Landscape typology in the Mediterranean context: a tool for habitat restoration

Despite the wide use of Landscape Character Assessment (LCA) as a tool for landscape planning in NW Europe, there are few examples of its application in the Mediterranean. This paper reports on the results from the development of a typology for LCA in a study area of northern Sardinia, Italy to provide a spatial framework for the analysis of current patterns of cork oak distribution and future restoration of this habitat. Landscape units were derived from a visual interpretation of map data stored within a GIS describing the physical and cultural characteristics of the study area. The units were subsequently grouped into Landscape Types according to the similarity of shared attributes using Two Way Indicator Species Analysis (TWINSPAN). The preliminary results showed that the methodology classified distinct Landscape Types but, based on field observations, there is a need for further refinement of the classification. The distribution and properties of two main cork oak habitats types was examined within the identified Landscape Types namely woodlands and wood pastures using Patch Analyst. The results show very clearly a correspondence between the distribution of cork oak pastures and cork oak woodland and landscape types. This forms the basis of the development of strategies for the maintenance, restoration and recreation of these habitat types within the study area, ultimately for the whole island of Sardinia. Future work is required to improve the landscape characterisation , particularly with respect to cultural factors, and to determine the validity of the landscape spatial framework for the analysis of cork oak distribution as part of a programme of habitat restoration and re-creation.

Seeds of change: The value of using Rhinanthus minor in grassland restoration

Question: What is the value of using Rhinanthus minor in grassland restoration and can restrictions on its establishment be overcome? Location: England (United Kingdom). Methods: Two experiments were established to determine the efficacy of inoculating R. minor on a suite of four agriculturally improved grasslands and the efficacy of using R. minor in grassland restoration. In Experiment 1, the effect of herbicide gap creation on the establishment and persistence of R. minor in grasslands ranging in productivity was investigated with respect to sward management. In Exp. 2, R. minor was sown at 1000 seeds/m(2) in conjunction with a standard meadow mix over a randomized plot design into Lolium perenne grassland of moderate productivity. The treatment of scarification was investigated as a treatment to promote R. minor. Results: Gap size had a significant role in the establishment and performance of R. minor, especially the 30 cm diameter gaps (Exp. 1). However, R. minor failed to establish long-term persistent populations in all of the agriculturally improved grasslands. In Exp. 2, establishment of R. minor was increased by scarification and its presence was associated with a significant increase in Shannon diversity and the number of sown and unsown species. Values of grass above-ground biomass were significantly lower in plots sown with R. minor, but values of total above-ground biomass (including R. minor) and forb biomass (not including R. minor) were not affected. Conclusions: The value of introducing R. minor into species-poor grassland to increase diversity has been demonstrated, but successful establishment was dependent on grassland type. The scope for using R. minor in grassland restoration schemes is therefore conditional, although establishment can be enhanced through disturbance such as sward scarification.

Contrasting success in the restoration of plant and phytophagous beetle assemblages of species-rich mesotrophic grasslands

Over the last 60 years changes to the management of species-rich mesotrophic grasslands have resulted in the large-scale loss and degradation of this habitat across Europe. Restoration of such grasslands on agriculturally improved pastures provides a potentially valuable approach to the conservation of these threatened areas. Over a four-year period a replicated block design was used to test the effects of seed addition (green hay spreading and brush harvest collection) and soil disturbance on the restoration of phytophagous beetle and plant communities. Patterns of increasing restoration success, particularly where hay spreading and soil disturbance were used in combination, were identified for the phytophagous beetles. In the case of the plants, however, initial differences in restoration success in response to these same treatments were not followed by subsequent temporal changes in plant community similarity to target mesotrophic grassland. It is possible that the long-term consequences of the management treatments would not be the establishment of beetle and plant communities characteristic of the targets for restoration. Restoration management to enhance plant establishment using hay spreading and soil disturbance techniques would, however, still increase community similarity in both taxa to that of species-rich mesotrophic grasslands, and so raise their conservation value.

Low genetic diversity in a marine nature reserve: re-evaluating diversity criteria in reserve design

Little consideration has been given to the genetic composition of populations associated with marine reserves, as reserve designation is generally to protect specific species, communities or habitats. Nevertheless, it is important to conserve genetic diversity since it provides the raw material for the maintenance of species diversity over longer, evolutionary time-scales and may also confer the basis for adaptation to environmental change. Many current marine reserves are small in size and isolated to some degree (e.g. sea loughs and offshore islands). While such features enable easier management, they may have important implications for the genetic structure of protected populations, the ability of populations to recover from local catastrophes and the potential for marine reserves to act as sources of propagules for surrounding areas. Here, we present a case study demonstrating genetic differentiation, isolation, inbreeding and reduced genetic diversity in populations of the dogwhelk Nucella lapillus in Lough Hyne Marine Nature Reserve (an isolated sea lough in southern Ireland), compared with populations on the local adjacent open coast and populations in England, Wales and France. Our study demonstrates that this sea lough is isolated from open coast populations, and highlights that there may be long-term genetic consequences of selecting reserves on the basis of isolation and ease of protection.

