Notes on fine-scale spatial distribution of three Cephalanthera species (Orchidaceae) that grow in sympatry in Korea: Implications for maintenance of species boundaries

AbstractA detailed knowledge on the spatial distribution of pests is crucial for predicting population outbreaks or developing control strategies and sustainable management plans. The diamondback moth, Plutella xylostella, is one of the most destructive pests of cruciferous crops worldwide. Despite the abundant research on the species’s ecology, little is known about the spatio-temporal pattern of P. xylostella in an agricultural landscape. Therefore, in this study, the spatial distribution of P. xylostella was characterized to assess the effect of landscape elements in a fine-scale agricultural landscape by geostatistical analysis. The P. xylostella adults captured by pheromone-baited traps showed a seasonal pattern of population fluctuation from October 2015 to September 2017, with a marked peak in spring, suggesting that mild temperatures, 15–25 °C, are favorable for P. xylostella. Geostatistics (GS) correlograms fitted with spherical and Gaussian models showed an aggregated distribution in 21 of the 47 cases interpolation contour maps. This result highlighted that spatial distribution of P. xylostella was not limited to the Brassica vegetable field, but presence was the highest there. Nevertheless, population aggregations also showed a seasonal variation associated with the growing stage of host plants. GS model analysis showed higher abundances in cruciferous fields than in any other patches of the landscape, indicating a strong host plant dependency. We demonstrate that Brassica vegetables distribution and growth stage, have dominant impacts on the spatial distribution of P. xylostella in a fine-scale landscape. This work clarified the spatio-temporal dynamic and distribution patterns of P. xylostella in an agricultural landscape, and the distribution model developed by geostatistical analysis can provide a scientific basis for precise targeting and localized control of P. xylostella.

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Prey-Driven Behavioral Habitat Use in a Low-Energy Ambush Predator

10.1101/2020.09.17.301697 ◽

2020 ◽

Author(s):

Annalee M. Tutterow ◽

Andrew S. Hoffman ◽

John L. Buffington ◽

Zachary T. Truelock ◽

William E. Peterman

Keyword(s):

Spatial Distribution ◽

Habitat Selection ◽

Small Mammal ◽

Optimal Foraging ◽

Prey Availability ◽

Low Energy ◽

List Type ◽

Fine Scale ◽

Timber Rattlesnake ◽

Ambush Predator

AbstractFood acquisition is an important modulator of animal behavior and habitat selection that can affect fitness. Optimal foraging theory predicts that predators should select habitat patches to maximize their foraging success and net energy gain, which predators can achieve by targeting spaces with high prey availability. However, it is debated whether prey availability drives fine-scale habitat selection for predators.We assessed whether an ambush predator, the timber rattlesnake (Crotalus horridus), exhibits optimal foraging site selection based on the spatial distribution and availability of prey.We evaluated the spatial concordance of radio-telemetered timber rattlesnake foraging locations and passive infrared game camera trap detections of potential small mammal prey (Peromyscus spp., Tamias striatus, and Sciurus spp.) in a mixed-use forest in southeastern Ohio from 2016–2019. We replicated a characteristic timber rattlesnake ambush position by focusing cameras over logs and modeled small mammal encounters across the landscape in relation to remotely-sensed forest and landscape structural features. To determine whether snakes selectively forage in areas with higher prey availability, we projected the estimated prey spatial relationships across the landscape and modeled their overlap of occurrence with observed timber rattlesnake foraging locations.We broadly predicted that prey availability was greatest in mature deciduous forests, but T. striatus and Sciurus spp. exhibited greater spatial heterogeneity compared to Peromyscus spp. We also combined predicted species encounter rates to encompass a body size gradient in potential prey. The spatial distribution of cumulative small mammal encounters (i.e. overall prey availability), rather than the distribution of any one species, was highly predictive of snake foraging.Timber rattlesnakes appear to select foraging locations where the probability of encountering prey is greatest. Our study provides evidence for fine-scale optimal foraging in a low-energy, ambush predator and offers new insights into drivers of snake foraging and habitat selection.

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Effects of socio-economic and environmental factors on the spatial heterogeneity of dengue fever investigated at a fine scale

Geospatial health ◽

10.4081/gh.2018.682 ◽

2018 ◽

Vol 13 (2) ◽

Cited By ~ 2

Author(s):

Yubing Qu ◽

Xun Shi ◽

Yong Wang ◽

Rendong Li ◽

Liang Lu ◽

...

