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Monarch butterflies are among the most popular insect species in the world and are an icon for conservation groups and environmental education programs. Monarch caterpillars and adults are easily recognizable as welcome visitors to gardens in North America and beyond, and their spectacular migration in eastern North America (from breeding locations in Canada and the United States to overwintering sites in Mexico) has captured the imagination of the public. Monarch migration, behavior, and chemical ecology have been studied for decades. Yet many aspects of monarch biology have come to light in only the past few years. These aspects include questions regarding large-scale trends in monarch population sizes, monarch interactions with pathogens and insect predators, and monarch molecular genetics and large-scale evolution. A growing number of current research findings build on the observations of citizen scientists, who monitor monarch migration, reproduction, survival, and disease. Monarchs face new threats from humans as they navigate a changing landscape marked by deforestation, pesticides, genetically modified crops, and a changing climate, all of which place the future of monarchs and their amazing migration in peril. To meet the demand for a timely synthesis of monarch biology, conservation and outreach, Monarchs in a Changing World summarizes recent developments in scientific research, highlights challenges and responses to threats to monarch conservation, and showcases the many ways that monarchs are used in citizen science programs, outreach, and education. It examines issues pertaining to the eastern and western North American migratory populations, as well as to monarchs in South America, the Pacific and Caribbean Islands, and Europe. The target audience includes entomologists, population biologists, conservation policymakers, and K-12 teachers. Contributors: Anurag A. Agrawal, Cornell University; Jared G. Ali, Michigan State University; Sonia Altizer, University of Georgia; Michael C. Anderson, Eden Prairie, Minnesota; Sophia M. Anderson, Eden Prairie, Minnesota; Kim Bailey, Georgia Department of Natural Resources; Rebecca Batalden, University of Minnesota; Kristen A. Baum, Oklahoma State University; Scott Hoffman Black, Xerces Society for Invertebrate Conservation; Brianna Borders, Xerces Society for Invertebrate Conservation; Lincoln P. Brower, Sweet Briar College; Wendy Caldwell, University of Minnesota; Mariana Cantú-Férnandez, Universidad Nacional Autónoma de México; Nicola Chamberlain, Harvard University; Sonya Charest, Montreal Insectarium; Andrew K. Davis, University of Georgia; Alma De Anda, Covina, California; Guadalupe del Rio Pesado, Alternare, A.C., Mexico; Janet Kudell-Ekstrum, USDA Forest Service; Linda S. Fink, Sweet Briar College; Mark Fishbein, Oklahoma State University; Juan Fernández-Haeger, University of Córdoba, Spain; Eligio García Serrano, Fondo Monarca, Mexico; Mark Garland, Cape May Monarch Monitoring Project; Brian Hayes, Monarch Teacher Network; Elizabeth Howard, Journey North; Mark D. Hunter, University of Michigan; Sarina Jepsen, Xerces Society for Invertebrate Conservation; Diego Jordano, University of Córdoba, Spain; Matthew C. Kaiser, University of Minnesota; Ridlon J. Kiphart, Texas Master Naturalists; Marcus R. Kronforst, University of Chicago; Jim Lovett, University of Kansas; Eric Lee-Mäder, Xerces Society for Invertebrate Conservation; Stephen B. Malcolm, Western Michigan University; Héctor Martínez-Torres, Universidad Nacional Autónoma de México; Susan Meyers, Stone Mountain Memorial Association; Erik A. Mollenhauer, Monarch Teacher Network; Mía Monroe, Xerces Society for Invertebrate Conservation; Eneida B. Montesinos-Patino, Monarch Butterfly Fund; Gail M. Morris, Southwest Monarch Study; Elisha K. Mueller, Oklahoma State University; Kelly R. Nail, University of Minnesota; Karen S. Oberhauser, University of Minnesota; Diego R. Pérez-Salicrup, Universidad Nacional Autónoma de México; Amanda A. Pierce, Emory University; John Pleasants, Iowa State University; Victoria Pocius, University of Kansas; Robert Michael Pyle, Northwest Lepidoptera Survey; M. Isabel Ramírez, Universidad Nacional Autónoma de México; Sergio Rasmann, University of California, Irvine; Gerald Rehfeldt, USDA Forest Service; Eduardo Rendón-Salinas, World Wildlife Fund-Mexico; Leslie Ries, National Socio-Environmental Synthesis Center; Jacobus C. de Roode, Emory University; Richard G. RuBino, Florida State University; Ann Ryan, University of Kansas; Cuauhtémoc Sáenz-Romero, Universidad Michoacana de San Nicolás de Hidalgo; Lidia Salas-Canela, Universidad Nacional Autónoma de México; Phil Schappert, Biophilia Consulting; Priya C. Shahani, Oregon State University; Benjamin H. Slager, Western Michigan University; Michelle J. Solensky, University of Jamestown; Douglas J. Taron, Chicago Academy of Sciences/Peggy Notebaert Nature Museum; Orley R. Taylor, University of Kansas; Rocío Treviño, Protección de la Fauna Mexicana A.C.; Francis X. Villablanca, California Polytechnic State University; Dick Walton, New Jersey Audubon/Cape May Bird Observatory; Ernest H. Williams, Hamilton College; Elisabeth Young-Isebrand, University of Minnesota; Myron P. Zalucki, University of Queensland; Raúl R. Zubieta, Universidad Nacional Autónoma de México

