Structural Complexity Metrics Research Articles

Structural Complexity of Coral Reefs in Guam, Mariana Islands

The complexity of tropical reef habitats affects the occurrence and diversity of the organisms residing in these ecosystems. Quantifying this complexity is important to better understand and monitor reef community assemblages and their roles in providing ecological services. This study employed structure-from-motion photogrammetry to produce accurate 3D reconstructions of eight reefs in Guam and quantified the structural complexity of these sites using seven terrain metrics: rugosity, slope, vector ruggedness measure (VRM), multiscale roughness (magnitude and scale), plan curvature, and profile curvature. The relationships between terrain complexity, benthic community diversity, and coral cover were investigated with generalized linear models. While the average structural complexity metrics did not differ between most sites, there was significant variation within sites. All surveyed transects exhibited high structural complexity, with an average rugosity of 2.28 and an average slope of 43 degrees. Benthic diversity was significantly correlated with the roughness magnitude. Coral cover was significantly correlated with slope, roughness magnitude, and VRM. This study is among the first to employ this methodology in Guam and provides additional insight into the structural complexity of Guam’s reefs, which can become an important component of holistic reef assessments in the future.

Nonnative plant invasion increases urban vegetation structure and influences arthropod communities

AbstractAimEcological theory and empirical evidence indicate that greater structural complexity and diversity in plant communities increases arthropod abundance and diversity. Nonnative plants are typically associated with low arthropod abundance and diversity due to lack of evolutionary history. However, nonnative plants increase the structural complexity of forests, as is common in urban forests. Therefore, urban forests are ideal ecosystems to determine whether structural complexity associated with nonnative plants will increase abundance and diversity of arthropods, as predicted by complexity literature, or whether structural complexity associated with nonnative plants will be depauperate of arthropods, as predicted by nonnative plant literature.LocationWe sampled 24 urban temperate deciduous and mixed forests in two cites, Raleigh, North Carolina and Newark, Delaware, in the eastern United States.MethodsWe quantified ground cover vegetation and shrub layer vegetation in each forest and created structural complexity metrics to represent total, nonnative and native understory vegetation structural complexity. We vacuum sampled arthropods from vegetation and quantified the abundance, biomass, richness and diversity of spiders and non‐spider arthropods.ResultsNonnative plants increase understory vegetation complexity in urban forests. In Raleigh and Newark, we found support for the hypotheses that dense vegetation will increase arthropod abundance and biomass, and against the hypothesis that nonnative vegetation will decrease arthropods. Urban forest arthropod abundance and biomass, but not diversity, increased with greater nonnative and native structural complexity.Main ConclusionsInvaded urban forests may provide adequate food in the form of arthropod biomass to transfer energy to the next trophic level, but likely fail to provide ecological services and functions offered by diverse species, like forest specialists. Urban land managers should survey urban forests for nonnative and native plant communities and prioritize replacing dense nonnative plants with native species when allocating vegetation maintenance resources.

Remote sensing of Antarctic polychaete reefs (Serpula narconensis): reproducible workflows for quantifying benthic structural complexity with action cameras, remotely operated vehicles and structure‐from‐motion photogrammetry

AbstractQuantifying the structural complexity provided by biogenic habitat structures is important in ecology, conservation and management, and yet remains a challenging task, particularly in deep sea and polar environments, that current photogrammetry tools can alleviate. In this study, we demonstrate how small remotely operated vehicles and compact underwater GoPro® action cameras can be easily integrated into coastal Antarctic surveys to quantify structural complexity of under‐ice benthos via underwater photogrammetry. Forty‐four pairs of 1 m2 quadrats at 1 cm resolution, each comprising an orthomosaic and three‐dimensional reconstructions, were analyzed to describe relationships between benthic cover and structural complexity metrics. The study case provided insights into a unique biogenic habitat, highlighting the role of integrating structural complexity metrics in Antarctic benthic surveys. Although no clear relationships between structural complexity and biodiversity were found, high cover of live reef‐building polychaetes was associated with higher levels of structural complexity, particularly fractal dimension (D). Further, broken biogenic structures, product of disturbance events retain habitat structural complexity known to be associated with larvae settlement and biogenic reef growth. This suggests that D can be used as a metric for detecting subtle changes in biogenic structural complexity. We build from available open‐source code, a reproducible scientific workflow that is expected to facilitate the acquisition and analysis of structural complexity metrics. The workflow presented aims to encourage and accelerate the use of photogrammetry tools for benthic studies aiming to quantify biogenic structural complexity across depths and latitudes.

