scholarly journals Road and landscape-context impacts on bird pollination in a Mediterranean-type shrubland of the southeastern Cape Floristic Region

2019 ◽  
Author(s):  
B. Adriaan Grobler ◽  
Eileen. E. Campbell
Keyword(s):  
Large Scale ◽  
Plant Density ◽  
Cape Floristic Region ◽  
Rural Landscape ◽  
Habitat Modification ◽  
Ecological Processes ◽  
Bird Pollination ◽  
The Road ◽  
Road Effects ◽  
Road Verges

AbstractRoad verges can provide important habitats for plants, especially in transformed landscapes. However, roads and their associated traffic have several adverse impacts on ecosystems that can disrupt vital ecological processes, including pollination. In transformed landscapes, road effects on pollination might be complemented by impacts of large-scale habitat modification. In these landscapes, road verge populations of plants that rely on pollinators for pollen transfer could thus be at risk of pollination failure. This study investigates the pollination of a reseeding, bird-pollinated shrub,Erica glandulosa, in road verges of a fragmented and transformed rural landscape in the southeastern Cape Floristic Region. We test for road impacts on pollination by comparing number of ruptured anther rings—a proxy for pollination—in fynbos vegetation fragments at different distances from the road (0–10, 20–30 and 40–50 m). We also test whether different land-cover types (intact fynbos, alien thickets and rangelands/pastures) next to road verges influence the number of ruptured anther rings. After controlling for robbing rate and plant density, fewer flowers were pollinated near the road than farther away, and fewer flowers were pollinated where road verges occurred next to alien thickets or pastures/rangelands compared to intact fynbos. However, bird pollination was not excluded in road verges: on average, ca. 20–30% of flowers were still visited by birds near the road. These findings potentially call into question the suitability of road verges as refugia for seed-dependent, bird-pollinated plant species in transformed landscapes.

scholarly journals Linkages in the Landscape: The Role of Corridors and Connectivity in wildlife Conservation

1999 ◽  
Vol 5 (2) ◽  
pp. 158 ◽  
Author(s):  
Chris Norwood
Keyword(s):  
Large Scale ◽  
Wildlife Conservation ◽  
Habitat Modification ◽  
World Population ◽  
Stepping Stones ◽  
Ecological Processes ◽  
Old Growth Forest ◽  
Migratory Routes ◽  
Forest Mosaic ◽  
Increasing Demand

Increasing demand for resources through a growing world population and the development of consumer led economies has led to large-scale habitat modification. One of the most disturbing aspects of these changes is the loss of biodiversity. Conservation biology as a discipline seeks to counteract or minimize the loss of biodiversity. Management is an Important aspect in achieving this goal. One concept used in Wildlife management and conservation is that of landscape linkages. Linkages are aimed at faclhtatmg .the connectivity for species, communities or ecological processes. There are many types of linkages in the landscape; both natural and human induced. Covered in this book are linkages such as greenways, dispersal corridors, riparian remnants, wildlife corridors, stepping stones, hedgerows and road underpasses. Linkages range in scale from small patches of old-growth forest in a forest mosaic to migratory routes for birds across and between continents.

scholarly journals Bat-fruit networks structure resist habitat modification but species roles change in the most transformed habitats

2019 ◽  
Author(s):  
John Harold Castaño ◽  
Jaime Andrés Carranza-Quiceno ◽  
Jairo Pérez-Torres
Keyword(s):  
Agricultural Landscape ◽  
Rural Landscape ◽  
Habitat Modification ◽  
Natural Environments ◽  
Forest Fragments ◽  
Ecological Processes ◽  
Network Characteristics ◽  
Landscape Modification ◽  
Species Roles ◽  
Networks Structure

AbstractSpecies do not function as isolated entities, rather they are organized in complex networks of interactions. These networks develop the ecological processes that provide ecosystem services for human societies. Understanding the causes and consequences of changes in ecological networks due to landscape modification would allow us to understand the consequences of ecological processes. However, there is still theoretical controversy and few empirical data on the effects of network characteristics on the loss of natural environments. We investigate how bat–fruit networks respond to three landscapes representing the gradient of modification from pre-montane forest to a heterogeneous agricultural landscape in the Colombian Andes (continuous forests, forest fragments, and crops). We found that forest contained smaller bat–fruit networks than forest fragments and crops. Modified landscapes had similar ecological network structures to forest (nestedness and modularity), but crops contained less specialized networks compared to forests and fragments and the species role in these habitats change. The networks in the rural coffee landscape maintain their structure in the different transformation scenarios, indicating that seed dispersal services are maintained even in the most transformed scenarios. This could be related to the high heterogeneity present in this rural landscape. Although the number of species does not decrease due to transformations, species change their roles in the most transformed habitats. This result sheds light on the way that biodiversity responds to anthropogenic transformations, showing higher stability than theoretically predicted.

