Estimates Of Population Size Research Articles

Plants stand still but hide: Imperfect and heterogeneous detection is the rule when counting plants

Abstract The estimation of population size and its variation across space and time largely relies on counts of individuals, generally carried out within spatial units such as quadrats or sites. Missing individuals during counting (i.e. imperfect detection) results in biased estimates of population size and trends. Imperfect detection has been shown to be the rule in animal studies, and most studies now correct for this bias by estimating detection probability. Yet this correction remains exceptional in plant studies, suggesting that most plant ecologists implicitly assume that all individuals are always detected. To assess if this assumption is valid, we conducted a field experiment to estimate individual detection probability in plant counts conducted in 1 × 1 m quadrats. We selected 30 herbaceous plant species along a gradient of conspicuousness at 24 sites along a gradient of habitat closure, and asked groups of observers to count individuals in 10 quadrats using three counting methods requiring progressively increasing times to complete (quick count, unlimited count and cell count). In total, 158 participants took part in the experiment, allowing an analysis of the results of 5024 counts. Over all field sessions, no observer succeeded in detecting all the individuals in the 10 quadrats. The mean detection rate was 0.44 (ranging from 0.11 to 0.82) for the quick count, 0.59 for the unlimited count (range 0.18–0.87) and 0.74 for the cell count (range 0.46–0.94). Detection probability increased with the conspicuousness of the target species and decreased with the density of individuals and habitat closure. The observer's experience in botany had little effect on detection probability, whereas detection was strongly affected by the time observers spent counting. Yet although the more time‐consuming methods increased detection probability, none achieved perfect detection, nor did they reduce the effect on detection probability of the variables we measured. Synthesis. Our results show that detection is imperfect and highly heterogeneous when counting plants. To avoid biased estimates when assessing the size, temporal or spatial trends of plant populations, plant ecologists should use methods that estimate the detection probability of individuals rather than relying on raw counts.

Estimates of Effective Population Size in Subdivided Populations

Estimates of Effective Population Size in Subdivided Populations

Drought Influences Annual Survival of Painted Turtles in Western Nebraska

Aquatic habitats in the Great Plains of North America have increased risk of droughts under climate forecasts. Droughts have the potential to influence the population dynamics of pond turtles, and long-term studies are useful to assess the impact of climatic variation on turtles. We compiled twelve years of mark-recapture data for painted turtles (Chrysemys picta) captured in a pond in Keith County, Nebraska during 2005–2016 that included two periods of drought. We used a robust design analysis to investigate influences on population size, annual survival, temporary immigration, and capture probability. Estimates of the annual population size ranged from 92 (CI: 90–94) to 180 (CI: 175–186) but did not vary with drought conditions. Despite a relatively stable depth of water in our study pond, the probability of annual survival was reduced by 0.07 in females and 0.10 in males during drought years. Approximately one-fifth (temporary emigration probability: 0.19, CI = 0.16–0.23) of the population was outside the study pond at any given time. Our long-term research provides insights into the potential challenges to turtles in aquatic habitats undergoing prolonged changes in long-term climate conditions.

Characteristics of the Stone Crayfish Population along a Disturbance Gradient—A Case Study of the Kustošak Stream, Croatia

The stone crayfish, Austropotamobius torrentium, is a native European freshwater species sensitive to habitat alterations such as stream channelization and urban development, putting its populations at risk. This study aims to assess how habitat alteration and subsequent water quality changes affect the stone crayfish population in the Kustošak Stream (Croatia) through three selected sites under different levels of anthropogenic disturbance: (1) undisturbed; (2) recently modified, and (3) long-time modified sites. At each site, crayfish were captured, measured, and marked to estimate population size, structure, and crayfish condition. Additionally, we examined whether water quality (18 measured physicochemical parameters) affects relative crayfish abundance. We also used mitochondrial sequencing and microsatellite genotyping to assess species genetic diversity and population connectivity and to compare results among the sites. The results showed that habitat alteration caused an overall reduction in population abundance and changes in size structure; however, it had not yet resulted in detectable genetic differences. Partial least squares regression showed that crayfish abundance was affected by the physicochemical parameters of water, including, among others, oxygen, calcium ions, nitrates, pH, and water temperature. We discuss our findings in the context of the effects of anthropogenic disturbance on the viability and persistence of this EU priority species.

