scholarly journals Selection of foraging and commuting habitats of the greater horseshoe bat, revealed by high-resolution GPS-tracking

2020 ◽  
Author(s):  
Emyo Fujioka ◽  
Koki Yoshimura ◽  
Tomohiro Ujino ◽  
Ken Yoda ◽  
Dai Fukui ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
Great Influence ◽  
Movement Patterns ◽  
Gps Tracking ◽  
Small Scale ◽  
Auditory Information ◽  
Natural Forests ◽  
In The Wild ◽  
Horseshoe Bat

Abstract Background Echolocating bats make a series of decisions to select their flight routes based on auditory information obtained by sonar; accumulations of these flight routes are represented as daily movement patterns. However, there is still a lack of a unified understanding of continuous movements of echolocating bats in the wild from small to large spatial scales (i.e., from meters to tens of kilometers). Methods In this study, we investigated nightly flight paths of the Japanese greater horseshoe bat, Rhinolophus ferrumequinum nippon , using high-resolution GPS data loggers. Our aim was to identify foraging and commuting behavior based on the observed movement patterns and to investigate the relationship between these movement types and specific habitats. Results We found that the majority of tagged bats alternated between foraging and commuting behavior throughout the tracking period, and one individual moved 23.6 km from its roost. The distance between two successive foraging sites was on average 332 ± 398 m (mean ± standard deviation), and half of all foraging periods lasted less than 3 min. An analysis of habitat preferences revealed that the bats preferred conifer plantation and natural forests as pathways and feeding habitats. Particularly, they locally traveled along forest roads at flight speeds significantly higher than those flown over other habitats. Conclusions Our findings suggest the forests and their structures have a great influence on the nocturnal behavior of the greater horseshoe bats. Although this study has a descriptive character due to a relatively small number of tagged individuals, it was possible to elucidate the small-scale interactions between wild Rhinolophus bats and their environment using the latest high-resolution GPS technology, which will allow us to give new insights into the foraging ecology of echolocating bats in the wild.

scholarly journals Foraging and commuting habitats of the greater horseshoe bat, revealed by high-resolution GPS-tracking

2020 ◽  
Author(s):  
Emyo Fujioka ◽  
Koki Yoshimura ◽  
Tomohiro Ujino ◽  
Ken Yoda ◽  
Dai Fukui ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
Great Influence ◽  
Movement Patterns ◽  
Gps Tracking ◽  
Small Scale ◽  
Auditory Information ◽  
Natural Forests ◽  
In The Wild ◽  
Horseshoe Bat

Abstract Background Echolocating bats make a series of decisions to select their flight routes based on auditory information obtained by sonar; accumulations of these flight routes are represented as daily movement patterns. However, there is still a lack of a unified understanding of continuous movements of echolocating bats in the wild from small to large spatial scales (i.e., from meters to tens of kilometers). In this study, we investigated nightly flight paths of the Japanese greater horseshoe bat, Rhinolophus ferrumequinum nippon, using high-resolution GPS data loggers. Our aim was to identify foraging and commuting behavior based on the observed movement patterns and to investigate the relationship between these movement types and specific habitats.Results We found that the majority of tagged bats alternated between foraging and commuting behavior throughout the tracking period, and one individual moved 23.6 km from its roost. The bats usually left a stay point in the opposite direction from which they entered it, indicating that almost all of the stay sites were on their way to another destination. The distance between two successive foraging sites was on average 332 ± 398 m (mean ± standard deviation), and half of all foraging periods lasted less than 3 min. An analysis of habitat use revealed that the bats used conifer plantation and natural forests as pathways and feeding habitats.Conclusions Our findings suggest that the structure of the forests have a great influence on the nocturnal behavior of the greater horseshoe bats. Although this study has a descriptive character due to a relatively small number of tagged individuals, it was possible to elucidate the small-scale interactions between wild Rhinolophus bats and their environment using the latest high-resolution GPS technology, which will allow us to give new insights into the foraging ecology of echolocating bats in the wild.

scholarly journals Foraging and Commuting Habitats of the Greater Horseshoe Bat, Revealed by High-Resolution GPS-Tracking

2020 ◽  
Author(s):  
Emyo Fujioka ◽  
Koki Yoshimura ◽  
Tomohiro Ujino ◽  
Ken Yoda ◽  
Dai Fukui ◽  
...  
Keyword(s):  
High Resolution ◽  
Great Influence ◽  
Movement Patterns ◽  
Gps Tracking ◽  
Small Scale ◽  
Auditory Information ◽  
Natural Forests ◽  
Daily Movement ◽  
In The Wild ◽  
Horseshoe Bat

