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476 records – page 1 of 48.

[Distribution and population density of Ixodes persulcatus ticks in Sakhalin].

https://arctichealth.org/en/permalink/ahliterature255612
Source
Med Parazitol (Mosk). 1972 Mar-Apr;41(2):220-3
Publication Type
Article
Author
V S Surkov
K V Kon'kova
I K Anikeev
Source
Med Parazitol (Mosk). 1972 Mar-Apr;41(2):220-3
Language
Russian
Publication Type
Article
Keywords
Ecology
Humans
Population Density
Siberia
Ticks
PubMed ID
5042564 View in PubMed
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Comparing population and incident data for optimal air ambulance base locations in Norway.

https://arctichealth.org/en/permalink/ahliterature294977
Source
Scand J Trauma Resusc Emerg Med. 2018 May 24; 26(1):42
Publication Type
Journal Article
Date
May-24-2018
Author
Jo Røislien
Pieter L van den Berg
Thomas Lindner
Erik Zakariassen
Oddvar Uleberg
Karen Aardal
J Theresia van Essen
Author Affiliation
Faculty of Health Sciences, University of Stavanger, Stavanger, Norway. jo.roislien@norskluftambulanse.no.
Source
Scand J Trauma Resusc Emerg Med. 2018 May 24; 26(1):42
Date
May-24-2018
Language
English
Publication Type
Journal Article
Keywords
Air Ambulances - organization & administration
Humans
Norway
Population Density
Abstract
Helicopter emergency medical services are important in many health care systems. Norway has a nationwide physician manned air ambulance service servicing a country with large geographical variations in population density and incident frequencies. The aim of the study was to compare optimal air ambulance base locations using both population and incident data.
We used municipality population and incident data for Norway from 2015. The 428 municipalities had a median (5-95 percentile) of 4675 (940-36,264) inhabitants and 10 (2-38) incidents. Optimal helicopter base locations were estimated using the Maximal Covering Location Problem (MCLP) optimization model, exploring the number and location of bases needed to cover various fractions of the population for time thresholds 30 and 45 min, in green field scenarios and conditioned on the existing base structure.
The existing bases covered 96.90% of the population and 91.86% of the incidents for time threshold 45 min. Correlation between municipality population and incident frequencies was -0.0027, and optimal base locations varied markedly between the two data types, particularly when lowering the target time. The optimal solution using population density data put focus on the greater Oslo area, where one third of Norwegians live, while using incident data put focus on low population high incident areas, such as northern Norway and winter sport resorts.
Using population density data as a proxy for incident frequency is not recommended, as the two data types lead to different optimal base locations. Lowering the target time increases the sensitivity to choice of data.
Notes
Cites: Acta Anaesthesiol Scand. 2017 Aug;61(7):841-847 PMID 28653327
Cites: Air Med J. 2015 Mar-Apr;34(2):98-103 PMID 25733116
Cites: Injury. 2014 Oct;45 Suppl 3:S93-9 PMID 25284243
Cites: Prehosp Emerg Care. 2013 Oct-Dec;17(4):521-5 PMID 23834231
Cites: J Trauma. 2010 Nov;69(5):1030-4; discussion 1034-6 PMID 21068607
Cites: Emerg Med Australas. 2004 Aug;16(4):318-23 PMID 15283719
Cites: Acta Anaesthesiol Scand. 2013 May;57(5):660-8 PMID 23289798
Cites: J Trauma Acute Care Surg. 2015 Nov;79(5):756-65 PMID 26335775
Cites: Tidsskr Nor Laegeforen. 2012 Sep 4;132(16):1848-9 PMID 22986968
Cites: Acta Anaesthesiol Scand. 2016 May;60(5):659-67 PMID 26810562
Cites: Scand J Trauma Resusc Emerg Med. 2012 Jan 26;20:3 PMID 22280935
Cites: J Trauma. 2004 Jan;56(1):94-8 PMID 14749573
Cites: Emerg Med J. 2013 Jun;30(6):462-6 PMID 22736718
Cites: JAMA. 2012 Apr 18;307(15):1602-10 PMID 22511688
Cites: J Trauma. 2001 Jul;51(1):118-22 PMID 11468478
Cites: Resuscitation. 2010 Apr;81(4):427-33 PMID 20122784
Cites: J Trauma Acute Care Surg. 2012 Mar;72(3):567-73; discussion 573-5; quiz 803 PMID 22491538
Cites: Acta Anaesthesiol Scand. 2002 Aug;46(7):771-8 PMID 12139529
Cites: Injury. 2011 Oct;42(10):1088-94 PMID 21459379
Cites: Ann Emerg Med. 2013 Oct;62(4):351-364.e19 PMID 23582619
Cites: Inj Prev. 2017 Feb;23 (1):10-15 PMID 27325670
PubMed ID
29793526 View in PubMed
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[Arctic regions and their populations].

