Limiting the soil degradational impacts of wildfire in pine and eucalyptus forests in Portugal: A comparison of alternative post-fire management practices

In newly burnt and unburnt pine and eucalyptus forest in Portugal, overland flow and soil losses were monitored to assess the impacts of the following post-fire treatments: application of different quantities of logging litter; rip-ploughing compared with minimum tillage prior to planting eucalyptus seedlings; and clearance of pine needles and vegetation. Eucalyptus logging litter reduced soil losses by up to 95 per cent. The impact of pine logging litter was equivocal, but removal of pine needles increased soil losses elevenfold. Implications for soil longevity, soil quality and land management strategy are discussed.     

A simple parameterization of sub-grid scale open water for climate models

The effects of small fractions ( < 30%) of open water covering a grid element are currently neglected even in atmospheric general circulation models (AGCMs) which incorporate complex land surface parameterization schemes. Here, a method for simulating sub-grid scale open water is proposed which permits any existing land surface model to be modified to account for open water. This new parameterization is tested as an addition to an advanced land surface scheme and, as expected, is shown to produce general increases in the surface latent heat flux at the expense of the surface sensible heat flux. Small changes in temperature are associated with this change in the partitioning of available energy which is driven by an increase in the wetness of the grid element. The sensitivity of the land surface to increasing amounts of open water is dependent upon the type of vegetation represented. Dense vegetation (with a high leaf area index) is shown to complicate the apparently simple model sensitivity and indicates that more advanced methods of incorporating open water into AGCMs need to be considered and compared against the parameterization suggested here. However, the sensitivity of one land surface model to incorporating open water is large enough to warrant consideration of its incorporation into climate models.     

Towards an operational system for oil-spill forecast over Spanish waters: initial developments and implementation test

The ESEOO Project, launched after the Prestige crisis, has boosted operational oceanography capacities in Spain, creating new operational oceanographic services and increasing synergies between these new operational tools and already existing systems. In consequence, the present preparedness to face an oil-spill crisis is enhanced, significantly improving the operational response regarding ocean, meteorological and oil-spill monitoring and forecasting. A key aspect of this progress has been the agreement between the scientific community and the Spanish Search and Rescue Institution (SASEMAR), significantly favoured within the ESEOO framework. Important achievements of this collaboration are: (1) the design of protocols that at the crisis time provide operational state-of-the-art information, derived from both forecasting and observing systems; (2) the establishment, in case of oil-spill crisis, of a new specialized unit, named USyP, to monitor and forecast the marine oceanographic situation, providing the required met-ocean and oil-spill information for the crisis managers. The oil-spill crisis scenario simulated during the international search and rescue Exercise "Gijón-2006", organized by SASEMAR, represented an excellent opportunity to test the capabilities and the effectiveness of this USyP unit, as well as the protocols established to analyze and transfer information. The results presented in this work illustrate the effectiveness of the operational approach, and constitute an encouraging and improved base to face oil-spill crisis.     

Application of HF radar currents to oil spill modelling

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed. This method is applied to data collected during the Galicia HF Radar Experience. This experiment was carried out to explore the capabilities of this technology for operational monitoring along the Spanish coast. Two long-range HF radar stations were installed and operated between November 2005 and February 2006 on the Galician coast. In addition, a drifter buoy was released inside the coverage area of the radar. The HF radar currents, as well as numerical wind data were used to simulate the buoy trajectory using the TESEO oil spill transport model. In order to evaluate the contribution of HF radar currents to trajectory analysis, two simulation alternatives were carried out. In the first one, wind data were used to simulate the motion of the buoy. In the second alternative, surface currents from the HF radar were also taken into account. For each alternative, the model was calibrated by means of the global optimization algorithm SCEM-UA (Shuffled Complex Evolution Metropolis) in order to obtain the probability density function of the model parameters. The buoy trajectory was computed for 24 h intervals using a Monte Carlo approach based on the results provided in the calibration process. A bivariate kernel estimator was applied to determine the 95% confidence areas. The analysis performed showed that simulated trajectories integrating HF radar currents are more accurate than those obtained considering only wind numerical data. After a 24 h period, the error in the final simulated position improves using HF radar currents. Averaging the information from all the simulated daily periods, the mean search and rescue area calculated using HF radar currents, is reduced by approximately a 62% in comparison with the search area calculated without these data. These results show the positive contribution of HF radar currents for trajectory analysis, and demonstrate that these data combined with atmospheric forecast models, are of value for trajectory analysis of oil spills or floating objects.     

