Spondias tuberosa trees grown in tropical, wet environments are more susceptible to drought than those grown in arid environments.

In this study, we investigated the different responses of Spondias tuberosa (umbu) trees, which grow in two different ecological life zones in northeast Brazil: tropical wet and tropical arid ecosystems. We evaluated the responses of plants grown under humid and dry conditions by measuring the photosynthesis, water status, fluorescence parameters, carbon isotopes and antioxidant system activity. The higher net photosynthesis values were recorded contemporaneously with the lower VPD values. The highest internal-to-ambient CO2 concentration and the absence of typical changes in the fluorescence parameters suggested an onset of a nonstomatal limitation in the photosynthesis. Our results showed that umbu plants can adjust their antioxidant activity during the dry season as a defensive strategy against the deleterious effects of water stress. This evidence is supported by the observed modifications in the pigment concentrations, increased accumulation of hydrogen peroxide and malondialdehyde, high levels of electrolyte leakage, increased antioxidant activity, and decreased carbon isotope discrimination in the umbu trees during the dry season. Supported by multivariate analysis of variance, significantly effect of interaction between categorical months of collect and location predicts a strong ?dry season effect? on our dataset. Taken together, our data show that umbu trees grown in a wet tropical environment are more susceptible to drought, as compared with their tropical arid counterparts.

Assessing the risk of the evolution of resistance to pesticides using spatially complex simulation models.

2008

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

MAGGnet: an international network to foster mitigation of agricultural greenhouse gases.

Research networks provide a framework for review, synthesis and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a GHG research network referred to as MAGGnet (Managing Agricultural Greenhouse Gases Network) was established within the Croplands Research Group of the Global Research Alliance on Agricultural Greenhouse Gases (GRA). With involvement from 46 alliance member countries, MAGGnet seeks to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. To date, metadata from 315 experimental studies in 20 countries have been compiled using a standardized spreadsheet. Most studies were completed (74%) and conducted within a 1-3-year duration (68%). Soil carbon and nitrous oxide emissions were measured in over 80% of the studies. Among plant variables, grain yield was assessed across studies most frequently (56%), followed by stover (35%) and root (9%) biomass. MAGGnet has contributed to modeling efforts and has spurred other research groups in the GRA to collect experimental site metadata using an adapted spreadsheet. With continued growth and investment, MAGGnet will leverage limited-resource investments by any one country to produce an inclusive, globally shared meta-database focused on the science of GHG mitigation.