Seasonal storage of nutrients by perennial herbaceous species in undisturbed and disturbed deciduous hardwood forests

Question: Pollution and eutrophication of surface water is increasingly a problem in agricultural landscapes. Do intact (relatively undisturbed) and degraded forests differ in seasonal nutrient storage and therefore potential to ameliorate nutrient pollution? Location: United States, Midwestern region. Methods: We used three sets of paired plots, where intact plots were located close to disturbed woodlands. Herbaceous perennials located in eight 0.25 m2 quadrats in the plots were harvested (in spring and mid-summer), dried, separated into above- and below-ground plant parts, and weighed to determine biomass. Nitrogen, phosphorus and potassium content of the plant tissues were then determined, and these data combined with biomass to estimate nutrient storage. Results: In spring, intact sites had 62% greater above-ground biomass than disturbed sites and 75% greater below-ground biomass. In summer, below-ground biomass of intact plots was still much greater than that of disturbed plots (73 percent), but above-ground biomass was similar. Nutrient tissue concentration generally did not differ, nor did soil nutrient levels. The disturbed sites were largely missing one group of species, the spring ephemerals, and this accounted for the difference in biomass and nutrient storage between sites. Conclusions: Relatively undisturbed woodlands in our study had a much greater capacity to store nutrients, and therefore ameliorate nutrient pollution, in early spring. This is significant because spring is also the time of highest potential leaching of nutrients into surface water.This is the peer-reviewed version of the following article: Mabry, Cathy M., Michaeleen E. Gerken, and Janette R. Thompson. "Seasonal storage of nutrients by perennial herbaceous species in undisturbed and disturbed deciduous hardwood forests." Applied Vegetation Science 11, no. 1 (2008): 37-44, which has been published in final form at DOI: 10.1111/j.1654-109X.2008.tb00202.x. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Copyright 2007 IAVS; Opulus Press Uppsala. Posted with permission

Genetic analyses of diverse populations improves discovery for complex traits.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities

Genetic analyses of diverse populations improves discovery for complex traits.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities