment of aeolian components in soils. Here we demonstrate that magnetic methods, which characterize the type and distribution of iron oxide minerals, can be applied to detect the presence of aeolian dust in young surficial sediments and soils over large arid-land areas. The magnetic results, combined with geochemical and textural analyses, form a basis for understanding the influence of fine-grained aeolian inputs on soil fertility of the central Colorado Plateau, Utah.

Utah↗

USGS2010

Water vapour correction of the daily 1 km AVHRR global land dataset: Part I validation and use of the Water Vapour input field

An atmospheric correction algorithm developed for the 1 km Advanced Very High Resolution Radiometer (AVHRR) global land dataset was modified to include a near real-time total column water vapour data input field to account for the natural variability of atmospheric water vapour. The real-time data input field used for this study is the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A global total column water vapour dataset. It was validated prior to its use in the AVHRR atmospheric correction process using two North American AVHRR scenes, namely 13 June and 28 November 1996. The validation results are consistent with those reported by others and entail a comparison between TOVS, radiosonde, experimental sounding, microwave radiometer, and data from a hand-held sunphotometer. The use of this data layer as input to the AVHRR atmospheric correction process is discussed.

International Journal of Remote Sensing↗

USGS2018

Pulsed flows, tributary inputs, and food web structure in a highly regulated river

1.Dams disrupt the river continuum, altering hydrology, biodiversity, and energy flow. Although research indicates that tributary inputs have the potential to dilute these effects, knowledge at the food web level is still scarce. 2.Here we examined the riverine food web structure of the Colorado River below Glen Canyon Dam, focusing on organic matter sources, trophic diversity, and food chain length. We asked how these components respond to pulsed flows from tributaries following monsoon thunderstorms that seasonally increase streamflow in the American Southwest. 3.Tributaries increased the relative importance of terrestrial organic matter, particularly during the wet season below junctures of key tributaries. This contrasted with the algal-based food web present immediately below Glen Canyon Dam. 4.Tributary inputs during the monsoon also increased trophic diversity and food chain length: food chain length peaked below the confluence with the largest tributary (by discharge) in Grand Canyon, increasing by >1 trophic level over a 4-5 kilometre reach possibly due to aquatic prey being flushed into the mainstem during heavy rain events. 5.Our results illustrate that large tributaries can create seasonal discontinuities, influencing riverine food web structure in terms of allochthony, food web diversity, and food chain length. 6.Synthesis and applications. Pulsed flows from unregulated tributaries following seasonal monsoon rains increase the importance of terrestrially-derived organic matter in large, regulated river food webs, increasing food chain length and trophic diversity downstream of tributary inputs. Protecting unregulated tributaries within hydropower cascades may be important if we are to mitigate food web structure alteration due to flow regulation by large dams. This is critical in the light of global hydropower development, especially in megadiverse, developing countries where dam placement (including completed and planned structures) is in tributaries.

Colorado River↗

USGS2011

Nutrient inputs to the Laurentian Great Lakes by source and watershed estimated using SPARROW watershed models

Nutrient input to the Laurentian Great Lakes continues to cause problems with eutrophication. To reduce the extent and severity of these problems, target nutrient loads were established and Total Maximum Daily Loads are being developed for many tributaries. Without detailed loading information it is difficult to determine if the targets are being met and how to prioritize rehabilitation efforts. To help address these issues, SPAtially Referenced Regressions On Watershed attributes (SPARROW) models were developed for estimating loads and sources of phosphorus (P) and nitrogen (N) from the United States (U.S.) portion of the Great Lakes, Upper Mississippi, Ohio, and Red River Basins. Results indicated that recent U.S. loadings to Lakes Michigan and Ontario are similar to those in the 1980s, whereas loadings to Lakes Superior, Huron, and Erie decreased. Highest loads were from tributaries with the largest watersheds, whereas highest yields were from areas with intense agriculture and large point sources of nutrients. Tributaries were ranked based on their relative loads and yields to each lake. Input from agricultural areas was a significant source of nutrients, contributing ∼33-44% of the P and ∼33-58% of the N, except for areas around Superior with little agriculture. Point sources were also significant, contributing ∼14-44% of the P and 13-34% of the N. Watersheds around Lake Erie contributed nutrients at the highest rate (similar to intensively farmed areas in the Midwest) because they have the largest nutrient inputs and highest delivery ratio.

