Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

Spatial extremes of wildfire sizes: Bayesian hierarchical models for extremes

In Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.     

In situ removal of arsenic from groundwater by using permeable reactive barriers of organic matter/limestone/zero-valent iron mixtures

In this study, two mixtures of municipal compost, limestone and, optionally, zero-valent iron were assessed in two column experiments on acid mine treatment. The effluent solution was systematically analysed throughout the experiment and precipitates from both columns were withdrawn for scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffractometry analysis and, from the column containing zero-valent iron, solid digestion and sequential extraction analysis. The results showed that waters were cleaned of arsenic, metals and acidity, but chemical and morphological analysis suggested that metal removal was not due predominantly to biogenic sulphide generation but to pH increase, i.e. metal (oxy)hydroxide and carbonate precipitation. Retained arsenic and metal removal were clearly associated to co-precipitation with and/or sorption on iron and aluminum (oxy)hydroxides. An improvement on the arsenic removal efficiency was achieved when the filling mixture contained zero-valent iron. Values of arsenic concentrations were then always below 10 μg/L.     

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

We here examine species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot. We extend the known occurrence for the treefrog Hypsiboas bischoffi (Anura: Hylidae) through GPS field surveys and use five modeling methods (BIOCLIM, DOMAIN, OM-GARP, SVM, and MAXENT) and selected bioclimatic and topographic variables to model the species distribution. Models were first trained using two calibration areas: the Brazilian Atlantic Forest (BAF) and the whole of South America (SA). All modeling methods showed good levels of predictive power and accuracy with mean AUC ranging from 0.77 (BIOCLIM/BAF) to 0.99 (MAXENT/SA). MAXENT and SVM were the most accurate presence-only methods among those tested here. All but the SVM models calibrated with SA predicted larger distribution areas when compared to models calibrated in BAF. OM-GARP dramatically overpredicted the species distribution for the model calibrated in SA, with a predicted area around 10⁶ km² larger than predicted by other SDMs. With increased calibration area (and environmental space), OM-GARP predictions followed changes in the environmental space associated with the increased calibration area, while MAXENT models were more consistent across calibration areas. MAXENT was the only method that retrieved consistent predictions across calibration areas, while allowing for some overprediction, a result that may be relevant for modeling the distribution of other spatially restricted organisms.     

Look before you leap - individual variation in social vigilance shapes socio-spatial group properties in an agent-based model

Next to predator detection, primate vigilance also serves to keep track of relevant conspecifics. The degree of vigilance towards group members often reflects the dominance rank of an individual: subordinates pay attention to dominants. Although it has been suggested that subordinates' vigilance may result in spatial centrality of dominants, this has not been addressed in either empirical or modeling studies. Using agent-based models, we determined how social vigilance affects socio-spatial properties of primate groups. A basic model without social vigilance, where individuals avoid potential aggressors (avoidance model), was contrasted with two models that each additionally included a different type of social vigilance: a) monitoring a specific potential aggressor to remain informed on its whereabouts (monitoring model) or b) scanning the whole group to detect potential aggressors (scanning model). Adding monitoring or scanning behavior to the avoidance model reinforced spatial centrality of dominants, a pattern often observed in primates, and resulted in more spread out groups. Moreover, variation in scanning tendency alone was already sufficient to generate spatial centrality of dominants: frequently scanning subordinates could move further away from the group center than dominants, before losing sight of group members. In the monitoring model, two mechanisms caused decreased encounter frequencies among subordinates: a) increased inter-individual distances, and b) frequent monitoring of central dominants. In the scanning model, encounters among subordinates decreased due to increased inter-individual distances. This agent-based model study provides a clear indication that individual variation in social vigilance may be an important structuring feature of primate social groups.     

Trophic cascade induced by molluscivore predator alters pore-water biogeochemistry via competitive release of prey

Effects of predation may cascade down the food web. By alleviating interspecific competition among prey, predators may promote biodiversity, but the precise mechanisms of how predators alter competition have remained elusive. Here we report on a predator-exclosure experiment carried out in a tropical intertidal ecosystem, providing evidence for a three-level trophic cascade induced by predation by molluscivore Red Knots (Calidris canutus) that affects pore water biogeochemistry. In the exclosures the knots' favorite prey (Dosinia isocardia) became dominant and reduced the individual growth rate in an alternative prey (Loripes lucinalis). Dosinia, a suspension feeder, consumes suspended particulate organic matter (POM), whereas Loripes is a facultative mixotroph, partly living on metabolites produced by sulfur-oxidizing chemoautotrophic bacteria, but also consuming suspended POM. Reduced sulfide concentrations in the exclosures suggest that, without predation on Dosinia, stronger competition for suspended POM forces Loripes to rely on energy produced by endosymbiotic bacteria, thus leading to an enhanced uptake of sulfide from the surrounding pore water. As sulfide is toxic to most organisms, this competition-induced diet shift by Loripes may detoxify the environment, which in turn may facilitate other species. The inference that predators affect the toxicity of their environment via a multi-level trophic cascade is novel, but we believe it may be a general phenomenon in detritus-based ecosystems.     

Suppressing antagonistic bioengineering feedbacks doubles restoration success

In a seagrass restoration project, we explored the potential for enhancing the restoration process by excluding antagonistic engineering interactions (i.e., biomechanical warfare) between two ecosystem engineers: the bioturbating lugworm Arenicola marina and the sediment-stabilizing seagrass Zostera noltii Hornem. Applying a shell layer underneath half of our seagrass transplants successfully reduced adult lugworm density by over 80% and reduced lugworm-induced microtopography (a proxy for lugworm disturbance) at the wave-sheltered site. At the wave-exposed site adult lugworm densities and microtopography were already lower than at the sheltered site but were further reduced in the shell-treated units. Excluding lugworms and their bioengineering effects corresponded well with a strongly enhanced seagrass growth at the wave-sheltered site, which was absent at the exposed site. Enhanced seagrass growth in the present study was fully assigned to the removal of lugworms' negative engineering effects and not to any (indirect) evolving effects such as an altered biogeochemistry or sediment-stabilizing effects by the shell layer. The context-dependency implies that seagrass establishment at the exposed site is not constrained by negative ecosystem-engineering interactions only, but also by overriding physical stresses causing poor growth conditions. Present findings underline that, in addition to recent emphasis on considering positive (facilitating) interactions in ecological theory and practice, it is equally important to consider negative engineering interactions between ecosystem-engineering species. Removal of such negative interactions between ecosystem-engineering species can give a head start to the target species at the initial establishment phase, when positive engineering feedbacks by the target species on itself are still lacking. Though our study was carried out in a marine environment with variable levels of wave disturbance, similar principles may be expected to apply to other ecosystems that are inhabited by ecosystem engineers.