https://arctichealth.org/en/permalink/ahliterature231599
Source
Duodecim. 1989;105(5):399-405
Publication Type
Article
Date
1989
Author
A. Naukkarinen
Source
Duodecim. 1989;105(5):399-405
Date
1989
Language
Finnish
Publication Type
Article
Keywords
Arctic Regions
Geography
Humans
Population Density
Social Conditions
PubMed ID
2721398 View in PubMed
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[Estimation of the population density and its significance in gene geography].

https://arctichealth.org/en/permalink/ahliterature200777
Source
Genetika. 1999 May;35(5):703-11
Publication Type
Article
Date
May-1999
Author
A N Evsiukov
O V Zhukova
Iu G Rychkov
Author Affiliation
Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.
Source
Genetika. 1999 May;35(5):703-11
Date
May-1999
Language
Russian
Publication Type
Article
Keywords
Anisotropy
Genetics, Population
Geography
Humans
Models, Statistical
Population Density
Abstract
A factor of the association between gene geographical data and populations of the mapped region was analyzed. This allowed for correction of the equations for the major statistical parameters of gene geographical maps (mean, variance, etc.) and gene geographical methods of estimating the spatial nonstationarity of data within a mapped region. The proposed approach is based on the use of the population density in a mapped region as a factor reflecting the anisotropy of the geographical space. The population density of the North Eurasian indigenous populations was mapped, and the application of the resulting map was illustrated with an example.
PubMed ID
10495955 View in PubMed
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[Prediction of malaria spread in Russia in the first quarter of the 21st century].

https://arctichealth.org/en/permalink/ahliterature179700
Source
Med Parazitol (Mosk). 2004 Apr-Jun;(2):31-3
Publication Type
Article
Author
V V Iasiukevich
Source
Med Parazitol (Mosk). 2004 Apr-Jun;(2):31-3
Language
Russian
Publication Type
Article
Keywords
Climate
Forecasting
Humans
Malaria - epidemiology
Population Density
Russia - epidemiology
Abstract
The paper presents a prediction of changes in the potential areas of tertian malaria till 2025. It shows that possible climatic changes whose main features are an increase in average annual temperatures do not imply a uniform expansion of areas for parasitic infections. The regional and seasonal trends of temperature changes in Russia (both established for the 20th century and predicted for the early 21st century) will both expand the area in its one part and reduce in its another part. Overall, the changes caused by climatic factors in the potential area of human malaria in Russia in the first quarter of the 21st century will not lead to a drastically aggravated malaria epidemiological situation.
PubMed ID
15193047 View in PubMed
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[Results of a comparison of methods for assessing a human blackfly attack].

https://arctichealth.org/en/permalink/ahliterature247036
Source
Med Parazitol (Mosk). 1979 Jul-Aug;48(4):56-62
Publication Type
Article
Author
S P Rasnitsyn
A N Bikunova
Source
Med Parazitol (Mosk). 1979 Jul-Aug;48(4):56-62
Language
Russian
Publication Type
Article
Keywords
Animals
Diptera
Entomology - methods
Humans
Population Density
Seasons
Siberia
PubMed ID
481329 View in PubMed
Less detail

