USING AUTO- AND CROSS-CORRELATIONS FROM SEISMIC NOISE TO MONITOR VELOCITY CHANGES AT VILLARRICA VOLCANO, CHILE

We used the Green's functions from auto-correlations and cross-correlations of seismic ambient noise to monitor temporal velocity changes in the subsurface at Villarrica volcano in the Southern Andes of Chile. Campaigns were conducted from March to October 2010 and February to April 2011 with 8 broadband and 6 short-period stations, respectively. We prepared the data by removing the instrument response, normalizing with a root-mean-square method, whitening the spectra, and filtering from 1 to 10 Hz. This frequency band was chosen based on the relatively high background noise level in that range. Hour-long auto- and cross-correlations were computed and the Green's functions stacked by day and total time. To track the temporal velocity changes we stretched a 24 hour moving window of correlation functions from 90% to 110% of the original and cross correlated them with the total stack. All of the stations' auto-correlations detected what is interpreted as an increase in velocity in 2010, with an average increase of 0.13%. Cross-correlations from station V01, near the summit, to the other stations show comparable changes that are also interpreted as increases in velocity. We attribute this change to the closing of cracks in the subsurface due either to seasonal snow loading or regional tectonics. In addition to the common increase in velocity across the stations, there are excursions in velocity on the same order lasting several days. Amplitude decreases as the station's distance from the vent increases suggesting these excursions may be attributed to changes within the volcanic edifice. In at least two occurrences the amplitudes at stations V06 and V07, the stations farthest from the vent, are smaller. Similar short temporal excursions were seen in the auto-correlations from 2011, however, there was little to no increase in the overall velocity.

Spatial and temporal analysis of land cover and landscape structure change in Zagros Forests

The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

Spatial and temporal patterns in ungulate-ecosystem interactions

Ungulates are important components of a variety of ecosystems worldwide. This dissertation integrates aspects of ungulate and forest ecology to increase our understanding of how they work together in ways that are of interest to natural resource managers, educators, and those who are simply curious about nature. Although animal ecology and ecosystem ecology are often studied separately, one of the general goals of this dissertation is to examine how they interact across spatial and temporal scales. Forest ecosystems are heterogeneous across a range of scales. Spatial and temporal habitat use patterns of forest ungulates tend to be congregated in patches where food and/or cover are readily available. Ungulates interact with ecosystem processes by selectively foraging on plants and excreting waste products in concentrated patches. Positive feedbacks may develop where these activities increase the value of habitat through soil fertilization or the alteration of plant chemistry and architecture. Heterogeneity in ecosystem processes and plant community structure, observed at both stand and local scales, may be the integrated outcome of feedbacks between ungulate behavior and abiotic resource gradients. The first chapter of this dissertation briefly discusses pertinent background information on ungulate ecology, with a focus on white-tailed deer (Odocoileus virginianus) in the Upper Great Lakes region and moose (Alces acles) in Isle Royale National Park, Michigan, USA. The second chapter demonstrates why ecological context is important for studying ungulate ecology in forest ecosystems. Excluding deer from eastern hemlock (Tsuga canadensis) stands, which deer use primarily as winter cover, resulted in less spatial complexity in soil reactive nitrogen and greater complexity in diffuse light compared to unfenced stands. The spatial patterning of herbaceous-layer cover was more similar to nitrogen where deer were present, and was a combination of nitrogen and light within deer exclosures. This relationship depends on the seasonal timing of deer habitat use because deer fertilize the soil during winter, but leave during the growing season. The third chapter draws upon an eight-year, 39-stand data set of deer fecal pellet counts in hemlock stands to estimate the amount of nitrogen that deer are depositing in hemlock stands each winter. In stands of high winter deer use, deer-excreted nitrogen inputs consistently exceeded those of atmospheric deposition at the stand scale. At the neighborhood scale, deer-excreted nitrogen was often in excess of atmospheric deposition due to the patchy distribution of deer habitat use. Spatial patterns in habitat use were consistent over the eight-year study at both stand and neighborhood scales. The fourth chapter explores how foraging selectivity by moose interacts with an abiotic resource gradient to influence forest structure and composition. Soil depth on Isle Royale varies from east to west according to glacial history. Fir saplings growing in deeper soils on the west side are generally more palatable forage for moose (lower foliar C:N) than those growing in shallower soils on the east side. Therefore, saplings growing in better conditions are less likely to reach the canopy due to moose browsing, and fir is a smaller overstory component on the west side. Lastly, chapter five focuses on issues surrounding eastern hemlock regeneration failure, which is a habitat type that is important to many wildlife species. Increasing hemlock on the landscape is complicated by several factors including disturbance regime and climate change, in addition to the influence of deer.

IMPACTS OF CLIMATE CHANGE ON SOIL MICROORGANISMS IN NORTHERN HARDWOOD FORESTS

As global climate continues to change, it becomes more important to understand possible feedbacks from soils to the climate system. This dissertation focuses on soil microbial community responses to climate change factors in northern hardwood forests. Two soil warming experiments at Harvard Forest in Massachusetts, and a climate change manipulation experiment with both elevated temperature and increased moisture inputs in Michigan were sampled. The hyphal in-growth bag method was to understand how soil fungal biomass and respiration respond to climate change factors. Our results from phospholipid fatty acid (PLFA) analyses suggest that the hyphal in-growth bag method allows relatively pure samples of fungal hyphae to be partitioned from bacteria in the soil. The contribution of fungal hyphal respiration to soil respiration was examined in climate change manipulation experiments in Massachusetts and Michigan. The Harvard Forest soil warming experiments in Massachusetts are long-term studies with 8 and 18 years of +5 °C warming treatment. Hyphal respiration and biomass production tended to decrease with soil warming at Harvard Forest. This suggests that fungal hyphae adjust to higher temperatures by decreasing the amount of carbon respired and the amount of carbon stored in biomass. The Ford Forestry Center experiment in Michigan has a 2 x 2 fully factorial design with warming (+4-5 °C) and moisture addition (+30% average ambient growing season precipitation). This experiment was used to examine hyphal growth and respiration of arbuscular mycorrhizal fungi (AMF), soil enzymatic capacity, microbial biomass and microbial community structure in the soil over two years of experimental treatment. Results from the hyphal in-growth bag study indicate that AMF hyphal growth and respiration respond negatively to drought. Soil enzyme activities tend to be higher in heated versus unheated soils. There were significant temporal variations in enzyme activity and microbial biomass estimates. When microbial biomass was estimated using chloroform fumigation extractions there were no differences between experimental treatments and the control. When PLFA analyses were used to estimate microbial biomass we found that biomass responds negatively to higher temperatures and positively to moisture addition. This pattern was present for both bacteria and fungi. More information on the quality and composition of the organic matter and nutrients in soils from climate change manipulation experiments will allow us to gain a more thorough understanding of the mechanisms driving the patterns reported here. The information presented here will improve current soil carbon and nitrogen cycling models.