Estimating the size of criminal populations

The North Cascades (Nooksack) elk (Cervus elaphus) population declined during the 1980s, prompting a closure to state and tribal hunting in 1997 and an effort to restore the herd to former abundance. In 2005, we began a study to assess the size of the elk population, judge the effectiveness of restoration efforts, and develop a practical monitoring strategy. We concurrently evaluated 2 monitoring approaches: sightability correction modeling and mark‐resight modeling. We collected data during February–April helicopter surveys and fit logistic regression models to predict the sightability of elk groups based on group and environmental variables. We used an information‐theoretic criterion to compare 9 models of varying complexity; the best model predicted sightability of elk groups based on 1) transformed (log2) group size, 2) forest canopy cover (%), and 3) a categorical activity variable (active vs. bedded). The sightability model indicated relatively steady and modest herd growth during 2006–2011, but estimates were less than minimum‐known‐alive counts. We also used the logit‐normal mixed effects (LNME) mark‐resight model to generate estimates of total elk population size and the sizes of the adult female and branch‐antlered male subpopulations. We explored 15 LNME models to predict total population size and 12 models to predict subpopulations. Our results indicated individual heterogeneity in resighting probabilities and variation in resighting probabilities across sexes and some years. Model‐averaged estimates of total population size increased from 639 (95% CI = 570–706) in spring 2006 to 1,248 (95% CI = 1,094–1,401) in 2011. We estimated the adult female subpopulation increased from 381 (95% CI = 338–424) in spring 2006 to 573 (95% CI = 507–639) by 2011. The branch‐antlered male subpopulation estimates increased from 87 (95% CI = 54–119) to 180 (95% CI = 118–241) from spring 2006 to spring 2011. The LNME model estimates were greater than sightability model estimates and minimum‐known‐alive counts. We concluded that mark‐resight performed better and was a viable approach for monitoring this small elk population and possibly others with similar characteristics (i.e., small population and landscape scales), but this approach requires periodic marking of elk; we estimated mark‐resight costs would be about 40% greater than sightability model application costs. The utility of sightability‐correction modeling was limited by a high proportion of groups with low detectability on our densely forested landscape. © 2012 The Wildlife Society.

Counts of reproductive units, i.e. family groups, constitute the main monitoring index for lynxLynx lynxpopulations in Scandinavia. However, for some purposes it is necessary to extrapolate from the number of family groups to obtain an estimate of total population size. Using data on survival and reproduction from radio‐marked lynx from three Scandinavian study areas, we simulated the lynx population structure in February. The average proportions of family groups out of all independent individuals, i.e. adults and yearlings, in these simulations were 21% ± 2.1 (SD), 22% ± 3.6 and 27% ±3.1 for the data sets from northern Sweden (Sarek), southeastern Norway (Hedmark) and south‐central Sweden (Bergslagen), respectively, and the overall mean for all three study areas was 23% ± 3.8. This translated into extrapolation factors of 6.14 ± 0.44,6.24 ± 0.73 and 5.48 ± 0.40 for the three study areas, respectively, leading to an overall mean for all three study areas of 5.95 ± 0.64. We conclude, that it is possible to extrapolate from the number of family groups to obtain an estimate of total lynx population size with a statistical measure of uncertainty.

We introduce new estimates of the size of the Eight Banner populations. Published estimates of the size of the population of the banners vary widely because of inconsistencies in the numbers reported in different original sources, and differences in the assumptions used to translated these numbers into estimates of total population size. For example, estimates of banner forces at the time of the Qing conquest vary from 60,000 to 350,000, with most clustered around 100,000-150,000. These typically multiply the numbers reported for the numbers in the banners by a scaling factor which includes an estimate of the number of household dependents. Assumptions about the scaling factor vary widely. We take a different approach used routinely by demographers to produce indirect estimates of total population size from fragmentary evidence on the numbers in specific age groups. We multiply numbers of adult males (ding) by ethnic banner reported for 1648, 1720, 1721, and 1723 in archival documents by a scaling factor that includes other age groups derived from stable population theory. In this approach, the choice of scaling factor only requires an assumption about mortality levels and the population growth rate. We produce a range of estimates of total population size based on different plausible assumptions about the life expectancy and population growth rate. We conclude that at the time of the conquest, the Eight Banner population at large was between 1.3 and 2.4 million people, and that seventy years later it had grown to between 2.6 and 4.8 million. Population in the Manchu banners in the middle seventeenth century was somewhere between 206,000 and 390,000, growing by 1720 to between 577,000 and 1.08 million.

