Multiple Spatial Scale Research Articles

Impacts of multiple temporal and spatial scale drought on grassland vegetation dynamics in the Tibetan Plateau region of China, 1982–2015

The Tibetan Plateau is a sensitive area to global climate change, and the special natural environmental conditions have nurtured extremely fragile vegetation and its ecosystems, making it one of the ideal regions to study the response of vegetation to climate change. In this study, we used the drought index (SPEI) and the vegetation index (NDVI) as drought and green indicators, respectively. The spatial and temporal variation patterns of vegetation greenness on the Tibetan Plateau from 1982 to 2015 were analysed, and the response of vegetation greenness to dry and wet changes was investigated. The results showed that the grassland vegetation improved overall (slope = 0.00015, P < 0.05) and degraded locally during 34 years. The NDVI of grassland vegetation showed an increasing trend from 1982 to 2008 (slope = 0.00005, P = 0.86), and a significant decreasing trend from 2009 to 2015 (slope = −0.002, P < 0.05). The degraded areas of grassland NDVI were mainly distributed in wet areas. Meanwhile, the Tibetan Plateau as a whole showed a non-significant trend of increasing drought, with a mitigating trend of drought in dry areas and an increasing trend of drought in wet areas. The probability of vegetation growth loss was higher with increasing drought. The vulnerability of grassland vegetation to drought events was significantly higher in the humid region than in the arid region. Under the current drought intensification, the risk of loss of grassland vegetation to drought in the humid zone will increase. This suggests that we need to pay more attention to the stability of vegetation in the humid region and drought trends.

Habitat choice for narrowly distributed species: Multiple spatial scales of habitat selection for the Mangshan pit viper

Understanding habitat demand is key to in situ fauna conservation. While there is increasing evidence of the importance of habitat selection research at multiple spatial scales, snake habitat research has typically neglected the rationality of selecting the size of each spatial scale and quantitative research at the macro scale. The Mangshan pit viper (Protobothrops mangshanensis) is a national first-class key protected species in China with a very narrow geographical distribution. Its habitat needs at multiple spatial scales have not yet been explored. Between 2016 and 2021, we studied the second order, third order, and fourth order of habitat selection of P. mangshanensis. The selection of macro (second order, third order) spatial scales refers to the size of the pit viper’s home range. For second order of habitat selection, P. mangshanensis selected areas with high average tree height (> 12 m), it avoiding areas with a high proportion of coniferous forest (< 27%). At the third order of habitat selection, it selectively used areas close to mountain streams (< 48 m), but avoided areas close to canopy gaps (> 52 m). At the fourth order of habitat selection, it chose fallen logs (> 22%) and vegetative coverage, such as shrubs (> 30%) and herbs (> 18%). The multiple spatial scale analysis reveals the relationship between P. mangshanensis and its habitat and demonstrates that more attention should be paid to habitat protection at different spatial scales.

Matching ecosystem services supply and demand in China's urban agglomerations for multiple-scale management

The unprecedented urbanization rate has profoundly impacted ecosystem functions and increased the demand for ecosystem services. Moving towards sustainable cities requires an insightful understanding of ecosystem services supply and demand (ESSD). However, most ESSD studies ignore the spillover effects of ecosystem services, hindering sustainable urban agglomeration (UA) development from multiple spatial scale perspectives. This study evaluated the supply, demand, and sustainability of urban ecosystem services, including food production, water retention, soil retention, and carbon sequestration, by considering 19 UAs in China (including 236 cities). The results showed that the supply and demand of urban ecosystem services increased from 2000 to 2020, together with spatial heterogeneity. A decrease in the sustainability of food production was observed at medium UAs. Large UAs can achieve sustainability of all studied ecosystem services at both the UAs' and national scales. However, the medium UAs in the northwest were unsustainable regarding water retention and carbon sequestration at the UAs’ scale. Land use/land cover (LULC) change was the key factor in ESSD change, followed by population. Finally, policy implications were proposed, including bringing ESSD into land use decision-making, reducing ecosystem service demand, implementing targeted restoration, and multiple-scale management.

Effect of multiple spatial scale characterization of land use on water quality.

