Citation frequency is often used in hiring and tenure decisions as an indicator of the quality of a researcher's publications. In this paper, we examine the influence of discipline, institution, journal impact factor, length of article, number of authors, seniority of author, and gender on citation rate of top-cited papers for academic faculty in geography and forestry departments. Self-citation practices and patterns of citation frequency across post-publication lifespan were also examined. Citation rates of the most-highly cited paper for all tenured forestry (N = 122) and geography (N = 91) faculty at Tech were compared. Foresters received significantly more citations than geographers (t = 2.46, P = 0.02) and more senior authors received more citations than junior researchers (r 2 = 0.14, P = 0.03). Articles published in journals with higher impact factors also received more citations (r 2 = 0.28, P = 0.00). The median self-citation rate was 10% and there was no temporal pattern to the frequency of citations received by an individual article (x 2 = 176). Our results stress the importance of only comparing citation rates within a given discipline and confirm the importance of author-seniority and journal rankings as factors that influence citation rate of a given article.

Given the economic importance of loblolly pine (Pinus taeda) in the southeastern US, there is a need to establish efficient methods of detecting potential nutrient deficiencies that may limit productivity. This study evaluated the use of remote sensing for macronutrient assessment in loblolly pine. Reflectance-based models were developed at two spatial scales: (1) a natural nutrient gradient across the species' range, and (2) localized fertilization and genotype treatments in North Carolina and Virginia. Fascicles were collected regionally from 237 samples of 3 flushes at 18 sites, and locally from 72 trees with 2 fertilization treatments and 6 genotypes. Sample spectral reflectance was calculated using a spectroradiometer, and nutrient concentrations were measured with dry combustion and wet chemical digestion. Results were analyzed statistically using nutrient correlations with reflectance and common vegetation indices, and partial least squares regression (PLSR). PLSR performed well at the regional scale, with R 2 values for nitrogen, phosphorus, potassium, calcium, and magnesium of 0. 81, 0.70, 0.68, 0.42, and 0.51, respectively. No model successfully predicted nutrients at local sites for any treatment or canopy stratum. This discrepancy implies that a large nutrient range and/or spatial scale may be necessary to model loblolly pine nutrients with spectral reflectance.