The ability to estimate the size of populations is an integral part of species conservation. I investigated the utility of counts of calling males for the rapid and efficient assessment of population size in the endangered frogs Geocrinia alba and G. vitellina from southwestern Australia. Multiple censuses were used to examine the optimum time of night and season to conduct surveys. Turnover of calling males was measured using removal and mark-recapture studies. Males called persistently throughout the night, but the time of the annual peak in the number of calling males varied among sites. Turnover of males was very low, with the majority of males in each population (76-96%) calling simultaneously. Combining knowl- edge of the sex ratio with counts of calling males, it is therefore possible to obtain a good estimate of total population size.

Guanacos (Lama guanicoe) are thought to have declined in Patagonia mainly as a result of hunting and sheep ranching. Currently accepted estimates of total population size are extrapolated from densities obtained through strip transects in local studies. We used road surveys (8,141 km) and distance sampling to estimate guanaco density and population size over major environmental gradients of Santa Cruz, a large region in southern Patagonia. We also calculated the survey effort required to detect population trends in Santa Cruz. We found considerable spatial variation in density (1.1 to 7.4 ind/km2), with a mean value of 4.8 ind/km2, which is more than twice the mean value guessed for central and northern Patagonia. Consequently, guanaco numbers in Santa Cruz were estimated at 1.1 million individuals (95% CI 0.7 to 1.6), which almost doubles current estimates of guanaco population size in South America. High guanaco abundance was found in arid lands, overgrazed and unable to support profitable sheep stocks. Detecting a 50% change in guanaco population size over a 10-year period requires substantial monitoring effort: the annual survey of between 40 and 80 30-km transects, which becomes up to 120 transects if trends are to be detected over 5 years. Regional patterns in guanaco density can only be detected through large-scale surveys. Coupling these surveys with distance sampling techniques produce robust estimates of density and its variation. Figures so obtained improve currently available estimates of guanaco population size across its geographic range, which seem to be extrapolated from strip counts over small areas. In arid lands degraded by sheep overgrazing, sustainable use of guanaco populations would help harmonize guanaco conservation, socio-economic progress of rural areas, and eventually the restoration of shrub-steppes.

The paper presents the project of an aggregative reconstruction of the population of Ger-many from the sixteenth century to 1840, when official statistics began to provide complete coverage of all German states. The creation of estimates of population size and of annual series of the crude birth, marriage and death rates rests on three types of sources: First, pairs of partial censuses of hearths, taxpayers, communicants, etc. for the same regional aggregate at two different points in time are used to derive annual growth rates of popula-tion. This information is used to derive approximate estimates of total population size in ten-year intervals. Second, to develop aggregate series of vital events the project aims to analyse approximately 450 to 600 parish registers. Third, the project makes use of proto-statistical material on population size and the number of vital events that states began to collect selectively from c. 1740. On the basis of material from Gehrmann (2000), from published studies on c. 140 parishes and from selected other sources we construct a pre-liminary dataset for the period 1730–1840. Our cumulative rates of natural increase are broadly consistent with independent estimates of population growth. We use these series for two explorative analyses: First, on the basis of inverse projection we generate tentative estimates of the gross reproduction rate, of life expectancy and the dependency ratio. The results suggest an increase of the life expectancy and of the dependency ratio, the latter being the result of persistent population growth. Second, by adding a real wage series we study Malthusian adaptation with two methods, namely, VAR and time varying cumulated lag regression. The results consistently suggest the presence of both the preventive and the positive check during the eighteenth century. Whereas the preventive check persisted into the nineteenth century, mortality became exogenous in the early nineteenth century. Par-ticularly the 1810s turn out as a period of major change in at least three dimensions: real wages increased, life expectancies rose, and the positive check disappeared. Thus, Germany became a non-Malthusian economy well before the advent of industrialisation. Additional information suggests that market integration was a driving force behind this process.

Although free‐roaming cats can have a significant impact on the environment, and substantial resources have been invested to find humane alternatives for managing free‐roaming cat populations, there are no empirical estimates of free‐roaming cat population size in medium to large cities. In addition, little is known about factors limiting free‐roaming cat population size and distribution. Using Guelph, ON, Canada (pop: 120 000; 86.7 km2) as a case‐study, we apply replicated distance transect sampling and likelihood‐based hierarchical modelling to compare human‐mediated landscape patterns of land use, distance to roads, distance to wooded areas, building density and socio‐economic status to explain the abundance of free‐roaming cats. We then derive an empirical estimate of total population size and present a spatially explicit prediction of free‐roaming cat density across an entire city. Cat abundance was highest in residential areas and lowest in commercial and institutional areas, negatively related to median household income, and positively related to distance from woods and building density. Total population size was estimated to be 7662 (95% bootstrap CI: 6145–9966) for Guelph; free‐roaming cat density varied from 0 to 49.4 cats per ha. Our estimate overlapped with an independent estimate of indoor‐outdoor cats (11 927; 95% CI: 6361–20 989) derived from random surveys of city residents, which implies our distance transect methodology was relatively robust and unbiased. Our approach used simple geographical information that is readily available for most urban areas in North America and can be applied broadly to inform cat management in urban areas. Finally, our results suggest that free‐roaming cat density in cities could be determined by bottom‐up processes (e.g. enhanced food availability in residential areas) as well as top‐down processes (e.g. enhanced susceptibility to coyote predation near wooded areas) which are typically reserved to explain wildlife populations in natural environments.

