Habitat Structural Complexity

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Relative importance of coral cover, habitat complexity
and diversity in determining the structure of reef fish
communities

Relative importance of coral cover, habitat complexity and diversity in determining the structure of reef fish communities

To estimate the effects of a range of habitat characteristics on the diversity and structure of the fish community within the lagoon, twenty-two 2x2 m quadrats were surveyed at each of three sites: Palfrey Island, Lizard Head and Bird Island reef. The sampling methodology used in this study is an adaptation of the previously used techniques [49–55]. The sites were selected haphazardly within the lagoon, where extensive reefs with a range of habitat types were present. Lizard Head and Bird Island reefs had more extensive reef slopes than Palfrey Island, and potentially are subject to larger current movements due to their proximity to the channel. No other obvious physical differences occur among sites. Quadrats were placed haphazardly on the reef flat and crest at depths ranging from approximately 1-4 m. This sampling effort and quadrat size was considered sufficient to represent the range of habitat diversity and habitat structural complexity present at each site. Quadrats were marked out by placing marker buoys at each of the corners.
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Cross scale habitat structure driven by coral species composition on tropical reefs

Cross scale habitat structure driven by coral species composition on tropical reefs

The availability of habitat structure across spatial scales can determine ecological organization and resilience. However, anthropogenic disturbances are altering the abundance and composition of habitat-forming organisms. How such shifts in the composition of these organisms alter the physical structure of habitats across ecologically important scales remains unclear. At a time of unprecedented coral loss and homogenization of coral assemblages globally, we investigate the inherent structural complexity of taxonomically distinct reefs, across five ecologically relevant scales of measurement (4–64 cm). We show that structural complexity was influenced by coral species composition, and was not a simple function of coral cover on the studied reefs. However, inter-habitat variation in structural complexity changed with scale. Importantly, the scales at which habitat structure was available also varied among habitats. Complexity at the smallest, most vulnerable scale (4 cm) varied the most among habitats, which could have inferences for as much as half of all reef fishes which are small-bodied and refuge dependent for much of their lives. As disturbances continue and species shifts persist, the future of these ecosystems may rely on a greater concern for the composition of habitat-building species and prioritization of particular configurations for protection of maximal cross-scale habitat structural complexity.
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Testing the power of an experiment to measure predator control and habitat complexity impacts on farmland bird abundance

Testing the power of an experiment to measure predator control and habitat complexity impacts on farmland bird abundance

Abstract: In this study I assess the statistical power to detect a significantly greater increase in bird population size on treatment farms than on control farms given that there is a substantial treatment effect. Computer simulations of bird populations on New Zealand sheep/beef farms were used to generate significant changes in bird abundance from (a) controlling predation by introduced small mammals, (b) habitat structural complexity, and (c) an interaction of both. A simplified computer model of bird population dynamics was developed that predicted a birth pulse of 357% when predators were controlled and 110% if not, and a target of detecting the experimental elevation of bird abundance at a statistically significant level (P < 0.05) in 75% of all attempts was set. If at least four farm pairs (treatment vs non-treatment) are monitored, this is feasible for 15 of 23 species common on farmlands for which sampling error of abundance estimation was below ~40%. A second virtual experiment measured the power of tests of whether habitat complexity and predation in combination led to added increases in bird abundance. It showed that a 75% detection of elevated benefits of predation control in complex habitats could only be achieved if at least 48 farms were monitored, and then only for species for which abundance could be estimated with <10% error. Researchers are advised to invest in increased within- site monitoring to achieve a reasonable precision in bird abundance estimation before increasing the number of replicates.
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Cross-scale habitat structure driven by coral species composition on tropical reefs

Cross-scale habitat structure driven by coral species composition on tropical reefs

Therefore, identifying the structural characteristics of particular coral configurations is critical for the conserva- tion of those systems. However, an understanding of the inherent variation in cross-scale structural complexity of coral reefs is currently lacking. To this end, this study aimed to investigate the influence of coral species com- position on cross-scale patterns of habitat structural complexity, at spatial scales of measurement relevant to fish refuge selection (adapted from ref. 8). Cross-scale structural complexity was quantified at randomly selected sites at Lizard Island in the northern Great Barrier Reef, Australia (14°41 ′ S, 145°27 ′ E), following a step-length geometric series using contour distance measuring wheels of different diameters (4–64 cm) along 10-m transects at each site (Fig. 1; see Supplementary Table S1). Specifically, we assessed i) the cross-scale structural complexity of four coral habitats with distinct species configurations and degraded ( < 10% total coral cover) reef habitat, and ii) cross-scale colony level structural complexity of the dominant coral species at our study location to elucidate the relationship between the complexity of taxa-specific morphologies and colony size.
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Habitat characteristics as determinants of the local diversity and structure of coral reef fish communities

