Measure Of Structural Complexity Research Articles

Insectivorous bats respond to vegetation complexity in urban green spaces.

Structural complexity is known to determine habitat quality for insectivorous bats, but how bats respond to habitat complexity in highly modified areas such as urban green spaces has been little explored. Furthermore, it is uncertain whether a recently developed measure of structural complexity is as effective as field‐based surveys when applied to urban environments. We assessed whether image‐derived structural complexity (MIG) was as/more effective than field‐based descriptors in this environment and evaluated the response of insectivorous bats to structural complexity in urban green spaces. Bat activity and species richness were assessed with ultrasonic devices at 180 locations within green spaces in Vienna, Austria. Vegetation complexity was assessed using 17 field‐based descriptors and by calculating the mean information gain (MIG) using digital images. Total bat activity and species richness decreased with increasing structural complexity of canopy cover, suggesting maneuverability and echolocation (sensorial) challenges for bat species using the canopy for flight and foraging. The negative response of functional groups to increased complexity was stronger for open‐space foragers than for edge‐space foragers. Nyctalus noctula, a species foraging in open space, showed a negative response to structural complexity, whereas Pipistrellus pygmaeus, an edge‐space forager, was positively influenced by the number of trees. Our results show that MIG is a useful, time‐ and cost‐effective tool to measure habitat complexity that complemented field‐based descriptors. Response of insectivorous bats to structural complexity was group‐ and species‐specific, which highlights the need for manifold management strategies (e.g., increasing or reinstating the extent of ground vegetation cover) to fulfill different species’ requirements and to conserve insectivorous bats in urban green spaces.

Spatio-Temporal Patterns in Coral Reef Communities of the Spermonde Archipelago, 2012–2014, I: Comprehensive Reef Monitoring of Water and Benthic Indicators Reflect Changes in Reef Health

Pollution, fishing, and outbreaks of predators can heavily impact coastal coral reef ecosystems, leading to decreased water quality and benthic community shifts. To determine the main environmental drivers of coral reef status in the Spermonde Archipelago, Indonesia, we monitored environmental variables and coral reef benthic community structure along an on-to-offshore gradient annually from 2012-2014. Findings revealed that concentrations of phosphate, chlorophyll a-like fluorescence, suspended particulate matter, and light attenuation significantly decreased from on-to-offshore, while concentrations of dissolved O2 and values of water pH significantly increased on-to-offshore. Nitrogen stable isotope signatures of sediment and an exemplary common brown alga were significantly enriched nearshore, identifying wastewater input as a primary N source from the city of Makassar. In contrast to the high temporal variability in water quality, coral reef benthic community cover did not show strong temporal, but rather, spatial patterns. Turf algae was the dominant group next to live coral, and was negatively correlated to live coral, crustose coralline algae (CCA), rubble and hard substrate. Variation in benthic cover along the gradient was explained by water quality variables linked to trophic status and physico-chemical variables. As an integrated measure of reef status and structural complexity, the benthic index, based on the ratio of relative cover of live coral and CCA to other coral reef organisms, and reef rugosity were determined. The benthic index was consistently low nearshore and increased offshore, with high variability in the midshelf sites across years. Reef rugosity was also lowest nearshore and increased further offshore. Both indices dropped in 2013, increasing again in 2014, indicating a period of acute disturbance and recovery within the study and suggesting that the mid-shelf reefs are more resilient to disturbance than nearshore reefs. We thus recommend using these two indices with a selected number of environmental variables as an integral part of future reef monitoring.

Floating neighborhoods reveal contribution of individual trees to high sub-stand scale heterogeneity