The Influence of Migration Patterns on Regional Demographic Development in Germany

Political decision-making related to future challenges, for example in the fields of medical care, the housing market or education highly depend on valid estimates of the future population size and structure. However, such developments are usually heterogeneous throughout a country making subnational projections necessary. It is well-known that these regional differences are highly influenced by both internal and external migration processes. In this paper, we investigate the consequences of different migration assumptions on regional development in Germany using a spatial dynamic microsimulation. We find that migration assumptions have a strong direct influence on the future population and composition at the regional level and, therefore, require special attention. Depending on the scenario selected, very different socio-demographic trends may emerge in specific districts or even district types. We also demonstrate that migration assumptions affect non-demographic indicators such as the participation rate, albeit to a lesser extent. The findings are relevant to understanding the sensitivity of population projections to migration assumptions both on the national and regional level. This also paves the way to analyze how potential political interventions behave under those assumed future migration processes.

A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton.

Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT techniques in detecting, classifying, and counting cotton insect pests and corresponding beneficial insects. The effectiveness and limitations of AI and IoT techniques in various cotton agricultural settings were comprehensively reviewed. This review indicates that insects can be detected with an accuracy of between 70 and 98% using camera/microphone sensors and enhanced deep learning algorithms. However, despite the numerous pests and beneficial insects, only a few species were targeted for detection and classification by AI and IoT systems. Not surprisingly, due to the challenges of identifying immature and predatory insects, few studies have designed systems to detect and characterize them. The location of the insects, sufficient data size, concentrated insects on the image, and similarity in species appearance are major obstacles when implementing AI. Similarly, IoT is constrained by a lack of effective field distance between sensors when targeting insects according to their estimated population size. Based on this study, the number of pest species monitored by AI and IoT technologies should be increased while improving the system's detection accuracy.

Landscape genomics reveals signals of climate adaptation and a cryptic lineage in Arthropodium fimbriatum

Habitat loss and fragmentation are critical threats to biodiversity. Consequent decreases in population size and connectivity can impact genetic diversity and, thus, future adaptability and resilience to environmental change. Understanding landscape patterns of genetic diversity, including patterns of adaptive variation, can assist in developing conservation strategies that maximise population persistence and adaptability in the face of environmental change. Using a reduced-representation genomic approach, we investigated genetic diversity, structure, and adaptive variation across an aridity gradient in the woodland forb Arthropodium fimbriatum. Moderate levels of genetic diversity (HS = 0.14–0.23) were found in all 13 sampled provenances. Inbreeding varied among provenances (FIS = 0.08–0.42) but was not associated with estimated population size. Four genetic clusters were identified, including one highly differentiated cluster. Higher pairwise FST (0.23–0.42) between the three provenances of this cluster and the remaining 10 provenances (pairwise FST between 10 provenances 0.02–0.32) suggested two highly divergent lineages or potentially a cryptic species. After excluding the three highly differentiated populations, outlier and genotype-environment association analysis identified 275 putatively adaptive loci suggesting genomic signatures of climate adaptation in A. fimbriatum is primarily associated with changes in aridity. Combined, these results suggest that all provenances have conservation value, contributing to the maintenance of genetic diversity and adaptive variation in this species. The uncovering of a potential cryptic taxon highlights the power of genomics approaches in conservation genetics and the importance of understanding the role of landscape variation shaping genetic variation to effectively define conservation management units in an era of rapid biodiversity decline.

