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Journal articles on the topic 'Geographic bias'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

Burgman, Mark, Frith Jarrad, and Ellen Main. "Decreasing geographic bias inConservation Biology." Conservation Biology 29, no. 5 (September 17, 2015): 1255–56. http://dx.doi.org/10.1111/cobi.12589.

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2

Nagarkar, Purushottam A., and Jeffrey E. Janis. "Eliminating Geographic Bias Improves Match Results." Plastic and Reconstructive Surgery 142, no. 1 (July 2018): 82e—88e. http://dx.doi.org/10.1097/prs.0000000000004485.

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3

Sheth, Seema N., Lúcia G. Lohmann, Trisha Distler, and Iván Jiménez. "Understanding bias in geographic range size estimates." Global Ecology and Biogeography 21, no. 7 (October 11, 2011): 732–42. http://dx.doi.org/10.1111/j.1466-8238.2011.00716.x.

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4

Sialm, Clemens, Zheng Sun, and Lu Zheng. "Home Bias and Local Contagion: Evidence from Funds of Hedge Funds." Review of Financial Studies 33, no. 10 (December 23, 2019): 4771–810. http://dx.doi.org/10.1093/rfs/hhz138.

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Abstract Our paper analyzes the geographical preferences of hedge fund investors and the implication of these preferences for hedge fund performance. We find that funds of hedge funds overweigh their investments in hedge funds located in the same geographical areas and that funds with a stronger local bias exhibit superior performance. Local bias also gives rise to excess flow comovement and extreme return clustering within geographic areas. Overall, our results suggest that while funds of funds benefit from local advantages, their local bias also creates market segmentation that can destabilize the underlying hedge funds.

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5

Meijaard, Erik, Marcel Cardillo, Emily M. Meijaard, and Hugh P. Possingham. "Geographic bias in citation rates of conservation research." Conservation Biology 29, no. 3 (March 27, 2015): 920–25. http://dx.doi.org/10.1111/cobi.12489.

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6

Cosentino, Francesca, and Luigi Maiorano. "Is geographic sampling bias representative of environmental space?" Ecological Informatics 64 (September 2021): 101369. http://dx.doi.org/10.1016/j.ecoinf.2021.101369.

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7

Nutting, Andrew W. "Discrimination and Information: Geographic Bias in College Basketball Polls." Eastern Economic Journal 42, no. 1 (August 18, 2014): 80–103. http://dx.doi.org/10.1057/eej.2014.41.

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8

Chu, Hong Jiang, Yue Wu, Wen Yun Lin, and Yue Hua Wan. "Geographic Profiling Methods: Improvement and Combination." Applied Mechanics and Materials 34-35 (October 2010): 1507–11. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1507.

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Geographic profiling uses locations of series crimes to detect the most probable residence of the offender. However, because of shortage of other information, the method doesn't perform well. To Solve this problem, the concept of geographic profiling was extended and a concept of human geographic profiling (HGP) was put forward to take offender’s bias, victims’ characteristics, and geographical circumstances into account. The physical geographic profiling (PGP) was obtained by combining an improved “spatial mean” method and an improved criminal geographic targeting (CGT) model by using a precisely deduced "Combination Function". Afterwards, HGP and PCG were combined by the same function. The resultant product was a three-dimentional probability map. Simulation result indicated high accuracy rates among which the lowest is 66% under an ideal situation. The introduction of HGP and deduction of combination function are discussed originally and are of great importance in this paper.

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Romo, Helena, Enrique García-Barros, and Jorge M. Lobo. "Identifying recorder-induced geographic bias in an Iberian butterfly database." Ecography 29, no. 6 (December 2006): 873–85. http://dx.doi.org/10.1111/j.2006.0906-7590.04680.x.

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10

Branch, Jordan. "Geographic Information Systems (GIS) in International Relations." International Organization 70, no. 4 (2016): 845–69. http://dx.doi.org/10.1017/s0020818316000199.

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AbstractGeographic Information Systems (GIS) are being applied with increasing frequency, and with increasing sophistication, in international relations and in political science more generally. Their benefits have been impressive: analyses that simply would not have been possible without GIS are now being completed, and the spatial component of international politics—long considered central but rarely incorporated analytically—has been given new emphasis. However, new methods face new challenges, and to apply GIS successfully, two specific issues need to be addressed: measurement validity and selection bias. Both relate to the challenge of conceptualizing nonspatial phenomena with the spatial tools of GIS. Significant measurement error can occur when the concepts that are coded as spatial variables are not, in fact, validly measured by the default data structure of GIS, and selection bias can arise when GIS systematically excludes certain types of units. Because these potential problems are hidden by the technical details of the method, GIS data sets and analyses can sometimes appear to overcome these challenges when, in fact, they fail to do so. Once these issues come to light, however, potential solutions become apparent—including some in existing applications in international relations and in other fields.