Deconstruction plan assessment using multi-criteria decision-making methods

The purpose of this paper is to present two multi-criteria decision-making models, including an Analytic Hierarchy Process (AHP) model and an Analytic Network Process (ANP) model for the assessment of deconstruction plans and to make a comparison between the two models with an experimental case study. Deconstruction planning is under pressure to reduce operation costs, adverse environmental impacts and duration, in the meanwhile to improve productivity and safety in accordance with structure characteristics, site conditions and past experiences. To achieve these targets in deconstruction projects, there is an impending need to develop a formal procedure for contractors to select a most appropriate deconstruction plan. Because numbers of factors influence the selection of deconstruction techniques, engineers definitely need effective tools to conduct the selection process. In this regard, multi-criteria decision-making methods such as AHP have been adopted to effectively support deconstruction technique selection in previous researches. in which it has been proved that AHP method can help decision-makers to make informed decisions on deconstruction technique selection based on a sound technical framework. In this paper, the authors present the application and comparison of two decision-making models including the AHP model and the ANP model for deconstruction plan assessment. The paper concludes that both AHP and ANP are viable and capable tools for deconstruction plan assessment under the same set of evaluation criteria. However, although the ANP can measure relationship among selection criteria and their sub-criteria, which is normally ignored in the AHP, the authors also indicate that whether the ANP model can provide a more accurate result should be examined in further research.

Assessing the PhD: a constructive view of criteria

Research and informed debate reveals that institutional practices in relation to research degree examining vary considerably across the sector. Within a context of accountability and quality assurance/total quality management, the range and specificity of criteria that are used to judge doctoral work is of particular relevance. First, a review of the literature indicates that, although interest in and concern about the process is burgeoning, there is little empirical research published from which practitioners can draw guidance. The second part of the paper reviews that available research, drawing conclusions about issues that seem to pertain at a general level across disciplines and institutions. Lest the variation is an artefact of discipline difference, the third part of the paper focuses on a within discipline study. Criteria expected/predicted by supervisors are compared and contrasted with those anticipated and experienced by candidates and with those implemented and considered important by examiners. The results are disturbing.

Stability criteria for the contextual emergence of macrostates in neural networks

More than thirty years ago, Amari and colleagues proposed a statistical framework for identifying structurally stable macrostates of neural networks from observations of their microstates. We compare their stochastic stability criterion with a deterministic stability criterion based on the ergodic theory of dynamical systems, recently proposed for the scheme of contextual emergence and applied to particular inter-level relations in neuroscience. Stochastic and deterministic stability criteria for macrostates rely on macro-level contexts, which make them sensitive to differences between different macro-levels.

Improvement of link failure restoration utilising MPLS as a means to maintain QoS

The availability of a network strongly depends on the frequency of service outages and the recovery time for each outage. The loss of network resources includes complete or partial failure of hardware and software components, power outages, scheduled maintenance such as software and hardware, operational errors such as configuration errors and acts of nature such as floods, tornadoes and earthquakes. This paper proposes a practical approach to the enhancement of QoS routing by means of providing alternative or repair paths in the event of a breakage of a working path. The proposed scheme guarantees that every Protected Node (PN) is connected to a multi-repair path such that no further failure or breakage of single or double repair paths can cause any simultaneous loss of connectivity between an ingress node and an egress node. Links to be protected in an MPLS network are predefined and an LSP request involves the establishment of a working path. The use of multi-protection paths permits the formation of numerous protection paths allowing greater flexibility. Our analysis will examine several methods including single, double and multi-repair routes and the prioritization of signals along the protected paths to improve the Quality of Service (QoS), throughput, reduce the cost of the protection path placement, delay, congestion and collision.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

Backward elimination model construction for regression and classification using leave-one-out criteria

A fundamental principle in practical nonlinear data modeling is the parsimonious principle of constructing the minimal model that explains the training data well. Leave-one-out (LOO) cross validation is often used to estimate generalization errors by choosing amongst different network architectures (M. Stone, "Cross validatory choice and assessment of statistical predictions", J. R. Stast. Soc., Ser. B, 36, pp. 117-147, 1974). Based upon the minimization of LOO criteria of either the mean squares of LOO errors or the LOO misclassification rate respectively, we present two backward elimination algorithms as model post-processing procedures for regression and classification problems. The proposed backward elimination procedures exploit an orthogonalization procedure to enable the orthogonality between the subspace as spanned by the pruned model and the deleted regressor. Subsequently, it is shown that the LOO criteria used in both algorithms can be calculated via some analytic recursive formula, as derived in this contribution, without actually splitting the estimation data set so as to reduce computational expense. Compared to most other model construction methods, the proposed algorithms are advantageous in several aspects; (i) There are no tuning parameters to be optimized through an extra validation data set; (ii) The procedure is fully automatic without an additional stopping criteria; and (iii) The model structure selection is directly based on model generalization performance. The illustrative examples on regression and classification are used to demonstrate that the proposed algorithms are viable post-processing methods to prune a model to gain extra sparsity and improved generalization.

Minimum stable convergence criteria for stochastic diffusion search

An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.