A simulation-based evaluation of methods for estimating census population size of terrestrial game species from genetically-identified parent-offspring pairs.

Estimates of wildlife population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Several methods have recently been developed that estimate abundance using kinship relationships observed in genetic samples, particularly parent-offspring pairs. While these methods are similar to traditional Capture-Mark-Recapture, they do not need physical recapture, as individuals are considered recaptured if a sample contains one or more close relatives. This makes methods based on genetically-identified parent-offspring pairs particularly interesting for species for which releasing marked animals back into the population is not desirable or not possible (e.g., harvested fish or game species). However, while these methods have successfully been applied in commercially important fish species, in the absence of life-history data, they are making several assumptions unlikely to be met for harvested terrestrial species. They assume that a sample contains only one generation of parents and one generation of juveniles of the year, while more than two generations can coexist in the hunting bags of long-lived species, or that the sampling probability is the same for each individual, an assumption that is violated when fecundity and/or survival depend on sex or other individual traits. In order to assess the usefulness of kin-based methods to estimate population sizes of terrestrial game species, we simulated population pedigrees of two different species with contrasting demographic strategies (wild boar and red deer), applied four different methods and compared the accuracy and precision of their estimates. We also performed a sensitivity analysis, simulating population pedigrees with varying fecundity characteristics and various levels of harvesting to identify optimal conditions of applicability of each method. We showed that all these methods reached the required levels of accuracy and precision to be effective in wildlife management under simulated circumstances (i.e., for species within a given range of fecundity and for a given range of sampling intensity), while being robust to fecundity variation. Despite the potential usefulness of the methods for terrestrial game species, care is needed as several biases linked to hunting practices still need to be investigated (e.g., when hunting bags are biased toward a particular group of individuals).

Error in demographic ratios from aerial surveys of white‐tailed deer in semi‐arid rangelands

AbstractAerial surveys can efficiently monitor populations of large animals in geographically extensive management units but are time‐ and cost‐intensive. Biologists often design population surveys to balance cost, spatial coverage, and precision in estimates of population size. Demographic ratio data from aerial surveys are an important component of population monitoring and management, yet the error of ratio data remains under‐appreciated, especially for low‐density populations. We quantified error in juvenile:female, male:female, and young:mature male ratios from 177 helicopter surveys of white‐tailed deer (Odocoileus virginianus) in 37 wildlife management units encompassing 3,269 km2 of semi‐arid grasslands and brush in South Texas, USA, during 2011–2015. We classified error (the % difference between the mean and the limits of the confidence interval) of surveys as appropriate for research‐based (≤25% error) or monitoring surveys (≤50% error). Overall, error usually met criteria for monitoring surveys but not for research‐based surveys; male:female (x̄ = 32% error) and juvenile:female (x̄ = 37%) ratios had smaller errors than young:mature male ratios (x̄ = 51%). As number of detections increased, errors declined; minimum number of detections for both components of a given ratio needed for monitoring and research‐based surveys was about 30–40 and 150–185 at the 90% confidence interval and 45–60 and 210–230 at the 95% confidence interval, respectively. Acceptable error to reliably detect changes in demographic ratios may require greater survey effort or a different survey design for low‐density populations. Furthermore, obtaining sufficient detections for acceptable error of male age structure estimates may not be feasible. Error of demographic ratios is an important consideration given their role in the design of harvest plans, evaluation of the effects of management, and tracking the effect of diseases, such as chronic wasting disease. The high effort required to obtain acceptable error with ratio data in areas with low deer densities indicates that helicopter surveys may not be an ideal platform to investigate fine‐scale variation in demographic data. Managers will have to consider trade‐offs between expenses and variance of ratio data collected from aerial surveys and whether obtaining acceptable error with ratio data is feasible given deer densities and detection probabilities are site‐specific.