Keyword(s):

Spatial Distribution ◽

Environmental Factors ◽

Spatial Heterogeneity ◽

Dengue Fever ◽

Scan Statistics ◽

Fine Scale ◽

Road Density ◽

Risk Area ◽

High Risk Area ◽

Guangzhou City

The spatial pattern of dengue fever cases is the result of complex interactions between the virus, the host and the vector, which may be affected by environmental conditions. The largest outbreak of dengue fever in Guangzhou city, China occurred in 2014 with case numbers 2.7 times the number of cumulative cases since 1978 and a significantly non-random spatial distribution. Selecting Guangzhou City as the study area, we used scan statistics to analyze the spatial heterogeneity of dengue fever and a generalized additive model to evaluate and examine the effects of socio-economic and environmental factors on spatial heterogeneity at a fine scale. The study found that the spatial distribution of dengue fever is highly heterogeneous and various factors differ in relative importance. The junction of the central districts of Guangzhou is a high-risk area with the urban village and urban-rural fringe zone formed by urbanization as important regional factors. The low gross domestic product per capita, the high population density, the high road density were perceived as risk factors. The Asian subtropical coastal area together with the socioeconomic and environmental factors were found to be the key drivers at the fine scale explaining the high spatial heterogeneity of dengue fever in Guangzhou City.

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Colony size affects breeding density, but not spatial distribution type, in a seabird

Behavioral Ecology ◽

10.1093/beheco/araa058 ◽

2020 ◽

Vol 31 (5) ◽

pp. 1113-1119 ◽

Cited By ~ 1

Author(s):

Sandra Bouwhuis ◽

Felix Ballani ◽

Marie Bourgeois ◽

Dietrich Stoyan

Keyword(s):

Spatial Distribution ◽

Density Dependence ◽

Colony Size ◽

Decision Rules ◽

Variable Density ◽

Breeding Density ◽

Fine Scale ◽

Nest Distribution ◽

The Social ◽

Distribution Type

Abstract The spatial distribution of individuals within populations can result in fine-scale density dependence and affect the social environment that is encountered. As such, it is important to quantify within-population spatial structuring and understand the factors that shape it. In this study, we make use of point process statistics to test whether colony size affects the statistical type of spatial nest distribution produced by common terns (Sterna hirundo) breeding at identical manmade rectangular and homogeneous islands of fixed physical size. Comparing subcolonies of variable density both within and across years, we find that inter-nest distances are smaller at higher local and overall breeding density, but that the spatial distribution type does not vary across the observed densities. This suggests that the birds’ main settlement rules do not depend on density. In our case, analyses of fine-scale density dependence or potential social effects therefore do not need to account for between-individual heterogeneity in settlement decision rules or acceptance of these rules. We urge, however, other studies to similarly test for density dependence of the spatial distribution of individuals before undertaking such “downstream” analyses.

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Modelling spatial distribution of fine-scale populations based on residential properties

International Journal of Remote Sensing ◽

10.1080/01431161.2019.1579387 ◽

2019 ◽

Vol 40 (14) ◽

pp. 5287-5300 ◽

Cited By ~ 8

Author(s):

Dongrui Han ◽

Xiaohuan Yang ◽

Hongyan Cai ◽

Xinliang Xu ◽

Zhi Qiao ◽

...

Keyword(s):

Spatial Distribution ◽

Fine Scale ◽

Residential Properties

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Fine-scale spatial distribution of the common lugworm Arenicola marina, and effects of intertidal clam fishing

Estuarine Coastal and Shelf Science ◽

10.1016/j.ecss.2014.03.019 ◽

2014 ◽

Vol 143 ◽

pp. 32-40 ◽

Cited By ~ 10

Author(s):

Inna Boldina ◽

Peter G. Beninger

Keyword(s):

Spatial Distribution ◽

Fine Scale ◽

Arenicola Marina ◽

The Common

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Fine-scale spatial distribution ofmurundusstructures in the semi-arid region of Brazil

Austral Ecology ◽

10.1111/aec.12562 ◽

2017 ◽

Vol 43 (3) ◽

pp. 268-279 ◽

Cited By ~ 4

Author(s):

Henrique J. De Souza ◽

Jacques H. C. Delabie

Keyword(s):

Spatial Distribution ◽

Arid Region ◽

Fine Scale ◽

Semi Arid Region ◽

Semi Arid

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Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrhoeal disease in Ifanadiana, rural Madagascar

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2020.2501 ◽

2021 ◽

Vol 288 (1946) ◽

pp. 20202501

Author(s):

Michelle V. Evans ◽

Matthew H. Bonds ◽

Laura F. Cordier ◽

John M. Drake ◽

Felana Ihantamalala ◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Patterns ◽