Reliable estimates of population size are important for developing and monitoring health programs in at-risk populations. Laska, Meisner, and Siegel (Biometrics 1988;44:461-72) developed an unbiased estimator for the size of a population at a single venue based on a single sample. Because many populations of interest are not contained within a single venue, this article generalizes the Laska, Meisner, and Siegel estimator to incorporate two- and three-stage sampling designs and enable estimation of total population size over multiple venues. Use of the estimator with two- and three-stage sampling designs is illustrated with examples that estimate the size of a population of individuals who socialize over a 4-week period at public venues where transmission of human immunodeficiency virus and other sexually transmitted infections is likely to occur.

Our aim was to develop a method for estimating the number of animals using a single site in an asynchronous species, meaning that not all animals are present at once so that no one count captures the entire population. This is a common problem in seasonal breeders, and in northern elephant seals, we have a model for quantifying asynchrony at the Año Nuevo colony. Here we test the model at several additional colonies having many years of observations and demonstrate how it can account for animals not present on any one day. This leads to correction factors that yield total population from any single count throughout a season. At seven colonies in California for which we had many years of counts of northern elephant seals, we found that female arrival date varied < 2 days between years within sites and by < 5 days between sites. As a result, the correction factor for any one day was consistent, and at each colony, multiplying a female count between 26 and 30 Jan by 1.15 yielded an estimate of total population size that minimized error. This provides a method for estimating the female population size at colonies not yet studied. Our method can produce population estimates with minimal expenditure of time and resources and will be applicable to many seasonal species with asynchronous breeding phenology, particularly colonial birds and other pinnipeds. In elephant seals, it will facilitate monitoring the population over its entire range.

Our aim was to develop a method for estimating the number of animals using a single site in an asynchronous species, meaning that not all animals are present at once so that no one count captures the entire population. This is a common problem in seasonal breeders, and in northern elephant seals, we have a model for quantifying asynchrony at the Año Nuevo colony. Here we test the model at several additional colonies having many years of observations and demonstrate how it can account for animals not present on any one day. This leads to correction factors that yield total population from any single count throughout a season. At seven colonies in California for which we had many years of counts of northern elephant seals, we found that female arrival date varied < 2 days between years within sites and by < 5 days between sites. As a result, the correction factor for any one day was consistent, and at each colony, multiplying a female count between 26 and 30 Jan by 1.15 yielded an estimate of total population size that minimized error. This provides a method for estimating the female population size at colonies not yet studied. Our method can produce population estimates with minimal expenditure of time and resources and will be applicable to many seasonal species with asynchronous breeding phenology, particularly colonial birds and other pinnipeds. In elephant seals, it will facilitate monitoring the population over its entire range.

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov–Malyshev–Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density. We also introduce a weighting scheme to estimate density on habitats that are not covered by survey transects, assuming that movement data on a subset of individuals is available. We test the performance of spatio-temporal and temporal approaches by a simulation study mimicking the Finnish winter track count survey. The results illustrate how the spatio-temporal modelling approach is able to borrow information from observations made on neighboring locations and times when estimating population density, and that spatio-temporal and temporal smoothing models can provide improved estimates of total population size compared to the FMP method.