Laurentian Great Lakes↗

USGS2001

Digital data used to relate nutrient input to water quality in the Chesapeake Bay watershed

Digital data sets compiled by the U.S. Geological Survey were used as input for a collection of Spatially Referenced Regressions On Watershed (SPARROW) attributes for the Chesapeake Bay region including parts of Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia, and the District of Columbia. These regressions use a nonlinear statistical approach to relate nutrient sources and land-surface characteristics to nutrient loads of streams throughout the Chesapeake Bay watershed. A digital segmented-watershed network serves as the primary framework for spatially referencing nutrient-source and land-surface characteristic data within a geographic information system. Flow direction and flow accumulation generated from a 30-meter cell-size Digital Elevation Model and attributes from 1:500,000-scale stream data were used to generate stream and watershed networks. Spatial data sets representing nutrient inputs of total nitrogen and total phosphorus from the early 1990's were created and compiled from numerous sources. Data include atmospheric deposition, septic systems, point-source locations, land use, land cover, and agricultural sources such as commercial fertilizer and manure. Some land-surface characteristic data sets representing factors that affect the transport of nutrients also were compiled. Data sets include land use, land cover, average-annual precipitation and temperature, slope, hydrogeomorphic regions, and soil permeability. Nutrient-input and land-surface characteristic data sets merged with the segmented-watershed network provide the spatial detail by watershed segment required by SPARROW. Stream-nutrient load estimates for 132 sampling sites representing the early 1990's (103 for total nitrogen and 121 for total phosphorus) serve as the dependent variables for the regressions. These estimates were used to calibrate models of total nitrogen and total phosphorus depicting 1992 land-surface conditions. Examples of model predictions consist of stream-nutrient load and source percentages contributed locally to each stream reach, as well as percentages of the load that reach Chesapeake Bay.

Open-File Report↗

USGS2017

The use of passive membrane samplers to assess organic contaminant inputs at five coastal sites in west Maui, Hawaii

Five passive membrane samplers were deployed for 28 continuous days at select sites along and near the west Maui coastline to assess organic compounds and contaminant inputs to diverse, shallow coral reef ecosystems. Daily and weekly fluctuations in such inputs were captured on the membranes using integrative sampling. The distribution of organic compounds observed at these five coastal sites showed considerable variation; with high concentrations of terrestrially sourced organic compounds such as C29 sterols and high molecular weight n -alkanes at the strongly groundwater-influenced Kahekili vent site. In comparison, the coastal sites were presumably influenced more by seasonal surface and stream water runoff and therefore had marine-sourced organic compounds and fewer pharmaceuticals and personal care products. The direct correlation to upstream land-use practices was not obvious and may require additional wet-season sampling. Pharmaceuticals and personal care products as well as flame retardants were detected at all sites, and the Kahekili vent site had the highest number of detections. Planned future work must also determine the organic compound and contaminant concentrations adsorbed onto water column particulate matter, because it may also be an important vector for contaminant transport to coral reef ecosystems. The impact of contaminants per individual (such as fecundity and metabolism) as well as per community (such as species abundance and diversity) is necessary for an accurate assessment of environmental stress. Results presented herein provide current contaminant inputs to select nearshore environments along the west Maui coastline captured during the dry season, and they can be useful to aid potential future evaluations and (or) comparisons.

