Population Estimation Techniques Research Articles

Optimization of an amplicon sequencing‐based microsatellite panel and protocol for stock identification and kinship inference of lake trout (Salvelinus namaycush)

Kinship-based methods of population assessment such as close-kin mark-recapture require accurate and efficient genotyping methods capable of resolving complex relationships among kin. Inference of such relationships can be difficult using biallelic loci due to the large number of markers required to obtain the necessary power. Sequencing-based microsatellite panels offer an efficient alternative, combining high polymorphism with efficient next-generation methods. Here we construct, optimize, and test one such panel for lake trout (Salvelinus namaycush) using a combination of previously-published loci adapted for sequencing and de novo loci mined from a genome assembly. We performed three rounds of primer optimization, yielding a final panel of 131 loci, followed by testing with two different levels of PCR multiplexing (all primers in one or two groups) and two different reaction volumes (5 and 10 μL). Our results showed that the use of the largest multiplex and smallest reaction volume did not substantially change results, allowing significant cost and time savings. To test panel accuracy, we used both a set of 153 known-origin samples from origins of management interest and a series of hatchery crosses representing nine families with parent-offspring, half-sibling, and largely-unrelated pairs. Our results indicate that sequencing-based microsatellite panels can efficiently and accurately provide the information required for a population genetics analyses including population assignment, calculation of between-population F ST, and kinship-based population estimation techniques. Such techniques are seeing increasing applications for a wide range of taxa; our findings should provide insight and guidance for the development of the necessary molecular resources.

Estimating the Population of a Middle Eastern City Based on a Normalized Difference Built-Up Index and Urban Morphology

The aim of this study is to introduce a method for estimating the population of a Middle Eastern city, the city of Hillah, in the absence of a census which was last conducted in 1997. The method incorporates the normalized difference built-up index and land use-land cover information to identify residential areas for four years 1987, 1997 (the last census), 2008, and 2018 using Landsat imagery. Dasymetric mapping is employed to rezone residential pixels to the city's administrative districts or mahallahs. Mahallah populations for each year are estimated using local and historical urban morphology characteristics combined with standardized housing and household sizes. The result of this study is a range of estimates for mahallah populations, but a reasonable estimate of the city of Hillah's population is developed. The use of historical information, urban design, and environmental data with remote sensing methods in a Middle Eastern context provides an added tool in the arsenal of population estimation techniques.

Evaluation of counting methods for monitoring populations of a cryptic alpine passerine, the rock wren (Passeriformes, Acanthisittidae, Xenicus gilviventris).

Developing and validating methods to determine trends in populations of threatened species is essential for evaluating the effectiveness of conservation interventions. For cryptic species inhabiting remote environments, this can be particularly challenging. Rock wrens, Xenicus gilviventris, are small passerines endemic to the alpine zone of southern New Zealand. They are highly vulnerable to predation by introduced mammalian predators. Establishing a robust, cost-effective monitoring tool to evaluate population trends in rock wrens is a priority for conservation of both the species and, more broadly, as part of a suite of indicators for evaluating effectiveness of management in New Zealand's alpine ecosystems. We assessed the relative accuracy and precision of three population estimation techniques (mark-resight, distance sampling and simple counts on line transects) for two populations of rock wrens in the Southern Alps over six breeding seasons (2012-2018). The performance of these population estimators was compared to known rock wren population size derived from simultaneous territory mapping. Indices of abundance derived from counts on transects were correlated with territory mapping at both study areas, and performed better than either mark-resight methods or distance sampling. Simple counts on standardised line transects are a highly cost-effective method of monitoring birds because they do not require banding a population. As such, we recommend that line transect counts using the design outlined in this paper be adopted as a standard method for long-term monitoring of rock wren populations. Although species-specific testing is required to validate use of low-cost population indices, our results may have utility for the monitoring of other cryptic passerines in relatively open habitats.

