scholarly journals Where in the air? Aerial habitat use of nocturnally migrating birds

2016 ◽  
Vol 12 (11) ◽  
pp. 20160591 ◽  
Author(s):  
Kyle G. Horton ◽  
Benjamin M. Van Doren ◽  
Phillip M. Stepanian ◽  
Andrew Farnsworth ◽  
Jeffrey F. Kelly
Keyword(s):  
Habitat Selection ◽  
Large Scale ◽  
Migratory Birds ◽  
Lower Atmosphere ◽  
Migration Activity ◽  
Maximum Wind ◽  
Eastern Usa ◽  
Migrant Birds ◽  
Spatio Temporal ◽  
Migrating Birds

The lower atmosphere (i.e. aerosphere) is critical habitat for migrant birds. This habitat is vast and little is known about the spatio-temporal patterns of distribution and abundance of migrants in it. Increased human encroachment into the aerosphere makes understanding where and when migratory birds use this airspace a key to reducing human–wildlife conflicts. We use weather surveillance radar to describe large-scale height distributions of nocturnally migrating birds and interpret these distributions as aggregate habitat selection behaviours of individual birds. As such, we detail wind cues that influence selection of flight heights. Using six radars in the eastern USA during the spring (2013–2015) and autumn (2013 and 2014), we found migrants tended to adjust their heights according to favourable wind profit. We found that migrants' flight altitudes correlated most closely with the altitude of maximum wind profit; however, absolute differences in flight heights and height of maximum wind profit were large. Migrants tended to fly slightly higher at inland sites compared with coastal sites during spring, but not during autumn. Migration activity was greater at coastal sites during autumn, but not during spring. This characterization of bird migration represents a critical advance in our understanding of migrant distributions in flight and a new window into habitat selection behaviours.

scholarly journals Theoretically possible spatial accuracy of geomagnetic maps used by migrating animals

2017 ◽  
Vol 14 (128) ◽  
pp. 20161002 ◽  
Author(s):  
Andrei V. Komolkin ◽  
Pavel Kupriyanov ◽  
Andrei Chudin ◽  
Julia Bojarinova ◽  
Kirill Kavokin ◽  
...  
Keyword(s):  
Field Intensity ◽  
Geomagnetic Field ◽  
Site Fidelity ◽  
Large Scale ◽  
Migratory Birds ◽  
Time Of Day ◽  
Northern Europe ◽  
Spatial Accuracy ◽  
Total Field ◽  
Migrating Birds

Many migrating animals, belonging to different taxa, annually move across the globe and cover hundreds and thousands of kilometres. Many of them are able to show site fidelity, i.e. to return to relatively small migratory targets, from distant areas located beyond the possible range of direct sensory perception. One widely debated possibility of how they do it is the use of a magnetic map, based on the dependence of parameters of the geomagnetic field (total field intensity and inclination) on geographical coordinates. We analysed temporal fluctuations of the geomagnetic field intensity as recorded by three geomagnetic observatories located in Europe within the route of many avian migrants, to study the highest theoretically possible spatial resolution of the putative map. If migratory birds measure total field intensity perfectly and take the time of day into account, in northern Europe 81% of them may return to a strip of land of 43 km in width along one of coordinates, whereas in more southern areas such a strip may be narrower than 10 km. However, if measurements are performed with an error of 0.1%, the strip width is increased by approximately 40 km, so that in spring migrating birds are able to return to within 90 km of their intended goal. In this case, migrating birds would probably need another navigation system, e.g. an olfactory map, intermediate between the large-scale geomagnetic map and the local landscape cues, to locate their goal to within several kilometres.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Air-Sea Interactions over Eddies in the Brazil-Malvinas Confluence

2021 ◽  
Vol 13 (7) ◽  
pp. 1335
Author(s):  
Ronald Souza ◽  
Luciano Pezzi ◽  
Sebastiaan Swart ◽  
Fabrício Oliveira ◽  
Marcelo Santini
Keyword(s):  
Latent Heat ◽  
Large Scale ◽  
Surface Wind ◽  
Heat Fluxes ◽  
Lower Atmosphere ◽  
Meteorological Variables ◽  
Global Ocean ◽  
Study Region ◽  
Cold Core

The Brazil–Malvinas Confluence (BMC) is one of the most dynamical regions of the global ocean. Its variability is dominated by the mesoscale, mainly expressed by the presence of meanders and eddies, which are understood to be local regulators of air-sea interaction processes. The objective of this work is to study the local modulation of air-sea interaction variables by the presence of either a warm (ED1) and a cold core (ED2) eddy, present in the BMC, during September to November 2013. The translation and lifespans of both eddies were determined using satellite-derived sea level anomaly (SLA) data. Time series of satellite-derived surface wind data, as well as these and other meteorological variables, retrieved from ERA5 reanalysis at the eddies’ successive positions in time, allowed us to investigate the temporal modulation of the lower atmosphere by the eddies’ presence along their translation and lifespan. The reanalysis data indicate a mean increase of 78% in sensible and 55% in latent heat fluxes along the warm eddy trajectory in comparison to the surrounding ocean of the study region. Over the cold core eddy, on the other hand, we noticed a mean reduction of 49% and 25% in sensible and latent heat fluxes, respectively, compared to the adjacent ocean. Additionally, a field campaign observed both eddies and the lower atmosphere from ship-borne observations before, during and after crossing both eddies in the study region during October 2013. The presence of the eddies was imprinted on several surface meteorological variables depending on the sea surface temperature (SST) in the eddy cores. In situ oceanographic and meteorological data, together with high frequency micrometeorological data, were also used here to demonstrate that the local, rather than the large scale forcing of the eddies on the atmosphere above, is, as expected, the principal driver of air-sea interaction when transient atmospheric systems are stable (not actively varying) in the study region. We also make use of the in situ data to show the differences (biases) between bulk heat flux estimates (used on atmospheric reanalysis products) and eddy covariance measurements (taken as “sea truth”) of both sensible and latent heat fluxes. The findings demonstrate the importance of short-term changes (minutes to hours) in both the atmosphere and the ocean in contributing to these biases. We conclude by emphasizing the importance of the mesoscale oceanographic structures in the BMC on impacting local air-sea heat fluxes and the marine atmospheric boundary layer stability, especially under large scale, high-pressure atmospheric conditions.