Land use in uplands is an important factor affecting water quality in its respective catchment, and its influences at the different spatial scales and configurations warrant further investigation. Here, we selected 26 catchments in the upper Han River (China) and sampled the surface water at the outlet of each catchment in four seasons during 2019. Multivariate statistics were used to identify the relationships between land use characteristics in uplands and water quality in river system. The results indicated that chemical oxygen demand (CODMn); pH; dissolved oxygen; electrical conductivity; nutrient, i.e., NH4+-N, NO3--N; and dissolved phosphorus (DP) in rivers displayed significant seasonal variations. Stepwise regression revealed that landscape metrics such as patch density, landscape shape index, and splitting index were important factors influencing water quality in rivers regardless of their spatiality and seasonality. Urban was the most frequently chosen land-use type in the best prediction models, and forest area showed a negative correlation with water quality parameters in most cases for example, DP. Overall, the influence of land use on river water quality was slightly stronger at reach scale than at catchment and riparian scales. Also, nutrients (i.e., NH4+-N, NO3--N, and DP) in rivers were primarily impacted by the land use characteristic at catchment and riparian scales. Our results suggested that multi-scale explorations would help to achieve a fully understanding on the impacts of land use on river water quality.

Multiple spatial scale mapping of time-resolved brain network reconfiguration during evoked pain in patients with rheumatoid arthritis.

Functional brain networks and the perception of pain can fluctuate over time. However, how the time-dependent reconfiguration of functional brain networks contributes to chronic pain remains largely unexplained. Here, we explored time-varying changes in brain network integration and segregation during pain over a disease-affected area (joint) compared to a neutral site (thumbnail) in 28 patients with rheumatoid arthritis (RA) in comparison with 22 healthy controls (HC). During functional magnetic resonance imaging, all subjects received individually calibrated pain pressures corresponding to visual analog scale 50 mm at joint and thumbnail. We implemented a novel approach to track changes of task-based network connectivity over time. Within this framework, we quantified measures of integration (participation coefficient, PC) and segregation (within-module degree z-score). Using these network measures at multiple spatial scales, both at the level of single nodes (brain regions) and communities (clusters of nodes), we found that PC at the community level was generally higher in RA patients compared to HC during and after painful pressure over the inflamed joint and corresponding site in HC. This shows that all brain communities integrate more in RA patients than in HC for time points following painful stimulation to a disease-relevant body site. However, the elevated community-related integration seen in patients appeared to not pertain uniquely to painful stimulation at the inflamed joint, but also at the neutral thumbnail, as integration and segregation at the community level did not differ across body sites in patients. Moreover, there was no specific nodal contribution to brain network integration or segregation. Altogether, our findings indicate widespread and persistent changes in network interaction in RA patients compared to HC in response to painful stimulation.

Coralligenous assemblages of continental shelf: Multiple spatial scale variability in the western Sardinia

Mediterranean mesophotic hard bottoms are mostly characterized by coralligenous banks. Although investigations on this habitat have increased in the last years, knowledge about its structure and spatial variability is still very limited as most studies are focused on the description of assemblages of peculiar and small locations such as biodiversity hotspots. This study aimed at i) describing coralligenous megafauna on the western Sardinian continental shelf between 80 and 120 m of depth, ii) assessing the distribution of the dominant taxa, and iii) estimating patterns of spatial variability at different scales. The coralligenous banks were studied along five sectors of the western Sardinian continental shelf by means of Remote Operated Vehicles (ROVs) and images were analyzed to identify the main taxa or morphological groups and their abundance. Results highlighted several common patterns among sectors, with assemblages dominated by the gorgonians Eunicella cavolini and Callogorgia verticillata. On the other hand, some taxa (e.g. Callogorgia verticillata, Paramuricea hirsuta, Antipathella subpinnata, Corallium rubrum Paramuricea clavata, Poecillastra compressa and Aplidium spp.) mainly contribute to segregate the coralligenous assemblages within the considered sectors of this study. A high small-scale variability was also observed. The presence of extensive and well diversified mesophotic animal forests stresses the importance to improve the conservation of the western Sardinian continental shelf.

Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China.