Abstract BackgroundEcholocating bats make a series of decisions to select their flight paths based on auditory information obtained by sonar as well as visual cues; accumulations of these flight routes are represented as daily movement patterns. However, there is still a lack of an understanding of continuous movements of echolocating bats in the wild (i.e., from meters to tens of kilometers). In this study, we investigated nightly flight paths of the Japanese greater horseshoe bat, Rhinolophus ferrumequinum nippon, using high-resolution GPS data loggers. Our aim was to identify foraging and commuting behavior based on the observed movement patterns and to investigate the relationship between these movement types and specific habitats. ResultsWe found that the majority of tagged bats alternated between foraging and commuting behavior throughout the tracking period, and one individual moved 23.6 km from its roost. The bats usually left a foraging area in the opposite direction from which they entered it, indicating that almost all of the stay sites were on their way to another destination. The distance between two successive foraging sites was on average 332 ± 398 m (mean ± standard deviation), and half of all foraging periods lasted less than 3 min. An analysis of habitat use revealed that the bats used conifer plantation and natural forests as pathways and feeding habitats. ConclusionsOur findings suggest that the structure of the forests have a great influence on the nocturnal behavior of the greater horseshoe bats. Although this study has a descriptive character due to a relatively small number of tagged individuals, it was possible to elucidate the small-scale interactions between wild Rhinolophus bats and their environment using the latest high-resolution GPS technology, which will allow us to give new insights into the foraging ecology of echolocating bats in the wild.

scholarly journals seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day

2018 ◽  
Vol 10 (1) ◽  
pp. 235-249 ◽  
Author(s):  
Cristian Lussana ◽  
Tuomo Saloranta ◽  
Thomas Skaugen ◽  
Jan Magnusson ◽  
Ole Einar Tveito ◽  
...  
Keyword(s):  
High Resolution ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
National Level ◽  
Calibration Procedure ◽  
Geographical Information ◽  
Optimal Interpolation ◽  
Small Scale ◽  
Meteorological Forcing ◽  
Atmospheric Sciences

Abstract. The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus in this paper is on climate and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The dataset constitutes a valuable meteorological input for snow and hydrological simulations; it is updated daily and presented on a high-resolution grid (1 km of grid spacing). The climate archive goes back to 1957. The spatial interpolation scheme builds upon classical methods, such as optimal interpolation and successive-correction schemes. An original approach based on (spatial) scale-separation concepts has been implemented which uses geographical coordinates and elevation as complementary information in the interpolation. seNorge2 daily precipitation fields represent local precipitation features at spatial scales of a few kilometers, depending on the station network density. In the surroundings of a station or in dense station areas, the predictions are quite accurate even for intense precipitation. For most of the grid points, the performances are comparable to or better than a state-of-the-art pan-European dataset (E-OBS), because of the higher effective resolution of seNorge2. However, in very data-sparse areas, such as in the mountainous region of southern Norway, seNorge2 underestimates precipitation because it does not make use of enough geographical information to compensate for the lack of observations. The evaluation of seNorge2 as the meteorological forcing for the seNorge snow model and the DDD (Distance Distribution Dynamics) rainfall–runoff model shows that both models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The seNorge2 dataset 1957–2015 is available at https://doi.org/10.5281/zenodo.845733. Daily updates from 2015 onwards are available at http://thredds.met.no/thredds/catalog/metusers/senorge2/seNorge2/provisional_archive/PREC1d/gridded_dataset/catalog.html.

scholarly journals Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

2010 ◽  
Vol 10 (2) ◽  
pp. 2357-2395 ◽  
Author(s):  
N. C. Dickson ◽  
K. M. Gierens ◽  
H. L. Rogers ◽  
R. L. Jones
Keyword(s):  
High Resolution ◽  
Relative Humidity ◽  
Climate Models ◽  
Numerical Models ◽  
Spatial Scales ◽  
Error Function ◽  
Global Distribution ◽  
Small Scale ◽  
Vertical Resolution ◽  
Average Relative Humidity

Abstract. The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensations trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. A robust assessment of the global distribution of ISSR will further this debate, and ISS event occurrence, frequency and spatial scales have recently attracted significant attention. The mean horizontal path length through ISSR as observed by MOZAIC aircraft is 150 km (±250 km). The average vertical thickness of ISS layers is 600–800 m (±575 m) but layers ranging from 25 m to 3000 m have been observed, with up to one third of ISS layers thought to be less than 100 m deep. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Specifically each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve describing the ISS fraction in any average relative humidity pressure layer. An empirical investigation has shown that this one curve is statistically valid for mid-latitude locations, irrespective of season and altitude, however, pressure layer depth is an important variable. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Here the statistical distributions of actual high resolution RHi observations in any thick pressure layer, along with an error function, are used to mathematically describe the s-shape. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8–10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

scholarly journals Predictive power of a shallow landslide model in a high resolution landscape: dissecting the effects of forest roads