Hawaii↗

USGS1999

Digital data used to relate nutrient inputs to water quality in the Chesapeake Bay watershed

Digital data sets were compiled by the U. S. Geological Survey (USGS) and used as input for a collection of Spatially Referenced Regressions On Watershed attributes for the Chesapeake Bay region. These regressions relate streamwater loads to nutrient sources and the factors that affect the transport of these nutrients throughout the watershed. A digital segmented network based on watershed boundaries serves as the primary foundation for spatially referencing total nitrogen and total phosphorus source and land-surface characteristic data sets within a Geographic Information System. Digital data sets of atmospheric wet deposition of nitrate, point-source discharge locations, land cover, and agricultural sources such as fertilizer and manure were created and compiled from numerous sources and represent nitrogen and phosphorus inputs. Some land-surface characteristics representing factors that affect the transport of nutrients include land use, land cover, average annual precipitation and temperature, slope, and soil permeability. Nutrient input and land-surface characteristic data sets merged with the segmented watershed network provide the spatial detail by watershed segment required by the models. Nutrient stream loads were estimated for total nitrogen, total phosphorus, nitrate/nitrite, amonium, phosphate, and total suspended soilds at as many as 109 sites within the Chesapeake Bay watershed. The total nitrogen and total phosphorus load estimates are the dependent variables for the regressions and were used for model calibration. Other nutrient-load estimates may be used for calibration in future applications of the models.

Open-File Report↗

USGS2016

Monitoring plant tissue nitrogen isotopes to assess nearshore inputs of nitrogen to Lake Crescent, Olympic National Park, Washington

Mats of filamentous-periphytic algae present in some nearshore areas of Lake Crescent, Olympic National Park, Washington, may indicate early stages of eutrophication from nutrient enrichment of an otherwise highly oligotrophic lake. Natural abundance ratios of stable isotopes of nitrogen (δ 15 N) measured in plant tissue growing in nearshore areas of the lake indicate that the major source of nitrogen used by these primary producing plants is derived mainly from atmospherically fixed nitrogen in an undeveloped forested ecosystem. Exceptions to this pattern occurred in the Barnes Point area where elevated δ 15 N ratios indicate that effluent from septic systems also contribute nitrogen to filamentous-periphytic algae growing in the littoral zone of that area. Near the Lyre River outlet of Lake Crescent, the δ 15 N of filamentous-periphytic algae growing in close proximity to the spawning areas of a unique species of trout show little evidence of elevated δ 15 N indicating that nitrogen from on-site septic systems is not a substantial source of nitrogen for these plants. The δ 15 N data corroborate estimates that nitrogen input to Lake Crescent from septic sources is comparatively small relative to input from motor vehicle exhaust and vegetative sources in undeveloped forests, including litterfall, pollen, and symbiotic nitrogen fixation. The seasonal timing of blooms of filamentous-periphytic algal near the lake shoreline is also consistent with nitrogen exported from stands of red alder trees ( Alnus rubra ). Isotope biomonitoring of filamentous-periphytic algae may be an effective approach to monitoring the littoral zone for nutrient input to Lake Crescent from septic sources.

Washington↗

USGS2019

Joint system-input identification of bridge structures

This paper presents a novel framework for system identification of bridge structures using recorded earthquake data. Bridge structures are prone to spatial variability of ground motions because they extend over relatively long distances. So, input motion measurement is a challenging task, especially for long bridges with multiple piers. Moreover, direct measurement of the bridge Foundation Input Motions (FIMs) may not be possible due to both inertial and kinematic Soil-Structure Interaction (SSI) effects. In this study, we propose a joint system-input identification solution using sparsely measured earthquake-induced responses. We verify this method and its applicability for real scale problems using simulated data obtained from the Golden Gate Bridge.

California↗

USGS2012

Impacts of climate change on biodiversity, ecosystems, and ecosystem services: technical input to the 2013 National Climate Assessment