Habitat characteristics as determinants of the local diversity and structure of coral reef fish communities

By comparison to coral diversity, habitat structural complexity was a relatively poor predictor of fish community structure (Chapter 2). While this result apparently conflicts with other studies (e.g. Risk 1972, Luckhurst and Luckhurst 1978, Sano et al. 1984, Friedlander et al. 2003, Bozec et.al. 2005), it is probable that habitat structural complexity may play a more important role for larger, more mobile reef fishes, as described elsewhere (e.g. Graham et al. 2006). In my study, fine-scale difference in topographic complexity could explain the strong associations of fishes with the two coral species E. horrida and H. rigida , which exhibited intermediate inter- branch space (Chapter 3). Fish species preference for specific coral species can be explained by considerable fitness advantages provided by these corals (Hixon and Menge 1991, Jones and Syms 1998, Holbrook et al. 2002a, b, Munday 2000, 2004). That is tightly branched corals should decrease predation levels and allow higher survival rate for smaller fish species, however, only a few fish species would be able to use these corals as refuge due to the size limitations. On the other hand, the more “open” corals, with large distances between branches and abundant free space available would allow a large number of different fish species to enter the colony; however it also means that larger predators can access prey more easily. Corals with intermediate branching structure would allow small to intermediate coral reef fish species to enter the colony and move between coral branches, while at the same time excluding large
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What is the impact on fish recruitment of anthropogenic physical and structural habitat change in shallow nearshore areas in temperate systems? A systematic review protocol

What is the impact on fish recruitment of anthropogenic physical and structural habitat change in shallow nearshore areas in temperate systems? A systematic review protocol

In temperate areas, many coastal populations of fish have seen marked declines during the past two decades [15–19]. These declines have been linked to a number of factors including overexploitation, but it is becoming increasingly evident that the problem of declining abun- dances appears to be caused by factors affecting the early life stages of many species [11, 20]. Indeed, several stud- ies have documented a widespread recruitment deficit in species dependent on shallow coastal habitats for repro- duction, and increased mortality during early stages has been suggested as the main cause for declining popula- tions of adult fish [21–23]. For example, continuous declines in density and abundance of coastal top preda- tory fish like pike (Esox lucius) and Eurasian perch (Perca fluviatilis) have been observed since the mid-1990s in parts of the Baltic Sea [23, 24]. Correspondingly, along parts of the coast as much as 40 % of the available repro- ductive areas were considered degraded or lost by 2005 [3]. Relationships between the size of adult fish popula- tions and the availability and quality of recruitment habi- tats, along with the multitude of pressures that shorelines face, highlight the need for better understanding of how various human activities along coasts may affect fish recruitment [23, 25, 26]. Moreover, altering the abun- dance and diversity of large piscivorous fish may invoke community-wide trophic cascades that have far-reaching, detrimental consequences for ecosystem functioning, fisheries and human livelihoods [19, 27]. Therefore, a bet- ter understanding of how anthropogenic activities affect shallow habitats and the fish dependent on these habitats is essential for guiding management actions that aim to preserve, enhance or restore ecosystem services [28– 30]. Today, controversies remain as to what the primary causes of larval and juvenile fish declines are; whether anthropogenic alteration or loss of nursery coastal habi- tats are responsible for the declines; to what extent vari- ous habitat restoration approaches are effective; and what, if anything, can be done to reverse the declines of fish stocks [5, 12]. However, recently, researchers have focused their attention on the links between anthropo- genic pressures and fish recruitment success, and the accumulation of new data (see for example: [31–35]) suggests that a systematic review on the topic could
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Habitat structure is more important than nutrient supply in modifying mussel bed assemblage in an upwelling area of the Peruvian coast