Error calculation in cross-correlation based population estimation technique of fish and mammals

Error calculation in cross-correlation based population estimation technique of fish and mammals

Estimating Mountain Lion Abundance in Arizona Using Statistical Population Reconstruction

ABSTRACTDirectly monitoring abundance of cryptic species, such as mountain lions (Puma concolor), over large areas is a challenge for wildlife managers because traditional population estimation techniques may be impractical and expensive. We generated annual estimates of mountain lion abundance in Arizona, USA, for 2004–2018 by employing statistical population reconstruction methods, which use available age‐at‐harvest data and auxiliary information such as estimated survival rates, harvest probabilities, and hunter effort. Using PopRecon 2.0 software, we estimated that the statewide abundance of all mountain lions including kittens ranged from 1,848 (95% CI = 650–3,046) to 4,661 (95% CI = 393–9,030) during 2004–2018. Abundance for subadults and adults was more stable and precisely estimated, ranging from 1,166 (95% CI = 622–1,709) to 1,715 (95% CI = 872–2,558). Our results suggest a stable statewide mountain lion population. This approach provides a practical and cost‐effective option for monitoring Arizona's mountain lion population, and will improve the ability of managers to monitor the population annually to respond to changes in abundance and to evaluate factors that influence mountain lion abundance. © 2019 The Authors. Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

Impact of underwater bandwidth and SNR on cross-correlation-based population estimation technique of fish and mammals

Impact of underwater bandwidth and SNR on cross-correlation-based population estimation technique of fish and mammals

A comparison of population estimation techniques for individually unidentifiable free-roaming dogs

BackgroundMeasuring the size of free roaming dog populations quickly and accurately is critical in the implementation of numerous preventive health and population control interventions. However, few studies have investigated the relative performance of population size assessment tools when applied to dogs. The aim of this study was to compare the commonly used mark-resight methodology with distance sampling methods, which are less resource intensive, to estimate free-roaming dog abundance in Goa, India.Twenty-six working zones were surveyed along all roads twice by the same surveyor at the same time of day, following a vaccination campaign which included marking of vaccinated dogs with a coloured paint. The Chapman estimate was then used to evaluate the mark-resight abundance. Additionally, the number of dogs and perpendicular distance from the road for all dogs sighted was recorded. This was used to estimate dog density and abundance using distance sampling methods. The detection function was fitted based on goodness-of-fit and AIC.ResultsThe Chapman abundance estimate for the entire study area was 5202 dogs (95%CI 4733.8–5671.0), and the distance sampling method abundance estimate was 5067 dogs (95%CI 4454.3–5764.2). For individual working zones, after taking other factors into account in a mixed effects model, the average distance sampling estimate was 35% higher (95%CI 20–53%) than the Chapman estimate. There was also evidence of a difference in estimates between surveyors of 21% (95%CI 7–37%) and between days (22% lower on day 2, 95%CI 8–38%) for individual working zones.ConclusionOur study demonstrated that the distance sampling estimates were comparable overall to the Chapman method of abundance estimation of free roaming dogs across the entire study region but there was noticeable variation between the two methods when individual zones were compared. Consequently, distance sampling methods may be suitable to enumerate dogs over large areas in a more time efficient manner than the widely used mark-resight approach.

No landward movement: examining 80 years of population migration and shoreline change in Louisiana

Louisiana lost nearly 5,000 km2 of its coastal land area due to relative sea level rise (including local, regional, and global factors driving relative sea level change) since 1932, mirroring both the hazards associated with sea level rise and the time horizons of sea level rise impacts expected this century. This represents an opportunity to examine the relationship between long-term population changes and shoreline change. Based on detailed land change data for the period 1932–2010 and a small area population estimation technique for the period 1940–2010, we examine intra-parish population changes in relation to shoreline changes for the one million plus residents living in the ten coastal parishes of Louisiana. We find that since 1940, only two of the ten coastal parishes exhibited landward population movement, which we define as movement perpendicular to the shoreline, exceeding 1 km. Three parishes exhibited seaward population movement in excess of 1 km. Overall, we find very little net intra-parish landward population movement for the region. Our findings suggest that coastal Louisiana’s historical population has not moved in concert with observed shoreline encroachment. We also find a potential tipping point related to population migration when a neighborhood loses at least 50% of its land area. Our findings suggest that this lack of landward population movement could be attributable to either localized adaptation strategies or migrations to other landward areas.

Redistribution population data across a regular spatial grid according to buildings characteristics

Abstract Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory.

