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Fieldwork is a major component of nearly every geoscience discipline. Over the past 3 decades, scientists have amassed an array of specialized instrumentation and equipment to help them measure and monitor a staggering assortment of geophysical phenomena.
This paper is not subject to U.S. copyright. Published in 2014 by the American Geophysical Union.
Eos, Vol. 95, No. 49, 9 December 2014
Streamlining Field Data
Collection With Mobile Apps
PAGES 453–454
Fieldwork is a major component of nearly
every geoscience discipline. Over the past
3 decades, scientists have amassed an array of
specialized instrumentation and equipment to
help them measure and monitor a staggering
assortment of geophysical phenomena.
Although this equipment gives scientists
valuable insight into the physical world, it is
not without drawbacks. Much of this special-
ized equipment comes with hefty price tags
and is often dif cult or impossible to custom-
ize. Despite the degree of sophistication of
much of the instr umentation, scientists often
lack the  exibility to adapt data collection to
best meet their own experimental or moni-
toring needs. In addition, technology ironi-
cally often sti es creativity and discourages
scientists from harnessing their powers of
basic obser vation—if there is not a button to
click or a box to  ll, all too often basic obser-
vations and critical insights go unrecorded.
Just 5 years ago, building custom apps was
beyond the skill sets of most geoscientists and
was a relatively costly investment. Today, users
no longer need to be expert programmers to
build and deploy their own apps with the help
of programs that expedite development by
using prede ned scripts and layouts. What’s
more, it is easy to leverage and integrate on-
board sensors in smar tphones and tablets
such as cameras, GPS, accelerometers, and
light sensors, among others. Users can also
combine the sensors and the agility of build-
ing custom apps with an assortment of cases
(e.g., Lifeproof® and OtterBox®) that make
smartphones and tablets ruggedized, even
The ability to develop customizable apps to
help with  eldwork is becoming increasingly
accessible to projects at all funding levels. Tak-
ing advantage of the advances, scientists and
software developers from Utah State Univer-
sit y’s (U SU’s) Ecoge omorpholog y and Topo -
graphic Analysis Lab, USU’s Fluvial Habitats
Center, and Eco Logical Research, Inc., work
together to develop custom apps to increase
ef ciency and data quality by providing a
template for data entry with quality control
enforced by validation rules (see, e.g., Fig-
ure 1 ). The many custom apps are designed
speci cally to facilitate data collection, includ-
ing one to design, implement, and monitor a
large‐ scale restoration project.
Why Build Apps?
Smartphones and tablets are much cheaper
than data collection devices designed speci -
cally for  eld use ($100–$600 versus $1500–
$5000). Rugged and waterproof ca ses are also
available for nearly any mobile device ($50–
$150) to make them  eldworthy. Mobile app
stores have an ever‐increasing list of practical
apps to aid  eld work, such as geographic
information systems (GIS) and data‐syncing
tools. Importantly, most people are now famil-
iar with the use of smartphones and tablets,
making these tools intuitive and practical
to use. These bene ts make common smar t-
phones and tablets the ideal  eld tool.
Interes tingly, geoscientists are not exploiting
these devices en masse. In the geosciences,
eld data are still frequently recorded on data
sheets and ma nually entered into a database for
storage. This transcription process is prone to
errors, and information can be lost completely
because of misplaced or soiled data sheets.
V O L U M E 9 5 N U M B E R 4 9
P A G E S 4 5 3 4 7 2
Fig. 1. Field personnel assessing a restoration structure on the South Fork of Asotin Creek, Wash.,
during an annual restoration effectiveness survey using the High Density Large Woody Debris
HD LW D) Eff ect iv ene ss a pp.
Eos, Vol. 95, No. 49, 9 December 2014
This paper is not subject to U.S. copyright. Published in 2014 by the American Geophysical Union.
Mobile database applications increase data
integrity by allowing users to enter informa-
tion into a structured database during initial
collection. In some cases, data can even be
synced to a central server when the user has
an internet or cellular connection. Mobile
applications have been developed for any-
thing from monitoring air pollution from user
photos to ribotyping bacteria [ Showstack,
2010 ; Guertler and Grando, 2013 ]. The bene ts
to individual projects are apparent, but the
limits of speci c methods are still being ex-
plored [ Teacher et al., 2 0 1 3 ] .