Soil/Tire Interaction Analysis Using FEM and FVM

2005 ◽  
Vol 33 (1) ◽  
pp. 38-62 ◽  
Author(s):  
S. Oida ◽  
E. Seta ◽  
H. Heguri ◽  
K. Kato
Keyword(s):  
Large Scale ◽  
Interaction Analysis ◽  
Yield Criterion ◽  
Surrounding Medium ◽  
Flow Analysis ◽  
Measurement Data ◽  
Traction Force ◽  
Elastoplastic Material ◽  
The Road ◽  
Soil Flow

Abstract Vehicles, such as an agricultural tractor, construction vehicle, mobile machinery, and 4-wheel drive vehicle, are often operated on unpaved ground. In many cases, the ground is deformable; therefore, the deformation should be taken into consideration in order to assess the off-the-road performance of a tire. Recent progress in computational mechanics enabled us to simulate the large scale coupling problem, in which the deformation of tire structure and of surrounding medium can be interactively considered. Using this technology, hydroplaning phenomena and tire traction on snow have been predicted. In this paper, the simulation methodology of tire/soil coupling problems is developed for pneumatic tires of arbitrary tread patterns. The Finite Element Method (FEM) and the Finite Volume Method (FVM) are used for structural and for soil-flow analysis, respectively. The soil is modeled as an elastoplastic material with a specified yield criterion and a nonlinear elasticity. The material constants are referred to measurement data, so that the cone penetration resistance and the shear resistance are represented. Finally, the traction force of the tire in a cultivated field is predicted, and a good correlation with experiments is obtained.

scholarly journals Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1030
Author(s):  
Julie Lake ◽  
Catherine S. Storm ◽  
Mary B. Makarious ◽  
Sara Bandres-Ciga
Keyword(s):  
Neurodegenerative Diseases ◽  
Large Scale ◽  
Disease Diagnosis ◽  
Open Science ◽  
Future Directions ◽  
The Road ◽  
Current State ◽  
Molecular Complexity ◽  
Science Framework ◽  
Lateral Sclerosis

Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson’s disease, Alzheimer’s disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.

scholarly journals Providing large-scale disk storage at CERN

2019 ◽  
Vol 214 ◽  
pp. 04033
Author(s):  
Hervé Rousseau ◽  
Belinda Chan Kwok Cheong ◽  
Cristian Contescu ◽  
Xavier Espinal Curull ◽  
Jan Iven ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Distributed Storage ◽  
Storage System ◽  
Primary Data ◽  
Disk Storage ◽  
The Road ◽  
Ongoing Work ◽  
Software Distribution ◽  
Microsoft Office

The CERN IT Storage group operates multiple distributed storage systems and is responsible for the support of the infrastructure to accommodate all CERN storage requirements, from the physics data generated by LHC and non-LHC experiments to the personnel users' files. EOS is now the key component of the CERN Storage strategy. It allows to operate at high incoming throughput for experiment data-taking while running concurrent complex production work-loads. This high-performance distributed storage provides now more than 250PB of raw disks and it is the key component behind the success of CERNBox, the CERN cloud synchronisation service which allows syncing and sharing files on all major mobile and desktop platforms to provide offline availability to any data stored in the EOS infrastructure. CERNBox recorded an exponential growth in the last couple of year in terms of files and data stored thanks to its increasing popularity inside CERN users community and thanks to its integration with a multitude of other CERN services (Batch, SWAN, Microsoft Office). In parallel CASTOR is being simplified and transitioning from an HSM into an archival system, focusing mainly in the long-term data recording of the primary data from the detectors, preparing the road to the next-generation tape archival system, CTA. The storage services at CERN cover as well the needs of the rest of our community: Ceph as data back-end for the CERN OpenStack infrastructure, NFS services and S3 functionality; AFS for legacy home directory filesystem services and its ongoing phase-out and CVMFS for software distribution. In this paper we will summarise our experience in supporting all our distributed storage system and the ongoing work in evolving our infrastructure, testing very-dense storage building block (nodes with more than 1PB of raw space) for the challenges waiting ahead.

scholarly journals A Parallel-Computing Approach for Vector Road-Network Matching Using GPU Architecture