Monarch butterfly --- Monarch butterfly. --- Anosia plexippus --- Danaus archippus --- Danaus plexippus --- Danaus --- Conservation

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Gardening on rooftops, balconies, and terraces is a popular trend. After thirty-five years of experience, Susan Brownmiller writes with honesty and humor about her oasis twenty floors above a Manhattan street. She reports the catastrophes: losing daytime access during building-wide renovations; assaults from a mockingbird during his mating season. And the joys: a peach tree fruited for fifteen years; the windswept birches lasted for twenty-five. Butterflies and bees pay annual visits. She pampers a buddleia, a honeysuckle, roses, hydrangeas, and more. Her adventures celebrate the tenacity of nature, inviting readers to marvel at her garden's resilience, and her own. Enhanced by over thirty color photographs, this passionate account of green life in a gritty, urban environment will appeal to readers and gardeners wherever they dwell.

Urban gardening --- Roof gardening --- City gardening --- Gardening --- Rooftop gardening --- Manhattan. --- apartment building. --- apartment. --- botany. --- city apartment. --- city landscape. --- city life. --- city. --- gardening. --- high rise. --- highrise. --- monarch butterfly. --- monarch. --- nature lover. --- nature. --- renovation. --- rooftop. --- street level. --- terrace. --- urban.

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Computational intelligence is a general term for a class of algorithms designed by nature's wisdom and human intelligence. Computer scientists have proposed many computational intelligence algorithms with heuristic features. These algorithms either mimic the evolutionary processes of the biological world, mimic the physiological structure and bodily functions of the organism,

individual updating strategy --- integrated design --- global optimum --- flexible job shop scheduling problem --- whale optimization algorithm --- EHO --- bat algorithm with multiple strategy coupling (mixBA) --- multi-objective DV-Hop localization algorithm --- optimization --- rock types --- variable neighborhood search --- biology --- average iteration times --- CEC2013 benchmarks --- slicing tree structure --- firefly algorithm (FA) --- benchmark --- single loop --- evolutionary computation --- memetic algorithm --- normal cloud model --- 0-1 knapsack problems --- elite strategy --- diversity maintenance --- material handling path --- artificial bee colony algorithm (ABC) --- urban design --- entropy --- evolutionary algorithms (EAs) --- monarch butterfly optimization --- numerical simulation --- architecture --- set-union knapsack problem --- Wilcoxon test --- convolutional neural network --- global position updating operator --- particle swarm optimization --- computation --- minimum load coloring --- topology structure --- adaptive multi-swarm --- minimum total dominating set --- mutation operation --- shape grammar --- greedy optimization algorithm --- ?-Hilbert space --- genetic algorithm --- large scale optimization --- large-scale optimization --- NSGA-II-DV-Hop --- constrained optimization problems (COPs) --- first-arrival picking --- transfer function --- SPEA 2 --- stochastic ranking (SR) --- wireless sensor networks (WSNs) --- acceleration search --- convergence point --- fuzzy c-means --- evolutionary algorithm --- success rates --- Artificial bee colony --- particle swarm optimizer --- random weight --- range detection --- adaptive weight --- large-scale --- automatic identification --- cloud model --- swarm intelligence --- evolutionary multi-objective optimization --- DV-Hop algorithm --- bat algorithm (BA) --- Friedman test --- quantum uncertainty property --- facility layout design --- local search --- deep learning --- Y conditional cloud generator --- benchmark functions --- discrete algorithm --- dispatching rule --- DE algorithm --- nonlinear convergence factor --- energy-efficient job shop scheduling --- t-test --- evolution --- dimension learning --- global optimization --- confidence term --- elephant herding optimization --- moth search algorithm --- evolutionary