Habitat structure is more important than nutrient supply in modifying mussel bed assemblage in an upwelling area of the Peruvian coast

substratum for smaller organisms (e.g. Bruno et al. 2003). Along the Chilean coast, Wieters (2005) has demonstrated how coastal upwelling may influence the individual traits of such facilitators, modifying the environment and deter- mining the degree to which other species benefit, involving thus important consequences for community regulation. In intertidal rocky shores, mytilids create a 3-dimensional structure that consists of three major components: the mussel matrix, an assemblage of associated organisms and accumulated detritus (Suchanek 1985). These structures facilitate colonization by certain organisms (Suchanek 1978, 1985), which would either decrease in density or altogether disappear if mytilids did not exist on the rocky substratum (Tokeshi and Romero 2000). Ecosystem engi- neering (i.e. the creation, modification and maintenance of habitats by organisms, Jones et al. 1994) by mussels modifies their local environment (e.g. McKindsey and Bourget 2001) by mitigating desiccation stress (Helmuth 1998), buffering hydrodynamic forces (Bertness et al. 2006; O’Donnell 2008), providing refugia against preda- tors (Borthagaray and Carranza 2007) and providing energy for the associated community (Norling and Kautsky 2007). Furthermore, by modifying heterogeneity and structural complexity (i.e. variation in habitat structure attributable to the absolute abundance of individual struc- tural components, Beck 2000), shell size seems to play an important role influencing community structure of the assemblage associated with mussel beds (Tsuchiya and Nishihira 1986). For instance, larger shells usually support more individuals of a given fouling species and a greater richness of fouling species than smaller ones (see Gutie´rrez et al. 2003).
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Habitat complexity and community composition: relationships between different ecosystem engineers and the associated macroinvertebrate assemblages

Habitat complexity and community composition: relationships between different ecosystem engineers and the associated macroinvertebrate assemblages

unnecessary sacrifice of valid replicates, we randomly chose a balanced set of ten plots per category and com- pared them statistically. After repeating this procedure three times, with three different sets of 10 randomly chosen replicates we always found the results consistent and never different from the unbalanced analysis (i.e. including n = 30, 20 and 10). The dominant species found showed a differential distribution among engineered habitats: the cryptogenic Tanais dulongii was more abundant at M hab- itat (Kruskal–Wallis test: H = 30.84, P \ 0.01, post hoc test, M [ S-M = B, P \ 0.01), the isopod Pseudosphaer- oma sp. at B habitat (Kruskal–Wallis test: H = 51.18, P \ 0.01, post hoc test: B [ S-M = M, P \ 0.01), and the limpet Siphonaria lessoni at M and B habitats (Kruskal– Wallis test: H = 75.96, P \ 0.01, post hoc test, M = B [ S-M, P \ 0.01). Of the total taxa identified, 70% were common to the three engineered habitats and just the iso- pod Idotea sp., the gastropod Trophon geversianus, and the polychaete Scoletoma tetraura, were exclusively found in habitat from S-M but at very low density (B0.01 ind 100 cm -2 , Table 2). However, the amphipod Orchestia gammarella was found almost exclusively at high density Table 2 Mean
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Stress Oriented Structural Optimization for Frame Structures

Stress Oriented Structural Optimization for Frame Structures

Structural Simplification for Fabrication There has been work on problems which aim to simplify the complex- ity of the structure of 3D shapes for fabrication. Many meth- ods are based on decomposing a 3D shape into smaller pieces and then assembling them to form the original shape or a resemblance of it. Luo et al. [13] suggest a method to 3D print large objects by first segmenting an object into smaller parts and then assembling the parts to form the larger shape. Hildebrand et al. [14] create parts from a 3D shape that can then be fabricated and assembled in an optimal direction. Interlocked planar [15, 16] or solid pieces [17, 18] can be used to form a shape that resembles the original. Zimmer et al. [19] describe an approach to approximate mesh surfaces by building physical structures with the Zometool construc- tion system. Vanek et al. [20] present a method to divide a mesh into parts which are then efficiently packed into space for 3D printing. Instead of decomposing a shape into smaller pieces, we simplify a frame structure by possibly removing elements from it. We contribute a semi-continuous optimiza- tion for this purpose.
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Categorical invariance and structural complexity in human concept learning

Categorical invariance and structural complexity in human concept learning

One interesting aspect of the CIM is that its reliance on both categorical invariance and category size tacitly suggests two distinct processes that may lie at the core of all of cognition: namely, pattern detection and working memory. This is most apparent when considering the parity phenomenon. More specifically, we hypothesize that parity effects may be the result of observers searching for invariances (perhaps using short-term or working memory and selective attention resources) within competing categories and settling for the one from which it is easiest to extract invariances in working memory. This is normally the smaller category unless the bigger category has a comparatively much higher degree of invariance than the smaller. However, this maxim works only up to a point: for even when there is a higher degree of invariance in a competing category, subjects probably opt to commit to long-term memory the competing category that has only one member, thereby bypassing the implicit analysis of invariance altogether. This tradeoff between memory limitations and pattern perception needs to be further researched empirically. However, a good first theoretical step toward identifying it is to characterize the role that both invariance and category size may be playing in concept formation and this is what we have done thus far through our characterization of structural complexity.
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Spatial Variation in Canopy Structure across Forest Landscapes

