Fauna community trends during early restoration of alluvial open forest/woodland ecosystems on former agricultural land

Vertebrate fauna was studied over 10 years following revegetation of a Eucalyptus tereticornis ecosystem on former agricultural land. We compared four vegetation types: remnant forest, plantings of a mix of native tree species on cleared land, natural regeneration of partially cleared land after livestock removal, and cleared pasture land with scattered paddock trees managed for livestock production. Pasture differed significantly from remnant in both bird and nonbird fauna. Although 10 years of ecosystem restoration is relatively short term in the restoration process, in this time bird assemblages in plantings and natural regeneration had diverged significantly from pasture, but still differed significantly from remnant. After 10 years, 70 and 66% of the total vertebrate species found in remnant had been recorded in plantings and natural regeneration, respectively. Although the fauna assemblages within plantings and natural regeneration were tracking toward those of remnant, significant differences in fauna between plantings and natural regeneration indicated community development along different restoration pathways. Because natural regeneration contained more mature trees (dbh > 30 cm), native shrub species, and coarse woody debris than plantings from the beginning of the study, these features possibly encouraged different fauna to the revegetation areas from the outset. The ability of plantings and natural regeneration to transition to the remnant state will be governed by a number of factors that were significant in the analyses, including shrub cover, herbaceous biomass, tree hollows, time since fire, and landscape condition. Both active and passive restoration produced significant change from the cleared state in the short term.

Can agroforest woodlots work as stepping stones for birds in the Atlantic forest region?

In fragmented landscapes, agroforest woodlots can potentially act as stepping stones facilitating movement between forest fragments. We assessed the influence of agroforest woodlots on bird distribution and diversity in the Atlantic forest region (SE Brazil), and also tested which categories of species can use different types of connection elements, and whether this use is influenced by the distance to large forest patches. We studied two fragmented landscapes, with and without stepping stones linking large fragments, and one forested landscape. Using a point count, a bird survey was undertaken in the fragmented landscapes in five different elements: large remnants (> 400 ha), agroforest woodlots (0.4-1.1 ha), small patches (0.5-7 ha), riparian corridor, and pasture areas (the main matrix). Generalist and open-area species were commonly observed in the agroforest system or other connection elements, whereas only a few forest species were present in these connections. For the latter species, the distance of woodlots to large patches was essential to determine their richness and abundance. Based on our results and data from literature, we suggest that there is an optimal relationship between the permeability of the matrix and the efficiency of stepping stones, which occurs at intermediate degrees of matrix resistance, and is species-dependent. Because the presence of agroforest system favors a higher richness of generalist species, they appeared to be more advantageous for conservation than the monoculture system; for this reason, they should be considered as a management alternative, particularly when the matrix permeability requirement is met.

Can't see the water for the trees

The work was both conceived and constructed in-situ within Gnombup Swamp a seasonal water body at Bremer Bay, Western Australia. The work interacts with site-specific conditions including wind patterns and a datum of seasonal water levels marks. The work is the result of collaboration between soil scientist Paula Deegan and Ian Weir. The installation was documented with a series of 30 still digital photographs, later animated in Microsoft Powerpoint.

Using decision trees in economizer repair decision making

The economiser is a critical component for efficient operation of coal-fired power stations. It consists of a large system of water-filled tubes which extract heat from the exhaust gases. When it fails, usually due to erosion causing a leak, the entire power station must be shut down to effect repairs. Not only are such repairs highly expensive, but the overall repair costs are significantly affected by fluctuations in electricity market prices, due to revenue lost during the outage. As a result, decisions about when to repair an economiser can alter the repair costs by millions of dollars. Therefore, economiser repair decisions are critical and must be optimised. However, making optimal repair decisions is difficult because economiser leaks are a type of interactive failure. If left unfixed, a leak in a tube can cause additional leaks in adjacent tubes which will need more time to repair. In addition, when choosing repair times, one also needs to consider a number of other uncertain inputs such as future electricity market prices and demands. Although many different decision models and methodologies have been developed, an effective decision-making method specifically for economiser repairs has yet to be defined. In this paper, we describe a Decision Tree based method to meet this need. An industrial case study is presented to demonstrate the application of our method.

Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox–Ingersoll–Ross and Ornstein–Uhlenbeck equations respectively.