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Poulin, Robert, Eleanor Hay, and Fátima Jorge. "Taxonomic and geographic bias in the genetic study of helminth parasites." International Journal for Parasitology 49, no. 6 (May 2019): 429–35. http://dx.doi.org/10.1016/j.ijpara.2018.12.005.

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12

Zhang, Guiming, and A.-Xing Zhu. "The representativeness and spatial bias of volunteered geographic information: a review." Annals of GIS 24, no. 3 (July 3, 2018): 151–62. http://dx.doi.org/10.1080/19475683.2018.1501607.

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13

Sólymos, P. "Geographic and taxonomic bias in land snail distribution data of Hungary." Community Ecology 8, no. 2 (December 2007): 239–46. http://dx.doi.org/10.1556/comec.8.2007.2.10.

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14

Russell, Michael P., and David R. Lindberg. "Real and random patterns associated with molluscan spatial and temporal distributions." Paleobiology 14, no. 4 (1988): 322–30. http://dx.doi.org/10.1017/s0094837300012070.

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The species-level properties of geographic range and geologic duration are often used as variables in evolutionary studies. However, estimates of species duration are not independent of estimates of geographic range. Before these properties are used in macroevolutionary hypotheses, error associated with these estimates must be quantified. This error may lead to spurious inferences of evolutionary processes. To assess the error associated with estimates of geographic range and geologic duration, we modeled various sampling regimes and calculated the bias associated with these estimates.We present three analyses which document the bias associated with estimates of geographic range and geologic duration. First, we find a positive correlation between local abundance and geographic range for a sample of 180 species of Recent prosobranch gastropods from the northeastern temperate Pacific Ocean. Therefore, geographically short-ranging species are less likely to be represented in the fossil record than geographically long-ranging species because of their local rarity. Second, we demonstrate that the chance of underestimating the geographic range of a species is acute for species with restricted spatial distributions, further compounding the problem of documenting their distribution in space and time. Third, we present a simulation which quantifies the degree of autocorrelation between geographic range and geologic duration for different levels of sampling resolution and spatial distributions of fossil localities.

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15

Bridges, F. Stephen, C. Bennett Williamson, and Jennifer J. Scheibe. "Abortion Affiliation, Urban Size, and Geographic Bias of Responses to Lost Letters." Psychological Reports 83, no. 3 (December 1998): 1107–12. http://dx.doi.org/10.2466/pr0.1998.83.3.1107.

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A study using 1800 “lost letters” was designed to test the hypothesis that returned responses would be greater in smaller rural communities (population M = 964) than in a city (population = 60,591) or the suburbs (population = 195,847) unless the addressee was affiliated with a pro-abortion group. Returns to control, Committee For Free Abortion, and Committee Against Free Abortion affiliates were 37.2%, 24.0%, 29.3%, respectively. From the city, the number of returned letters was much larger than the number from the suburbs except for those letters with an affiliation to the pro-abortion condition. Returned letters from the city were fewer than those from smaller rural communities except those letters affiliated with the pro-abortion group. More letters affiliated with the pro-abortion condition were returned from the suburbs than from the smaller rural communities. The geographic condition influenced over-all rates of return. Rates were higher when letters were addressed to a city P.O. Box than to a rural one. Second, rates were also greater in smaller rural communities for letters bearing “in-town” (Molino) and “out-of-town” (Pensacola) addresses than those from the city bearing an “out-of-town” (Molino) address. These findings seem to indicate the possibility that there may be some geographic bias in the willingness of people to help a stranger in need by returning a lost letter.

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16

Johnson, Rich G., and Miles Romney. "How the West Was Lost: Geographic Bias on Sports- Network Highlight Shows." Journal of Sports Media 13, no. 1 (2018): 99–121. http://dx.doi.org/10.1353/jsm.2018.0004.

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BRIDGE, F. STEPHEN. "ABORTION AFFILIATION, URBAN SIZE, AND GEOGRAPHIC BIAS OF RESPONSES TO LOST LETTERS." Psychological Reports 83, no. 7 (1998): 1107. http://dx.doi.org/10.2466/pr0.83.7.1107-1112.

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18

Baden, Brett M., Douglas S. Noonan, and Rama Mohana R. Turaga. "Scales of justice: Is there a geographic bias in environmental equity analysis?" Journal of Environmental Planning and Management 50, no. 2 (March 2007): 163–85. http://dx.doi.org/10.1080/09640560601156433.