Spatial Variation in Canopy Structure across Forest Landscapes

Quantifying forest and canopy structural complexity metrics from terrestrial LiDAR data using the. 362[r]

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Habitat characteristics as determinants of the local diversity and structure of coral reef fish communities

Habitat characteristics as determinants of the local diversity and structure of coral reef fish communities

The relationships between a range of habitat features and local fish diversity, abundance and community structure were investigated by sampling over sixty 2m² quadrats at three sites in the Lizard Island lagoon. Fish species richness, total abundance and community structure were examined in relation to location within the lagoon and a wide range of habitat variables, including topographic complexity, habitat diversity, coral diversity, coral species richness, hard coral cover, branching coral cover and the cover of corymbose corals. Fish species richness and total abundance were strongly related to coral species richness and cover, but only weakly related to topographic complexity. Regression tree analysis indicated that coral species richness accounted for over 63% of the variation in fish species richness, while hard coral cover explained more variation in total fish abundance (17.4%), than any other variable. The results suggest that the diversity of scleractinian corals is critical in maintaining local coral reef fish diversity, and loss of coral species will in turn lead to declining fish diversity.
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Habitat complexity and management intensity positively influence fledging success in the endangered hihi (Notiomystis cincta)

Habitat complexity and management intensity positively influence fledging success in the endangered hihi (Notiomystis cincta)

Forest age, habitat complexity and fledging success In the general analysis it was clear that fledging rates were not only influenced by management factors, but also a habitat classification related to forest age (i.e. immature regenerating forest vs mature old forest; Fig. 2), which was broadly related to forest structural complexity and diversity. Our results suggest that under conditions of food supplementation these habitat effects would become redundant with respect to reproductive success. This association between habitat age and hihi productivity was further strengthened by the analysis of natural nesting sites, and the relationship between their local habitat variables and fledging success. Of the nine variables we considered, only local habitat complexity (as measured by summed height-frequency scores of vegetation) and the nest tree diameter at breast height were good predictors of fledging success – both factors are correlated with habitat age. The final regression-tree analysis, where we divided the height-frequency complexity scores into five categories, suggests that it is vegetation structure and probably diversity in the lower to mid-sections of the forest (i.e. <12 m high) that are most important for hihi. Although this is based on only 36 nests, this result is supported by two other pieces of information. First, we know that competition between hihi, bellbirds (Anthornis melanura) and tūī (Prosthemadera novaeseelandiae) leads to species-specific partitioning of vertical space in the forest, with hihi mainly utilising resources in the lower to mid-sections (Rasch & Craig 1988; Wilson 1997). Because invertebrates account for a large proportion of nestling diets (Castro et al.
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Strategies for managing the structural and dynamic consequences of project complexity

Strategies for managing the structural and dynamic consequences of project complexity

communications are most likely to be effective in preventing the “magic field” kind of structural consequences of complexity. Irreducible Variety. This third type of structural complexity context becomes prominent when the number of relevant fac- tors is important but existing representations cannot reduce them to a more parsimonious set of essential properties with which participants can operate. As a result, participants are likely to concentrate selectively on some of these factors at some moments and on others at another time. This precludes them from converging on a stable project form. This kind of context is likely to be observed in software projects in which the high number of concrete factors cannot be adequately captured with most architectural modeling methods, leading to an endless succession of beta prototypes before the release of a still imperfectly stable product. A particular case could be ICT solutions developed for various implementation con- ditions, such as countries, sectors, or types of organizations, all of which impose different needs and constraints, which are difficult to compress into a unique parsimonious set of requirements. More generally, this is also the case for the technical aspects of projects, in which taking into account the impact of so many factors (dimensions and other properties) makes designing them a highly iterative endeavor [132, 133].
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Fish Biodiversity, Habitat Complexity, and Soundscape Characteristics of Patch Reefs in a Tropical, Back-Reef Nursery.

