Dendritic stream networks are inherently spatially and hierarchically structured, but the effects of this structure on stream communities are largely unknown. My aim was to investigate spatial patterns in stream networks using extensive spatial sampling of both adult and benthic macroinvertebrates in four stream networks on the West Coast of the South Island, New Zealand. Using spatial modelling and analyses, I answered questions about appropriate spatial measurements to capture ecological processes in stream networks, metacommunity processes at different scales in space and time, and how local and regional processes interact to structure metacommunities in stream networks. Spatial eigenfunction analyses showed that distance measures that explained most variance in stream macroinvertebrate communities were stream distance and weighted stream distance measures. They performed better than Euclidean distance to measure spatial structure that is ecologically relevant to stream network communities. The spatial pattern of benthic stream macroinvertebrates was stable over time, whereas community composition changed significantly, as shown by space-time interactions modelled by MANOVA-like redundancy analysis. Thus, spatial processes structuring stream metacommunities remained constant, in agreement with neutral model predictions. Network-scale properties, particularly flood disturbances, influenced the relative importance of spatial and environmental variation in stream network metacommunities. Additionally, quantile regression indicated that three key variables, habitat size, isolation and local habitat conditions, jointly limited community structure in stream networks, providing empirical support for both island biogeography and metacommunity theories. My study indicated that spatial structuring has an important influence on stream macroinvertebrate communities. The results contribute to broader ecological theory and understanding of community assembly by relating empirical results to theoretical predictions. In particular, they advance understanding of spatial processes in stream networks. The research also highlights a number of new methods, which were successfully applied to stream systems to elucidate complex spatial patterns.

The usefulness of watershed hydrological process models is considerably increased when they can be extrapolated across spatial and temporal scales. This scale transfer problem, meaning the description and prediction of characteristics and processes at a scale different from the one at which observations and measurements are made, and has become the subject of much current research in hydrology and other areas. Quantitative description of fractal scaling behavior of runoff and stream network morphometry in agricultural watersheds has not been previously reported. In the present study, fractal and multifractal scaling of daily runoff rate in four experimental agricultural watersheds and their associated sub-watersheds (32 in total) were investigated. The time series of daily runoff rate were obtained from the database (comprising about 16,600 station years of rainfall and runoff data for small agricultural watersheds across the U.S.) developed by the Hydrological and Remote Sensing Laboratory, Agricultural Research Service, US Department of Agriculture (HRSL/ARS/USDA). Fractal scaling patterns of the Digital Elevation Model (DEM)-extracted stream network morphometry for these four watersheds were also examined. The morphometry of stream networks of four watersheds were obtained by Geographic Information System (GIS) manipulation of digital elevation data downloaded from the most recent (July 2004) U.S. Geological Survey (USGS) National Elevation Dataset (NED). Several threshold values of contribution area for stream initiation were used to extract stream networks for each of the four watersheds. The principal measures of fractal scaling determined for the runoff series were the Hurst exponent obtained by rescaled range (R/S) analysis, the fractal dimension estimated by the shifted box-counting method, and the multifractal scaling function parameters (a and C1) of the Universal Multifractal Model (UMM). Corresponding measures for the DEM-extracted stream networks at each threshold value were the fractal dimension estimated using the box-counting technique and the Horton ratios of the network. Daily runoff rate exhibited strong long-term dependence and scale invariance over certain time scales. The same fractal dimensions and Hurst exponents were obtained for the sub-watersheds within each watershed. Runoff exhibited multifractal behavior that was well described by UMM. The multifractal parameters a (quantifies how far the process is from monofractality) and C1 (characterizes the sparseness or inhomogeneity of the mean of the process) were reasonably close to each other for sub-watersheds within a watershed and were generally similar among four watersheds. For the DEM-extracted networks, the morphometric attributes and Horton ratios as well as their fractal dimensions were dependent on the threshold values of contribution area used in the extraction process. The fractal dimensions were almost identical for DEM-extracted stream networks of the four watersheds. The DEM-extracted stream network displayed a single scaling pattern, rather than multifractal behavior. Explanation of the physical significance of fractal characteristics of the stream network in relation to runoff time series would require more data than were available in this study. / Ph. D.

