Institution
University of Alaska Fairbanks
Education•Fairbanks, Alaska, United States•
About: University of Alaska Fairbanks is a(n) education organization based out in Fairbanks, Alaska, United States. It is known for research contribution in the topic(s): Arctic & Population. The organization has 7106 authors who have published 17049 publication(s) receiving 750590 citation(s). The organization is also known as: UAF & University of Alaska, Fairbanks.
Topics: Arctic, Population, Permafrost, Sea ice, Tundra
Papers published on a yearly basis
Papers
More filters
[...]
University of Wisconsin-Madison1, University of Maryland, College Park2, Carnegie Institution for Science3, National Center for Atmospheric Research4, University of Alaska Fairbanks5, Woods Hole Oceanographic Institution6, Stanford University7, University of Bristol8, University of Illinois at Urbana–Champaign9
TL;DR: Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity.
Abstract: Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet’s resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.
8,813 citations
[...]
Stockholm Environment Institute1, Stockholm University2, Australian National University3, University of Alaska Fairbanks4, Université catholique de Louvain5, University of East Anglia6, Wageningen University and Research Centre7, Royal Swedish Academy of Sciences8, Potsdam Institute for Climate Impact Research9, University of Oxford10, James Cook University11, Arizona State University12, Royal Institute of Technology13, University of Minnesota14, University of Vermont15, Stockholm International Water Institute16, California State University San Marcos17, Goddard Institute for Space Studies18, Commonwealth Scientific and Industrial Research Organisation19, University of Arizona20, Max Planck Society21
TL;DR: Identifying and quantifying planetary boundaries that must not be transgressed could help prevent human activities from causing unacceptable environmental change, argue Johan Rockstrom and colleagues.
Abstract: Identifying and quantifying planetary boundaries that must not be transgressed could help prevent human activities from causing unacceptable environmental change, argue Johan Rockstrom and colleagues.
7,735 citations
[...]
University of Buenos Aires1, University of Alaska Fairbanks2, University of Chile3, University of California, Berkeley4, Environmental Defense Fund5, National Autonomous University of Mexico6, Technische Universität München7, New Mexico State University8, Duke University9, Arizona State University10, University of Notre Dame11, Stanford University12, Colorado State University13, Commonwealth Scientific and Industrial Research Organisation14
TL;DR: This study identified a ranking of the importance of drivers of change, aranking of the biomes with respect to expected changes, and the major sources of uncertainties in projections of future biodiversity change.
Abstract: Scenarios of changes in biodiversity for the year 2100 can now be developed based on scenarios of changes in atmospheric carbon dioxide, climate, vegetation, and land use and the known sensitivity of biodiversity to these changes. This study identified a ranking of the importance of drivers of change, a ranking of the biomes with respect to expected changes, and the major sources of uncertainties. For terrestrial ecosystems, land-use change probably will have the largest effect, followed by climate change, nitrogen deposition, biotic exchange, and elevated carbon dioxide concentration. For freshwater ecosystems, biotic exchange is much more important. Mediterranean climate and grassland ecosystems likely will experience the greatest proportional change in biodiversity because of the substantial influence of all drivers of biodiversity change. Northern temperate ecosystems are estimated to experience the least biodiversity change because major land-use change has already occurred. Plausible changes in biodiversity in other biomes depend on interactions among the causes of biodiversity change. These interactions represent one of the largest uncertainties in projections of future biodiversity change.
7,686 citations
[...]
University of Melbourne1, Stony Brook University2, City University of New York3, Princeton University4, University of Lausanne5, University of California, Berkeley6, University of Alaska Fairbanks7, National Institute of Water and Atmospheric Research8, Commonwealth Scientific and Industrial Research Organisation9, University of São Paulo10, University of Missouri11, Consejo Nacional de Ciencia y Tecnología12, University of Kansas13, Landcare Research14, AT&T15, McGill University16, James Cook University17, Swiss Federal Institute for Forest, Snow and Landscape Research18
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
6,718 citations
[...]
Western Washington University1, University of Alaska Fairbanks2, United States Forest Service3, University of Zurich4, Centre national de la recherche scientifique5, Natural Environment Research Council6, University of Notre Dame7, École Normale Supérieure8, Columbia University9, University of Helsinki10, United States Geological Survey11, University of Michigan12, Swedish University of Agricultural Sciences13, Landcare Research14
TL;DR: Understanding this complexity, while taking strong steps to minimize current losses of species, is necessary for responsible management of Earth's ecosystems and the diverse biota they contain.
Abstract: Humans are altering the composition of biological communities through a variety of activities that increase rates of species invasions and species extinctions, at all scales, from local to global. These changes in components of the Earth's biodiversity cause concern for ethical and aesthetic reasons, but they also have a strong potential to alter ecosystem properties and the goods and services they provide to humanity. Ecological experiments, observations, and theoretical developments show that ecosystem properties depend greatly on biodiversity in terms of the functional characteristics of organisms present in the ecosystem and the distribution and abundance of those organisms over space and time. Species effects act in concert with the effects of climate, resource availability, and disturbance regimes in influencing ecosystem properties. Human activities can modify all of the above factors; here we focus on modification of these biotic controls. The scientific community has come to a broad consensus on many aspects of the re- lationship between biodiversity and ecosystem functioning, including many points relevant to management of ecosystems. Further progress will require integration of knowledge about biotic and abiotic controls on ecosystem properties, how ecological communities are struc- tured, and the forces driving species extinctions and invasions. To strengthen links to policy and management, we also need to integrate our ecological knowledge with understanding of the social and economic constraints of potential management practices. Understanding this complexity, while taking strong steps to minimize current losses of species, is necessary for responsible management of Earth's ecosystems and the diverse biota they contain.
6,315 citations
Authors
Showing all 7106 results
Name | H-index | Papers | Citations |
---|---|---|---|
George Perry | 139 | 923 | 77721 |
Lei Zhang | 135 | 2240 | 99365 |
Peter M. Vitousek | 127 | 352 | 96184 |
F. Stuart Chapin | 123 | 375 | 86236 |
William C. Knowler | 105 | 427 | 68336 |
Bernhard Schmid | 103 | 460 | 46419 |
Gordon E. Brown | 100 | 454 | 32152 |
Xiongwei Zhu | 96 | 403 | 34715 |
Jing Zhang | 95 | 1271 | 42163 |
K. Rawlins | 91 | 415 | 26589 |
John P. Smol | 91 | 655 | 41366 |
Daniel P. Costa | 89 | 531 | 26309 |
Gary Parker | 89 | 409 | 25543 |
Joshua P. Schimel | 83 | 187 | 29476 |
Pamela A. Matson | 82 | 188 | 48741 |