Accurate Estimates Of Population Size Research Articles

Population size and residency patterns of northern bottlenose whales (Hyperoodon ampullatus) using the Gully, Nova Scotia

A population of northern bottlenose whales (Hyperoodon ampullatus) uses the Gully, a submarine canyon off the coast of Nova Scotia, Canada. Eleven years of photo-identification records has permitted estimation of population size using mark-recapture techniques. The population estimate was small (133 individuals, 95% CI = 111-166 from left side identifications; 127 individuals, 95% CI = 106-160 from right side identifications). The population was not closed, with the combined mortality, mark change and emigration rate estimated at 13% per year for left side identifications (95% CI = 9-17) and 14% for right side identifications (95% CI = 10-18). There was no significant increase or decrease in the population size between 1988-1999 (change in population size: left side: –0.13% per year, 95% CI = -3.4 to 3.9; right side: –0.43% per year, 95% CI = -4.5 to 3.1). The sex ratio was roughly 1:1, with equal numbers of sub-adult and mature males. Over the summer field season, individuals emigrated from, and re-immigrated into the Gully, spending an average of 20 days within the Gully before leaving (left side identifications 19 days, SE = 17; right side identifications 23 days, SE = 10). Approximately 34% of the population was present in the Gully at any time. Individuals of all age and sex classes displayed similar residency patterns although there were annual differences as individuals spent less time in the Gully in 1996 than in 1990 and 1997. Sighting rates were similar in all years with extensive fieldwork, indicating little variability in the number of whales in the Gully each summer. Accurate estimates of population size and residency patterns will be useful in determining the regulations and required coverage for a marine protected area in the Gully.

Evaluating tools for capture-recapture model selection to estimate the size of hidden populations: it works in practice, but does it work in theory?

Capture-recapture methods estimate the size of hidden populations by leveraging the proportion of overlap of the population on independent lists. Log-linear modeling relaxes the assumption of list independence, but best model selection criteria remain uncertain. Incorrect model selection can deliver incorrect and even implausible size estimates. We used simulations to model when capture-recapture methods deliver biased or unbiased estimates and compare model selection criteria. Simulations included five scenarios for list dependence among three incomplete lists of population of interest. We compared metrics of log-linear model selection, accuracy, and precision. We also compared log-linear model performance to the decomposable graph approach (a Bayesian model average), the sparse multiple systems estimation (SparseMSE) approach that accounts for zero or low cell counts, and the Sample Coverage approach. Log-linear models selected by Akaike's information criterion (AIC) calculated accurate population size estimates in all scenarios except for those with sparse or zero cell counts. In these scenarios, the decomposable graph and the Sample Coverage models produced more accurate size estimates. Conventional capture-recapture model selection fails with sparse cell counts. This naïve approach to model selection should be replaced with the implementation of multiple different models in order triangulate the truth in real-world applications.

Combining surface and soil environmental DNA with artificial cover objects to improve terrestrial reptile survey detection.

Reptiles are increasingly of conservation concern due to their susceptibility to habitat loss, emerging disease, and harvest in the wildlife trade. However, reptile populations are often difficult to monitor given the frequency of crypsis in their life history. This difficulty has left uncertain the conservation status of many species and the efficacy of conservation actions unknown. Environmental DNA (eDNA) surveys consistently elevate the detection rate of species they are designed to monitor, and while their use is promising for terrestrial reptile conservation, successes in developing such surveys have been sparse. We tested the degree to which inclusion of surface and soil eDNA sampling into conventional artificial-cover methods elevates the detection probability of a small, cryptic terrestrial lizard, Scincella lateralis. The eDNA sampling of cover object surfaces with paint rollers elevated per sample detection probabilities for this species 4-16 times compared with visual surveys alone. We readily detected S. lateralis eDNA under cover objects up to 2 weeks after the last visual detection, and at some cover objects where no S. lateralis were visually observed in prior months. With sufficient sampling intensity, eDNA testing of soil under cover objects produced comparable per sample detection probabilities as roller surface methods. Our results suggest that combining eDNA and cover object methods can considerably increase the detection power of reptile monitoring programs, allowing more accurate estimates of population size, detection of temporal and spatial changes in habitat use, and tracking success of restoration efforts. Further research into the deposition and decay rates of reptile eDNA under cover objects, as well as tailored protocols for different species and habitats, is needed to bring the technique into widespread use.