New Structural Complexity Metrics for Forests from Single Terrestrial Lidar Scans

We developed new measures of structural complexity using single point terrestrial laser scanning (TLS) point clouds. These metrics are depth, openness, and isovist. Depth is a three-dimensional, radial measure of the visible distance in all directions from plot center. Openness is the percent of scan pulses in the near-omnidirectional view without a return. Isovists are a measurement of the area visible from the scan location, a quantified measurement of the viewshed within the forest canopy. 243 scans were acquired in 27 forested stands in the Pacific Northwest region of the United States, in different ecoregions representing a broad gradient in structural complexity. All stands were designated natural areas with little to no human perturbations. We created “structural signatures” from depth and openness metrics that can be used to qualitatively visualize differences in forest structures and quantitively distinguish the structural composition of a forest at differing height strata. In most cases, the structural signatures of stands were effective at providing statistically significant metrics differentiating forests from various ecoregions and growth patterns. Isovists were less effective at differentiating between forested stands across multiple ecoregions, but they still quantify the ecological important metric of occlusion. These new metrics appear to capture the structural complexity of forests with a high level of precision and low observer bias and have great potential for quantifying structural change to forest ecosystems, quantifying effects of forest management activities, and describing habitat for organisms. Our measures of structure can be used to ground truth data obtained from aerial lidar to develop models estimating forest structure.

Unraveling Forest Complexity: Resource Use Efficiency, Disturbance, and the Structure‐Function Relationship

AbstractStructurally complex forests optimize resources to assimilate carbon more effectively, leading to higher productivity. Information obtained from Light Detection and Ranging (LiDAR)‐derived canopy structural complexity (CSC) metrics across spatial scales serves as a powerful indicator of ecosystem‐scale functions such as gross primary productivity (GPP). However, our understanding of mechanistic links between forest structure and function, and the impact of disturbance on the relationship, is limited. Here, we paired eddy covariance measurements of carbon and water fluxes from nine forested sites within the 10 × 10 km CHEESEHEAD19 study domain in Northern Wisconsin, USA with drone LiDAR measurements of CSC to establish which CSC metrics were strong drivers of GPP, and tested potential mediators of the relationship. Mechanistic relationships were inspected at five resolutions (0.25, 2, 10, 25, and 50 m) to determine whether relationships persisted with scale. Vertical heterogeneity metrics were the most influential in predicting productivity for forests with a significant degree of heterogeneity in management, forest type, and species composition. CSC metrics included in the structure‐function relationship as well as driver strength was dependent on metric calculation resolution. The relationship was mediated by light use efficiency (LUE) and water use efficiency (WUE), with WUE being a stronger mediator and driver of GPP. These findings allow us to improve representation in ecosystem models of how CSC impacts light and water‐sensitive processes, and ultimately GPP. Improved models enhance our capacity to accurately simulate forest responses to management, furthering our ability to assess climate mitigation strategies.