To bridge the gap between the technology
people use every day and the outdated or
expensive technologies scientists use in the
eld, scientists and programmers have devel-
oped mobile database apps for a range of
basic  eld data collection and observations,
including geotagged  eld voice and video
recordings,  uvial audits,  sh surveys, habitat
inventories, beaver dam sur veys, geomatics
survey notebook s, geomorphic unit mapping,
and logs created for use with River Styles,
among others.
Case Study: Stream Restoration Design
and Effectiveness Monitoring
To illustrate the power of using apps in the
eld, we describe an example of a custom
app developed by scientists at Utah State Uni-
versity. This app, named High Density Large
Woody Debris (
HD LWD) Effectiveness, has im-
proved pro ciency at transparently document-
ing a  eld desig n, cataloging the cons truction
process, and facilitating explicit testing of
design hypotheses for a large‐scale stream
restoration project.
The HD LWD Effectiveness app is used to
speci cally monitor the implementation and
effectiveness of a large‐scale experimental
stream restoration project on Asotin Creek in
southeast Washington State. The project in-
volves the addition of a high density of large
woody debris to three streams in the Asotin
Creek watershed [ Bennett et al., 2 0 1 2 ; Wheaton
et al., 2012 ] to increase or improve juvenile
steelhead trout habitat. Historic land use prac-
tices have left the channel in a static, degraded
state composed mostly of uniform runs and
rapids. The goal of the restoration project
is to return LWD densities to historic levels
and thereby to facilitate the creation of pools
and bars that can shelter young steelhead.
This application incorporates the dynamic
design, implementation, and recurrent annual
monitoring of the more than 600 restora-
tion structures—woody debris deliberately
placed along the creek—built for the project
(Figure 1 ).
The app is used to monitor the presence
of hydraulic and geomorphic responses that
are speci c to hypotheses in the project de-
sign. When size, location, and descriptions of
speci c channel units are entered into this
app, it automatically creates spatially explicit
maps of how channel units (e.g., pools, bars,
runs) surrounding every structure are con-
nected (Fig ure 2 ). The app get s very detailed—
there are many speci c types of channel units,
and each one is created through speci c
uvial processes. Armed with these data,
scientists can better determine the ef cacy of
the restoration project in altering hydraulic
and geomorphic complexity in the study
Aspect s of the project are divided into
easily navigable tabs within one application,
and data are stored in a single database. Data
validation rules are set up to keep numeric
values within an acceptable range, and drop
down lists are used for common and repeat-
able inputs.
Using this app, researchers can collect
much more data than was previously feasible
in one  eld season. The ability to store videos
of each structure nearly eliminates confu-
sion for the implementation crews when they
are expected to operate remotely and un-
supervised. Photos are directly stored within
“container”  elds in the database, making it
operate like a digital photo librar y as well.
In addition, by incorporating the bulk of the
restoration monitoring into a single applica-
tion, the data are readily accessible and shar-
able among the working group.
Apps for Citizen Science
Citizen science projects are becoming more
popular but are typically limited in scope by
a nonspecialist user’s knowledge and ability.
Providing a mobile application with imme-
diate quality control and integrated help fea-
tures can greatly expand the expectations and
dependability of crowdsourcing data.
The scientists and programmers at USU re-
cently launched a statewide citizen science
monitoring program with Utah State Universi-
ty’s Water Quality Extension group to monitor
beaver dams throughout the state. The data
are being used both to guide wildlife manage-
ment and to validate predictive models de-
veloped to assess the capacity of riverscapes
to support dam‐building activity by beavers
Fig. 2. Screenshot of the app showing the channel unit assemblage builder, used to record the size,
location, and pertinent attributes of geomorphic units within 50 meters of every structure (red = run,
orange = rapid, gray = bar, blue = pool, yellow = undercut bank). The assemblages can be exported
from the app as spatially explicit rasters for analysis.
This paper is not subject to U.S. copyright. Published in 2014 by the American Geophysical Union.
Eos, Vol. 95, No. 49, 9 December 2014
(J. M. Wheaton and W. W. MacFarlane, Mod-
eling the capacity of riverscapes to support
beaver dams, submitted to Ecohydrology , 2013).
Using custom applications to control data en-
try can make crowdsourcing a viable option
for more geoscience projects.
