Soil organic carbon stocks in Veracruz State (Mexico) estimated using the 1:250,000 soil database of INEGI: biophysical contributions

Purpose

In this study, we quantified soil organic carbon (SOC) stocks and analyzed their relationship with biophysical factors and soil properties.

Materials and methods

The study region was Veracruz State, located in the eastern part of Mexico, covering an area of 72,410 km². A soil database that contains physicochemical analyses of soil horizons such as carbon concentration data was the source of information used in this study. The database consisted of 163 soil profiles representing 464 genetic horizons. Statistical analysis was used to investigate the effect of each factor (climate, altitude, slope) on SOC stock to 0.50 m depth and to assess differences in the distribution of SOC stock in terms of soil depth (0.0–0.20, 0.20–0.40, 0.40–0.60, 0.60–0.80, 0.80–1.0 m) and land use. In order to compute the spatial distribution of SOC stock to 0.50 m depth based on the soil sampling location, the kriging method was used.

Results and discussion

Results indicated that SOC stock (0.50 m depth) ranged between 0.44 and 41.2 kg C m^?2. Regression analysis showed that SOC stocks (0.50 m depth) are negatively correlated with temperature (r?=??0.38; P?<?0.001) and positively correlated with altitude (r?=?0.40; P?<?0.001) and slope (r?=?0.40; P?<?0.001). In addition, by multiple regression, temperature combined with precipitation explained more SOC stock variations (r?=?0.43; P?<?0.001) than the regression model with precipitation (r?=?0.13; P?=?0.16) alone. Also, slope combined with temperature and precipitation explained more SOC stock variations (r?=?0.46; P?<?0.001) than the regression model with slope alone. Forest lands, grasslands, and croplands have higher SOC stocks in the 0.0–0.20-m soil layer than in deeper layers. On average, forest lands, grasslands, croplands, and other lands (wetland and dunes) had a SOC stock of 13.6, 14.6, 15.1, and 8.5 kg C m^?2 at 1 m depth, respectively. Soil color correlated (?0.25 ≤ r ≤ ?0.89) with SOC content.

Conclusions

Overall, these results indicate the influence of major interactions between biophysical factors and SOC stocks. This research indicated that SOC stock decreased with soil depth, but with slight variations depending on land use. Thus, there remains a need for more SOC data that include an improved distribution of soil sampling points in order to entirely understand the contributions of biophysical factors to SOC stocks in Veracruz State.     

Implications of SNP weighting on single‐step genomic predictions for different reference population sizes

We investigated the importance of SNP weighting in populations with 2,000 to 25,000 genotyped animals. Populations were simulated with two effective sizes (20 or 100) and three numbers of QTL (10, 50 or 500). Pedigree information was available for six generations; phenotypes were recorded for the four middle generations. Animals from the last three generations were genotyped for 45,000 SNP. Single‐step genomic BLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used to estimate genomic EBV using a genomic relationship matrix ( G ). The WssGBLUP performed better in small genotyped populations; however, any advantage for WssGBLUP was reduced or eliminated when more animals were genotyped. WssGBLUP had greater resolution for genome‐wide association (GWA) as did increasing the number of genotyped animals. For few QTL, accuracy was greater for WssGBLUP than ssGBLUP; however, for many QTL, accuracy was the same for both methods. The largest genotyped set was used to assess the dimensionality of genomic information (number of effective SNP). The number of effective SNP was considerably less in weighted G than in unweighted G . Once the number of independent SNP is well represented in the genotyped population, the impact of SNP weighting becomes less important.