A Protocol for Extracting Structural Metrics From 3D Reconstructions of Corals

The 3D structure of individual coral colonies provides insights into their ecological functioning. While structure from motion techniques make it possible to reconstruct 3D models of coral colonies based on overlapping images, the extraction of relevant metrics of complexity in a reproducible way remains challenging. We present a method and associated scripts for the 3D reconstruction of coral colonies from in-situ images and the automatic extraction of eleven structural complexity metrics, designed to be run in widely-used software packages. The metrics are designed to capture aspects of complexity relating to the colony’s size and shape that are related to their ecological function. We explored the potential ecological applications of some of these metrics using linear models, comparing aspects of complexity among colonies of different size and morphotaxa (combined information on morphology and taxa). Our results showed that a metric as simple as colony diameter explained 95% of the variation in shelter provisioning capability when paired with information on colony morphotaxa. Further, the habitat provisioning of colonies of comparable size was similar among the six of the seven morphotaxa examined. During the current period of rapid uptake of photogrammetry among ecologists, the results of our study provide a basis to use data derived from 3D models to further explore the nuances of the relationship between structure and function of corals at the colony scale in a replicable and standardised way.

Does anthropogenic fragmentation selectively filter avian phylogenetic diversity in a critically endangered forest system?

SummaryDocumenting phylogenetic diversity for conservation practice allows elucidation of ecosystem functioning and processes by highlighting the commonality and divergence of species’ functional traits within their evolutionary context. Conserving distinct evolutionary histories has intrinsic value, and the conservation of phylogenetically diverse communities is more likely to preserve distinct or relic evolutionary lineages. We explored the potential for anthropogenic forest fragmentation to act as a selective filter of avian phylogenetic diversity within the community of forest-dependent birds of the critically endangered Indian Ocean Coastal Belt Forest (IOCBF), South Africa. We conducted avian point count surveys during the austral breeding season, and calculated fragmentation metrics of forest structural complexity, patch size and isolation. We constructed a maximum likelihood phylogeny using the combined analysis of two mitochondrial genes and three nuclear markers and measured the influence of the fragmentation metrics on six measures of phylogenetic diversity. Our results indicated that the avian community was variously affected by anthropogenic forest fragmentation, with the different metrics of phylogenetic diversity responding with no definitive overall pattern. However, forest structural complexity emerged as an important metric explaining phylogenetic structuring. While the avian community’s phylogenetic diversity displayed resilience to anthropogenic fragmentation, previous research showed a reduction in functional diversity along the fragmentation gradient. Therefore, we recommend studies that especially aim to guide conservation management, incorporate both phylogenetic and functional diversity measures to sufficiently interrogate communities’ resilience to the threats under investigation.

Development phase delineation in primeval European beech using the dominant biomass strata protocol

Reliable characterizations of developmental condition can help elucidate disturbance regimes, characterize structural development, and identify and describe old-growth. However, current forest life cycle development phase classifications are based on inconsistent, incompatible, or unreliable a priori archetypal structures that fail to capture the natural dynamics of old-growth European beech (Fagus sylvatica L.) forests subject to a small-scale disturbance regime. We demonstrate an alternative protocol for capturing phases of biomass upgrade based solely on the proportion of live-tree volume in seven progressive tree size classes, with an optional deadwood-share cut-off (30%) to also identify deadwood-rich patches when desired. The proportions of a 10-ha primeval European beech forest in the Ukraine assigned in 156.25 m2 grid cells to each of the Dominant Biomass Strata phases were in keeping with previously reported estimates. Amid a matrix (>60%) of Overstory, Upper Overstory, and Emergent phases, roughly a tenth of the area was classified to the early Open/Seedling and Understory phases, the Lower and Upper Midstory phases, and the Lower Overstory phase, respectively. Further, 12% of grid cells—across all phases—were deadwood-rich. The biomass proxies of live volume, basal area, and mean tree size increased distinctly with each subsequent phase, and were lower in the deadwood-rich category, in accordance with the forest life cycle. Structural complexity proxies varied inversely with biomass when defined as the distribution of volume among canopy layers, but similarly to biomass when defined using metrics based on tree size differences. High volumes of large-diameter deadwood were observed in all phases, consistent with previous observations of acyclic transitions following mortality. In pure primeval European beech, the synchronous pattern of biomass and size-based structural complexity metrics (including the standard deviation of tree diameters, the Gini coefficient for basal area, the diameter differentiation index T, and the structural complexity index SCI) may provide a natural model for the simultaneous optimization of volume and small-scale complexity in managed forests. With local adaptation, the proposed Dominant Biomass Strata classification protocol could be applicable to any site or forest type and used to classify stand development phases in young forests following stand-initiation or to classify patch development phases in old-growth forests subject to maintenance dynamics.