Simple Apps Do the Heavy Lifting
Native custom mobile database
applications—apps that require extensive
programming knowledge because they are
built from the ground up—are ideal but expen-
sive. Every project and researcher would bene-
t from using native apps, but few researchers
could afford it, and even fewer have the knowl-
edge to develop the apps themselves.
The apps developed by the USU groups and
Eco Logical Research, Inc., do not reinvent
the wheel—they pull from other codes and
software, tailoring them for speci c projects.
For example, the FileMaker Go app was used
to deploy FileMaker Pro databases and data
entry forms on iOS devices (think of this as an
app within an app) so that the developers of
HD LWD Effectiveness app did not have to
program anything for device interaction and
basic app infrastructure. This saved time
and money. Other database‐driven apps (e.g.,
GISPro and HanDBase) can be employed for
the same bene t.
By leveraging simple database‐driven apps
and software that already exist to do the
heavy lifting, the time and cost to develop a
custom application are dramatically reduced.
In this way, geoscientists may be able to de-
velop and use mobile devices and custom
apps more regularly to aid their  eldwork.
For more information on the apps dis-
cussed in this article or on using mobile data-
base applicat ions, contact the correspondin g
author. We would like to thank the Utah State
University Fluvial Habitats Center and Eco
Logical Research, Inc., in par ticular, Nick
Weber, for developing the FileMaker work ow.
Steve Bennett and Nick Bouwes were instru-
mental in the structure design and monitoring
process that facilitated the development of
HD LWD app.
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( 2012 ), Southeas t Washington Inten sively Moni-
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State Recreation and Conserv. Off. , Olympia .
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( 2012 ), A sotin Creek Intensively Monitored
Watershed: Restoration plan for Charley
Creek, North Fork Asotin, & South Fork Asotin
Creeks, Snake River Salmon Recovery Board,
Dayton, Wash .
Department of Watershed Sciences, Utah State
University, Logan; email:
... We conduct rapid field assessments (e.g. Camp and Wheaton, 2014) of beaver dams to supplement existing empirical data describing the size and condition of beaver dams and beaver dam complexes. These data also describe and differentiate between the size attributes of primary and secondary dams, which have not been reported by previous studies. ...
... In the field, we visited beaver dam locations and collected data describing the location, height, type, condition, and construction material of each beaver dam via rapid assessments using iPads (e.g. Camp and Wheaton, 2014) equipped with GIS software (Table 2.3). An observer would walk upstream along the stream until they observed a beaver dam. ...
... To ensure the flow of critical information across one system, the mobile application can function as an information resource and a data logging mechanism [86,87,90,100,101]. The mobile application should contain an external outward-facing platform that is visible to the general public and an internal platform that is visible only to the internal platform stakeholders. ...
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... In the field, we visited beaver dam locations and collected data describing the location, height, type, condition, and construction material of each beaver dam via rapid assessments using iPads (e.g. Camp and Wheaton, 2014) equipped with field GIS software. Only perennial streams were surveyed. ...
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Stream ecosystems can be dramatically altered by dam‐building activities of North American beaver (Castor canadensis). The extent to which beavers’ ecosystem engineering alters riverscapes is driven by the density, longevity, and size (i.e. height and length) of the dams constructed. In comparison to the relative ubiquity of beaver dams on the landscape, there is a scarcity of data describing dam heights. We collected data describing dam height and dam condition (i.e. damaged or intact) of 500 beaver dams via rapid field survey, differentiating between primary and secondary dams and associating each dam with a beaver dam complex. With these data, we examined the influence of beaver dam type (primary/secondary), drainage area, streamflow, stream power, valley bottom width, and HUC12 watershed on beaver dam height with linear regression and the probability that a beaver dam was damaged with logistic regression. On average, primary dams were 0.46 m taller than secondary dams; 15% of observed dams were primary and 85% secondary. Dam type accounted for 21% of dam height variation (p<0.0001). Slope (p=0.0107), discharge (p=0.0029), and drainage area (p=0.0399) also affected dam height, but each accounted for less than 3% of dam height variation. The average number of dams in a dam complex was 6.1 (SD±4.5) and ranged from 1 to 21. The watershed a beaver dam was located in accounted for the most variability (17.8%) in the probability that a beaver dam was damaged, which was greater than the variability explained by any multiple logistic regression model. These results indicate that temporally dynamic variables are important influencers of dam longevity and that beaver dam ecology is a primary factor influencing beaver dam height.