Abstract Forest structure is typically characterized using approaches that fail to capture the sub-stand heterogeneity reflecting the processes shaping stand structure at neighborhood patch scales. We propose a focal-tree based approach that flexibly scales across natural tree neighborhoods and demonstrate it by quantifying small-scale structural heterogeneity using diameter distributions across multiple scales in an old-growth mixed conifer forest in western Oregon exhibiting a rotated sigmoid shape. Tree-centered delineation of neighborhoods via Delaunay triangulation (spatial tessellation) was used to connect natural tree neighbors. At the First-order neighborhood scale, each tree was connected to an average of 6 neighbors in 75 m2 of convex hull area, which increased to 118 neighbors covering 2542 m2 by the Fifth-order scale. Agglomerative clustering identified the ten most prevalent sub-stand diameter distribution types (DDTs). At the smallest scale, these ten DDTs were characterized by four different distribution shapes (negative exponential, concave, rotated sigmoid, and unimodal) and varied considerably in the abundance of trees in different size classes and species composition (Douglas-fir composing the larger trees and western hemlock and western redcedar the smaller). On average, each individual tree contributed to over 3 different DDTs at any given scale. Small-scale tree neighborhoods were tremendously heterogeneous, such that the stand-level diameter distribution represented an aggregation across extremely disparate sub-stand distributions. As expected, these distributions exhibited spatial smoothing (i.e., increasing homogeneity with increasing scale) as small, heterogeneous tree neighborhoods were expanded into larger neighborhoods with more similar average composition, which converged on a rotated-sigmoid shape by the Fifth-order scale. Structural complexity in the demonstration stand likely owes more to shade-tolerant ingrowth below residual trees than to gap processes. The diversity of structural contribution (e.g., the number of DDTs to which a tree contributes) may be a more informative measure of structural complexity than indices based on a fixed spatial perspective. The floating neighborhood delineation and scaling approach allows for the identification of natural neighborhoods, permits the assessment of multiple conditions for any given tree, and provides of a logical mechanism for exploring scale-dependent ecological phenomena.

High refuge availability on coral reefs increases the vulnerability of reef-associated predators to overexploitation.

Refuge availability and fishing alter predator-prey interactions on coral reefs, but our understanding of how they interact to drive food web dynamics, community structure and vulnerability of different trophic groups is unclear. Here, we apply a size-based ecosystem model of coral reefs, parameterized with empirical measures of structural complexity, to predict fish biomass, productivity and community structure in reef ecosystems under a broad range of refuge availability and fishing regimes. In unfished ecosystems, the expected positive correlation between reef structural complexity and biomass emerges, but a non-linear effect of predation refuges is observed for the productivity of predatory fish. Reefs with intermediate complexity have the highest predator productivity, but when refuge availability is high and prey are less available, predator growth rates decrease, with significant implications for fisheries. Specifically, as fishing intensity increases, predators in habitats with high refuge availability exhibit vulnerability to over-exploitation, resulting in communities dominated by herbivores. Our study reveals mechanisms for threshold dynamics in predators living in complex habitats and elucidates how predators can be food-limited when most of their prey are able to hide. We also highlight the importance of nutrient recycling via the detrital pathway, to support high predator biomasses on coral reefs.

Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes

Information on habitat associations from survey data, combined with spatial modelling, allow the development of more refined species distribution modelling which may identify areas of high conservation/fisheries value and consequentially improve conservation efforts. Generalised additive models were used to model the probability of occurrence of six focal species after surveys that utilised two remote underwater video sampling methods (i.e. baited and towed video). Models developed for the towed video method had consistently better predictive performance for all but one study species although only three models had a good to fair fit, and the rest were poor fits, highlighting the challenges associated with modelling habitat associations of marine species in highly homogenous, low relief environments. Models based on baited video dataset regularly included large-scale measures of structural complexity, suggesting fish attraction to a single focus point by bait. Conversely, models based on the towed video data often incorporated small-scale measures of habitat complexity and were more likely to reflect true species-habitat relationships. The cost associated with use of the towed video systems for surveying low-relief seascapes was also relatively low providing additional support for considering this method for marine spatial ecological modelling.

Information-based measures of structural complexity of crystals

Information-based measures of structural complexity of crystals

A holistic approach to determine tree structural complexity based on laser scanning data and fractal analysis.

The three‐dimensional forest structure affects many ecosystem functions and services provided by forests. As forests are made of trees it seems reasonable to approach their structure by investigating individual tree structure. Based on three‐dimensional point clouds from laser scanning, a newly developed holistic approach is presented that enables to calculate the box dimension as a measure of structural complexity of individual trees using fractal analysis. It was found that the box dimension of trees was significantly different among the tested species, among trees belonging to the same species but exposed to different growing conditions (at gap vs. forest interior) or to different kinds of competition (intraspecific vs. interspecific). Furthermore, it was shown that the box dimension is positively related to the trees’ growth rate. The box dimension was identified as an easy to calculate measure that integrates the effect of several external drivers of tree structure, such as competition strength and type, while simultaneously providing information on structure‐related properties, like tree growth.

