Environmetrics Silver Anniversary Special Issue

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  • Author: Statistics Views
  • Date: 30 December 2014

With the current issue, Environmetrics completes its 25th year of operation, and to celebrate, Walter W. Piegorsch and Peter Guttorp present a Special Issue on the past, present, and future of environmetrics as an endeavour. Readers may recall that the journal began in 1990 as a response to the growing need for modern quantitative methods that help understand environmental problems. Founding editors A. H. El-Shaarawi and I. B. MacNeill responded with gusto: Issue 1 of Volume 1 in 1990 contained an extensive suite of articles from the First International Conference on Statistical Methods for the Environmental Sciences, held 4–7 April 1989, in Cairo, Egypt.

thumbnail image: Environmetrics Silver Anniversary Special Issue

From those auspicious beginnings, the journal has ridden forward on a wave of ever-increasing technological development, ‘big’ data acquisition, multi-dimensional environmental challenges, and even into a new millennium. To celebrate this quarter century of growth and advancement, this 25th volume Special Anniversary Issue collects together a variety of perspectives on what environmetrics is and what it can become.

The issue begins with a series of contributions on methodology for spatial data, a common theme in modern environmetrics. Huque et al. lead with a study of how covariate measurement error—an ongoing and growing concern with environmental epidemiology data—can affect geographically indexed information. Feng et al. next give models for spatial ordinal and spatial proportional data, followed by Jun et al. and their study of Bayesian models for spatial processes. The variety of the three articles, while interrelated by the spatial data theme, illustrates the broad environmetric aspects and future potential of this topic area.

We next move into applications in forestry and ecology, also bellwether areas of environmental statistics. Finley et al. bridge the transition with a description of dynamic spatial models for analysis of forest stand tables. Schliep et al. follow with hierarchical Bayesian tree growth models, helping to again illustrate the value and potential Bayesian models bring to environmetric analysis. Cai et al. next explore stochastic models that focus on associations between crop development and effects from climate change. Climate change and climate disruption are, of course, important concerns in modern environmental science. Reich and Gardner complete the Special Issue with a return to spatial modeling, this time motivated by the long-standing ecological question of properly analyzing capture–recapture data. In all, the articles give us a sense of how environmental matters drive development of statistical and mathematical methods to understand the associated data, a goal of Environmetrics from its very beginning. We look forward to seeing more such advances in these and other new, emerging areas—environmental/ecological informatics, environmental forensics, and environmental justice come to mind, to name just a few—over the next 25 years and beyond!

Read Walter W. Piegorsch's editorial on the 25th anniversary of Environmetrics from the start of 2014 here.

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