... This data guided our restoration design process and will provide a baseline of instream habitat that we can use to assess the effectiveness of the project. We used a custom iPad application to document the location and proportions of in-channel channel units and their sediment composition, and the locations of LWD pieces and jams (e.g., Camp and Wheaton, 2014). ...
... References for monitoring protocols and other information relevant to preand post-project data collection are provided at: Additionally, field data collection through mobile device applications has become popular by some workers. Camp and Wheaton (2014) provide an overview of tools developed at Utah State University. ...
Technical Report
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Stream restoration practitioners and researchers have devoted a great deal of effort in recent decades to developing extensive guidance for stream restoration. The available resources are diverse, reflecting the wide ranging approaches used and expertise required to develop effective stream restoration projects. To help practitioners in sorting through the extensive amount of available information, this technical note has been developed to provide a guide to the available guidance. The document structure is primarily a series of short literature reviews followed by a hyperlinked reference list for readers to find more information on each topic. The primary topics incorporated into this guidance include general methods, an overview of stream processes and restoration, case studies, data compilation, preliminary assessments, and field data collection. Analysis methods and tools, and planning and design guidance for specific restoration features are also provided. This technical note is a bibliographic repository of information available to assist professionals with the process of planning, analyzing, and designing stream restoration projects. It is updated periodically.
... For example, a number of SHAs use intelligent compaction (IC) technology, which combines a real-time kinematic (RTK) GPS and vibratory roller integrated sensors to assess soil compactness in real time (White 2008;Mooney 2010). Portable mobile tablets/smartphones with embedded on-board sensors, such as cameras, GPS, accelerometers, and light sensors, are also leading the way in increasing efficiency and data quality along with customizable user interfaces for field data collection (Camp 2014). ...
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... Future efforts at landscape monitoring should take into account experiences elsewhere with mobile technologies, including new apps to streamline field work (Camp and Wheaton 2014). It would also be worthwhile keeping a watching brief on new ideas and approaches to landscape monitoring elsewhere, especially in the Vital Signs program of the US National Park Service. ...
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Technical Report
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The Asotin Creek Intensively Monitored Watershed Project was established in 2008 as a large-scale, long-term experiment to test the effectiveness of stream restoration at improving freshwater habitat conditions and increasing production and productivity of a wild summer run steelhead population. Asotin Creek is recovering from past disturbances such as riparian clearing, channel straightening, removal of large woody debris, and excessive sediment from upland farming practices. However, the majority of channels are still single thread, have low large woody debris frequency, limited floodplain connection, and consist of mostly planar geomorphic features (e.g., runs, rapids). To increase geomorphic diversity, we developed and implemented a low-tech process-based restoration method we call High-density Large Woody Debris (HDLWD) using post-assisted log structures (PALS) to create hand-built debris jams. The project area includes three tributaries to Asotin Creek and in each tributary we established three 4 km long monitoring sections, two control and one treatment section in each tributary (total study area 36 km). We have monitored juvenile steelhead since 2008 using passive integrated transponder (PIT) tags and mark-recapture methods to estimate abundance, growth, emigration, survival, production, and productivity in treatment and control sections – pre and post-restoration. Washington Department of Fish and Wildlife also provide monitoring of juvenile emigration and adult escapement near the mouth of Asotin Creek. We installed over 650 PALS in 14 km of treatment area from 2012-2016 using a staircase experimental design. To date the restoration has been effective at increasing instream complexity of steelhead habitat by forcing greater hydraulic diversity, which has led to greater pool and bar frequency and area, developing more off-channel habitat, and promoted tree recruitment. However, there has been limited floodplain connection. As a result, juvenile abundance has increased in treatment areas with minimal changes in growth or survival which suggests either egg-fry or fry-juvenile survival may have increased due to restoration. Preliminary results also suggest biomass and production of juvenile steelhead has increased in treatment sections. The increases in fish abundance and production so far are modest (15-40% increases) but we hypothesize that the greatest population increases will be realized when the restoration promotes “greater floodplain reconnection” and the project is poised to demonstrate this in the coming years. The results from this IMW will have broad applications to wadeable streams across western North America that make up the majority of stream miles in a watershed and will help to promote cost-effective and science-based approaches to stream restoration and recovery of ESA listed salmon and steelhead.