Age-related differences in the structural complexity of subcortical and ventricular structures

It has been well established that the volume of several subcortical structures decreases in relation to age. Different metrics of cortical structure (e.g., volume, thickness, surface area, and gyrification) have been shown to index distinct characteristics of interindividual differences; thus, it is important to consider the relation of age to multiple structural measures. Here, we compare age-related differences in subcortical and ventricular volume to those differences revealed with a measure of structural complexity, quantified as fractal dimensionality. Across 3 large data sets, totaling nearly 900 individuals across the adult lifespan (aged 18–94 years), we found greater age-related differences in complexity than volume for the subcortical structures, particularly in the caudate and thalamus. The structural complexity of ventricular structures was not more strongly related to age than volume. These results demonstrate that considering shape-related characteristics improves sensitivity to detect age-related differences in subcortical structures.

Uncovering context-induced status quo effects in choice experiments

In this study five design dimensions are varied systematically investigating context-induced status quo effects in choice experiments. Additionally, two structural complexity measures, entropy and the number of attribute level changes, are used to capture status quo effects from the similarity between alternatives and the number of trade-offs. A crucial finding is that the frequency of status quo choices is negatively associated with the number of alternatives indicating preference matching effects. By contrast, the probability of choosing the status quo increases with a higher number of choice tasks, a wider level range, and the similarity between alternatives. Status quo choices are further affected by the current environmental situation perceived by respondents. We also find that marginal and non-marginal welfare estimates are significantly affected by the choice design. One key finding is that the most used choice task format in environmental economics, i.e., two hypothetical and a status quo alternative, is likely to increase the propensity to choose the status quo option.

Impact of technology infusion on system architecture complexity

ABSTRACTIn complex systems with long life cycles, it is expected that the requirements of these systems will change over time. Therefore, it is important to be able to upgrade the system accordingly over time. This is often accomplished by infusing new technologies into the host system in order to update or improve the overall system performance. However, technology infusion often requires a redesign of the host system, resulting in a change in the overall system architecture complexity. In this study, we used the structural complexity index to analyse the impact of technology infusion by performing three main steps: (1) measurement of structural complexity, (2) Comparative Analysis A to determine the impact of components and their interfaces in each system and (3) Comparative Analysis B to determine the impact of technology infusion. To demonstrate the proposed process, we analyse technology infusion concepts for a hydrogen-enhanced combustion engine. Results show that the structural complexity index can be used as an indicator of the impact of design changes. To manage complex systems, decision-makers should consider the impact of technology infusion on the upgraded system, and select a better solution with high benefits and lower costs.

Depth-based hypergraph complexity traces from directed line graphs

In this paper, we aim to characterize the structure of hypergraphs in terms of structural complexity measure. Measuring the complexity of a hypergraph in a straightforward way tends to be elusive since the hyperedges of a hypergraph may exhibit varying relational orders. We thus transform a hypergraph into a line graph which not only accurately reflects the multiple relationships exhibited by the hyperedges but is also easier to manipulate for complexity analysis. To locate the dominant substructure within a line graph, we identify a centroid vertex by computing the minimum variance of its shortest path lengths. A family of centroid expansion subgraphs of the line graph is then derived from the centroid vertex. We compute the depth-based complexity traces for the hypergraph by measuring either the directed or undirected entropies of its centroid expansion subgraphs. The resulting complexity traces provide a flexible framework that can be applied to both hypergraphs and graphs. We perform (hyper)graph classification in the principal component space of the complexity trace vectors. Experiments on (hyper)graph datasets abstracted from bioinformatics and computer vision data demonstrate the effectiveness and efficiency of the complexity traces.