Assessing the efficacy of electronic quail callers in attracting stubble quail and non-target predators.

Hunting is a prominent feature of many human societies. Advancements in hunting technologies can challenge the ethics and sustainability of hunting globally. We investigated the efficacy of an electronic acoustic lure (‘quail caller’), in attracting the otherwise difficult-to hunt stubble quail Coturnix pectoralis in Victoria, Australia. Using distance sampling, the density and abundance of stubble quail was estimated at 79 sites across a range of habitat types in an agricultural setting, each with an active ‘quail caller’ station continuously broadcasting for 48 hours, and a control station (no broadcast). Quail detectability at the active stations (62.9%) far exceeded that at control stations (6.3%). Most (57%) detections occurred within 30 m of active ‘quail callers’. Stubble quail relative abundance was substantially greater when ‘quail callers’ were broadcasting. Cameras mounted near ‘quail callers’ identified the predatory red fox as a non-target predator, although rates of attraction appear similar between active and control sites. ‘Quail callers’ are highly effective at attracting stubble quail and concentrating them to a known area, raising questions in relation to sustainable hunting practices, indirect effects, and ethical implications. ‘Quail callers’ do, however, also offer a tool for estimating quail abundance and developing more accurate population size estimates.

Considerations for the Development of a Juvenile Production Estimate for Central Valley Spring-Run Chinook Salmon

Effective species management depends on accurate estimates of population size. There are, however, no estimates of annual juvenile production for Central Valley spring-run Chinook Salmon (“spring run”), a highly imperiled species in California, making it difficult to evaluate population status and effectively manage key issues such as entrainment of this species at water diversions. In recognition of this critical information gap, we initiated an effort to develop a juvenile production estimate (JPE) for spring run, defined here as an annual forecast of the number of juvenile Central Valley spring-run Chinook Salmon that enter the Sacramento–San Joaquin Delta (“Delta”) from the Sacramento Valley. This metric would allow for a more robust scientific assessment of the population, which is needed to effectively manage water to reduce effects on spring run, a key condition of state permit requirements. To help guide this effort, we organized a workshop for stake-holders, managers, and scientists to review some of the key aspects of spring-run biology, examine the management and conservation importance of a JPE, identify knowledge gaps, introduce new tools, and discuss alternative approaches to forecasting the number of spring run emigrating from the Sacramento River drainage and into the Delta. This paper summarizes the spring-run biology, monitoring, and emergent methods for assessment considered at the workshop, as well as the guiding concepts identified by workshop participants necessary to develop a JPE for spring-run Chinook Salmon.

Comparative detection, density, and reproductive performance of Kirtland's warbler in jack and red pine

AbstractThe formerly endangered Kirtland's warbler (Setophaga kirtlandii) is among a growing number of conservation‐reliant species that depend on active management to avoid reverting to endangered status. Because the Kirtland's warbler is a habitat specialist of young, even‐aged jack pine (Pinus banksiana), managers of the recovery effort stressed creating new jack pine stands and monitoring numbers of singing males through an annual census using single visits to individual stands. Kirtland's warbler will occupy and breed in red pine (P. resinosa), but red pine has not been surveyed for Kirtland's warblers in the annual population census. Furthermore, the current monitoring approach cannot determine their species detection probability or individual detection probability, which is essential to evaluate both red pine use and the accuracy of the census. From 2016–2018 we estimated density and detection probabilities in jack pine and red pine stands through repeated visits to a limited number of stands rather than single visits to many stands. Estimates of species detection probability indicated that ≥1 male Kirtland's warbler would be detected on most sites when any were present, but individual detection probabilities were less and varied by stand type, indicating that single visits to sites would underestimate numbers and that accurate estimation of detection probability was important for estimation of density in different stand types. We offer quantitative estimates of detection probabilities for determination of Kirtland's warbler population size in jack pine versus red pine stands in the same areas and breeding seasons. Managers of Kirtland's warblers should incorporate detection probabilities into population surveys to achieve more accurate estimates of population size.