Continuous air pollution (CAP) incidents last even longer and generate greater health hazards relative to conventional air pollution episodes. However, few studies have focused on the spatiotemporal distribution characteristics and driving factors of CAP in China. Drawing on the daily reported ground monitoring data on the ambient air quality in 2019 in China, this paper identifies the spatiotemporal distribution characteristics of CAP across 337 Chinese cities above the prefecture level using descriptive statistics and spatial statistical analysis methods, and further examines the spatial heterogeneity effects of both socioeconomic factors and natural factors on CAP with a Multiscale Geographically Weighted Regression (MGWR) model. The results show that the average proportion of CAP days in 2019 reached 11.50% of the whole year across Chinese cities, a figure equaling to about 65 days, while the average frequency, the maximum amount of days and the average amount of days of CAP were 8.02 times, 7.85 days and 4.20 days, respectively. Furthermore, there was a distinct spatiotemporal distribution disparity in CAP in China. Spatially, the areas with high proportions of CAP days were concentrated in the North China Plain and the Southwestern Xinjiang Autonomous Region in terms of the spatial pattern, while the proportion of CAP days showed a monthly W-shaped change in terms of the temporal pattern. In addition, the types of regions containing major pollutants during the CAP period could be divided into four types, including “Composite pollution”, “O3 + NO2 pollution”, “PM10 + PM2.5 pollution” and “O3 + PM2.5 pollution”, while the region type “PM10 + PM2.5 pollution” covered the highest number of cities. The MGWR model, characterized by multiple spatial scale impacts among the driving factors, outperformed the traditional OLS and GWR model, and both socioeconomic factors and natural factors were found to have a spatial non-stationary relationship with CAP in China. Our findings provide new policy insights for understanding the spatiotemporal distribution characteristics of CAP in urban China and can help the Chinese government make prevention and control measures of CAP incidents.

Research on Wastewater Treatment Monitoring Algorithms Based on Deep Convolutional Neural Networks

Around the problems of data loss, noise, and different temporal and spatial scale features of urban wastewater treatment process data, a method of monitoring and predicting wastewater treatment process data based on deep convolutional neural networks is proposed in the paper. Firstly, to address the problem that urban wastewater treatment process data has multiple spatial and temporal scale characteristics, which makes it difficult for the data to be used effectively, a spatial and temporal data fusion model based on fuzzy neural network (FNN) is proposed. Fuzzy neural networks have strong generalization ability and robustness. Secondly, to enable accurate and real-time monitoring of the content of the monitored components in the effluent of the urban wastewater treatment process, an intelligent prediction model based on SDF-FNN is established for the effluent. Finally, in order to verify the effectiveness of this intelligent prediction model, the model is tested using data collected from actual municipal wastewater treatment plants. The experimental results show that the wastewater treatment intelligent monitoring model is effective and can predict the content of the effluent monitoring index with high accuracy.

Simplifying the Process of Going From Cells to Tissues Using Statistical Mechanics.

The value of digital twins for prototyping controllers or interventions in a sandbox environment are well-established in engineering and physics. However, this is challenging for biophysics trying to seamlessly compose models of multiple spatial and temporal scale behavior into the digital twin. Two challenges stand out as constraining progress: (i) ensuring physical consistency of conservation laws across composite models and (ii) drawing useful and timely clinical and scientific information from conceptually and computationally complex models. Challenge (i) can be robustly addressed with bondgraphs. However, challenge (ii) is exacerbated using this approach. The complexity question can be looked at from multiple angles. First from the perspective of discretizations that reflect underlying biophysics (functional tissue units) and secondly by exploring maximum entropy as the principle guiding multicellular biophysics. Statistical mechanics, long applied to understanding emergent phenomena from atomic physics, coupled with the observation that cellular architecture in tissue is orchestrated by biophysical constraints on metabolism and communication, shows conceptual promise. This architecture along with cell specific properties can be used to define tissue specific network motifs associated with energetic contributions. Complexity can be addressed based on energy considerations and finding mean measures of dependent variables. A probability distribution of the tissue's network motif can be approximated with exponential random graph models. A prototype problem shows how these approaches could be implemented in practice and the type of information that could be extracted.

Organic agriculture and field edges uphold endospheric wheat microbiota at field and landscape scale.

Agricultural intensification has been demonstrated to induce a loss of biodiversity. Despite the key role of symbiotic microorganisms in plant nutrition and protection, the impact of agricultural intensification on these microorganisms is not fully understood. Organic farming and field edges (as semi-natural elements) may promote a higher microbial diversity thanks to lower anthropic disturbance and higher plant diversity. We sampled wheat individuals in pairs of wheat fields (one organic and one conventional) along a distance gradient to the edges (hedgerow vs. grassy), in 20 landscape windows selected along an uncorrelated gradient of organic farming and hedgerow density. We demonstrated that organic farming shaped microbial composition and increased fungal and bacterial richness, while hedgerows had a neutral or negative effect on richness depending on the microbial phyla considered. In contrast to bacteria, fungal communities were heterogeneously distributed within fields, having a higher diversity for some phyla close to field edges. Overall we highlighted that fungi responded more to the field scale while bacteria were more affected by landscape scale. The effect of agricultural intensification on plant microbiota and therefore on the functions provided by microorganisms to the plants has to be considered at a multiple spatial scale-from field to landscape.