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

AbstractVegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high‐biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height‐normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

Structure area curves in Eastern Hardwoods: implications for minimum plot sizes to capture spatially explicit structure indices

Sampling needs differ by forest type for timber inventory and structural complexity metrics. We demonstrate in a typical mixed Eastern Hardwoods forest that optimal sampling of timber inventory metrics and spatially explicit structure indices may be achieved in one large plot plus a cruise for large diameter trees, but accurately capturing inventory metrics may not be possible with sparse large-scale sampling. Managing forest stand structures for multiple objectives require accurate and precise estimates of structural features that may be best estimated at different scales. We document minimum necessary plot sizes for structural metrics and spatially explicit indices to characterize structure in a mature North American Eastern hardwoods forest. Metrics and indices (Index of Aggregation, Diameter Differentiation Index, Dissimilarity Coefficient, Structural Complexity Index) were calculated within 0.05–1.75-ha plots for 1000 iterations of random placement in two 2.0-ha macroplots. Estimation adequacy required (1) precision (varied < 10% among plots) and (2) accuracy (within 10% of the 2.0-ha value at 5th and 95th percentiles). Minimum single plot sizes to achieve estimation adequacy were 0.25–0.75 ha for spatially explicit indices and 0.5–2 ha for stand metrics. A minimum of five 0.10-ha subplots would be needed for most indices and 6–25 for most metrics, but an untenable 375+ for the density of large diameter trees. Estimation adequacy for structural complexity requires no greater sampling intensity than for timber metrics, except for density of large trees. A single large plot may be most cost-effective. National inventories in Eastern hardwoods may not estimate structural complexity well due to inadequate sampling intensity.

Metrics of Coral Reef Structural Complexity Extracted from 3D Mesh Models and Digital Elevation Models

Underwater photogrammetry has been increasingly used in coral-reef research in recent years. Habitat metrics extracted from resulting three-dimensional (3D) reconstructions can be used to examine associations between the structural complexity of the reef habitats and the distribution of reef organisms. We created simulated 3D models of bare surface structures and 3D reconstructions of coral morphologies to investigate the behavior of various habitat metrics that were extracted from both Digital Elevation Models (DEMs) and 3D mesh models. Analyzing the resulting values provided us with important insights into how these metrics would compare with one another in the characterization of coral-reef habitats. Surface complexity (i.e., reef rugosity), fractal dimension extracted from DEMs and vector dispersion obtained from 3D mesh models exhibited consistent patterns in the ranking of structural complexity among the simulated bare surfaces and coral morphologies. The vector ruggedness measure obtained from DEMs at three different resolutions of 1, 2, and 4 cm effectively captured differences in the structural complexity among different coral morphologies. Profile curvature and planform curvature, on the other hand, were better suited to capture the structural complexity derived from surface topography such as walls and overhanging ledges. Our results indicate that habitat metrics extracted from DEMs are generally suitable when characterizing a relatively large plot of a coral reef captured from an overhead planar angle, while the 3D metric of vector dispersion is suitable when characterizing a coral colony or a relatively small plot methodically captured from various angles.