2013 ◽  
Vol 10 (7) ◽  
pp. 9761-9798 ◽  
Author(s):  
D. Penna ◽  
M. Borga ◽  
G. T. Aronica ◽  
G. Brigandì ◽  
P. Tarolli
Keyword(s):  
High Resolution ◽  
Predictive Power ◽  
Spatial Scales ◽  
Model Performance ◽  
Shallow Landslide ◽  
Small Scale ◽  
Forest Roads ◽  
Forest Road ◽  
The Impact ◽  
Landslide Model

Abstract. This work evaluates the predictive power of the quasi-dynamic shallow landslide model QD-SLaM to simulate shallow landslide locations in a small-scale Mediterranean landscape: the Giampilieri catchment located in Sicily (Italy). The catchment was impacted by a sequence of high-intensity storms over the years 2007–2009. The effect of high resolution Digital Terrain Models (DTMs) on the quality of model predictions is tested by considering four DTM resolutions: 2 m, 4 m, 10 m and 20 m. Moreover, the impact of the dense forest road network on the model performance is evaluated by considering separately road-related landslides and natural landslides. The landslide model does not incorporate the description of road-related failures. The model predictive power is shown to be DTM-resolution dependent. When assessed over the sample of mapped natural landslides, better model performances are reported for 4 m and 10 m DTM resolution, thus highlighting the fact that higher DTM resolution does not necessarily mean better model performances. Model performances over road-related failures are, as expected, lower than for the other cases. These findings show that shallow landslide predictive power can benefit from increasing DTM resolution only when the model is able to describe the physical processes emerging at the smaller spatial scales resolved by the digital topography. Model results show also that the combined use of high DTM resolution and a model capable to deal with road-related processes may lead to substantially better performances in landscapes where forest roads are a significant factor of slope stability.

A downscaling framework for precipitation nowcasting by merging radar retrievals at different scales and resolutions

2021 ◽  
Author(s):  
Roberto Deidda ◽  
Stefano Farris ◽  
Maria Grazia Badas ◽  
Marino Marrocu ◽  
Luca Massidda ◽  
...  
Keyword(s):  
High Resolution ◽  
Prediction Models ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Weather Radar ◽  
Early Warning Systems ◽  
Small Scale ◽  
Time Step ◽  
Radar Network ◽  
X Band

<p>Convective rainfall events represent one of the most critical issues in urban areas, where numerical weather prediction models are affected by a large uncertainty related to the short temporal and spatial scales involved, thus making early warning systems ineffective. Conversely, radar-based nowcasting models may be a useful tool to guarantee short-term forecasts, through the extrapolation of most recent properties in observed precipitation fields, for lead times ranging from minutes to few hours.</p><p>In this study we develop a procedure for merging relevant information from two radar products with different resolutions and scales: (i) high-resolution observations retrieved by an X-band weather radar in a small domain (the metropolitan area of Cagliari, located in Sardinia, Italy), and (ii) the mosaic data provided by the Italian Civil Protection national radar network (the whole region of Sardinia). Specifically, we here adapt some STEPS procedures to merge the large-scale advection from the latter radar network, and the small-scale statistical properties for the former X-band weather radar. We thus combine the corresponding forecasts preserving the higher resolution scale. In details, for each time step we (i) evaluate the power spectra of the two forecasts (ii) merge the two spectra taking the power of the large (small) frequencies from the high (low) resolution data spectrum and (iii) achieve optimal downscaling by reconstructing the high-resolution nowcast from the blend of the two spectra.</p>

Präzisions-Forstwirtschaft – was ist das? | Precision forestry – what's that?