Remote sensor camera traps provide the first density estimate for the largest natural population of the numbat (Myrmecobius fasciatus)

Context Accurate estimates of population size is fundamentally important for effective conservation management of threatened species. Remote sensor camera traps often capture cryptic species that are difficult to sight or capture. When animals are individually identifiable, camera traps can be used in conjunction with mark–recapture methods to provide a robust estimate of density. This has been effective for medium and large mammals such as felid and quoll species. Less is known about whether this may be an effective approach for smaller species. The numbat (Myrmecobius fasciatus), a small diurnal marsupial once widespread across southern Australia, is now highly restricted. Low densities and crypsis make them challenging to survey, and current population monitoring methods (driving transects and sign surveys) do not provide accurate density estimates. Aims This study aimed to: (1) assess whether numbats can be individually identified using camera trap images; and (2) use spatial and non-spatial capture–recapture methods to investigate whether camera trapping is a viable population monitoring tool for numbats in the largest extant population. Methods We conducted spatial and non-spatial population modelling using images captured incidentally during a large camera-trapping project. Key results We found numbats could be individually identified by stripe patterns from camera images that, in conjunction with capture–recapture modelling, could provide a density estimate. From 6950 trap nights there were 116 numbat detections on 57 of 250 cameras. Of these, 61 detections were used to identify 29 individuals and provide a density estimate of 0.017 ha−1 ± 0.004 (CV = 0.26). This density applied across the estimated extent of distribution suggests a substantially larger numbat population in the Upper Warren, Western Australia (~1900 adults) than previously assumed. Conclusions Camera trapping is a potential method for monitoring the population density of small uniquely marked species, such as the numbat, and for monitoring population trends in response to conservation efforts such as introduced predator control and translocations, as well as management actions such as prescribed burning and timber harvesting. Implications This study contributes to the understanding of situations where camera traps can be utilised to survey small, cryptic species. To provide a more reliable density estimate, and to develop an optimal sampling layout for numbats, further studies would be required.

Female sex workers population size estimation in Rwanda using a three-source capture−recapture method

Establishing accurate population size estimates (PSE) is important for prioritising and planning provision of services. Multiple source capture-recapture sampling method increases PSE accuracy and reliability. In August 2018, the three-source capture-recapture (3S-CRC) method was employed with a stringent assumption of sample independence to estimate the number of female sex workers (FSW) in Rwanda. Using Rwanda 2017 FSW hotspots mapping data, street and venue-based FSW were sampled at the sector level of each province and tagged with two unique gifts. Each capture was completed within one week to minimise FSW migration between provinces and recall bias. The three captures had 1042, 1204 and 1488 FSW. There were 111 FSW recaptured between captures 1 and 2; 237 between captures 2 and 3; 203 between captures 1 and 3 and 46 captured in all three. The PSE for street and venue-based FSW in Rwanda lies within 95% credible set: 8328-22 806 with corresponding median of 13 716 FSW. The 3S-CRC technique was low-cost and relatively easy to use for PSE in hard-to-reach populations. This estimate provides the basis for determining the denominators to assess HIV programme performance towards FSW and epidemic control and warrants further PSE for home- and cyber-based FSW in Rwanda.

Bias reduction in the population size estimation of large data sets

Estimation of the population size of large data sets and hard to reach populations can be a significant problem. For example, in the military, manpower is limited and the manual processing of large data sets can be time consuming. In addition, accessing the full population of data may be restricted by factors such as cost, time, and safety. Four new population size estimators are proposed, as extensions of existing methods, and their performances are compared in terms of bias with two existing methods in the big data literature. These would be particularly beneficial in the context of time-critical decisions or actions. The comparison is based on a simulation study and the application to five real network data sets (Twitter, LiveJournal, Pokec, Youtube, Wikipedia Talk). Whilst no single estimator (out of the four proposed) generates the most accurate estimates overall, the proposed estimators are shown to produce more accurate population size estimates for small sample sizes, but in some cases show more variability than existing estimators in the literature.

Differential habitat selection in boreal songbirds influences estimates of population size and distribution

