William W. Taylor

Bio: William W. Taylor is an academic researcher from Michigan State University. The author has contributed to research in topics: Fisheries management & Population. The author has an hindex of 37, co-authored 141 publications receiving 8334 citations.

Complexity of coupled human and natural systems

Abstract: Integrated studies of coupled human and natural systems reveal new and complex patterns and processes not evident when studied by social or natural scientists separately. Synthesis of six case studies from around the world shows that couplings between human and natural systems vary across space, time, and organizational units. They also exhibit nonlinear dynamics with thresholds, reciprocal feedback loops, time lags, resilience, heterogeneity, and surprises. Furthermore, past couplings have legacy effects on present conditions and future possibilities.

Emerging threats and persistent conservation challenges for freshwater biodiversity

Abstract: In the 12 years since Dudgeon et al. (2006) reviewed major pressures on freshwater ecosystems, the biodiversity crisis in the world’s lakes, reservoirs, rivers, streams and wetlands has deepened. While lakes, reservoirs and rivers cover only 2.3% of the Earth’s surface, these ecosystems host at least 9.5% of the Earth’s described animal species. Furthermore, using the World Wide Fund for Nature’s Living Planet Index, freshwater population declines (83% between 1970 and 2014) continue to outpace contemporaneous declines in marine or terrestrial systems. The Anthropocene has brought multiple new and varied threats that disproportionately impact freshwater systems. We document 12 emerging threats to freshwater biodiversity that are either entirely new since 2006 or have since intensified: (i) changing climates; (ii) e-commerce and invasions; (iii) infectious diseases; (iv) harmful algal blooms; (v) expanding hydropower; (vi) emerging contaminants; (vii) engineered nanomaterials; (viii) microplastic pollution; (ix) light and noise; (x) freshwater salinisation; (xi) declining calcium; and (xii) cumulative stressors. Effects are evidenced for amphibians, fishes, invertebrates, microbes, plants, turtles and waterbirds, with potential for ecosystem-level changes through bottom-up and top-down processes. In our highly uncertain future, the net effects of these threats raise serious concerns for freshwater ecosystems. However, we also highlight opportunities for conservation gains as a result of novel management tools (e.g. environmental flows, environmental DNA) and specific conservation-oriented actions (e.g. dam removal, habitat protection policies,managed relocation of species) that have been met with varying levels of success.Moving forward, we advocate hybrid approaches that manage fresh waters as crucial ecosystems for human life support as well as essential hotspots of biodiversity and ecological function. Efforts to reverse global trends in freshwater degradation now depend on bridging an immense gap between the aspirations of conservation biologists and the accelerating rate of species endangerment.

Coupled Human and Natural Systems

Abstract: Humans have continuously interacted with natural systems, resulting in the formation and development of coupled human and natural systems (CHANS). Recent studies reveal the complexity of organizational, spatial, and temporal couplings of CHANS. These couplings have evolved from direct to more indirect interactions, from adjacent to more distant linkages, from local to global scales, and from simple to complex patterns and processes. Untangling complexities, such as reciprocal effects and emergent properties, can lead to novel scientific discoveries and is essential to developing effective policies for ecological and socioeconomic sustainability. Opportunities for truly integrating various disciplines are emerging to address fundamental questions about CHANS and meet society's unprecedented challenges.

Compartments revealed in food-web structure

Abstract: Compartments1 in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups2. Theoretically, compartments increase the stability in networks1,2,3,4,5, such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches6,7,8,9 or insufficient methodological rigour8,10,11. Here we show that a method for detecting compartments from the social networking science12,13,14 identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results12,13,14. A graphical presentation14 reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs15,16,17.

