Using Geotechnology to Estimate Annual Soil Loss Rate in the Brazilian Cerrado

Soil erosion is a serious environmental problem that has adversely affected the world’s food production through the reduction of land productivity and water availability. The present study estimated annual soil loss rate and its spatial distribution in the most important Brazil’s agricultural region, the Brazilian Cerrado, using Revised Soil Loss Equation (RUSLE) model into Geographic Information System (GIS) framework. For this purpose, the soil erosion annual rate was determined in function of RUSLE model factors: rainfall erosivity (R), soil erodibility (K), topography (LS), crop management (C) and supporting conservation practice (P). All factors were obtained from literature. They were processed and integrated into a GIS, resulting in a map of annual soil loss rate. The methodology applied showed acceptable precision and it was possible to identify the most susceptible areas to water erosion. The average estimated rate of soil loss for the entire Cerrado was 12.8 t∙ha−1∙yr−1. Large part of the Cerrado is under low soil loss zone corresponding to 79.91% of total surface area, while 15.70%, 3.74%, and 0.66% are under moderate, high, and very high, respectively. The average estimated rate of soil loss in areas used for silviculture was 52.1 t∙ha−1∙yr−1. In semi-perennial, perennial, and annual crops cultivation were 29.3, 23.9, and 9.8 t∙ha−1∙yr−1, respectively, while in the pasture was 13.3 t∙ha−1∙yr−1. Except for annual crops, all farm and silviculture areas showed average soil loss ranging from moderate to high rate. These results suggest that the implementation of more effective management techniques and conservation practices are necessary for the Cerrado to maintain and to improve land productivity by ensuring national and international food demands

DTM ASSESMENT IN SLOPE INSTABILITY MODELING

Uma parte dos métodos de previsão de escorregamentos na paisagem tem como base principal a topografia, que pode ser gerada sob diferentes formas e ferramentas. Assim, este trabalho teve como objetivo avaliar a eficiência de dois Modelos Digitais de Terreno (MDT’s) baseados nos pontos LiDAR e em curvas de nível em um mapeamento de áreas suscetíveis a escorregamentos rasos. Para avaliar os MDT’s, fez-se uso do modelo em base física SHALSTAB. Os testes foram realizados em uma bacia hidrográfica afetada por escorregamentos rasos deflagrados após intensa precipitação, em março de 2011, na área urbana do município de Antonina (PR), na parte Sul da Serra do Mar. Os dados das propriedades físicas do solo necessários foram obtidos no interior de uma das cicatrizes de escorregamento de 2011. No intuito de avaliar o mapa de suscetibilidade, foram comparados os padrões espaciais das classes de instabilidade previstas pelo SHALSTAB com o mapa de cicatrizes. Dentre os resultados foi verificado que um dos índices de validação apresentou melhor performance do MDT derivado do LiDAR, enquanto que no segundo foi constatado uma reduzida diferença entre os MDT’s, sendo que ambos demostraram uma similar distribuição na frequência de classes.Part of the landslide prediction methods in the landscape is mainly based on the topography, which can be generated in different forms and tools. Thus, tis paper aimed to assess the efficiency of two sets of Digital Terrain Model (DTM), based on LiDAR data, and on traditional contour lines in a mapping of areas susceptible to shallow landslides. To evaluate the DTMs, we used the physically based model, SHALSTAB. The tests were carried out in a watershed affected by shallow landslides caused by intensive rainfall during March 2011, in the urban area of Antonina municipality (Parana State), the southern part of the Serra do Mar mountain range. The physical soil properties data needed for the model consisted of two sets of values (literature) measured from 2011 landslide scars. In order to validate the landslide susceptibility maps, we compared the spatial pattern of instability classes predicted by SHALSTAB with the mapped landslide scars. To evaluate the susceptibility map, we compared the spatial patterns of instability classes provided by SHALSTAB with the maps of scars. Among the results, it was verified that in one of the validation indexes presented a better performance of LiDAR-derived DTM, whereas, the second index was identified a small difference between DTMs, also both demonstrated a similar distribution of class frequency

Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates

We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets of airborne light detection and ranging (lidar), including five multi-temporal and 610 single-date lidar datasets. Specifically, we (1) compared the fixed height and relative height methods for gap delineation and established a relationship between static and dynamic gaps (newly created gaps); (2) explored potential environmental/climate drivers explaining gap occurrence using generalized linear models; and (3) cross-related our findings to mortality estimates from 181 field plots. Our findings suggest that static gaps are significantly correlated to dynamic gaps and can inform about structural changes in the forest canopy. Moreover, the relative height outperformed the fixed height method for gap delineation. Well-defined and consistent spatial patterns of dynamic gaps were found over the Amazon, while also revealing the dynamics of areas never sampled in the field. The predominant pattern indicates 20–35% higher gap dynamics at the west and southeast than at the central-east and north. These estimates were notably consistent with field mortality patterns, but they showed 60% lower magnitude likely due to the predominant detection of the broken/uprooted mode of death. While topographic predictors did not explain gap occurrence, the water deficit, soil fertility, forest flooding and degradation were key drivers of gap variability at the regional scale. These findings highlight the importance of lidar in providing opportunities for large-scale gap dynamics and tree mortality monitoring over the Amazon

Nitrogen stable isotopes indicate differences in nitrogen cycling between two contrasting Jamaican montane forests

Background and aims The aim of this study is to enhance our knowledge of nitrogen (N) cycling and N acquisition in tropical montane forests through analysis of stable N isotopes (δ15N). Methods Leaves from eight common tree species, leaf litter, soils from three depths and roots were sampled from two contrasting montane forest types in Jamaica (mull ridge and mor ridge) and were analysed for δ15N. Results All foliar δ15N values were negative and varied among the tree species but were significantly more negative in the mor ridge forest (by about 2 ‰). δ15N of soils and roots were also more negative in mor ridge forests by about 3 ‰. Foliar δ15N values were closer to that of soil ammonium than soil nitrate suggesting that trees in these forests may have a preference for ammonium; this may explain the high losses of nitrate from similar tropical montane forests. There was no correlation between the rankings of foliar δ15N in the two forest types suggesting a changing uptake ratio of different N forms between forest types. Conclusions These results indicate that N is found at low concentrations in this ecosystem and that there is a tighter N cycle in the mor ridge forest, confirmed by reduced nitrogen availability and lower rates of nitrification. Overall, soil or root δ15N values are more useful in assessing ecosystem N cycling patterns as different tree species showed differences in foliar δ15N between the two forest types