Landscape Configuration Influences Species Occupancy Over Multiple Spatial Scales: A Case Study On Tawny Owl

2021 ◽  
Author(s):  
Jakob Wildraut ◽  
Marco Basile
Keyword(s):  
Spatial Scale ◽  
Spatial Scales ◽  
Coniferous Forest ◽  
Landscape Configuration ◽  
Species Occurrence ◽  
Forest Patches ◽  
Tawny Owl ◽  
Generalist Species ◽  
Multiple Spatial Scales ◽  
Time Substitution

ABSTRACT Landscape configuration can influence the distribution of species across multiple spatial scales. The primary factors related to this process are connectivity, the size and position of habitat patches, and edge effects. These factors together determine the overall fragmentation of a landscape, which in turn influences species occurrence. Although some species show a negative response to fragmentation, others benefit from it. Potential effects may act over multiple spatial scales, possibly with contrasting effects on species occurrence. We chose the Tawny Owl (Strix aluco), a ubiquitous and generalist species, to study the influence of fragmentation on species occurrence and to identify relevant landscape metrics, using multi-scale hierarchical modelling. Between 2016 and 2018, we recorded Tawny Owls on 64 sampling sites located in a forested landscape. We used a space-for-time substitution in the framework of occupancy modelling to assess Tawny Owl responses to landscape fragmentation. We found that the Tawny Owl is widespread in the study area. Its distribution across the landscape (larger spatial scale) was related to a heterogeneous configuration of forest patches, while high connectivity of coniferous forest influenced its occurrence at a smaller spatial scale (sites). Overall, the Tawny Owl prefers landscapes with well-connected forest patches and an uneven patch distribution in the surrounding area.

scholarly journals Testing the Eltonian Noise Hypothesis in a Species-rich Community

2021 ◽  
Author(s):  
Robert Francis ◽  
David Berg ◽  
Neil Ford ◽  
Ashley Walters
Keyword(s):  
Spatial Scale ◽  
Species Interactions ◽  
Spatial Scales ◽  
Freshwater Mussel ◽  
Strong Interactions ◽  
Ecological Niche Models ◽  
Distribution Models ◽  
Multiple Spatial Scales ◽  
Presence Data ◽  
Negative Relationships

Few ecological niche models (ENM) incorporate the Eltonian niche or examine a population’s niche at multiple spatial scales. We used Bayesian Joint Species Distribution Models (JSDMs) across multiple spatial scales to examine whether freshwater mussel communities in east Texas adhered to the Eltonian Noise Hypothesis, which asserts that species interactions exert greater influence on conspecific species at finer spatial scales. For both abundance and presence data, we observed a statistically greater number of strong interactions at the finest spatial scale compared to larger spatial scales. While 34% of abundance interactions and 24% of presence interactions showed strong positive relationships, only 6% of abundance interactions and 0% of presence interactions showed strong negative relationships. We found that freshwater mussel communities conform to the Eltonian Noise Hypothesis. Inclusion of the Eltonian niche and consideration of spatial scale are necessary to accurately model niches and increase efficacy of ENMs as conservation tools.

scholarly journals Landscape structure shapes the diversity of tree seedlings at multiple spatial scales in a fragmented tropical rainforest

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253284
Author(s):  
Sergio Nicasio-Arzeta ◽  
Isela E. Zermeño-Hernández ◽  
Susana Maza-Villalobos ◽  
Julieta Benítez-Malvido
Keyword(s):  
Landscape Structure ◽  
Secondary Forest ◽  
Spatial Scales ◽  
Landscape Composition ◽  
Landscape Configuration ◽  
Secondary Forests ◽  
Tree Seedling ◽  
Forest Patches ◽  
Β Diversity ◽  
Α Diversity