Classification of marine bioregions on the east coast of South Africa

Marine bioregional planning requires a meaningful classification and spatial delineation of the ocean environment using biological and physical characteristics. The relative inaccessibility of much of the ocean and the paucity of directly measured data spanning entire planning regions mean that surrogate data, such as satellite imagery, are frequently used to develop spatial classifications. However, due to a lack of appropriate biological data, these classifications often rely on abiotic variables, which act as surrogates for biodiversity. The aim of this study was to produce a fine-scale bioregional classification, using multivariate clustering, for the inshore and offshore marine environment off the east coast of South Africa, adjacent to the province of KwaZulu-Natal and out to the boundary of the exclusive economic zone (EEZ), 200 nautical miles offshore. We used remotely sensed data of sea surface temperature, chlorophyll a and turbidity, together with interpolated bathymetry and continental-slope data, as well as additional inshore data on sediments, seabed oxygen and bottom temperature. A multivariate k-means analysis was used to produce a fine-scale marine bioregionalisation, with three bioregions subdivided into 12 biozones. The offshore classification was primarily a pelagic bioregionalisation, whereas the inshore classification (on the continental shelf) was a coupled benthopelagic bioregionalisation, owing to the availability of benthic data for this area. The resulting classification was used as a base layer for a systematic conservation plan developed for the province, and provided the methods for subsequent planning conducted for the entire South African EEZ. Validation of the classification is currently being conducted in marine research programmes that are sampling benthic biota and habitats in a sampling design stratified according to the biozones delineated in this study.     

Riverine dominance of a nearshore marine demersal food web: evidence from stable isotope and C/N ratio analysis

The Thukela Bank, KwaZulu-Natal, supports a diverse ecosystem and South Africa’s only prawn fishery. Oceanographic studies suggest riverine input is not important for the biology of this system, whereas biological studies suggest the contrary, with prawn catches increasing with increased fluvial run-off. The aim of this study was to determine (i) the importance of riverine and marine organic matter for the Thukela Bank food web; and (ii) whether there are seasonal changes in the Thukela River stable isotope values, and, if so, whether these are reflected in the isotope values of demersal organisms. Estuarine organic matter, sediments and demersal organisms were collected from several sites across the bank in the wet and dry seasons of 2008, 2009 and 2010. Marine particulate organic matter was also collected in 2010 and analysed for δ13C and δ15N, as well as C/N ratios. There were strong seasonal changes in isotopic values of organic matter and fauna, especially faunal δ13C. There was an apparent time-lag in organisms assimilating riverine organic matter isotopic values, with the isotopic signature of demersal organisms reflecting that of riverine organic matter from the previous season, which is likely the result of tissue turnover time. In 2010, Thukela Bank sediment organic matter was of riverine origin and this maintained the demersal food web. We conclude that Thukela River organic matter is an important input to the food web of the Thukela Bank, indicating that any future damming of the catchment area could have serious consequences for this ecosystem.     

Stochastic Lagrangian trajectory model for drifting objects in the ocean

The prediction of drifting object trajectories in the ocean is a complex problem plagued with uncertainties. This problem is usually solved simulating the possible trajectories based on wind and advective numerical and/or instrumental data in real time, which are incorporated into Lagrangian trajectory models. However, both data and Lagrangian models are approximations of reality and when comparing trajectory data collected from drifter exercises with respect to Lagrangian models results, they differ considerably. This paper introduces a stochastic Lagrangian trajectory model that allows quantifying the uncertainties related to: (i) the wind and currents numerical and/or instrumental data, and (ii) the Lagrangian trajectory model. These uncertainties are accounted for within the model through random model parameters. The quantification of these uncertainties consists in an estimation problem, where the parameters of the probability distribution functions of the random variables are estimated based on drifter exercise data. Particularly, it is assumed that estimated parameters maximize the likelihood of our model to reproduce the trajectories from the exercise. Once the probability distribution parameters are estimated, they can be used to simulate different trajectories, obtaining location probability density functions at different times. The advantage of this method is that it allows: (i) site specific calibration, and (ii) comparing uncertainties related to different wind and currents predictive tools. The proposed method is applied to data collected during the DRIFTER Project (eranet AMPERA, VI Programa Marco), showing very good predictive skills.     

The population genetic structure of the waratah anemone (Actinia tenebrosa) around New Zealand

The genetic structure of populations is often shaped by the reproductive system and larval properties of the species. The waratah anemone (Actinia tenebrosa) reproduces through both asexual clones, which have very short-distance dispersal, and sexual larvae, which are believed to disperse much greater distances. The impact of this mixed strategy on the New Zealand population structure of Actinia tenebrosa was investigated using microsatellite markers. The analysis incorporated 24 sampling locations from around New Zealand and one Australian location, using four microsatellite markers, n = 420. We observed low connectivity and high genetic differentiation between all locations sampled, with a distinct pattern of isolation by distance. The most distinct grouping of locations sampled was the north-east of the North Island from Cape Reinga to East Cape, which was identified by SAMOVA and STRUCTURE analyses as being moderately diverged from the remainder of the country. A tentative correlation was observed between genetic clustering and biogeographic regionalisation, where the distribution of a number of genetic clusters matched previously defined biogeographic regions. Within each location sampled, large numbers of clones were present and a latitudinal cline was observed in the relative contribution of asexually and sexually generated recruits, with an increase in asexual recruits on the South Island's east coast.