The impacts of environmental and anthropogenic stressors on largemouth bass: an integration of field and laboratory studies

Several environmental stressors can impact the physiology and survival of fishes. Fish experience natural fluctuations in temperature and dissolved oxygen, but variations in these parameters due to anthropogenic sources are typically greater in magnitude and duration. Changes in temperature and oxygen of anthropogenic origins may therefore have larger negative impacts on fish than those occurring during natural events. Physiological parameters are sensitive indicators of the impacts of stressors by providing insight into the manner in which fish are disturbed by the stressor. Fish may display cumulative physiological responses to successive stressors, but the concept of synergy among multiple thermal stressors is poorly understood. Further, some fish species can be subjected to competitive angling events, which expose fish to an array of additional stressors that can increase mortality. The impacts of these events may change over seasons as fish display seasonal changes in behavior and physiology. Latitudinal origin may also affect the physiological response and mortality of fish exposed to common environmental stressors as individual populations are adapted to local environmental conditions. This thesis focuses on addressing these potential impacts on physiological parameters and mortality of largemouth bass (Micropterus salmoides) and provides implications for management and conservation. Largemouth bass were relatively robust to abrupt changes in temperature and oxygen, but were perturbed from physiological homeostasis during large (12°C) temperature shocks and low (< 4 mg O2/L) levels of dissolved oxygen. Cumulative physiological impacts of multiple cold shocks were only slightly greater than the disturbances sustained during a single cold shock, suggesting largemouth bass are able to tolerate successive thermal stressors. Largemouth bass exhibited seasonal changes in physiological parameters but the responses of fish to angling tournaments were relatively similar across seasons when compared with seasonal controls. Mortality was low during angling tournaments held during four seasons and no apparent seasonal trends were observed. Lastly, largemouth bass from two latitudinally separated populations exhibited differences in their physiological responses to acute cold stressors and overwinter mortality, characterized by greater mortality and physiological disturbances of southern fish than northern fish. Knowledge gained from this study can be used to make management and conservation decisions regarding a host of environmental factors and provides insight into the mechanisms by which fish species can persist over large latitudinal ranges.

Approximation Algorithms for Network Design and Orienteering

This thesis presents approximation algorithms for some NP-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P is not equal to NP, there are no efficient (i.e., polynomial-time) algorithms that solve these problems exactly. Hence, if one desires efficient algorithms for such problems, it is necessary to consider approximate solutions: An approximation algorithm for an NP-Hard problem is a polynomial time algorithm which, for any instance of the problem, finds a solution whose value is guaranteed to be within a multiplicative factor of the value of an optimal solution to that instance. We attempt to design algorithms for which this factor, referred to as the approximation ratio of the algorithm, is as small as possible. The field of Network Design comprises a large class of problems that deal with constructing networks of low cost and/or high capacity, routing data through existing networks, and many related issues. In this thesis, we focus chiefly on designing fault-tolerant networks. Two vertices u,v in a network are said to be k-edge-connected if deleting any set of k − 1 edges leaves u and v connected; similarly, they are k-vertex connected if deleting any set of k − 1 other vertices or edges leaves u and v connected. We focus on building networks that are highly connected, meaning that even if a small number of edges and nodes fail, the remaining nodes will still be able to communicate. A brief description of some of our results is given below. We study the problem of building 2-vertex-connected networks that are large and have low cost. Given an n-node graph with costs on its edges and any integer k, we give an O(log n log k) approximation for the problem of finding a minimum-cost 2-vertex-connected subgraph containing at least k nodes. We also give an algorithm of similar approximation ratio for maximizing the number of nodes in a 2-vertex-connected subgraph subject to a budget constraint on the total cost of its edges. Our algorithms are based on a pruning process that, given a 2-vertex-connected graph, finds a 2-vertex-connected subgraph of any desired size and of density comparable to the input graph, where the density of a graph is the ratio of its cost to the number of vertices it contains. This pruning algorithm is simple and efficient, and is likely to find additional applications. Recent breakthroughs on vertex-connectivity have made use of algorithms for element-connectivity problems. We develop an algorithm that, given a graph with some vertices marked as terminals, significantly simplifies the graph while preserving the pairwise element-connectivity of all terminals; in fact, the resulting graph is bipartite. We believe that our simplification/reduction algorithm will be a useful tool in many settings. We illustrate its applicability by giving algorithms to find many trees that each span a given terminal set, while being disjoint on edges and non-terminal vertices; such problems have applications in VLSI design and other areas. We also use this reduction algorithm to analyze simple algorithms for single-sink network design problems with high vertex-connectivity requirements; we give an O(k log n)-approximation for the problem of k-connecting a given set of terminals to a common sink. We study similar problems in which different types of links, of varying capacities and costs, can be used to connect nodes; assuming there are economies of scale, we give algorithms to construct low-cost networks with sufficient capacity or bandwidth to simultaneously support flow from each terminal to the common sink along many vertex-disjoint paths. We further investigate capacitated network design, where edges may have arbitrary costs and capacities. Given a connectivity requirement R_uv for each pair of vertices u,v, the goal is to find a low-cost network which, for each uv, can support a flow of R_uv units of traffic between u and v. We study several special cases of this problem, giving both algorithmic and hardness results. In addition to Network Design, we consider certain Traveling Salesperson-like problems, where the goal is to find short walks that visit many distinct vertices. We give a (2 + epsilon)-approximation for Orienteering in undirected graphs, achieving the best known approximation ratio, and the first approximation algorithm for Orienteering in directed graphs. We also give improved algorithms for Orienteering with time windows, in which vertices must be visited between specified release times and deadlines, and other related problems. These problems are motivated by applications in the fields of vehicle routing, delivery and transportation of goods, and robot path planning.