The maintenance of seedling diversity of animal-dispersed tree species is fundamental for the structure and function of forest patches in fragmented tropical rainforests. Nonetheless, the effects of landscape structure at different spatial scales on α- and β-diversity of tree seedling communities are recently explored. Using a multi-scale approach, we assessed the relative effect of landscape composition and configuration on α- and β-diversity of animal-dispersed seedlings within 16 forest patches in the Lacandona rainforest, Mexico. We assessed these effects at 13 spatial scales (from 300 to 1500 m radius, at 100 m intervals) for three metrics of effective number of species considering α- and β-diversity. We found that α-diversity was largely affected by landscape composition and β-diversity by landscape configuration. On the one hand, the amount of secondary forest influenced α-diversity. Additionally, species richness increased in landscapes with highly aggregated forest patches. On the other hand, β-diversity was affected positively by forest fragmentation and negatively by the edge contrast of forest patches with the surrounding matrix. Our findings indicate that landscape configuration is a strong driver of seedling diversity in highly deforested rainforests. Promoting forest patches and secondary forests through payment for ecosystem services’ programs, favoring matrix quality within land-sharing schemes of smallholder agriculture and secondary forest management, and identifying restoration opportunities for assisted or unassisted natural regeneration are urgently needed for conservation of seedling diversity in human-modified tropical landscapes.

scholarly journals Subjective wellbeing at different spatial scales for individuals satisfied and dissatisfied with life

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6502 ◽  
Author(s):  
Ida Kubiszewski ◽  
Nabeeh Zakariyya ◽  
Diane Jarvis
Keyword(s):  
Life Satisfaction ◽  
Regression Analysis ◽  
Spatial Scale ◽  
Subjective Wellbeing ◽  
Multiple Scales ◽  
Spatial Scales ◽  
National Level ◽  
International Comparisons ◽  
Multiple Spatial Scales ◽  
The World

Indicators that attempt to gauge wellbeing have been created and used at multiple spatial scales around the world. The most commonly used indicators are at the national level to enable international comparisons. When analyzing subjective life satisfaction (LS), an aspect of wellbeing, at multiple spatial scales in Australia, variables (drawn from environmental, social, and economic domains) that are significantly correlated to LS at smaller scales become less significant at larger sub-national scales. The reverse is seen for other variables, which become more significant at larger scales. Regression analysis over multiple scales on three groups (1) all individuals within the sample, (2) individuals with self-reported LS as dissatisfied (LS ≤ 5), and (3) individuals self-reporting LS as satisfied (LS > 5), show that variables critical for LS differ between subgroups of the sample as well as by spatial scale. Wellbeing measures need to be created at multiple scales appropriate to the purpose of the indicator. Concurrently, policies need to address the factors that are important to wellbeing at those respective scales, segments, and values of the population.

scholarly journals Modeling Pediatric Body Mass Index and Neighborhood Environment at Different Spatial Scales

2018 ◽  
Vol 15 (3) ◽  
pp. 473 ◽  
Author(s):  
Lauren Grant ◽  
Chris Gennings ◽  
Edmond Wickham ◽  
Derek Chapman ◽  
Shumei Sun ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Census Tract ◽  
Spatial Scales ◽  
Block Group ◽  
Group Level ◽  
Census Block ◽  
Census Block Group ◽  
Multiple Spatial Scales ◽  
Census Tract Level ◽  
Selection Of

In public health research, it has been well established that geographic location plays an important role in influencing health outcomes. In recent years, there has been an increased emphasis on the impact of neighborhood or contextual factors as potential risk factors for childhood obesity. Some neighborhood factors relevant to childhood obesity include access to food sources, access to recreational facilities, neighborhood safety, and socioeconomic status (SES) variables. It is common for neighborhood or area-level variables to be available at multiple spatial scales (SS) or geographic units, such as the census block group and census tract, and selection of the spatial scale for area-level variables can be considered as a model selection problem. In this paper, we model the variation in body mass index (BMI) in a study of pediatric patients of the Virginia Commonwealth University (VCU) Medical Center, while considering the selection of spatial scale for a set of neighborhood-level variables available at multiple spatial scales using four recently proposed spatial scale selection algorithms: SS forward stepwise regression, SS incremental forward stagewise regression, SS least angle regression (LARS), and SS lasso. For pediatric BMI, we found evidence of significant positive associations with visit age and black race at the individual level, percent Hispanic white at the census block group level, percent Hispanic black at the census tract level, and percent vacant housing at the census tract level. We also found significant negative associations with population density at the census tract level, median household income at the census tract level, percent renter at the census tract level, and exercise equipment expenditures at the census block group level. The SS algorithms selected covariates at different spatial scales, producing better goodness-of-fit in comparison to traditional models, where all area-level covariates were modeled at the same scale. These findings underscore the importance of considering spatial scale when performing model selection.