Technical Report
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Background The Asotin Creek Intensively Monitored Watershed (IMW) was implemented in 2008. The focal species are natural reproducing summer steelhead. Based on previous habitat assessments and preliminary IMW monitoring it was decided that riparian function and instream habitat complexity were impaired. The restoration proposed was fencing, native plant revegetation, and weed control to enhance riparian function in the long-term, and the addition of large woody debris (LWD) in the short-term to increase habitat diversity and promote a more dynamic channel (e.g., increase sediment sorting, pool frequency, and floodplain connection). We implemented the IMW using a staircase experimental design where restoration actions were implemented in different years starting in 2012 and ending in 2016 in three different streams. Each stream is divided into three 4 km long sections and one or more sections has been restored in each stream with the remaining sections acting as controls. We have built 654 large woody debris structures at an average density of 4.7 structures per 100 m in the treatment sections (~39% of the study area has been restored and 61% remains as controls). We have continued to add LWD to treatment sections as needed based on annual habitat survey results in order to keep the density of wood high in treatment sections compared to control areas (annual maintenance). We are using extensive habitat sampling and fish PIT tagging and resighting to estimate habitat changes and changes juvenile steelhead abundance, growth, survival, movement, production, and productivity in each experimental section. There are five passive transponder tag (PIT) interrogation sites within Asotin Creek that are used to monitor adult and juvenile PIT tag steelhead movement in Asotin Creek watershed – three of these sites (ACM, ACB, AFC) were upgraded with new equipment in 2018. Analyses Approaches We continue to develop and refine tools/models to help us analyze our data. We completed and present summary results on the following analyses: • Geomorphic unit delineation tool (GUT) to quantify geomorphic units (e.g., pools, bars, planar features) from topographic data collected from Columbia Habitat Monitoring (CHaMP) data we collect at 18 sites (105 visits). • Barker model for calculating true survival, site fidelity, and probability of captures. We have now completed and run all fish capture and resighting data for each season and year from 2008-2016 • Bayesian based model for aging all of our fish using a subsample of known ages and acquired from scale samples and fish lengths. We use the age model to estimate the age of tagged fish that were not aged with scales so that we can determine the brood year of migrants and calculate migrants per female as well as assess treatment responses by age class. All tagged juvenile steelhead have been aged to 2017. • Net rate of energy intake model (NREI) has been run for all CHaMP site visits from 2011-2017 to estimate the fish capacity changes by year. • Staircase statistical models to analyze juvenile steelhead abundance 2008-2017 (previously presented) • Migrant production of treatment and control sites pre and post restoration have been estimated from 2008-2017 by estimating the number of migrants (smolts) by age class and then back-calculating the brood year they came from using PIT tag detections at the interrogation sites at the mouths of each IMW study stream. Trends Habitat • We continue to see habitat responses that are in line with many of original hypotheses of treatment areas becoming more complex after restoration, but the changes are inconsistent. • The frequency of wood in the treatments is staying high relative to the control sections. • The frequency of pools and bars has increased in some treatment areas compared to control areas. • Geomorphic unit analyses are not as clean as we would have hoped and provides mixed results on habitat change. Fish • We have observed positive trends in fish abundance and are beginning to see difference in the fish response by stream. Like the habitat changes, the fish response in the North Fork appears to be greater than the other two streams despite being treated last (i.e., we are observing a Year 3 response in North Fork, Year 4 in Charley, and Year 5 in South Fork). • We observed a positive increase in survival (especially fall) in treatment sections compared control sections • Migrant production is highest in North Fork, but Charley and South Fork migrants/female is consistently higher. • Very preliminary analysis suggests that there may be a positive trend in the productivity of treatment sections compared to control sections General • It appears that responses, both habitat fish, are positive but relatively small and inconsistent. One explanation for this is the stream types themselves. They are confined streams with limited floodplain habitat. The North Fork appears to be responding to most to restoration and this may be because it has higher stream flow and more floodplain – so restoration can make relatively more habitat (and habitat change) than in Charley and South Fork. We are considering what options we have (including more restoration) based on our analysis to date. • We have implemented a robust design, completed a large restoration treatment, maintained a high quality data stream for both habitat and fish for 11 years, developed a series of geomorphically and empirically based set of tools to summarize raw data, and developed a staircase statistical model to analyze these data and separate multiple sources of variance from the true treatment response. • We are now in the phase of the project where we need to complete enough years of post-treatment monitoring to complete the migrants/female table, develop models that can explain what factors are driving the responses we see (i.e., causal mechanisms), and assessing if the responses are consistent, persistent, and how they vary between stream types.