Water quality and river/stream ecosystems are important for all living creatures. To protect human health, aquatic life and the surrounding ecosystem, a considerable amount of time and money has been spent on sampling and monitoring streams and rivers. Water quality monitoring and analysis can help researchers predict and learn from natural processes in the environment and determine human impacts on an ecosystem. Measurements such as temperature, pH, nitrogen concentration, algae and fish count collected along the network are all important factors in water quality analysis. The main purposes of the statistical analysis in this thesis are (1) to assess the relationship between the variable measured in the water (response variable) and other variables that describe either the locations on/along the stream network or certain characteristics at each location (explanatory variable), and (2) to assess the degree of similarity between the response variable values measured at different locations of the stream, i.e. spatial dependence structure. It is commonly accepted that measurements taken at two locations close to each other should have more similarity than locations far away. However, this is not always true for observations from stream networks. Observations from two sites that do not share water flow could be independent of each other even if they are very close in terms of stream distance, especially those observations taken on objects that move passively with the water flow. To model stream network data correctly, it is important to quantify the strength of association between observations from sites that do not share water.

Ephemeral streams are small headwater streams that only experience streamflow in response to a precipitation event. Due to their highly complex and dynamic spatial and temporal nature, ephemeral streams have been difficult to monitor and are in general poorly understood. This research implemented an extensive network of recently developed electrical resistance sensors to monitor ephemeral streamflow in a Southern Ontario watershed, located in Guelph, Ontario. From this data, patterns of stream network expansion and contraction were determined. Further analysis examined a series of spatial and temporal variables that were monitored to explain the occurrence of ephemeral channel activity through binary logistic regression. The results suggest that the most common patterns of network expansion and contraction at the study site are incomplete coalescence and disintegration, respectively. Analysis of the primary controls on ephemeral streamflow showed only weak relationships, suggesting that there are more complex processes at work in these ephemeral streams. This research has implications for improving ephemeral streamflow monitoring in the future, which will be important for developing and implementing meaningful conservation and management strategies.

This thesis concerns general improvements to rainfall runoff models and focuses on two particular aspects, namely flood-wave routing in the main channel and consistent parameterisation of the rainfall-runoff process under different degrees of discretization of the catchment. The primary goal is to: 1) describe a general methodology for parameterisation of a rainfall runoff model so that the parameters are consistent across catchments modelled at different discretization scales and 2) develop an improved channel routing technique which takes proper account of the effects of all characteristics of wave motions in the channels. The first of these concerns methods for removing the inconsistency of parameterisation that results from different catchment discretizations in rainfall-runoff models. A stochastic Tokunaga network is developed for dealing with the scaling inconsistence. The problem of network embedding is also discussed. The second is a relatively simple method for the solution of the full dynamic wave equations for one-dimensional channel flow, which accurately simulates the effects of shocks. / PhD Doctorate

In environmental studies, measurements of interest are often taken on multiple variables. The results of spatial data analyses can be substantially affected by the spatial configuration of the sites where measurements are taken. Hence, optimal designs which result in data guaranteeing efficient statistical inferences need to be studied. We study optimal designs on two large classes of spatial regions with respect to three design criteria, which were prediction, covariance parameter estimation, and empirical prediction. The first class of regions includes those in the plane, where Euclidean distance is used. The performance of the optimal designs is compared to that of randomly chosen designs. Optimal designs for a small example and a relatively large example are obtained. For the small example, complete enumeration of all possible designs is computationally feasible. For the large example, the computational difficulty in searching for the optimal spatial sampling design is overcome by a simulated annealing algorithm. The second class of spatial regions includes streams and rivers, where the distance is defined as distance along the stream network. A moving average construction is used to establish valid covariance and cross-covariance models using stream distance. Optimal designs for small and large examples are obtained. An application of our methodology to a real stream network is included. We discuss the impact of asymmetry in the cross covariance function on the spatial multivariate design. The relationship between multivariate optimal design and univariate optimal design if the multivariate design is restricted to be completely collocated is studied. The efficiency lost if we consider the design that is optimal within the class of collocated designs is discussed.