Disease Risk ◽

Spatial Scales ◽

Explanatory Power ◽

Diarrhoeal Disease ◽

Local Health ◽

Fine Scale ◽

Local Public Health ◽

Precision Health

Precision health mapping is a technique that uses spatial relationships between socio-ecological variables and disease to map the spatial distribution of disease, particularly for diseases with strong environmental signatures, such as diarrhoeal disease (DD). While some studies use GPS-tagged location data, other precision health mapping efforts rely heavily on data collected at coarse-spatial scales and may not produce operationally relevant predictions at fine enough spatio-temporal scales to inform local health programmes. We use two fine-scale health datasets collected in a rural district of Madagascar to identify socio-ecological covariates associated with childhood DD. We constructed generalized linear mixed models including socio-demographic, climatic and landcover variables and estimated variable importance via multi-model inference. We find that socio-demographic variables, and not environmental variables, are strong predictors of the spatial distribution of disease risk at both individual and commune-level (cluster of villages) spatial scales. Climatic variables predicted strong seasonality in DD, with the highest incidence in colder, drier months, but did not explain spatial patterns. Interestingly, the occurrence of a national holiday was highly predictive of increased DD incidence, highlighting the need for including cultural factors in modelling efforts. Our findings suggest that precision health mapping efforts that do not include socio-demographic covariates may have reduced explanatory power at the local scale. More research is needed to better define the set of conditions under which the application of precision health mapping can be operationally useful to local public health professionals.

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Dwarf-shrubs dynamics in Mediterranean high mountain ecosystems

10.1101/2021.10.06.463306 ◽

2021 ◽

Author(s):

Andrea De Toma ◽

Marta Carboni ◽

Manuele Bazzichetto ◽

Marco Malavasi ◽

Maurizio Cutini

Keyword(s):

Land Use ◽

Spatial Distribution ◽

Environmental Factors ◽

Environmental Heterogeneity ◽

Temporal Trends ◽

Shrub Encroachment ◽

High Mountain ◽

Fine Scale ◽

Dwarf Shrubs ◽

The Past

AbstractQuestionVegetation in the alpine and treeline ecotone faces changes in both climate and land use. Shrub encroachment is considered an effect of these changes, but it’s still unclear how this effect is mediated by environmental heterogeneity. Our goal is to determine which environmental factors shape the fine-scale spatial distribution and temporal trends of alpine dwarf shrub.LocationThree sites in the Central Apennine, Italy.MethodsWe used a comprehensive set of environmental factors across a broad temporal span to model, at a fine-scale, both (1) the current spatial distribution and (2) the change in shrub cover over the past 60 years.ResultsOur results show that dwarf shrubs have generally increased in our study sites over the past 60 years, yet their distribution is strongly shaped by the joint influence of the fine-scale topography, productivity, land use and micro-climate. In particular, shrubs have been locally favored in areas with harsher alpine environmental constraints and stronger resource limitation. Instead, contrary to expectations, at this fine scale, warmer temperatures and the decline in grazing have not favored shrub encroachment.ConclusionDwarf shrubs appear as a stress-tolerant, pioneer vegetation that is currently distributed mainly over areas that are otherwise sparsely vegetated. It appears that shrubs exhibit poor competitive ability to invade grasslands and, though they have increased overall, they remain restricted to the least productive areas. Fine-scale environmental heterogeneity may strongly influence future responses of dwarf shrubs in changing alpine ecosystems.

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Influence of Spatiotemporal Dynamics on the Fine-Scale Spatial Genetic Structure of Differently Managed Picea abies Stands

Forests ◽

10.3390/f9100622 ◽

2018 ◽

Vol 9 (10) ◽

pp. 622 ◽

Cited By ~ 1

Author(s):

Andrea Piotti ◽

Matteo Garbarino ◽

Camilla Avanzi ◽

Roberta Berretti ◽

Renzo Motta ◽

...

Keyword(s):

Genetic Diversity ◽

Spatial Distribution ◽

Genetic Structure ◽

Spatial Structure ◽

Norway Spruce ◽

Management Practices ◽

Spatial Genetic Structure ◽

Genetic Data ◽

Permanent Plots ◽

Fine Scale

The tandem analysis of dendrochronological and genetic data is piquing forest ecologists’ interest and represents a promising approach for studying the temporal development of genetic structure in forest tree populations. Such multidisciplinary approach can help elucidate to what extent different management practices have impacted the fine-scale spatial genetic structure of forest stands through time. In this study, we jointly analysed spatial, age and genetic data from three differently managed Norway spruce permanent plots to assess: (1) possible differences among plots in the spatial distribution of individuals and their genetic structure due to different management practices, and (2) whether modifications in the age structure influenced the fine-scale spatial genetic structure within each permanent plot. With these aims, we genetically characterized at five nuclear microsatellite markers a large subset (328) of all the trees for which spatial and age data were collected (1472). We found that different management practices determined a similar spatial structure in terms of trees’ ages (r < 25 m in all plots) and neutral genetic diversity (Sp ranging from 0.002 to 0.004). Hot spots and cold spots of trees’ age were not statistically different in terms of genetic diversity, and trees’ age was not statistically different among the genetic clusters detected. On the other hand, the spatial distribution of individuals was significantly clustered up to 22 m only in the wooded pasture plot. Our main findings show that forest land use and management can indeed determine markedly different spatial layouts of Norway spruce individuals but do not produce strong distortions in the spatial structure of age and genetic parameters.

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