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19

Díaz-Muñoz, Samuel L., Olivier Tenaillon, Daniel Goldhill, Kristen Brao, Paul E. Turner, and Lin Chao. "Electrophoretic mobility confirms reassortment bias among geographic isolates of segmented RNA phages." BMC Evolutionary Biology 13, no. 1 (2013): 206. http://dx.doi.org/10.1186/1471-2148-13-206.

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20

Irmak, Caglar, Rebecca Walker Naylor, and William O. Bearden. "The out-of-region bias: Distance estimations based on geographic category membership." Marketing Letters 22, no. 2 (July 16, 2010): 181–96. http://dx.doi.org/10.1007/s11002-010-9120-3.

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21

Martin, Gregory J., and Steven W. Webster. "Does residential sorting explain geographic polarization?" Political Science Research and Methods 8, no. 2 (October 22, 2018): 215–31. http://dx.doi.org/10.1017/psrm.2018.44.

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AbstractPolitical preferences in the United States are highly correlated with population density, at national, state, and metropolitan-area scales. Using new data from voter registration records, we assess the extent to which this pattern can be explained by geographic mobility. We find that the revealed preferences of voters who move from one residence to another correlate with partisan affiliation, though voters appear to be sorting on non-political neighborhood attributes that covary with partisan preferences rather than explicitly seeking politically congruent neighbors. But, critically, we demonstrate through a simulation study that the estimated partisan bias in moving choices is on the order of five times too small to sustain the current geographic polarization of preferences. We conclude that location must have some influence on political preference, rather than the other way around, and provide evidence in support of this theory.

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22

Donaldson, Michael R., Nicholas J. Burnett, Douglas C. Braun, Cory D. Suski, Scott G. Hinch, Steven J. Cooke, and Jeremy T. Kerr. "Taxonomic bias and international biodiversity conservation research." FACETS 1, no. 1 (March 1, 2017): 105–13. http://dx.doi.org/10.1139/facets-2016-0011.

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While greater research on threatened species alone cannot ensure their protection, understanding taxonomic bias may be helpful to address knowledge gaps in order to identify research directions and inform policy. Using data for over 10 000 animal species listed on the International Union for Conservation of Nature Red List, we investigated taxonomic and geographic biodiversity conservation research trends worldwide. We found extreme bias in conservation research effort on threatened vertebrates compared with lesser-studied invertebrates in both terrestrial and aquatic habitats at a global scale. Based on an analysis of common threats affecting vertebrates and invertebrates, we suggest a path forward for narrowing the research gap between threatened vertebrates and invertebrates.

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23

Culumber, Zachary W., Jaime M. Anaya-Rojas, William W. Booker, Alexandra P. Hooks, Elizabeth C. Lange, Benjamin Pluer, Natali Ramírez-Bullón, and Joseph Travis. "Widespread Biases in Ecological and Evolutionary Studies." BioScience 69, no. 8 (July 10, 2019): 631–40. http://dx.doi.org/10.1093/biosci/biz063.

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Abstract There has been widespread discussion of biases in the sciences. The extent of most forms of bias has scarcely been confronted with rigorous data. In the present article, we evaluated the potential for geographic, taxonomic, and citation biases in publications between temperate and tropical systems for nine broad topics in ecology and evolutionary biology. Across 1,800 papers sampled from 60,000 peer-reviewed, empirical studies, we found consistent patterns of bias in the form of increased numbers of studies in temperate systems. Tropical studies were nearly absent from some topics. Furthermore, there were strong taxonomic biases across topics and geographic regions, as well as evidence for citation biases in many topics. Our results indicate a strong geographic imbalance in publishing patterns and among different taxonomic groups across a wide range of topics. The task ahead is to address what these biases mean and how they influence the state of our knowledge in ecology and evolution.

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24

Schootman, M., D. Sterling, J. Struthers, Y. Yan, T. Laboube, B. Emo, and G. Higgs. "Positional Accuracy and Geographic Bias of 3 Methods of Geocoding in Epidemiologic Research." American Journal of Epidemiology 163, suppl_11 (June 1, 2006): S26. http://dx.doi.org/10.1093/aje/163.suppl_11.s26-d.

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25

Cai, Qingzhong, Gongliu Yang, Ningfang Song, Lifen Wang, Hongliang Yin, and Yiliang Liu. "Online Calibration of the Geographic-Frame-Equivalent Gyro Bias in Dual-Axis RINS." IEEE Transactions on Instrumentation and Measurement 67, no. 7 (July 2018): 1609–16. http://dx.doi.org/10.1109/tim.2018.2800878.

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26

Schootman, Mario, David A. Sterling, James Struthers, Yan Yan, Ted Laboube, Brett Emo, and Gary Higgs. "Positional Accuracy and Geographic Bias of Four Methods of Geocoding in Epidemiologic Research." Annals of Epidemiology 17, no. 6 (June 2007): 464–70. http://dx.doi.org/10.1016/j.annepidem.2006.10.015.