Prevalence, Trend, and Risk Factors for Early Chronic Obstructive Pulmonary Disease: An Analysis of the Nationwide Population-Based Survey from 2010 to 2019 in South Korea

This study aimed to evaluate the prevalence, trends, and risk factors of early chronic obstructive pulmonary disease (COPD) by using a nationally representative sample. The datasets of the Korea National Health and Nutrition Examination Survey 2010–2019 were used, where 80,860 individuals were identified; of these, 9,045 participants aged 40–49 years who underwent spirometry with no missing data were analyzed. Early COPD was defined as forced expiratory volume in 1 s /forced vital capacity ratio < the lower limit of normal (2.5th percentile) in individuals aged <50 years without a history of asthma, inhaler therapy, or persistent respiratory symptoms. The prevalence and trend of early COPD were estimated according to features such as smoking status and pack-years. Joinpoint regression analysis was used to analyze the significant annual change in the trend according to sex, smoking status, and pack-years. A complex sample multivariable-adjusted regression model was used to identify factors affecting early COPD. The estimated population size during 2010–2019 was 82,326,178. Early COPD was present in 4.5% of patients (6.5% of men and 2.3% of women). It was present in 7.7% of current smokers, followed by former and never smokers. Among smokers with ≥ 10 pack-years, early COPD was present in 8.2%, whereas it was present in 2.6% of smokers with < 10 pack-years. Joinpoint regression analyses found a recent decrease in the trend of prevalence in males who were former and current smokers. The multivariable-adjusted logistic regression model showed that being male, lower educational level, smoking status, and pack-years were factors that affected the presence of early COPD. Continued surveillance of this pre-disease condition is required, and further research are warrant.

Development of a new SNP panel for bowhead whales (Balaena mysticetus)

Population genetic research is a critical tool for the conservation and management of marine mammals and other species. The bowhead whale (Balaena mysticetus) is subject to aboriginal subsistence hunting in Alaska, Canada, Chukotka, and Greenland and managed by the International Whaling Commission for all those countries except Canada. Genetic studies support conservation management plans and the determination of safe hunting quotas by providing information on levels of genetic diversity, estimates of abundance and effective population size, and stock separation. Because bowhead populations are monitored in several countries, including genetic monitoring, there is a need for methods that can be consistently used in multiple labs that provide comparable data that can be publicly shared and built upon by successive studies. Here we present a new panel of single nucleotide polymorphisms (SNPs), derived from multiple bowhead populations, that meet those criteria. We describe the use of the Fluidigm SNPtype assay for analyzing 69 autosomal, 6 X-chromosome, and 1 Y-chromosome SNPs. Results indicate that the methods herein are reliable and have low error rates. Because SNPs are discrete sequence-based genetic markers, the panel of loci described here can be replicated, used in different labs, and are directly comparable, making SNPs more useful than existing microsatellite markers.

Comparing minimum number of individuals and abundance from non-invasive DNA sampling and camera trapping in the red fox (Vulpes vulpes)

Applying the most appropriate sampling method is essential for estimating population size. Sampling methods and techniques to estimate abundance may be limited by environmental characteristics, species traits, specific requirements of the techniques, or the economic resources to carry out the sampling. Thus, evaluating multiple sampling methods in monitoring populations is essential for establishing effective conservation strategies. In this study, we compare two of the most commonly used sampling methods with the red fox (Vulpes vulpes) as the type species. On the one hand, we compared the minimum number of individuals (NI) detected by camera trapping, identifying individuals by morphological characteristics with the minimum number of individuals detected by DNA faeces and a set of 16 microsatellites. On the other hand, we estimated abundance by performing an N-mixture model using information from camera-traps to study the relationship between abundance and the minimum number of individuals detected. Results showed that the minimum NI provided by camera trapping was slightly higher than that of DNA faecal genotyping, with 23.66 and 19 individuals, respectively. In addition, abundance and NI detected by camera trapping showed a positive relationship. In contrast, there was a non-significant negative relationship between NI detected by faecal DNA and abundance estimates. Our results suggest using the minimum number of photo-identified individuals as a reliable index to study variation in red fox abundance when other advanced methods cannot be implemented in the study of population size. However, it is necessary to improve the methods of faecal sampling to study the relationship with camera-trap data.

