No abstract

No abstract

Our objective is to provide an optimistic strategy for reversing soil degradation by increasing public and private research efforts to understand the role of soil biology, particularly microbiology, on the health of our world's soils. We begin by defining soil quality/soil health (which we consider to be interchangeable terms), characterizing healthy soil resources, and relating the significance of soil health to agroecosystems and their functions. We examine how soil biology influences soil health and how biological properties and processes contribute to sustainability of agriculture and ecosystem services. We continue by examining what can be done to manipulate soil biology to: (i) increase nutrient availability for production of high yielding, high quality crops; (ii) protect crops from pests, pathogens, weeds; and (iii) manage other factors limiting production, provision of ecosystem services, and resilience to stresses like droughts. Next we look to the future by asking what needs to be known about soil biology that is not currently recognized or fully understood and how these needs could be addressed using emerging research tools. We conclude, based on our perceptions of how new knowledge regarding soil biology will help make agriculture more sustainable and productive, by recommending research emphases that should receive first priority through enhanced public and private research in order to reverse the trajectory toward global soil degradation.

Good management of rangelands promotes C sequestration and reduces the likelihood of these ecosystems becoming net sources of CO2 As part of an ongoing study, soil was sampled in 2003 to investigate the long‐term effects of different livestock grazing treatments on soil organic carbon (SOC), total nitrogen (TN), and microbial communities. The three treatments studied (no grazing, EX; continuously, lightly grazed [10% utilization], CL; and continuously, heavily grazed [50% utilization], CH) have been imposed on a northern mixed‐grass prairie near Cheyenne, WY, for 21 yr. In the 10 yr since treatments were last sampled in 1993, the study area has been subject to several years of drought. In the 0 to 60 cm depth there was little change in SOC in the EX or CL treatments between 1993 and 2003, whereas there was a 30% loss of SOC in the CH treatment. This loss is attributed to plant community changes (from a cool‐season [C3] to a warm‐season [C4] plant dominated community) resulting in organic C accumulating nearer the soil surface, making it more vulnerable to loss. Soil TN increased in the EX and CL treatments between 1993 and 2003, but declined in the CH treatment. Differences in plant community composition and subsequent changes in SOC and TN may have contributed to microbial biomass, respiration, and N‐mineralization rates generally being greatest in CL and least in the CH treatment. Although no significant differences were observed in any specific microbial group based on concentrations of phospholipid fatty acid (PLFA) biomarkers, multivariate analysis of PLFA data revealed that microbial community structure differed among treatments. The CH grazing rate during a drought period altered plant community and microbial composition which subsequently impacted biogeochemical C and N cycles.

Ecological diversity indices are frequently applied to molecular profiling methods, such as terminal restriction fragment length polymorphism (T-RFLP), in order to compare diversity among microbial communities. We performed simulations to determine whether diversity indices calculated from T-RFLP profiles could reflect the true diversity of the underlying communities despite potential analytical artifacts. These include multiple taxa generating the same terminal restriction fragment (TRF) and rare TRFs being excluded by a relative abundance (fluorescence) threshold. True community diversity was simulated using the lognormal species abundance distribution. Simulated T-RFLP profiles were generated by assigning each species a TRF size based on an empirical or modeled TRF size distribution. With a typical threshold (1%), the only consistently useful relationship was between Smith and Wilson evenness applied to T-RFLP data (TRF-E var ) and true Shannon diversity (H), with correlations between 0.71 and 0.81. TRF-H and true H were well correlated in the simulations using the lowest number of species, but this correlation declined substantially in simulations using greater numbers of species, to the point where TRF-H cannot be considered a useful statistic. The relationships between TRF diversity indices and true indices were sensitive to the relative abundance threshold, with greatly improved correlations observed using a 0.1% threshold, which was investigated for comparative purposes but is not possible to consistently achieve with current technology. In general, the use of diversity indices on T-RFLP data provides inaccurate estimates of true diversity in microbial communities (with the possible exception of TRF-E var ). We suggest that, where significant differences in T-RFLP diversity indices were found in previous work, these should be reinterpreted as a reflection of differences in community composition rather than a true difference in community diversity.