Wolf habitat selection at the territory level : seasonal and interannual variation and influence on reproductive success

Habitat selection has been one of the main research topics in ecology for decades. Nevertheless, many aspects of habitat selection still need to be explored. In particular, previous studies have overlooked the importance of temporal variation in habitat selection and the value of including data on reproductive success in order to describe the best quality habitat for a species. We used data collected from radiocollared wolves in Yellowstone National Park (USA), between 1996 and 2008, to describe wolf habitat selection. In particular, we aimed to identify i) seasonal differences in wolf habitat selection, ii) factors influencing interannual variation in habitat selection, and iii) the effect of habitat selection on wolf reproductive success. We used probability density functions to describe wolf habitat use and habitat coverages to represent the habitat available to wolves. We used regression analysis to connect habitat use with habitat characteristics and habitat selection with reproductive success. Our most relevant result was discovering strong interannual variability in wolf habitat selection. This variability was in part explained by pack identity and differences in litter size and leadership of a pack between two years (summer) and in pack size and precipitation (winter). We also detected some seasonal differences. Wolves selected open habitats, intermediate elevations, intermediate distances from roads, and avoided steep slopes in late winter. They selected areas close to roads and avoided steep slopes in summer. In early winter, wolves selected wetlands, herbaceous and shrub vegetation types, and areas at intermediate elevation and distance from roads. Surprisingly, the habitat characteristics selected by wolves were not useful in predicting reproductive success. We hypothesize that interannual variability in wolf habitat selection may be too strong to detect effects on reproductive success. Moreover, prey availability and competitor pressure may also have an influence on wolf reproductive success, which we did not assess. This project demonstrated how important temporal variation is in shaping patterns of habitat selection. We still believe in the value of running long-term studies, but the effect of temporal variation should always be taken into account.

Analysis of atmospheric transport and the effects of seasonal and interannual transport variability on measurements made at the Pico Mountain observatory

A non-hierarchical K-means algorithm is used to cluster 47 years (1960–2006) of 10-day HYSPLIT backward trajectories to the Pico Mountain (PM) observatory on a seasonal basis. The resulting cluster centers identify the major transport pathways and collectively comprise a long-term climatology of transport to the observatory. The transport climatology improves our ability to interpret the observations made there and our understanding of pollution source regions to the station and the central North Atlantic region. I determine which pathways dominate transport to the observatory and examine the impacts of these transport patterns on the O3, NOy, NOx, and CO measurements made there during 2001–2006. Transport from the U.S., Canada, and the Atlantic most frequently reaches the station, but Europe, east Africa, and the Pacific can also contribute significantly depending on the season. Transport from Canada was correlated with the North Atlantic Oscillation (NAO) in spring and winter, and transport from the Pacific was uncorrelated with the NAO. The highest CO and O3 are observed during spring. Summer is also characterized by high CO and O3 and the highest NOy and NOx of any season. Previous studies at the station attributed the summer time high CO and O3 to transport of boreal wildfire emissions (for 2002–2004), and boreal fires continued to affect the station during 2005 and 2006. The particle dispersion model FLEXPART was used to calculate anthropogenic and biomass-burning CO tracer values at the station in an attempt to identify the regions responsible for the high CO and O3 observations during spring and biomass-burning impacts in summer.

Inductive-Capacitive Resonant Circuit Sensors for Structural Health and Environmental Monitoring