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27

Coën, Alain, Arnaud Simon, and Saadallah Zaiter. "Why is there a Home Bias? An Analysis of US REITs Geographic Concentration." Finance Vol. 42, no. 1 (May 18, 2021): 111–54. http://dx.doi.org/10.3917/fina.421.0111.

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28

Nowak, Adam D., and Patrick S. Smith. "Quality-Adjusted House Price Indexes." American Economic Review: Insights 2, no. 3 (September 1, 2020): 339–56. http://dx.doi.org/10.1257/aeri.20190337.

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The constant-quality assumption in repeat-sales house price indexes (HPIs) introduces a significant time-varying attribute bias. The direction, magnitude, and source of the bias varies throughout the market cycle and across metropolitan statistical areas (MSAs). We mitigate the bias using a data-driven textual analysis approach that identifies and includes salient text from real estate agent remarks in the repeat-sales estimation. Absent the text, MSA-level HPIs are biased downward by as much as 7 percent during the financial crisis and upward by as much as 20 percent after the crisis. The geographic concentration of the bias magnifies its effect on local HPIs. (JEL C43, E31, R11, R31)

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29

Fowler, Christopher S., and Leif Jensen. "Bridging the gap between geographic concept and the data we have: The case of labor markets in the USA." Environment and Planning A: Economy and Space 52, no. 7 (February 14, 2020): 1395–414. http://dx.doi.org/10.1177/0308518x20906154.

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A broad literature has made it clear that geographic units must be selected with care or they are likely to introduce error and uncertainty into results. Nevertheless, researchers often use data “off the shelf” with the implicit assumptions that their observations are consistent with the geographical concept relevant for their research question, and that they are of uniformly high quality in capturing this geographic identity. In this paper, we consider the geographical concept of “labor market” and offer a template for both clarifying its meaning for research and testing the suitability of extant labor-market delineations. We establish a set of metrics for comparing the quality of existing labor-market delineations with respect to the diverse meanings that researchers apply to the concept. Using the fit metrics established here, researchers can explore how delineations vary geographically, how they vary over time, and how this variation may shape research outcomes. Our assessment is that the quality of the extant delineations is relatively high overall. However, we find that different delineations vary significantly in the types of labor markets they represent, and that regional variations in fit within any given delineation may introduce noise or regional bias that merits consideration in any analysis conducted with these units. More broadly, the kinds of metrics we propose here have applicability for many other geographic entities where boundaries and scale can be only imperfectly defined.

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30

Mennis, Jeremy, Michael Mason, Donna L. Coffman, and Kevin Henry. "Geographic Imputation of Missing Activity Space Data from Ecological Momentary Assessment (EMA) GPS Positions." International Journal of Environmental Research and Public Health 15, no. 12 (December 4, 2018): 2740. http://dx.doi.org/10.3390/ijerph15122740.

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This research presents a pilot study to develop and compare methods of geographic imputation for estimating the location of missing activity space data collected using geographic ecological momentary assessment (GEMA). As a demonstration, we use data from a previously published analysis of the effect of neighborhood disadvantage, captured at the U.S. Census Bureau tract level, on momentary psychological stress among a sample of 137 urban adolescents. We investigate the impact of listwise deletion on model results and test two geographic imputation techniques adapted for activity space data from hot deck and centroid imputation approaches. Our results indicate that listwise deletion can bias estimates of place effects on health, and that these impacts are mitigated by the use of geographic imputation, particularly regarding inflation of the standard errors. These geographic imputation techniques may be extended in future research by incorporating approaches from the non-spatial imputation literature as well as from conventional geographic imputation and spatial interpolation research that focus on non-activity space data.

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Webb, Gregory E., William J. Sando, and Anne Raymond. "Mississippian coral latitudinal diversity gradients (western interior United States): Testing the limits of high resolution diversity data." Journal of Paleontology 71, no. 5 (September 1997): 780–91. http://dx.doi.org/10.1017/s0022336000035733.