Landscape Sustainability of Architecture in Fernando Menis’s Work: A Sensitive Design Rooted in Volcanic Nature

The many declinations of the idea of sustainability in architecture concern different disciplinary areas as well as all phases of the construction process. Alongside the more established categories of the sustainability of materials used and the technical construction processes and economic investments mobilized, there are now new facets of the idea of sustainability. They affect the impact that architecture can have on communities in terms of social relations and quality of context of life. This work explores the idea of landscape sustainability of architecture, understood as the ability of man-made interventions to belong to the context and the inhabitants, while promoting forms of alliance with the ecosystems at multiple spatial and temporal scale. Starting from the analysis of some trends in contemporary architecture that deals with these problems, the research identifies the volcanic environment as a terrain for exploration, with particular interest in its natural characteristics and dynamic interactions with anthropic contexts. After choosing the region of Macaronesia as a case study, the research focuses on the work of Fernando Menis. As an architect from the Canary Islands, he has developed his own modus operandi which, while rooted in its original context, is inspired by principles of social, cultural, and landscape sustainability of architecture that are valid today everywhere. The objective of this work is therefore to draw a reflection from his architectural poetics, with the intention of outlining the features of a possible contemporary design posture based on principles of landscape sustainability.

An improved multi-scale two phase method for bubbly flows

Multiple spatial scale is an important characteristic of two phase flow phenomena. The micro-scale and macro-scale flow structures are obviously different in flow state and have different effects on the mass, momentum and energy transfer between two phases. Different modeling approaches have been developed for each scale physical phenomenon in traditional numerical simulations. However, it is difficult to simulate two phase flow systems with multi-scale flow structures simultaneously. In order to address this problem, a multi-scale two phase method is developed based on the combination of Volume of Fluid (VOF) interface capture method and Euler–Lagrange particle tracking method. The fundamental assumption of the present method is that there is a clear scale separation between VOF interfaces and bubbles. Therefore, VOF method with artificial compressive algorithm is used to simulate the dynamic evolution of macro-scale air-water interface. While Euler–Lagrange method is used to track the micro-scale bubbles that cannot be captured in grids. Collision, coalescence and breakup of Lagrange bubbles and two-way coupling are fully considered to construct a comprehensive micro-bubble solving procedure. Transformation criteria and the corresponding algorithms between micro-scale and macro-scale flow structures are designed and discussed in detail. In addition, a new curvature-based algorithm for the transformation from VOF interface to Lagrange bubbles is proposed. Simulations of typical two phase flow problems involving multi-scale flow transformation are carried out to test the performance of the multi-scale solver. Results indicate that the multi-scale two phase method performs significantly better than the pure VOF method in capturing micro-scale phenomena. Besides, the curvature-based transformation algorithm proposed in this paper is proved to be more precise and efficient than the previous identify-based one. From the perspective of simulation accuracy and efficiency, the multi-scale two phase method is more promising for the simulation of actual complex two-phase flows.

Multiple Spatial Scale Analysis of the Niche Characteristics of the Rhododendron dauricum Plant Communities in Northeast China

This study aims to verify the concept of niches at multiple spatial scales in plant communities. To this end, we analyzed the niche characteristic of Rhododendron dauricum plant communities in Northeast China at three spatial scales. At the local scale, we calculated the Importance Value (IV) of species in five communities in the north of the Da Hinggan Mountains. At the intermediate scale, we examined five communities in their entirety, calculated the niche breadth of the species, and integrated niche overlap and interspecific association to analyze interspecific relationships. Further, the generalized additive model (GAM) was used to analyze the impact of topography and soil factors on niche characteristics. At the regional scale, we analyzed the geographical distribution of dominant species of R. dauricum plant communities in Northeast China and used principal component analysis (PCA) to analyze the impact of geographical and climate factors on species distribution. The results show that at the local scale, the IV of the species in each community varies widely. At the intermediate scale, species with a wide niche breadth tend to have a high value for IV. Larix gmelinii, Betula platyphylla, R. dauricum, Ledum palustre, and Vaccinium vitis-idaea had a relatively wide niche breadth and a high niche overlap, and the interspecific associations were almost all positive. Elevation and soil nutrients were the most dominant environmental factors. At the regional scale, species with a wide niche breadth tend to have a wide range of distribution, and temperature and precipitation were the most dominant environmental factors. This study suggests that the niche characteristics at three scales are both related and different. Niche characteristics at the local scale were various and labile, and niche characteristics at the intermediate and regional scales were relatively regular. These results show some degree of consistency with previous studies from an evolutionary perspective. The action mechanisms of these communities are related to differences in the dominant environmental factors. In addition, the integration of niche overlap and interspecific association determine interspecific relationships more accurately.