Technical Report
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EXECUTIVE SUMMARY Asotin Creek in southeast Washington was chosen as a site to develop an Intensively Monitored Watershed Project (IMW). The purpose of the IMW program is to implement stream restoration actions in an experimental framework to determine the effectiveness of restoration at increasing salmon and steelhead production and to identify casual mechanisms of the fish response to help guide restoration actions in other watersheds. Asotin Creek is designated a wild steelhead refuge and steelhead are the focus of the IMW. • The Asotin Creek IMW has a hierarchical-staircase experimental design which includes the lower 12 km of three tributaries: Charley Creek, North Fork Asotin Creek, and South Fork Asotin Creek (hereafter the study creeks). Each study creek is divided in three 4 km long sections and one section of each creek will be treated (i.e., restoration applied) with the remaining sections acting as controls. Treatments will be staggered over three years with one section treated each year starting in 2012. A total of 12 km will be treated. • The study creeks consist primarily of highly homogenized and degraded habitats, which are thought to be limiting steelhead production. One of the primary limiting factors in these study creeks is a lack of pool habitat and cover for fish, particularly a relatively low abundance, density and mean size of large woody debris (LWD) compared to reference conditions and assumed historic recruitment levels. Therefore, LWD restoration treatments have been proposed for the Asotin IMW. • The addition of LWD to streams to improve habitat complexity and quality is not a new restoration strategy. However, we argue that most projects place undue focus on the size and stability of LWD with frequent attempts to anchor LWD in place. From a stream or watershed perspective, we think that the low density of LWD is a much bigger problem than the size, and streams with healthy rates of LWD recruitment see much more dynamic behavior in their LWD (i.e., it moves regularly). We seek to produce a population-level response in steelhead in the Asotin Creek Watershed by treating over 12 km of stream in three study creeks with 500 – 600 LWD structures. We expect this to fundamentally alter the complexity of habitat at three sections within the project area inducing an increase in steelhead production at the stream scale. • To achieve the desired LWD densities with traditional treatment methods would be extremely expensive, highly disruptive to the existing riparian vegetation, and logistically infeasible to implement over the broad range of steelhead habitat in the Columbia Basin. We instead propose to test the effectiveness of a simple, unobtrusive, method of installing Dynamic Woody Structures (DWS), which are constructed of wood posts, driven into the streambed, and augmented with LWD cut to lengths that can be moved by hand. • Dynamic Woody Structures are installed with a hand-carried, hydraulic post-pounder by a crew of 2-4 people. Typical installation time is on the order of 1-2 hours per structure and material costs are < $100. Thus, if the treatment method proves effective, this is potentially an easy and cost-effective method to transfer to other streams. • Dynamic Woody Structures, like naturally occurring LWD jams, are designed to produce an immediate hydraulic response by constricting the flow width. Like natural LWD accumulations, this alteration of the flow field creates more hydraulic heterogeneity, providing shear zones for energy conservation for fish next to swift areas with high rates of invertebrate drift. Moreover, the convergent flow produced by the constriction is likely to scour and/or maintain pools at high flows, and divergent flow downstream of the DWS where the stream width expands, may promote active bars that provide good spawning habitat. • The fate of an individual structure is not as critical as the overall density of structures. A high density of DWS will increase the large-scale roughness of the stream section creating much more variability in flow width and opportunities to build, alter, and maintain complex assemblages of active bar and pool habitat. Ultimately, we hope to use the DWS to initiate a more regular exchange of materials (sediment, water, LWD, etc.) with the adjacent riparian area. • We have articulated these predicted responses into a series of explicit design hypotheses, which are guiding our monitoring efforts. The monitoring is part of an adaptive management plan and is nested within the hierarchal-staircase experimental design. A targeted blend of detailed, habitat monitoring and fish sampling nested within treatment and control sections is combined with coarser-grained rapid assessment inventories and remote sensing at the stream and watershed scale. This approach ensures that we can reliably detect and infer mechanisms of geomorphic changes and fish response at local scales, but we can then reasonably expand these understandings to the stream and population scales. • The staggered implementation of the restoration (i.e., staircase design) provides explicit opportunities within the adaptive management plan to refine and adapt implementation and monitoring specifics as may be necessary. • Preliminary results from the performance of 15 trial structures installed in the summer of 2011 suggest that the structures are able to withstand higher than average spring floods (the peak March 2012 discharge was the largest in 12 years at the confluence of North Fork and South Fork) and produced many of the intended hydraulic and geomorphic responses.