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Analysis of high resolution diversity data for Mississippian corals in the western interior United States yielded mild latitudinal diversity gradients despite the small geographic area covered by samples and a large influence on diversity patterns by geographic sampling intensity (sample bias). Three competing plate tectonic reconstructions were tested using the diversity patterns. Although none could be forcefully rejected, one reconstruction proved less consistent with diversity patterns than the other two and additional coral diversity data from farther north in Canada would better discriminate the two equivalent reconstructions.Despite the relatively high sampling intensity represented by the analyzed database, diversity patterns were greatly affected by sample abundance and distribution. Hence, some effort at recognizing and accounting for sample bias should be undertaken in any study of latitudinal diversity gradients. Small-scale geographic lumping of sample localities had only small effects on geographic diversity patterns. However, large-scale (e.g., regional) geographic lumping of diversity data may not yield latitudinally sensitive diversity patterns. Temporal changes in coral diversity in this region reflect changes in eustacy, local tectonism, and terrigenous sediment flux, far more than they do shifting latitude. Highest regional diversity occurred during the interval when the studied region occupied the highest latitude. Therefore, diversity data from different regions may not be comparable, in terms of latitudinal inference. Small-scale stratigraphic lumping of the data caused a nearly complete loss of the latitudinal diversity patterns apparent prior to lumping. Hence, the narrowest possible stratigraphic resolution should be maintained in analyzing latitudinal diversity gradients.

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32

Eagles, Paul F. J., and Hector Ceballos-Lascurain. "Bias in American Ornithologists' Union Bird Names." Canadian Field-Naturalist 123, no. 3 (July 1, 2009): 295. http://dx.doi.org/10.22621/cfn.v123i3.980.

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Ornithology has developed bodies to make collective decisions on the taxonomy, scientific names, and common names of birds. This tradition within ornithology assists with communication and reduces confusion. For North and Central America, a committee of the American Ornithologists' Union standardizes the taxonomy and nomenclature of all the birds that naturally occur within that area. This paper makes the point that this activity has been dominated by members from the United States, with insufficient attention paid to the appropriate use of the term "American" or to the concerns of citizens of countries other than the USA. As a result, the term "American" is used inappropriately as a synonym for North American in a geographic distribution sense. In addition, the terms "Canadian" and "Mexican" are used very sparingly or not at all in the English common name for species that occur in those countries. Suggestions are made with regards to the membership of the nomenclature committee and for remedying this problem with English common names.

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33

Hansen, Richard A., Amanda Clarke Henley, Emily S. Brouwer, Adaora N. Oraefo, and Mary T. Roth. "Geographic Information System mapping as a tool to assess nonresponse bias in survey research." Research in Social and Administrative Pharmacy 3, no. 3 (September 2007): 249–64. http://dx.doi.org/10.1016/j.sapharm.2006.10.001.

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34

Botts, Emily A., Barend F. N. Erasmus, and Graham J. Alexander. "Geographic sampling bias in the South African Frog Atlas Project: implications for conservation planning." Biodiversity and Conservation 20, no. 1 (December 5, 2010): 119–39. http://dx.doi.org/10.1007/s10531-010-9950-6.

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35

Beck, Jan, Marianne Böller, Andreas Erhardt, and Wolfgang Schwanghart. "Spatial bias in the GBIF database and its effect on modeling species' geographic distributions." Ecological Informatics 19 (January 2014): 10–15. http://dx.doi.org/10.1016/j.ecoinf.2013.11.002.

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36

Medina, Richard M., Emily A. Nicolosi, Simon Brewer, and Erin Moore. "A Geographical Analysis of Socioeconomic and Ideological Drivers of Hate Crime in the United States." International Journal of Applied Geospatial Research 12, no. 2 (April 2021): 39–56. http://dx.doi.org/10.4018/ijagr.2021040103.

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Criminal activities motivated by hate are the most extreme form of bias against people. While hating a class of people and organizing in hate groups to express feelings against those people are not illegal, hate crimes, violent and non-violent, are illegal. However, there remains much to be learned about geographic patterns of hate crimes and facilitating environments. This exploratory research examines hate crime occurrences aggregated to counties in the conterminous United States and attempts to explain resulting patterns using socioeconomic and ideological correlates with traditional and spatial statistics. Geographical patterns of hate crimes in the Unites States are found to be a complicated phenomenon.

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37

Davis, Melanie L., Brian Neelon, Paul J. Nietert, Kelly J. Hunt, Lane F. Burgette, Andrew B. Lawson, and Leonard E. Egede. "Addressing geographic confounding through spatial propensity scores: a study of racial disparities in diabetes." Statistical Methods in Medical Research 28, no. 3 (November 16, 2017): 734–48. http://dx.doi.org/10.1177/0962280217735700.