Fish Biodiversity, Habitat Complexity, and Soundscape Characteristics of Patch Reefs in a Tropical, Back-Reef Nursery.

recorded in a given habitat accurately reflect the complexity of the habitat and biodiversity of its inhabitants? For the seagrass-dominated back-reef habitat examined in this study, there are two general answers: (i) no, the low frequency sounds that might be produced by juvenile fish did not correlate with the diversity of fish on or habitat complexity of experimental patch reefs, and (ii) yes, invertebrate snaps likely associated with snapping shrimp were positively correlated with reef habitat complexity. Specifically, sound pressure levels in the low frequency band (0.1 – 1.5 kHz), indicative of reef fish vocalizations, occasionally peaked twice per day at three of the most complex sites around crepuscular times; however, the relationships between habitat and low frequency SPL and ACI were not significant. Sound pressure levels in the high frequency band (4 – 20 kHz), as well as invertebrate snap rates, peaked at night. Acoustic variables collected at these biologically relevant temporal periods were compared with habitat complexity and fish biodiversity. High frequency SPLs and snap rates were significantly correlated with structural rugosity, although not fish biodiversity. Low frequency sound pressure levels showed no relationships with habitat complexity or fish biodiversity. Acoustic complexity values were not related to fish biodiversity or habitat complexity for neither low nor high frequencies.
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Working towards best practice with international and other EAL students

Working towards best practice with international and other EAL students

However, there are problems with expression and the appropriate choice of words and whilst there is good structural control, the complexity and variation in the sentences are limited.”[r]

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The role of habitat structure in a freshwater food web

The role of habitat structure in a freshwater food web

11 Introduction 11 Mcibo& 15 The macrophytes 15 Indices of structural complexity 16 Data Analysis 19 Results 20 Discussion 22 Indices of stmctural complexity 22 Macroinvertebrate distrib[r]

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Habitat complexity and patch choice : spatiotemporal distribution of foraging shorebirds on intertidal sand flats

Habitat complexity and patch choice : spatiotemporal distribution of foraging shorebirds on intertidal sand flats

Beyond the area-edge ratio or total edge length, characteristics of the margin itself (defined as the “glossy” area along the water edge), such as width and slope, could be important in determining its relative value compared to other edges available in the landscape. A gently sloping margin results in more “newly exposed area” (and a wider band of active prey) than a steeply sloped margin of the same tide-line length. Following mid ebb tide, the margin of Semi-Enclosed Flat changed drastically in slope (Fig 1). Between mid ebb and low tide very little new area was exposed on the flat, while each of the other flats expanded drastically. Differences in “newly exposed area” per edge length affect the amount of accessible prey on a flat, and, consequently, its value as foraging habitat.
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Habitat complexity influences the structure of food webs in Great Barrier Reef seagrass meadows

Habitat complexity influences the structure of food webs in Great Barrier Reef seagrass meadows

Theories of energy and matter transfer in food webs can help to distinguish among mechanisms that cause relationships between structural com- plexity and productivity. Mechanisms that might influence productivity include which sources of primary productivity support the food web, how effectively the food web is transferring energy to higher trophic levels, the distribution of preda- tors and prey within a food web, and the pres- ence of energetic subsidies (Jennings and Mackinson 2003, Trebilco et al. 2013). Animal size spectra and isotopic diet studies can help to understand which of these mechanisms are oper- ating. Size spectra are expressed as a slope expo- nent (b) for body mass (M) and b scales with either abundance, biomass, or energy use in a predictable way (Trebilco et al. 2013). When ana- lyzing the body mass–abundance relationship in size-structured communities, slopes are typically expected to be more negative (steeper) than the
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A Review and Analysis of Software Complexity Metrics in Structural Testing

A Review and Analysis of Software Complexity Metrics in Structural Testing

The Software complexity is based on well-known software metrics, this would be likely to reduce the time spent and cost estimation in the testing phase of the software development life cycle (SDLC), which can only be used after program coding is done. Improving quality of software is a quantitative measure of the quality of source code. This can be achieved through definition of metrics, values for which can be calculated by analyzing source code or program is coded. A number of software metrics widely used in the software industry are still not well understood [1]. Although some software complexity measures were proposed over thirty years ago and some others proposed later. Sometimes software growth is usually considered in terms of complexity of source code. Various metrics are used, which unable to compare approaches and results. In addition, it is not possible or equally easy to evaluate for a given source code [2]. Software complexity, deals with how difficult a program is to comprehend and work with [3]. Software maintainability [3], is the degree to which characteristics that hamper software maintenance are present and determined by software complexity. There dependencies are shown in Fig. 1.
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