Technical Report
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This report summarizes the first four years of pre-restoration IMW monitoring and infrastructure development. Restoration began in the summer of 2012 and be implemented in a hierarchical-staircase design (see below) in three tributaries to Asotin Creek over three consecutive years. Monitoring of the restoration effectiveness will continue until 2018.
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Smartphones and their apps (application software) are now used by millions of people worldwide and represent a powerful combination of sensors, information transfer, and computing power that deserves better exploitation by ecological and evolutionary researchers. We outline the development process for research apps, provide contrasting case studies for two new research apps, and scan the research horizon to suggest how apps can contribute to the rapid collection, interpretation, and dissemination of data in ecology and evolutionary biology. We emphasize that the usefulness of an app relies heavily on the development process, recommend that app developers are engaged with the process at the earliest possible stage, and commend efforts to create open-source software scaffolds on which customized apps can be built by nonexperts. We conclude that smartphones and their apps could replace many traditional handheld sensors, calculators, and data storage devices in ecological and evolutionary research. We identify their potential use in the high-throughput collection, analysis, and storage of complex ecological information.
A new smartphone application takes advantage of various technological capabilities and sensors to help users monitor air quality. Tapping into smartphone cameras, Global Positioning System (GPS) sensors, compasses, and accelerometers, computer scientists with the University of Southern California's (USC) Viterbi School of Engineering have developed a new application, provisionally entitled “Visibility.”
Clostridium difficile causes outbreaks of infectious diarrhoea, most commonly occurring in healthcare institutions. Recently, concern has been raised with reports of C. difficile disease in those traditionally thought to be at low risk i.e. community acquired rather than healthcare acquired. This has increased awareness for the need to track outbreaks and PCR-ribotyping has found widespread use to elucidate epidemiologically linked isolates. PCR-ribotyping uses conserved regions of the 16S rRNA gene and 23S rRNA gene as primer binding sites to produce varying PCR products due to the intergenic spacer (ITS1) regions of the multiple operons. With the explosion of whole genome sequence data it became possible to analyse the start of the 23S rRNA gene for a more accurate selection of regions closer to the end of the ITS1. However the following questions must still be asked: (i) Does the chromosomal organisation of the rrn operon vary between C. difficile strains? and (ii) just how conserved are the primer binding regions? Eight published C. difficile genomes have been aligned to produce a detailed database of indels of the ITS1's from the rrn operon sets. An iPad Filemaker Go App has been constructed and named RiboTyping (RT). It contains detail such as sequences, ribotypes, strain numbers, GenBank numbers and genome position numbers. Access to various levels of the database is provided so that details can be printed. There are three main regions of the rrn operon that have been analysed by the database and related to each other by strain, ribotype and operon: (1) 16S gene (2) ITS1 indels (3) 23S gene. This has enabled direct intra- and inter-genomic comparisons at the strain, ribotype and operon (allele) levels in each of the three genomic regions. This is the first time that such an analysis has been done. By using the RT App with search criteria it will be possible to select probe combinations for specific strains/ribotypes/rrn operons for experiments to do with diagnostics, typing and recombination of operons. Many more incomplete C. difficile whole genome sequencing projects are recorded in GenBank as underway and the rrn operon information from these can also be added to the RT App when available. The RT App will help simplify probe selection because of the complexity of the ITS1 in C. difficile even in a single genome and because other allele-specific regions (16S and 23S genes) of variability can be relationally compared to design extra probes to increase sensitivity.
Southeast Washington Intensively Monitored Watershed Project in Asotin Creek: Year 4 pretreatment monitoring summary report , Wash. State Recreation and Conserv
  • S Bennett
  • R Camp
  • N Trahan
  • N Bouwes
Bennett, S., R. Camp, N. Trahan, and N. Bouwes ( 2012 ), Southeast Washington Intensively Monitored Watershed Project in Asotin Creek: Year 4 pretreatment monitoring summary report, Wash. State Recreation and Conserv. Off., Olympia.