[Denmark is overcrowded, I wonder when we'll discover the danger?].

https://arctichealth.org/en/permalink/ahliterature253183
Source
Ugeskr Laeger. 1974 Sep 2;136(36):2055-6
Publication Type
Article
Date
Sep-2-1974
Author
S. Kratholm
Source
Ugeskr Laeger. 1974 Sep 2;136(36):2055-6
Date
Sep-2-1974
Language
Danish
Publication Type
Article
Keywords
Animals
Crowding
Denmark
Great Britain
Humans
Mice
Population Density
PubMed ID
4409138 View in PubMed
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[Effect of population density on ecological characteristics of the grass moth Loxostege sticticalis L. (Lepidoptera: Pyralidae) in the gradation cycle]

https://arctichealth.org/en/permalink/ahliterature46175
Source
Izv Akad Nauk Ser Biol. 2000 Jan-Feb;(1):75-83
Publication Type
Article
Author
I B Knorr
A N Bashev
A A Alekseev
E N Naumova
Author Affiliation
Institute of Animal Systematics and Ecology, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.
Source
Izv Akad Nauk Ser Biol. 2000 Jan-Feb;(1):75-83
Language
Russian
Publication Type
Article
Keywords
Animals
Ecosystem
English Abstract
Moths - physiology
Pigmentation
Population Density
Siberia
Abstract
We continued to study the diversity of responses of the grass moth Loxostege sticticalis L. to variations of density. We estimated the dynamics of the internal state of individuals and considered the influence of the population prehistory on ecological characteristics of the phytophage. In experiments on studying the structure of flower forms of the larval stage, we showed the dependence of the parameters of the internal state of individuals on prehistory, specifically on the conditions of life and type of individuals of the preceding generation. At the same time, comparison of the experimental results of 1991 and 1994 revealed a drift of the parameters of the reaction to variations in the grass moth population density by the structure of the larval flower forms and actual fertility of the imago. On the whole, the data obtained suggests that the studied species is characterized by a complex system of endogenous mechanisms underlying the regulation of numbers. The dynamics of environmental parameters is mediated by a cascade of endogenous rearrangements, as a result of which transition from depression to mass reproduction is realized through succession of the types of individuals in the population, when instead of a single phase, the flock phase starts to dominate.
PubMed ID
10881430 View in PubMed
Less detail

Predicting grizzly bear density in western North America.

https://arctichealth.org/en/permalink/ahliterature257211
Source
PLoS One. 2013;8(12):e82757
Publication Type
Article
Date
2013
Author
Garth Mowat
Douglas C Heard
Carl J Schwarz
Author Affiliation
Natural Resource Science Section, Ministry of Forests, Lands and Natural Resource Operations, Nelson, British Columbia, Canada.
Source
PLoS One. 2013;8(12):e82757
Date
2013
Language
English
Publication Type
Article
Keywords
Animals
Canada
Ecosystem
Humans
North America
Population Density
Salmon
Ursidae
Abstract
Conservation of grizzly bears (Ursus arctos) is often controversial and the disagreement often is focused on the estimates of density used to calculate allowable kill. Many recent estimates of grizzly bear density are now available but field-based estimates will never be available for more than a small portion of hunted populations. Current methods of predicting density in areas of management interest are subjective and untested. Objective methods have been proposed, but these statistical models are so dependent on results from individual study areas that the models do not generalize well. We built regression models to relate grizzly bear density to ultimate measures of ecosystem productivity and mortality for interior and coastal ecosystems in North America. We used 90 measures of grizzly bear density in interior ecosystems, of which 14 were currently known to be unoccupied by grizzly bears. In coastal areas, we used 17 measures of density including 2 unoccupied areas. Our best model for coastal areas included a negative relationship with tree cover and positive relationships with the proportion of salmon in the diet and topographic ruggedness, which was correlated with precipitation. Our best interior model included 3 variables that indexed terrestrial productivity, 1 describing vegetation cover, 2 indices of human use of the landscape and, an index of topographic ruggedness. We used our models to predict current population sizes across Canada and present these as alternatives to current population estimates. Our models predict fewer grizzly bears in British Columbia but more bears in Canada than in the latest status review. These predictions can be used to assess population status, set limits for total human-caused mortality, and for conservation planning, but because our predictions are static, they cannot be used to assess population trend.
Notes
Cites: Science. 2002 Mar 22;295(5563):2273-611910114
Cites: Oecologia. 2004 Feb;138(3):465-7414673639
Cites: Oecologia. 2005 Sep;145(2):276-8116001227
Cites: Ecol Appl. 2006 Dec;16(6):2333-4317205908
Cites: Ecol Appl. 2007 Jul;17(5):1424-4017708219
Cites: Ecol Appl. 2008 Jun;18(4):1014-2718536259
Cites: PLoS One. 2010;5(5):e1041620463959
Cites: Philos Trans R Soc Lond B Biol Sci. 2010 Jul 27;365(1550):2245-5420566501
Cites: Philos Trans R Soc Lond B Biol Sci. 2010 Jul 27;365(1550):2255-6520566502
Cites: J Anim Ecol. 2013 Jul;82(4):836-4523461483
PubMed ID
24367552 View in PubMed
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Quantifying suitable late summer brood habitats for willow ptarmigan in Norway.