Associations between Benthic Cover and Habitat Complexity Metrics Obtained from 3D Reconstruction of Coral Reefs at Different Resolutions

Quantifying the three-dimensional (3D) habitat structure of coral reefs is an important aspect of coral reef monitoring, as habitat architecture affects the abundance and diversity of reef organisms. Here, we used photogrammetric techniques to generate 3D reconstructions of coral reefs and examined relationships between benthic cover and various habitat metrics obtained at six different resolutions of raster cells, ranging from 1 to 32 cm. For metrics of 3D structural complexity, fractal dimension, which utilizes information on 3D surface areas obtained at different resolutions, and vector ruggedness measure (VRM) obtained at 1-, 2- or 4-cm resolution correlated well with benthic cover, with a relatively large amount of variability in these metrics being explained by the proportions of corals and crustose coralline algae. Curvature measures were, on the other hand, correlated with branching and mounding coral cover when obtained at 1-cm resolution, but the amount of variability explained by benthic cover was generally very low when obtained at all other resolutions. These results show that either fractal dimension or VRM obtained at 1-, 2- or 4-cm resolution, along with curvature obtained at 1-cm resolution, can effectively capture the 3D habitat structure provided by specific benthic organisms.

Developing Spectral Structural Complexity Metrics

There are various approaches to measure the complexity of engineered systems. The structural approach to the measurement of system complexity is only one of the possible routes that are currently under consideration. This approach considers the complexity of the internal structure of the system and the organization of its components, as a snapshot frozen in time.The most common approach to the definition of structural complexity metrics is through the concepts of entropy, algorithmic information content, and logical depth. Another approach looks at the set of the eigenvalues–the spectrum–of a graph representation of the system of interest. The most popular spectral structural complexity metrics are graph energy and natural connectivity. The authors in this article present a set of metrics that are created based on the existing metrics. The metrics assume that the graphs representing the system of interest are weighted with values representing the complexity of components and interfaces. The metrics are then explored through two sets of random graphs, representing the architecture of an engineered system.

Evaluating the efficacy of small‐scale marine protected areas for preserving reef health: A case study applying emerging monitoring technology

Abstract Marine protected areas (MPAs) are widely used as management tools to conserve species and ecosystems at risk from human impact. Coastal managers often focus MPA designation on biogenic reef environments due to their value and sensitivity to damage. However, difficulties in enforcement and a lack of capacity to adequately monitor MPAs often make it hard for managers to assess the effectiveness of MPAs, particularly in under‐resourced, low‐income coastal countries. Reef community data were collected at three long‐term managed reserves within the Western Visayas region of the central Philippines in order to assess the state of reef community structure inside and outside of these small‐scale locally managed MPAs. In addition, 3D structural data were captured using recently developed 'Structure from Motion' photogrammetry techniques, demonstrating how multiple quantitative metrics of physical structural complexity and health can be recorded in such analyses. These community‐run MPAs were shown to be effective even when small (10–20 ha). Mean fish biomass density was five times greater within present‐day protected sites, alongside significantly increased levels of fish diversity, richness, and size. No significant structural differences were observed inside and outside of MPAs; however, average reef rugosity, height, and roughness were significantly higher in unfished reefs compared to blast‐fished reefs. Reef substrate complexity, coral composition, and level of management, were also shown to structure fish community assemblages, with the link between reef structure and fish richness/abundance disrupted outside of MPAs. The Structure from Motion technique allows a greater range of quantitative morphometrics to be assessed than traditional methods and at relatively low cost. The technique is rapid, non‐destructive and can be archived, increasing the value of data for managers wishing to quantify reef health and efficiently monitor benthic changes through time. We discuss both the limitations and benefits of this technology's future use.