Ecosystems, and the biodiversity and services they support, are intrinsically dependent on climate. During the twentieth century, climate change has had documented impacts on ecological systems, and impacts are expected to increase as climate change continues and perhaps even accelerates. This technical input to the National Climate Assessment synthesizes our scientific understanding of the way climate change is affecting biodiversity, ecosystems, ecosystem services, and what strategies might be employed to decrease current and future risks. Building on past assessments of how climate change and other stressors are affecting ecosystems in the United States and around the world, we approach the subject from several different perspectives. First, we review the observed and projected impacts on biodiversity, with a focus on genes, species, and assemblages of species. Next, we examine how climate change is affecting ecosystem structural elements—such as biomass, architecture, and heterogeneity—and functions—specifically, as related to the fluxes of energy and matter. People experience climate change impacts on biodiversity and ecosystems as changes in ecosystem services; people depend on ecosystems for resources that are harvested, their role in regulating the movement of materials and disturbances, and their recreational, cultural, and aesthetic value. Thus, we review newly emerging research to determine how human activities and a changing climate are likely to alter the delivery of these ecosystem services. This technical input also examines two cross-cutting topics. First, we recognize that climate change is happening against the backdrop of a wide range of other environmental and anthropogenic stressors, many of which have caused dramatic ecosystem degradation already. This broader range of stressors interacts with climate change, and complicates our abilities to predict and manage the impacts on biodiversity, ecosystems, and the services they support. The second cross-cutting topic is the rapidly advancing field of climate adaptation, where there has been significant progress in developing the conceptual framework, planning approaches, and strategies for safeguarding biodiversity and other ecological resources. At the same time, ecosystem-based adaptation is becoming more prominent as a way to utilize ecosystem services to help human systems adapt to climate change. In this summary, we present key findings of the technical input, focusing on themes that can be found throughout the report. Thus, this summary takes a more integrated look at the question of how climate change is affecting our ecological resources, the implications for humans, and possible response strategies. This integrated approach better reflects the impacts of climate in the real world, where changes in ecosystem structure or function will alter the viability of different species and the efficacy of ecosystem services. Likewise, adaptation to climate change will simultaneously address a range of conservation goals. Case studies are used to illustrate this complete picture throughout the report; a snapshot of one case study, 2011 Las Conchas, New Mexico Fire , is included in this summary.

Report↗

USGS2023

Assessing snowpack stratigraphy accuracy based on different input data: Insights for operations avalanche forecasting

Avalanche forecasters and snow scientists use physically based snow stratigraphy models to fill spatial and temporal gaps in field-based snow profile observations. These models generate stratigraphy predictions using meteorological input from automated weather stations (AWS) or numerical weather prediction (NWP) models. The choice of input data is often determined by data availability or convenience instead of giving full consideration to the most appropriate source for a particular application. For example, while AWS may provide weather observations that better represent a particular site, they have large up-front costs and require specialized personnel to service and maintain. The goal of this study is to quantify the accuracy of snow stratigraphy produced by the SNOWPACK model driven by different input data, with a particular focus on cost-benefit analysis for operational avalanche forecasting. We generate modeled snow profiles at a field site in the Bridger Range of southwestern Montana, USA, using a) observations from an AWS at the field site and b) NWP output from the NOAA High-Resolution Rapid Refresh (HRRR) model. Validation data consist of a season-long time series of 10 manual snow profiles. We use dynamic time-warping (DTW) to quantify the overall and grain-type categorized similarities between modeled and in-situ observed profiles that are collocated in time and in space. Based on the similarity results, we present a cost-benefit analysis that considers the cost of installing and maintaining an AWS alongside the improved representation of snow depth, grain size, and weak layer types.

Montana↗

USGS2023

Comparing snowpack meteorological inputs to support regional wet snow avalanche forecasting

Wet snow avalanches are predicted to increase in frequency with climate change and are often difficult to forecast. Improving our understanding of wet snow avalanche timing will help with current forecasting challenges. The onset of wet snow avalanching is closely tied to the temporal progression of liquid water flow through the seasonal snowpack. Measuring the flow of water through the snowpack in-situ is difficult due to the spatial variability of snow depth and structure. However, physical snowpack models can potentially simulate this process. The accuracy of snowpack models is heavily dependent upon the quality of the meteorological input data. A thorough investigation of model output differences using several different meteorological inputs for forecasting water movement and wet snow avalanches has not yet been thoroughly investigated. Here, we evaluate indicators of regional wet snow avalanches produced by the SNOWPACK model using different meteorological input. We compare the accuracy of SNOWPACK modeled outputs driven by two different numerical weather prediction (NWP) forecast models: the High-Resolution Deterministic Prediction System (HRDPS) and the North American Model (NAMnest). We leverage hourly automated weather station data, daily operational avalanche observations along the Going-to-the-Sun Road in Glacier National Park, Montana, United States, and in-situ snow stratigraphy and wetness profile observations to validate the SNOWPACK modeled outputs. This research is directly applicable to avalanche forecasting operations and future avalanche research as wet snow avalanche timing evolves due to climate change.