scholarly journals A Variance-decomposition Approach to Investigating Multiscale Habitat Associations

The Condor ◽  
2006 ◽  
Vol 108 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Joshua J. Lawler ◽  
Thomas C. Edwards
Keyword(s):  
Spatial Scale ◽  
Spatial Scales ◽  
Analytical Techniques ◽  
Variance Decomposition ◽  
Relative Strength ◽  
Habitat Associations ◽  
Alternative Methods ◽  
Decomposition Approach ◽  
Analytical Technique ◽  
Multiple Spatial Scales

Abstract The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales.

Geomorphology, hyporheic exchange, and selection of spawning habitat by bull trout (Salvelinus confluentus)

2000 ◽  
Vol 57 (7) ◽  
pp. 1470-1481 ◽  
Author(s):  
Colden V Baxter ◽  
F Richard Hauer
Keyword(s):  
Spatial Scale ◽  
Stream Water ◽  
Spatial Scales ◽  
Hyporheic Exchange ◽  
Bull Trout ◽  
Spawning Habitat ◽  
Alluvial Valley ◽  
Salvelinus Confluentus ◽  
Multiple Spatial Scales ◽  
Swan River

The distribution and abundance of bull trout (Salvelinus confluentus) spawning were affected by geomorphology and hyporheic groundwater - stream water exchange across multiple spatial scales in streams of the Swan River basin, northwestern Montana. Among spawning tributary streams, the abundance of bull trout redds increased with increased area of alluvial valley segments that were longitudinally confined by geomorphic knickpoints. Among all valley segment types, bull trout redds were primarily found in these bounded alluvial valley segments, which possessed complex patterns of hyporheic exchange and extensive upwelling zones. Bull trout used stream reaches for spawning that were strongly influenced by upwelling. However, within these selected reaches, bull trout redds were primarily located in transitional bedforms that possessed strong localized downwelling and high intragravel flow rates. The changing relationship of spawning habitat selection, in which bull trout selected upwelling zones at one spatial scale and downwelling zones at another spatial scale, emphasizes the importance of considering multiple spatial scales within a hierarchical geomorphic context when considering the ecology of this species or plans for bull trout conservation and restoration.

scholarly journals Multi-spatial scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia

2021 ◽  
pp. 1-48
Author(s):  
A. Iraji ◽  
A. Faghiri ◽  
Z. Fu ◽  
S. Rachakonda ◽  
P. Kochunov ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Spatial Scales ◽  
Dynamic State ◽  
Model Order Selection ◽  
Dynamic Interactions ◽  
Model Order ◽  
Functional Interactions ◽  
Multiple Spatial Scales ◽  
Temporal Domain ◽  
The Brain

Abstract We introduce an extension of independent component analysis (ICA), called multiscale ICA (msICA), and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. msICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and -common connectivity patterns in schizophrenia. Results show dynamic reconfiguration and interaction within and between multi-spatial scales. Sex specific differences occur (1) within the subcortical domain, (2) between the somatomotor and cerebellum domains, and (3) between the temporal domain and several others, including the subcortical, visual, and default mode domains. Most of the sex-specific differences belong to between-spatial scale functional interactions and are associated with a dynamic state with strong functional interactions between the visual, somatomotor, and temporal domains and their anticorrelation patterns with the rest of the brain. We observed significant correlations between multi-spatial scale functional interactions and symptom scores,highlighting the importance of multiscale analyses to identify potential biomarkers for schizophrenia. As such, we recommend such analyses as an important option for future functional connectivity studies.

