Annual report ... interagency regional monitoring, Northwest Forest Plan [microform].

Description based on: 2001; title from cover.

Improving the efficiency of wildlife monitoring by estimating detectability: a case study of foxes (Vulpes vulpes) on the Eyre Peninsula, South Australia

Demonstrating the existence of trends in monitoring data is of increasing practical importance to conservation managers wishing to preserve threatened species or reduce the impact of pest species. However, the ability to do so can be compromised if the species in question has low detectability and the true occupancy level or abundance of the species is thus obscured. Zero-inflated models that explicitly model detectability improve the ability to make sound ecological inference in such situations. In this paper we apply an occupancy model including detectability to data from the initial stages of a fox-monitoring program on the Eyre Peninsula, South Australia. We find that detectability is extremely low (< 18%) and varies according to season and the presence or absence of roadside vegetation. We show that simple methods of using monitoring data to inform management, such as plotting the raw data or performing logistic regression, fail to accurately diagnose either the status of the fox population or its trajectory over time. We use the results of the detectability model to consider how future monitoring could be redesigned to achieve efficiency gains. A wide range of monitoring programs could benefit from similar analyses, as part of an active adaptive approach to improving monitoring and management.

Water quality monitoring: A combined approach to investigate gradients of change in the Great Barrier Reef, Australia

For the managers of a region as large as the Great Barrier Reef, it is a challenge to develop a cost effective monitoring program, with appropriate temporal and spatial resolution to detect changes in water quality. The current study compares water quality data (phytoplankton abundance and water clarity) from remote sensing with field sampling (continuous underway profiles of water quality and fixed site sampling) at different spatial scales in the Great Barrier Reef north of Mackay (20 degrees S). Five transects (20-30 km long) were conducted from clean oceanic water to the turbid waters adjacent to the mainland. The different data sources demonstrated high correlations when compared on a similar spatial scale (18 fixed sites). However, each data source also contributed unique information that could not be obtained by the other techniques. A combination of remote sensing, underway sampling and fixed stations will deliver the best spatial and temporal monitoring of water quality in the Great Barrier Reef. (c) 2004 Elsevier Ltd. All rights reserved.

The effects of self-monitoring on homework completion and accuracy rates of students with disabilities in an inclusive general education classroom

This study investigated the effects of self-monitoring on the homework completion and accuracy rates of four, fourth-grade students with disabilities in an inclusive general education classroom. A multiple baseline across subjects design was utilized to examine four dependent variables: completion of spelling homework, accuracy of spelling homework, completion of math homework, accuracy of math homework. Data were collected and analyzed during baseline, three phases of intervention, and maintenance. ^ Throughout baseline and all phases, participants followed typical classroom procedures, brought their homework to school each day and gave it to the general education teacher. During Phase I of the intervention, participants self-monitored with a daily sheet at home and on the computer at school in the morning using KidTools (Fitzgerald & Koury, 2003); a student friendly, self-monitoring program. They also participated in brief daily conferences to review their self-monitoring sheets with the investigator, their special education teacher. Phase II followed the same steps except conferencing was reduced to two days a week, which were randomly selected by the researcher and Phase III conferencing was one random day a week. Maintenance data were taken over a two-to-three week period subsequent to the end of the intervention. ^ Results of this study demonstrated self-monitoring substantially improved spelling and math homework completion and accuracy rates of students with disabilities in an inclusive, general education classroom. On average, completion and accuracy rates were highest over baseline in Phase III. Self-monitoring led to higher percentages of completion and accuracy during each phase of the intervention compared to baseline, group percentages also rose slightly during maintenance. Therefore, results suggest self-monitoring leads to short-term maintenance in spelling and math homework completion and accuracy. ^ This study adds to the existing literature by investigating the effects of self-monitoring of homework for students with disabilities included in general education classrooms. Future research should consider selecting participants with other demographic characteristics, using peers for conferencing instead of the teacher, and the use of self-monitoring with other academic subjects (e.g., science, history). Additionally, future research could investigate the effects of each of the two self-monitoring components used alone, with or without the conferencing.^

Derivation of lake mixing and stratification indices from high-resolution lake buoy data

Lake Analyzer is a numerical code coupled with supporting visualization tools for determining indices of mixing and stratification that are critical to the biogeochemical cycles of lakes and reservoirs. Stability indices, including Lake Number, Wedderburn Number, Schmidt Stability, and thermocline depth are calculated according to established literature definitions and returned to the user in a time series format. The program was created for the analysis of high-frequency data collected from instrumented lake buoys, in support of the emerging field of aquatic sensor network science. Available outputs for the Lake Analyzer program are: water temperature (error-checked and/or down-sampled), wind speed (error-checked and/or down-sampled), metalimnion extent (top and bottom), thermocline depth, friction velocity, Lake Number, Wedderburn Number, Schmidt Stability, mode-1 vertical seiche period, and Brunt-Väisälä buoyancy frequency. Secondary outputs for several of these indices delineate the parent thermocline depth (seasonal thermocline) from the shallower secondary or diurnal thermocline. Lake Analyzer provides a program suite and best practices for the comparison of mixing and stratification indices in lakes across gradients of climate, hydro-physiography, and time, and enables a more detailed understanding of the resulting biogeochemical transformations at different spatial and temporal scales.