2007 ◽  
Vol 158 (8) ◽  
pp. 235-242 ◽  
Author(s):  
Hans Rudolf Heinimann
Keyword(s):  
Business Processes ◽  
Spatial Scales ◽  
Supply Chain Coordination ◽  
Sensor Technology ◽  
Small Scale ◽  
Soil Physics ◽  
Coordination Problem ◽  
Precision Engineering ◽  
Precision Forestry ◽  
And Control

The term «precision forestry» was first introduced and discussed at a conference in 2001. The aims of this paper are to explore the scientific roots of the precision concept, define «precision forestry», and sketch the challenges that the implementation of this new concept may present to practitioners, educators, and researchers. The term «precision» does not mean accuracy on a small scale, but instead refers to the concurrent coordination and control of processes at spatial scales between 1 m and 100 km. Precision strives for an automatic control of processes. Precision land use differs from precision engineering by the requirements of gathering,storing and managing spatio-temporal variability of site and vegetation parameters. Practitioners will be facing the challenge of designing holistic, standardized business processes that are valid for whole networks of firms,and that follow available standards (e.g., SCOR, WoodX). There is a need to educate and train forestry professionals in the areas of business process re-engineering, computer supported management of business transactions,methods of remote sensing, sensor technology and control theory. Researchers will face the challenge of integrating plant physiology, soil physics and production sciences and solving the supply chain coordination problem (SCCP).

scholarly journals Dispersal and Land Cover Contribute to Pseudorabies Virus Exposure in Invasive Wild Pigs

EcoHealth ◽  
2021 ◽  
Author(s):  
Felipe A. Hernández ◽  
Amanda N. Carr ◽  
Michael P. Milleson ◽  
Hunter R. Merrill ◽  
Michael L. Avery ◽  
...  
Keyword(s):  
Land Cover ◽  
Disease Transmission ◽  
Wildlife Conservation ◽  
Pseudorabies Virus ◽  
Spatial Scales ◽  
Information Criterion ◽  
Small Scale ◽  
Wild Pigs ◽  
Bacterial Agent ◽  
Open Canopy

AbstractWe investigated the landscape epidemiology of a globally distributed mammal, the wild pig (Sus scrofa), in Florida (U.S.), where it is considered an invasive species and reservoir to pathogens that impact the health of people, domestic animals, and wildlife. Specifically, we tested the hypothesis that two commonly cited factors in disease transmission, connectivity among populations and abundant resources, would increase the likelihood of exposure to both pseudorabies virus (PrV) and Brucella spp. (bacterial agent of brucellosis) in wild pigs across the Kissimmee Valley of Florida. Using DNA from 348 wild pigs and sera from 320 individuals at 24 sites, we employed population genetic techniques to infer individual dispersal, and an Akaike information criterion framework to compare candidate logistic regression models that incorporated both dispersal and land cover composition. Our findings suggested that recent dispersal conferred higher odds of exposure to PrV, but not Brucella spp., among wild pigs throughout the Kissimmee Valley region. Odds of exposure also increased in association with agriculture and open canopy pine, prairie, and scrub habitats, likely because of highly localized resources within those land cover types. Because the effect of open canopy on PrV exposure reversed when agricultural cover was available, we suggest that small-scale resource distribution may be more important than overall resource abundance. Our results underscore the importance of studying and managing disease dynamics through multiple processes and spatial scales, particularly for non-native pathogens that threaten wildlife conservation, economy, and public health.

scholarly journals Object Oriented Classification for Mapping Mixed and Pure Forest Stands Using Very-High Resolution Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2508
Author(s):  
Loredana Oreti ◽  
Diego Giuliarelli ◽  
Antonio Tomao ◽  
Anna Barbati
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
Parametric Method ◽  
Mixed Forest ◽  
Mixed Stands ◽  
Mapping Unit ◽  
Mixed Forests ◽  
High Resolution Imagery ◽  
Very High Resolution Imagery ◽  
Very High

The importance of mixed forests is increasingly recognized on a scientific level, due to their greater productivity and efficiency in resource use, compared to pure stands. However, a reliable quantification of the actual spatial extent of mixed stands on a fine spatial scale is still lacking. Indeed, classification and mapping of mixed populations, especially with semi-automatic procedures, has been a challenging issue up to date. The main objective of this study is to evaluate the potential of Object-Based Image Analysis (OBIA) and Very-High-Resolution imagery (VHR) to detect and map mixed forests of broadleaves and coniferous trees with a Minimum Mapping Unit (MMU) of 500 m2. This study evaluates segmentation-based classification paired with non-parametric method K- nearest-neighbors (K-NN), trained with a dataset independent from the validation one. The forest area mapped as mixed forest canopies in the study area amounts to 11%, with an overall accuracy being equal to 85% and K of 0.78. Better levels of user and producer accuracies (85–93%) are reached in conifer and broadleaved dominated stands. The study findings demonstrate that the very high resolution images (0.20 m of spatial resolutions) can be reliably used to detect the fine-grained pattern of rare mixed forests, thus supporting the monitoring and management of forest resources also on fine spatial scales.

Sign in / Sign up

Export Citation Format

Share Document