Statistical framework for fully register based population counts.

The increasing availability of registers or administrative archives has been a strong push towards moving from traditional censuses to combined censuses or even completely register based censuses. In this context, a statistical framework needs to be designed in order to delineate all the statistical issues of the new estimation process. To this aim, a population frame needs to be defined for both surveying and estimation phases. Sampling surveys should be designed for quality assessment and for improving the quality of the register based estimation process. Drawing on similar experiences, a formalisation of the population size estimation process fully based on administrative data is presented. An application to Italian estimation process is reported.

Genetic variability and &lt;i&gt;ex situ&lt;/i&gt; conservation strategies for the neotropical tree &lt;i&gt;Parkia platycephala&lt;/i&gt; Benth.

Parkia platycephala, known commonly as faveira, is a native species that occurs widely throughout Brazil and has high nutritional value and ecological potential. The objective of this study was to estimate the genetic variability in a P. platycephala provenance and progeny test. The test was established using a randomized block design, with 45 progenies from three provenances. The evaluated quantitative traits included height (HEI), diameter at ground level (DGL), and diameter below the first bifurcation (DFB). The data were submitted to Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP) analysis, from which estimates of genetic parameters, genetic correlations, BLUPs, genetic gains, and effective population size were obtained. Estimates of individual narrow sense heritability (h2a) and within progeny heritability (h2w) ranged from low to moderate (0.01 a 0.39), with the highest values observed for DGL (0.32 and 0.39, respectively). The coefficient of individual variation (CVgi(%)) and between progeny genetic variation (CVgp(%)) indicate the existence of genetic variability between and within provenances. The FST vaues demonstrate low to moderate genetic differentiation among the three populations, and genetic correlations between traits were all positive and significant. The results obtained show that there is genetic variability between the studied provenances and progenies. This ensures not only the ex situ conservation of the species, but it can also be exploited in breeding programs.

Comparing estimates of census and effective population size in an endangered amphibian

AbstractThe field of conservation has seen a shift in focus from monitoring trends in census population size to trends in ‘effective’ population size. Numerous genetic methods exist for estimating effective population size, resulting in uncertainty among conservation practitioners as to which methods are most appropriate when conducting population assessments or evaluating recovery efforts. Demographic approaches offer a promising avenue to provide a link between census and effective population size using life‐history information, but rarely do studies have all three sources of data (genetic, demographic, life history) necessary to perform an explicit evaluation of their performance. Using data from a long‐term study of reticulated flatwoods salamanders (Ambystoma bishopi) in western Florida, USA, we assessed the magnitude of temporal variation in census population sizes and the effective number of breeders of two breeding populations to (1) document changes in the number of breeding adults over the 9‐year study duration, (2) determine whether and provide similar information about population size and trends and (3) compare alternative demographic and genetic approaches for estimating . We found that genetic estimates of , particularly if averaged across multiple estimation methods, closely tracked spatiotemporal variation in . Demographic estimates of also closely tracked but were sensitive to the assumed variance in reproductive success. In the absence of genetic information, detailed knowledge of mating systems and the environmental factors that skew reproductive contributions appear necessary for demographic to reliably inform management decisions. In these populations, appears too small (&lt;40 individuals) to confer long‐term genetic resilience, highlighting the importance of restoring landscape connectivity and indicating that caution must be taken when sourcing animals for reintroduction efforts. More generally, our study reveals insights into the utility of alternative estimation methods in guiding recovery efforts of threatened and endangered species.

Population Size Estimation of Men Who Have Sex With Men in Rwanda: Three-Source Capture-Recapture Method.

