scholarly journals Multi-scale Cover Selection by White-tailed Deer, Odocoileus virginianus, in an Agro-forested Landscape

2009 ◽  
Vol 123 (1) ◽  
pp. 32
Author(s):  
Tim L. Hiller ◽  
Henry Campa ◽  
Scott R. Winterstein

Resource selection studies are commonly conducted at a single spatial scale, but this likely does not fully or accurately assess the hierarchical selection process used by animals. We used a multi-spatial scale approach to quantify White-tailed Deer (Odocoileus virginianus) cover selection in south-central Michigan during 2004–2006 by varying definitions of use and availability and ranking the relative importance of cover types under each study design. The number of cover types assigned as selected (proportional use > proportional availability) decreased from coarse (landscape level) to fine (within home range) scales, although at finer scales, selection seemed to be more consistent. Although the relative importance changed substantially across spatial scales, two cover types (conifers, upland deciduous forests) were consistently ranked as the two most important, providing strong evidence of their value to deer in the study area. Testing for resource selection patterns using a multi-spatial scale approach would provide additional insight into the ecology and behavior of a particular species.

2021 ◽  
Vol 12 ◽  
Author(s):  
Francesco Giardini ◽  
Erica Lazzeri ◽  
Giulia Vitale ◽  
Cecilia Ferrantini ◽  
Irene Costantini ◽  
...  

Proper three-dimensional (3D)-cardiomyocyte orientation is important for an effective tension production in cardiac muscle. Cardiac diseases can cause severe remodeling processes in the heart, such as cellular misalignment, that can affect both the electrical and mechanical functions of the organ. To date, a proven methodology to map and quantify myocytes disarray in massive samples is missing. In this study, we present an experimental pipeline to reconstruct and analyze the 3D cardiomyocyte architecture in massive samples. We employed tissue clearing, staining, and advanced microscopy techniques to detect sarcomeres in relatively large human myocardial strips with micrometric resolution. Z-bands periodicity was exploited in a frequency analysis approach to extract the 3D myofilament orientation, providing an orientation map used to characterize the tissue organization at different spatial scales. As a proof-of-principle, we applied the proposed method to healthy and pathologically remodeled human cardiac tissue strips. Preliminary results suggest the reliability of the method: strips from a healthy donor are characterized by a well-organized tissue, where the local disarray is log-normally distributed and slightly depends on the spatial scale of analysis; on the contrary, pathological strips show pronounced tissue disorganization, characterized by local disarray significantly dependent on the spatial scale of analysis. A virtual sample generator is developed to link this multi-scale disarray analysis with the underlying cellular architecture. This approach allowed us to quantitatively assess tissue organization in terms of 3D myocyte angular dispersion and may pave the way for developing novel predictive models based on structural data at cellular resolution.


2021 ◽  
Vol 9 ◽  
Author(s):  
David S. Pescador ◽  
Francesco de Bello ◽  
Jesús López-Angulo ◽  
Fernando Valladares ◽  
Adrián Escudero

Understanding how functional and phylogenetic patterns vary among scales and along ecological gradients within a given species pool is critical for inferring community assembly processes. However, we lack a clear understanding of these patterns in stressful habitats such as Mediterranean high mountains where ongoing global warming is expected to affect species fitness and species interactions, and subsequently species turnover. In this study, we investigated 39 grasslands with the same type of plant community and very little species turnover across an elevation gradient above the treeline at Sierra de Guadarrama National Park in central Spain. In particular, we assessed functional and phylogenetic patterns, including functional heterogeneity, using a multi-scale approach (cells, subplots, and plots) and determined the relevance of key ecological factors (i.e., elevation, potential solar radiation, pH, soil organic carbon, species richness, and functional heterogeneity) that affect functional and phylogenetic patterns at each spatial scale. Overall, at the plot scale, coexisting species tended to be more functionally and phylogenetically similar. By contrast, at the subplot and cell scales, species tended to be more functionally different but phylogenetically similar. Functional heterogeneity at the cell scale was comparable to the variation across plots along the gradient. The relevance of ecological factors that regulate diversity patterns varied among spatial scales. An increase in elevation resulted in functional clustering at larger scales and phylogenetic overdispersion at a smaller scale. The soil pH and organic carbon levels exhibited complex functional patterns, especially at small spatial scales, where an increase in pH led to clustering patterns for the traits related to the leaf economic spectrum (i.e., foliar thickness, specific leaf area, and leaf dry matter content). Our findings confirm the presence of primary environmental filters (coldness and summer drought at our study sites) that constrain the regional species pool, suggesting the presence of additional assembly mechanisms that act at the smallest scale (e.g., micro-environmental gradients and/or species interactions). Functional and phylogenetic relatedness should be determined using a multi-scale approach to help interpret community assembly processes and understand the initial community responses to environmental changes, including ongoing global warming.


2007 ◽  
Vol 85 (3) ◽  
pp. 372-380 ◽  
Author(s):  
Johan Månsson ◽  
Henrik Andrén ◽  
Åke Pehrson ◽  
Roger Bergström

Scale dependence is a fundamentally important topic in ecology because it determines whether results can be generalized over different spatial scales. We studied the relationship between forage consumption by moose ( Alces alces (L., 1758)) and forage availability across six nested spatial scales in south-central Sweden. By using multiple regression, we concluded that the amount of available forage was the best single variable explaining absolute consumption, irrespectively of scale. Forage species diversity, site productivity, and moose density were also important for predicting forage consumption, but their effects differed across the different spatial scales. A multiple regression including forage availability, moose density, site productivity, and forage diversity explained between 31% and 49% of the variation in forage consumption. The importance of a moose index as an explanatory variable decreased with increasing spatial scale, whereas the importance of site productivity increased. According to model selection based on Akaike's information criterion, the same model was ranked highest at the four smallest spatial scales, whereas the top-ranked models at the two largest spatial scales differed. Furthermore, the relationship between consumption and forage availability changed from underutilization at small scales to proportional use at the home range level. Thus, for a comprehensive understanding of moose browsing in relation to food resources, we conclude that a multi-scale approach is necessary.


