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David S Schimel

Publications and source records attributed to David S Schimel.

2 recordsLinked to original sources

A more representative community of ecologists

Ecologists play a crucial role in providing solutions to the challenges facing the world. For most of the history of the field, however, the science of ecology has been pursued by white men, and increasingly, by white women. This lack of diversity is untenable today, not only because it is socially unjust, but also because solving environmental problems requires diversity. Ecology as a science is an extremely rewarding and fun career choice for many, but how can the field recruit a more diverse workforce to do this important and gratifying work? Attracting and retaining future ecologists of color is the focus of this Forum. How do young people choose a career in ecology and environmental sciences? For many ecologists, environmental scientists and managers, and future natural resource professionals, an early field experience provides a crucial introduction and gateway. A sojourn at a field station, an extended field trip, or field expedition has introduced many of today’s professionals to their fields, but at the same time, a growing literature documents problematic behavior, discrimination, and other forms of harassment that have been far too frequently reported, and little attention has been given to conscious or implicit exclusion of students from diverse backgrounds. In their lead article, Bowser and Cid, two leading researchers and long-time champions of diversity in ecology, build on experience in long-running programs as well as the literature to diagnose challenges facing diverse youth, and present approaches to encourage, rather than discourage, further engagement. They describe affirmative and creative measures that foster a sense of inclusion and community among young scholars; this sense of belonging and empowerment allows many to advance to studies and careers in ecology and environmental science. In the subsequent six papers, authors explore topics either responding to, or inspired by, the lead paper. They explore alternatives to a field experience as a gateway to a career in ecology or environmental sciences through, for example, data science or the social sciences. Other comment papers describe challenges faced in the next phases of an academic career, barriers faced by specific cultural groups and the approaches, challenges, and outcomes of programs aiming to increase the diversity of the environmental STEM workforce. All responses sound a clarion call for change to hear and value different voices and perspectives to be heard and valued. These include (1) structural and cultural change to our institutions and reward structures; (2) developing and nurturing personal relationships among students and their mentors, within teams and in internships; (3) making entry to ecology inviting and making advancement in ecology free from systemic barriers; and (4) broadening our vision of ecology, and the ways we learn about the world’s ecosystems. The Ecological Society of America, the home for Ecological Applications , is committed to the diversity, equity and inclusion needed to tackle environmental challenges in unity (https://www.esa.org/esablog/2020/09/24/time-for-action-esa-initiates-a-diversity-equity-inclusion-and-justice-deij-task-force/). The world needs all available talent and perspectives to meet environmental challenges today. Ecological Applications has long published occasional papers on the profession of ecology and never ones more important or timely than these. The editorial team is proud to provide an outlet for the voices of our field, in all its current, if inadequate, diversity and honored to host the passionate and committed views of our authors.

Ecological Applications

Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica

The most important requirements for large-area environmental modeling are a tight integration between models and data, and a close match of the spatial scale at which the model is developed with the scale at which the model is to be applied. To better match the scale of data with that of the model, we propose a set of principles for the development of stochastic modeling systems based on linkage of deterministic models with GIS data. For modeling purposes, a region is usually rasterized into cells and the environmental conditions of those cells are specified by ranges or classes using GIS data layers. It is not necessary to simulate each and every GIS cell in the study area because many cells may have similar environmental conditions and can be grouped together to form cohorts. We define a cohort as the assembly of the cells sharing a unique combination of environmental conditions within the study region. Multiple model simulations can be performed for any given cohort. For each simulation, some of the parameter values can be randomly generated within the specified environmental conditions of the cohort according to a certain statistical distribution which, in turn, can be specified by GIS data layers. By this method the variance and covariance of environmental variables in space and time are integrated into the simulation processes with these modeling systems to make full use of the available data and to assess the uncertainties of the simulated results. An integrated simulation system between CENTURY model and GIS was developed to demonstrate the value of the concepts imbedded in stochastic simulation systems for large area studies.

Conference Paper