Multi-scale drivers of soil resistance predict vulnerability of seasonally wet meadows to trampling by pack stock animals in the Sierra Nevada, USA

BackgroundMeadow ecosystems have important ecological functions and support socioeconomic services, yet are subject to multiple stressors that can lead to rapid degradation. In the Sierra Nevada of the western USA, recreational pack stock (horses and mules) use in seasonally wet mountain meadows may lead to soil trampling and meadow degradation, especially when soil water content is high and vegetation is developing.MethodsIn order to improve the ability to predict meadow vulnerability to soil disturbance from pack stock use, we measured soil resistance (SR), which is an index of vulnerability to trampling disturbance, at two spatial scales using a stratified-random sampling design. We then compared SR to several soil and vegetation explanatory variables that were also measured at the two spatial scales: plant community type (local scale) and topographic gradient class (meadow scale).ResultsWe found that local-scale differences in drivers of SR were contingent on the meadow scale, which is important because multiple spatial scale evaluation of ecological metrics provides a broader understanding of the potential controls on ecological processes than assessments conducted at a single spatial scale. We also found two contrasting explanatory models for drivers of SR at the local scale: (1) soil gravimetric water content effects on soil disaggregation and (2) soil bulk density and root mass influence on soil cohesion. Soil resistance was insufficient to sustain pack stock use without incurring soil deformation in wet plant communities, even when plant cover was maximal during a major drought.ConclusionsOur study provides new information on seasonally wet meadow vulnerability to trampling by pack stock animals using multi-scale drivers of SR, including the contrasting roles of soil disaggregation, friction, and cohesion. Our work aims to inform meadow management efforts in the Sierra Nevada and herbaceous ecosystems in similar regions that are subject to seasonal soil saturation and livestock use.

Distribution of agricultural land regulates stream water isotopes over multiple spatial scale in a subtropical forested watershed

Distribution of agricultural land regulates stream water isotopes over multiple spatial scale in a subtropical forested watershed

Photovoltaic–wind joint power probability model based on multiple temporal and spatial scale

With an increasing number of renewable energy integrated into the power system, the impact of intermittent and random wind power and photovoltaic power on the power system is becoming larger and larger. To study the probabilistic correlation between wind power and photovoltaic power on different temporal and spatial scale, a joint probability model needs to be established. On the basis of the third-order Gaussian mixture model, a photovoltaic-wind joint power probability model is proposed in this study. By analysing the statistical probability characteristics of the measured power output data, this method avoids the error accumulation caused by the individual modelling of the wind and photovoltaic generators and considers the joint correlation between wind power and photovoltaic power. On the basis of this model, the corresponding time series of wind power and photovoltaic power is calculated. The results indicated that the coastal joint power probability model and the inland joint power probability model are quite different on the same time scale, the parameters of joint probability model on different time scales are close to each other. The effectiveness of the proposed method is verified by the measured data.

Urban sprawl in a megaregion: A multiple spatial and temporal perspective

Numerous studies have been conducted to examine the characteristics of urban sprawl at multiple scales, ranging from neighborhood, to city, and metropolitan statistical area. However, few studies have investigated urban sprawl in a megaregion, particularly from a multiple spatial and temporal scale perspective. Focusing on the Beijing-Tianjin-Hebei (BTH) megaregion, one of the largest urban megaregion in China, we quantified the multiscale characteristics of urban sprawl, and how they changed by time, using a combination of density (land consumption per capita) and centrality (Moran’s I coefficient of developed land) indicators. We found: (1) The BTH urban megaregion experienced rapid urban expansion during 1984–2015, with large variations in annual growth rates, and the two measures of sprawl among cities and counties. (2) Land consumption per capita in the megaregion had a clear increasing trend at all three levels, suggesting decreased density and land use efficiency, and thus increased urban sprawl. (3) In contrast, Moran’s I coefficient had trends of increase at multiple scales, suggesting urban developed lands tended to become more clustered spatially. (4) Nonlinear relationships between the two measures of sprawl and the total area and proportional cover of developed lands at county level. Land consumption per capita first increased, and then decreased with the increase of the total area and proportional cover of developed lands, following the pattern of the reversed U shape curve. Similar patterns were found for Moran’s I coefficient. Our results highlight the importance of quantifying urban sprawl at multiple temporal and spatial scales, using multi-dimensional indicators. Results from this study can enhance our understanding on the spatiotemporal characteristics of urban sprawl, and can provide important insights to inform public policy for urban growth management and planning.