scholarly journals Multi-Spatial Scale Dynamic Interactions between Functional Sources Reveal Sex-Specific Changes in Schizophrenia

2021 ◽  
Author(s):  
A. Iraji ◽  
A. Faghiri ◽  
Z. Fu ◽  
S. Rachakonda ◽  
P. Kochunov ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Spatial Scales ◽  
Dynamic State ◽  
Model Order Selection ◽  
Dynamic Interactions ◽  
Model Order ◽  
Functional Interactions ◽  
Multiple Spatial Scales ◽  
Temporal Domain ◽  
The Brain

AbstractWe introduce an extension of independent component analysis (ICA), called multiscale ICA (msICA), and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. msICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and -common connectivity patterns in schizophrenia.Results show dynamic reconfiguration and interaction within and between multi-spatial scales. Sex-specific differences occur (1) within the subcortical domain, (2) between the somatomotor and cerebellum domains, and (3) between the temporal domain and several others, including the subcortical, visual, and default mode domains. Most of the sex-specific differences belong to between-spatial scale functional interactions and are associated with a dynamic state with strong functional interactions between the visual, somatomotor, and temporal domains and their anticorrelation patterns with the rest of the brain. We observed significant correlations between multi-spatial-scale functional interactions and symptom scores, highlighting the importance of multiscale analyses to identify potential biomarkers for schizophrenia. As such, we recommend such analyses as an important option for future functional connectivity studies.

scholarly journals Landscape structure shapes tree seedlings’ diversity at multiple spatial scales in a fragmented tropical rainforest

2019 ◽  
Author(s):  
Sergio Nicasio-Arzeta ◽  
Isela E. Zermeño-Hernández ◽  
Susana Maza-Villalobos ◽  
Julieta Benítez-Malvido
Keyword(s):  
Functional Connectivity ◽  
Landscape Structure ◽  
Dominant Species ◽  
Secondary Forest ◽  
Spatial Scales ◽  
Landscape Configuration ◽  
Forest Patches ◽  
Management Actions ◽  
Β Diversity ◽  
Α Diversity

AbstractBiotic-dispersed tree seedling species are fundamental for the maintenance of the structure and function of forest patches in fragmented rainforest landscapes. Nonetheless, the effects of landscape structure and the spatial scale at which operates on seedling α- and β-diversity is unknown. Using a multi-scale approach, we assessed the relative effect of landscape composition (i.e., percentage of old-growth/secondary forest cover), configuration (i.e., aggregation/density of forest patches) and connectivity (i.e., structural and functional) on α- and β-diversity of biotic-dispersed seedlings in 16 forest patches in the Lacandona rainforest, Mexico. We assessed these effects at 13 spatial scales (from 300 to 1500 m radius, at 100 m intervals) for three α- and β-diversity orders (rare, common and dominant species). We found that patch aggregation increased species richness and reduced β-diversity of common and dominant species at similar spatial scales (500 to 600 m). Additionally, functional connectivity had a positive effect on the β-diversity of rare species in the 800 m spatial extent. These effects suggest that landscape configuration and functional connectivity sustain seedling diversity by preserving seed rain richness and the presence of large terrestrial herbivorous mammals. In contrast, the percentage of secondary forest matrix was detrimental for all α-diversity orders and the β-diversity of common and dominant species. Forthcoming conservation strategies should prevent deforestation, increase habitat amount and promote functional connectivity of forest-dependent fauna through matrix management actions.

Inhibition of coral settlement at multiple spatial scales by a pervasive algal competitor

2019 ◽  
Vol 612 ◽  
pp. 29-42 ◽  
Author(s):  
NR Evensen ◽  
C Doropoulos ◽  
KM Morrow ◽  
CA Motti ◽  
PJ Mumby
Keyword(s):  
Spatial Scales ◽  
Coral Settlement ◽  
Multiple Spatial Scales
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