Preparation of environmental monitoring plan pattern for surface water quality in Iran (Case study: Gharehsou River)

Using water quality management programs is a necessary and inevitable way for preservation and sustainable use of water resources. One of the important issues in determining the quality of water in rivers is designing effective quality control networks, so that the measured quality variables in these stations are, as far as possible, indicative of overall changes in water quality. One of the methods to achieve this goal is increasing the number of quality monitoring stations and sampling instances. Since this will dramatically increase the annual cost of monitoring, deciding on which stations and parameters are the most important ones, along with increasing the instances of sampling, in a way that shows maximum change in the system under study can affect the future decision-making processes for optimizing the efficacy of extant monitoring network, removing or adding new stations or parameters and decreasing or increasing sampling instances. This end, the efficiency of multivariate statistical procedures was studied in this thesis. Multivariate statistical procedure, with regard to its features, can be used as a practical and useful method in recognizing and analyzing rivers’ pollution and consequently in understanding, reasoning, controlling, and correct decision-making in water quality management. This research was carried out using multivariate statistical techniques for analyzing the quality of water and monitoring the variables affecting its quality in Gharasou river, in Ardabil province in northwest of Iran. During a year, 28 physical and chemical parameters were sampled in 11 stations. The results of these measurements were analyzed by multivariate procedures such as: Cluster Analysis (CA), Principal Component Analysis (PCA), Factor Analysis (FA), and Discriminant Analysis (DA). Based on the findings from cluster analysis, principal component analysis, and factor analysis the stations were divided into three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding spatial variations in water quality for effective river water quality management. This study also shows the effectiveness of these techniques for getting better information about the water quality and design of monitoring network for effective management of water resources. Therefore, based on the results, Gharasou river water quality monitoring program was developed and presented.

Ambient Water Monitoring Strategy for Iowa: 2016-2021, November 30, 2016

The Iowa Department of Natural Resources (DNR) Ambient Water Monitoring Program provides consistent, unbiased information about the condition of Iowa’s water resources to support decisions affecting the development, management and protection of these resources. To strengthen its services, the program worked with a variety of stakeholders and other DNR programs to develop a five-year strategy for Iowa’s ambient water monitoring efforts. The strategy identifies opportunities to improve the program’s effectiveness in several categories: monitoring objectives, sampling design, data management, products and services, and program evaluation and coordination. Iowa DNR managers and technical staff will use the new strategy to guide decisions affecting the ambient monitoring program over the next five years. The strategy should also serve as a robust informational resource for stakeholders, policy makers, legislators and the public.

Governing the water conservation in the Urmia Lake Basin: addressing macro systems’ fit and micro users’ behavior

To change unadapted water governing systems, and water users’ traditional conducts in line with climate change, understanding of systems’ structures and users’ behaviors is necessary. To this aim, comprehensive and pragmatic research was designed and implemented in the Urmia Lake Basin where due to the severe droughts, and human-made influences, especially through the agricultural development, the lake has been shrunken drastically. To analyze the water governance and conservation issues in the basin, an innovative framework was developed based on mathematical physics concepts and pro-environmental behavior theories. Accordingly, in system level (macro/meso), the problem of fit of the early-shaped water governing system associating with the function of “political-security” and “political-economic” factors in the basin was identified through mean-field models. Furthermore, the effect of a “political-environmental” factor, the Urmia Lake Restoration Program (ULRP), on reforming the system structure and hence its fit was assessed. The analysis results revealed that by revising the provincial boundaries (horizontal alternation) for the entity of Kurdistan province to permit that interact with the headquarter of West Azerbaijan province for its water demand-supply initiatives, the system fit can increase. Also, the constitution of the ULRP (vertical arrangement) not only could increase the structural fit of the water governing system to the basin, but also significantly could enhance the system fit through its water-saving policy. Besides, in individual level (micro), the governing factors of water conservation behavior of the major users/farmers were identified through rational and moral socio-psychological models. In rational approach, incorporating PMT and TPB, the SEM results demonstrated that “Perceived Vulnerability”, “Self-Efficacy”, “Response Efficacy”, “Response Cost”, “Subjective Norms” and “Institutional Trust” significantly affect the water-saving intention/behavior. Likewise, NAM based analysis as a moral approach, uncovered the significant effects of “Awareness of Consequences”, “Appraisal of Responsibility”, “Personal Norms” as well as “Place Attachment” and “Emotions” on water-saving intention.