Stream fish assemblages exist within stream networks defined by the size and proximity of connected streams (i.e., stream network topology). The spatial position of sites within stream networks may therefore regulate opportunities for fish dispersal to access distant resources or colonize "new" habitats. Such inter-stream dispersal dynamics will influence local fish assemblage structure and the vulnerability of local assemblages to anthropogenic stressors. In this dissertation, I explored the effects of stream network topology on fish assemblage structure in the mid-Atlantic highlands, USA and tested the hypothesis that dispersal would affect the sensitivity of fish-based environmental quality assessments (i.e., bioassessments). In chapter 1, I evaluated the effects of stream networks by comparing fish assemblages between sites with and without large downstream confluences (>3rd order) in western Virginia, USA (i.e., mainstem tributaries and headwater tributaries, respectively). I found that local species richness was higher in mainstem tributaries than headwater tributaries and that these effects could not be explained by variation in local environmental habitat conditions. In chapter 2, I developed and applied a continuous model of stream network topology to explore the effects of downstream size and proximity on local fish assemblage structure within the mid-Atlantic highlands. I found that fish assemblage structure (i.e., Bray-Curtis distances in species abundance) was significantly related to variation in stream network topology up to approximately 9 fluvial km from sites. Chapters 3 and 4 explored the implications of inter-stream dispersal for fish bioassessments. In Chapter 3, I identified 10 fish metrics that corresponded predictably to environmental stressors in the mid-Atlantic highlands. However, headwater tributary assemblages showed stronger relations to local environmental quality than mainstem tributaries, consistent with the hypothesis of riverine dispersal. In Chapter 4, I compared the effects of stream network topology on fish and benthic macroinvertebrate assemblages. Fish metrics were influenced by the size and proximity of connected streams but benthic macroinvertebrate metrics were not. This finding suggests that stream fishes may complement benthic macroinvertebrate bioassessments by indicating environmental conditions at larger spatial grains. / Ph. D.

Digital elevation models (DEMs) and their derivatives such as slope, flow direction and flow accumulation maps, are used frequently as inputs to hydrologic and nonpoint source modeling. The depressions which are frequently present in DEMs may represent the actual topography, but are often the result of errors. Creating a depression-free surface is commonly required prior to deriving flow direction, flow accumulation, flow network, and watershed boundary maps. The objectives of this study were: 1) characterize the occurrence of depressions in 30m USGS DEMs and assess correlations to watershed topographic characteristics, and 2) compare the performance of two algorithms used to remove depressions and delineate flow networks from DEMs. Sixty-six watersheds were selected to represent a range of topographic conditions characteristic of the Piedmont and Mountain and Valley regions of Virginia. Analysis was based on USGS 30m DEMs with elevations in integer meters. With few exceptions watersheds fell on single 7.5minute USGS quadrangle sheets, ranged in size from 450 to 3000 hectares, and had average slopes ranging from 3 to 20 percent. ArcView (3.1) with the Spatial Analyst (1.1) extension was used to summarize characteristics of each watershed including slope, elevation range, elevation standard deviation, curvature, channel slope, and drainage density. TOPAZ (ver 1.2) and ArcView were each used to generate a depression-free surface, flow network and watershed area. Characteristics of the areas 'cut' and 'filled' by the algorithms were compared to topographic characteristics of the watersheds. Blue line streams were digitized from scanned USGS 7.5minute topographic maps (DRGs) then rasterized at 30 m for analysis of distance from the derived flow networks. The removal of depressions resulted in changes in elevation values in 0 - 11% of the cells in the watersheds. The percentage of area changed was higher in flatter watersheds. Changed elevation cells resulted in changes in two to three times as many cells in derivative flow direction, flow accumulation and slope grids. Mean fill depth by watershed ranged from 0 to 10 m, with maximum fill depths up to 40 m. In comparison with ArcView, TOPAZ, on average affected 30% fewer cells with less change in elevation. The significance of the difference between ArcView and TOPAZ decreased as watershed slope increased. A spatial assessment of the modified elevation and slope cells showed that depressions in the DEMs occur predominantly on or along the flow network. Flow networks derived by ArcView and TOPAZ were not significantly different from blue line streams digitized from the USGS quadrangles as indicated by a paired t test. Watershed area delineated by ArcView and TOPAZ was different for almost all watersheds, but was generally within 1%. Conclusions from this study are: 1) The depressions in 30 m DEMs can make up a significant portion of the area especially for flatter watersheds; 2) The TOPAZ algorithm performed better than ArcView in minimizing the area modified in the process of creating a depressionless surface, particularly in flatter topography; 3) Areas affected by removing depressions are predominantly adjacent to the stream network; 4) For every elevation cell changed, slopes are changed for two to three cells, on average; and 5) ArcView and TOPAZ derived flow networks closely matched the blue line streams. / Master of Science

