Soil C and N changes with afforestation of grasslands across gradients of precipitation and plantation age

Afforestation, the conversion of unforested lands to forests, is a tool for sequestering anthropogenic carbon dioxide into plant biomass. However, in addition to altering biomass, afforestation can have substantial effects on soil organic carbon (SOC) pools, some of which have much longer turnover times than plant biomass. An increasing body of evidence suggests that the effect of afforestation on SOC may depend on mean annual precipitation (MAP). The goal of this study was to test how labile and bulk pools of SOC and total soil nitrogen (TN) change with afforestation across a rainfall gradient of 600-1500 mm in the Rio de la Plata grasslands of Argentina and Uruguay. The sites were all former grasslands planted with Eucalyptus spp. Overall, we found that afforestation increased (up to 1012 kg C x ha(-1) x yr(-1)) or decreased (as much as 1294 kg C x ha(-1) x yr(-1)) SOC pools in this region and that these changes were significantly related to MAP. Drier sites gained, and wetter sites lost, SOC and TN (r2 = 0.59, P = 0.003; and r2 = 0.57, P = 0.004, respectively). Labile C and N in microbial biomass and extractable soil pools followed similar patterns to bulk SOC and TN. Interestingly, drier sites gained more SOC and TN as plantations aged, while losses reversed as plantations aged in wet sites, suggesting that plantation age in addition to precipitation is a critical driver of changes in soil organic matter with afforestation. This new evidence implies that longer intervals between harvests for plantations could improve SOC storage, ameliorating the negative trends found in humid sites. Our results suggest that the value of afforestation as a carbon sequestration tool should be considered in the context of precipitation and age of the forest stand.     

Better estimates of soil carbon from geographical data: a revised global approach

Mitigation and Adaptation Strategies for Global Change - Soils hold the largest pool of organic carbon (C) on Earth; yet, soil organic carbon (SOC) reservoirs are not well represented in climate...     

Monitoring genotoxicity among gasoline station attendants and traffic enforcers in the City of Manila using the micronucleus assay with exfoliated epithelial cells

Some types of occupations involve high levels of exposure to potentially genotoxic gaseous and particulate substances from internal combustion engines used in motor vehicles. These occupational exposures may contribute to the development of many illnesses, usually through chromosomal change mechanisms that include strand breakage, deletions, sister chromatid exchange and non-disjunction. To determine the effect of occupational exposure in gasoline station attendants and traffic enforcers, the micronucleus test was used. Exfoliated oral mucosa cells from 18 gasoline station attendants, 18 traffic enforcers and 18 control subjects in the City of Manila were examined for micronucleated cell (MNC) frequency. Analysis of buccal cells showed that MNC frequencies in exposed individuals were significantly greater than in control subjects (p < or = 0.05). However, between gasoline station attendants and traffic enforcers, MNC frequencies of the two exposed groups exhibited no significant difference. No relation was also found between MNC frequency and any of the factors such as age, smoking habits, alcohol habits and working period. This was further confirmed in the multiple regression analysis which showed that only occupational exposure was a good predictor of MNC frequency. The results of this study suggest that gasoline station attendants and traffic enforcers, compared to the control individuals, are at a greater risk of chromosomal damage. For the assessment of chromosomal damage, the study, development, and standardization of tests are recommended for public institutions concerned with matters regarding environmental quality and community health.     

How to evaluate models: Observed vs. predicted or predicted vs. observed?

A common and simple approach to evaluate models is to regress predicted vs. observed values (or vice versa) and compare slope and intercept parameters against the 1:1 line. However, based on a review of the literature it seems to be no consensus on which variable (predicted or observed) should be placed in each axis. Although some researchers think that it is identical, probably because r² is the same for both regressions, the intercept and the slope of each regression differ and, in turn, may change the result of the model evaluation. We present mathematical evidence showing that the regression of predicted (in the y-axis) vs. observed data (in the x-axis) (PO) to evaluate models is incorrect and should lead to an erroneous estimate of the slope and intercept. In other words, a spurious effect is added to the regression parameters when regressing PO values and comparing them against the 1:1 line. Observed (in the y-axis) vs. predicted (in the x-axis) (OP) regressions should be used instead. We also show in an example from the literature that both approaches produce significantly different results that may change the conclusions of the model evaluation.