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Motivated by a study exploring differences in glycemic control between non-Hispanic black and non-Hispanic white veterans with type 2 diabetes, we aim to address a type of confounding that arises in spatially referenced observational studies. Specifically, we develop a spatial doubly robust propensity score estimator to reduce bias associated with geographic confounding, which occurs when measured or unmeasured confounding factors vary by geographic location, leading to imbalanced group comparisons. We augment the doubly robust estimator with spatial random effects, which are assigned conditionally autoregressive priors to improve inferences by borrowing information across neighboring geographic regions. Through a series of simulations, we show that ignoring spatial variation results in increased absolute bias and mean squared error, while the spatial doubly robust estimator performs well under various levels of spatial heterogeneity and moderate sample sizes. In the motivating application, we construct three global estimates of the risk difference between race groups: an unadjusted estimate, a doubly robust estimate that adjusts only for patient-level information, and a hierarchical spatial doubly robust estimate. Results indicate a gradual reduction in the risk difference at each stage, with the inclusion of spatial random effects providing a 20% reduction compared to an estimate that ignores spatial heterogeneity. Smoothed maps indicate poor glycemic control across Alabama and southern Georgia, areas comprising the so-called “stroke belt.” These results suggest the need for community-specific interventions to target diabetes in geographic areas of greatest need.

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38

Truchado, Daniel A., Alejandro Llanos-Garrido, David A. Oropesa-Olmedo, Belén Cerrada, Pablo Cea, Michaël A. J. Moens, Esperanza Gomez-Lucia, et al. "Comparative Metagenomics of Palearctic and Neotropical Avian Cloacal Viromes Reveal Geographic Bias in Virus Discovery." Microorganisms 8, no. 12 (November 26, 2020): 1869. http://dx.doi.org/10.3390/microorganisms8121869.

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Our understanding about viruses carried by wild animals is still scarce. The viral diversity of wildlife may be best described with discovery-driven approaches to the study of viral diversity that broaden research efforts towards non-canonical hosts and remote geographic regions. Birds have been key organisms in the transmission of viruses causing important diseases, and wild birds are threatened by viral spillovers associated with human activities. However, our knowledge of the avian virome may be biased towards poultry and highly pathogenic diseases. We describe and compare the fecal virome of two passerine-dominated bird assemblages sampled in a remote Neotropical rainforest in French Guiana (Nouragues Natural Reserve) and a Mediterranean forest in central Spain (La Herrería). We used metagenomic data to quantify the degree of functional and genetic novelty of viruses recovered by examining if the similarity of the contigs we obtained to reference sequences differed between both locations. In general, contigs from Nouragues were significantly less similar to viruses in databases than contigs from La Herrería using Blastn but not for Blastx, suggesting that pristine regions harbor a yet unknown viral diversity with genetically more singular viruses than more studied areas. Additionally, we describe putative novel viruses of the families Picornaviridae, Reoviridae and Hepeviridae. These results highlight the importance of wild animals and remote regions as sources of novel viruses that substantially broaden the current knowledge of the global diversity of viruses.

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39

Fisch, Harry, and Erik T. Goluboff. "Geographic variations in sperm counts: a potential cause of bias in studies of semen quality." Fertility and Sterility 65, no. 5 (May 1996): 1044–46. http://dx.doi.org/10.1016/s0015-0282(16)58284-3.

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40

Zhang, Guiming, and A‐Xing Zhu. "Sample size and spatial configuration of volunteered geographic information affect effectiveness of spatial bias mitigation." Transactions in GIS 24, no. 5 (August 17, 2020): 1315–40. http://dx.doi.org/10.1111/tgis.12679.

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41

Barnes, Matthew A., Christopher L. Jerde, Marion E. Wittmann, W. Lindsay Chadderton, Jianqing Ding, Jialiang Zhang, Matthew Purcell, Milan Budhathoki, and David M. Lodge. "Geographic selection bias of occurrence data influences transferability of invasive H ydrilla verticillata distribution models." Ecology and Evolution 4, no. 12 (May 26, 2014): 2584–93. http://dx.doi.org/10.1002/ece3.1120.

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42

Roberts, Beth E. I., W. Edwin Harris, Geoff M. Hilton, and Stuart J. Marsden. "Taxonomic and Geographic Bias in Conservation Biology Research: A Systematic Review of Wildfowl Demography Studies." PLOS ONE 11, no. 5 (May 11, 2016): e0153908. http://dx.doi.org/10.1371/journal.pone.0153908.

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43

Kerminen, Sini, Alicia R. Martin, Jukka Koskela, Sanni E. Ruotsalainen, Aki S. Havulinna, Ida Surakka, Aarno Palotie, et al. "Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland." American Journal of Human Genetics 104, no. 6 (June 2019): 1169–81. http://dx.doi.org/10.1016/j.ajhg.2019.05.001.

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Fenollosa, Erola, Laia Jené, and Sergi Munné-Bosch. "Geographic patterns of seed trait variation in an invasive species: how much can close populations differ?" Oecologia 196, no. 3 (July 2021): 747–61. http://dx.doi.org/10.1007/s00442-021-04971-2.