Mood states as an indication of staleness and recovery

Elite athletes repeatedly completed the Profile of Mood States (POMS) during a six month training season to determine whether athletes who are stale show different values from those who are intensely trained but not stale. Nineteen elite male and female swimmers were studied at five time points: three times during training (early-, mid-, and late-season), during tapering prior to, and then shortly after, major competition. Of the 14 subjects who completed the entire monitoring program, three were classified as stale based on several criteria including poorer performance and prolonged high level of fatigue. Two of the stale swimmers showed higher scores for several of the POMS measures throughout the season compared with the remainder who were classified as non-stale. However, the third stale swimmer showed similar scores to those of the non-stale swimmers. Several POMS measures were significantly correlated with training intensity but not with training volume. It was concluded that stale athletes may not always demonstrate different mood scores from non-stale athletes but that the total mood disturbance score (TMD) as evaluated by the POMS may be used to indicate those athletes predisposed to the condition long before the symptoms of poor performance and prolonged fatigue are observed. TMD scores were chosen to monitor staleness since they represent a synthesis of the six specific mood states measured by the POMS.

A quantitative state and transition model for the Mitchell grasslands of central western Queensland

Concerns of reduced productivity and land degradation in the Mitchell grasslands of central western Queensland were addressed through a range monitoring program to interpret condition and trend. Botanical and eclaphic parameters were recorded along piosphere and grazing gradients, and across fenceline impact areas, to maximise changes resulting from grazing. The Degradation Gradient Method was used in conjunction with State and Transition Models to develop models of rangeland dynamics and condition. States were found to be ordered along a degradation gradient, indicator species developed according to rainfall trends and transitions determined from field data and available literature. Astrebla spp. abundance declined with declining range condition and increasing grazing pressure, while annual grasses and forbs increased in dominance under poor range condition. Soil erosion increased and litter decreased with decreasing range condition. An approach to quantitatively define states within a variable rainfall environment based upon a time-series ordination analysis is described. The derived model could provide the interpretive framework necessary to integrate on-ground monitoring, remote sensing and geographic information systems to trace states and transitions at the paddock scale. However, further work is needed to determine the full catalogue of states and transitions and to refine the model for application at the paddock scale.

Caracterização das rejeições na pescaria de demersais nos Açores

Dissertação de Mestrado, Estudos Integrados dos Oceanos, 26 de Fevereiro de 2014, Universidade dos Açores.

Necessidades dos idosos do concelho da Praia da Vitória em cuidados continuados domiciliários

Dissertação de Mestrado em Gerontologia Social

Instrumentação e monitorização de estruturas geotécnicas na Rede Ferroviária Nacional: estudo de caso do talude de aterro entre os Km's 236+450 e 236+720 da Linha do Sul

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Vias de Comunicação e Transportes

Análise por ultra-sons no controlo de condição

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Phlebotominae sand flies (Diptera: Psychodidae): potential vectors of American cutaneous leishmaniasis agents in the area associated with the Santo Antônio Hydroelectric System in Western Amazonian Brazil

INTRODUCTION: An entomological study was conducted as part of a vector-monitoring program in the area associated with the Santo Antônio hydroelectric system in State of Rondônia, Western Amazonian Brazil. METHODS: Fourteen sampling sites were surveyed to obtain data on the potential vectors of Leishmania spp. in the area. Sand flies were collected from 2011 to 2014 during the months of January/February (rainy season), May/June (dry season), and September/October (intermediary season) using light traps arranged in three vertical strata (0.5, 1, and 20m). RESULTS : A total of 7,575 individuals belonging to 62 species/subspecies were collected. The five most frequently collected sand flies were Psychodopygus davisi (Root) (36.67%), Trichophoromyia ubiquitalis (Mangabeira) (8.51%), Nyssomyia umbratilis (Ward & Fraiha) (6.14%), Bichromomyia flaviscutellata (Mangabeira) (5.74%), and Psychodopygus complexus (Mangabeira) (5.25%). These species have been implicated in the transmission of American cutaneous leishmaniasis agents in the Brazilian Amazon region and described as potential vectors of this disease in the study area. CONCLUSIONS: Additional surveillance is needed, especially in areas where these five species of sand fly are found.