Call for nomination for the Lamberson Award 2017
The Rollie Lamberson Award celebrates the contribution of Professor Rollie Lamberson to the field of natural resource modeling and the growth of the Resource Modeling Association by recognizing each year the most outstanding paper in natural resource modeling in the previous two years. See http://resourcemodeling.org/lamberson/ or below for more details.
- Only current RMA members are eligible for the award.
- All papers published in Natural Resource Modeling during the previous two calendar years (namely 2015-2016) will be considered automatically provided at least one of the authors is a current member.
- Papers published in other journals may be nominated for consideration provided at least one of the co-authors is a current member. To be considered, the submission must comprise:
- an electronic version of the paper in English,
- a nominating letter specifying why the paper is deserving of the Rollie Lamberson Award. Criteria below.
Send your nominations to RMA presidence or to RMA contact from the website. The submission for the award 2017 will be closed on January 20, 2017.
The Lamberson prize will be delivered to the winners during the 2017 RMA conference to be held in Barcelona on June 6-9, 2017.
Ni hou! Don’t Miss Out on Guangzhou – deadlines approaching
World Conference on Natural Resource Modeling – June, 2018 Guangzhou, China
You want a career in marine biology but your maths is weak. Relax, the basic skills can be mastered.
Marine biology: Charting sea life
You want a career in marine biology but your maths is weak. Relax, the basic skills can be mastered.
- Nature 528, 295-297 (2015) doi:10.1038/nj7581-295a
- Published online 09 December 2015 Go to article
This article was originally published in the journal Nature
ESA SEEDS receives NSF Award to seed new Network for Next Generation Careers
From: Ecological Society of America: grants, jobs, news [ECOLOG-L@LISTSERV.UMD.EDU] on behalf of Liza Lester [llester@ESA.ORG] Sent: Wednesday, 16 September 2015 9:15 AM
To: ECOLOG-L@LISTSERV.UMD.EDU
Subject: [ECOLOG-L] ESA SEEDS receives NSF Award to seed new Network for Next Generation Careers
Read this release online: http://www.esa.org/esa/esa-receives-nsf-award-to-seed-new-network-for-next-generation-careers/
FOR IMMEDIATE RELEASE: Tuesday, 15 September 2015
Contact: Alison Mize, 202-833-8773 ext. 205, Alison@esa.org
The Ecological Society of America, in partnership with the Society for Conservation Biology (SCB), will create a new network of prospective employers, faculty and professional societies over the next eighteen months with a $48,000 grant from the National Science Foundation (NSF). The Next Generation Careers – Innovation in Environmental Biology Education (NGC) incubator project will explore undergraduate college career progression into environmental biology, including fields such as ecology, evolution, conservation, and natural resource management.
“We all know that academia is able to absorb only a limited number of biology graduates. A vast majority of graduates find their way into industry, government, or other applied and non-science jobs,” said Teresa Mourad, ESA’s Director of Education and Diversity Programs and Principal Investigator for the project. “What is not clear is how Biology students are being prepared for these rapidly evolving career tracks in environmental biology with an innovative mindset.”
New groups of professionals will be brought together that include academic faculty, industry, government, and non-profit organization personnel. By working together, the network will develop materials, programs and career development tracks designed for 21st century STEM professionals in environmental biology and inform the broader community of the nature of education and skills that are necessary for future jobs in this ever-changing field. This project addresses the goals and programs of NSF’s Improving Undergraduate STEM Education initiative, particularly the goal of building the professional STEM workforce for tomorrow.
The incubator project activities include surveys of biology department chairs, academic counselors, graduate schools as well as biology faculty and those at the nexus of biology and mathematics. Additionally, an analysis of job postings for entry-level positions in related jobs will seek to identify the most commonly sought skills for graduates with an associate’s or bachelor’s degree. Focus groups at selected disciplinary and professional scientific society meetings will also be organized to gather input.
The results will be presented at a workshop of participants from academia, private sector, government, and non-governmental organizations in the fall of 2016. Implications of the findings for underrepresented populations of students will be underscored.
“Recommendations generated at the workshop will help us establish the network of prospective employers, higher education and professional associations essential to invigorate career preparation programs,” said Geri Unger, SCB’s Executive Director and co-PI on the project. “This will enable us to identify what faculty need to effectively inspire, motivate and mentor new students and build new synergies across sectors to advance Next Generation careers in Environmental Biology and allied fields.”
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Book: A Primer in Biological Data Analysis and Visualization Using R
Description:
R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen’s extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences.
Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.
About the Author:
Gregg Hartvigsen is a professor in the Department of Biology at the State University of New York at Geneseo. He taught a workshop on network analysis using R at the National Institute for Mathematical and Biological Synthesis at the University of Tennessee, Knoxville, and was a visiting scientist and site reviewer for the Mathematical Biosciences Institute at Ohio State University. He also served as co-PI on a National Science Foundation training grant for undergraduate biology and mathematics.