Observer presence may alter the behaviour of reef fishes associated with coral colonies

Although underwater visual census (UVC) is the most frequently used technique for quantifying reef fish assemblages, remote video analysis has been gaining attention as a potential alternative. In the South Atlantic Ocean, Millepora spp. (class Hydrozoa) are the only branching coral species; however, little is known about the ecological role that they play for reef fish communities. We compared these two observation methods (remote video and UVC) to estimate reef fish abundance and species richness associated with colonies of the fire‐coral Millepora alcicornis at Tamandaré Reefs, Northeast Brazil. Additionally, the two different techniques were used to compare species behaviour in association with fire‐corals in order to examine the biases associated with each technique and provide useful information for behavioural ecologists studying fish–coral associations. There were no differences in reef fish abundance or species richness sampled by remote video or UVC. However, a significant difference in the behaviour of associated fish was recorded between the two methods. In the presence of a diver carrying out a UVC, fish were observed spending more time sheltered amongst the coral branches compared with passively swimming on coral colonies with the remote video technique. Specifically, on the remote video recordings agonistic interactions between fish and passive swimming accounted for 33.3% and 22.2% of the census time, respectively. By comparison, when observed by a diver fish spent 34.8% of their time sheltering amongst the coral branches. We demonstrate that both techniques are similarly effective for recording fish abundance and species richness associated with fire‐corals. However, differences were observed in the ability of each method to detect the behaviour of coral‐associated fishes. Our findings show that behavioural ecologists studying complex fish–coral associations need to ensure that their aims are clearly defined and that they choose the most appropriate technique for their study in order to minimize methodological biases.     

Hierarchical simulation of aquifer heterogeneity: implications of different simulation settings on solute-transport modeling

The fine-scale heterogeneity of porous media affects the large-scale transport of solutes and contaminants in groundwater and it can be reproduced by means of several geostatistical simulation tools. However, including the available geological information in these tools is often cumbersome. A hierarchical simulation procedure based on a binary tree is proposed and tested on two real-world blocks of alluvial sediments, of a few cubic meters volume, that represent small-scale aquifer analogs. The procedure is implemented using the sequential indicator simulation, but it is so general that it can be adapted to various geostatistical simulation tools, improving their capability to incorporate geological information, i.e., the sedimentological and architectural characterization of heterogeneity. When compared with a standard sequential indicator approach on bi-dimensional simulations, in terms of proportions and connectivity indicators, the proposed procedure yields reliable results, closer to the reference observations. Different ensembles of three-dimensional simulations based on different hierarchical sequences are used to perform numerical experiments of conservative solute transport and to obtain ensembles of equivalent pore velocity and dispersion coefficient at the scale length of the blocks (meter). Their statistics are used to estimate the impact of the variability of the transport properties of the simulated blocks on contaminant transport modeled on bigger domains (hectometer). This is investigated with a one-dimensional transport modeling based on the Kolmogorov-Dmitriev theory of branching stochastic processes. Applying the proposed approach with diverse binary trees and different simulation settings provides a great flexibility, which is revealed by the differences in the breakthrough curves.     

Reply to Comment on “Impact of groundwater withdrawals on the interaction of multi-layered aquifers in the Viterbo geothermal area (central Italy)”: report published in Hydrogeology Journal (2013) 21:1339–1353, by Antonella Baiocchi,Francesca Lotti and Vincenzo Piscopo

Hydrogeology Journal -     

A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa,Peru

The town of Santa Teresa (Cusco Region, Peru) has been affected by several large debris-flow events in the recent past, which destroyed parts of the town and resulted in a resettlement of the municipality. Here, we present a risk analysis and a risk management strategy for debris-flows and glacier lake outbursts in the Sacsara catchment. Data scarcity and limited understanding of both physical and social processes impede a full quantitative risk assessment. Therefore, a bottom-up approach is chosen in order to establish an integrated risk management strategy that is robust against uncertainties in the risk analysis. With the Rapid Mass Movement Simulation (RAMMS) model, a reconstruction of a major event from 1998 in the Sacsara catchment is calculated, including a sensitivity analysis for various model parameters. Based on the simulation results, potential future debris-flows scenarios of different magnitudes, including outbursts of two glacier lakes, are modeled for assessing the hazard. For the local communities in the catchment, the hazard assessment is complemented by the analysis of high-resolution satellite imagery and fieldwork. Physical, social, economic, and institutional vulnerability are considered for the vulnerability assessment, and risk is eventually evaluated by crossing the local hazard maps with the vulnerability. Based on this risk analysis, a risk management strategy is developed, consisting of three complementing elements: (i) standardized risk sheets for the communities; (ii) activities with the local population and authorities to increase social and institutional preparedness; and (iii) a simple Early Warning System. By combining scientific, technical, and social aspects, this work is an example of a framework for an integrated risk management strategy in a data scarce, remote mountain catchment in a developing country.     

Testing optically stimulated luminescence dating on sand-sized quartz of deltaic deposits from the Sperchios delta plain,central Greece

This study reports on the first investigation into the potential of luminescence dating to establish a chronological framework for the depositional sequences of the Sperchios delta plain, central Greece. A series of three borehole cores(20 m deep) and two shallow cores(4 m deep), from across the delta plain, were extracted, and samples were collected for luminescence dating. The luminescence ages of sand-sized quartz grains were obtained from small aliquots of quartz, using the Single-Aliquot Regenerative-dose(SAR) protocol.The equivalent dose determination included a series of tests and the selection of the Minimum Age Model(MAM) as the most appropriate statistical model. This made it possible to confirm the applicability of quartz Optically Stimulated Luminescence(OSL) dating to establish absolute chronology for deltaic sediments from the Sperchios delta plain.Testing age results of the five cores showed that the deltaic sediments were deposited during the Holocene.A relatively rapid deposition is implied for the top ~14 m possibly as a result of the deceleration in the rate of the sea-level rise and the transition to terrestrial conditions, while on the deeper parts, the reduced sedimentation rate may indicate a lagoonal or coastal environment.     

High-dimensional geostatistical history matching

Hydrocarbon reservoir modelling and characterisation is a challenging subject within the oil and gas industry due to the lack of well data and the natural heterogeneities of the Earth’s subsurface. Integrating historical production data into the geo-modelling workflow, commonly designated by history matching, allows better reservoir characterisation and the possibility of predicting the reservoir behaviour. We present herein a geostatistical-based multi-objective history matching methodology. It starts with the generation of an initial ensemble of the subsurface petrophysical property of interest through stochastic sequential simulation. Each model is then ranked according the match between its dynamic response, after fluid flow simulation, and the observed available historical production data. This enables building regionalised Pareto fronts and the definition of a large ensemble of optimal subsurface Earth models that fit all the observed production data without compromising the exploration of the uncertainty space. The proposed geostatistical multi-objective history matching technique is successfully implemented in a benchmark synthetic reservoir dataset, the PUNQ-S3, where 12 objectives are targeted.