AbstractAimMost large‐scale species distribution models assume spatially constant habitat selection throughout a species' geographic range. However, there is evidence this assumption may not be valid for a number of boreal bird species, which could lead to biased predictions of density and distribution in range‐wide models. Our goal was to test for and quantify differential habitat selection (DHS) in songbirds among regions of the Canadian boreal forest.LocationNorthern Alberta, western Ontario and southern Quebec, Canada.MethodsWe used hierarchical analysis of covariance models with region‐specific parameter estimates to test for differential selection of forest attributes among three regions for six boreal bird species. We used the results of these models to quantify intraspecific niche overlap between regions and compared posterior predictive accuracy to models that did not account for DHS.ResultsWe found a generally large standardized effect size (median effect size = 1.674) of region on selection of specific habitat variables for all six species, although there was high variability among species, variables and regional comparisons. The proportion of niche overlap between regions was generally low (mean overlap = 0.309 for all pairwise comparisons), with no spatial pattern to the overlap. Models accounting for DHS had significantly higher posterior predictive accuracy according to the Watanabe–Akaike information criterion.Main ConclusionsWe found strong evidence for DHS among regions for six boreal songbird species in individual habitat attributes and overall niche space. The higher predictive accuracy of our DHS models suggests that failure to account for spatial variability in habitat selection can lead to biased estimates of density and spatial distribution. Models that did not account for DHS overestimated density relative to DHS models. We conclude that large‐scale species distribution models should account for regional variation in habitat selection in order to obtain accurate estimates of population size and distribution.

Size, spatial and household distribution, and rabies vaccination coverage of the Brazilian owned-dog population.

Dog rabies and human rabies transmitted by dogs can be prevented through adequate dog vaccination coverage. For surveillance purposes, this coverage must be calculated using accurate population size estimates to avoid misleading conclusions. We used data from a Brazilian national survey comprising 64,348 households, to calculate point estimates and confidence intervals of the size, household density, and rabies vaccination coverage of the owned-dog population in Brazilian federative units. We also evaluated the precision of owned-dog population size estimates, based on the extrapolation among different areas, of the mean number of dogs per household and the human/dog ratio. The estimated owned-dog population size in Brazil was 52,198,324 (95% CI=51,028,583-53,368,066) and the dog vaccination coverage was 80.09% (95% CI=79.09%-81.09%). Both estimates had marked variation across Brazilian federative units and urban/rural strata. Only two of the 27 federative units had a confidence interval in rural vaccination coverage above 70% and six did not pass this threshold in their urban stratum. For the first time, we reported probabilistic estimates for an entire country and its main administrative areas. The estimated coverage for the country was high because the most populated federative unit also had high coverage. The mean number of dogs per household and the human/dog ratio were useful as survey estimates to characterize owned-dog density. However, the simple extrapolation of these parameters resulted in estimates of owned-dog population sizes with large errors (up to 254%) that must be interpreted with caution to avoid misleading conclusions. To evaluate the dog population size, we recommend the use of probabilistic sampling designs instead of simple human/dog ratio extrapolations, and the inclusion of animal-related questions in censuses and national surveys to obtain reliable estimates to support improvements in animal and human health.

Distance models as a tool for modelling detection probability and density of native bumblebees

AbstractEffective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators.

Should I stay or should I go? Movement of adult Triatoma sordida within the peridomestic area of a typical Brazilian Cerrado rural household

BackgroundChagas disease, or American trypanosomiasis, is an important neglected tropical illness caused by the flagellate protozoan Trypanosoma cruzi, which is primarily transmitted to humans by hematophagous insects of the subfamily Triatominae. Although knowledge on triatomine movement capabilities at the micro-geographical scale is of fundamental importance concerning the development of effective vector control strategies, it remains a poorly understood subject. Furthermore, survival rates and size estimates of natural populations are important topics to consider when evaluating transmission intensity.ResultsThe movement of adult Triatoma sordida within the peridomestic area of a rural Brazilian household was evaluated via mark-release-recapture assays. A total of 210 insects had their pronota marked with fluorescent dyes and were released at different distances from the chicken coop (two, five, ten and 20 m), and from the horse corral (27, 32, 35, 46 and 56 m). Recaptures occurred in three consecutive 15-day intervals. Specimens were successfully recaptured at all distances up to 32 m. Bayesian models were used to estimate recapture probability, survival rates (males vs females) and population size. Although recapture probability was inversely proportional to distance for both sexes, females were more affected by increased distance. On the other hand, no significant difference was detected in the survival rates between males and females in a 15-day period. Fisher-Ford and Bayesian models gave more accurate population size estimates than Lincoln method.ConclusionsTriatoma sordida adults were able to cover a distance of 32 m in 45 days. Recapture data modelling reveals that male dispersal was more effective suggesting that T. sordida males are more likely to contribute as potential colonizers of the peridomestic environment. Increasing the distance between the peridomestic structures and the sylvatic environment as much as possible appears to be a simple and feasible recommendation to reduce the contact rate between humans and infected bugs and ultimately Chagas disease transmission.