Montana↗

USGS2009

Compositional changes in sediments of subalpine lakes, Uinta Mountains (Utah): Evidence for the effects of human activity on atmospheric dust inputs

Sediments in Marshall and Hidden Lakes in the Uinta Mountains of northeastern Utah contain records of atmospheric mineral-dust deposition as revealed by differences in mineralogy and geochemistry of lake sediments relative to Precambrian clastic rocks in the watersheds. In cores spanning more than a thousand years, the largest changes in composition occurred within the past approximately 140 years. Many elements associated with ore deposits (Ag, As, Bi, Cd, Cu, In, Mo, Pb, S, Sb, Sn, and Te) increase in the lake sediments above depths that correspond to about AD 1870. Sources of these metals from mining districts to the west of the Uinta Mountains are suggested by (1) the absence of mining and smelting of these metals in the Uinta Mountains, and (2) lower concentrations of most of these elements in post-settlement sediments of Hidden Lake than in those of Marshall Lake, which is closer to areas of mining and the densely urbanized part of north-central Utah that is termed the Wasatch Front, and (3) correspondence of Pb isotopic compositions in the sediments with isotopic composition of ores likely to have been smelted in the Wasatch Front. A major source of Cu in lake sediments may have been the Bingham Canyon open-pit mine 110 km west of Marshall Lake. Numerous other sources of metals beyond the Wasatch Front are likely, on the basis of the widespread increases of industrial activities in western United States since about AD 1900. In sediment deposited since ca. AD 1945, as estimated using 239+240 Pu activities, increases in concentrations of Mn, Fe, S, and some other redox-sensitive metals may result partly from diagenesis related to changes in redox. However, our results indicate that these elemental increases are also related to atmospheric inputs on the basis of their large increases that are nearly coincident with abrupt increases in silt-sized, titanium-bearing detrital magnetite. Such magnetite is interpreted as a component of atmospheric dust, because it is absent in catchment bedrock. Enrichment of P in sediments deposited after ca. AD 1950 appears to be caused largely by atmospheric inputs, perhaps from agricultural fertilizer along with magnetite-bearing soil.

Utah↗

USGS2018

The sensitivity of ecosystem service models to choices of input data and spatial resolution

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

Applied Geography↗

USGS2023

Evaluation of nearshore bathymetric inversion algorithms using camera observations and synthetic numerical input of surface waves during storms

Nearshore bathymetry is difficult to measure using survey methods when wave heights approach the breaking limit. Remote sensing using digital cameras offers a way to observe the surf zone and calculate water depths based on phase speed but comes with its challenges of potentially noisy data that can introduce error into estimates of frequency and wavenumber used in phase speed calculation. This study investigates the robustness of a new version of a bathymetric inversion algorithm (cBathy, version 2.0) in moderate to energetic wave conditions by comparing depth estimates from timeseries’ of pixel intensity with depth estimates from synthetic water level data. The synthetic data are generated by the phase-resolving numerical model, SWASH, and optical data were collected during a field experiment in 2015. Model results from SWASH computed with known bathymetry are used as input to cBathy, and depth estimates are compared to nearshore surveys. Argus camera observations are also used as input to cBathy for the same times as the SWASH simulations. The SWASH simulations resolve breaking waves and do not include (optical) changes to the relation between water surface slope and pixel intensity, termed modulation transfer function, that occur during wave breaking, enabling better estimates from bathymetric inversion algorithms near morphologic features like sand bars. The results indicate that improvements result from eliminating of disruptions to the modulation transfer function caused by wave breaking and residual foam. We show that the use of synthetic wave data is a valuable means of isolating errors in bathymetric inversion algorithms.

