Expedient Metrics to Describe Plant Community Change Across Gradients of Anthropogenic Influence

Human influence associated with land use may cause considerable biodiversity losses, namely in oceanic islands such as the Azores. Our goal was to identify plant indicator species across two gradients of increasing anthropogenic influence and management (arborescent and herbaceous communities) and determine similarity between plant communities of uncategorized vegetation plots to those in reference gradients using metrics derived from R programming. We intend to test and provide an expedient way to determine the conservation value of a given uncategorized vegetation plot based on the number of native, endemic, introduced, and invasive indicator species present. Using the metric IndVal, plant taxa with a significant indicator value for each community type in the two anthropogenic gradients were determined. A new metric, ComVal, was developed to assess the similarity of an uncategorized vegetation plot toward a reference community type, based on (i) the percentage of pre-defined indicator species from reference communities present in the vegetation plots, and (ii) the percentage of indicator species, specific to a given reference community type, present in the vegetation plot. Using a data resampling approach, the communities were randomly used as training or validation sets to classify vegetation plots based on ComVal. The percentage match with reference community types ranged from 77 to 100 % and from 79 to 100 %, for herbaceous and arborescent vegetation plots, respectively. Both IndVal and ComVal are part of a suite of useful tools characterizing plant communities and plant community change along gradients of anthropogenic influence without a priori knowledge of their biology and ecology.     

Transesterification of Caesalpinia eriostachys seed oil using heterogeneous and homogeneous basic catalysts

Caesalpinea eriostachys seed oil, as a source of triglycerides with potential application for biodiesel production in Mexico is introduced. Its lipid profile obtained by Gas Chromatography-Mass Spectrometry (GC-MS) revealed saturated and unsaturated glycerol esters as the constituents. Therefore, heterogeneous and homogeneous catalyzed transesterification reactions were assayed employing ZnAl hydrotalcites and KOH, as the catalysts, respectively. The transesterification reactions yielded 59% for Zn/Al(2), 79% for Zn/Al(4), and 90% for KOH, depicting typical behavior, as in biodiesel production data from literature, where Zn-Al hydrotalcites or KOH were assayed. The caloric, density, viscosity values, and fatty acid methyl esters profile from reaction products were concordant to EN 14214, suggesting C. eriostachys as a promising feedstock for biodiesel production.     

A survey on the public perception of CCS in France

An awareness and opinion survey on carbon capture and storage (CCS) was conducted on a representative sample of French residents aged 15 years and above. About 6% of respondents were able to provide a satisfactory definition of the technology. The key question about ‘approval of or opposition to’ the use of CCS in France was asked twice, first after presenting the technology, then after explaining its potential adverse consequences. The approval rates, which were 59% and 38%, respectively, show that there is no a priori rejection of the technology. The sample was split in two to test for a semantic effect: half of the questionnaires used “Stockage” (English: storage), the other half “Sequestration”. Manipulating the vocabulary had no statistically significant effect on approval rates. Stockage is more meaningful, but does not convey the idea of permanent monitoring.     

BR-319: Brazil’s Manaus-Porto Velho Highway and the Potential Impact of Linking the Arc of Deforestation to Central Amazonia

Brazil’s BR-319 Highway linked Manaus, in the state of Amazonas, to Porto Velho, Rondônia, until it became impassable in 1988. Now it is proposed for reconstruction and paving, which would facilitate migration from the “Arc of Deforestation” in the southern part of the Amazon region to new frontiers farther north. The purpose of the highway, which is to facilitate transport to São Paulo of products from factories in the Manaus Free Trade Zone, would be better served by sending the containers by ship to the port of Santos. The lack of a land connection to Manaus currently represents a significant barrier to migration to central and northern Amazonia. Discourse regarding the highway systematically overestimates the highway’s benefits and underestimates its impacts. A variety of changes would be needed prior to paving the highway if these potential impacts are to be attenuated. These include zoning, reserve creation, and increased governance in various forms, including deforestation licensing and control programs. More fundamental changes are also needed, especially the abandonment of the long-standing tradition in Brazil of granting squatters’ rights to those who invade public land. Organizing Amazonian occupation in such a way that road construction and improvement cease to lead to explosive and uncontrolled deforestation should be a prerequisite for approval of the BR-319 and other road projects for which major impacts are expected. These projects could provide the impetus that is needed to achieve the transition away from appropriation of public land by both small squatters and by grileiros (large-scale illegal claimants). A delay in reconstructing the highway is advisable until appropriate changes can be effected.     

Is Urban Stream Restoration Worth It?1

Kenney, Melissa A., Peter R. Wilcock, Benjamin F. Hobbs, Nicholas E. Flores, and Daniela C. Martínez, 2012. Is Urban Stream Restoration Worth It? Journal of the American Water Resources Association (JAWRA) 48(3): 603-615. DOI: 10.1111/j.1752-1688.2011.00635.x Abstract: Public investment in urban stream restoration is growing, yet little has been done to quantify whether its benefits outweigh its cost. The most common drivers of urban stream projects are water quality improvement and infrastructure protection, although recreational and aesthetic benefits are often important community goals. We use standard economic methods to show that these contributions of restoration can be quantified and compared to costs. The approach is demonstrated with a case study in Baltimore, Maryland, a city with a legal mandate to reduce its pollutant load. Typical urban stream restoration costs of US$500-1,200 per foot are larger than the cost of the least expensive alternatives for management of nitrogen loads from stormwater (here, detention ponds, equivalent to $30-120 per foot of restored stream) and for protecting infrastructure (rip-rap armoring of streambanks, at $0-120 per foot). However, the higher costs of stream restoration can in some cases be justified by its aesthetic and recreational benefits, valued using a contingent valuation survey at $560-1,100 per foot. We do not intend to provide a definitive answer regarding the worth of stream restoration, but demonstrate that questions of worth can be asked and answered. Broader application of economic analysis would provide a defensible basis for understanding restoration benefits and for making restoration decisions.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630–690 nm), band 5 (1550–1750 nm) and the ratio between bands 1 (450–520 nm) and 4 (760–900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520–600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.