Dynamic expansions and contractions of stream networks can play an important role for hydrologic processes as they can connect different parts of the landscape to the stream channels. However, we know little about the temporal and spatial variations of stream networks during different flow and wetness conditions. This study focuses on the contraction and expansion of stream networks during different flow conditions in the boreal Krycklan catchment, located in Northern Sweden. The stream network and initiation points were extracted from a gridded digital elevation model (DEM) of 5-meter resolution, and then compared with the stream network initiation points (heads) observed during the spring flood (freshet) period in 2012. From the results of the study, it was clearly seen that the observed stream heads and the stream heads appearing in the stream network map extracted from DEM did not agree very well. 49% of the total observed stream heads (49) fell onto the low order stream branches and headwater streams derived from the DEM. Only few of them exactly matched the modeled stream heads. Moreover, the modeled stream network was much denser than the observed stream network, and so the simple raster based dynamic model developed could not well represent the dynamic stream network extension in the real system. Most headwater streams in the study catchment were man-made ditches, which were dug to drain water wetlands and to increase forest productivity. The majority of observed stream heads were formed by seepage from the saturated surrounding soils, while only a few of them were formed by saturation overland flow.  On the other hand, the dynamic stream network derived from the DEM suggested that the number of streams of lower order and their lengths was sensitive to change in streamflow, especially during the high flow episode.

What drives species diversity across landscapes is one of the most fundamental questions in ecology. Further, understanding the mechanisms underlying species diversity patterns is important not only for forming and challenging ecological theories but also essential for appropriate landscape management and effective nature conservation. This thesis focuses on patterns of vascular plant, moss and liverwort species richness and composition in relation to water flow in boreal-forest catchments, focusing mostly on riparian zones (RZs), that is terrestrial areas bordering streams and rivers. I addressed some of the most essential questions related to the ecology of riparian vegetation including the role of stream network position, groundwater (GW) flow paths, substrate availability, upland perturbations, and stream restoration. I also investigated how riparian soil processes and habitat properties relate to these factors in order to provide a holistic understanding of riparian dynamics. The results showed that the species richness and composition of riparian vascular plants, mosses and liverworts are strongly influenced by position along the stream network, GW discharge, presence of variable substrates in RZs, and by stream restoration. Generally, more species were found downstream in the network, at sites with inputs of upland GW, sites with high diversity of substrates (e.g., open mineral soil, rocks, stones, wood and bark), and along streams restored after channelization. This thesis also describes how riparian habitat properties responded to position in the landscape and human impacts, thus providing mechanistic links between plant species diversity and riparian processes across spatial scales. These ecological insights are further implemented into numerous recommendations for freshwater and upland management in boreal Sweden. Given that streams and rivers connect landscape elements both longitudinally and laterally I argue that management plans should be designed for entire catchments instead of individual river segments. Ignoring the connectivity of streams as well as the high connectivity of riparian areas to uplands via GW flows may result in failure of restoration, mitigation and/or protection actions. Further, during forestry operations more emphasis should be placed on GW discharge areas along streams and rivers, because they represent important ecological and biogeochemical hotspots in the landscape. The riparian buffers left along streams in boreal catchments affected by forestry are presently insufficiently wide and often uniform in width. This threatens the assemblages of species in GW discharge hotspots and the ecosystem services they provide. Overall, this thesis describes a holistic picture of riparian diversity patterns and riparian processes in boreal landscapes, acknowledges and elaborates on current ecological theories, presenting new patterns in biodiversity, and offers management guidelines.