10.6084/m9.figshare.947682.v2 Adam Wilson Adam Wilson From imperfection to inference: issues of scale and uncertainty in global change biology figshare 2015 Global change ecology bayesian models fire ecology remote sensing species distribution models demographic models uncertainty Statistics Probability Plant Biology Bioinformatics Distributed Computing Applied Computer Science Environmental Science Ecology Biological Techniques Botany Climate Science Data Format 2015-05-20 21:45:01 Dataset https://figshare.com/articles/dataset/From_imperfection_to_inference_issues_of_scale_and_uncertainty_in_global_change_biology/947682 <p>Invited seminar to Department of Environmental Science, Policy, and Management colloqium at UC Berkeley.  File includes animations that are only visible when viewed with Adobe Acrobat.  </p> <p> </p> <p><strong>Abstract</strong></p> <p>Integrated research across biological scales is vital to understand and anticipate the impacts of global change on ecosystem function and biodiversity. There is now a plethora of ecological, natural history, climate, and remotely sensed data available to address this important issue. Integrating these disparate (and often ‘messy’) datasets into models across spatial, temporal, and biological scales is tantalizing but perilous. Using examples ranging from fire ecology in South Africa to three-toed woodpecker distributions in North America to high resolution maps of global cloud cover, I will discuss several important challenges that must be addressed to rigorously harness these data streams (and keep track of their uncertainties) for scientific progress and prudent decision-making.</p>