North Carolina↗

USGS2014

The effect of adjusting model inputs to achieve mass balance on time-dynamic simulations in a food-web model of Lake Huron

Ecopath with Ecosim (EwE) is a widely used modeling tool in fishery research and management. Ecopath requires a mass-balanced snapshot of a food web at a particular point in time, which Ecosim then uses to simulate changes in biomass over time. Initial inputs to Ecopath, including estimates for biomasses, production to biomass ratios, consumption to biomass ratios, and diets, rarely produce mass balance, and thus ad hoc changes to inputs are required to balance the model. There has been little previous research of whether ad hoc changes to achieve mass balance affect Ecosim simulations. We constructed an EwE model for the offshore community of Lake Huron, and balanced the model using four contrasting but realistic methods. The four balancing methods were based on two contrasting approaches; in the first approach, production of unbalanced groups was increased by increasing either biomass or the production to biomass ratio, while in the second approach, consumption of predators on unbalanced groups was decreased by decreasing either biomass or the consumption to biomass ratio. We compared six simulation scenarios based on three alternative assumptions about the extent to which mortality rates of prey can change in response to changes in predator biomass (i.e., vulnerabilities) under perturbations to either fishing mortality or environmental production. Changes in simulated biomass values over time were used in a principal components analysis to assess the comparative effect of balancing method, vulnerabilities, and perturbation types. Vulnerabilities explained the most variation in biomass, followed by the type of perturbation. Choice of balancing method explained little of the overall variation in biomass. Under scenarios where changes in predator biomass caused large changes in mortality rates of prey (i.e., high vulnerabilities), variation in biomass was greater than when changes in predator biomass caused only small changes in mortality rates of prey (i.e., low vulnerabilities), and was amplified when environmental production was increased. When standardized to mean changes in biomass within each scenario, scenarios when vulnerabilities were low and when fishing mortality was increased explained the most variation in biomass. Our findings suggested that approaches to balancing Ecopath models have relatively little effect on changes in biomass over time, especially when compared to assumptions about how mortality rates of prey change in response to changes in predator biomass. We concluded that when constructing food-web models using EwE, determining the effect of changes in predator biomass on mortality rates of prey should be prioritized over determining the best way to balance the model.

Lake Huron↗

USGS2023

Future climate-induced changes in mixing and deep oxygen content of a caldera lake with hydrothermal heat and salt inputs

Vertical profiles of temperature, salinity and dissolved oxygen in Crater Lake, a caldera lake in the Oregon Cascade Range that receives hydrothermal inputs of heat and salt, were simulated with a 1-dimensional model. Twelve Global Circulation Models and two Representative Concentration Pathways (RCPs) were used to develop boundary conditions from 1950 to 2099. The model simulated the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. All models predicted a reduction in the frequency of deep ventilation events, from an ensemble median frequency of 5.4 winters decade−1 during 1950–2005 to 4.3 (RCP4.5) or 2.5 (RCP8.5) winters decade−1 during 2045–2099. Favorable conditions for thermobaric instability-induced mixing currently occur infrequently and will become rare in the future. The salinity gradient resulting from hydrothermal inputs presents an additional barrier to thermobaric instability that will continue through 2099. A redistribution of salt to the deep lake may prevent ventilation all the way to the bottom in the future. Hypolimnetic dissolved oxygen percent saturation remained above 75% within the 21st century, consistent with oligotrophy and very small oxygen demands. The rate of change in all variables accelerated approaching 2099, coincident with elimination of winter reverse stratification. Historically, about half of the hydrothermal heat added to Crater Lake has been vented to the atmosphere. In the RCP8.5 scenario, the hydrothermal heat will cease to be vented to the atmosphere by the end of the 21st century, and then the temperature of the deep waters will increase rapidly.

Oregon↗