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    Complexity in ecology and conservation : mathematical, statistical, and computational challenges (2006)
    American Institute of Biological Sciences
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © American Institute of Biological Sciences, 2005. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 55 (2005): 501–510, doi:10.1641/0006-3568(2005)055[0501:CIEACM]2.0.CO;2.
    Description: Creative approaches at the interface of ecology, statistics, mathematics, informatics, and computational science are essential for improving our understanding of complex ecological systems. For example, new information technologies, including powerful computers, spatially embedded sensor networks, and Semantic Web tools, are emerging as potentially revolutionary tools for studying ecological phenomena. These technologies can play an important role in developing and testing detailed models that describe real-world systems at multiple scales. Key challenges include choosing the appropriate level of model complexity necessary for understanding biological patterns across space and time, and applying this understanding to solve problems in conservation biology and resource management. Meeting these challenges requires novel statistical and mathematical techniques for distinguishing among alternative ecological theories and hypotheses. Examples from a wide array of research areas in population biology and community ecology highlight the importance of fostering synergistic ties across disciplines for current and future research and application.
    Description: This paper is the result of a National Science Foundation (NSF) workshop on quantitative environmental and integrative biology (DEB-0092081). J. L. G. would like to acknowledge financial support from the NSF (DEB-0107555).
    Keywords: Ecological complexity ; Quantitative conservation biology ; Cyberinfrastructure ; Metadata ; Semantic Web
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: 577104 bytes
    Format: application/pdf
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  • 2
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    Simulating social-ecological systems : the Island Digital Ecosystem Avatars (IDEA) consortium (2016)
    BioMed Central
    Details
    Publication Date: 2022-05-26
    Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in GigaScience 5 (2016): 14, doi:10.1186/s13742-016-0118-5.
    Description: Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine–terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.
    Description: Work was supported in part by: the Institute of Theoretical Physics and the Pauli Center at ETH Zurich; the US National Science Foundation (NSF Moorea Coral Reef Long Term Ecological Research Site, OCE-1236905; Socio-Ecosystem Dynamics of Natural-Human Networks on Model Islands, CNH-1313830; Coastal SEES: Adaptive Capacity, Resilience, and Coral Reef State Shifts in Social-ecological Systems, OCE-1325652, OCE-1325554); the Gordon and Betty Moore Foundation (Berkeley Initiative in Global Change Biology; Genomic Standards Consortium); Courtney Ross and the Ross Institute; UC Berkeley Vice Chancellor for Research; CRIOBE; and the France Berkeley Fund (FBF 2014-0015).
    Keywords: Computational ecology ; Biodiversity ; Genomics ; Biocode ; Earth observations ; Social-ecological system ; Ecosystem dynamics ; Climate change scenarios ; Predictive modeling
    Repository Name: Woods Hole Open Access Server
    Type: Article
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