2018 ◽  
Vol 7 (12) ◽  
pp. 472 ◽  
Author(s):  
Bo Wan ◽  
Lin Yang ◽  
Shunping Zhou ◽  
Run Wang ◽  
Dezhi Wang ◽  
...  
Keyword(s):  
Road Network ◽  
Large Scale ◽  
Graphics Processing Unit ◽  
Road Networks ◽  
Processing Unit ◽  
Data Partition ◽  
Matching Method ◽  
The Road ◽  
Central Processing ◽  
Relaxation Matching

The road-network matching method is an effective tool for map integration, fusion, and update. Due to the complexity of road networks in the real world, matching methods often contain a series of complicated processes to identify homonymous roads and deal with their intricate relationship. However, traditional road-network matching algorithms, which are mainly central processing unit (CPU)-based approaches, may have performance bottleneck problems when facing big data. We developed a particle-swarm optimization (PSO)-based parallel road-network matching method on graphics-processing unit (GPU). Based on the characteristics of the two main stages (similarity computation and matching-relationship identification), data-partition and task-partition strategies were utilized, respectively, to fully use GPU threads. Experiments were conducted on datasets with 14 different scales. Results indicate that the parallel PSO-based matching algorithm (PSOM) could correctly identify most matching relationships with an average accuracy of 84.44%, which was at the same level as the accuracy of a benchmark—the probability-relaxation-matching (PRM) method. The PSOM approach significantly reduced the road-network matching time in dealing with large amounts of data in comparison with the PRM method. This paper provides a common parallel algorithm framework for road-network matching algorithms and contributes to integration and update of large-scale road-networks.

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

scholarly journals Deep-Learning-Based Road Crack Detection Frameworks for Dashcam-captured Images under Different Illumination Conditions

2021 ◽  
Author(s):  
Da-Ren Chen ◽  
Wei-Min Chiu
Keyword(s):  
Object Detection ◽  
Large Scale ◽  
Crack Detection ◽  
State Of The Art ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Machine Learning Techniques ◽  
Detection Accuracy ◽  
The Road ◽  
Art Object

Abstract Machine learning techniques have been used to increase detection accuracy of cracks in road surfaces. Most studies failed to consider variable illumination conditions on the target of interest (ToI), and only focus on detecting the presence or absence of road cracks. This paper proposes a new road crack detection method, IlumiCrack, which integrates Gaussian mixture models (GMM) and object detection CNN models. This work provides the following contributions: 1) For the first time, a large-scale road crack image dataset with a range of illumination conditions (e.g., day and night) is prepared using a dashcam. 2) Based on GMM, experimental evaluations on 2 to 4 levels of brightness are conducted for optimal classification. 3) the IlumiCrack framework is used to integrate state-of-the-art object detecting methods with CNN to classify the road crack images into eight types with high accuracy. Experimental results show that IlumiCrack outperforms the state-of-the-art R-CNN object detection frameworks.

GERI – The emerging Global Ecosystem Research Infrastructure

2021 ◽  
Author(s):  
Jaana Bäck ◽  
Werner Kutsch ◽  
Michael Mirtl
Keyword(s):  
Global Economy ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Research Infrastructure ◽  
Ecological Processes ◽  
Unique Challenge ◽  
Ecosystem Research ◽  
Decadal Scale ◽  
Research Infrastructures ◽  
Access To Data

<p>Ecosystem Research Infrastructures around the world have been designed, constructed, and are now operational as a distributed effort. The common goal is to address research questions that require long-term ecosystem observations and other service components at national to continental scales, which cannot be tackled in the framework of single and time limited projects.  By design, these Research Infrastructures capture data and provide a wider range of services including access to data and well instrumented research sites. The coevolution of supporting infrastructures and ecological sciences has developed into new science disciplines such as macrosystems ecology, whereby large-scale and multi-decadal-scale ecological processes are being explored. </p><p>Governments, decision-makers, researchers and the public have all recognized that the global economy, quality of life, and the environment are intrinsically intertwined and that ecosystem services ultimately depend on resilient ecological processes. These have been altered and threatened by various components of Global Change, e.g. land degradation, global warming and species loss. These threats are the unintended result of increasing anthropogenic activities and have the potential to change the fundamental trajectory of mankind.  This creates a unique challenge never before faced by society or science—how best to provide a sustainable economic future while understanding and globally managing a changing environment and human health upon which it relies.</p><p>The increasing number of Research Infrastructures around the globe now provides a unique and historical opportunity to respond to this challenge. Six major ecosystem Research Infrastructures (SAEON/South Africa, TERN/Australia, CERN/China, NEON/USA, ICOS/Europe, eLTER/Europe) have started federating to tackle the programmatic work needed for concerted operation and the provisioning of interoperable data and services. This Global Ecosystem Research Infrastructure (GERI) will be presented with a focus on the involved programmatic challenges and the GERI science rationale.</p>

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