Bar-tailed Godwits Limosa lapponica in Alaska: revisiting population estimates from the staging grounds

Wader Study ◽  
2021 ◽  
Vol 128 (3) ◽  
Author(s):  
Daniel R. Ruthrauff ◽  
Zachary M. Pohlen ◽  
Heather M. Wilson ◽  
James A. Johnson
Keyword(s):  
Population Estimates

Net migration estimates for Greece by age, sex and citizenship, 1991-2001

2008 ◽  
Vol 5 (2) ◽  
pp. 189-202
Author(s):  
Cleon Tsimbos
Keyword(s):  
Reproductive Age ◽  
Population Estimates ◽  
Demographic Analysis ◽  
Resident Population ◽  
Net Migration ◽  
Intercensal Period ◽  
Working Age ◽  
Official Data ◽  
Migration Component ◽  
Of Greece

This paper applies techniques of demographic analysis to official data of Greece to obtain net migration estimates by age, sex and citizenship for the intercensal period 1991-2001. It is found that the overall net immigration rate for the decade is 6.3 per 100 resident population and the contribution of foreign immigrants to this figure is 88.2 per cent. 85.4 % of the net immigrants are of working age and 70.3 % of net immigrant women are of reproductive age. The results of the study can be used to formulate assumptions regarding the migration component when handling population estimates and projections.

DNA Is Not Destiny

2018 ◽  
Author(s):  
Rose McDermott ◽  
Peter K. Hatemi
Keyword(s):  
Social Context ◽  
Dna Sequence ◽  
Social Factors ◽  
Personal Experience ◽  
Human Agency ◽  
Social Behaviors ◽  
Genetic Influences ◽  
Population Estimates ◽  
Qualitative Investigation ◽  
Individual Accountability

Genetic influences are often misinterpreted to mean that an individual with a particular genotype is inevitably predisposed to engage in a given behavior or that genetic influences operate outside of human agency and social context. This chapter undertakes a qualitative investigation of a genetically informed (MAOA) sample to illustrate the critical differences between population estimates and individual accountability. The sample includes those whose lives have revolved around violence (e.g., gang members) and those whose lives are committed to peace (e.g., Buddhist monks). It is found that genotype alone cannot predict any one individual’s social behaviors, and it is argued that any decisions or legal precedents targeted toward predicting how a specific individual may act based on his or her DNA sequence require a more nuanced appreciation of how social factors, genetic dispositions, and personal experience intertwine in the context of human agency.

scholarly journals Population estimates of Antillean manatees in Puerto Rico: an analytical framework for aerial surveys using multi-pass removal sampling

2019 ◽  
Vol 100 (4) ◽  
pp. 1340-1349
Author(s):  
Jaime A Collazo ◽  
Matthew J Krachey ◽  
Kenneth H Pollock ◽  
Francisco J Pérez-Aguilo ◽  
Jan P Zegarra ◽  
...  
Keyword(s):  
Puerto Rico ◽  
Detection Probability ◽  
Analytical Framework ◽  
Population Estimates ◽  
High Concentration ◽  
Imperfect Detection ◽  
Factors Affecting ◽  
Management Actions ◽  
Aerial Surveys ◽  
Population Size Estimates

AbstractEffective management of the threatened Antillean manatee (Trichechus manatus manatus) in Puerto Rico requires reliable estimates of population size. Estimates are needed to assess population responses to management actions, and whether recovery objectives have been met. Aerial surveys have been conducted since 1976, but none adjusted for imperfect detection. We summarize surveys since 1976, report on current distribution, and provide population estimates after accounting for apparent detection probability for surveys between June 2010 and March 2014. Estimates in areas of high concentration (hotspots) averaged 317 ± 101, three times higher than unadjusted counts (104 ± 0.56). Adjusted estimates in three areas outside hotspots also differed markedly from counts (75 ± 9.89 versus 19.5 ± 3.5). Average minimum island-wide estimate was 386 ± 89, similar to the maximum estimate of 360 suggested in 2005, but fewer than the 700 recently suggested by the Puerto Rico Manatee Conservation Center. Manatees were more widespread than previously understood. Improving estimates, locally or island-wide, will require stratifying the island differently and greater knowledge about factors affecting detection probability. Sharing our protocol with partners in nearby islands (e.g., Cuba, Jamaica, Hispaniola), whose populations share genetic make-up, would contribute to enhanced regional conservation through better population estimates and tracking range expansion.El manejo efectivo del manatí antillano amenazado en Puerto Rico requiere estimados de tamaños de poblaciónes confiables. Dichas estimaciones poblacionales son necesarias para evaluar las respuestas a las acciones de manejo, y para determinar si los objetivos de recuperación han sido alcanzados. Se han realizado censos aéreos desde 1976, pero ninguno de ellos han sido ajustados para detecciones imperfectas. Aquí resumimos los censos desde 1976, actualizamos la distribución, y reportamos los primeros estimados poblacionales ajustados para la probabilidad de detección aparente en los censos de Junio 2010 a Marzo 2014. Las estimaciones poblacionales en áreas de mayor concentración del manatí promedió 317 ± 103, tres veces más abundante que los conteos sin ajuste (104 ± 0.56). Las estimaciones poblacionales en tres áreas fuera de las áreas de mayor concentración del manatí también fueron marcadamente diferentes (75 ± 9.89 vs 19.5 ± 3.5). El estimado mínimo poblacional en la isla entera fue de 386 ± 89, similar al estimado máximo de 360 sugerido en el año 2005, pero menor a los 700 sugeridos recientemente por el Centro de Conservación de Manatíes de Puerto Rico. Documentamos que el manatí tiene una distribución más amplia de lo que se sabía con anterioridad. El mejoramiento de los estimados poblacionales locales o a nivel de isla requerirá que se estratifique a la isla en forma diferente y que se investiguen los factores que influencian a la probabilidad de detección. Compartir protocolos como este con colaboradores de islas vecinas (por. ej., Cuba, Jamaica, Española), cuyas poblaciones de manatíes comparten material genético, contribuiría a la conservación regional mediante mejores estimaciones poblacionales y monitoreo de la expansión de su ámbito doméstico.