A Comparison of Small-Area Population Estimation Techniques Using Built-Area and Height Data, Riyadh, Saudi Arabia

Small-area population estimation is important for many applications. This paper explores the usefulness of Landsat ${\bf ETM} + $ data, remotely sensed height data, census population, and dwelling unit data to provide small-area population estimates. Riyadh, Saudi Arabia was selected as a suitable area to test a set of methods for population downscaling. Two broad approaches were applied: 1) statistical modeling and 2) areal interpolation. With regard to statistical modeling, regression through the origin was used to model the relationship between density of dwelling units and built area proportion at the block level and the coefficients were used to downscale the density of dwelling units to the parcel level. Areal interpolation with ancillary data (dasymetric mapping) used the block and parcel levels as the source and target zones, respectively. The population distribution was then estimated based on the average population per dwelling unit. Eight models were developed and tested. A conventional regression model, using only built area as a covariate, was used as a benchmark and compared with the more sophisticated models. Remotely sensed height data were used to: 1) create number of floors; 2) classify the built area into different categories; and 3) increase the user’s accuracy of the built area. It was found that remotely sensed height data were useful to explain the variation in the dependent variable across the selected study area. Dasymetric mapping was applied in order to provide a comparison, while acknowledging that the method uses population data not available in the regression approach.

Population size, growth and movements of Anguilla australis in a small lake.

To study growth rates, movements and estimate population size of shortfin eels Anguilla australis in a small lake (2·5 ha) near Christchurch, New Zealand, 617 A. australis were tagged with PIT tags. Tag retention was high (95%) and over the seven recapture events spread over 2 years, 55% of tagged A. australis were recaptured. Growth of recaptured A. australis averaged 13·1 mm year(-1) and declined slightly with increasing total length. Distance moved from original capture site increased with increasing time at large. Population estimates of A. australis > 400 mm (susceptible to capture by fyke net) from recaptures of individuals averaged 1451 A. australis, with a biomass of 170 kg ha(-1) . An average of 6·6% of the estimated total population matured as male silver A. australis each year. Results from radio-tracking of four A. australis gave an average nightly foraging area of 2780 m(2) , and there was no apparent preference for inshore movement (within 5-6 m of the shoreline) or offshore movement. Fyke-net efficiency (total catch relative to the estimated total population available to each net) measured over four consecutive nights fishing was 88%. The lack of precision of the shoreline triangulation system used, ±10 m, meant that the positional data were considered too coarse to be used in a proposed novel population estimation technique based on determining population size within foraging areas.

Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem

Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model MH), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final estimate and demonstrates why each is necessary.

Residential-Source Emission Inventory for the Niger Delta - A Methodological Approach

This paper describes the methods applied to construct a GIS-based emission inventory infrastructure for specific air pollutants and greenhouse gases released from domestic cooking and lighting in the Niger Delta using publicly accessible data. The purpose is to identify and enhance knowledge of existing data gaps in order to progress the development of appropriate mechanisms to collect data in formats required for more accurate emission estimation. The major data gaps identified, which are demographic, activity-based, emission factors and spatial distribution of sources, are consistent across the majority of developing countries. Consequently, the methodological approach focuses on the use of a series of assumptions, emission factors from regions similar to the Niger Delta, and population estimation techniques to generate input data to support the limited publicly available government and research-based data. Developing countries with similar data limitations will benefit from the transferrable methodology. The infrastructure, which is constructed at 10 km-grid resolutions, produced total emission estimates of 70 kt/yr CO, 50 kt/yr NOx, 3 kt/yr PM10, 2.4 kt/yr SO2, 60 t/yr VOC, 5.7 mt/yr CO2 and 2 kt/yr CH4. Domestic lighting using generators and domestic cooking using firewood and kerosene constitute sources of significant emissions of air pollutants in the region. Due to the limited accuracy and completeness of currently available data, the estimates generated have high uncertainties.

Comparison of the first-year response of beaked and sperm whale populations to the Northern Gulf oil spill based on passive acoustic monitoring

This paper continues a discussion on using passive acoustic methods to study the environmental impact of the recent oil spill in the Northern Gulf of Mexico on resident populations of marine mammals. The Littoral Acoustic Demonstration Center, possessing several broadband acoustic datasets collected near the spill site before and after the event, is in a unique position for monitoring long-term environmental impacts in the vicinity of the incident The pre-spill recordings provide a baseline which, when combined with post-spill measurements, give important indicators of changes in the local populations. Ackleh et al., J. Acoust. Soc. Am. 131, 2306-2314, provide a comparison of 2007 and 2010 measurements showing a decrease in acoustic activity and abundance of sperm whales at the 9-mile distant site, whereas acoustic activity and abundance at the 25-mile distantsite has clearly increased. This may indicate that some sperm whales have relocated farther away from the spill subject to food source availability. This paper reports on applying developed population estimation techniques to monitor beaked whale response that appears to be different from that of sperm whales. Follow-up experiments will be critical for understanding the long-term impact on different species. [Research supported by SPAWAR, NSF, and Greenpeace.]

