We developed photographic techniques to characterize coarse (>2‐mm) and fine (≤2‐mm) streambed particle sizes in 12 streams in Anchorage, Alaska. Results were compared with current sampling techniques to assess which provided greater sampling efficiency and accuracy. The streams sampled were wadeable and contained gravel—cobble streambeds. Gradients ranged from about 5% at the upstream sites to about 0.25% at the downstream sites. Mean particle sizes and size‐frequency distributions resulting from digitized photographs differed significantly from those resulting from Wolman pebble counts for five sites in the analysis. Wolman counts were biased toward selecting larger particles. Photographic analysis also yielded a greater number of measured particles (mean = 989) than did the Wolman counts (mean = 328). Stream embeddedness ratings assigned from field and photographic observations were significantly different at 5 of the 12 sites, although both types of ratings showed a positive relationship with digitized surface fines. Visual estimates of embeddedness and digitized surface fines may both be useful indicators of benthic conditions, but digitizing surface fines produces quantitative rather than qualitative data. Benefits of the photographic techniques include reduced field time, minimal streambed disturbance, convenience of postfield processing, easy sample archiving, and improved accuracy and replication potential.
, hydrologist with the U.S. Geological Survey, Alaska Science Program, is setting up a survey-grade global positioning system on a Natural Resources Canada-Geodetic Survey Division benchmark. Survey-grade global positioning systems are used to update and expand survey control along Kootenay Lake, British Columbia. Right: U.S. Geological Survey scientists on the Kootenai River are mapping riverbank elevations by means of a mapping-grade laser rangefinder and angle encoder interfaced with a survey-grade global positioning system. The scientists also are mapping the river bathymetry by using an onboard, survey-grade echo sounder interfaced with a survey-grade global positioning system and bathymetric mapping software.
Appendix 1. Coordinate and elevation file for bathymetric data collected by the USGS and topographic data collected by ADOT&PF. Appendix 2. Coordinates and elevations and predicted water-surface elevations, flow velocities, and horizontal components of velocity for the calibration discharge of 25,600 ft 3 /s. Appendix 3. Coordinates and elevations and predicted water-surface elevations, flow velocities, and horizontal components of velocity for the 100-year recurrence interval discharge of 51,900 ft 3 /s. Appendix 4. Coordinates and elevations and predicted water-surface elevations, flow velocities, and horizontal components of velocity for the simulation of the 100-year recurrence interval discharge of 51,900 ft 3 /s with the existing bridge piers removed.
In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon (Scaphirhynchus albus) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.Bioenergetics models can be used in fish life-history models to help partition energy intake based on the laws of thermodynamics, where the energy consumed by a fish must balance the energy required by physiological processes and growth (Enders & Scruton 2006). A bioenergetics model provides an approach of estimating the consumed energy that is partitioned into three basic components: metabolism, waste loss and growth. This modelling framework accounts for the energy cost experienced by the fish and is used to solve for the level of consumption consistent with the observed growth, integrating the array of environmental conditions experienced by the fish (Moss 2001). Essentially, bioenergetics models are used to understand the relationship between growth and feeding rates under different environmental conditions. Over the last few decades, bioenergetics models have been used widely as a tool in fisheries management and the agricultural industry to address issues related to management of sport fish populations (Chipps & Wahl 2008).One well-known bioenergetics modelling approach used in fisheries is known as the Wisconsin model (Kitchell et al. 1977); its application has been reviewed by Hanson et al. (1997). The Wisconsin model refers to an approach that incorporates maximum feeding rates (C max ) and P values (% of C max ) as a way to explore consumption patterns. The P values are meant to put consumption estimates into context (i.e. a fish feeding at 40% or 95% of C max ). As part of the Wisconsin approach, consumption is equated to the sum of metabolic cost, waste loss and net gain in weight, wi...
Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land-Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process-based models of ecosystem composition under different climate scenarios. Plain Language Summary The decisions human organizations like cities or countries make can have a big influence on the environment, and the environment can influence our decisions. Scientists have some tools for modeling long-term interactions between cities and the environment. It is hard to learn if these tools are working, because even if we know how a particular decision-if made-would influence the environment, we are not good at predicting what decisions will be made. We show that there is a specific mathematical shape to the relationship between a city's population and the total built-up area: things like roads, parking lots, or buildings. This mathematical relationship shows us that in cities with larger populations, there is less space available per person and so built-up areas are more intensely used. We then test whether other researchers' predictions about interactions between urban population and built-up areas predict that these places will be more intensely used, like we showed. We show that the other researchers' predictions do correctly represent some important things we know about cities. This helps us know more about how reliable our predictions of interactions between human organizations and the environment might be.
We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere-ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, climate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our downscaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.
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