Inductive-capacitive (LC) resonant circuit sensors are low-cost, wireless, durable, simple to fabricate and battery-less. Consequently, they are well suited to sensing applications in harsh environments or in situations where large numbers of sensors are needed. They are also advantageous in applications where access to the sensor is limited or impossible or when sensors are needed on a disposable basis. Due to their many advantages, LC sensors have been used for sensing a variety of parameters including humidity, temperature, chemical concentrations, pH, stress/pressure, strain, food quality and even biological growth. However, current versions of the LC sensor technology are limited to sensing only one parameter. The purpose of this work is to develop new types of LC sensor systems that are simpler to fabricate (hence lower cost) or capable of monitoring multiple parameters simultaneously. One design presented in this work, referred to as the multi-element LC sensor, is able to measure multiple parameters simultaneously using a second capacitive element. Compared to conventional LC sensors, this design can sense multiple parameters with a higher detection range than two independent sensors while maintaining the same overall sensor footprint. In addition, the two-element sensor does not suffer from interference issues normally encountered while implementing two LC sensors in close proximity. Another design, the single-spiral inductive-capacitive sensor, utilizes the parasitic capacitance of a coil or spring structure to form a single layer LC resonant circuit. Unlike conventional LC sensors, this design is truly planar, thus simplifying its fabrication process and reducing sensor cost. Due to the simplicity of this sensor layout it will be easier and more cost-effective for embedding in common building or packaging materials during manufacturing processes, thereby adding functionality to current products (such as drywall sheets) while having a minor impact on overall unit cost. These modifications to the LC sensor design significantly improve the functionality and commercial feasibility of this technology, especially for applications where a large array of sensors or multiple sensing parameters are required.

Use of hydroclimatic forecasts for improved water management in central Texas

Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

Study of water use and supply in the district of Independencia, Peru

Peru is a developing country with abundant fresh water resources, yet the lack of infrastructure leaves much of the population without access to safe water for domestic uses. The author of this report was a Peace Corps Volunteer in the sector of water & sanitation in the district of Independencia, Ica, Peru. Independencia is located in the arid coastal region of the country, receiving on average 15 mm of rain annually. The water source for this district comes from the Pisco River, originating in the Andean highlands and outflowing into the Pacific Ocean near the town of Pisco, Peru. The objectives of this report are to assess the water supply and sanitation practices, model the existing water distribution system, and make recommendations for future expansion of the distribution system in the district of Independencia, Peru. The assessment of water supply will be based on the results from community surveys done in the district of Independencia, water quality testing done by a detachment of the U.S. Navy, as well as on the results of a hydraulic model built in EPANET 2.0 to represent the distribution system. Sanitation practice assessments will be based on the surveys as well as observations from the author while living in Peru. Recommendations for system expansions will be made based on results from the EPANET model and the municipality’s technical report for the existing distribution system. Household water use and sanitation surveys were conducted with 84 families in the district revealing that upwards of 85% store their domestic water in regularly washed containers with lids. Over 80% of those surveyed are drinking water that is treated, mostly boiled. Of those surveyed, over 95% reported washing their hands and over 60% mentioned at least one critical time for hand washing when asked for specific instances. From the surveys, it was also discovered that over 80% of houses are properly disposing of excrement, in either latrines or septic tanks. There were 43 families interviewed with children five years of age or under, and just over 18% reported the child had a case of diarrhea within the last month at the time of the interview. Finally, from the surveys it was calculated that the average water use per person per day is about 22 liters. Water quality testing carried out by a detachment of the U.S. Navy revealed that the water intended for consumption in the houses surveyed was not suitable for consumption, with a median E. coli most probable number of 47/100 ml for the 61 houses sampled. The median total coliforms was 3,000 colony forming units per 100 ml. EPANET was used to simulate the water delivery system and evaluate its performance. EPANET is designed for continuous water delivery systems, assuming all pipes are always flowing full. To account for the intermittent nature of the system, multiple EPANET network models were created to simulate how water is routed to the different parts of the system throughout the day. The models were created from interviews with the water technicians and a map of the system created using handheld GPS units. The purpose is to analyze the performance of the water system that services approximately 13,276 people in the district of Independencia, Peru, as well as provide recommendations for future growth and improvement of the service level. Performance evaluation of the existing system is based on meeting 25 liters per person per day while maintaining positive pressure at all nodes in the network. The future performance is based on meeting a minimum pressure of 20 psi in the main line, as proposed by Chase (2000). The EPANET model results yield an average nodal pressure for all communities of 71 psi, with a range from 1.3 – 160 psi. Thus, if the current water delivery schedule obtained from the local municipality is followed, all communities should have sufficient pressure to deliver 25 l/p/d, with the exception of Los Rosales, which can only supply 3.25 l/p/d. However, if the line to Los Rosales were increased from one to four inches, the system could supply this community with 25 l/p/d. The district of Independencia could greatly benefit from increasing the service level to 24-hour water delivery and a minimum of 50 l/p/d, so that communities without reliable access due to insufficient pressure would become equal beneficiaries of this invaluable resource. To evaluate the feasibility of this, EPANET was used to model the system with a range of population growth rates, system lifetimes, and demands. In order to meet a minimum pressure of 20 psi in the main line, the 6-inch diameter main line must be increased and approximately two miles of trench must be excavated up to 30 feet deep. The sections of the main line that must be excavated are mile 0-1 and 1.5-2.5, and the first 3.4 miles of the main line must be increased from 6 to 16 inches, contracting to 10 inches for the remaining 5.8 miles. Doing this would allow 24-hour water delivery and provide 50 l/p/d for a range of population growth rates and system lifetimes. It is expected that improving the water delivery service would reduce the morbidity and mortality from diarrheal diseases by decreasing the recontamination of the water due to transport and household storage, as well as by maintaining continuous pressure in the system to prevent infiltration of contaminated groundwater. However, this expansion must be carefully planned so as not to affect aquatic ecosystems or other districts utilizing water from the Pisco River. It is recommended that stream gaging of the Pisco River and precipitation monitoring of the surrounding watershed is initiated in order to begin a hydrological study that would be integrated into the district’s water resource planning. It is also recommended that the district begin routine water quality testing, with the results available to the public.