3D HABITAT COMPLEXITY OF CORAL REEFS IN THE NORTHWESTERN HAWAIIAN ISLANDS IS DRIVEN BY CORAL ASSEMBLAGE STRUCTURE

Abstract. Corals act as ecosystem engineers by secreting structurally complex calcium carbonate skeletons on the benthic substrate that provide habitat for a diverse array of associated reef organisms. Communities of living corals create large and dynamic benthic structures that directly affect ecological parameters such as habitat provisioning and light availability, thus influencing overall ecosystem function. Despite the important role 3D structural complexity plays in ecosystem biodiversity and productivity, the field of coral ecology has lacked accessibility to practical technology capable of quantifying 3D characteristics of underwater habitats. Advancements in the field of computer vision has led to Structure-from-Motion (SfM) photogrammetry, which provides a simple and cost-effective method for creating high-resolution and spatially accurate 3D reconstructions of natural environments. Integrating SfM approaches into coral reef research and monitoring has provided useful insight into the relationship between 3D habitat complexity and ecological processes. In this study, we examined the relationships among 2D estimates of live coral cover and several metrics of 3D habitat structural complexity among eleven long-term monitoring sites at French Frigate Shoals. Our findings show that coral assemblage structure acts as a significant driver of 3D structural complexity of coral reef habitats at this atoll. This study highlights the importance of diverse and abundant coral assemblages in supporting structurally complex coral reef habitats and provides a framework for future investigations into the ecological role of various coral morphotypes.

Linking Landsat to terrestrial LiDAR: Vegetation metrics of forest greenness are correlated with canopy structural complexity

Vegetation metrics derived from satellite imagery provide continuous and large spatial-scale measurements that are critical for interpreting and predicting ecosystem function. However, uncertainty still remains as to the precise structural information that could be estimated from these metrics. Landsat-derived metrics provide pixel measurements of vegetation across the landscape, whereas Light Detection and Ranging (LiDAR) provides multidimensional data on the vertical arrangement of forests. Terrestrial LiDAR metrics of structural complexity describe the arrangement of vegetation in the canopy, and could be coupled with Landsat-derived metrics through their influence on energy and light. Linking Landsat to terrestrial LiDAR estimates of canopy structure could expand the interpretation of Landsat-derived metrics and broaden the spatial scale at which structural complexity can be evaluated. Here, we examined associations between Landsat-derived metrics and terrestrial LiDAR measurements of structural complexity. Structural complexity measurements were obtained with terrestrial LiDAR from plots within eight forested NEON sites across eastern North America. Vegetation metrics (NDVI, EVI, tasseled cap metrics) were calculated for corresponding locations from Landsat 8 satellite imagery. Results showed that canopy reflectance, greenness and brightness, were linked with several measures of canopy structure. Higher levels of greenness were associated with stands having a taller canopy, greater leaf area density and variability, and a less open and porous canopy. Among greenness metrics, NDVI was most strongly correlated with structural complexity metrics (adj. R2 = 0.52 – 0.62 for six metrics). Additionally, we found that a brighter canopy was associated with greater leaf area density and variability, canopy cover, porosity, and lower leaf clumping. Our results demonstrated the potential for large-spatial extent estimates of structural complexity using satellite imagery, and may lead to improved predictions of forest ecosystem functioning such as those predicted in “big leaf” ecosystem models.

Integrating distribution models and habitat classification maps into marine protected area planning

Effective conservation planning requires biotic data across an entire region. In data-poor ecosystems conservation planning is informed by using environmental surrogates (e.g. temperature) predominantly in two ways: to develop habitat classification schemes (1) or develop species distribution models (2). We test the utility of both approaches for conservation planning of marine ecosystems, and rank environmental surrogates, such as depth and distance from shore, according to their power to predict the distribution and abundance of biotic species. Specifically, we compared a habitat classification scheme; based on coarse levels of habitat types derived from depth and distance from shore; against species distribution models, which predict fish abundance and prevalence as a function of environmental surrogates (depth, distance from shore, latitude, reef area, zoning, and several metrics of habitat structural complexity). We consistently set conservation target levels to 21% of each conservation feature, following global standards and a sensitivity analyses. Thus when running scenarios to protect fish species we aimed to protect at least 21% of each species, and when running scenarios of habitat classes, we aimed to protect at least 21% of each habitat class. We found that when aiming to protect 21% of the chosen conservation targets, distribution models protected 21% of the predicted abundance/occurrence of all modelled species and functional groups, but did not protect most habitats. Contrastingly, using a habitat classification scheme protected 21% of all habitat types and 34% of all species and functional groups, but required protecting three times more area. Thus, using only distribution models as targets in data-poor ecosystems could be a risky conservation planning strategy. Ultimately the best conservation outcomes were achieved by incorporating local knowledge to synthesize the conservation outcomes of both scenarios.