Globally, men who have sex with men (MSM) continue to bear a disproportionately high burden of HIV infection. Rwanda experiences a mixed HIV epidemic, which is generalized in the adult population, with aspects of a concentrated epidemic among certain key populations at higher risk of HIV infection, including MSM. Limited data exist to estimate the population size of MSM at a national scale; hence, an important piece is missing in determining the denominators to use in estimates for policy makers, program managers, and planners to effectively monitor HIV epidemic control. The aims of this study were to provide the first national population size estimate (PSE) and geographic distribution of MSM in Rwanda. Between October and December 2021, a three-source capture-recapture method was used to estimate the MSM population size in Rwanda. Unique objects were distributed to MSM through their networks (first capture), who were then tagged according to MSM-friendly service provision (second capture), and a respondent-driven sampling survey was used as the third capture. Capture histories were aggregated in a 2k-1 contingency table, where k indicates the number of capture occasions and "1" and "0" indicate captured and not captured, respectively. Statistical analysis was performed in R (version 4.0.5) and the Bayesian nonparametric latent-class capture-recapture package was used to produce the final PSE with 95% credibility sets (CS). We sampled 2465, 1314, and 2211 MSM in capture one, two, and three, respectively. There were 721 recaptures between captures one and two, 415 recaptures between captures two and three, and 422 recaptures between captures one and three. There were 210 MSM captured in all three captures. The total estimated population size of MSM above 18 years old in Rwanda was 18,100 (95% CS 11,300-29,700), corresponding to 0.70% (95% CI 0.4%-1.1%) of total adult males. Most MSM reside in the city of Kigali (7842, 95% CS 4587-13,153), followed by the Western province (2469, 95% CS 1994-3518), Northern province (2375, 95% CS 842-4239), Eastern province (2287, 95% CS 1927-3014), and Southern province (2109, 95% CS 1681-3418). Our study provides, for the first time, a PSE of MSM aged 18 years or older in Rwanda. MSM are concentrated in the city of Kigali and are almost evenly distributed across the other 4 provinces. The national proportion estimate bounds of MSM out of the total adult males includes the World Health Organization's minimum recommended proportion (at least 1.0%) based on 2012 census population projections for 2021. These results will inform denominators to be used for estimating service coverage and fill existing information gaps to enable policy makers and planners to monitor the HIV epidemic among MSM nationally. There is an opportunity for conducting small-area MSM PSEs for subnational-level HIV treatment and prevention interventions.

The Genetic Composition of Wild Steelhead Based on Spatial Proximity to a Hatchery

AbstractManagement of hatchery and wild stocks of steelhead Oncorhynchus mykiss within the same watershed requires careful consideration when management objectives include the use of the hatchery stock to meet fishery objectives while maintaining the genetic integrity of coexisting wild stocks. This scenario can be further complicated when management objectives for the hatchery stock include supplementation of natural production. The lower Clearwater River in Idaho provided an ideal location to evaluate hatchery steelhead genetic influence within a drainage with separate wild steelhead and supplementation management emphasis areas. We collected 813 genetic samples from wild juvenile steelhead from two sample years in 10 tributaries to the lower Clearwater River to explore genetic structure and assess hatchery influence. Overall, levels of genetic diversity of wild groups were comparable with those observed elsewhere in the Snake River basin. Estimates of effective population size of sample tributaries ranged from 22 to 198 spawners, with a median of 84. All but two tributaries had &gt;50 spawners, and evidence of natural gene flow from other stocks was observed. Results of the study display three zones of hatchery influence in the lower Clearwater River: (1) no influence in lower tributaries with wild steelhead emphasis, (2) moderate influence in wild steelhead tributaries in close proximity to the hatchery facility, and (3) significant influence in hatchery‐supplementation tributaries. Interestingly, a number of wild steelhead reporting groups from elsewhere in the Snake River basin were observed in the assignments of study fish, suggesting movement of wild steelhead among larger drainage areas. Techniques outlined in this study can be used to monitor future hatchery influence in the Clearwater River drainage, track historic versus contemporary genetic influence in the drainage, and apply to other watersheds with hatchery and wild steelhead management objectives.