Towards measurement of structural complexity for ontologies

Ontologies represent knowledge of a particular domain and form an elementary unit for inference techniques on the semantic web. It is important to measure the complexity of ontologies in order for users to better understand, maintain, reuse and integrate them. Existing measures for the complexity of an ontology either handle complexity at schema and instance levels or define subjective parameters to measure ontology complexity. To this end, we present a semi-automated framework to measure the structural complexity at different abstraction levels of an ontology. Moreover, our metrics leverage the information provided by ontology editors, which can be useful to the ontology designer for selection of the ontology with optimum complexity among alternative ontologies. Our framework is inspired by the concept of component-based software complexity metrics and its metrics have been validated against Briand's and Weyuker's benchmarks. We have also performed comparative analysis on public ontologies.

Complexity and fragility in system of systems

SoS are an ensemble of complex systems, which have the potential for an extraordinary amount of structural complexity, even temporarily, as a result of interconnections and couplings that can vary in strength. Because of this, SoS can be vulnerable to sudden catastrophic collapse as a result of small and insignificant partial functionality losses in one of the constituent systems. This paper provides an analysis of the response SoS to uncertainties in the form of partial failures, which is complemented by the presentation of a measure of structural complexity for SoS. Experiments with the development of random graphs to simulate SoS show that a partial failure initiated in one system has a high possibility of leading to a collapse of another system of SoS, sometimes even before leading to total failure in the originating system. After pinpointing the effect of the complexity of today's system of systems (SoS), we present a first-step understanding of why unanticipated failures find more potential and more pathways to their occurrence when interventions in SoS operations, standards or processes are conducted without enough insight and without consideration of the fundamental nature of complexity. We then demonstrate a condition where the incremental changes actually lead to failure of the SoS to meet its performance parameters.

A Wavelet Based Multiscale Weighted Permutation Entropy Method for Sensor Fault Feature Extraction and Identification

Sensor is the core module in signal perception and measurement applications. Due to the harsh external environment, aging, and so forth, sensor easily causes failure and unreliability. In this paper, three kinds of common faults of single sensor, bias, drift, and stuck-at, are investigated. And a fault diagnosis method based on wavelet permutation entropy is proposed. It takes advantage of the multiresolution ability of wavelet and the internal structure complexity measure of permutation entropy to extract fault feature. Multicluster feature selection (MCFS) is used to reduce the dimension of feature vector, and a three-layer back-propagation neural network classifier is designed for fault recognition. The experimental results show that the proposed method can effectively identify the different sensor faults and has good classification and recognition performance.

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

In tropical reef ecosystems corals are the key habitat builders providing most ecosystem structure, which influences coral reef biodiversity and resilience. Remote sensing applications have progressed significantly and photogrammetry together with application of structure from motion software is emerging as a leading technique to create three-dimensional (3D) models of corals and reefs from which biophysical properties of structural complexity can be quantified. This enables the addressing of a range of important marine research questions, such as what the role of habitat complexity is in driving key ecological processes (i.e., foraging). Yet, it is essential to assess the accuracy and precision of photogrammetric measurements to support their application in mapping, monitoring and quantifying coral reef form and structure. This study evaluated the precision (by repeated modeling) and accuracy (by comparison with laser reference models) of geometry and structural complexity metrics derived from photogrammetric 3D models of marine benthic habitat at two ecologically relevant spatial extents; individual coral colonies of a range of common morphologies and patches of reef area of 100s of square metres. Surface rugosity measurements were generally precise across all morphologies and spatial extents with average differences in the geometry of replicate models of 1–6 mm for coral colonies and 25 mm for the reef area. Precision decreased with complexity of the coral morphology, with metrics for small massive corals being the most precise (1% coefficient of variation (CV) in surface rugosity) and metrics for bottlebrush corals being the least precise (10% CV in surface rugosity). There was no indication however that precision was related to complexity for the patch-scale modelling. The 3D geometry of coral models differed by only 1–3 mm from laser reference models. However, high spatial variation in these differences around the model led to a consistent underestimation of surface rugosity values for all morphs of between 8% and 37%. This study highlights the utility of several off-the-shelf photogrammetry tools for the measurement of structural complexity across a range of scales relevant to ecologist and managers. It also provides important information on the accuracy and precision of these systems which should allow for their targeted use by non-experts in computer vision within these contexts.