Integrating sign surveys and telemetry data for estimating brown bear (Ursus arctos) density in the Romanian Carpathians.

Accurate population size estimates are important information for sustainable wildlife management. The Romanian Carpathians harbor the largest brown bear (Ursus arctos) population in Europe, yet current management relies on estimates of density that lack statistical oversight and ignore uncertainty deriving from track surveys. In this study, we investigate an alternative approach to estimate brown bear density using sign surveys along transects within a novel integration of occupancy models and home range methods. We performed repeated surveys along 2‐km segments of forest roads during three distinct seasons: spring 2011, fall‐winter 2011, and spring 2012, within three game management units and a Natura 2000 site. We estimated bears abundances along transects using the number of unique tracks observed per survey occasion via N‐mixture hierarchical models, which account for imperfect detection. To obtain brown bear densities, we combined these abundances with the effective sampling area of the transects, that is, estimated as a function of the median (± bootstrapped SE) of the core home range (5.58 ± 1.08 km2) based on telemetry data from 17 bears tracked for 1‐month periods overlapping our surveys windows. Our analyses yielded average brown bear densities (and 95% confidence intervals) for the three seasons of: 11.5 (7.8–15.3), 11.3 (7.4–15.2), and 12.4 (8.6–16.3) individuals/100 km2. Across game management units, mean densities ranged between 7.5 and 14.8 individuals/100 km2. Our method incorporates multiple sources of uncertainty (e.g., effective sampling area, imperfect detection) to estimate brown bear density, but the inference fundamentally relies on unmarked individuals only. While useful as a temporary approach to monitor brown bears, we urge implementing DNA capture–recapture methods regionally to inform brown bear management and recommend increasing resources for GPS collars to improve estimates of effective sampling area.

Age structure: an indicator to monitor populations of large herbivores

Most populations of large herbivores are hunted over much of their distribution. The size of these populations over time must be monitored to detect responses to management actions and environmental changes. Here, I first review the limits in precision and accuracy of most methods used to estimate population size in wild herbivores. I then show how density-dependence of age structure can be used to monitor harvested populations, using simulated and empirical data. Accurate estimates of population size are difficult, costly in time and effort, and mostly impracticable at a large scale. Indices are widely used to monitor population size at a large scale, but are rarely tested, and assumptions of constant detection rates over years are questionable. In a recent approach, the effects of population density on habitat quality and individual performance were used as ecological indicators to infer changes in population size over time. Populations of large mammals are strongly age structured. In harvested populations, density-dependence and harvest affect age structure through changes in age-specific vital rates. Because age- and sex-specific vital rates are density-dependent, changes over time in age structure should reflect the response of population to changes in environmental conditions such as density and harvest rate. Time series of age-structure may be used as an ecological indicator to monitor harvested populations, and to infer their demographic trajectory, especially when used within a set of ecological indicators. However, attention needs to be paid in the use of ecological indicators because of the potential bias introduced in data collection by hunter selectivity.

The Importance of Survey Timing on Shorebird Density Estimates at East Bay, Nunavut, Canada

Accurate estimates of population size and trends are often necessary for wildlife conservation, but imperfect and variable rates of detection can lead to substantially biased counts during surveys. The influence of survey timing relative to timing of breeding on the counts recorded for five shorebird species during transect surveys at East Bay, Nunavut, Canada, from 2000 to 2010 was examined. Transect counts varied widely among species and years, and transect counts were most strongly predicted by the density of nests found during more intensive surveys. However, after accounting for this variation, survey counts were influenced substantially by survey timing. Surveys carried out shortly after the median date of nest initiation (∼2 days after) corresponded most closely to the densities of found nests, and if surveys were not within several days of the median date, the discrepancy between the two estimates was large. Although neither nest densities nor transect surveys are believed to be a perfect indication of local population status, these results suggest that the nearly inevitable variation in survey timing could introduce substantial bias into density estimates.