https://arctichealth.org/en/permalink/ahliterature298227
Source
BMC Ecol. 2018 10 03; 18(1):41
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Date
10-03-2018
Author
Mikkel Andreas Jørnsøn Kvasnes
Hans Christian Pedersen
Erlend Birkeland Nilsen
Author Affiliation
Norwegian Institute for Nature Research, Torgarden, P.O.Box 5685, Trondheim, 7485, Norway. mikkel.kvasnes@nina.no.
Source
BMC Ecol. 2018 10 03; 18(1):41
Date
10-03-2018
Language
English
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Keywords
Animals
Ecosystem
Galliformes - physiology
Models, Biological
Norway
Population Density
Seasons
Abstract
Habitat models provide information about which habitat management should target to avoid species extinctions or range contractions. The willow ptarmigan inhabits alpine- and arctic tundra habitats in the northern hemisphere and is listed as near threatened (NT) in the Norwegian red list due to declining population size. Habitat alteration is one of several factors affecting willow ptarmigan populations, but there is a lack of studies quantifying and describing habitat selection in willow ptarmigan. We used data from an extensive line transect survey program from 2014 to 2017 to develop resource selection functions (RSF) for willow ptarmigan in Norway. The selection coefficients for the RSF were estimated using a mixed-effects logistic regression model fitted with random intercepts for each area. We predicted relative probability of selection across Norway and quantile-binned the predictions in 10 RSF bins ranging from low-(1) to high-(10) relative probability of selection.
Random cross-validation suggest that our models were highly predictive, but validation based spatial blocking revealed that the predictability was better in southern parts of Norway compared to the northernmost region. Willow ptarmigan selected for herb-rich meadows and avoided lichen rich heathlands. There was generally stronger selection for vegetation types with dense field layer and for rich bogs and avoidance of vegetation types with sparse field layer cover and for lowland forest. Further, willow ptarmigan selected for areas around the timberline and for intermediate slopes. Mapping of the RSF showed that 60% of Norway is in the lowest ranked RSF bin and only 2% in the highest ranked RSF bin.
Willow ptarmigan selected for vegetation types with dense field layer and bogs at intermediate slopes around the timberline. Selection coincides with previous habitat selection studies on willow ptarmigan. This is the first attempt to assess and quantify habitat selection for willow ptarmigan at a large scale using data from line transect distance sampling surveys. Spatial variation in predictability suggests that habitat selection in late summer might vary from north to south. The resource selection map can be a useful tool when planning harvest quotas and habitat interventions in alpine areas.
PubMed ID
30285717 View in PubMed
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476 records – page 1 of 48.