Modeling and measuring the structural complexity in assembly supply chain networks

Complexity of assembly supply chains (ASCs) is a challenge for designers and managers, especially when ASC systems become increasingly complex due to technological developments and geographically various sourcing arrangements. One of the major challenges at the early design stage is to make decision about an appropriate configuration of ASC. This paper addresses modeling and measuring the structural complexity of ASC networks in order to establish a framework obtaining the optimal ASC configuration. Considering relationship between supply chains and assembly systems, structural complexity measures for ASC network and assembly lines inside the network are developed based on Shannon’s information entropy. This complexity model can be used to configure supply chain networks and assembly systems with robust performance. In order to generate different feasible configurations of ASCs, a four-step algorithm is proposed considering assembly sequence constraint. Finally, the optimal ASC network is obtained by comparing the total complexity values of the feasible configurations.

Idiom properties influencing idiom production in younger and older adults

In order to study the factors influencing storage, access, and retrieval of idioms as they relate to advancing age, we investigated the properties of idioms that directly influence idiom production and their relation to aging. In particular, we selected measures of structural complexity (grammatical class, syntactic frozenness) and a measure of semantic complexity (compositionality) along with several other measures that interact with representation and processing (idiom familiarity, word frequency, semantic neighborhood density). The performance of younger adults (age 18–30) was predicted by idiom familiarity; that of older adults (age 60–85) was predicted by frozenness. In addition, both younger and older adults performed better on full-sentence idioms than on verb-phrase ones. The results are discussed within a theoretical framework of idiom production and aging.

A new arc–chord ratio (ACR) rugosity index for quantifying three-dimensional landscape structural complexity

Rugosity is an index of surface roughness that is widely used as a measure of landscape structural complexity in studies investigating spatially explicit ecological patterns and processes. This paper identifies and demonstrates significant issues with how we presently measure rugosity and, by building on recent advances, proposes a novel rugosity index that overcomes these issues. The new arc-chord ratio (ACR) rugosity index is defined as the contoured area of the surface divided by the area of the surface orthogonally projected onto a plane of best fit (POBF), where the POBF is a function (interpolation) of the boundary data only. The ACR method is described in general, so that it may be applied to a range of rugosity analyses, and its application is detailed for three common analyses: (a) measuring the rugosity of a two-dimensional profile, (b) generating a rugosity raster from an elevation raster (a three-dimensional analysis), and (c) measuring the rugosity of a three-dimensional surface. Two case studies are used to compare the ACR rugosity index with the rugosity index most commonly used (i.e. surface ratio rugosity), demonstrating the advantages of the ACR index. The ACR method for quantifying rugosity is simple, accurate, extremely versatile, and consistent in its principles independent of data dimensionality (2-D or 3-D), scale and analysis software used. It overcomes significant issues presented by traditional rugosity indices (e.g. decouples rugosity from slope) and is a promising new landscape metric. To further increase ease of use I provide multiple ArcGIS® resources in the electronic supplementary materials (e.g. Online Appendix 1: a downloadable ArcToolbox containing two ACR rugosity geoprocessing model tools).

Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03–0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

Cognitive Task Complexity and Iranian EFL Learners’ Written Linguistic Performance across Writing Proficiency Levels

Recently tasks, as the basic units of syllabi, and the cognitive complexity, as the criterion for sequencing them, have caught many second language researchers’ attention. This study sought to explore the effect of utilizing the cognitively simple and complex tasks on high- and low-proficient EFL Iranian writers’ linguistic performance, i.e., fluency, accuracy, lexical complexity, and structural complexity. At first, based on their scores on the writing test of TOFEL (2003), participants were assigned to high- and low-proficient writers. Participants in both groups first accomplished the simple task which was the narration of a story based on a set of pictures. One week later, they were asked to perform the complex task which was writing about a topic requiring reasons. Then the written productions were encoded on the measures of fluency, accuracy, lexical complexity, and structural complexity. Four two-way mixed-design ANOVAs were conducted. The results revealed that the learners significantly generated less accurate, more structurally complex, and more fluent language in the complex task. No significant effect was found for the lexical complexity measure. The high-proficient group performed significantly better in the four measures. The interaction between task complexity and writing proficiency did not yield any significant results. On the whole, based on the findings, the ‘limited attentional model’ was shown to be more accurate in comparison with ‘cognition hypothesis’ and the ‘threshold level hypothesis’ was not confirmed.