VERIFYING SUCCESS OF ARTIFICIAL REEFS IN THE HURON-ERIE CORRIDOR FOR LAKE STURGEON

Lake sturgeon (Acipenser fulvescens) were historically abundant in the Huron-Erie Corridor (HEC), a 160 km river/channel network composed of the St. Clair River, Lake St. Clair, and the Detroit River that connects Lake Huron to Lake Erie. In the HEC, most natural lake sturgeon spawning substrates have been eliminated or degraded as a result of channelization and dredging. To address significant habitat loss in HEC, multi-agency restoration efforts are underway to restore spawning substrate by constructing artificial spawning reefs. The main objective of this study was to conduct post-construction monitoring of lake sturgeon egg deposition and larval emergence near two of these artificial reef projects; Fighting Island Reef in the Detroit River, and Middle Channel Spawning Reef in the lower St. Clair River. We also investigated seasonal and nightly timing of larval emergence, growth, and vertical distribution in the water column at these sites, and an additional site in the St. Clair River where lake sturgeon are known to spawn on a bed of ~100 year old coal clinkers. From 2010-12, we collected viable eggs and larvae at all three sites indicating that these artificial reefs are creating conditions suitable for egg deposition, fertilization, incubation, and larval emergence. The construction methods and materials, and physical site conditions present in HEC artificial reef projects can be used to inform future spawning habitat restoration or enhancement efforts. The results from this study have also identified the likelihood of additional uncharacterized natural spawning sites in the St. Clair River. In addition to the field study, we conducted a laboratory experiment involving actual substrate materials that have been used in artificial reef construction in this system. Although coal clinkers are chemically inert, some trace elements can be reincorporated with the clinker material during the combustion process. Since lake sturgeon eggs and larvae are developing in close proximity to this material, it is important to measure the concentration of potentially toxic trace elements. This study focused on arsenic, which occurs naturally in coal and can be toxic to fishes. Total arsenic concentration was measured in samples taken from four substrate treatments submerged in distilled water; limestone cobble, rinsed limestone cobble, coal clinker, and rinsed coal clinker. Samples were taken at three time intervals: 24 hours, 11 days, and 21 days. ICP-MS analysis showed that concentrations of total arsenic were below the EPA drinking water standard (10 ppb) for all samples. However, at the 24 hour sampling interval, a two way repeated measures ANOVA with a Holm-Sidak post hoc analysis (α= 0.05) showed that the mean arsenic concentration was significantly higher in the coal clinker substrate treatment then in the rinsed coal clinker treatment (p=0.006), the limestone cobble treatment (p