Comparative woodland caribou population surveys in Slate Islands Provincial Park, Ontario

We evaluated three methods of estimating population size of woodland caribou (boreal ecotype) on the Slate Islands in northern Ontario. Located on the north shore of Lake Superior, the Slate Islands provide a protected and closed population with very limited predator influence that is ideal for a comparison of survey methods. Our objective was to determine the costs and benefits of three population estimation techniques: (1) forward looking infrared (FLIR) technology to count the number of caribou on regular-spaced transects flown by fixed-wing aircraft; (2) observers to count the number of caribou seen or heard while walking random transects in the spring; and, (3) mark-recapture sampling of caribou pellets using DNA analysis. FLIR and the genetics 3-window approach gave much tighter confidence intervals but similar population estimates were found from all three techniques based on their overlapping confidence intervals. There are various costs and benefits to each technique that are discussed further. Understanding the costs and benefits of different population estimation techniques is necessary to develop cost-effective programs for inventorying and monitoring this threatened species not only on the Slate Islands but for other populations as well.

Practical field ecology: a project guide

Tables. Figures. Boxes. Case Studies. Preface. Acknowledgements. 1 Preparation. Choosing a topic for study. Ecological research questions. Monitoring individual species and groups of species. Monitoring species richness. Monitoring population sizes and density. Monitoring community structure. Monitoring behaviour. A note of caution. Creating aims, objectives and hypotheses. Reviewing the literature. Primary literature. Secondary literature. Other sources of information. Search terms. Reading papers. Practical considerations. Legal aspects. Health and safety issues. Implementation. Time management. Project design and data management. Designing and setting up experiments and surveys. Types of data. Sampling designs. Planning statistical analysis. Choosing sampling methods. Summary. 2 Monitoring site characteristics. Site selection. Site characterisation. Habitat mapping. Examination of landscape scale. Measuring microclimatic variables. Monitoring substrates. Monitoring water. Other physical attributes. Measuring biological attributes. Identification. 3 Sampling static organisms. Sampling techniques for static organisms. Quadrat sampling. Pin-frames. Transects. Distribution of static organisms. Forestry techniques. 4 Sampling mobile organisms. General issues. Distribution of mobile organisms. Direct observation. Behaviour. Indirect methods. Capture techniques. Marking individuals. Radio-tracking. Invertebrates. Direct observation. Indirect methods. Capture techniques. Marking individuals. Capturing aquatic invertebrates. Netting. Suction sampling. Benthic coring. Drags, dredges and grabs. Wet extraction. Artificial substrate samplers. Baited traps. Capturing soil-living invertebrates. Dry sieving. Floatation and phase-separation. Tullgren funnels as a method of dry extraction. Chemical extraction. Electrical extraction. Capturing ground-active invertebrates. Pitfall traps. Suction samplers. Emergence traps. Capturing invertebrates from plants. Pootering. Sweep netting. Beating. Fogging. Capturing airborne invertebrates. Sticky traps. Using attractants. Refuges. Flight interception (window and malaise) traps. Light traps. Rotary traps. Water traps. Fish. Direct observation. Indirect methods. Capture techniques. Marking individuals. Amphibians. Direct observation. Indirect methods. Capture techniques. Marking individuals. Reptiles. Direct observation. Indirect methods. Capture techniques. Marking individuals. Birds. Direct observation. Indirect methods. Capture techniques. Marking individuals. Mammals. Direct observation. Indirect methods. Capture techniques. Marking individuals. 5 Analysing and interpreting information. Keys to tests. Exploring and describing data. Transforming and screening data. Spatial and temporal distributions. Population estimation techniques: densities and population sizes. Richness and diversity. Similarity, dissimilarity and distance coefficients. Recording descriptive statistics. Testing hypotheses using basic statistical tests and simple general linear models. Differences between samples. Relationships between variables. Associations between frequency distributions. More advanced general linear models for predictive analysis. Multiple regression. Analysis of covariance and multivariate analysis of variance. Discriminant function analysis. Generalized linear models. Extensions of the generalized linear model. Statistical methods to examine pattern and structure in communities: classification, indicator species and ordination. Classification. Indicator species analysis. Ordination. 6 Presenting the information. Structure. Title. Abstract. Acknowledgements. Contents. Introduction. Methods. Results. Discussion. References. Appendices. Writing style. Tense. Numbers. Abbreviations. Punctuation. Choice of font. Common mistakes. Computer files. Summary. References. Appendix 1 Glossary of statistical terms. Index.