Multiple Spatial Scale Analysis Provide an Understanding of Benthic Macro-Invertebrate Community Structure Across a Lagoonal Ecosystem

Chilika, the largest coastal lagoon of Asia, represents a complex transitional zone between terrestrial and marine ecosystems. In this study benthic macro-invertebrate community structure was elucidated based on multiple spatial scales approach (station-wise, sector-wise and region-wise) across Chilika from June 2013 to February 2015 (temporal scale), encompassing 23 pre-selected stations in link with measurement of abiotic parameters. Sixty two macro-invertebrate species representing seven macrofaunal groups were encountered, of which gastropods were the most abundant in terms of density (~96%) and species composition (~43%), and crustaceans were the least. The structure of the macrofaunal community (in terms of abundance) showed significant differences across spatial (station-wise, sector-wise and region-wise), and temporal scales (month-wise). While macro-invertebrate species composition revealed heterogeneity both station-wise and month-wise but it was found to be homogenous within the sector-wise and region-wise scales. BIO-ENV analysis indicated that salinity together with sediment nature were major abiotic variables associated with observed macro-invertebrate patterns. The results together demonstrated that macro-invertebrate communities are adapted to prevailing environmental conditions of Chilika lagoon; homogeneous and heterogeneous distribution and diversity patterns across multiple spatial scales revealed assemblages distinct to this ecosystem. The multiple scales approach could prove to be useful for ecological monitoring of lagoons.

Control factors and scale analysis of annual river water, sediments and carbon transport in China.

Under the context of dramatic human disturbances on river system, the processes that control the transport of water, sediment, and carbon from river basins to coastal seas are not completely understood. Here we performed a quantitative synthesis for 121 sites across China to find control factors of annual river exports (Rc: runoff coefficient; TSSC: total suspended sediment concentration; TSSL: total suspended sediment loads; TOCL: total organic carbon loads) at different spatial scales. The results indicated that human activities such as dam construction and vegetation restoration might have a greater influence than climate on the transport of river sediment and carbon, although climate was a major driver of Rc. Multiple spatial scale analyses indicated that Rc increased from the small to medium scale by 20% and then decreased at the sizable scale by 20%. TSSC decreased from the small to sizeable scale but increase from the sizeable to large scales; however, TSSL significantly decreased from small (768 g·m−2·a−1) to medium spatial scale basins (258 g·m−2·a−1), and TOCL decreased from the medium to large scale. Our results will improve the understanding of water, sediment and carbon transport processes and contribute better water and land resources management strategies from different spatial scales.

Cross‐Shelf Habitat Occupancy Probabilities for Juvenile Groupers in the Florida Keys Coral Reef Ecosystem

AbstractIn the Florida Keys coral reef ecosystem, delineation of reef fish distributions in relationship to habitat patterns is important for improving the design characteristics of fishery‐independent surveys. Efficient survey design depends on analysis of fish distribution patterns to inform and improve the precision of future surveys. We used a diver visual survey to quantify occupancy patterns of preexploitation‐size Black GrouperMycteroperca bonaciand Red GrouperEpinephelus morio. The survey was based on a stratified random sampling design with strata reflecting cross‐shelf coral reef habitat types. A multiple spatial scale modeling approach confirmed a cross‐shelf occurrence gradient for Red Grouper, with higher nearer‐to‐shore occupancy probability and lower offshore occupancy probability. Black Grouper occurrence followed a latitudinal gradient, with higher occurrence probabilities in the lower Florida Keys than in the upper Keys. Local habitat characteristics measured within reef strata suggested that occupancy relationships for both species varied according to vertical relief. Our analysis also included multilevel slope coefficients (random effects), which revealed unforeseen variance structure in Black Grouper occurrence probability among cross‐shelf reef strata. Our study improves on previous qualitative observations of juvenile grouper distributions in the Florida Keys and highlights the use of multilevel models in revealing variance structures of fish distributions not revealed by fixed‐effects models. Our analysis contributes to a discussion about foraging characteristics in producing the observed distributional patterns, and we suggest that examining the links between the distributions of forage fishes and larger predators (i.e., groupers) would be a useful step in improving survey stratification schemes.Received February 23, 2015; accepted July 2, 2015