Estimating demographic parameters for wide-ranging and elusive species living at low density is challenging, especially at the scale of an entire country. To produce wolf distribution and abundance estimates for the whole south-central portion of the Italian wolf population, we developed an integrated spatial model, based on the data collected during a 7-month sampling campaign in 2020-2021. Data collection comprised an extensive survey of wolf presence signs, and an intensive survey in 13 sampling areas, aimed at collecting non-invasive genetic samples (NGS). The model comprised (i) a single-season, multiple data-source, multi-event occupancy model and (ii) a spatially explicit capture-recapture model. The information about species' absence was used to inform local density estimates. We also performed a simulation-based assessment, to estimate the best conditions for optimizing sub-sampling and population modelling in the future. The integrated spatial model estimated that 74.2% of the study area in south-central Italy (95% CIs = 70.5% to 77.9%) was occupied by wolves, for a total extent of the wolf distribution of 108,534 km2 (95% CIs = 103,200 to 114,000). The estimate of total population size for the Apennine wolf population was of 2557 individuals (SD = 171.5; 95% CIs = 2127 to 2844). Simulations suggested that the integrated spatial model was associated with an average tendency to slightly underestimate population size. Also, the main contribution of the integrated approach was to increase precision in the abundance estimates, whereas it did not affect accuracy significantly. In the future, the area subject to NGS should be increased to at least 30%, while at least a similar proportion should be sampled for presence-absence data, to further improve the accuracy of population size estimates and avoid the risk of underestimation. This approach could be applied to other wide-ranging species and in other geographical areas, but specific a priori evaluations of model requirements and expected performance should be made.

SummaryThe Taita ApalisApalis fuscigularis(IUCN category: Critically Endangered) is a species endemic to south-eastern Kenya. We assessed population size and habitat use in the three forest sites in which it is known to occur (Ngangao, Chawia and Vuria, totalling 257 ha). The estimate of total population size, derived from distance sampling at 412 sample points, ranged from 310 to 654 individuals, with the northern section of Ngangao fragment having 10-fold higher densities than Chawia (2.47–4.93 versus 0.22–0.41 birds ha−1). Ngangao north alone hosted 50% of the global population of the species. The highly degraded Vuria fragment also had moderately high densities (1.63–3.72 birds ha−1) suggesting that the species tolerates some human disturbance. Taita Apalis prefers vegetation with abundant climbers, but the predictive power of habitat use models was low, suggesting that habitat structure is not a primary cause for the low density of the species in Chawia. Protecting the subpopulation in the northern section of Ngangao is a priority, as is identifying factors responsible of the low abundance in Chawia, because ameliorating conditions in this large fragment could substantially increase the population of Taita Apalis.

Southern elephant seals (Mirounga leonina) play a pivotal role in the Southern Ocean as wide-ranging marine predators and major prey consumers within Southern Ocean marine ecosystems. Due to their circumpolar distribution and the remoteness of their habitat, large uncertainties remain about their total population sizes. This is especially true for elephant seal populations in the French Southern Territories in the southern Indian Ocean (i.e. Crozet and Kerguelen Archipelagos) as many breeding sites are inaccessible for ground censuses. Here, we present a simple and efficient approach for estimating the total elephant seal populations of the Kerguelen and Crozet Archipelagos by using very high-resolution satellite imagery (&amp;lt;1m resolution). Twenty-eight satellite images taken during the breeding season to count female elephant seals in inaccessible areas were used and complemented the traditional annual ground counts in accessible areas. For Kerguelen Island sectors likely to host colonies and where no satellite images were available for the breeding season, a statistical predictive model was built to estimate the most likely number of breeding females to be present on a given beach according to its physiographic characteristics. Our results show the reliability of using very high-resolution satellite images, a relatively low-cost platform, to count pinniped populations and provide the first estimation of the total southern elephant seal population for both the Kerguelen 347,995 (s e = 4,950) and Crozet 13,065 (s e = 169) Archipelagos. The combined total represents over 35% of the global elephant seal population with the Kerguelen stock being numerically equivalent to the South Georgia stock. In addition, we re-examined the population trends since the last mid-century for Kerguelen and over the last five decades for Crozet. The demographic trends of the southern Indian Ocean populations show marked growth over the last decade (5.1% and 1.6% annual growth rate for Crozet and Kerguelen respectively), particularly on Crozet where the elephant seal population has more than tripled.

In South America, Royal Terns (Thalasseus maximus maximus) and Cayenne Terns (Thalasseus sandvicensis eurygnathus) breed mostly in Argentina and Brazil. Royal Terns have been recorded in at least 22 locations (six in Brazil and 14 in Argentina). Cayenne Terns have been recorded in at least 38 locations (15 in Brazil and 23 in Argentina). At 15 locations, mostly located in Argentina, Royal and Cayenne terns breed in association, often with their nests intermingled. Total population size for Royal Terns was estimated in at least 750 pairs in Brazil and less than 5000 in Argentina, while that of Cayenne Tern was estimated in at least 8000 pairs in Brazil and less than 10000 in Argentina. However, lack of counts at some coastal sectors and changes among breeding sites between seasons preclude an accurate estimation of total population size for both species and make spatial management challenging. Main threats faced by their populations in both countries are human disturbance, fisheries, egging, and expanding Kelp Gull (Larus dominicanus) populations. Priority research and conservation actions are presented.