BatCount: A software program to count moving animals.

One of the biggest challenges with species conservation is collecting accurate and efficient information on population sizes, especially from species that are difficult to count. Bats worldwide are declining due to disease, habitat destruction, and climate change, and many species lack reliable population information to guide management decisions. Current approaches for estimating population sizes of bats in densely occupied colonies are time-intensive, may negatively impact the population due to disturbance, and/or have low accuracy. Research-based video tracking options are rarely used by conservation or management agencies for animal counting due to the perceived training and elevated operating costs. In this paper, we present BatCount, a free software program created in direct consultation with end-users designed to automatically count bats emerging from cave roosts (historical populations 20,000-250,000) with a streamlined and user-friendly interface. We report on the software package and provide performance metrics for different recording habitat conditions. Our analysis demonstrates that BatCount is an efficient and reliable option for counting bats in flight, with performance hundreds of times faster than manual counting, and has important implications for range- and species-wide population monitoring. Furthermore, this software can be extended to count any organisms moving across a camera including birds, mammals, fish or insects.

Fish condition as an indicator of stock status: Insights from condition index in a food‐limiting environment

AbstractIndividual performance defines population dynamics. Condition index – a ratio of weight and some function of length – has been louded as an indicator of individual performance and recommended as a tool in fisheries management and conservation. However, insufficient understanding of the correlation between individual‐level processes and population‐level responses hinders its adoption. To this end, we use composite modelling to link individual's condition, expressed through the condition index, to population‐level status. We start by modelling ontogeny of European pilchard (Sardina pilchardus, Clupeidae) as a function of food and constant temperature using Dynamic Energy Budget theory. We then provide a framework to simultaneously track the individual‐ and population‐level statistics by incorporating the dynamic energy budget model into an individual‐based model. Lastly, we explore the effects of fishing pressure on the statistics in two constant and food‐limited environmental carrying capacity scenarios. Results show that, regardless of the species' environmental carrying capacity, individual condition index will increase with fishing mortality, that is, with reduction of stock size. Same patterns are observed for gilthead seabream (Sparus aurata, Sparidae), a significantly different species. Condition index can, therefore, in food‐limited populations, be used to (i) estimate population size relative to carrying capacity and (ii) distinguish overfished from underfished populations. Our findings promote a practical way to operationally incorporate the condition index into fisheries management and marine conservation, thus providing additional use for the commonly collected biometric data. Some real‐world applications, however, may require additional research to account for other variables such as fluctuating environmental conditions and individual variability.

Abundance of humpback whales on the Abrolhos Bank wintering ground, Brazil

Abundance estimates are presented for the humpback whales wintering off Brazil which ‘visit’ a surveyed area off Abrolhos Bank and display fluke-exposing behaviour. The study is based on photo-identification data collected between 1996 and 2000. Chapman-corrected Petersen estimates for all pairs of data result in estimates from 1,948 individuals up to 3,001 with coefficients of variation around 0.25. A more elaborate closed population multiple-recapture maximum-likelihood estimate is 2,393 with 95% profile-likelihood confidence interval (CI=1,924, 3,060). Replacing the closed-population assumption with a population allowed to grow (or decrease) according to some constant rate over the study period, the maximum-likelihood estimate of population size for the year 2000 becomes 3,871 (CI=2,795, 5,542) associated to an estimated annual growth rate of 31% over the study period and in the surveyed area. Although the inclusion of the growth rate results in a less restrictive assumption about population size, it is unclear at this time how to interpret it since the population around the Abrolhos Bank is some (unknown) fraction of whales wintering off Brazil. Alternatively, a fit of Whitehead’s model allowing for emigration and re-immigration gives an estimate of about 3,000 whales (CI=2,500, 3,650).