Integrating Landscape Ecology into Natural Resource Management

Abstract: List of contributors Foreward Eugene P. Odum Preface Jianguo Liu and William W. Taylor Acknowledgements Part I. Introduction and Concepts: 1. Coupling landscape ecology with natural resource management: paradigm shifts and new approaches Jianguo Liu and William W. Taylor Part II. Landscape Structure and Multi-scale Management: 2. Integrating landscape structure and scale into natural resource management John A. Wiens, Beatrice Van Horne and Barry R. Noon 3. Focal patch landscape studies for wildlife management: optimising sampling effort across scales Julie M. Brennan, Darren J. Bender, Thomas A. Contreras and Lenore Fahrig 4. Managing for small patch in human-dominated landscapes: cultural factors and corn belt agriculture Robert C. Corry and Joan Iverson Nassauer 5. A landscape approach to managing the biota of streams Charles F. Rabeni and Scott P. Sowa 6. Linking ecological and social scales for natural resource management Kristiina A. Vogt, Morgan Grove, Heidi Asbjornsen, Keely B. Maxwell, Daniel J. Vogt, Ragnhildur Sigurdardottir, Bruce C. Larson, Leo Schibli and Michael Dove Part III. Landscape Function and Cross-boundary Management: 7. Assessing the ecological consequences of forest policies in a multi-ownership province in Oregon Thomas A. Spies, Gordon Reeves, Kelly Burnett, William McComb, K. Norman Johnson, Gordon Grant, Janet Ohman, Steve Garman and Pete Bettinger 8. Incorporating the effects of habitat edges into landscape models: effective area models for cross-boundary management Thomas D. Sisk and Nick M. Haddad 9. Aquatic-terrestrial linkages and implications for landscape management Rebecca L. Schneider, Edward L. Mills and Daniel C. Josephson Part IV. Landscape Change and Adaptive Management: 10. A landscape transition matrix approach for landscape management Virginia H. Dale, Desmond T. Fortes and Tom L. Ashwood 11. Tactical monitoring of landscapes Dean L. Urban 12. Landscape change: patterns, effects and implications for adaptive management of wildlife resources Daniel T. Rutledge, Christopher A. Lepczyk and Jianguo Liu 13. Landscape ecology in highly managed regions: the benefits of collaboration between management and researchers John B. Dunning Jr. Part V. Landscape Integrity and Integrated Management: 14. Putting multiple use and sustained yield into a landscape context Thomas R. Crow 15. Integrating landscape ecology into fisheries management: a rationale and practical considerations W. W. Taylor, D. B. Hayes, C. P. Ferreri, K. D. Lynch, K. R. Newman and E. F. Roseman 16. Applications of advanced technologies in studying and managing grassland landscape integrity Greg A. Hoch, Brent L. Brock and John M. Briggs 17. An integrated approach to landscape science and management Richard J. Hobbs and Robert Lambeck Part VI. Syntheses and Perspectives: 18. Bridging the gap between landscape ecology and natural resource management Monica G. Turner, Thomas R. Crow, Jianguo Liu, Dale Rabe, Charles F. Rabeni, Patricia A. Soranno, William W. Taylor, Kristiina A. Vogt and John A. Wiens 19. Landscape ecology of the future: a regional interface of ecology and socioeconomics Eugene P. Odum 20. Epilogue Richard T. T. Forman Index.

Community detection in graphs

Abstract: The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.

Influence of Diet On the Distribtion of Nitrogen Isotopes in Animals

Abstract: The influence of diet on the distribution of nitrogen isotopes in animals was investigated by analyzing animals grown in the laboratory on diets of constant nitrogen isotopic composition. The isotopic composition of the nitrogen in an animal reflects the nitrogen isotopic composition of its diet. The δ^(15)N values of the whole bodies of animals are usually more positive than those of their diets. Different individuals of a species raised on the same diet can have significantly different δ^(15)N values. The variability of the relationship between the δ^(15)N values of animals and their diets is greater for different species raised on the same diet than for the same species raised on different diets. Different tissues of mice are also enriched in ^(15)N relative to the diet, with the difference between the δ^(15)N values of a tissue and the diet depending on both the kind of tissue and the diet involved. The δ^(15)N values of collagen and chitin, biochemical components that are often preserved in fossil animal remains, are also related to the δ^(15)N value of the diet. The dependence of the δ^(15)N values of whole animals and their tissues and biochemical components on the δ^(15)N value of diet indicates that the isotopic composition of animal nitrogen can be used to obtain information about an animal's diet if its potential food sources had different δ^(15)N values. The nitrogen isotopic method of dietary analysis probably can be used to estimate the relative use of legumes vs non-legumes or of aquatic vs terrestrial organisms as food sources for extant and fossil animals. However, the method probably will not be applicable in those modern ecosystems in which the use of chemical fertilizers has influenced the distribution of nitrogen isotopes in food sources. The isotopic method of dietary analysis was used to reconstruct changes in the diet of the human population that occupied the Tehuacan Valley of Mexico over a 7000 yr span. Variations in the δ^(15)C and δ^(15)N values of bone collagen suggest that C_4 and/or CAM plants (presumably mostly corn) and legumes (presumably mostly beans) were introduced into the diet much earlier than suggested by conventional archaeological analysis.

Finding community structure in networks using the eigenvectors of matrices

Abstract: We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as ``modularity'' over possible divisions of a network. Here we show that this maximization process can be written in terms of the eigenspectrum of a matrix we call the modularity matrix, which plays a role in community detection similar to that played by the graph Laplacian in graph partitioning calculations. This result leads us to a number of possible algorithms for detecting community structure, as well as several other results, including a spectral measure of bipartite structure in networks and a centrality measure that identifies vertices that occupy central positions within the communities to which they belong. The algorithms and measures proposed are illustrated with applications to a variety of real-world complex networks.