scholarly journals Combining Regional Habitat Selection Models for Large-Scale Prediction: Circumpolar Habitat Selection of Southern Ocean Humpback Whales

2021 ◽  
Vol 13 (11) ◽  
pp. 2074
Author(s):  
Ryan R. Reisinger ◽  
Ari S. Friedlaender ◽  
Alexandre N. Zerbini ◽  
Daniel M. Palacios ◽  
Virginia Andrews-Goff ◽  
...  
Keyword(s):  
Habitat Selection ◽  
Predictive Models ◽  
Regional Variation ◽  
Large Scale ◽  
Predictive Performance ◽  
Humpback Whale ◽  
Machine Learning Algorithms ◽  
Humpback Whales ◽  
Environmental Covariates ◽  
Animal Habitat

Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and regions; thus, it would seem preferable to fit region- or population-specific models of habitat selection for more accurate inference and prediction, rather than fitting large-scale models using pooled data. However, where the aim is to make range-wide predictions, including areas for which there are no existing data or models of habitat selection, how can regional models best be combined? We propose that ensemble approaches commonly used to combine different algorithms for a single region can be reframed, treating regional habitat selection models as the candidate models. By doing so, we can incorporate regional variation when fitting predictive models of animal habitat selection across large ranges. We test this approach using satellite telemetry data from 168 humpback whales across five geographic regions in the Southern Ocean. Using random forests, we fitted a large-scale model relating humpback whale locations, versus background locations, to 10 environmental covariates, and made a circumpolar prediction of humpback whale habitat selection. We also fitted five regional models, the predictions of which we used as input features for four ensemble approaches: an unweighted ensemble, an ensemble weighted by environmental similarity in each cell, stacked generalization, and a hybrid approach wherein the environmental covariates and regional predictions were used as input features in a new model. We tested the predictive performance of these approaches on an independent validation dataset of humpback whale sightings and whaling catches. These multiregional ensemble approaches resulted in models with higher predictive performance than the circumpolar naive model. These approaches can be used to incorporate regional variation in animal habitat selection when fitting range-wide predictive models using machine learning algorithms. This can yield more accurate predictions across regions or populations of animals that may show variation in habitat selection.

scholarly journals Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

Science ◽  
2021 ◽  
pp. eabf2946
Author(s):  
Louis du Plessis ◽  
John T. McCrone ◽  
Alexander E. Zarebski ◽  
Verity Hill ◽  
Christopher Ruis ◽  
...  
Keyword(s):  
Large Scale ◽  
Phylogenetic Analyses ◽  
Transmission Dynamics ◽  
Genetic Lineage ◽  
Size Dependent ◽  
Spatio Temporal ◽  
The Uk ◽  
Lineage Structure ◽  
And Control ◽  
Lineage Diversity

The UK’s COVID-19 epidemic during early 2020 was one of world’s largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country’s first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, while lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

scholarly journals Analysis of local habitat selection and large-scale attraction/avoidance based on animal tracking data: is there a single best method?

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Moritz Mercker ◽  
Philipp Schwemmer ◽  
Verena Peschko ◽  
Leonie Enners ◽  
Stefan Garthe
Keyword(s):  
Habitat Selection ◽  
Large Scale ◽  
Error Rates ◽  
Process Models ◽  
Statistical Hypothesis ◽  
Type I ◽  
Tracking Data ◽  
Selection Models ◽  
Animal Tracking ◽  
Step Selection

Abstract Background New wildlife telemetry and tracking technologies have become available in the last decade, leading to a large increase in the volume and resolution of animal tracking data. These technical developments have been accompanied by various statistical tools aimed at analysing the data obtained by these methods. Methods We used simulated habitat and tracking data to compare some of the different statistical methods frequently used to infer local resource selection and large-scale attraction/avoidance from tracking data. Notably, we compared spatial logistic regression models (SLRMs), spatio-temporal point process models (ST-PPMs), step selection models (SSMs), and integrated step selection models (iSSMs) and their interplay with habitat and animal movement properties in terms of statistical hypothesis testing. Results We demonstrated that only iSSMs and ST-PPMs showed nominal type I error rates in all studied cases, whereas SSMs may slightly and SLRMs may frequently and strongly exceed these levels. iSSMs appeared to have on average a more robust and higher statistical power than ST-PPMs. Conclusions Based on our results, we recommend the use of iSSMs to infer habitat selection or large-scale attraction/avoidance from animal tracking data. Further advantages over other approaches include short computation times, predictive capacity, and the possibility of deriving mechanistic movement models.

scholarly journals Historical drought patterns over Canada and their teleconnections with large-scale climate signals

2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Kendall Test ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Data Sets ◽  
Canadian Prairies ◽  
Agriculture Industry ◽  
Spatio Temporal

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

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