Plant invasions research in Latin America: fast track to a more focused agenda

While many developed countries have invested heavily in research on plant invasions over the last 50 years, the immense region of Latin America has made little progress. Recognising this, a group of scientists working on plant invasions in Latin America met in Chile in late 2010 to develop a research agenda for the region based on lessons learned elsewhere. Our three main findings are as follows. (1) Globalisation is inevitable, but the resultant plant introductions can be slowed or prevented by effective quarantine and early intervention. Development of spatially explicit inventories, research on the invasion process and weed risk assessments can help prioritise and streamline action. (2) Eradication has limited application for plants and control is expensive and requires strict prioritisation and careful planning and evaluation. (3) Accepting the concept of novel ecosystems, new combinations of native and introduced species that no longer depend on human intervention, may help optimise invasive species management. Our vision of novel ecosystem management is through actions that: (a) maintain as much native biodiversity and ecosystem functionality as possible, (b) minimise management intervention to invasives with known impact, and (c) maximise the area of intervention. We propose the creation of a Latin American Invasive Plants Network to help focus the new research agenda for member countries. The network would coordinate research and training and establish funding priorities, develop and strengthen tools to share knowledge, and raise awareness at the community, governmental and intergovernmental levels about the social, economic and environmental costs of plant invasions.

Constraining the dark energy and smoothness parameter with type Ia supernovae and gamma-ray bursts

The existence of inhomogeneities in the observed Universe modifies the distance-redshift relations thereby affecting the results of cosmological tests in comparison to the ones derived assuming spatially uniform models. By modeling the inhomogeneities through a Zeldovich-Kantowski-Dyer-Roeder approach which is phenomenologically characterized by a smoothness parameter alpha, we rediscuss the constraints on the cosmic parameters based on type Ia supernovae (SNe Ia) and gamma-ray bursts (GRBs) data. The present analysis is restricted to a flat Lambda CDM model with the reasonable assumption that Lambda does not clump. A chi(2) analysis using 557 SNe Ia data from the Union2 compilation data (R. Amanullah et al., Astrophys. J. 716, 712 (2010).) constrains the pair of parameters (Omega(m), alpha) to Omega(m) = 0.27(-0.03)(+0.08) (2 sigma) and alpha >= 0.25. A similar analysis based only on 59 Hymnium GRBs (H. Wei, J. Cosmol. Astropart. Phys. 08 (2010) 020.) constrains the matter density parameter to be Omega(m) = 0.35(-0.24)(+0.62) (2 sigma) while all values for the smoothness parameter are allowed. By performing a joint analysis, it is found that Omega(m) = 0.27(-0.06)(+0.06) and alpha >= 0.52. As a general result, although considering that current GRB data alone cannot constrain the smoothness alpha parameter, our analysis provides an interesting cosmological probe for dark energy even in the presence of inhomogeneities.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.