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AbstractSeeds play a major role in plant species persistence and expansion, and therefore they are essential when modeling species dynamics. However, homogeneity in seed traits is generally assumed, underestimating intraspecific trait variability across the geographic space, which might bias species success models. The aim of this study was to evaluate the existence and consequences of interpopulation variability in seed traits of the invasive species Carpobrotus edulis at different geographical scales. We measured seed production, morphology, vigour and longevity of nine populations of C. edulis along the Catalan coast (NE Spain) from three differentiated zones with a human presence gradient. Geographic distances between populations were contrasted against individual and multivariate trait distances to explore trait variation along the territory, evaluating the role of bioclimatic variables and human density of the different zones. The analysis revealed high interpopulation variability that was not explained by geographic distance, as regardless of the little distance between some populations (< 0.5 km), significant differences were found in several seed traits. Seed production, germination, and persistence traits showed the strongest spatial variability up to 6000% of percent trait variability between populations, leading to differentiated C. edulis soil seed bank dynamics at small distances, which may demand differentiated strategies for a cost-effective species management. Seed trait variability was influenced by human density but also bioclimatic conditions, suggesting a potential impact of increased anthropogenic pressure and climate shifts. Geographic interpopulation trait variation should be included in ecological models and will be important for assessing species responses to environmental heterogeneity and change.

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Rettie, W. James, and Philip D. McLoughlin. "Overcoming radiotelemetry bias in habitat-selection studies." Canadian Journal of Zoology 77, no. 8 (November 1, 1999): 1175–84. http://dx.doi.org/10.1139/z99-079.

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For many species, determination of habitat selection is based on habitat-use data obtained through radiotelemetry. Recent papers pertaining to study techniques have largely ignored the effect of habitat-dependent bias in the performance of radiotelemetry systems. Such biases cannot be overcome by increasing radiotelemetry precision, excluding data, or increasing sample sizes, as the biases are centred around data that are missing or that contain habitat-dependent errors in location. The problem is best addressed at the data-analysis stage through the use of geographic information systems. We used Monte Carlo simulations to assess the effect of habitat-dependent bias in radiotelemetry studies on the assessment of habitat selection. We looked at the effects of habitat-patch size, level of telemetry signal inhibition, level of habitat co-occurrence, and selection pattern. We demonstrated that regarding use as the composition of habitat types within a circular area around each telemetry location can help to overcome the inaccurate assessment of habitat-selection patterns that biased data produce. The size of the circular area best able to overcome the bias is related to habitat patch size and to the level of association between two or more habitat types. Furthermore, we argue that the characteristics of habitat mosaics selected by animals can and should be studied in this way.

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Zhang, Xiaping, and Qun Yang. "Association between serum copper levels and lung cancer risk: A meta-analysis." Journal of International Medical Research 46, no. 12 (October 8, 2018): 4863–73. http://dx.doi.org/10.1177/0300060518798507.

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Objective To evaluate the association between serum copper levels and lung cancer risk. Methods We searched the electronic PubMed, WanFang, CNKI, and SinoMed databases to identify studies including information on serum copper levels and lung cancer. Standard mean differences and corresponding 95% confidence intervals were calculated using Stata 12.0 software. We performed a meta-analysis on the identified studies overall and according to geographic location. We also evaluated heterogeneity among the studies and the occurrence of publication bias. Results Thirty-three articles including 3026 cases and 9439 controls were included in our study. The combined results showed that serum copper levels were higher in patients with lung cancer compared with controls without lung cancer, though the results showed high heterogeneity. In a subgroup analysis according to geographic location, significant associations between copper levels and lung cancer were found for both Asian and European populations. No publication bias was detected in this meta-analysis. Conclusions High serum copper levels could increase the risk of lung cancer, suggesting that environmental copper exposure may be a risk factor for the development of lung cancer.

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Kalkauskas, Antanas, Umberto Perron, Yuxuan Sun, Nick Goldman, Guy Baele, Stephane Guindon, and Nicola De Maio. "Sampling bias and model choice in continuous phylogeography: Getting lost on a random walk." PLOS Computational Biology 17, no. 1 (January 6, 2021): e1008561. http://dx.doi.org/10.1371/journal.pcbi.1008561.

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Phylogeographic inference allows reconstruction of past geographical spread of pathogens or living organisms by integrating genetic and geographic data. A popular model in continuous phylogeography—with location data provided in the form of latitude and longitude coordinates—describes spread as a Brownian motion (Brownian Motion Phylogeography, BMP) in continuous space and time, akin to similar models of continuous trait evolution. Here, we show that reconstructions using this model can be strongly affected by sampling biases, such as the lack of sampling from certain areas. As an attempt to reduce the effects of sampling bias on BMP, we consider the addition of sequence-free samples from under-sampled areas. While this approach alleviates the effects of sampling bias, in most scenarios this will not be a viable option due to the need for prior knowledge of an outbreak’s spatial distribution. We therefore consider an alternative model, the spatial Λ-Fleming-Viot process (ΛFV), which has recently gained popularity in population genetics. Despite the ΛFV’s robustness to sampling biases, we find that the different assumptions of the ΛFV and BMP models result in different applicabilities, with the ΛFV being more appropriate for scenarios of endemic spread, and BMP being more appropriate for recent outbreaks or colonizations.