Fecal Near Infrared Spectroscopy to Discriminate Physiological Status in Giant Pandas

Giant panda (Ailuropoda melanoleuca) monitoring and research often require accurate estimates of population size and density. However, obtaining these estimates has been challenging. Innovative technologies, such as fecal near infrared reflectance spectroscopy (FNIRS), may be used to differentiate between sex, age class, and reproductive status as has been shown for several other species. The objective of this study was to determine if FNIRS could be similarly used for giant panda physiological discriminations. Based on samples from captive animals in four U.S. zoos, FNIRS calibrations correctly identified 78% of samples from adult males, 81% from adult females, 85% from adults, 89% from juveniles, 75% from pregnant and 70% from non-pregnant females. However, diet had an impact on the success of the calibrations. When diet was controlled for plant part such that “leaf only” feces were evaluated, FNIRS calibrations correctly identified 93% of samples from adult males and 95% from adult females. These data show that FNIRS has the potential to differentiate between the sex, age class, and reproductive status in the giant panda and may be applicable for surveying wild populations.

Improving the accuracy of population size estimates for burrow‐nesting seabirds

Seabird numbers can change rapidly as a result of environmental processes, both natural and anthropogenic. Informed management and conservation of seabirds requires accurate and precise monitoring of population size. However, for burrow‐nesting species this is rarely achieved due to spatial and temporal heterogeneity in burrow occupancy. Here, we describe a novel method for deriving more accurate population size estimates that employs mark‐recapture methods to correct for unknown variation in nest occupancy throughout a breeding season. We apply it to estimate breeding numbers of a colonial, burrowing seabird, the Little Penguin Eudyptula minor, on the Summerland Peninsula, Phillip Island, Australia. Estimates of active burrow numbers during the September 2008 to February 2009 breeding season were adjusted to numbers of breeding birds based on burrow occupation and modelled population demographics at six, fortnightly monitored reference sites. The population was estimated to be 26 100 (95% CI: 21 100–31 100) and 28 400 (23 800–33 000) breeding Penguins in two temporally separated surveys within one breeding season. We demonstrate using simulation that the method is robust to variation in burrow occupancy throughout the breeding season, providing consistent and more accurate estimates of population size. The advantage of using the corrected method is that confidence intervals will include the true population size. Confidence limits widened as burrow occupancy declined, reflecting the increased uncertainty as larger adjustments for low burrow occupancy were required. In contrast, the uncorrected method that uses burrow occupancy alone as a measure of breeding numbers was inconsistent and significantly underestimated population size across much of the breeding season. Although requiring considerably more survey effort, the corrected approach provides a more accurate means for monitoring population changes in colonially breeding animals while collecting demographic data that can help diagnose the drivers of population change.

Lessons from the 2006 Louisiana Health and Population Survey

The 2005 hurricane season caused extensive damage and induced a mass migration of approximately 1.1 million people from southern Louisiana in the United States. Current and accurate estimates of population size and demographics and an assessment of the critical needs for public services were required to guide recovery efforts. Since forecasts using pre-hurricane data may produce inaccurate estimates of the post-hurricane population, a household survey in 18 hurricane-affected parishes was conducted to provide timely and credible information on the size of these populations, their demographics and their condition. This paper describes the methods used, the challenges encountered, and the key factors for successful implementation. This post-disaster survey was unique because it identified the needs of the people in the affected parishes and quantified the number of people with these needs. Consequently, this survey established new population and health indicator baselines that otherwise would have not been available to guide the relief and recovery efforts in southern Louisiana.

Functional habitat area as a reliable proxy for population size: case study using two butterfly species of conservation concern

Accurate estimates of population size are essential for effective conservation and restoration management of threatened species. Nevertheless, reliable methods to estimate population size, such as mark-release-recapture studies (MRR), are time and labour consuming and may generate negative impact(s) on both the habitats and organisms studied. This may complicate their use if several sites need to be studied concurrently. Consequently, there is a strong interest to develop reliable proxies of population size, e.g., to be used in Population Viability Analysis. Habitat area has often been used as an obvious proxy. For butterflies, many studies focused on the area of host plant patches, but resource-based definition of the habitat (i.e., the area containing the different ecological resources and conditions needed by the individuals) has recently gained much attention. Using two peat bog butterflies, we tested the reliability of these two measures of habitat area as proxies for population size by (1) predicting population sizes based on the product of larval habitat area by the number of emerged butterflies per spatial unit of habitat (eliminated by ground cover traps) and (2) comparing these predictions to accurate population size estimates inferred from MRR studies. Results on both species showed that: (1) adult population size was strongly related to larval habitat availability and quality when habitat was accurately defined according to functional resources, (2) resources other than the host plant have to be included in the habitat definition, (3) after careful control of its similarity, the resource-based habitat delineation can be reasonably well transferred among populations of the same species in a wider region.