Trapping of Rhizophora mangle Propagules by Coexisting Early Successional Species

Distributions of mangroves in coastal wetlands are influenced by abiotic conditions and the net effect of biotic interactions, including competition, facilitation, and consumer pressure. In coastal wetlands, early successional shrubs, herbs, and grasses may facilitate recruitment of mangroves through multiple mechanisms, including amelioration of environmental conditions, propagule trapping, and structural support. In Mosquito Lagoon, FL, we observed an aggregated distribution of Rhizophora mangle propagules along vegetated shorelines with Batis maritima and Sarcocornia perennis and hypothesized that this distribution was a result of propagule trapping by the vegetation. We designed a field experiment to evaluate retention of R. mangle propagules on vegetated and unvegetated shorelines in Mosquito Lagoon. Significant differences were found in the retention time of mangrove propagules at each shoreline type, with vegetated shorelines retaining propagules significantly longer than unvegetated shorelines. Results from this study help to define facilitative mechanisms which may be important in successional processes of coastal wetlands and have direct restoration applications. Successful recovery of mangroves at restoration sites may be facilitated by establishment of B. maritima and S. perennis, when natural propagule sources are available, or through planting mangrove seedlings into existing stands of these halophytes when restoration areas are propagule-limited.     

A spatial statistical analysis of the occurrence of earthquakes along the Red Sea floor spreading: clusters of seismicity

The aim of this study is to apply spatial pattern analysis techniques to a seismic data catalog of earthquakes beneath the Red Sea to try and detect clusters and explore global and local spatial patterns in the occurrence of earthquakes over the years from 1900 to 2009 using a geographical information system (GIS). The spatial pattern analysis techniques chosen for this study were quadrant count analysis, average nearest neighbor, global Moran’s I, Getis–Ord general G, Anselin Local Moran’s I, Getis–Ord Gi*, kernel density estimation, and geographical distributions. Each of these techniques was implemented in the GIS so that computations could be carried out quickly and efficiently. Results showed that (1) these techniques were capable of detecting clusters in the spatial patterns of the occurrence of the earthquakes; (2) both global and local spatial statistics indicate that earthquakes were clustered in the study area beneath the Red Sea; (3) earthquakes with higher magnitudes on the Richter scale were notably concentrated in the central and southern parts of the Red Sea where seismic activities were most active; and (4) earthquakes with moderate magnitudes on the Richter scale were particularly concentrated in the northern part of the Red Sea where there is an area of late-stage continental rifting comprised of a broad trough without a recognizable spreading center, although there were several small, isolated deep troughs. We conclude that the pattern analysis techniques applied to the seismic data catalog of earthquakes beneath the Red Sea could detect clusters in the occurrence of earthquakes from 1900 to 2009.     

A comparison of a GCM response to historical anthropogenic land cover change and model sensitivity to uncertainty in present-day land cover representations

This study assesses the sensitivity of the fully coupled NCAR-DOE PCM to three different representations of present-day land cover, based on IPCC SRES land cover information. We conclude that there is significant model sensitivity to current land cover characterization, with an observed average global temperature range of 0.21 K between the simulations. Much larger contrasts (up to 5 K) are found on the regional scale; however, these changes are largely offsetting on the global scale. These results show that significant biases can be introduced when outside data sources are used to conduct anthropogenic land cover change experiments in GCMs that have been calibrated to their own representation of present-day land cover. We conclude that hybrid systems that combine the natural vegetation from the native GCM datasets combined with human land cover information from other sources are best for simulating such impacts. We also performed a prehuman simulation, which had a 0.39 K ~higher average global temperature and, perhaps of greater importance, temperature changes regionally of about 2 K. In this study, the larger regional changes coincide with large-scale agricultural areas. The initial cooling from energy balance changes appear to create feedbacks that intensify mid-latitude circulation features and weaken the summer monsoon circulation over Asia, leading to further cooling. From these results, we conclude that land cover change plays a significant role in anthropogenically forced climate change. Because these changes coincide with regions of the highest human population this climate impact could have a disproportionate impact on human systems. Therefore, it is important that land cover change be included in past and future climate change simulations.     

Sorption characteristics of peat of Brunei Darussalam IV: equilibrium,thermodynamics and kinetics of adsorption of methylene blue and malachite green dyes from aqueous solution

Peat of Brunei Darussalam shows a great potential for the removal of methylene blue (MB) and malachite green (MG) dyes from aqueous solution. Carefully controlled batch experiments performed by changing one parameter at a time indicate that the optimum time periods of agitation and settling required for maximum removal of MB are 2.0 and 1.0 h, respectively, while these values for MG are 4.0 and 1.0 h, respectively. The optimum pH is determined to be the ambient value, and under the optimum conditions, 90 % removal of both dyes was determined under laboratory conditions. The equilibrium adsorption data analyzed for various isotherm models suggest that the Sips and Redlich–Peterson (R–P) models are valid for MB and MG, respectively. Further, thermodynamic studies show that the adsorption of both dyes on peat is spontaneous and endothermic. The adsorption capacities (q _max) of MB and MG dyes on peat are 0.45 and 0.31 mmol g^?1, respectively. Characterization of the surfaces of peat before and after treatment of dyes by SEM and FTIR provides conclusive evidence of adsorption of both dyes. Kinetics studies indicate that the adsorption of both MB and MG dyes is favored toward the pseudo-second-order model, with a little contribution of MG to the pseudo-first-order model. These results suggest that peat is a potential low-cost adsorbent for the removal of MB and MG dyes.