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Griffith, Daniel A., Yongwan Chun, and Monghyeon Lee. "Deeper Spatial Statistical Insights into Small Geographic Area Data Uncertainty." International Journal of Environmental Research and Public Health 18, no. 1 (December 30, 2020): 231. http://dx.doi.org/10.3390/ijerph18010231.

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Small areas refer to small geographic areas, a more literal meaning of the phrase, as well as small domains (e.g., small sub-populations), a more figurative meaning of the phrase. With post-stratification, even with big data, either case can encounter the problem of small local sample sizes, which tend to inflate local uncertainty and undermine otherwise sound statistical analyses. This condition is the opposite of that afflicting statistical significance in the context of big data. These two definitions can also occur jointly, such as during the standardization of data: small geographic units may contain small populations, which in turn have small counts in various age cohorts. Accordingly, big spatial data can become not-so-big spatial data after post-stratification by geography and, for example, by age cohorts. This situation can be ameliorated to some degree by the large volume of and high velocity of big spatial data. However, the variety of any big spatial data may well exacerbate this situation, compromising veracity in terms of bias, noise, and abnormalities in these data. The purpose of this paper is to establish deeper insights into big spatial data with regard to their uncertainty through one of the hallmarks of georeferenced data, namely spatial autocorrelation, coupled with small geographic areas. Impacts of interest concern the nature, degree, and mixture of spatial autocorrelation. The cancer data employed (from Florida for 2001–2010) represent a data category that is beginning to enter the realm of big spatial data; its volume, velocity, and variety are increasing through the widespread use of digital medical records.

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Özdoğan, Mehmet. "Amidst Mesopotamia-centric and Euro-centric approaches: the changing role of the Anatolian peninsula between the East and the West." Anatolian Studies 57 (December 2007): 17–24. http://dx.doi.org/10.1017/s0066154600008462.

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AbstractDue to its geographical position, the Anatolian plateau has always been considered as a bridge in transmitting cultural formations that originated in the Near East to southeastern Europe and to the Aegean. Such a standpoint downgrades the role played by the Anatolian plateau to a transit route between the East and the West, overlooking its distinct structure. It seems that the main bias is in considering the Anatolian plateau as a single cultural unit, ignoring the multifarious nature of its structure. The role the Anatolian plateau played between the ‘East’ and the ‘West’ was much more complex and multi-facetted than assumed, even at times hampering all interaction. Yet another bias is considering Anatolia, in spite of its geographic extent, as the dividing line in defining the boundary between the East and the West. However, it is evident that the geographic limits of the peninsula do not necessarily correspond with the cultural entities. Thus, for example, while the cultural boundary separating the East and the West was somewhere in between the Aegean littoral and the central plateau during the Neolithic period, later it shifted considerably in both directions. On the other hand, through the earlier part of the Chalcolithic period, the extent of the Taurus mountains marks the dividing line between the Near Eastern and Anatolia-Balkan cultural formative zones, which by the Late Chalcolithic period moved much further to the west, up to the Marmara region, the Sea of Marmara then acting as a cultural barrier. Presented here is a conspectus of the recent picture on changing cultural boundaries through the Neolithic to the Early Bronze Age.

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Feyrer, James. "Trade and Income—Exploiting Time Series in Geography." American Economic Journal: Applied Economics 11, no. 4 (October 1, 2019): 1–35. http://dx.doi.org/10.1257/app.20170616.

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Establishing a robust causal relationship between trade and income has been difficult. Frankel and Romer (1999) uses a geographic instrument to identify a positive effect of trade on income. Rodriguez and Rodrik (2001) shows that these results are not robust to controlling for omitted variables such as distance to the equator or institutions. This paper solves the omitted variable problem by generating a time-varying geographic instrument. Improvements in aircraft technology have caused the quantity of world trade carried by air to increase over time. Country pairs with relatively short air routes compared to sea routes benefit more from this change in technology. This heterogeneity can be used to generate a geography-based instrument for trade that varies over time. The time-series variation allows for controls for country fixed effects, eliminating the bias from time-invariant variables such as distance from the equator or historically determined institutions. Trade has a significant effect on income with an elasticity of roughly one-half. Differences in predicted trade growth can explain roughly 17 percent of the variation in cross-country income growth between 1960 and 1995. (JEL F14, F43, L93)

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