Habitat structural complexity metrics improve predictions of fish abundance and distribution

Habitat structural complexity influences biotic diversity and abundance, but its influence on marine ecosystems has not been widely addressed. Recent advances in computer vision and robotics allow quantification of structural complexity at higher‐resolutions than previously achieved. This provides an important opportunity to determine the ecological role of habitat structural complexity in marine ecosystems. We used high‐resolution three‐dimensional (3D) maps to test multiple structural complexity metrics, depth and benthic biota as surrogates of fish assemblages across hundreds of meters on subtropical reefs. Non‐parametric multivariate statistics were used to determine the relationship between these surrogates and the entire fish assemblage. Fish were divided into functional groups, which were used to further investigate the relationship between surrogates and fish abundance using generalized linear models. Fish community composition and abundance were strongly related to habitat complexity metrics, benthic biota and depth. Surface rugosity and its variance had a significant positive influence on the abundance of piscivores and sediment infauna predators, and a negative effect on the abundance of predators, herbivores, planktivores and cleaners. Final models for fish functional groups explained up to 68% of the variance. The best metrics to explain the variance in fish abundance were benthic biota (25 ±7.5% of variance explained, mean ± SE) and complexity metrics (16 ±6.6%, mean ± SE). Our results show that high‐resolution 3D maps and derived metrics can predict a large percentage of variance in fish abundance and potentially serve as useful surrogates of fish abundance across all functional groups in spatially dynamic reefs.

Impact of supply base structural complexity on financial performance: Roles of visible and not-so-visible characteristics

Supply chains have become increasingly complex in the last decade, which makes their structural characteristics important determinants of firm performance. Prior studies on supply chain structure have largely emphasized network-level attributes but ignored supply-base level characteristics. However, in many cases it is the 1st tier suppliers, not those “deep in the network,” that have most immediate influence on the buyer. In addition, some structural characteristics, such as direct links between the buyer's suppliers and its customers, are not-so-visible to the buyer, yet can impact its financial performance dramatically. The existing literature has overlooked these not-so-visible structural links. Using objective supply chain data collected from Mergent Online and Compustat, we map the supply base structure of 867 public firms. We construct three visible (horizontal, vertical and spatial) and two not-so-visible (eliminative and cooperative) structural complexity metrics, and examine their impacts on buyer firms' financial performance as measured by Return on Assets and Tobin's Q. Our empirical analysis shows that the five dimensions have differential effects: some have negligible impacts while others appear to strongly affect financial performance. Contrary to the common belief that complexity hurts performance, we find that an individual complexity dimension may have both positive and negative effects, and the overall effect may be non-linear.

Linking fishes to multiple metrics of coral reef structural complexity using three-dimensional technology

Structural complexity strongly influences biodiversity and ecosystem productivity. On coral reefs, structural complexity is typically measured using a single and small-scale metric (‘rugosity’) that represents multiple spatial attributes differentially exploited by species, thus limiting a complete understanding of how fish associate with reef structure. We used a novel approach to compare relationships between fishes and previously unavailable components of reef complexity, and contrasted the results against the traditional rugosity index. This study focused on damselfish to explore relationships between fishes and reef structure. Three territorial species, with contrasting trophic habits and expected use of the reef structure, were examined to infer the potential species-specific mechanisms associated with how complexity influences habitat selection. Three-dimensional reef reconstructions from photogrammetry quantified the following metrics of habitat quality: 1) visual exposure to predators and competitors, 2) density of predation refuges and 3) substrate-related food availability. These metrics explained the species distribution better than the traditional measure of rugosity, and each species responded to different complexity components. Given that a critical effect of reef degradation is loss of structure, adopting three-dimensional technologies potentially offers a new tool to both understand species-habitat association and help forecast how fishes will be affected by the flattening of reefs.