scholarly journals How Does Administrative Data Compare with Census Data for the Measurement of Internal Migration? The Case of Northern Ireland, 2001–2011

2021 ◽  
Author(s):  
Brian Foley ◽  
Tony Champion ◽  
Ian Shuttleworth
Keyword(s):  
Administrative Data ◽  
Internal Migration ◽  
Census Data ◽  
Local Population ◽  
Population Data ◽  
Population Estimates ◽  
Demographic Groups ◽  
Small Areas ◽  
Intercensal Period ◽  
Statistical Agencies

AbstractThe paper compares and contrasts internal migration measured by healthcard-based administrative data with census figures. This is useful because the collection of population data, its processing, and its dissemination by statistical agencies is becoming more reliant on administrative data. Statistical agencies already use healthcard data to make migration estimates and are increasingly confident about local population estimates from administrative sources. This analysis goes further than this work as it assesses how far healthcard data can produce reliable data products of the kind to which academics are accustomed. It does this by examining migration events versus transitions over a full intercensal period; population flows into and out of small areas; and the extent to which it produces microdata on migration equivalent to that in the census. It is shown that for most demographic groups and places healthcard data is an adequate substitute for census-based migration counts, the exceptions being for student households and younger people. However, census-like information is still needed to provide covariates for analysis and this will still be required whatever the future of the traditional census.

scholarly journals Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level

2021 ◽  
Vol 10 (6) ◽  
pp. 227
Author(s):  
Yago Martín ◽  
Zhenlong Li ◽  
Yue Ge ◽  
Xiao Huang
Keyword(s):  
Large Scale ◽  
Local Population ◽  
External Validation ◽  
Population Estimates ◽  
County Level ◽  
Internal Validation ◽  
Population Movements ◽  
Dynamic Component ◽  
Home Location ◽  
Non Local

The study of migrations and mobility has historically been severely limited by the absence of reliable data or the temporal sparsity of available data. Using geospatial digital trace data, the study of population movements can be much more precisely and dynamically measured. Our research seeks to develop a near real-time (one-day lag) Twitter census that gives a more temporally granular picture of local and non-local population at the county level. Internal validation reveals over 80% accuracy when compared with users’ self-reported home location. External validation results suggest these stocks correlate with available statistics of residents/non-residents at the county level and can accurately reflect regular (seasonal tourism) and non-regular events such as the Great American Solar Eclipse of 2017. The findings demonstrate that Twitter holds the potential to introduce the dynamic component often lacking in population estimates. This study could potentially benefit various fields such as demography, tourism, emergency management, and public health and create new opportunities for large-scale mobility analyses.

scholarly journals Lessons learned from comparing spatially explicit models and the Partners in Flight approach to estimate population sizes of boreal birds in Alberta, Canada

The Condor ◽  
2020 ◽  
Vol 122 (2) ◽  
Author(s):  
Péter Sólymos ◽  
Judith D Toms ◽  
Steven M Matsuoka ◽  
Steven G Cumming ◽  
Nicole K S Barker ◽  
...  
Keyword(s):  
North America ◽  
Time Of Day ◽  
Lessons Learned ◽  
Population Estimates ◽  
Spatially Explicit ◽  
Species Variation ◽  
Detection Distance ◽  
Spatially Explicit Models ◽  
Population Sizes ◽  
Partners In Flight

Abstract Estimating the population abundance of landbirds is a challenging task complicated by the amount, type, and quality of available data. Avian conservationists have relied on population estimates from Partners in Flight (PIF), which primarily uses roadside data from the North American Breeding Bird Survey (BBS). However, the BBS was not designed to estimate population sizes. Therefore, we set out to compare the PIF approach with spatially explicit models incorporating roadside and off-road point-count surveys. We calculated population estimates for 81 landbird species in Bird Conservation Region 6 in Alberta, Canada, using land cover and climate as predictors. We also developed a framework to evaluate how the differences between the detection distance, time-of-day, roadside count, and habitat representation adjustments explain discrepancies between the 2 estimators. We showed that the key assumptions of the PIF population estimator were commonly violated in this region, and that the 2 approaches provided different population estimates for most species. The average differences between estimators were explained by differences in the detection-distance and time-of-day components, but these adjustments left much unexplained variation among species. Differences in the roadside count and habitat representation components explained most of the among-species variation. The variation caused by these factors was large enough to change the population ranking of the species. The roadside count bias needs serious attention when roadside surveys are used to extrapolate over off-road areas. Habitat representation bias is likely prevalent in regions sparsely and non-representatively sampled by roadside surveys, such as the boreal region of North America, and thus population estimates for these regions need to be treated with caution for certain species. Additional sampling and integrated modeling of available data sources can contribute towards more accurate population estimates for conservation in remote areas of North America.

Historical Population Estimates: Unraveling the Consensus

2002 ◽  
Vol 28 (2) ◽  
pp. 183-204 ◽  
Author(s):  
John C. Caldwell ◽  
Thomas Schindlmayr
Keyword(s):  
Population Estimates
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