2016 ◽  
Vol 2 ◽  
pp. e80 ◽  
Author(s):  
Alexander Toet

We propose a multi-scale image fusion scheme based on guided filtering. Guided filtering can effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves spatial consistency by using guided filtering both at the decomposition and at the recombination stage of the multi-scale fusion process. First, size-selective iterative guided filtering is applied to decompose the source images into approximation and residual layers at multiple spatial scales. Then, frequency-tuned filtering is used to compute saliency maps at successive spatial scales. Next, at each spatial scale binary weighting maps are obtained as the pixelwise maximum of corresponding source saliency maps. Guided filtering of the binary weighting maps with their corresponding source images as guidance images serves to reduce noise and to restore spatial consistency. The final fused image is obtained as the weighted recombination of the individual residual layers and the mean of the approximation layers at the coarsest spatial scale. Application to multiband visual (intensified) and thermal infrared imagery demonstrates that the proposed method obtains state-of-the-art performance for the fusion of multispectral nightvision images. The method has a simple implementation and is computationally efficient.


2018 ◽  
Author(s):  
F. Reyes ◽  
B. Pallas ◽  
C. Pradal ◽  
F. Vaggi ◽  
D. Zanotelli ◽  
...  

ABSTRACTBackground and aimsCarbon allocation in plants is usually represented at a specific spatial scale, peculiar to each model. This makes the results obtained by different models, and the impact of their scale of representation, difficult to compare. In this work we developed a Multi Scale Carbon Allocation model (MuSCA) that can be applied at different, user-defined, topological scales of a plant, and used to assess the impact of each spatial scale on simulated results and computation time.MethodsModel multi-scale consistency and behavior were tested by applications on three realistic apple tree structures. Carbon allocation was computed at five spatial scales, spanning from the metamer (the finest scale, used as a reference) up to 1st order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data.Key ResultsThe model showed physiological coherence in representing competition for carbon assimilates. Results from intermediate values of the friction parameter best fitted the field data. For these, fruit growth simulated at the metamer scale (considered as a reference) differed from about 1% at growth unit scale up to 35% at first order branch scale. Generally, the coarser the spatial scale the more fruit growth diverged from the reference and the lower the obtained within-tree fruit growth variability. Coherence in the carbon allocated across scales was also differently impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time up to four orders of magnitude.ConclusionsMuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation, suggesting that this factor should be carefully evaluated when using different carbon allocation models or comparing their results. Trades-off between computation time and prediction accuracy can be evaluated by changing topological scales.


2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.


Author(s):  
Alessandra R. Kortz ◽  
Anne E. Magurran

AbstractHow do invasive species change native biodiversity? One reason why this long-standing question remains challenging to answer could be because the main focus of the invasion literature has been on shifts in species richness (a measure of α-diversity). As the underlying components of community structure—intraspecific aggregation, interspecific density and the species abundance distribution (SAD)—are potentially impacted in different ways during invasion, trends in species richness provide only limited insight into the mechanisms leading to biodiversity change. In addition, these impacts can be manifested in distinct ways at different spatial scales. Here we take advantage of the new Measurement of Biodiversity (MoB) framework to reanalyse data collected in an invasion front in the Brazilian Cerrado biodiversity hotspot. We show that, by using the MoB multi-scale approach, we are able to link reductions in species richness in invaded sites to restructuring in the SAD. This restructuring takes the form of lower evenness in sites invaded by pines relative to sites without pines. Shifts in aggregation also occur. There is a clear signature of spatial scale in biodiversity change linked to the presence of an invasive species. These results demonstrate how the MoB approach can play an important role in helping invasion ecologists, field biologists and conservation managers move towards a more mechanistic approach to detecting and interpreting changes in ecological systems following invasion.


Author(s):  
Jia-Rong Yeh ◽  
Chung-Kang Peng ◽  
Norden E. Huang

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal’s complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease.


Author(s):  
Chunli Zhao ◽  
Jianguo Chen ◽  
Peng Du ◽  
Hongyong Yuan

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.


2010 ◽  
Vol 61 (11) ◽  
pp. 1227 ◽  
Author(s):  
Elisabeth M. A. Strain ◽  
Craig R. Johnson

Habitat characteristics can influence marine herbivore densities at a range of spatial scales. We examined the relationship between benthic habitat characteristics and adult blacklip abalone (Haliotis rubra) densities across local scales (0.0625–16 m2), at 2 depths, 4 sites and 2 locations, in Tasmania, Australia. Biotic characteristics that were highly correlated with abalone densities included cover of non-calcareous encrusting red algae (NERA), non-geniculate coralline algae (NCA), a matrix of filamentous algae and sediment, sessile invertebrates, and foliose red algae. The precision of relationships varied with spatial scale. At smaller scales (0.0625–0.25 m2), there was a positive relationship between NERA and ERA, and negative relationships between sediment matrix, sessile invertebrates and abalone densities. At the largest scale (16 m2), there was a positive relationship between NERA and abalone densities. Thus, for some biotic characteristics, the relationship between NERA and abalone densities may be scalable. There was very little variability between depths and sites; however, the optimal spatial scale differed between locations. Our results suggest a dynamic interplay between the behavioural responses of H. rubra to microhabitat and/or to abalone maintaining NERA free of algae, sediment, and sessile invertebrates. This approach could be used to describe the relationship between habitat characteristics and species densities at the optimal spatial scales.


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