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Promoting ACademic Excellence in Mathematics and Science for Workers of the 21st Century (PACE) was a consortium project made up of Indiana University Northwest, the Gary Community Schools, and the Merrillville Community Schools. The focus of this project was to prepare teachers and curricula for Tech Prep mathematics and science courses for the two school districts. The courses and course units prepared by the project are intended to promote the Core 40 Competencies of the Indiana Department of Education for High School courses. This document contains units for biology designed to provide students with an overview of assorted biological fields such as genetics, classification, ecology, conservation, microbiology, and detailed plant and animal studies. The course advocates practical application, inquiry, exploration, and collaborative participation. Units are as follows: (1) Scientific Potpourri; (2) Microorganisms; (3) Cell Growth and Reproduction; (4) Plant Growth and Reproduction; (5) Genetics; (6) Nutrition; (7) Human Environmental Awareness; (8) Ecology; (9) Natural Resources; and (10) Water. (JRH)

In boreal forests where the fire return interval is long, the high structural variability of stands may affect wood traits. Here, we build on earlier work that revealed a difference in wood mechanical traits of black spruce between regular (regenerated from fire in the last 200 years) and irregular (undisturbed by fire for at least 200 years) stands. This study aimed to identify the ecological drivers of this variation in wood traits. To do so, we first sought to corroborate existing results on the effects of stand structure induced by the time since the last stand-replacing fire (TSLF) on wood mechanical stiffness in the eastern boreal forest of Canada. Results confirmed that black spruce from regular stands tend to produce wood with higher modulus of elasticity (MOE) than those from irregular stands. For both regular and irregular stands, we compared a set of linear models that were defined a priori to determine the structural and site productivity variables having the largest influence on MOE. The ‘growth efficiency index’ (aboveground woody biomass production per unit leaf area) was the best predictor of MOE variation among regular stands. For irregular stands, the model with TSLF as the sole explanatory variable was a better predictor of MOE than any other candidate model. However, we did not find strong evidence of a direct relationship between TSLF and wood traits, since our best models explained a relatively small proportion of the variance. Our results suggest that differences in wood traits could be attributable to the seed or layer origin of the trees and/or to the length of time trees remain in the understory. We propose that intensive wood production strategies focus on stands of the first post-fire cohort.