Testing the effectiveness of capture mark recapture population estimation techniques using a computer simulation with known population size

Estimation of small mammal population sizes is important for monitoring ecosystem condition and for conservation. Here, we test the accuracy of standard methods of population size estimation using Capture-Mark-Recapture (CMR) on a simulated population of agents. The use of a computer simulation allows complete control of population sizes and behaviors, thereby avoiding assumptions that may be violated in real populations. We find that the recommended protocol for CMR sampling, using uniformly distributed traps, consistently overestimates population sizes by as much as 100% when studies are conducted over only two trapping periods. More than 20 trapping periods are required before this method, or that of placing traps randomly, gives an accurate estimation of population size (i.e., within a 95% confidence limit of the actual value). Non-random sampling, by placing traps on runways used by small mammals, produces the most accurate, and least variable, estimates of population. However, we show that around 10 trapping periods are still required to produce an accurate population estimate using this method. Given that most real populations do not comply with the ‘ideal’ assumptions made by CMR, we suggest that population estimates based on CMR may be fundamentally flawed, and recommend that protocols for CMR population estimation methods may need revising.

Population Estimation Techniques for Lekking Species

With the decline of many lekking species, the need to develop a rigorous population estimation technique is critical for successful conservation and management. We employed mark–resight methods to estimate population size for 2 lekking species: greater sage-grouse (Centrocercus urophasianus) and Gunnison sage-grouse (Centrocercus minimus). We evaluated 2 different estimators: Bowden's estimator and the mixed logit-normal mark–resight model. We captured and marked 75 greater sage-grouse. We counted marked and unmarked birds as they attended 15 known leks. We used 36 and 37 marked Gunnison sage-grouse to estimate population size in 2003 and 2004, respectively. We observed marked and unmarked Gunnison sage-grouse daily as they attended 6 leks in 2003 and 3 leks in 2004. Based on our examination of the assumptions of each mark–resight estimator, relative to behavior and biology of these species, we concluded the mixed logit-normal mark–resight model is preferred. We recommend wildlife managers employ mark–resight approaches when statistically rigorous population estimates are required for management and conservation of lekking species.

Population Estimation Techniques for Lekking Species

Abstract: With the decline of many lekking species, the need to develop a rigorous population estimation technique is critical for successful conservation and management. We employed mark—resight methods to estimate population size for 2 lekking species: greater sage‐grouse (Centrocercus urophasianus) and Gunnison sage‐grouse (Centrocercus minimus). We evaluated 2 different estimators: Bowden's estimator and the mixed logit‐normal mark—resight model. We captured and marked 75 greater sage‐grouse. We counted marked and unmarked birds as they attended 15 known leks. We used 36 and 37 marked Gunnison sage‐grouse to estimate population size in 2003 and 2004, respectively. We observed marked and unmarked Gunnison sage‐grouse daily as they attended 6 leks in 2003 and 3 leks in 2004. Based on our examination of the assumptions of each mark—resight estimator, relative to behavior and biology of these species, we concluded the mixed logit‐normal mark—resight model is preferred. We recommend wildlife managers employ mark—resight approaches when statistically rigorous population estimates are required for management and conservation of lekking species.

Practical Approaches to Spatial Estimation of Disaster-Affected Populations

When a disaster occurs, the response depends critically on an estimate of the affected population. However, retrieval of crucial statistics can be time consuming, often at the expense of the neediest populations. This article reviews spatial population estimation techniques and datasets that facilitate disaster response and management. The authors conclude that the LandScan population distribution estimates best suit the needs of Population Explorer, an Internet GIS that presents a way to quickly deliver answers to queries about local population and demographic composition to users who may not be formally trained in GIS or demography. By referencing LandScan population distributions, Population Explorer retrieves adjusted, official census population counts, for user-defined point buffers, line buffers, or polygons on a global map. Participants from a variety of agencies, i.e., government and non-government, local and international, can collaborate in updating baseline population estimates with local information that can then be queried with the baseline counts.